Article

Energy Efficiency in Massive MIMO-Based 5G Networks: Opportunities and Challenges

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Abstract

As we make progress towards the era of fifth generation (5G) communication networks, energy efficiency (EE) becomes an important design criterion because it guarantees sustainable evolution. In this regard, the massive multiple-input multiple-output (MIMO) technology, where the base stations (BSs) are equipped with a large number of antennas so as to achieve multiple orders of spectral and energy efficiency gains, will be a key technology enabler for 5G. In this article, we present a comprehensive discussion on state-of-the-art techniques which further enhance the EE gains offered by massive MIMO (MM). We begin with an overview of MM systems and discuss how realistic power consumption models can be developed for these systems. Thereby, we discuss and identify few shortcomings of some of the most prominent EE-maximization techniques present in the current literature. Then, we discuss "hybrid MM systems" operating in a 5G architecture, where MM operates in conjunction with other potential technology enablers, such as millimetre wave, heterogenous networks, and energy harvesting networks. Multiple opportunities and challenges arise in such a 5G architecture because these technologies benefit mutually from each other and their coexistence introduces several new constraints on the design of energy-efficient systems. Despite clear evidence that hybrid MM systems can achieve significantly higher EE gains than conventional MM systems, several open research problems continue to roadblock system designers from fully harnessing the EE gains offered by hybrid MM systems. Our discussions lead to the conclusion that hybrid MM systems offer a sustainable evolution towards 5G networks and are therefore an important research topic for future work.

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... However, the performance benefits of massive MIMO come from using more hardware, e.g., multiple radio frequency (RF) chains per base station. Therefore, the study and optimization of the total cost and energy efficiency of massive MIMO systems has been an active research area over the last decade [2]. ...
... where h u ∈ C B is the channel vector, x is the precoded signal as in (1), and f (x) = [ f 1 (x 1 ), . . . , f B (x B )] T denotes the output of the PAs as described in (2). Furthermore, w u ∼ CN (0, N 0 ) is the additive white Gaussian noise (AWGN). ...
... The base station is equipped with B transmit antennas serving U UEs via spatial multiplexing. Each transmit antenna is equipped with a PA whose nonlinearity characteristics and power consumption are modeled as(2) and(20), respectively. ...
Article
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A significant portion of the operating power of a base station is consumed by power amplifiers (PAs). Much of this power is dissipated in the form of heat, as the overall efficiency of currently deployed PAs is typically very low. This is because the structure of conventional precoding techniques typically results in a relatively high variation in output power at different antennas in the array, and many PAs are operated well below saturation to avoid distortion of the transmitted signals. In this work, we use a realistic model for power consumption in PAs and study the impact of power variation across antennas in the array on the energy efficiency of a massive MIMO downlink system. We introduce a family of linear precoding matrices that allow us to control the spatial peak-to-average power ratio by projecting a fraction of the transmitted power onto the null space of the channel. These precoding matrices preserve the structure of conventional precoders; e.g., they suppress multiuser interference when used together with zeroforcing precoding and bring advantages over these precoders by operating PAs in a more power-efficient region and reducing the total radiated distortion. Our numerical results show that by controlling the power variations between antennas in the array and incorporating the nonlinearity properties of PA into the precoder optimization, significant gains in energy efficiency can be achieved over conventional precoding techniques.
... The FBMC with the MIMO channels over the frequency based on the channels and for the selective channels. The FBMC multi-carrier system compares with the Universal Multi Carrier signal Modulation System, OFDM system [11]. Here the Table 1 compares the different parameters Out of band, Orthogonal, PAPR, Latency and spectral efficiency of the OFDM, UFMC and FBMC system. ...
... Only a selection of the (active) subcarriers are used as pilot tones in model proposed by Wang and Tian [9], with the rest holding information symbols. The subchannel reply estimates are computed using an iterative (EM-based) algorithm, similar to joint estimation/detection. Based on frequency sampling, subchannel measurements were also calculated by Prasad et al. [11]. Wang et al. [12] was the first to calculate the channel impulse response (CIR). ...
... The signal part can be further simplified as: From the Eq. (11). ...
Article
Filter Bank Multicarrier (FBMC) frameworks are a subclass of multicarrier (MC) frameworks. The essential guideline, separating spectrum into many thin sub channels, may not be new, MC frameworks have seen wide appropriation. These days, multicarrier regulation frameworks dependent on the discrete Fourier transforms are usually used to transmit over recurrence particular channels subject to forceful noise aggravations. In any case, these handsets experience the ill effects of poor sub channel spectral control, that is, the measure of inter channel impedance isn't unimportant. It very well may be indicated that the framework execution reduces when it is dependent upon an unsettling influence with a large portion of its energy focused on a narrow frequency band. This Paper aims that identify the Filter Bank Multi Carrier (FBMC) performance. The MIMO system combined with the FBMC then identifies the over Frequency Selective Channel (FSC). Here the analysis for FSC, Flat fading model FBMC and system with MMSE equalization. The Prototype filters are analyzing the system performance characteristics. The Power Spectral Density (PSD) of the MIMO FBMC system for the given spectrum. The proposed systems are best to compare all existing technique and we measure the spectral efficiency of the system.
... Throughout reality, wireless networking is not only constrained to cellular networks, multiple types of new devices would be expected to participate in vast wireless communications to incorporate the Internet of Everything (IoE) principles in the immediate future. The information and communication technology (ICT) industry has made fast strides towards cellular networks of the fifth generation (5G), which are supposed to integrate virtually all into the internet across the globe [3]. In the design of the cellular infrastructure, the key goal is to be able to expand the channel bandwidth. ...
... In the design of the cellular infrastructure, the key goal is to be able to expand the channel bandwidth. For instance, multiple access is an useful approach for next generations to accommodate as many calls as feasible at a given bandwidth with a fair extent of service quality [3]. Nonorthogonal multiple access (NOMA) is perceived to be an innovative multiple access system for cellular networks of the fifth generation (5G) and beyond 5G (B5G) that can substantially potentially increase device propagation performance [4]. ...
... Where, P 1 (e) is the Bit error rate given in (3). For the case of U ser, i ≥ 2, attainable rate will be ...
Preprint
The ever-growing number of users has brought about the challenge to identify a convenient technique for multiple access in next generation wireless communications. It has been seen that non-orthogonal multiple access (NOMA) technique provides far better performance than orthogonal multiple access (OMA) technique while taking advantage of the available resources. Interference can be minimized adequately through the use of Successive Interference Cancellation (SIC) when implemented extensively. But massive implementation increases the complexity of the system and as a result energy efficiency is reduced. To counteract the disadvantages of NOMA technique, interest in hybrid NOMA techniques has grown. Many recent papers have suggested hybrid NOMA schemes as a viable option to mitigate the disadvantages of NOMA. This paper performs an analysis of the performance between hybrid NOMA techniques which are hybrid NOMA-OMA,NOMA Space shift keying (NOMA-SSK) and Successive user relaying cooperative NOMA (SR-NOMA). A comparison of all these techniques is conducted to identify the best hybrid NOMA technique for 5G and beyond wireless communication. The expressions for sum rate and outage probability have been derived for all the techniques. Through analysis and simulation results depicted that NOMA-SSK provides the best performance in terms of sum rate and outage probability among the discussed schemes.
... BSs are equipped with a number of antennas to achieve multiple orders of spectral and energy efficiency gains over current LTE networks [37,38]. However, more antenna devices will consume more circuit power as wells as more signaling overhead in MIMO systems. ...
... Specially, some work highlight the energy efficient 5G wireless network based on outstanding technology, like Massive MIMO in [37] and switching on-off BSs in [56]. The work in [37] discusses an overview of massive MIMO technology, a realistic power consumption models in MIMO systems and some outstanding techniques for EE-maximization. ...
... Specially, some work highlight the energy efficient 5G wireless network based on outstanding technology, like Massive MIMO in [37] and switching on-off BSs in [56]. The work in [37] discusses an overview of massive MIMO technology, a realistic power consumption models in MIMO systems and some outstanding techniques for EE-maximization. The survey pointed out that EE-maximization of a Massive MIMO system can be achieved using the Massive MIMO technique through minimizing power amplifier (PA) power loss, scaling the number of BS antennas and reducing radio frequency requirements at BS. ...
Thesis
The design target of energy efficiency for 5G networks is at least 1000-fold than the currently available 4G system, while offering higher data transmission rate and very low latency. To evaluate the performance of large representative cellular networks and capture the main factors involved in the energy consumption process, representative and accurate models must be developed. To develop tractable and efficient models, we use the spatial fluid modeling framework and compute the energy efficiency metric. Our model consists of a downlink transmission of an OFDMA cellular network, composed of several base stations and multiple user equipments randomly distributed over the area. An analytical expression of energy efficiency is then derived to study the impact of the major factors involved in the energy consumption process such as fading and shadowing attenuation, cellular coverage type and quality. Extensive numerical simulations were run to compare the results obtained by Monte Carlo simulations and demonstrate the effectiveness and accuracy of the fluid modeling for large cellular networks. The numerical results indicate that user density does not affect energy efficiency. Besides, energy efficiency is more important in suburban environments than in urban environments where the shadowing effect is great, regardless of the cellular coverage type. However, and more generally, micro-cellular networks’deployment offers better energy efficiency than the conventional macro-cellular ones. Besides, we evaluated the effect of the promising Joint Transmission Coordinated MultiPoint (JT-CoMP) technique on energy efficiency, which is significantly improved as the number of coordinated BSs increases. On the other hand, coordination between base stations is only effective for user equipment that is remote from their base station. To resume, our numerical results illustrate the effectiveness and accuracy of fluid modeling, which can be considered a mathematical tool by operators to benchmark cellular networks’energy efficiency.
... Throughout reality, wireless networking is not only constrained to cellular networks, multiple types of new devices would be expected to participate in vast wireless communications to incorporate the Internet of Everything (IoE) principles in the immediate future. The information and communication technology (ICT) industry has made fast strides towards cellular networks of the fifth generation (5G), which are supposed to integrate virtually all into the internet across the globe [3]. In the design of the cellular infrastructure, the key goal is to be able to expand the channel bandwidth. ...
... In the design of the cellular infrastructure, the key goal is to be able to expand the channel bandwidth. For instance, multiple access is an useful approach for next generations to accommodate as many cells as feasible at a given bandwidth with a fair extent of service quality [3]. Nonorthogonal multiple access (NOMA) is perceived to be an innovative multiple access system for cellular networks of the fifth generation (5G) and beyond 5G (B5G) that can potentially increase device propagation performance [4]- [6]. ...
... Where, P 1 (e) is the Bit error rate given in (3). For the case of U ser, i ≥ 2, attainable rate will be ...
Conference Paper
Full-text available
The ever-growing number of users has brought about the challenge to identify a convenient technique for multiple access in next generation wireless communications. It has been seen that non-orthogonal multiple access (NOMA) technique provides far better performance than orthogonal multiple access (OMA) technique while taking advantage of the available resources. Interference can be minimized adequately through the use of Successive Interference Cancellation (SIC) when implemented extensively. But massive implementation increases the complexity of the system and as a result energy efficiency is reduced. To counteract the disadvantages of NOMA technique, interest in hybrid NOMA techniques has grown. Many recent papers have suggested hybrid NOMA schemes as a viable option to mitigate the disadvantages of NOMA. This paper performs an analysis of the performance between hybrid NOMA techniques which are hybrid NOMA-OMA, NOMA Space shift keying (NOMA-SSK) and Successive user relaying cooperative NOMA (SR-NOMA). A comparison of all these techniques is conducted to identify the best hybrid NOMA technique for 5G and beyond wireless communication. The expressions for sum rate and outage probability have been derived for all the techniques. Through analysis and simulation results depicted that NOMA-SSK provides the best performance in terms of sum rate and outage probability among the discussed schemes.
... In addition, it improves energy efficiency since it focuses the energy into ever-smaller areas of space, which makes it a promising technology for sustainable 5G networks [12]- [14]. In [15] the authors discussed the scenarios of boosting the energy FIGURE 6: Green 5G technologies and sustainability indicators. efficiency gains provided by the M-MIMO system, such as reducing the power loss of the amplifiers, lowering the RF chain requirements, executing low complexity operations at the BS, and scaling the number of antennas at the BS. ...
... The authors in [15] inspected the energy efficiency for VOLUME 4, 2021 5G networks and the challenge of the green backhauling. ...
... Further, M-MIMO was inspected in [8] as a green 5G technology to improve the spatial degree of freedom. This technology has an important role in increasing the energy and spectrum efficiency [8], [11]- [15] since it improves the array and multiplexing gain. Another important method to increase the energy efficiency (SDG 7 -clean energy) is by adopting energy harvesting and alternative energy sources such as solar power, fuel cells, and wind power which improves sustainability by reducing the environmental impact, minimizing costs, and assisting in making mobile networks more affordable for the clients [3], [8], [87]. ...
Article
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5G wireless communication systems provide massive system capacity with high data rates, very short low-latency, and ultra-high reliability, in addition to high connection density with a positive experience on smart cities and the Internet of Things (IoT). Future networks are anticipated to revolutionize typical applications such as the enhanced mobile broadband services (EMBB), ultra-reliable low latency communication (uRLLC), and massive machine-type communications (mMTC) anywhere and everywhere. This rationalizes the need to investigate the sustainable elements of 5G networks in smart cities to understand how 5G networks can be more environmentally- friendly and energy-efficient. This paper aims to investigate how 5G networks can act as key enablers in achieving sustainability in smart cities, using a macroscopic review. An overview of 5G communication networks and several 5G technologies used in smart city applications to enhance sustainability is presented. This is followed by investigating the indicators that measure sustainability in 5G networks across the environmental, social, and economic dimensions; and sub-dimensions such as energy efficiency, power consumption, carbon footprint, pollution, cost, health, safety, and security. The results show that the majority of research papers focus on the environmental dimensions of sustainability (42%) when attempting to address sustainability in 5G systems and smart cities. The findings also showed a huge interest in the economic (37%) and social (21%) dimensions as well. Further, when examining the sub-dimensions, it was found that most of the studies focused on energy efficiency (20%), power consumption (17%), and cost (15%).
... In addition, the fifth generation (5G) standards look for higher spectral and energy efficiency by including massive multiple input multiple output (mMIMO) techniques [5]. They, however, pose the issue of estimating a large number of channel coefficients for a massive number of antennas. ...
... In this constellation, all users experience the same performance, thus the same BLER and throughput. We calculate the throughput for each user from BLER using (5). On the other hand, in TMS case we can analyze the performance for one user in its corresponding time instant, which is the single user performance reduced by a factor due to the time sharing. ...
... Array signal processing is a crucial research issue in signal processing and has been extensively used in radar [1,2], sensor [3,4], remote sensing [5][6][7], target detection [8,9], and wireless communication [10][11][12]. ...
... The newŴ is substituted into formula (20) to obtainr. After several iterations, we obtain all the DOA candidates as follows: (1) An equivalentR is obtained through calculation of formulas (3), (5), (6), (7) and (8) (2) The Toeplitz matrix containing DOA information is constructed by using formula (10) (3) Formulas (14)- (16) were combined to obtain formula (18) (4) Initialize B r ð Þ by usingr 0 in formula (21), and utilize the B r ð Þ to constructŴ via formula (18) (5) The exactr is obtained through several iterations of formulas (18) and (20) (6) All DOA candidates were obtained by calculating formula (22) (7) DOA values were obtained from all DOA candidates via formula (23) 4 ...
Article
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A principal singular vector based on multiple Toeplitz matrices is proposed to solve the accuracy problem of direction-of-arrival (DOA) estimation for coherent signals. First, the data matrix received by uniform linear array (ULA) is transformed into a Toeplitz matrix. An equivalent covariance matrix is obtained by square weighted summation method using the Toeplitz matrix. Then, a polynomial containing DOA information is constructed because the signal space and the steering matrix have the same column space; the Toeplitz matrix is built using polynomial coefficients. The problem is transformed into solving linear equations by establishing the relationship between the Toeplitz matrix and the signal subspace. Furthermore, the weighted least square method is used to obtain multiple candidates for linear equations. Finally, the maximum likelihood (ML) rule is used to select source signal candidates from multiple candidates. In comparison with currently known algorithm, the proposed algorithm has the characteristics of high estimation accuracy, low-complexity, and strong anti-interference ability and resolution. Even when the signal-to-noise ratio (SNR) is low, the snapshot number is small, and multiple signals exist; this method can still provide good estimation performance and resolution, which is more than 90% in most cases. Simulation experiments verify the superiority of the algorithm.
... Massive MIMO has been proven to be capable of provid- VOLUME 4, 2016 ing substantial spectral efficiency (SE) [12], [13]. However, the large number of antennas deployed in massive MIMO systems also cause a significant increase in power consumption, hardware cost, and system complexity [14], [15]. Especially for green communications, power consumption is one of the most important concerns [15], [16]. ...
... However, the large number of antennas deployed in massive MIMO systems also cause a significant increase in power consumption, hardware cost, and system complexity [14], [15]. Especially for green communications, power consumption is one of the most important concerns [15], [16]. Therefore, numerous studies have been motivated for power saving in massive MIMO systems [16]- [19]. ...
Article
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In this paper, two green receivers with antenna turn-off and multi-level-mixed-ADC resolution design are proposed for massive MIMO systems, such as 5G networks and Internet of Things (IOT). For practicality, a generic power consumption model for massive MIMO receivers, including ADC resolution, symbol detection, and receiver circuits, is considered. The two proposed green receivers are formulated to minimize power consumption with respect to their individual spectral efficiency (SE) constraints, which are aimed at obtaining the optimal solution of the number of active receive antennas and corresponding multi-level-mixed-ADC resolutions. First, the proposed schemes enable the number of active receive antennas to be equal to the number of receive antennas. Second, a variant of the decremental searching and dynamic programming (DSDP) method [1] is conducted to obtain the correspondingly optimal candidate of the multi-level-mixed-ADC resolution. Third, decrease the number of active receive antennas by 1 and then conduct the variant of DSDP again to search the correspondingly optimal resolution candidate of multi-level mixed ADCs. Fourth, repeat these mechanisms to obtain all optimal multi-level-mixed-ADC resolution candidates for different numbers of active receive antennas. Last, the number of active receive antennas and the corresponding multi-level-mixed-ADC resolution candidate, which achieve the minimum power consumption, are chosen as the optimal solution. In addition, a novel mechanism for accelerating the work of searching the number of turn-off antennas has been designed in the proposed receivers. The simulation results show that compared to DSDP, the two proposed green receivers can provide the advantage of the adjustable flexibility of power consumption with different SE requirements.
... Massive MIMO, NOMA, small cell, mmWave, beamforming, and MEC are the six main pillars that helped to implement 5G networks in real life. Chataut and Akl [7] Yes -Yes ---Yes --Prasad et al. [8] Yes -Yes ------Kiani and Nsari [9] -Yes -----Yes -Timotheou and Krikidis [10] -Yes ------Yes Yong Niu et al. [11] --Yes --Yes ---Qiao et al. [12] --Yes -----Yes Ramesh et al. [13] Yes -Yes ------Khurpade et al. [14] Yes Yes -Yes -----Bega et al. [15] ----Yes ---Yes Abrol and jha [16] -----Yes --Yes Wei et al. [17] -Yes ------Jakob Hoydis et al. [18] -----Yes ---Papadopoulos et al. [19] Yes -----Yes --Shweta Rajoria et al. [20] Yes -Yes --Yes Yes --Demosthenes Vouyioukas [21] Yes -----Yes --Al-Imari et al. [22] - ...
... In [8], different approaches that increased the energy efficiency benefits provided by massive MIMO were presented. They analyzed the massive MIMO technology and described the detailed design of the energy consumption model for massive MIMO systems. ...
Article
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In wireless communication, Fifth Generation (5G) Technology is a recent generation of mobile networks. In this paper, evaluations in the field of mobile communication technology are presented. In each evolution, multiple challenges were faced that were captured with the help of next-generation mobile networks. Among all the previously existing mobile networks, 5G provides a high-speed internet facility, anytime, anywhere, for everyone. 5G is slightly different due to its novel features such as interconnecting people, controlling devices, objects, and machines. 5G mobile system will bring diverse levels of performance and capability, which will serve as new user experiences and connect new enterprises. Therefore, it is essential to know where the enterprise can utilize the benefits of 5G. In this research article, it was observed that extensive research and analysis unfolds different aspects, namely, millimeter wave (mmWave), massive multiple-input and multiple-output (Massive-MIMO), small cell, mobile edge computing (MEC), beamforming, different antenna technology, etc. This article’s main aim is to highlight some of the most recent enhancements made towards the 5G mobile system and discuss its future research objectives.
... In mmWave communications, a large number of antennas with beamforming are required to overcome the high propagation path loss [4]. However, the hardware complexity, energy consumption, and channel estimation overhead generally increase with the number of antennas, which impose constraints on the application of mmWave communication [5,6]. ...
... Require: Pre-designed analog beamforming vectors for the BS, f RF,k , k ∈ {1, . . . , N} 1: Initialize n = 1, k i,n = 0, the number of detection repetition L = 1, and trigger condition = 1 2: while == 1 do 3: Search for M + 1 beam space 4: for i = 1 : M + 1 5: Receiving signal with f RF,i , for the i-th direction: 6: ...
Article
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This paper proposes an effective strongest angles of arrival (AoAs) estimation algorithm for a hybrid millimeter wave (mmWave) communication system with 1-bit analog-to-digital/digital-to-analog converters (A/Ds) equipped at transceivers. The proposed algorithm aims to reduce the required number of estimation overheads, while maintaining the root mean square error (RMSE) of strongest AoA estimates at the base station. We obtain the quantization thresholds of A/Ds for different signal-to-noise ratios (SNRs) and numbers of antennas via numerical simulations, based on which, the strongest AoAs can be estimated with a small amount of overheads. The proposed algorithm is compared with conventional schemes including 1-bit FFT and 1-bit exhaustive search, as well as 1-bit Cramér-Rao lower bound. Simulation results verify the effectiveness of our proposed algorithm in terms of reducing estimation overheads while maintaining reasonable estimation performance in low SNRs.
... In [8], an alternating optimization algorithm that determines an active antenna set and transmit precoding in an iterative water-filling fashion was proposed to maximize the EE. A comprehensive survey on energy-efficient design is found in [9]. ...
Preprint
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The use of low-resolution digital-to-analog and analog-to-digital converters (DACs and ADCs) significantly benefits energy efficiency (EE) at the cost of high quantization noise in implementing massive multiple-input multiple-output (MIMO) systems. For maximizing EE in quantized downlink massive MIMO systems, this paper formulates a precoding optimization problem with antenna selection; yet acquiring the optimal joint precoding and antenna selection solution is challenging due to the intricate EE characterization. To resolve this challenge, we decompose the problem into precoding direction and power optimization problems. For precoding direction, we characterize the first-order optimality condition, which entails the effects of quantization distortion and antenna selection. For precoding power, we obtain the optimum solution using a gradient descent algorithm to maximize EE for given precoding direction. We cast the derived condition as a functional eigenvalue problem, wherein finding the principal eigenvector attains the best local optimal point. To this end, we propose generalized power iteration based algorithm. Alternating these two methods, our algorithm identifies a joint solution of the active antenna set and the precoding direction and power. In simulations, the proposed methods provide considerable performance gains. Our results suggest that a few-bit DACs are sufficient for achieving high EE in massive MIMO systems.
... • Proposed (AO-BS) algorithm 2017 [17] To achieve multiple spectral and EE gains. ...
... To support various applications, a high data rate and stable communication would therefore be needed [1], [2]. The main aim is to be able to extend the channel capacity in the architecture of the cellular networks [3]. For instance, multiple access is an useful approach for next generations to accommodate as many cells as feasible at a given bandwidth with a fair extent of service quality [4], [5]. ...
Conference Paper
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The steadily developing number of users has achieved the test to distinguish an advantageous strategy for different access in upcoming wireless communication. It has been seen that non-orthogonal multiple access (NOMA) method gives far superior execution than orthogonal multiple access (OMA) procedure while exploiting the accessible assets. Interferences can be limited enough using successive interference cancellation (SIC) when actualized broadly, however it is normal situation in NOMA. But enormous usage increments the complexity of the framework and as a result energy effectiveness is decreased. To balance the detriments of NOMA procedure, interest in hybrid NOMA strategies has developed. Numerous new papers have proposed hybrid NOMA schemes as a reasonable alternative to moderate the disservices of NOMA.
... The characteristics of 5G-enabled vehicular networks have a wide high bandwidth and coverage area. Based on data shared by 5G wireless, during peak periods, the data transmission rate can approach 20 Gb/s, while the average data transfer rate is over 100 Mb/s [5][6][7][8]. The capacity of the supported network is 1000 times that of conventional networks, and it can give a more steady connection [9][10][11]. ...
Article
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The vehicles in the fifth-generation (5G)-enabled vehicular networks exchange the data about road conditions, since the message transmission rate and the downloading service rate have been considerably brighter. The data shared by vehicles are vulnerable to privacy and security issues. Notably, the existing schemes require expensive components, namely a road-side unit (RSU), to authenticate the messages for the joining process. To cope with these issues, this paper proposes a provably secure efficient data-sharing scheme without RSU for 5G-enabled vehicular networks. Our work included six phases, namely: TA initialization (TASetup) phase, pseudonym-identity generation (PIDGen) phase, key generation (KeyGen) phase, message signing (MsgSign) phase, single verification (SigVerify) phase, and batch signatures verification (BSigVerify) phase. The vehicle in our work has the ability to verify multiple signatures simultaneously. Our work not only achieves privacy and security requirements but also withstands various security attacks on the vehicular network. Ultimately, our work also evaluates favourable performance compared to other existing schemes with regards to costs of communication and computation.
... Massive multiple-input-multiple-output (MIMO) antennas are moving towards the millimeter-wave (mmwave) to increase high data rate and enhance spectral and energy efficiencies based on larger bandwidth in the mm-wave frequency bands. The high multiplexing gains are achievable with a huge number of antennas for both transmitter and receiver [1]. Increasing the large data to active users, obtaining better costs, and conventional energy efficiency are considered key components of 5G wireless communication systems. ...
Preprint
Full-text available
Millimeter-wave (mm-wave) is a promising technique to enhance the network capacity and coverage of next-generation (5G) based on utilizing a great number of available spectrum resources in mobile communication. Improving the 5G network requires enhancing and employing mm-wave beamforming channel propagation characteristics. To achieve high data rates, system performance remains a challenge given the impact of propagation channels in mm-wave that is insufficient in both path loss, delay spread, and penetration loss. Additional challenges arise due to high cost and energy consumption, which require combining both analog and digital beamforming (hybrid beamforming) to reduce the number of radio frequency (RF) chains. In this paper, the distributed powers in the small cell to suppress path loss by specifying a considerable power and controlling the distributed power to reduce the high cost and energy consumption was proposed. The hybrid beamforming in mm-wave exploits a large bandwidth which reduces the large path loss in Rayleigh fading channel. Also, the trade-off between the energy consumption of RF chains and cost efficiency depends on reducing the number of RF chains and the distributed number of users. This paper finds that hybrid beamforming for massive multiple?input multiple-output (MIMO) systems constitute a promising platform for advancing and capitalizing on 5G networks
... Although M-MIMO enables reduction of the transmitted power, through high effective antenna gain obtained using beamforming, it is not always enough to compensate the power consumed by hardware components e.g., transceivers chains, filters, modulators [3]. Moreover, the 5G system will be typically a heterogeneous network (HetNet), i.e., a network composed of overlapping cells of various sizes, with each Base Station (BS) equipped with an antenna array [4]. Although HetNet can provide large spectral-efficiency benefits, increased energy consumption is expected. ...
Preprint
Full-text available
Energy Efficiency (EE) is of high importance while considering Massive Multiple-Input Multiple-Output (M-MIMO) networks where base stations (BSs) are equipped with an antenna array composed of up to hundreds of elements. M-MIMO transmission, although highly spectrally efficient, results in high energy consumption growing with the number of antennas. This paper investigates EE improvement through switching on/off underutilized BSs. It is proposed to use the location-aware approach, where data about an optimal active BSs set is stored in a Radio Environment Map (REM). For efficient acquisition, processing and utilization of the REM data, reinforcement learning (RL) algorithms are used. State-of-the-art exploration/exploitation methods including e-greedy, Upper Confidence Bound (UCB), and Gradient Bandit are evaluated. Then analytical action filtering, and an REM-based Exploration Algorithm (REM-EA) are proposed to improve the RL convergence time. Algorithms are evaluated using an advanced, system-level simulator of an M-MIMO Heterogeneous Network (HetNet) utilizing an accurate 3D-ray-tracing radio channel model. The proposed RL-based BSs switching algorithm is proven to provide 70% gains in EE over a state-of-the-art algorithm using an analytical heuristic. Moreover, the proposed action filtering and REM-EA can reduce RL convergence time in relation to the best-performing state-of-the-art exploration method by 60% and 83%, respectively.
... A UAV can transmit realtime video from the vehicle to a base station/remote pilot, as in a monitoring procedure. Media with bandwidth requirements needs to be used to deliver high-speed data packets (often higher in full HD video transmission or wireless backhauling) [23]. ...
... Although M-MIMO enables reduction of the transmitted power, through high effective antenna gain obtained using beamforming, it is not always enough to compensate the power consumed by hardware components e.g., transceivers chains, filters, modulators [3]. Moreover, the 5G system will be typically a heterogeneous network (HetNet), i.e., a network composed of overlapping cells of various sizes, with each Base Station (BS) equipped with an antenna array [4]. Although HetNet can provide large spectral-efficiency benefits, increased energy consumption is expected. ...
Article
Energy Efficiency (EE) is of high importance while considering Massive Multiple-Input Multiple-Output (M-MIMO) networks where base stations (BSs) are equipped with an antenna array composed of up to hundreds of elements. M-MIMO transmission, although highly spectrally efficient, results in high energy consumption growing with the number of antennas. This paper investigates EE improvement through switching on/off underutilized BSs. It is proposed to use the location-aware approach, where data about an optimal active BSs set is stored in a Radio Environment Map (REM). For efficient acquisition, processing and utilization of the REM data, reinforcement learning (RL) algorithms are used. State-of-the-art exploration/exploitation methods including ϵ-greedy, Upper Confidence Bound (UCB), and Gradient Bandit are evaluated. Then analytical action filtering, and an REM-based Exploration Algorithm (REM-EA) are proposed to improve the RL convergence time. Algorithms are evaluated using an advanced, system-level simulator of an M-MIMO Heterogeneous Network (HetNet) utilizing an accurate 3D-ray-tracing radio channel model. The proposed RL-based BSs switching algorithm is proven to provide 70% gains in EE over a state-of-the-art algorithm using an analytical heuristic. Moreover, the proposed action filtering and REM-EA can reduce RL convergence time in relation to the best-performing state-of-the-art exploration method by 60% and 83%, respectively.
... When the traffic load is low, the energy consumption of a mMIMO system may be reduced by using only a subset of the available BS antennas and/or transceiver modules, according to traffic requirements and avoiding resource waste. This type of approaches are referred to as antenna selection or channel shutdown [158], [159]. ...
Preprint
Cellular networks have changed the world we are living in, and the fifth generation (5G) of radio technology is expected to further revolutionise our everyday lives, by enabling a high degree of automation, through its larger capacity, massive connectivity, and ultra-reliable low-latency communications. In addition, the third generation partnership project (3GPP) new radio (NR) specification also provides tools to significantly decrease the energy consumption and the green house emissions of next generations networks, thus contributing towards information and communication technology (ICT) sustainability targets. In this survey paper, we thoroughly review the state-of-the-art on current energy efficiency research. We first categorise and carefully analyse the different power consumption models and energy efficiency metrics, which have helped to make progress on the understanding of green networks. Then, as a main contribution, we survey in detail -- from a theoretical and a practical viewpoint -- the main energy efficiency enabling technologies that 3GPP NR provides, together with their main benefits and challenges. Special attention is paid to four key enabling technologies, i.e., massive multiple-input multiple-output (MIMO), lean carrier design, and advanced idle modes, together with the role of artificial intelligence capabilities. We dive into their implementation and operational details, and thoroughly discuss their optimal operation points and theoretical-trade-offs from an energy consumption perspective. This will help the reader to grasp the fundamentals of -- and the status on -- green networking. Finally, the areas of research where more effort is needed to make future networks greener are also discussed.
... A challenging task for large phased array at mm-wave is represented by the cooling system for dissipating heat [19], [20]. Passive cooling systems are preferred to active ones from industry since they do not need electricity. ...
Article
Full-text available
A thorough analysis of the performance of planar arrays with a regular periodic lattice is carried out and applied to massive multiple-input-multiple-output (MIMO) systems operating within 5G NR n257 and n258 frequency band. It is shown that, among different arrangements with uniform spacing, a triangular lattice guarantees the reduction of the Average Side Lobe Level (ASLL), a better angular scan resolution of the main beam within a predefined angular sector and a lower mutual coupling level among elements. Moreover, single beam and multibeam application scenarios are considered for the performance comparison and both cases assess the remarkable features offered by a triangular arrangement. Particular attention is paid to illustrate, for different propagation channel scenarios, the effects of the array lattice on overall system performance including average gain as well as Signal-to-Interference plus Noise Ratio (SINR) and Sum Spectral Efficiency (SSE). The obtained results prove that a regular and periodic triangular lattice is appealing for arrays to be adopted in massive MIMO 5G systems.
... Massive multiple-input-multiple-output (MIMO) antennas are moving towards the millimeter-wave (mmwave) to increase high data rate and enhance spectral and energy efficiencies based on larger bandwidth in the mm-wave frequency bands. The high multiplexing gains are achievable with a huge number of antennas for both transmitter and receiver [1]. Increasing the large data to active users, obtaining better costs, and conventional energy efficiency are considered key components of 5G wireless communication systems. ...
Article
Full-text available
Researchers and robotic development groups have recently started paying special attention to autonomous mobile robot navigation in indoor environments using vision sensors. The required data is provided for robot navigation and object detection using a camera as a sensor. The aim of the project is to construct a mobile robot that has integrated vision system capability used by a webcam to locate, track and follow a moving object. To achieve this task, multiple image processing algorithms are implemented and processed in real-time. A mini-laptop was used for collecting the necessary data to be sent to a PIC microcontroller that turns the processes of data obtained to provide the robot's proper orientation. A vision system can be utilized in object recognition for robot control applications. The results demonstrate that the proposed mobile robot can be successfully operated through a webcam that detects the object and distinguishes a tennis ball based on its color and shape.
... Most of the existing studies [22]- [25] discussed standalone planning for mRRUs. For instance, in [26], the energy efficiency prospects of 5G wireless networks are analyzed for reducing energy consumption in different parts of the networks. The work in [27] introduced an analytical model for planning and dimensioning of 5G cloud RAN in the context of energy efficiency. ...
Article
Full-text available
With the ever-increasing traffic demand of wireless users, resulting from the huge deployment of Internet-of-Things (IoT) devices and the emergence of smart city applications requiring ultra-low latency networks, the Fifth Generation (5G) of cellular networks have been introduced as a revolutionary broadband technology to boost the quality of service of mobile users. In this paper, we investigate the planning process for a 5G radio access network having mmWave Micro Remote Radio Units (mRRUs) on top of sub-6 GHz Macro Remote Radio Units (MRRUs). We rely on proper channel models and link budgets as well as Urban Macro-cells (UMa) and Urban Micro-cells (UMi) characteristics to carefully formulate a 5G network planning optimization problem. We aim to jointly determine the minimum number of MRRUs and mRRUs to install and find their locations in a given geographical area while fulfilling coverage and user traffic demand constraints. In order to solve this planning process, we propose a two-step process where we first employ a low complexity meta-heuristic algorithm to optimize the locations of RRUs followed by an iterative elimination method to remove redundant cells. To evaluate the performances of this proposed approach, we conduct a comparative study using Accelerated Particle Swarm Optimization and Simulated Annealing. Simulations results using sub-6 GHz UMa and 28 GHz UMi demonstrate the ability of the proposed planning approach to achieve more than 98% coverage with minimum cell capacity outage rate, not exceeding the 2%, for different scenarios and illustrate the efficiency of the evolutionary algorithms in solving this NP-hard problem in reasonable running time. INDEX TERMS 5G networks, radio heterogeneous network planning, network dimensioning, swarm intelligence, evolutionary algorithm.
... To reduce the CO 2 footprint and energy consumption, cellular operators need to adopt green management of the cells and reduce their operational expenditures (OPEX) [6]. Since around 60% of the energy is consumed by the base stations (BSs) [7], [8], the main focus of energy savings is on the BSs where the significant cost is related to the radio transmission and its related chain (amplifier, mixer, etc. ) From the mobile user perspective, energy efficiency is also essential as it leads to more extended operation due to the limited battery power. ...
Article
Full-text available
In this paper, we study the energy efficiency (EE) of orthogonal frequency-division multiple access (OFDMA) cellular networks under the 5G requirement of EE enhancement. We aim to present a power allocation scheme maximizing the EE of downlink cellular communications while avoiding numerical methods such as fractional programming. We focus on two EE forms; global EE and weighted sum EE. Therefore, we propose a novel explicit expression of the optimal power allocation related to each subcarrier. We also present the power control with limited power budget or/and minimal transmission rate constraint in both base station and subcarrier perspectives. As a result, we notice the occurrence of some transmission outage events depending on the constraints' parameters. From another side, we extend our study to analyze the effect of the channel state information (CSI) unavailability on our proposed power scheme. In the numerical results, we show that our proposed power control improves the EE, especially at high power budget regime and low minimal rate regime. We also show that having more subcarriers enhances the OFDMA EE. Finally, we show that EE degradation due to CSI unavailability is very small showing the robustness of the proposed scheme against CSI imperfectness.
... Proposed (AO-BS) algorithm 2017 [10] To achieve multiple spectral and EE gains. ...
... Since 4G LTE, the ability to fit more packets on a radio wave has been slowing, with research indicating [69] the Shannon Bound has effectively been reached. However, thankfully in 5G the deployment of much higher order Massive Multiple-In, Multiple-Out (mMIMO) radio technology [70] provides the possibility to greatly improve wide-area network spectral efficiency [71], [72]. Indeed, this is one of the main tools in the fifth generation of cellular technologies [73]. ...
Preprint
Full-text available
Techno-economic assessment is a fundamental technique engineers use for evaluating new communications technologies. However, despite the techno-economics of the fifth cellular generation (5G) being an active research area, it is surprising there are few comprehensive evaluations of this growing literature. With mobile network operators deploying 5G across their networks, it is therefore an opportune time to appraise current accomplishments and review the state-of-the-art. Such insight can inform the flurry of 6G research papers currently underway and help engineers in their mission to provide affordable high-capacity, low-latency broadband connectivity, globally. The survey discusses emerging trends from the 5G techno-economic literature and makes six key recommendations for the design and standardization of Next Generation 6G wireless technologies.
... The Internet of Things has expanded the service scope of the mobile Internet, extending the communication between people to things and the intelligent interconnection between people and things. The mobile communication technology has been applied to all areas of society [2]. Literature [3] presents a Doppler frequency shift estimation and compensation algorithm based on position and precompensation for millimeter-wave HSR scene. ...
Article
Full-text available
Mobile Internet will promote the continuous change of human interaction, leading to an increase in mobile traffic, so the demand for network bandwidth and data volume is rising rapidly, which is also one of the problems that 5G needs to solve. The mobile communication network of the railway system has the characteristics of high-speed user mobility, large-scale group mobility of users, high certainty of user mobile lines, and high QoS requirements for dispatching information. In order to improve the transmission reliability requirements of the railway system for wireless communication, a quick search method algorithm based on GMCS model to encode the number of each subinterval is proposed. Hybrid precoding is designed according to multivariate symmetry rules. The target beam is designed according to the GMCS model, and the hierarchical training beam is designed to minimize the mean square error between the training beam and the target beam as the objective function. Then, the fast search model based on beam overlap is extended to NLoS to solve the problem of misjudgment caused by multipath. In the simulation experiment, it proves that the search success rate of the research in this paper is 10% higher than that of the traditional algorithm. It improves the search speed and has obvious advantages in complexity. It can provide a dynamic reliable conversion mechanism for the railway communication environment, reduce the transmission power of the base station, and optimize the actual effect of uplink and downlink service requirements.
... In large-scale multiple antennas, the base station is equipped with a large number of antennas and serves many users in the same time and frequency domain, which provides gigabit-level wireless traffic and scales-up multiplexing and array gain [15]. Deploying a large number of antennas at the base station makes the wireless channel to be nearly deterministic because the links between base stations to end-user become nearly orthogonal to each other [16]. However, the challenges such as high complexity, increased RF circuit power, significant gain, and increased signal processing cost arise with the deployment of large-scale multiple antennas in a base station [17]. ...
Article
Energy consumption growth of the fifth-generation (5G) mobile network infrastructure can be significant due to the increased traffic demand for a massive number of end-users with increasing traffic volume, user density, and data rate. The emerging technologies of radio access networks (RAN), e.g., millimeter-wave (mm-wave) communication and large–scale antennas, make a considerable contribution to such an increase in energy consumption. The multiband 2-tier heterogeneous network (HetNet), cloud radio access network (C-RAN), and heterogeneous cloud radio access network (H-CRAN) are considered the prospective RAN architectures of the 5G mobile communication. This paper explores these novel architectures from the energy consumption and network power efficiency perspective considering the varying high volume traffic load, the number of antennas, varying bandwidth, and varying density of low power nodes (LPNs), integrated with mm-wave communication and large-scale multiple antennas. The architectural differences of these networks are highlighted and power consumption analytical models that characterize the energy consumption of radio resource heads (RRHs), base band unit (BBU) pool, fronthaul, macro base station (MBS), and small cell base stations (SCBs) in HetNet, C-RAN, and H-CRAN are developed. The network power efficiency with the consideration of propagation environment and network constraints is investigated to identify the energy-efficient architecture for the 5G mobile network. The simulation results reveal that the power consumption of all these architectures increases in all considered scenarios due to an increase in power consumption of radio frequency components and computation power. Moreover, CRAN is the most energy-efficient RAN architecture due to its cooperative processing and decreased cooling and site support devices and H-CRAN consumes most of the energy compared to other 5G RAN architectures mainly due to a high level of heterogeneity.
... The energy focusing capability achieved by the M-MIMO technology with beamforming has clear benefits in terms of enhanced capacity and EE [73,74,75]. Unfortunately, such gains come with greater interference on the border of the cells [76,8]. ...
Thesis
Mobile operators are continuously challenged to offer faster and better connectivity to their customers. The mobile networks are expected to provide enhanced capacities while dealing with a new variety of services. 5G brings a wide range of novelty to increase the quality and services offered by the operators. These novelties include, but are not limited to, new antenna technologies, the apparition of Multi-User scheduling, new architectures, but also the inclusion of more artificial intelligence in the network decisions. The changes brought by 5G vastly increases the complexity of the networks. 5G comes with a wide range of new parameter to be set in an optimized manner. The demand towards the operators are higher than ever whereas the network is more complex. In 4G, the number of parameters to be chosen was already high and complex. To optimize the network and enable the users to get the best quality of experience, Self-Organizing Network (SON) had been introduced in 4G network. SON allows the network to enable self-optimization, self-configuration and self-healing. The SON has to evolve to deal with the new challenges of the network. M-MIMO and beamforming present the opportunity to focus signal on users, and thus increasing throughputs. However, focused signal come with new complexity and new challenges to overcome. We consider in this thesis the self-optimization of network relying on M-MIMO with Multi-User (MU)-schedulers. First, we consider a heterogeneous network. Densifying a network by adding small-cells increases quickly the capacity of the network. Massive Multiple Input Multiple Output (M-MIMO) and MU-scheduler render the 4G SON solutions out-of-date and present a new challenge to overcome. In this thesis, we propose a MU-collaborative scheduler for 5th Generation (5G) M-MIMO cell that takes into account the impact of the macro scheduling on the small-cells located in the macro cell’s area. We also assess the performance of the scheduler through numerical experiments. Interferences between neighboring M-MIMO cells are also an important topic to be addressed in 5G network. In this work, we propose three different approaches to this problem. The Automatic Neighbor Beam Relation (ANBR) solution is a heuristic solution offering a low complexity and a reactive solution to deal with neighboring cells. The thesis then introduce a Multi-Armed-Bandit (MAB) solution to enhance the previous heuristic to deal with neighboring interferences in a 5G M-MIMO network with online learning. Finally, a third approach based on the exploitation of geolocalized data to take advantage of information at a finer granularity is explored.
... It presents a plethora of challenges as well as opportunities for vehicular networks [4][5][6]. Under 5G wireless networks, the characteristics are 20 Gb/s and 100 Mb/s for data transmission and average data transmission rates, respectively [7,8]. ...
Article
Full-text available
The security and privacy concerns in vehicular communication are often faced with schemes depending on either elliptic curve (EC) or bilinear pair (BP) cryptographies. However, the operations used by BP and EC are time-consuming and more complicated. None of the previous studies fittingly tackled the efficient performance of signing messages and verifying signatures. Therefore, a chaotic map-based conditional privacy-preserving authentication (CM-CPPA) scheme is proposed to provide communication security in 5G-enabled vehicular networks in this paper. The proposed CM-CPPA scheme employs a Chebyshev polynomial mapping operation and a hash function based on a chaotic map to sign and verify messages. Furthermore, by using the AVISPA simulator for security analysis, the results of the proposed CM-CPPA scheme are good and safe against general attacks. Since EC and BP operations do not employ the proposed CM-CPPA scheme, their performance evaluation in terms of overhead such as computation and communication outperforms other most recent related schemes. Ultimately, the proposed CM-CPPA scheme decreases the overhead of computation of verifying the signatures and signing the messages by 24.2% and 62.52%, respectively. Whilst, the proposed CM-CPPA scheme decreases the overhead of communication of the format tuple by 57.69%
... Massive multiple-input multiple-output (M-MIMO) refers to large arrays (potentially hundreds) of antennas at BSs, allowing multiple users to be served simultaneously. This improves energy efficiency by enabling large multiplexing and array gains (see [12]). ...
Article
Full-text available
The energy efficiency and consumption of mobile networks have received increasing attention from academics and industry in recent years. This has been provoked by rapid increases in mobile data traffic and projected further rapid increases over the next decade. As a result, dramatic improvements in the energy efficiency of mobile networks are required to ensure that future traffic levels are both environmentally and economically sustainable. In this context, a good deal of research has focused on technologies and strategies that can improve the energy efficiency of 5G and future mobile networks more broadly. However, existing reviews in the field of green or sustainable mobile communications on the topic of the energy use implications of 5G overlook a number of issues that broader literatures on the energy use impacts of ICTs suggest could be significant. Addressing this gap, we conduct a literature review to examine whole network level assessments of the operational energy use implications of 5G, the embodied energy use associated with 5G, and indirect effects associated with 5G-driven changes in user behaviour and patterns of consumption and production in other sectors of the economy. In general, we find that these issues and their energy use implications have received insufficient attention in publicly available studies on the energy use impacts of 5G.
... This can be achieved by reducing the cell size and increasing the number of deployed RAUs. However, a large number of RAUs also involves high energy consumption, high cost and contribution to the global carbon footprint [1], [9]. Therefore, it is crucial to provide solutions to properly supply the required power to the RAUs [10]. ...
Article
Full-text available
We report the implementation of a full optically-powered 5G new radio (5G NR) fiber-wireless (FiWi) system based on power-over-fiber (PoF) and radio-over-fiber (RoF) technologies. Our approach enables the simultaneous transmission of a 5G NR signal at 3.5 GHz with bandwidth up to 100 MHz and a 2.2-W optical power signal employing dedicated fiber-optics links. The optical-wireless data link consists of a 12.5-km single-mode fiber (SMF) optical fronthaul followed by a 10-m wireless propagation environment, which is the longest wireless reach reported in literature up to now, regarding optically-powered FiWi systems. The proposed PoF system is able to deliver stable electrical power up to 475 mW, by means of using a 100-m multimode fiber (MMF) link, with the purpose of optically powering a 5G NR remote antenna unit (RAU). An overall power transmission efficiency (PTE) of 23.5% is experimentally demonstrated in a real 5G NR system. Furthermore, the FiWi system performance is investigated in accordance with the $3^{\mathrm rd}$ generation partnership project (3GPP) Release 15 requirements, in terms of root mean square error vector magnitude (${\mathrm EVM}_{\mathrm RMS}$). The proposed optically-powered 5G NR FiWi system provides 500 Mbit/s throughput with ${\mathrm EVM}_{\mathrm RMS}$ as low as 3.9%, employing 64-quadrature amplitude modulation (QAM) without using optical amplification.
... Since 4G LTE, the ability to fit more packets on a radio wave has been slowing, with research indicating [69] the Shannon Bound has effectively been reached. However, thankfully in 5G the deployment of much higher order Massive Multiple-In, Multiple-Out (mMIMO) radio technology [70] provides the possibility to greatly improve wide-area network spectral efficiency [71], [72]. Indeed, this is one of the main tools in the fifth generation of cellular technologies [73]. ...
Article
Full-text available
Techno-economic assessment is a fundamental technique engineers use for evaluating new communications technologies. However, despite the techno-economics of the fifth cellular generation (5G) being an active research area, it is surprising there are few comprehensive evaluations of this growing literature. With mobile network operators deploying 5G across their networks, it is therefore an opportune time to appraise current accomplishments and review the state-of-the-art. Such insight can inform the flurry of 6G research papers currently underway and help engineers in their mission to provide affordable high-capacity, low-latency broadband connectivity, globally. The survey discusses emerging trends from the 5G techno-economic literature and makes five key recommendations for the design and standardization of Next Generation 6G wireless technologies.
... Hardware components are the other major constraints to increase the EE, so minimizing Radio Frequency (RF) chain requirements can solve the problem at the Base Station (BS). Antenna selection, hybrid beamforming, and transceiver design can promise an increase in EE at the massive MIMO networks [2]. As the data rate increase circuit power and transmit power also increase. ...
... There is the need for providers of cellular networks to invest as much as billions of dollars yearly for the acquisition of wireless spectrum, which is required for the building of a network with excellent coverage [24]. Since 5G networks will need to deploy small dense cell so as to be able to enable capacity by 1000 times, a key challenge will be the huge of cost of providing a backhaul solution. ...
Conference Paper
Full-text available
Through the new wireless generation, technology is required to composition a fifth-generation base station and the configuration of all of that base station This procedure takes into account many qualifications, such as Electromagnetic Fields levels radiated by means of the installed base station. the scientist developed many technologies, including these five major technology, they utilize each of small cells, massive multiple-input, multiple-output, device-to-device communication, Machine-to-machine communication, and millimeter wave band. each one of these technologies have to designed with a constrain of (EMF) aware with a view to promote the network performance. This paper provides an elaborate survey concerning the fifth-generation network and relating to the prospect health peril related with Electromagnetic Fields exposure and the various metrics that are actually utilized for estimating the impacts of this sort of exposition on the public. likewise, challenges are illustrated and several EMF constraints are mentioned. This paper as well reviews the probable impacts of new 5G technologies (mm-wave) exposure on the human body together with focusing on physiological impacts (human skin) and biological impact (immune system).
... Likewise, the tremendous number of receive antennas can be controlled by one device or appropriated to numerous devices. Other than acquiring the advantages of conventional MIMO systems, a massive MIMO framework can also extremely upgrade both spectral efficiency and energy efficiency (Rusek, Persson et al. 2013, Prasad, Hossain et al. 2017. Besides, in massive MIMO frameworks, there is no impacts of noise and fast fading, and reducing of intracell interference can be do it by utilizing simple linear precoding and detection methods. ...
Conference Paper
The fast growth of mobile telecommunication fast motivating the companies to plan continuously and work from first generation until fourth generation, many companies in this field planned and started their scenarios toward fifth generation (5G) mobile, this is because of the need of higher data rate transmission and wireless system radio network, many challenges expected will be problem during this project, this paper is an attempt to contribute as a proposed C-Node-B base station transceiver for 5G mobile system, 64 64 64 MIMO system has been used with presenting the beam forming technique, MIMO parameters and the main basic parameters in beamforming has been optimized in the proposed design KEY WORDS: 5G system; MIMO system; C-Node-B cell; 5G data rate.
... In general, EE in massive MIMO systems can be improved by either lowering the signal processing complexity and thus its associated power consumption, or by improving the hardware resources utilization 1 [7]. Following this criteria, a joint optimization of time domain beam-steering with peak-toaverage power ratio (PAPR) reduction was proposed in [8] and [9], where computational complexity is significantly reduced while improving the power amplifier efficiency. ...
Article
Full-text available
This paper explores key parameters of a massive MIMO system and their impact on energy efficiency at transmission. In particular, the effect of the digital to analog converter resolution and peak to average power ratio reduction techniques are addressed, in the context of practical user location distributions for both line and non line of sight channels. Results show interesting design trade-offs, and highlight the relevance of an accurate model for the user locations for the correct evaluation of the achievable performance.
... Currently, some new technologies are proposed for the coming age of wireless networks. Massive MIMO technology [2,3], in which large number of antennas are mounted at the base station (BS) to serve considerable amount of users, offers an extensive array of spatial multiplexing gain [4,5]. Massive MIMO technology is an actual approach to enhance throughput of wireless network without requiring additional bandwidth or power transmission. ...
Article
Full-text available
The influence of circuit intake power on Spectral Energy Efficiency (S.E.E) of massive Multiple-Input-Multiple-Output (MIMO) under the existence of channel estimation errors is examined using Zero-Forcing (ZF) linear pre-coding scheme. The system model which includes new defined total intake power involving the transmit power of amplifiers and the circuit power intake of the analog devices is developed. To analyze the impact of circuit intake power on S.E.E, the S.E.E with and without circuit intake power is investigated and presented after formulating a closed-form expression of S.E.E that incorporates new defined power model. Our investigation reveals that, the impact of circuit intake power is very significant when Base Station (BS) is arrayed with large number of antennas. Using the new S.E.E closed-form formula, derived from our new defined power intake model, the S.E.E is evaluated when the number of BS antennas (M) rises and it is observed that, S.E.E behaves like a concave function. The same results for S.E.E are also observed when transmit power increases. We conclude that, it is easy to get maximum S.E.E using a small number of BS antennas and optimal transmit power, when circuit power intake is included in the power consumption model. When transmit power totally dominates the circuit intake power, the maximum S.E.E is obtained only when all antennas are used (meaning maximum S.E.E is obtained when the number of BS antennas becomes very large). The numerical results reveal the importance of circuit intake power on optimizing S.E.E of massive MIMO under the presence of channel estimation errors.
... However, the underlying cost of improved network throughput is reduced Energy Efficiency (EE). This phenomenon is mainly related to the increased power consumption caused by additional hardware related to each of the BS antennas [3]. As high power consumption affects network operators' costs and contributes to the world's carbon footprint, EE optimization is identified as one of the key challenges for fifth generation (5G) and beyond networks [4], [5]. ...
Article
Full-text available
To provide users with high throughputs, the fifth generation (5G) and beyond networks are expected to utilize the Massive Multiple-Input Multiple-Output technology (MMIMO), i.e., large antenna arrays. However, additional antennas require the installation of dedicated hardware. As a result the power consumption of a 5G MMIMO network grows. This implies, e.g., higher operator costs. From this angle, the improvement of Energy Efficiency (EE) is identified as one of the key challenges for the 5G and beyond networks. EE can be improved through intelligent antenna switching, i.e., disabling some of the antennas installed at a 5G MMIMO Base Station (BS) when there are few User Equipments (UEs) within the cell area. To improve EE in this scenario we propose to utilize a sub-class of Machine Learning techniques named Reinforcement Learning (RL). Because 5G and beyond networks are expected to come with accurate UE localization, the proposed RL algorithm is based on UE location information stored in an intelligent database named a Radio Environment Map (REM). Two approaches are proposed: first EE is maximized independently for every set of UEs’ positions. After that the process of learning is accelerated by exploiting similarities between data in REM, i.e., REM-Empowered Action Selection Algorithm (REASA) is proposed. The proposed RL algorithms are evaluated with the use of a realistic simulator of the 5G MMIMO network utilizing an accurate 3D-Ray-Tracing radio channel model. The utilization of RL provides about 18.5% EE gains over algorithms based on standard optimization methods. Moreover, when REASA is used the process of learning can be accomplished approximately two times faster.
Article
Unmanned aerial vehicles (UAVs) have a wide range of military and commercial applications. UAVs play an important role in 6G networks due to their low cost and flexible positioning. UAVs can play different roles in the network and act as an air base station, as a relay, or as users in cellular networks. One of the major challenges in these systems is to increase lifespan with low energy consumption. The automatic repeat request (ARQ) protocol is used to increase throughput and obtain dependable communications for multi-input multiple-input multiple-output (MIMO) systems, even in the presence of severe propagation conditions. On the other hand, (UAV)-enabled communication system provides flexibility and reliability compared to conventional ones which have been considered in the new generation of wireless communications. Thus, using ARQ protocols in this system faces serious challenges such as increasing delay and operational implementation complexities in the receiver. Therefore, to meet the ARQ challenge in the uplink of massive MIMO systems, we have investigated utilizing joint iterative detection and decoding methods with reduced computational complexity have been proposed in a UAV-enabled communication system in the condition that users are equipped with two antennas to provide a solution to reduce energy consumption. In this structure, system performance improves as the computational complexity increases. Therefore, we look for methods that reduce complexity while maintaining system performance at an acceptable level. In this study, we seek to provide a solution that can establish a reasonable compromise between system performance and computational complexity. This aim is achieved by establishing a connection between the components of soft joint detection and decoding, linear detection with approximation methods, and sorting. The first part of the receiver is sorting the users before detection, then, in the next module, a turbo-process-based low-complexity MIMO iterative detection and decoding (IDD) algorithm, with minimum mean square error (MMSE) detector and soft channel decoder, is used. For solving the challenge of computational complexity, utilizing of approximation-based detection method is proposed. This structure works in such a way that after sorting the users, in the first iteration, a certain number of users are decoded using a hard decoding scheme after the soft detection and decoding. Therefore, these data are subtracted from the soft feedback information (prior data) to the detector, as inter user interference (IUI) and the Joint IDD module continue the iterative cycle until all users’ data are decoded.
Article
Mobile communication technologies are tremendously grown in the last few years. With the advent of the fifth generation of wireless networks, and with millions of base stations and billions of connected devices, the need for spectral and energy-efficient system design will be more convincing. In this paper, the evolution of mobile communication networks starting from first-generation to the fifth generation with comparative studies are first introduced. Then, summarizing the recent research initiatives towards the next generation, 5G, evolution. The main requirements of 5G networks and emerging technologies are highlighted. Furthermore, an overview of several technologies that might be used to achieve the 5G requirements including Massive-MIMO, Millimetre-waves, beamforming, full-duplex, and Small-Cells are explained. Finally, a comparative analysis survey of Spectral Efficiency (SE) and Energy-Efficiency (EE) based Massive MIMO techniques is introduced as a key contribution of this review article. Good trade-off conditions between EE and SE technologies based on various algorithms are explained with comparative analysis.
Article
Purpose In recent years, multiuser-multiple-input multiple-output (MU-MIMO)-based wireless communication system has emerged as a prominent 5G technique that has several advantages over conventional MIMO systems such as high data rate and channel capacity. In this paper, the authors introduce a novel low-complexity radix factorization-based fast Fourier transform (FFT) as a multibeamformer and maximal likelihood-MU detection (ML-MUD) techniques as an optimal signal subdetector which results with considerable complexity reduction with intolerable error rate performance. Design/methodology/approach The proposed radix-factorized FFT-multibeamforming (RF-FFT-MBF) architectures have the potential to reduce both hardware complexity and energy consumptions as compared to its state-of-the-art methods while meeting the throughput requirements of emerging 5G devices. Here through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors. Findings Here through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors. Through experimental results, it is well proved that the proposed detector offers significant hardware and energy efficiency with the least possible error rate performance overhead. Originality/value Here through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors. Through experimental results, it is well proved that the proposed detector offers significant hardware and energy efficiency with the least possible error rate performance overhead.
Article
Systematic operations of Massive multiple-input multiple-output (MIMO) to increase the performance has been proposed. Even though there is no doubt that Massive MIMO is a key technology to increase both energy efficiency (EE) and spectral efficiency (SE), there are many parameters to determine in Massive MIMO systems, such as the number of operating service antennas, uplink and downlink radiation powers, and coverage distance. Since the communication environment changes rapidly, these parameters should be adaptively determined to increase the efficiency of the system. In this regard, we present a scheme of fast parameter determination based on the inverse of derived closed-form equations. Due to the channel hardening effect, the proposed method based on closed-form equations can be well applicable to real systems. We numerically analyze the proposed scheme in various situations to show the robustness in various environments. Downlink radiation power is divided by the number of user equipments (UEs), while uplink radiation powers from the distributed UEs are aggregated to the base station (BS). Within the same radiation power assumption, the downlink case requires more resources. When the number of UEs is much larger than the number of service antennas at BS, the increment of the radiation power for uplink and downlink little affect the performance. Simulation results are provided to validate the analytical results.
Article
Active research on MIMO systems and, in particular, on MIMO systems with automatic antenna selection has recently been carried out. The most effective antenna selection criteria require an enumeration of all possible antenna combinations. The criterion for the maximal throughput implies an algorithm using the Frobenius norm, which does not require an enumeration of all possible combinations of antennas. However, it leads to a significant deterioration in performance. In this paper, we propose an antenna selection algorithm using the criterion of the minimal trace of the correlation matrix (minimum mean square error, MMSE), which does not require an enumeration of all combinations of antennas and has small losses compared to complete enumeration.
Article
Purpose The suggested work examines the latest developments such as the techniques employed for allocation of power, browser techniques, modern analysis and bandwidth efficiency of nonorthogonal multiple accesses (NOMA) in the network of 5G. Furthermore, the proposed work also illustrates the performance of NOMA when it is combined with various techniques of wireless communication namely network coding, multiple-input multiple-output (MIMO), space-time coding, collective communications, as well as many more. In the case of the MIMO system, the proposed research work specifically deals with a less complex recursive linear minimum mean square error (LMMSE) multiuser detector along with NOMA (MIMO-NOMA); here the multiple-antenna base station (BS) and multiple single-antenna users interact with each other instantaneously. Although LMMSE is a linear detector with a low intricacy, it performs poorly in multiuser identification because of the incompatibility between LMMSE identification and multiuser decoding. Thus, to obtain a desirable iterative identification rate, the proposed research work presents matching constraints among the decoders and identifiers of MIMO-NOMA. Design/methodology/approach To improve the performance in 5G technologies as well as in cellular communication, the NOMA technique is employed and contemplated as one of the best methodologies for accessing radio. The above-stated technique offers several advantages such as enhanced spectrum performance in contrast to the high-capacity orthogonal multiple access (OMA) approach that is also known as orthogonal frequency division multiple access (OFDMA). Code and power domain are some of the categories of the NOMA technique. The suggested research work mainly concentrates on the technique of NOMA, which is based on the power domain. This approach correspondingly makes use of superposition coding (SC) as well as successive interference cancellation (SIC) at source and recipient. For the fifth-generation applications, the network-level, as well as user-experienced data rate prerequisites, are successfully illustrated by various researchers. Findings The suggested combined methodology such as MIMO-NOMA demonstrates a synchronized iterative LMMSE system that can accomplish the optimized efficiency of symmetric MIMO NOMA with several users. To transmit the information from sender to the receiver, hybrid methodologies are confined to 2 × 2 as well as 4 × 4 antenna arrays, and thereby parameters such as PAPR, BER, SNR are analyzed and efficiency for various modulation strategies such as BPSK and QAM j (j should vary from 8,16,32,64) are computed. Originality/value The proposed hybrid MIMO-NOMA methodologies are synchronized in terms of iterative process for optimization of LMMSE that can accomplish the optimized efficiency of symmetric for several users under different noisy conditions. From the obtained simulated results, it is found, there are 18%, 23% 16%, and 8% improvement in terms of Bit Error Rate (BER), Least Minimum Mean Squared Error (LMMSE), Peak to Average Power Ratio (PAPR), and capacity of channel respectively for Binary Phase Shift Key (BPSK) and Quadrature Amplitude Modulation (QAM) modulation techniques.
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Multiple-input Multiple-output (MIMO) technologies play an important role in modern and future wireless communication systems as they can improve the capacity without increasing the bandwidth. MIMO detection is one of the key technologies for MIMO system designs. MIMO detection schemes based on Message Passing (MP) algorithms have attracted extensive attention in recent years. The MIMO detection scheme based on Expectation Propagation (EP), which is also a kind of MP algorithms, has been proved to achieve the Bayes-optimal performance under the conditions of large system limit and compression rate threshold. However, there is improvement space for the detection performance of the EP algorithm when the conditions are not satisfied, which are the common cases in the practical applications. In this paper, when the conditions of the large system limit and compression rate threshold are not satisfied, we analyze the influences of two factors, the initial parameters selection and the moment matching strategy, on the performance of EP based detection scheme. As a result, we propose an improved EP detection scheme based on optimizing the two factors. Simulation results show that the proposed scheme outperforms the original EP detection scheme in different MIMO scenarios.
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With the explosive growth of mobile data demand, the fifth generation (5G) mobile network would exploit the enormous amount of spectrum in the millimeter wave (mmWave) bands to greatly increase communication capacity. There are fundamental differences between mmWave communications and existing other communication systems, in terms of high propagation loss, directivity, and sensitivity to blockage. These characteristics of mmWave communications pose several challenges to fully exploit the potential of mmWave communications, including integrated circuits and system design, interference management, spatial reuse, anti-blockage, and dynamics control. To address these challenges, we carry out a survey of existing solutions and standards, and propose design guidelines in architectures and protocols for mmWave communications. We also discuss the potential applications of mmWave communications in the 5G network, including the small cell access, the cellular access, and the wireless backhaul. Finally, we discuss relevant open research issues including the new physical layer technology, software-defined network architecture, measurements of network state information, efficient control mechanisms, and heterogeneous networking, which should be further investigated to facilitate the deployment of mmWave communication systems in the future 5G networks.
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Assume that a multi-user multiple-input multiple-output (MIMO) system is designed from scratch to uniformly cover a given area with maximal energy efficiency (EE). What are the optimal number of antennas, active users, and transmit power? The aim of this paper is to answer this fundamental question. We consider jointly the uplink and downlink with different processing schemes at the base station and propose a new realistic power consumption model that reveals how the above parameters affect the EE. Closed-form expressions for the EE-optimal value of each parameter, when the other two are fixed, are provided for zero-forcing (ZF) processing in single-cell scenarios. These expressions prove how the parameters interact. For example, in sharp contrast to common belief, the transmit power is found to increase (not to decrease) with the number of antennas. This implies that energy-efficient systems can operate in high signal-to-noise ratio regimes in which interference-suppressing signal processing is mandatory. Numerical and analytical results show that the maximal EE is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve a relatively large number of users using ZF processing. The numerical results show the same behavior under imperfect channel state information and in symmetric multi-cell scenarios.
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Massive MIMO systems are well-suited for mm-wave communications, as large arrays can be built with reasonable form factors, and the high array gains enable reasonable coverage even for outdoor communications. One of the main obstacles for using such systems in frequency-division duplex mode, namely the high overhead for the feedback of channel state information (CSI) to the transmitter, can be mitigated by the recently proposed JSDM (Joint Spatial Division and Multiplexing) algorithm. In this paper we analyze the performance of this algorithm in {\em realistic} propagation channels that take into account the partial overlap of the angular spectra from different users, as well as the sparsity of mm-wave channels. We formulate the problem of user grouping for two different objectives, namely maximizing spatial multiplexing, and maximizing total received power, in a graph-theoretic framework. As the resulting problems are numerically difficult, we proposed (sub optimum) greedy algorithms as efficient solution methods. Numerical examples show that the different algorithms may be superior in different settings. We furthermore develop a new, ``degenerate'' version of JSDM that only requires average CSI at the transmitter, and thus greatly reduces the computational burden. Evaluations in propagation channels obtained from ray tracing results, as well as in {\em measured} outdoor channels show that this low-complexity version performs surprisingly well in mm-wave channels.
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In this letter, we consider a large-scale multiple-input multiple-output (MIMO) system where the receiver should harvest energy from the transmitter by wireless power transfer to support its wireless information transmission. The energy beamforming in the large-scale MIMO system is utilized to address the challenging problem of long-distance wireless power transfer. Furthermore, considering the limitation of the power in such a system, this letter focuses on the maximization of the energy efficiency of information transmission (bit per Joule) while satisfying the quality-of-service (QoS) requirement, i.e. delay constraint, by jointly optimizing transfer duration and transmit power. By solving the optimization problem, we derive an energy-efficient resource allocation scheme. Numerical results validate the effectiveness of the proposed scheme.
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We consider a heterogeneous cellular network (HetNet) where a macrocell tier with a large antenna array base station (BS) is overlaid with a dense tier of small cells (SCs). We investigate the potential benefits of incorporating a massive MIMO BS in a TDD-based HetNet and we provide analytical expressions for the coverage probability and the area spectral efficiency using stochastic geometry. The duplexing mode in which SCs should operate during uplink macrocell transmissions is optimized. Furthermore, we consider a reverse TDD scheme, in which the massive MIMO BS can estimate the SC interference covariance matrix. Our results suggest that significant throughput improvement can be achieved by exploiting interference nulling and implicit coordination across the tiers due to flexible and asymmetric TDD operation.
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To improve the cellular energy efficiency, without sacrificing quality-of-service (QoS) at the users, the network topology must be densified to enable higher spatial reuse. We analyze a combination of two densification approaches, namely "massive" multiple-input multiple-output (MIMO) base stations and small-cell access points. If the latter are operator-deployed, a spatial soft-cell approach can be taken where the multiple transmitters serve the users by joint non-coherent multiflow beamforming. We minimize the total power consumption (both dynamic emitted power and static hardware power) while satisfying QoS constraints. This problem is proved to have a hidden convexity that enables efficient solution algorithms. Interestingly, the optimal solution promotes exclusive assignment of users to transmitters. Furthermore, we provide promising simulation results showing how the total power consumption can be greatly improved by combining massive MIMO and small cells; this is possible with both optimal and low-complexity beamforming.
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Mobile data traffic is predicted to grow exponentially in the future. To address the challenge and consider the form factor limitation at the base station, 3D millimeter wave massive MIMO has been introduced as an enabling technology for 5G systems. In 3D millimeter wave massive MIMO systems, due to the large number of antennas and limited number of clusters, a base station will mainly rely on the uplink sounding signals instead of the feedback to figure out the channel knowledge to perform 3D MIMO operation. Accordingly, multi-dimensional channel estimation becomes critical for such systems to realize the predicted rate gains. In this paper, the performance of direction of arrival (DoA) estimation at the base station using ESPRIT method is characterized. The DoA estimation is further related to the underlying 3D MIMO achievable rate and the optimal transmission strategy is characterized. Finally, the impact of channel estimation error on the underlying achievable rate is analyzed. Our results suggest that DoA estimation is crucial for the transmit beam-forming of 3D millimeter wave massive MIMO systems. Furthermore, the optimal transmission strategy depends heavily on the performance of the underlying DoA estimation.
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Wireless information and energy transfer (WIET) is a prominent technology to prolong the lifetime of battery-charging wireless networks. In this paper, we exploit the benefit of massive MIMO for WIET under external interference, and propose the antenna partition for information decoding and energy harvesting. Considering the effects of the external interference, i.e., interfering the information reception and benefiting the energy harvesting, we analyze the tradeoff between the data rate and the harvested energy, and obtain the achievable rate-energy (R-E) region. Then, we propose a low-complexity receive antenna partition algorithm for WIET in massive MIMO systems with the consideration of interference mitigation. The algorithm maximizes the data rate while guaranteeing a minimum harvested energy. It is found that the SNR of the low-complexity algorithm is at least an approximable half of the optimal SNR. Simulation results verify our theoretical claims and show the effectiveness of the proposed low-complexity antenna partition algorithm.
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Massive MIMO, also known as very-large MIMO or large-scale antenna systems, is a new technique that potentially can offer large network capacities in multi-user scenarios. With a massive MIMO system, we consider the case where a base station equipped with a large number of antenna elements simultaneously serves multiple single-antenna users in the same time-frequency resource. So far, investigations are mostly based on theoretical channels with independent and identically distributed (i.i.d.) complex Gaussian coefficients, i.e., i.i.d. Rayleigh channels. Here, we investigate how massive MIMO performs in channels measured in real propagation environments. Channel measurements were performed at 2.6 GHz using a virtual uniform linear array (ULA), which has a physically large aperture, and a practical uniform cylindrical array (UCA), which is more compact in size, both having 128 antenna ports. Based on measurement data, we illustrate channel behavior of massive MIMO in three representative propagation conditions, and evaluate the corresponding performance. The investigation shows that the measured channels, for both array types, allow us to achieve performance close to that in i.i.d. Rayleigh channels. It is concluded that in real propagation environments we have characteristics that can allow for efficient use of massive MIMO, i.e., the theoretical advantages of this new technology can also be harvested in real channels.
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The combination of energy harvesting and large-scale multiple antenna technologies provides a promising solution for improving the energy efficiency (EE) by exploiting renewable energy sources and reducing the transmission power per user and per antenna. However, the introduction of energy harvesting capabilities into large-scale multiple antenna systems poses many new challenges for energy-efficient system design due to the intermittent characteristics of renewable energy sources and limited battery capacity. Furthermore, the total manufacture cost and the sum power of a large number of radio frequency (RF) chains can not be ignored, and it would be impractical to use all the antennas for transmission. In this paper, we propose an energy-efficient antenna selection and power allocation algorithm to maximize the EE subject to the constraint of user's quality of service (QoS). An iterative offline optimization algorithm is proposed to solve the non-convex EE optimization problem by exploiting the properties of nonlinear fractional programming. The relationships among maximum EE, selected antenna number, battery capacity, and EE-SE tradeoff are analyzed and verified through computer simulations.
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In this paper, we present a vision beyond the conventional Long Term Evolution Fourth Generation (LTE-4G) evolution path and suggest that time division duplexing (TDD) could be a key enabler for a new heterogeneous network architecture with the potential to provide ubiquitous coverage and unprecedented spectral area efficiencies. This architecture is based on a co-channel deployment of macro base stations (BSs) with very large antenna arrays and a secondary tier of small cells (SCs) with a few antennas each. Both tiers employ a TDD protocol in a synchronized fashion. The resulting channel reciprocity enables not only the estimation of large-dimensional channels at the BSs, but also an implicit coordination between both tiers without the need to exchange user data or channel state information (CSI) over the backhaul. In particular, during the uplink (UL), the BSs and SCs can locally estimate the dominant interference sub-space. This knowledge can be leveraged for downlink (DL) precoding to reduce intra- and inter-tier interference. In other words, the BSs and SCs “sacrifice” some of their degrees of freedom for interference rejection. Our simulation results demonstrate that the proposed architecture and precoding scheme can achieve a very attractive rate region compared to several baseline scenarios. For example, with 100 antennas at each BS and four antennas at each SC, we observe an aggregate area throughput of 7.63 Gb/s/km2 (DL) and 8.93 Gb/s/km2 (UL) on a 20 MHz band shared by about 100 mobile devices.
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A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval. Time-division duplex operation combined with reverse-link pilots enables the base station to estimate the reciprocal forward- and reverse-link channels. The conjugate-transpose of the channel estimates are used as a linear precoder and combiner respectively on the forward and reverse links. Propagation, unknown to both terminals and base station, comprises fast fading, log-normal shadow fading, and geometric attenuation. In the limit of an infinite number of antennas a complete multi-cellular analysis, which accounts for inter-cellular interference and the overhead and errors associated with channel-state information, yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve. In particular the effects of uncorrelated noise and fast fading vanish, throughput and the number of terminals are independent of the size of the cells, spectral efficiency is independent of bandwidth, and the required transmitted energy per bit vanishes. The only remaining impairment is inter-cellular interference caused by re-use of the pilot sequences in other cells (pilot contamination) which does not vanish with unlimited number of antennas.
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In this paper we introduce a new perspective to the implementation of wireless MIMO transmission systems with increased bandwidth efficiency. Unlike traditional spatial multiplexing techniques in MIMO systems, where additional information can be sent through the wireless channel by feeding uncorrelated antenna elements with diverse bitstreams, we use the idea of mapping diverse bitstreams onto orthogonal bases defined in the beamspace domain of the transmitting array far-field region. Using this approach we show that we can increase the capacity of wireless communication systems using compact parasitic antenna architectures and a single RF front end at the transmitter, thus paving the way for integrating MIMO systems in cost and size sensitive wireless devices such as mobile terminals and mobile personal digital assistants.
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We provide an overview of the extensive results on the Shannon capacity of single-user and multiuser multiple-input multiple-output (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about the underlying time-varying channel model and how well it can be tracked at the receiver, as well as at the transmitter. More realistic assumptions can dramatically impact the potential capacity gains of MIMO techniques. For time-varying MIMO channels there are multiple Shannon theoretic capacity definitions and, for each definition, different correlation models and channel information assumptions that we consider. We first provide a comprehensive summary of ergodic and capacity versus outage results for single-user MIMO channels. These results indicate that the capacity gain obtained from multiple antennas heavily depends on the available channel information at either the receiver or transmitter, the channel signal-to-noise ratio, and the correlation between the channel gains on each antenna element. We then focus attention on the capacity region of the multiple-access channels (MACs) and the largest known achievable rate region for the broadcast channel. In contrast to single-user MIMO channels, capacity results for these multiuser MIMO channels are quite difficult to obtain, even for constant channels. We summarize results for the MIMO broadcast and MAC for channels that are either constant or fading with perfect instantaneous knowledge of the antenna gains at both transmitter(s) and receiver(s). We show that the capacity region of the MIMO multiple access and the largest known achievable rate region (called the dirty-paper region) for the MIMO broadcast channel are intimately related via a duality transformation. This transformation facilitates finding the transmission strategies that achieve a point on the boundary of the MIMO MAC capacity region in terms of the transmission strategies of the MIMO broadcast dirty-paper region and vice-versa. Finally, we discuss capacity results for multicell MIMO channels with base station cooperation. The base stations then act as a spatially diverse antenna array and transmission strategies that exploit this structure exhibit signifi- cant capacity gains. This section also provides a brief discussion of system level issues associated with MIMO cellular. Open problems in this field abound and are discussed throughout the paper.
Ericsson Energy and Carbon Report
  • Ericsson
Ericsson, "Ericsson Energy and Carbon Report," Technical Report, November 2014.
Energy-efficient antenna selection and power allocation for large-scale multiple antenna systems with hybrid energy supply
  • Z Zhou
  • S Zhou
  • J Gong
Z. Zhou, S. Zhou, J. Gong, et. al., "Energy-efficient antenna selection and power allocation for large-scale multiple antenna systems with hybrid energy supply," in 2014 IEEE Global Communications Conference (GLOBECOM), pp. 2574-2579, 8-12 Dec. 2014.
Wireless information and energy transfer in interference aware massive MIMO systems
  • H Wang
  • W Wang
  • X Chen
H. Wang, W. Wang, X. Chen, et. al., "Wireless information and energy transfer in interference aware massive MIMO systems," in 2014 IEEE Global Communications Conference, pp. 2556-2561, 8-12 Dec. 2014.