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Sleep mode management in cellular networks: A traffic based technique enabling energy saving
Abstract
Because of the environmental policies that pursue a significant reduction of global greenhouse gas and to the ambition of the network operators to keep under control operational and maintenance expenditures, energy efficiency has recently become one of the most relevant issues for present and future research activities. This contribution deals with the management of the base station sleep mode in a cellular network. The forecasting based sleep mode algorithm, justified by daily and weekly periodic behaviour of traffic, is presented and evaluated for general deployments of second and third generation cellular networks. The energy consumption of each base station and the area power consumption are the metrics, which are considered for our simulations. The results show a significant increase of the energy efficiency during low traffic periods with respect to the usual scenario, thanks to the adoption of the proposed strategy. The forecasting based sleep mode algorithm has been also compared with a strategy based on real-time measurements and the results show similar performances while the number of updates of the network configuration and the global complexity are decreased. Copyright © 2013 John Wiley & Sons, Ltd.
... Another study has analyzed the strategy for the reduction of unnecessary use of energy consumption of base transceiver stations by using Monte Carlo simulation method for experimental data collected [19]. For the green radio techniques, two adaptive algorithms, which are based on traffic forecast and real-time measurements, are compared with the goal of optimal radio resource management [20]. In addition, these techniques track the traffic behavior and end up reducing the number of active power amplifiers during the day by shutting down the carriers which are not needed. ...
... High energy saving and easier to implement Quality degrade during BSs on/off and interference Dynamic Transmitter Shut Down Techniques [19], [20] Selected TRX shut down and no handover adjustment Load balancing Compromise in quality due to uncertainty issues Radio Resource Management [21], [22] Resource allocation for signalling and channel Low cost to implement Trade-off between performance and resource. ...
... The power consumption was observed on the BS after all TRX of one PA were shut down. Although [20] had proposed an approximation but a more realistic modification considering TRX shut down duration, cell availability and channel availability is proposed. ...
Due to the increasing demand of wireless communication, the number of radio base stations has been growing excessively. The wireless network is designed for maximum traffic load, but the traffic load is unevenly distributed resulting in wastage of energy consumption
most of the time during low traffic. Traditional energy saving techniques like switching off certain BSs completely during low traffic creates problems in restoring to optimum capacity when traffic increases. There is the potential of saving energy consumption along with maintaining the quality of service and resulting environmental impact by introducing dynamic transmitter shutdown technique.
In this paper, an algorithm of dynamic transmitter shut down techniques during low traffic is proposed. The algorithm depends on automatically switching off unnecessary transmitter when the traffic is low and switching on the required transmitter when the traffic starts to
increase. With this technique, base stations dynamically adjust the number of transmitters to be enabled based on the user traffic and required channels without compromising the service quality. The measured results revealed that the proposed model reduces the energy consumption of base stations by up to 18.8 % as compared with the traditional static BSs, which is a step forward towards the implementation of green wireless communication.
... However, they do not consider coverage and interference control from user perspectives. Additionally, methods in [11,12] mainly discuss BS sleep gains from the point of traffic prediction 2 Mobile Information Systems and BS power mode analysis. But coverage compensation methods and interference control methods for sleep BS are theoretical. ...
... Here traffic is taken as the load factor in (4). There are many traffic prediction methods which have been used in BS sleep methods, such as Holt-Winters in [11] and online stochastic game theoretic algorithm in [20]. But they are not suitable for traffic with small value and the accuracy can be improved. ...
... In ( Moreover, and are differential order and seasonal differential order, respectively. Then we call the model in (11) S-ARIMA( , , ) × ( , , ) model with season . ...
Aiming at the lack of integrated energy-saving (ES) methods based on hybrid energy supplies in LTE heterogeneous networks, a novel ES management mechanism considering hybrid energy supplies and self-organized network (SON) is proposed. The mechanism firstly constructs ES optimization model with hybrid energy supplies. And then a SON framework is proposed to resolve the model under practical networks. According to the framework, we divide the ES problem into four stages, which are traffic variation prediction, regional Base Station (BS) mode determination, BS-user association, and power supply. And four corresponding low-complexity algorithms are proposed to resolve them. Simulations are taken on under LTE underlay heterogeneous networks. Compared with other algorithms, results show that our mechanism can save 47.4% energy consumption of the network, while keeping coverage, interference, and service quality above acceptable levels, which takes on great green-economy significance.
... In order to improve the energy efficiency (EE), the consumed power in the base station (BS) should scale as close as possible to the amount of traffic load served, which can in principle be accomplished by using more efficient and traffic load adaptive hardware equipments and software modules [3,4]. Taking advantage of cooperative communication [5], the EE of cellular networks can be improved by reducing the number of active BSs required in an area by adapting the network layout according to mobile users' traffic demands [6][7][8]. The work in [8] offers one of the earliest insights on load-adaptive operation where the authors propose the usage of cell zooming. ...
... The proposed scheme maintains the coverage and reduces the number of active cells by changing the coverage pattern of cells based on traffic load and hence offering potential power consumption reduction. In [7], the overall power consumption of a telecommunication network is estimated through analysing the power requirements of network equipment and the amount of traffic received from the users. The authors claim that future networks with sleep mode and load adaptation enabled will save a consistent amount of energy. ...
... As observed in the earlier results, the HetNet experiences poor EE when they are operating under low traffic load conditions. It can be shown that EE curves degrade in the early morning hours (3)(4)(5)(6)(7)(8) excluding these with fully load adaptive operation mode. When the traffic load is the lowest (around 6:30 AM), it can be seen that the EE increased from 1140 (bits/joule) with conventional operation to 8385 (bits/joule) for fully adaptive operation which is equivalent to more than 86% improvement in network EE performance. ...
One of the main approaches for improving the network energy efficiency (EE) is through the introduction of load adaptive techniques, where the network's components/subsystems are switched off when the network is lightly loaded. Optimising such a dynamic operation in a heterogeneous network (HetNet) remains an active topic of research. In this paper, a traffic load-adaptive model that aims to evaluate the EE of base stations in Long Term Evolution (LTE) HetNet is presented. First, a model that simulates the load-adaptive power consumption behaviour of LTE HetNet is developed. In this regard, a load adaptation factor is introduced to assess the network's EE performance. The model also adapts and predicts the achievable data rate of each base station with respect to the traffic load. Our study shows that the fully load-adaptive LTE HetNet can significantly improve network's EE up to 10%, 40%, and 80% for high, medium, and low loads, respectively, as compared to the conventional non load-adaptive HetNet. In addition, we show that the full adaptive network operation can achieve significant EE gains under a realistic daily traffic profile up to 86%. The proposed evaluation model is essential to assess the network EE and can be used in future studies that focus on improving the adaptation level of the already installed network equipments. Copyright © 2014 John Wiley & Sons, Ltd.
... The aptness of forecast for cellular traffic has been already considered in [21] and [22] and its applicability at energy efficiency maximisation has been previously used to introduce cell sleep mode. In particular in [23] authors apply compressed sensing technique while in [24] and [25] the exponential smoothing technique is evaluated. In both cases, in order to save energy, some radio resources are switched to the sleep mode when a low traffic is foreseen. ...
... In this paper, the exponential smoothing technique is applied to traffic forecast in a given area, also by considering daily and weekly variations: as a consequence, the maximum base station transmission power is managed even if the requested network capacity is guaranteed. This power saving strategy can be considered as an improvement of the strategy proposed in [24] and [25]. Whereas previous contributions focused on the traffic forecast which allows the sleep mode at carrier or cell level, in this work the prediction enables base station transmission power adaptation with time varying quality of service constraints. ...
... Results show that this technique make the network power consumptions related to the effective requests of traffic with performance very close to the optimum case. The proposed strategy could be easily applied jointly with specific solutions for micro cells BTS [24] and [25]: while at micro cell level the forecast enables base station sleep mode, at macro cell one the energy saving is obtained by the solution proposed in this paper. ...
Nowadays, the pursuit of energy efficiency is one of the main challenges of present and future mobile communications. The growth of the mobile communication market which has been increased by the proliferation of smartphones and laptops and the rising of data traffic subscriptions claims for an improvement of network capacity and, consequently, of the infrastructure. In this scenario, in order to contain operative expenditures, the network operators must pay attention to energy saving strategies that may eventually also contribute to reduction of greenhouse emissions. In this paper, the exponential smoothing technique is applied to achieve a traffic forecast for all the coverage area, considering daily and weekly data communication trends: in particular, the base station transmission power can be adapted in order to save energy and guarantee the requested network capacity. Results show the effectiveness of traffic forecast technique for the prediction of the requested capacity and for the maximization of the energy efficiency, allowing performance very close to the optimum case.
... A given service rate is guaranteed to mobile terminals and the cost of rearranging the network when traffic demand changes is taken into account by optimizing the actual number of BS switchings, defined as the number of active/inactive state transitions in a twenty-four hour period. As highlighted in [9], the forecast approach requires a lower number of switch on/off operations with respect to the procedure which is based on instantaneous traffic measurements; as a result, the control traffic and handover operations are also reduced. This work extends the results presented in [10] by considering a multiobjective optimization framework, designed to inspect the network sleep mode operation cost over a daily pattern of traffic demands. ...
... end for 7: until convergence 8: Update π ij as in Eqn. (9) ∀i ∈ B ∀j ∈ U 9: Update P i to the maximum allowed value ∀i ∈ B ...
... We use the Vienna LTE-A [37] to build the whole simulation platform. We set the related parameters of this simulation Table 1, according to the model of energy consumption mentioned in [38,39]. Reference [38] is derived from the data of [39]. ...
... We set the related parameters of this simulation Table 1, according to the model of energy consumption mentioned in [38,39]. Reference [38] is derived from the data of [39]. ...
As the current network is designed for peak loads, it results in insufficient resource utilization and energy waste. Virtualized technology makes it possible that intelligent energy perception network could be deployed and resource sharing could become an effective energy saving technology. How to make more small cells into sleeping state for energy saving in ultradense small cell system has become a research hot spot. Based on the mapping feature of virtualized network, a new wireless resource mapping algorithm for saving energy in ultradense small cells has been put forward when wireless resource amount is satisfied in every small cell. First of all, the method divides the virtual cells. Again through the alternate updating between small cell mapping and wireless resource allocation, least amount of small cells is used and other small cells turn into sleeping state on the premise of guaranteeing users’ QoS. Next, the energy consumption of the wireless access system, wireless resource utilization, and the convergence of the proposed algorithm are analyzed in theory. Finally, the simulation results demonstrate that the algorithm can effectively reduce the system energy consumption and required wireless resource amount under the condition of satisfying users’ QoS.
... In [16] an energy saving strategy combining these aspects is proposed in a scenario with macro and micro base stations: besides, the joint strategy is driven by the use of a traffic forecast. The use of the forecast for energy efficiency maximisation has been already considered in [17] and [18]. As highlighted in [18], the forecast approach requires a lower number of switch on/off operations with respect to the procedure based on istantaneous traffic measurements; as a result, the signaling traffic and handover operations are also reduced. ...
... The use of the forecast for energy efficiency maximisation has been already considered in [17] and [18]. As highlighted in [18], the forecast approach requires a lower number of switch on/off operations with respect to the procedure based on istantaneous traffic measurements; as a result, the signaling traffic and handover operations are also reduced. Since the implementation of an energy saving strategy should not introduce any significant decreasing in the network and system performance, this work extends the results presented in [16] by introducing a detailed evaluation of the users' quality of service (QoS) based on simulations done by a discrete event simulator (NS-3 1 ). ...
The objective of increasing the Energy Efficiency of communication systems must cope with a sustained growth of the market, a greater penetration of broadband services in everyday life, higher data rate services and a large increase of the number of mobile subscriptions. In this scenario, a particular attention has to be devoted to energy saving strategies that may also contribute to the reduction of greenhouse gas emissions. The goal of an effective energy saving strategy is to reduce the power consumption without introducing any significant decrease in the network and system performance. In this paper we present the complete performance evaluation of a previously proposed strategy: particularly, the considered joint Radio Resource Management (RRM) strategy is based on the use of the cell sleep mode and the reduction of the maximum transmission power at the base station; the exponential smoothing technique is applied to forecast traffic in a given area considering daily and weekly variations. A detailed evaluation of system performance is done with reference to the no energy saving case. Results show the effectiveness of the propose strategy in heterogeneous networks (Het-Nets) where cells of different sizes effectively coexist.
... The key of this strategy is the use of traffic forecast in order to allow the base stations to know the traffic behaviour in their coverage area. The aptness of forecast for cellular traffic has been already considered in [22] and [23]; moreover, its application in the energy efficiency maximisation has been used to introduce cell sleep mode: in particular in [24] authors apply compressed sensing technique while in [25] and [26] the exponential smoothing technique is evaluated. In both cases when forecasted traffic is low some radio resources are switched to the sleep mode to save energy. ...
... With respect to these previous works, the strategy proposed in this paper can be considered an improvement which use the traffic prevision to jointly introduce sleep mode at micro cell level and adapting the maximum transmission power at macro cell level. As highlighted in [26], the forecast approach requires a lower number of switch on/off operations with respect to the procedure which is based on istantaneous traffic measurements; as a result, the control traffic and handover operations are also reduced. ...
Energy efficiency is one of the main challenges to be faced by mobile communications in the near future. The growth of the mobile communications market which is boosted by the increasing penetration of smartphones and laptops requires an increase of the network capacity and, consequently, a great leap forward also for the infrastructures. In this scenario, in order to reduce the operative expenditures, the network operators pay attention to energy saving strategies that may also contribute to the reduction of greenhouse emissions. In this paper the exponential smoothing technique is applied to forecast traffic in a given area considering daily and weekly variations. The availability of a reliable prediction of the future traffic values allows the adaptation of macro base station transmission power and the introduction of a sleep mode for micro base stations and permits to guarantee the requested network capacity while saving energy consumption. Results show the effectiveness of traffic forecast technique for capacity prediction and the usefulness of the proposed algorithms for energy efficiency maximization, affording very good performance, very close to the optimum one.
... Sleep mode techniques for base stations reduce energy consumption by deactivating unused components during low traffic and reactivating them as traffic increases. In [17], a "sleep mode" solution was proposed for reducing energy consumption at radio sites based on daily traffic predictions for 2G Voice (GSM) and 3G Data (HSPA). The Holt-Winters model was used to forecast 2G Voice traffic (in erlangs) and 3G Data traffic (in Mbps). ...
... In the past, fixed relay-based [2][3][4][5] system models are studied and suggested for reliable communication. In the past, LTE-based several types of research have been proposed for railway communication [6][7][8], which uses the moving relay [9][10][11][12][13][14][15]. HD moving relay-based HetNet models for downlink [16,17] and uplink [18,19] have been studied recently. ...
In vehicular communication, high mobility causes frequent signal variation, which results in frequent handover and poor quality of service for vehicular users. Installing a relay on the top of the vehicle is a promising technology for overcoming these issues because these relays compensate the Vehicle Penetration Loss. Also, due to the deployment of next-generation networks and low-power nodes, network density and heterogeneity are increasing. As a result, interference is also increasing. Therefore, in the past, the performance of cooperative user in vehicular scenarios was analyzed using an amplify-and-forward (AF) mode based half-duplex (HD) relay in a heterogeneous network (HetNet). But the performance of HD relay is limited due to transmission capacity and bandwidth efficiency. In this paper, we use the AF mode based full-duplex (FD) relay in HetNet to analyze the performance of cooperative user in terms of coverage probability and outage capacity and, we compare the results with the AF mode based HD relay in vehicular scenario. Simulation results show that the performance of the FD relay depends on residual self-interference (RSI) in HetNet, and it outperforms the HD relay for the low value of RSI. The results are analyzed using both the analytical method and Monte Carlo simulation. These results provide the theoretical support for the deployment of relays in next-generation networks with high mobility scenario.
... Similarly, when the estimated traffic load is higher than the threshold traffic (N Th ) than switched off BSs must be switched on so that they are available as per the proposed algorithm. Although [50] had proposed an approximation but a more realistic approach by considering shut down duration, cell availability and channel availability is proposed. ...
Cell zooming has emerged as a potential energy optimization avenue towards the implementation of 5G mobile communication. The voice and data traffic of mobile communication is low most of the timeresulting in the wastage of energy consumption. Static cell zooming techniques created the restoring problems to optimum capacity when traffic suddenly increased. There is the potential of optimizing the energy consumption through dynamic cell zooming technique without compromising in the quality of service.
This paper proposes a traffic-driven cell zooming technique, where the coverage area of Base Stations can expand and contract as per the traffic volume. This is done by switching-off BSs having low traffic and compensating the coverage loss by expanding the neighbouring BSs coverage through increasing transmits power. The developed algorithm firstly adjuststhe number of BSs to be enabled or disabled dynamically as per the traffic volume, secondly it determines how much transmit power of enabled BSs should be increased in order to cover the coverage area of disabled BSs and lastly guarantee the quality of service. The measured results of the proposed algorithm show that the power consumption can be reduced up to 20 % as compared with the static cell zooming.
... The strategy for the reduction of unnecessary usage of energy consumption of base transceiver stations is analysed by using Monte Carlo simulation method for experimental data collected [20]. The two adaptive algorithms which are based on traffic forecast and real time measurements are compared with the goal optimal radio resource management [21]. An energy-efficient cell breathing and offloading mechanism in both macro cellular and heterogeneous networks has shown a combined approach in a single framework for macro/femto environment [22]. ...
To meet the subscribers ever increasing traffic demand, micro and macro base stations are being deployed excessively. As the traffic pattern varies according to the user's behavior, the deployment of micro and macro base stations plays a vital role in saving energy while maintaining the traffic demand of the subscribers. A macro base station consumes more than double the energy than a micro base station. Due to the space and time characteristics of the traffic, the BS cannot allocate resources effectively, which results in wasting energy consumption and low energy efficiency. Therefore, energy saving through deployment of base stations play a significant role to increase the energy efficiency. In this paper, the user traffic pattern is determined and the resources needed to fulfill the traffic are analyzed and finally the deployment strategies for the base stations are formulated. Since the base stations are fully loaded only for few hours a day, energy saving on the stations during low traffic will be significant. The energy saving schemes saved up to 18.8 % of energy in macro and 26.9 % of energy in micro BS. So, it would be more efficient to implement a heterogeneous network with more micro cells with energy saving schemes than just macro base stations.
... In the recent years, several types of research are going on the railway communication. Conventional Global System for Mobile Communications (GSM) is adapted for the railway-specific application which is termed as the GSM-R [3]. But it becomes successful only for voice communication in the high-speed railway (HSR) not for data service. ...
The demand for wireless communication has widely increased in high-speed railway (HSR). The people demand high capacity and efficient communication independent of their location and speed. As the HSR provides more convenience to people, so the main attention is given to provide the reliable communication inside the train. It is the challenging task due to the high mobility of train and frequent need of handoff. To reduce the number of handoffs, the modified Hata model has been used in this paper. The performance of system is evaluated in terms of outage probability, coverage probability, transmission capacity and number of base stations. Results show improvement in coverage probability, transmission capacity and reduction in the outage probability and number of base stations. Hence, the cost of communication for high mobility vehicles can be reduced by decreasing the number of base stations.
... In the recent years, several types of research are going on the railway communication [3]. Conventional Global System for Mobile Communications (GSM) is adapted for the railway-specific application which is termed as the GSM-R [4]. But it is successful only for voice communication in the high-speed railway (HSR) not for data service. ...
The high speed railway (HSR) provides more convenience to people, so the main attention is given to provide the reliable communication inside the train. It is the challenging task due to the high mobility of train and frequent need of handoff to each communicating users. In this paper, the individual handoff problem is solved by group handoff by using moving relays (MR) through cooperative communication. The system model for non-cooperative and cooperative communication in multi-tier heterogeneous network is proposed. Two different scenario for HSR communication i.e. without MR or direct communication and with MR, are discussed. Moreover, effect of interference, noise signal and power control factor are also considered in this paper. The performance of system model is analyzed by handoff probability, outage probability, coverage probability and transmission capacity. The results show that the outage probability and handoff probability decreases and coverage probability and transmission capacity increases as the number of MR increases due to cooperative communication. The analytical results are also verified by the Monte-Carlo simulation.
... Temporal prediction is aiming at predicting future variation direction based on past and [20] or S-ARIMA model [21] to construct prediction sequences, which will be useful for abnormal traffic recognition. Moreover, joint temporalspatial predication approaches deserve more attention as well. ...
An attractive architecture called heterogeneous cloud radio access networks (H-CRAN) becomes one of the important components of 5G networks, which can provide ubiquitous high-bandwidth services with flexible network construction. However, massive access nodes increase the risk of cell outages, leading to negative impact on user-perceived QoS (Quality of Service) and QoE (Quality of Experience). Thus, cell outage management (COM) became a key function proposed in SON (Self-Organized Networks) use cases. Based on COM, cell outage detection (COD) will be resolved before cell outage compensation (COC). Currently few studies concentrate on COD for 5G H-CRAN, and we propose self-organized COD architecture and approach for it. We firstly summarize current COD solutions for LTE/LTE-A HetNets and then introduce self-organized architecture and approach suitable for H-CRAN, which includes COD architecture and procedures, and corresponding key technologies for it. Based on the architecture, we take a use case with handover data analysis using modified LOF (Local Outlier Factor) detection approach to detect outage for different kinds of cells in H-CRAN. Results show that the proposed approach can identify the outage cell effectively.
... Dalam sebuah penelitian lain yang dilakukan pada heterogeneous deployment dengan studi kasus sebagian area pada kota Munich, Jerman dengan sleep-mode juga didapatkan nilai efisiensi energi hingga 90% pada akhir pekan di area bisnis dan perkantoran, dan 30%-40% pada kasus yang lain [9]. Beberapa paper lain [10][11] juga mendapatkan nilai efisiensi energi antara 20%-40% dengan menggunakan pendekatan cell zooming dan 26%-39% dengan pendekatan traffict prediction [12]. ...
Penggunaan Teknologi Komunikasi pada dekade ini menunjukkan peningkatan trafik data yang sangat signifikan. Dalam hal ini, operator jaringan seluler melakukan inovasi untuk mengurangi jumlah penggunaan energi yang ditimbulkan dari banyaknya jumlah energi yang digunakan tanpa mengurangi quality of service (QoS) kepada costumer. Tujuan pemanfaatan penggunaan energi ini supaya operator jaringan lebih efisiendan tidak mengurangi tingkat efektifitas dalam pemakaian energi yang dikeluarkan. Paper ini menjelaskan mengenai pemakaian jaringan dengan teknologi teknik Base-Station Sleep-Mode. Metode ini akan menjalankan auto controluntuk menjalankan fungsinya pada pemancar jaringan, sehingga dibutuhkan sebuah pendekatan untuk memproses dengan menggunakan parameter-parameter yang dibutuhkan diantaranya User Association, SON (Self-Organizing Network), Cell Zooming, Traffic Prediction, dan Heterogenous Deployment. Salah satu hasil penelitian dari BS Sleeping mode menunjukkan hasil yaitu didapatkan nilai efisiensi energi hingga 90% pada akhir pekan di area bisnis dan perkantoran, dan 30-40%.
... In [16], the authors present adaptive algorithms for radio resource management based on traffic forecast in green cellular network. A sleep mode and traffic-based radio resource management scheme for cellular network is investigated in [17]. ...
With global concern for climate change, and for cutting down the energy cost, especially in off grid areas, use of renewable energy has been gaining widespread attention in many areas including cellular communication. The base station (BS) has emerged as a strong candidate for the integration of renewable energy sources (RES), particularly solar and wind. The incorporation of renewable energy opens many possibilities for energy conservation through strategies such as energy cooperation between BSs during the off-peak hours, when the energy harvested from renewable energy sources may become surplus. In this paper, we present the case for cellular BSs enabled with renewable energy sources (RES) to have an arrangement in which the BS provide surplus energy to a neighboring BS, thus minimizing the use of conventional energy. A realistic objective is developed for northern region of Pakistan, which entails modeling of solar panels and wind-turbine according to the average solar irradiation and wind speed of the region. We also model the dynamic load of the BS, which depicts temporal fluctuations with traffic variations. Based on these models we initiate an energy cooperation scheme between the BS in which an energy cost minimization framework is mathematically modeled and solved through the interior point method algorithm. Results are obtained for different times of the year for different number of base stations showing respective energy cost savings.
... The so-called sleep mode concept can be divided into three main approaches: saving energy through actions in time, frequency, and spatial domain [66]. Thus, switching off devices (BSs) for some period of time by taking into account the traffic amount helps to save energy. ...
... Energy Efficient Ethernet to manage transitions between low powered and standard powered states [5]. Using traffic forecasting to manage sleep modes has been suggest by Morosi et al. [6]. Their forecasting based algorithm, forecasting based sleep mode algorithm (FBSMA), allows for daily calculations of approximate traffic. ...
With the rise in popularity of cloud computing the amount of energy consumed by the cloud computing data centres has increased dramatically. Cloud service providers are aiming to reduce their carbon footprint by reducing the energy their data centres produce, while maintain an expected Quality-of-Service adhering to set Service Level Agreements. In this paper, we present our suggested approach for using previously researched energy efficiency techniques, particularly Dynamic Voltage/Frequency Scaling and sleep states, more efficiently
through the aid of an SLA-based priority scheduling algorithm, and the results we expect from our research.
... The process of BS-UE association is also thoroughly dealt with and this is good for QoS. The strategy introduced in [28] makes use of Holt-Winter forecast method to decide at what point to switch off BSs. The technique is a recursive scheme that updates at each observation of the phenomena in question. ...
This paper presents a survey of the latest technologies that have been advanced by both academia and industry in an attempt to reduce the energy consumed by Base stations (BS) in cellular networks. Since BSs are the primary energy consumers in cellular networks, BS sleeping technologies are promising proposals in reducing BS energy consumption. The main goal of the survey is to gain an in-depth understanding of the benefits and shortcomings of these proposed technologies. The survey presented the authors with an opportunity to offer clear insights to researchers working on Green Cellular Networks for them to choose and adapt the most efficient ways of reducing BS energy consumption without compromising Quality of Service (QoS).
... Traffic aware network energy management is considered in [8,9] to preserve power consumption. Authors in [10] investigate two sleep mode algorithms, the first algorithm is dynamic sleep mode and the second one is semi-static sleep mode. ...
Power consumption of wireless network is increasing as the demands in wireless data rates are escalating in modern life. Base stations are the major power consumption component in the wireless network. Therefore, the main challenge is to reduce the total power consumed in the network while maintaining the network coverage and its capacity. In this paper, a new relay switching perspective is introduced for relay blossoming and withering algorithm. First, relay switching is considered as a function of time representing the rate of active relays. The effect of the rate of active relays, arrival rate and average load factor of relays on the total network power consumption is modelled. It is found that the rate of active relay function that optimises the network power consumption obeys linear first-order ordinary differential equation. The effect of different synthesised arrival rate profiles on the rate of active relay is presented. Moreover, relative relay to base station capacity parameter is defined, and its effect on the power optimisation is investigated. Based on the solutions of the ordinary differential equation, an approximate fuzzy-based relay sleeping mode is introduced. The fuzzy logic sleeping mode utilises the arrival rate and its derivative as inputs. The solution of the differential equations shows that power saving up to 45 and 30 per cent can be achieved in sleeping and idling modes, respectively, in contrast to 42 per cent achieved from the fuzzy sleeping mode. The increasing slope of the arrival rate results in less power saving. Copyright © 2015 John Wiley & Sons, Ltd.
... A method of traffic forecasting is proposed by Morosi et al. [7] to deal with the management of base station sleep modes in a mobile network. The forecasting based sleep mode algorithm (FBSMA) allows for the adaption of the number of radio resources to the approximate traffic within the network as calculated by a forecast created daily. ...
In recent years energy consumption from ICT has increased due to the popularity of cloud computing. This consumption is also estimated to double every five years. A key topic of recent research is the focus on increasing the energy efficiency of ICT, in particular the area of cloud computing. In our research we aim to improve the energy efficiency of cloud computing data centres while maintaining the Quality-of-Service (QoS) expected. A literature review has been conducted into various methods of increasing energy efficiency and the beginnings of experimentation into our own research and theories have been documented in this paper.
... " Therefore, radio context awareness concerns the ability of detecting a system state or estimating a system parameter in order to enhance communication performance from the physical to the network layers or in order to provide the necessary context information for advanced services and applications. Channel state information, energy consumption, positioning and environment mapping, mutual interference among active devices, and spectrum usage are examples of system state information that can enhance either the efficiency of the communication network itself or the effectiveness of the applications which can be built on this context knowledge [2][3][4][5][6][7][8][9][10][11][12]. Nowadays, it is clear that radio context aware techniques can give a further strong impulse to new applications and enhance the communication performance operating on several aspects of the system. ...
The context refers to “any information that can be used to characterize the situation of an entity, where an entity can be a person, place, or physical object.” Radio context awareness is defined as the ability of detecting and estimating a system state or parameter, either globally or concerning one of its components, in a radio system for enhancing performance at the physical, network, or application layers. In this paper, we review the fundamentals of context awareness and the recent advances in the main radio techniques that increase the context awareness and smartness, posing challenges and renewed opportunities to added-value applications in the context of the next generation of wireless networks.
With the astronomical increase in cellular traffic, there is need to cut down on the power consumption so as to reduce CO2 emissions and in the process lowering network operational expenditure (OPEX). In this thesis, one method that can be used to lower a Base Station energy consumption is proposed. Traditional cellular networks are designed to offer maximum coverage and connectivity for peak traffic. This is not energy efficient since a lot of energy will go to waste during the time cellular traffic is very low. The scheme that was developed, identifies Base Stations that have very low traffic loads and User Equipment that can all be
transferred to neighbouring Base Stations and put the Base Stations to sleep for as long asnecessary to save energy and to maintain Quality of Services (QoS) at an
acceptable level. The Next Generation Networks (specifically 5G) will be heterogeneous networks as heterogeneous are a promising solution in increasing network performance especially in providing indoor and cell-edges coverage. The solution that was developed in this thesis was specifically designed to work with heterogeneous networks and its performance was also tested on heterogeneous
networks. OMNeT++ V4.6 together with INET 2.3.0 and SimuLTE 9.1 were used for the validation of the proposed scheme. After extensive simulations were carried out, it was concluded that some Base Stations in a cellular network, can be put to sleep during the time that cellular traffic is low without compromising the Quality of Service. End-to-end delay, sum throughputs, queue length and Channel Quality Indicator were some of the performance metrics that were used to check whether the developed scheme did not reduce the QoS of a network.
Ultra dense networks are a promising technique to achieve increasing 1000 times data rate requirements of the fifth generation (5G) wireless communications. However, due to the 'tidal effect' of mobile Internet traffic, the energy efficiency of the 5G communication system decreases dramatically, especially in off-peak hour, such as midnight. The software-defined wireless networks (SDWN) architecture provides a solution to reduce the energy consumption via cells management. To facilitate wide usage of cells management in SDWN, we consider in this paper the problem of joint ultra dense cells management and resource allocation, with the objective to minimize the network power consumption while guaranteeing the quality of service requirements of users and the coverage rate requirement. The problem is formulated as a mixed-integer nonlinear programming problem. To deal with this problem, we utilize the sparse characteristics of the beamforming vector and the method of reweighted l 1 norm to approximate l 0 norm. Because the coverage rate requirement constraint is still non-convex, we propose an iterative algorithm to derive the lower bound of the problem, and then propose a heuristic iterative algorithm to obtain a practical solution. Simulation results confirm that minimizing the total network power consumption results in sparse network topologies, and some of the small cells are inactivated when possible. The performance of the proposed heuristic algorithm is only increased by 13.09% compared with the lower bound, while the target signal-to-interference-plus-noise ratio grow from 0 to 8 dB. And the proposed heuristic algorithm can achieve good performance compared with the conventional sparsity-based algorithm.
Future wireless networks are envisioned to be heterogeneous with macro base stations (MBSs) and small cell base stations (SBSs) playing different roles through C/U plane separation [1–3]. The idea of C/U plane separation is to allow SBS users to maintain dual connectivity with both the MBS and SBS simultaneously, whereby the control and signaling traffic is handled by the MBS while the data traffic is served by the SBS [1]. The separation of control plane and user plane can improve mobile user experience [4, 5].
This paper aims at providing a thorough analysis of the energy efficiency of the TeTRA (TErrestrial Trunked RAdio) private cellular system. In particular some effective dynamic radio resource management solutions are presented, highlighting the impact on daily energy consumption. Moreover, the potential benefits of the transition which can be envisaged to the recently proposed TeTRA over LTE system are evaluated in terms of capacity and energy saving.
To further improve the energy efficiency of heterogeneous networks, a separation architecture called hyper-cellular network (HCN) has been proposed, which decouples the control signaling and data transmission functions. Specifically, the control coverage is guaranteed by macro base stations (MBSs), whereas small cells (SCs) are only utilized for data transmission. Under HCN, SCs can be dynamically turned off when traffic load decreases for energy saving. A fundamental problem then arises: how many SCs can be turned off as traffic varies- In this paper, we address this problem in a theoretical way, where two sleeping schemes (i.e., random and repulsive schemes) with vertical inter-layer offloading are considered. Analytical results indicate the following facts: (1) Under the random scheme where SCs are turned off with certain probability, the expected ratio of sleeping SCs is inversely proportional to the traffic load of SC-layer and decreases linearly with the traffic load of MBS-layer; (2) The repulsive scheme, which only turns off the SCs close to MBSs, is less sensitive to the traffic variations; (3) deploying denser MBSs enables turning off more SCs, which may help to improve network energy-efficiency. Numerical results show that about 50% SCs can be turned off on average under the predefined daily traffic profiles, and 10% more SCs can be further turned off with inter-layer channel borrowing.
In this paper, a survey of the mobile data traffic growth over the last decade is performed, showing historically how data consumption patterns have evolved. Based on the results from the survey and the most important factors for unprecedented traffic growth from last years, a set of user-centric services and scenarios are identified as the most prevalent by 2020. Based on service characteristics and subscribers' behaviour and consumption regarding traffic generation, four user segments are derived. All these factors allow introducing an impact model that characterises user segment's behaviour over post-4G cellular networks, namely, its consistency and stability towards traffic generation, data consumption and service usage, providing mobile network operators with relevant information to predict user segment dispersion, stability and risk. Real and estimated market data are used to test the impact model, and most relevant results are shown. Overall, the proposed impact model aims to bring together technological, sociological and also economical perspectives into a single analytical framework, meeting both mobile network operators and subscriber's expectations of high quality of service with continuous cost decrease. Copyright © 2015 John Wiley & Sons, Ltd.
The last ten years have witnessed explosive growth in mobile data traffic, which leads to rapid increases in energy consumption of cellular networks. One potential solution to this issue is to seek out a green deployment strategy. In this paper, we investigate the energy-efficient deployment strategy under coverage performance constraints for both homogeneous and heterogeneous cellular networks. Unlike just considering the base station (BS) density in previous work, we jointly optimize the BS density and the BS transmission power. First, we derive the relation between the average coverage probability and deployment strategy (i.e., BS density and BS transmission power) with stochastic geometry tools. Then, based on the expression results, we formulate a network energy consumption minimization framework considering coverage performance constraints and jointly determine the optimal macro BS (MaBS) density, MaBS transmission power, and micro BS (MiBS) density. With practical data sets, numerical simulation results show the following: 1) compared with homogeneous network deployment, heterogeneous network deployment has the advantage in energy efficiency performance, and 2) our joint BS density and BS transmission power optimization strategy exceeds the existing strategy, which just considers the BS density optimization in terms of energy efficiency.
The green communications paradigm has been receiving much attention in wireless networks in recent years. More specifically, in the context of cellular communications, the concept of Cell Switch Off (CSO) has been recognized as a promising approach to reduce the energy consumption. The need is expected to be pressing especially in the next decade with the increasing small cell deployment. However, the cell switch on/off decisions compounded by the resource allocation task in CSO constitute a highly challenging optimization problem due to the fact that this problem can be viewed as a generalized version of the resource allocation (scheduling) problem in the conventional cellular networks without CSO, which itself is already difficult. This paper introduces a novel framework to CSO based on multiobjective evolutionary optimization. The main contribution of this paper is that the proposed multiobjective framework takes the traffic behaviour in both space and time (known by operators) into account in the optimal cell switch on/off decision making which is entangled with the corresponding resource allocation task. The exploitation of this statistical information is done in a number of ways, including through the introduction of a weighted network capacity metric. This indicator prioritizes cells which are expected to have traffic concentration resulting in on/off decisions that achieve substantial energy savings in scenarios where traffic is highly unbalanced, without compromising the QoS. The proposed framework distinguishes itself from the CSO papers in the literature in two ways: 1) The number of cell switch on/off transitions as well as handoffs are minimized. 2) The computationally-heavy part of the algorithm is executed offline, which makes the real-time implementation feasible.
Conventional peak-traffic-based provisioning of cellular mobile networks leads to a significant wastage of electrical energy. Therefore, we propose a novel traffic-aware two-dimensional dynamic network provisioning mechanism for enhancing the energy efficiency in orthogonal frequency division multiple access (OFDMA)-based cellular systems. Proposed scheme, named as joint dynamic sectorisation and switching of base station (BS), adaptively provisions cellular access networks by switching the redundant BSs as well as sectors into sleep mode. Quality of service, namely, user data rate, service continuity and network coverage, is also maintained. Because of the high complexity of the formulated generalised energy optimisation problem, the two dimensions (i.e. sector switching and BS switching) are decoupled in time-domain into two sub-problems, each executing its own heuristically guided algorithm. Moreover, a novel exponentially weighted moving average (EWMA)-based load factor estimator is employed for reducing the occurrence of network provisioning. System performance is evaluated using extensive simulations demonstrating substantial energy savings. In addition, impact on the spectral efficiency and resource utilisation is presented. Effectiveness of joint dynamic sectorisation and switching of BS is further validated by comparing with the individual application of sectorisation and BS switching. Furthermore, for realistic traffic patterns, use of EWMA estimator achieves over 40% reduction in network provisioning events without compromising energy-saving performance. Copyright © 2014 John Wiley & Sons, Ltd.
In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows. Copyright © 2013 John Wiley & Sons, Ltd.
The energy consumption of network elements has become a big concern due to the exponential traffic growth and the rapid expansion of communication infrastructures. To deal with this problem, we propose a new approach called Backbone network Energy Saving based on Traffic engineering (BEST), which reduces the power consumption of network elements at the backbone level through jointly optimising data placement and traffic routing. Based on analysis on traffic characteristics, BEST firstly optimises the placement of data services such that the pairwise traffic demands can be better coordinated with the pairwise network costs, in order to minimise the traffic burden imposed on the network elements. Then, BEST optimises the routing of traffic flows and tries to find the minimum-power network subset that must remain active to fulfill the traffic requirements. Efficient heuristics are given by BEST to find an admissible solution when the problem size is very large. The simulation results illustrate the efficacy and efficiency of BEST in energy conservation on backbone networks. Copyright © 2013 John Wiley & Sons, Ltd.
In radio access networks, the base stations’ (BSs) power consumption does not merely depend on the traffic loads within its coverage. The auxiliary devices, especially the cooling system in BSs, contribute to significant energy exhaustion. As the traffic loads fluctuate spatially and temporally, the BSs consequently suffer from heavy energy wastage when the traffic loads of their coverage are low. In this paper, an energy saving scheme over predicted traffic loads is proposed to tackle this energy inefficiency problem in incumbent radio access networks induced by the fluctuations of traffic loads. The proposed scheme firstly takes advantage of the spatial–temporal pattern of traffic loads and employs the compressive sensing method to predict the future traffic loads. Then, a grid-based energy saving scheme is developed to improve the energy efficiency through turning some BSs into sleeping mode while ensuring the quality of experience. Results of the simulation with real traffic load statistics finally validate the accuracy of the traffic load prediction and large improvement of energy efficiency. Copyright © 2012 John Wiley & Sons, Ltd.
In cellular networks, the base station power consumption is not simply proportional to the traffic loads of its coverage. As the traffic load fluctuates spatially and temporally, the base stations consequently suffer from heavy energy wastage when the traffic loads of their coverage are low. In this paper, we propose a grid-based energy saving scheme over predicted traffic loads. We firstly take advantage of the spatial-temporal pattern of traffic loads and employ the compressed sensing method to predict the future traffic loads. Then, we propose a grid-based energy saving scheme to improve the energy efficiency through turning some base stations into sleeping mode while ensuring the quality of service. Results of the simulation with real traffic loads1 finally show the accuracy of the traffic load prediction and large energy efficiency improvement.
The energy consumption problem in the mobile industry has become crucial. For the sustainable growth of the mobile industry, energy efficiency (EE) of wireless systems has to be significantly improved. Plenty of efforts have been invested in achieving green wireless communications. This article provides an overview of network energy saving studies currently conducted in the 3GPP LTE standard body. The aim is to gain a better understanding of energy consumption and identify key EE research problems in wireless access networks. Classifying network energy saving technologies into the time, frequency, and spatial domains, the main solutions in each domain are described briefly. As presently the attention is mainly focused on solutions involving a single radio base station, we believe network solutions involving multiple networks/systems will be the most promising technologies toward green wireless access networks.
The sensitiveness toward energy consumption problems is driv- ing Telecommunications operators to optimize network equipment utilization. Since cellular systems are often dimensioned for peak hour traffic, during low traffic periods, such as night, many devices are underutilized but still, by being active, consume power. In this paper, we show that dynamic planning, consisting in reducing the number of active access devices when traffic is low, can achieve significant power saving. In our study, we consider three different UMTS scenarios with a simplified traffic model describing three classes of services, quality of service guarantees, link-budget, propagation and electromagnetic exposure constraints.
In this paper we study with simple analytical models the energy-aware management of cellular access networks, trying to characterize the amount of energy that can be saved by reducing the number of active cells during the periods when they are not necessary because traffic is low. When some cells are switched off, radio coverage and service provisioning are taken care of by the cells that remain active, so as to guarantee that service is available over the whole area. We show how to optimize the energy saving, first assuming that any fraction of cells can be turned off, and then accounting for the constraints resulting from the cell layout.
This article quantifies the global carbon footprint of mobile communication systems, and discusses its ecological and economic implications. Using up-to-date data and life cycle assessment models, we predict an increase of CO2 equivalent emissions by a factor of three until 2020 compared to 2007, rising from about 86 to 235 Mto CO2e, suggesting a steeper increase than predicted in the well-known SMART2020 report. We provide a breakdown of the global carbon footprint, which reveals that production of mobile devices and global radio access network operation will remain the major contributors, accompanied by an increasing share of emissions due to data transfer in the backbone resulting from rising mobile traffic volumes. The energy bill due to network operation will gain increasing importance in cellular business models. Furthermore, technologies to reduce energy consumption are considered a key enabler for the spread of mobile communications in developing countries. Taking into account several scenarios of technological advancement and rollout, we analyze the overall energy consumption of global radio access networks and illustrate the saving potential of green communication technologies. We conclude that, conditioned on quick implementation and alongside other "classical" improvements of spectral efficiency, these technologies offer the potential to serve three orders of magnitude more traffic with the same overall energy consumption as today.
The explosive development of ICT (information and com-munication technology) industry has emerged as one of the major sources of world energy consumption. Therefore, this paper concerns about the BS (base station) energy saving issue, for most energy consumption of the communication network comes from the BSs and the core network. Par-ticularly, we consider dynamically turning off certain BSs when the network traffic is low. Centralized and decentral-ized implementations are investigated. Simulations demon-strate the energy efficiency of the proposed algorithms and the tradeoff between energy saving and coverage guarantee.
The paper will provide an analysis on the trend of energy consumption for the next generation access network, taking into account VDSL2 deployment in FTTx architectures. It points out the related issues and needs for a Telco as Telecom Italia, which aims to manage the energy consumption evolution in a sustainable way. The analysis will give evidence of the growing energy consumption trend that can only be faced by a strong and coordinated action between regulators, operators and industries, aiming to the optimization (reduction) of energy consumption (e.g. through standardization activities). The parallel constantly growing cost of electrical energy could lead to unacceptable energy budgets for Telcos, together with a strong negative impact on eco sustainability. The initiative of "code of conduct on energy consumption reduction of BB equipment" issued by the European Commission will be quoted and details will be provided. The paper will also focus on further aspects for a sustainable deployment of active equipment in the access network for FTTx architecture, such as need of new standardized environmental classes for active equipment to be hosted in outdoor cabinets, need of action on the mechanical aspects to have a reduction of the needed space, possible back-up sources for availability of service (life-line service). These issues, together with the energy consumption minimization, are the key factors for a successful and sustainable deployment of FTTx architecture. The paper will, in its final section, propose a focus on possible alternative and renewable energy sources for Telecommunications application: Telecom Italia is analyzing possible alternative energy sources to be adopted in the power feeding in its network, matching a national energy policy scenario leading to deeper attention to energy savings and usage of alternative energy sources.
Energy-efficiency, one of the major design goals in wireless cellular networks, has received much attention lately, due to increased awareness of environmental and economic issues for network operators. In this paper, we develop a theoretical framework for BS energy saving that encompasses dynamic BS operation and the related problem of user association together. Specifically, we formulate a total cost minimization that allows for a flexible tradeoff between flow-level performance and energy consumption. For the user association problem, we propose an optimal energy-efficient user association policy and further present a distributed implementation with provable convergence. For the BS operation problem (i.e., BS switching on/off), which is a challenging combinatorial problem, we propose simple greedy-on and greedy-off algorithms that are inspired by the mathematical background of submodularity maximization problem. Moreover, we propose other heuristic algorithms based on the distances between BSs or the utilizations of BSs that do not impose any additional signaling overhead and thus are easy to implement in practice. Extensive simulations under various practical configurations demonstrate that the proposed user association and BS operation algorithms can significantly reduce energy consumption.
In wireless communications micro cells are potentially more energy efficient than conventional macro cells due to the high path loss exponent. Also, heterogeneous deployments of both cell types can be used to optimize the energy efficiency. Energy efficiency of any deployment is impacted by the power consumption of each individual network element and the dependency of transmit power and load. In this paper we developed such power models for macro and micro base stations relying on data sheets of several GSM and UMTS base stations with focus on component level, e.g., power amplifier and cooling equipment. In a first application of the model a traditional macro cell deployment and a heterogeneous deployment are compared.
Mobile communications are increasingly contributing to global energy consumption. In this article, a holistic approach for energy efficient mobile radio networks is presented. The matter of having appropriate metrics and evaluation methods that allow assessing the energy efficiency of the entire system is discussed. The mutual supplementary saving concepts comprise component, link and network levels. At the component level the power amplifier complemented by a transceiver and a digital platform supporting advanced power management are key to efficient radio implementations. Discontinuous transmission by base stations, where hardware components are switched off, facilitate energy efficient operation at the link level. At the network level, the potential for reducing energy consumption is in the layout of networks and their management, that take into account slowly changing daily load patterns, as well as highly dynamic traffic fluctuations. Moreover, research has to analyze new disruptive architectural approaches, including multi-hop transmission, ad-hoc meshed networks, terminal-to-terminal communications, and cooperative multipoint architectures.
Due to increasing data traffic rates and rollout of advanced radio transmission technologies wireless networks consume increasing amount of energy and contribute a growing fraction to the CO2 emissions of ICT industry. Thus, climate and cost issues now shift the research focus of wireless communications to energy consumption and energy efficiency. Two approaches can be followed: Incremental improvements of existing systems or a clean slate re-design with a fundamental change of paradigms. We describe two such initiatives and discuss their differences. The EC FP7 project EARTH is a 30 month project aiming for a reduction of the overall energy consumption of 4G mobile broadband networks by 50%, regarding network aspects and individual radio components from a holistic point of view. The Green Touch Initiative is a privately financed consortium addressing fundamental research that will pave the way to much higher reductions for future systems in the order of several magnitudes, with first proof of concepts available in 5 years.
Optimization of the energy efficiency is considered not only to positively contribute to the ecological assessment, but gains in importance from operator's point of view as well, since energy costs for running a mobile radio network have an increasing share of the operational expenditure. From this perspective, the utilization of small, low power base stations is regarded as a promising strategy to enhance a network's throughput and to increase the energy efficiency. In this paper we investigate on the efficiency of homogeneous and heterogeneous networks consisting of a varying number of micro sites with regard to traffic load conditions.
Cell size in cellular networks is in general fixed based on the estimated traffic load. However, the traffic load can have significant spatial and temporal fluctuations, which bring both challenges and opportunities to the planning and operating of cellular networks. This article introduces a concept of cell zooming, which adaptively adjusts the cell size according to traffic load, user requirements and channel conditions. The implementation issues of cell zooming are then presented. Finally a usage case of cell zooming for energy saving is investigated. Centralized and distributed cell zooming algorithms are developed, and simulation results show that the proposed algorithms can greatly reduce the energy consumption, which leads to green cellular networks.
Recent analysis by manufacturers and network operators has shown that current wireless networks are not very energy efficient, particularly the base stations by which terminals access services from the network. In response to this observation the Mobile Virtual Centre of Excellence (VCE) Green Radio project was established in 2009 to establish how significant energy savings may be obtained in future wireless systems. This article discusses the technical background to the project and discusses models of current energy consumption in base station devices. It also describes some of the most promising research directions in reducing the energy consumption of future base stations.
Constant envelope partial response Gaussian Minimum Shift Keying (GMSK) with a channel spacing of 200 kHz is deployed to support 125 duplex channels in the uplink and downlink bands of a Pan-European Mobile Radio System. The controlled GMSK-induced and uncontrolled channel-induced intersymbol interferences are removed by the channel equalizer. The set of standardized wide-band GSM channels is introduced in order to provide benchmarkers for performance comparisons. Efficient power budgeting and minimum co-channel interferences are ensured by the combination of adaptive power- and handover-control based on weighted averaging of up to 8 uplink and downlink system parameters. Discontinuous transmissions further reduced interference and power consumption.
This paper presents a distributed mechanism for improving the overall energy efficiency of a wireless network where users can control their uplink transmit power targeted to the multiple access points in the network. This mechanism lets the network achieve a trade-off between energy efficiency and spectral efficiency through the use of suitably designed utility functions. A user's utility is a function of throughput and average transmission power. Throughput is assumed to be a sigmoidal function of signal-to-interference-plus-noise ratio. Each user, being selfish and rational, acts to maximise its utility in response to signal-to-interference-plus-noise ratio by adjusting its power. The resulting mechanism is a distributed power control scheme that can incline towards energy-efficient or spectrally efficient operating points depending on the choice of utility function. Existence and uniqueness of Nash equilibrium points in this game are shown via convergence of the distributed power iterations. It is shown that, in the best-response strategy, each user selects a single access point. An extension of this result for a multicarrier system is considered, and the corresponding power levels used for various priorities between energy efficiency and spectral efficiency are characterised. Finally, several numerical studies are presented to illustrate the analysis. Copyright © 2012 John Wiley & Sons, Ltd.
The RRM strategies and the deployment guidelines to be adopted in a multi-layer heterogeneous mobile network with the goal of the optimization of the Area Power Consumption are presented in this paper: in the considered scenarios, several radio environments are considered, the coverage is guaranteed by different cell types, and the capacity and blockage probability are kept unaltered by the adoption of the green radio approaches with respect to basic configuration. The benefits in terms of energy savings are determined for all possible solutions: within this framework we compare alternative approaches, such as the macro-cell coverage and the strategies which resorts to a higher number of lower power micro-cells to cover the spot.
The objective of the reduction of the energy consumption in the next years has led the scientific community to investigate the possible solution to be adopted in the cellular networks: therefore, a huge attention is currently dedicated to the green radio techniques since even the future business models of the mobile telecom operators will be deeply influenced by the trends which will be chosen today. In this paper, two adaptive algorithms which are based on traffic forecast and real-time measurements are proposed and compared with the goal of the optimal radio resources management.
In this paper, a power consumption model for both macrocell and microcell base stations is proposed. This model is validated by temporal power measurements on actual base stations, and an excellent agreement is obtained. Furthermore, the power consumption's evolution during the day is investigated by means of these measurements. The energy efficiency of three different wireless technologies is compared namely mobile Worldwide Interoperability for Microwave Access, Long Term Evolution and High Speed Packet Access. With the model proposed, the deployment tool Green Radio Access Network Design is implemented, which allows to design an energy-efficient access network for a predefined area. In general and with the assumptions made, a macrocell base station consumes about 4.4 times more than a microcell base station. However, a microcell base station is less energy efficient than a macrocell base station because of its lower coverage range. Despite this, it is still useful to introduce them in the network as the same coverage can be obtained with a lower total power consumption than with a network where only macrocell base stations are used. Copyright © 2012 John Wiley & Sons, Ltd.
Having considered the mapping of logical traffic and control channels onto physical channels, speech and error correction coding, interleaving as well as the TDMA hierarchy and syn- chronisation problems in Part I of this contribution, here mainly transmission issues are addressed (I - 61 and some performance figures are provided. Constant envelope partial response Gaussian Minimum Shift Keying (GMSK) with a channel spacing of 200 kHz is deployed to support 125 duplex channels in the 890 - 91 5MHz uplink and 935 - 960 MHz downlink bands, respectively. At a transmission rate of 271 kbitls 1.35 bitlslHz spectral efficiency is achieved. The controlled GMSK-induced and un-controlled channel-induced inter-symbol interferences are removed by the channel equaliser. The set of standardised wide-band GSM channels is introduced in order to pro- vide bench-markers for performance comparisons. Efficient power budgeting and minimum co- - - channel interferences are ensured by the combination of adaptive power- and handover-control based on weighted averaging of up to eight uplink and downlink system parameters. Discontinu- ous transmissions (DTX) assisted by reliable spectral-domain voice activity detection (VAD) and comfort-noise insertion further reduce interferences and power consumption. Due to ciphering, no unprotected information is sent via the radio link. As a result, spectrally efficient, high-quality mo- bile communications with a variety of services and international roaming is possible in cells of up to 35km radius for signal to noise- and interference-ratios in excess of 10 - 12 dBs.
Following the launch of the Pan-European digital mobile radio (GSM) system its salient features are summarised in this tutorial review [1,8]. Time Division Multiple Access (TDMA) with eight users per carrier is used at a multi-user rate of 271 kbit/s, demanding a channel equaliser to combat dispersion. The error protected chip-rate of the full-rate traffic channels is 22.8 kbit/s, while in half-rate channels is 11.4 kbit/s. There are two speech traffic channels, five different-rate data traffic channels and 14 various control and signalling channels to support the system's operation. A moderately complex, 13 kbit/s Regular Pulse Excited speech codec with long term predictor (LTP) is used, combined with an embedded three-class error correction codec and multi-layer interleaving to provide sensitivity-matched unequal error protection for the speech bits. An overall speech delay of 57.5 ms is maintained. Slow frequency hopping at 217 hops/s yields substantial performance gains for slowly moving pedestrians.
for reducing energy consumption of radio access networks. We propose an offline-optimized controller that associates to each traffic an activation/deactivation policy that maximizes a multiple objective function of the Quality of Service (QoS) and the energy consumption. We focus on practical implementation issues that may affect the QoS and the stability of the system. We namely consider the activation time issue that results in the degradation of the throughput and the ping-pong effect that results in unnecessary ON/OFF oscillations. We illustrate our results numerically in beyond 3G networks.
In this paper, we develop new energy-efficient, radio resource management schemes for green wireless networks. Our goal is to optimize energy consumption at the network scale while preserving the Quality of Service (QoS) perceived by users. We specifically propose two new sleep mechanisms for base station where a number of resources in system can be shut down for some traffic scenarios in one of two ways: a dynamic way where resources are activated/deactivated in real-time as a function of the instantaneous load of the system, and a semi-static one where resources are kept unchanged during longer time intervals, in the order of one hour. We apply the proposed schemes to 2G and HSPA (High Speed Packet Access) systems and show that the dynamic one achieves larger energy reductions while the semi-static one has an acceptable performance with low complexity.
This paper studies the impact of a femto-cell underlay deployment that shares radio frequency resources with urban macro-cells. Due to their random and uncoordinated deployment, femto-cells potentially cause destructive interference to macro-cells and vice versa. On the other hand, femto-cells promise to substantially enhance the spectral efficiency due to an increased reuse of radio resources. The performance of networks with indoor Home Evolved NodeB (HeNB) deployment is compared to a system where all users, including indoor users, are served by the outdoor macro Evolved NodeB (eNB). In addition, the impact of closed-access and open-access femto-cell operation is examined. It is demonstrated that significant capacity gains can be achieved through such HeNB deployment, regardless of whether closed-access or open-access is considered. Results clearly indicate that the capacity gains through femto-cell deployment outweigh the additional interference they introduce. Copyright © 2010 John Wiley & Sons, Ltd.
In this paper are presented the Work Items on Energy saving that are in the ETSI standardization work programme. An overview of the activities on energy consumption in other standardization bodies having links with ETSI is also provided together with a brief overview of the European regulation 2005/32/EC.
This paper presents a technique for evaluation of future radio traffic of circuit switched services in Erlang for near-term outlook using Holt-Winter's exponential smoothing. The proposed traffic prediction technique relies on analysis of traffic data on cells. We propose how to classify traffic data for prediction. The result from a trial in history data of commercial GSM/GPRS network is presented. It shows that predicted traffic is good fitted with original one within our classification. The technique should be used in automated overload warning and express estimation of future traffic for capacity planning.
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