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5G Heterogeneous cellular networks

Goal: Analysis of 5G Heterogeneous cellular networks

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Arumugam Nallanathan
added a research item
Increasing the deployment density of small base stations (SBS) is a key method designed to satisfy high data traffic in 5th generation mobile network (5G). However, a large number of SBSs in such ultradense network (UDN) may cause ping-pong handovers (HOs), accompanied by increased delay and HO failure. In addition, because of the separation of control and data signaling in 5G, the HO procedure must be performed in both layers. In this paper, we introduce an SDN-based intelligent dynamic HO parameter optimization strategy to minimize both HO failures and ping-pong HOs together. The goal of the proposed strategy is to reduce the HO failure rate and redundant HO (i.e. ping-pong HO) while enabling user equipment (UE) to make full use of the benefits of dense deployment of BSs. Simulation results present that the method proposed in this paper effectively suppresses the ping-pong effect and keeps it at a low level in all of the investigated scenes. In addition, compared with the other algorithms, the HO failure rate is significantly reduced and the throughput of UE is greatly increased, especially in the case of high BS density. Therefore, the benefits of intensive BS deployment are retained.
Muhammad Nadeem Sial
added a research item
To overcome the limitations of Dedicated Short Range Communications (DSRC) with short range, non-supportability of high-density networks, unreliable broadcast services, signal congestion and connectivity disruptions, vehicle-to-everything (V2X) communication networks, standardized in 3rd Generation Partnership Project (3GPP) Release 14, have been recently introduced to cover broader vehicular communication scenarios including vehicle-to-vehicle (V2V), vehicle-to-pedestrian (V2P) and vehicle-to-infrastructure/network (V2I/N). Motivated by the stringent connection reliability and coverage requirements in V2X, this paper presents the first comprehensive and tractable analytical framework for the uplink and downlink performance of cellular V2X networks, where the vehicles can deliver their information via V2N/cellular network (vehicle-to-base station, V2B communication link) or directly between vehicles in the sidelink, based on their distances, propagation environments and the bias factor. By practically modeling the vehicles on the roads using the doubly stochastic Cox process and the BSs, we derive new association probabilities of V2B and V2V links, new success probabilities of the V2B and V2V communications, and overall success probability of the V2X communication, which are validated by the simulations results. Our results reveal the benefits of V2X communication compared to V2V communication in terms of success probability.
Muhammad Nadeem Sial
added 3 research items
High data rate demands of users have resulted into initiation of research on 5th Generation (5G) mobile networks. Up till now, Heterogeneous Networks (HetNets), Massive Multiple-Input Multiple Output (MIMO) and millimeter Wave (mmWave) technologies have been identified as key enabling technologies for emerging 5G networks. Out of these, HetNets along with efficient user association mechanisms are considered the most promising technology to achieve desired 5G objectives. At present, the cell association in existing HetNets is based on Downlink Reference Signal Received Power (DL RSRP) termed as coupled association which results into sub-optimal user performance, asymmetric load distributions and mobility management due to coverage areas asymmetries in HetNets. In order to improve existing HetNet user association, Downlink-Uplink Decoupling (DUDe) and biased cell association techniques have been proposed in literature. Out of these, the concept of DUDe has been recently introduced to address the shortcomings of coupled and biased cell user association. In DUDe, mobile may receive DL traffic from one BS based on DL RSRP and send UL traffic through another base-station (BS) based on the path loss. The DUDe can also be jointly used with dual connectivity to consume radio resources of at least two different network points for spectrum aggregation. Currently, some initial research on decoupled access has been undertaken but analysis in realistic scenarios is still an open research area. In the prior works, all network users are assumed to utilize decoupled access without considering its necessity and viability along with user location. Moreover, insights on the decoupling effects in terms of number of HetNet tiers and degree of HetNet densities has not been presented in the literature. The use of decoupled access with dual connectivity has also not been analyzed in multi-tier settings. In this research work, we propose a new and practical hybrid coupled / decoupled and Joint DUDe Dual Connectivity cell association schemes for $K$-tier HetNets which can be selected depending upon user location and by considering its benefits. Due to proposed scheme, one type of users can have UL-DL Coupled Association (CoA) with same BS despite the permissibility of decoupled association. Second type of users can follow UL-DL decoupled access called DUDe association policy. This type of user association in which users can have both coupled or decoupled access is called hybrid coupled / decoupled. In the thesis, analysis starts by examining the basic form of hybrid coupled / decoupled in two tier HetNets where UL and DL associations are based on path loss and DL received power respectively. Later on, the analysis is further extended for $K$-tier HetNets to generalize the analytical model. This analysis is followed by analytical modeling of Joint DUDe Dual Connectivity where user is allowed to aggregate channels based on Dual Connectivity along with Decoupled Access. With the use of stochastic geometry, we have developed closed form solutions for coverage, outage probabilities and average throughput by considering uplink power control, receiver noise and K-tiers of HetNets which is not available in the existing literature. The resultant performance metrics are also evaluated in terms of achieved gains over existing coupled access policies. Results show that cell association technique based on DUDe or Joint DUDe Dual Connectivity can significantly improve UL performance for forthcoming 5G HetNets in terms of coverage probability, outage probability and average throughput. Finally, the thesis is concluded by a summary of the findings and main outcomes from the conducted research along with suggested future directions.
5th generation networks are envisioned to provide seamless and ubiquitous connection to 1000-fold more devices and is believed to provide ultra-low latency and higher data rates up to tens of Gbps. Different technologies enabling these requirements are being developed including mmWave communications, Massive MIMO and beamforming, Device to Device (D2D) communications and Heterogeneous Networks. D2D communication is a promising technology to enable applications requiring high bandwidth such as online streaming and online gaming etc. It can also provide ultra-low latencies required for applications like vehicle to vehicle communication for autonomous driving. D2D communication can provide higher data rates with high energy efficiency and spectral efficiency compared to conventional communication. The performance benefits of D2D communication can be best achieved when D2D users reuses the spectrum being utilized by the conventional cellular users. This spectrum sharing in a multi-tier heterogeneous network will introduce complex interference among D2D users and cellular users which needs to be resolved. Motivated by limited number of surveys for interference mitigation and resource allocation in D2D enabled heterogeneous networks, we have surveyed different conventional and artificial intelligence based interference mitigation and resource allocation schemes developed in recent years. Our contribution lies in the analysis of conventional interference mitigation techniques and their shortcomings. Finally, the strengths of AI based techniques are determined and open research challenges deduced from the recent research are presented.
Device to device (D2D) communication technology is widely considered in 5G for providing higher data rates and increase network capacity. The performance benefits of D2D communication are best achieved if it takes place in shared mode in which it reuses the spectrum being utilized by conventional cellular users. This induces significant challenges in allocating resources because of severe interference among D2D and cellular users. Moreover, centralized resource allocation techniques proposed in literature for D2D users can no longer be practical in dense heterogeneous networks considered for 5G. In this paper, we present a distributed learning based spectrum allocation scheme in which D2D users learn the environment and autonomously select spectrum resources to maximize their Throughput and Spectral Efficiency (SE) while causing minimum interference to the cellular users. We have employed distributed learning in a stochastic geometry based realistic network. Our evaluation results show that the employed learning scheme enables users to achieve high Throughput and Spectral Efficiency while meeting QoS requirements of macro and femto tier.
Muhammad Nadeem Sial
added 2 research items
Green communication with energy harvesting techniques are being considered for 5 th generation cellular networks to conserve energy and to prolong network life time. Moreover, Device to Device (D2D) communication on shared channels for 5G cellular networks is also a promising technology to achieve higher data rates, ultra-low latency communication and spectral efficiency. Presently, network optimization with an aim to maximize network throughput by meeting joint constraints of admitted user performance, maximization of admitted users, resource allocation, mode assignment as per available energy, power allocation along with different energy harvesting techniques have not been investigated in the literature due to it's infeasible nature. In this paper, we have formulated NP hard mix integer nonlinear programming (MINLP) optimization problem and then we have proposed a low complexity and efficient algorithm, Adaptive Resource Allocation and Energy Sentient Network (ARA-ESN) using Branch-Bound and Mesh Adaptive Direct Search (MADs) methods with energy harvesting through ambient energy and Radio Frequency (RF) energy transfer techniques. We have applied outer approximation approach (OAA) based linearization technique, which guarantees convergence to the optimal solution. The results show that ARA-ESN MADS outperforms ARA-ESN Branch-Bound method interms of performance and complexity. Moreover, ambient harvesting increases performance of network due to better acquisition of energy as compared to RF energy transfer.
Green communication with sustainable energy is being considered for 5G cellular network and Internet of Things (IoT) mainly with focus on energy harvesting to prolong network lifetime. Moreover, device-to-device communication on shared channels is also considered as a promising technology to achieve high data rates, ultra-low latency communication and high spectral efficiency. In this article, we investigated resource allocation in energy harvesting (EH) aided D2D communication underlying 5G cellular along with enabling IoT services. The objective is to maximize throughput of the network subject to the joint constraints on user performance, number of admitted users for equity and fair usage, mode assignment (cellular or D2D) as per available energy and transmit power allocation along with energy harvesting techniques which results in a mix integer nonlinear programming (MINLP) problem. We have proposed a low complexity and efficient algorithm, Adaptive Resource Allocation and Energy Sentient Network (ARA-ESN) using Branch-Cut, Branch-Bound and Mesh Adaptive Direct Search (MADs) solutions, where cellular or D2D communication is based on available energy and user performance criteria along with energy harvesting through ambient energy and Radio Frequency (RF) energy transfer techniques. We applied the outer approximation based linearization technique which guarantees the convergence to the optimal solution. The results show that ARA-ESN Branch-Cut outperforms ARA-ESN Branch-Bound and ARA-ESN MADs. Moreover, we have also observed that ambient harvesting increases performance of network due to better acquisition of energy as compared to RF energy transfer.
Arumugam Nallanathan
added a research item
Device-to-Device (D2D) communication based on cognitive radio (CR) technology can significantly improve the coverage and spectral efficiency. Existing research on D2D communications mainly focus on optimizing the network Quality of Service (QoS) in single-tier networks. However, the exponential growth in data traffic has inspired the move from traditional single-tier cellular networks toward heterogeneous cellular networks (HetNets). Hence, in this paper, we consider a CR-based HetNet coexisting with cognitive D2D pairs and cellular users, where the cellular users are primary users (PUs) and D2D pairs are secondary users (SUs). Considering Quality of Experience (QoE) is an important metric to quantify and measure quality of experience from the user perspective, we focus on the QoE optimization of the D2D pairs via the BS association, the discrete power control, and the resource block (RB) assignment. To do so, we first formulate the cross-layer optimization problem to maximize the average QoE of the D2D pairs while satisfying the QoE requirements of cellular users. We then propose the centralized resource allocation, namely the genetic algorithm (GA), and semi-distributed resource allocation method, namely Stackelberg game based algorithm, to solve the non-convex optimization problem. The GA is proposed to ensure the maximum achievable QoE with known channel state information (CSI), whereas the Stackelberg game based algorithm is proposed to cope with the strong needs for distributed D2D solutions with only local CSI of each D2D link. Our proposed algorithms can achieve substantial improvement of QoE performance for D2D pairs via increasing the number of RBs.
Arumugam Nallanathan
added 2 research items
With the proliferation of computation-extensive and latency-critical applications in the 5G and beyond networks, mobile-edge computing (MEC) or fog computing, which provides cloud-clone computation and/or storage capabilities at the network edge, is envisioned to reduce computation latency as well as conserve energy for wireless devices (WDs). This paper studies a novel device-to-device (D2D)-enabled multi-helper MEC system, in which a local user offloads its computation tasks to multiple helpers for cooperative computation. We assume a time division multiple access (TDMA) transmission protocol, under which the local user offloads the tasks to multiple helpers and downloads the results from them over orthogonal pre-scheduled time slots. Under this setup, we minimize the computation latency by optimizing the local user's task assignment jointly with the time and rate for task offloading and results downloading, as well as the computation frequency for task execution, subject to individual energy and computation capacity constraints at the local user and the helpers. However, the formulated problem is a mixed-integer non-linear program (MINLP) that is difficult to solve. To tackle this challenge, we propose an efficient algorithm by first relaxing the original problem into a convex one, and then constructing suboptimal task assignment based on the obtained optimal solution. Next, we consider a benchmark scheme that endows the WDs with their maximum computation capacities. To further reduce the implementation complexity, we also develop a heuristic scheme based on the greedy task assignment. Finally, numerical results validate the effectiveness of our proposed algorithm, as compared against the heuristic scheme and other benchmark ones without joint optimization of radio and computation resources or without task assignment design.
Muhammad Nadeem Sial
added 2 research items
Multi-tier Heterogeneous Networks (Hetnets) and Device-to-Device (D2D) communication are vastly considered in 5G networks. The interference mitigation and resource allocation in D2D enabled multi-tier Het-nets is a cumbersome and challenging task that cannot be solved by conventional centralized resource allocation techniques proposed in literature. In this paper, we propose a distributed multi agent learning based spectrum allocation scheme in which D2D users learn the wireless environment and select spectrum resources autonomously to maximize their Throughput and Spectral Efficiency (SE) while causing minimum interference to the cellular users. We have employed distributed learning in a stochastic geometry based realistic multi-tier heterogeneous network to validate the performance of our scheme. The proposed scheme enables D2D users to achieve higher throughput and SE, higher SINR and low Outage Ratio for Cellular users, better computational time efficiency and performs well in dense multi-tier Hetnets without affecting network coverage compared to Distance based Resource Criterion (DRC) and Joint-Resource Allocation and Link Adaptation (RALA) schemes.
Cell association policies in present-day heterogeneous networks (HetNets) cannot promise fairness and high capacity to all network users. To optimize this cell association, concept of downlink (DL)–uplink (UL) decoupling (DUDe) has been introduced where uplink and downlink channels can be associated with two different base stations (BSs) instead of existing policy of being associated with same BS. For this decoupled access, a number of theoretical uplink or downlink analysis frameworks have been proposed. However, these frameworks do not fully take into account the practical realization aspects. In these preceding works, all network users are assumed to employ decoupled access despite the fact that it is not preferred by all users. These models also ignore noise to get simplified solutions which can result into practical inaccuracies. In this paper, we propose a realistic user association technique in which both coupled access and decoupled access are permissible to users, depending upon their location and benefits. Therefore, the goal of the present paper is to present K-tier uplink analysis framework for network devices that prefer decoupled access. Simple closed-form solutions without ignoring noise are presented, which relate user performance to number of HetNet tiers, base-station densities and power levels. Moreover, derived distributions are also employed to compare performance of DUDe case with existing process of coupled access. Finally, decoupling impacts on K-tier network design have been presented. Based on conducted analysis, it can be concluded that decoupling is beneficial and can be easily realized in 5G K-tier HetNets.
Arumugam Nallanathan
added a research item
The weighted sum-rate (WSR) maximization problem of ultra-dense cloud radio access networks (C-RANs) is considered. The user-centric clustering is adopted for reducing the complexity. To reduce the training overhead, one only needs to estimate the intra-cluster CSI, while only the large-scale channel gains are available outside the cluster. We first derive the rate lower bound (LB) relying on Jensen’s inequality. For the special case of non-overlapping clusters, the accurate data rate expression is derived in closed-form. Simulation results show the tightness of the LB for both the overlapped and non-overlapped cases. Then, we consider an alternative problem where the actual data rate is replaced by its LB, which constitutes a non-convex optimization problem. First, the globally optimal solution is obtained by applying the high-complexity outer polyblock approximation (OPA) algorithm. Then we invoke the reduced- complexity modified weighted minimum mean square error (WMMSE) algorithm for mitigating the deleterious effects of realistic imperfect CSI. For the subproblem solved by each WMMSE iteration, the beamforming (BF) vectors are derived in closed form relying on the Lagrangian dual decomposition method. Finally, our simulation results show that the modified WMMSE algorithm’s performance is comparable to that of the high-complexity OPA algorithm, whilst outperforms other benchmark algorithms.
Arumugam Nallanathan
added a research item
In this paper, a security-aware energy-efficient resource allocation is modeled as a fractional programming problem for heterogeneous multi-homing networks. The security-aware resource allocation is subject to the average packet delay, the average packet dropping probability, and the total available power consumption. In order to guarantee the packet-level quality of service (QoS), first, the average packet delay and the average packet dropping probability requirement at the link layer for each mobile terminal (MT) are transformed as a minimum secrecy rate constraint at the physical layer. Then, the maximization problem is transformed into a convex problem with an equivalent epigraph form. A security-aware energy-efficient resource allocation algorithm is proposed leveraging dual decomposition method and bi-section search method. Finally, a heuristic security-aware resource allocation algorithm is proposed to serve as a benchmark. Simulation results demonstrate that the proposed security-aware energy-efficient resource allocation algorithm not only improves the secrecy energy efficiency and throughput, but also guarantees the packet-level QoS. Index Terms Heterogeneous networks, cross-layer resource allocation, tri-convex programming, packet delay, packet dropping probability. Lei Xu is at the
Arumugam Nallanathan
added a research item
The weighted sum rate maximization problem of ultra-dense cloud radio access networks (C-RANs) is considered, where realistic fronthaul capacity constraints are incorporated. To reduce the training overhead, pilot reuse is adopted and the transmit-beamforming used is designed to be robust to the channel estimation errors. In contrast to the conventional C-RAN where the remote radio heads (RRHs) coherently transmit their data symbols to the user, we consider their non-coherent transmission, where no strict phase-synchronization is required. By exploiting the classic successive interference cancellation (SIC) technique, we first derive the closed-form expressions of the individual data rates from each serving RRH to the user and the overall data rate for each user that is not related to their decoding order. Then, we adopt the reweighted l1-norm technique to approximate the l0-norm in the fronthaul capacity constraints as the weighted power constraints. A low-complexity algorithm based on a novel sequential convex approximation (SCA) algorithm is developed to solve the resultant optimization problem with convergence guarantee. A beneficial initialization method is proposed to find the initial points of the SCA algorithm. Our simulation results show that in the high fronthaul capacity regime, the coherent transmission is superior to the non-coherent one in terms of its weighted sum rate. However, significant performance gains can be achieved by the non-coherent transmission over the non-coherent one in the low fronthaul capacity regime, which is the case in ultra-dense C-RANs, where mmWave fronthaul links with stringent capacity requirements are employed. Index Terms-Ultra-dense networks (UDN), C-RAN, fronthaul capacity, pilot reuse, robust design.
Arumugam Nallanathan
added a research item
We propose a power-and rate-adaptation scheme for cloud radio access networks (C-RANs), where each radio remote head (RRH) is connected to the baseband unit (BBU) pool through optical links. The RRHs jointly support the users by efficiently exploiting the enhanced spatial degrees of freedom. Our proposed scheme aims for maximizing the effective capacity (EC) of the user subject to both per-RRH average-and peak-power constraints, where the EC is defined as the maximum arrival rate that can be supported by the C-RAN under the statistical delay requirement. We first transform the EC maximization problem into an equivalent convex optimization problem. By using the Lagrange dual decomposition method and solving the Karush-Kuhn-Tucker (KKT) equations, the optimal transmission power of each RRH can be obtained in closed-form. Furthermore, an online tracking method is provided for approximating the average power of each RRH for the sake of updating the Lagrange dual variables. For the special case of two RRHs, the expression of the average power of each RRH can be calculated in explicit form. Hence, the Lagrange dual variables can be computed in advance in this special case. Furthermore, we derive the power allocation for two important extreme cases: 1) no delay constraint; 2) extremely stringent delay-requirements. Our simulation results show that the proposed scheme significantly outperforms the conventional algorithm without considering the delay requirements. Furthermore, when appropriately tuning the value of the delay exponent, our proposed algorithm is capable of guaranteeing a delay outage probability below $10^{-9}$ when the maximum tolerable delay is 1 ms. This is suitable for the future ultra-reliable low latency communications (URLLC).
Arumugam Nallanathan
added a research item
In this paper, we investigate the downlink transmission for cache-enabled fog radio access networks aiming at maximizing the delivery rate under the constraints of fronthaul capacity, maximum transmit power, and size of files. To reduce the delivery latency and the burden on fronthaul links and make full use of the local cache and baseband signal processing capabilities of enhanced remote radio heads (eRRHs), a two-level transmission scheme including cache-level and network-level transmission is proposed. In cache-level transmission, only requested files cached at the local cache are transmitted to the corresponding users. The duration of cache-level transmission is the delay caused by the transfer between the baseband unit (BBU) and eRRHs as well as the signal processing at the BBU. The remaining requested files are jointly transmitted to the corresponding users at network-level transmission. For cache-level transmission, a centralized optimization algorithm is firstly presented and then a decentralized optimization algorithm is provided to avoid the exchange of signaling among eRRHs. Meanwhile, another centralized optimization algorithm is presented to tackle the optimization problem for network-level transmission. All presented algorithms are proved to converge to the Karush-Kuhn-Tucker (KKT) solutions of the problems. Numerical results are provided to validate the effectiveness of the proposed transmission scheme as well as evaluating the system performance. Index Terms S. He is with the
Arumugam Nallanathan
added 15 research items
In this paper, we present an energy-efficient medium access control (MAC) protocol for distributed full-duplex (FD) wireless network, termed as Energy-FDM. The key aspects of the Energy-FDM include energy-efficiency, co-existence of distinct types of FD links, throughput improvement, and backward comparability with conventional half-duplex (HD) nodes. Performance evaluation demonstrates the effectiveness of proposed protocol as a viable solution for full-duplex wireless networks.
Increasing the cell edge user throughput in the Long Term Evolution (LTE) systems is a relatively new arising research area. The requirement for higher data rates especially at cell edges is becoming ever more pressing as the advantages could help satisfy better Quality of Service (QoS) on an enduser level and mean higher profitability on the operator side. Therefore developing algorithms and techniques to mitigate the inherently increased inter-cell interference (ICI) and reduced signal to interference and noise ratio (SINR) in the cell edge is a challenge with high potential benefits and rewards. To serve the above objective, we study the downlink (DL) packet scheduling and resource allocation of an LTE system under proportional fairness (PF) with an innovated utility function and a frequency reuse factor of one. We present our joint ICI-avoiding cooperative packet scheduling algorithm and show through simulations, cell edge throughput improvements of about 40% as an exchange for a 16% decrease in cooperating cells' throughput in comparison to the results obtained under no cooperation between the evolved Node Bs (eNB).
Full-duplex small cells provide a promising solution for meeting the capacity requirements of future wireless networks. The main objective of this paper is to analyse the sum ergodic capacity of full-duplex small cells operating in heterogeneous environments. A theoretical framework is developed and closed-form approximations for sum ergodic capacity have been derived. In order to evaluate the benefits of full-duplex small cells, the proposed framework compares three distinct scenarios: full-duplex small cells with full-duplex devices, full-duplex small cells with half-duplex devices, and the conventional half-duplex heterogeneous network.
Arumugam Nallanathan
added a research item
In this paper, a video packet scheduling framework with stochastic quality of service (QoS) is proposed for cognitive heterogeneous networks based on inter-network cooperation. The video packet scheduling is subject to constraints in the available energy at each call for secondary mobile terminal (MT), the time varying channel state information (CSI) at different interfaces, the total interference power, the target call duration, and the video characteristics. The objective function maximizes the minimum lower bound of video quality. In order to solve the above video packet scheduling problem with stochastic QoS guarantee, a video packet scheduling scheme based on forward-auction theory is proposed. Then, the cumulative distribution function (CDF) for video quality is analyzed. Finally, the power allocation scheme to maximize the minimization lower bound of video quality among different secondary MTs is presented. Simulation results demonstrate the proposed video packet scheduling scheme with stochastic QoS requirement improves the video quality for secondary MT significantly.
Muhammad Nadeem Sial
added a research item
To overcome the limitations of Dedicated Short Range Communications (DSRC) with short range, non-supportability of high density networks, unreliable broadcast services, signal congestion and connectivity disruptions, Vehicle-to-anything (V2X) communication networks, standardized in 3rd Generation Partnership Project (3GPP) Release 14, have been recently introduced to cover broader vehicular communication scenarios including vehicle-to-vehicle (V2V), vehicle-to-pedestrian (V2P) and vehicle-to-infrastructure/network (V2I/N). Motivated by the stringent connection reliability and coverage requirements in V2X , this paper presents the first comprehensive and tractable analytical framework for the uplink performance of cellular V2X networks, where the vehicles can deliver its information via vehicle-to-base station (V2B) communication or directly between vehicles in the sidelink, based on their distances and the bias factor. By practically modeling the vehicles on the roads using the doubly stochastic Cox process and the BSs, we derive new association probability of the V2B communication, new success probabilities of the V2B and V2V communications, and overall success probability of the V2X communication, which are validated by the simulations results. Our results reveal the benefits of V2X communication compared to V2V communication in terms of success probability.
Muhammad Nadeem Sial
added a research item
To overcome the limitations of Dedicated Short Range Communications (DSRC) with short range, non-supportability of high density networks, unreliable broadcast services, signal congestion and connectivity disruptions, cellular vehicle-to-everything (C-V2X) communication networks, standardized in 3rd Generation Partnership Project (3GPP) Release 14, have been recently introduced to cover broader vehicular communication scenarios including vehicleto- vehicle (V2V), vehicle-to-pedestrian (V2P) and vehicle-toinfrastructure/ network (V2I/N). In C-V2X, vehicles can directly communicate over PC5 based dedicated sidelinks called direct mode or V2V communication. However, high vehicle densities may require reuse of cellular spectrum for V2V. Moreover, infrastructure mode communication through V2I/N links can augment V2V communication by enhancing communication range and reliability for enhanced safety along with consistent performance under traffic congestions. Motivated by the stringent connection reliability, spectral efficiency, and coverage requirements in CV2X, this paper presents the first comprehensive and tractable analytical framework for performance of C-V2X networks over shared V2V and cellular uplink channels, where the transmitting vehicles can deliver their information via infrastructure or direct mode, based on their distances, propagation environments and the bias factor. By practically modeling the vehicles on the roads using the doubly stochastic Cox process and the base-stations, we derive new association probabilities, new success probabilities of infrastructure and direct mode, and overall success probability of the C-V2X communication over shared channels, which are validated by the simulations results. Our results reveal the benefits of our proposed model (possibility of selecting both direct and infrastructure modes over shared channels) compared to V2V network in terms of success probability.
Muhammad Nadeem Sial
added a research item
Cell association in present day Heterogeneous Networks (HetNets) is still based on technique used by Homogeneous Cellular Networks (HCN) despite power and coverage area disparities of network nodes. In ongoing policy, both uplink (UL) and downlink (DL) association is coupled based on DL characteristics which introduces UL-DL asymmetry and cell load imbalances. Recently, decoupled cell association also known as Downlink-Uplink Decoupling (DUDe) has been introduced in 3rd Generation Partnership Project (3GPP) Release to improve uplink performance, load balancing and cell capacity. In DUDe, characteristics of both DL and UL channels can be considered. By using this concept, various theoretical UL or DL analytical decoupled access models have been proposed without giving their practical realization. In these frameworks, all network users are assumed to use DL-UL decoupled access without considering its practical utility. Existing solutions also ignore noise which may lead to practical inaccuracies. This paper proposes a novel and realistic hybrid scheme in which coupled or decoupled cell association can be selected depending upon user location and its advantages. Building upon this innovative approach, it has been established that decoupled access is opted by few users and accordingly a two-tier analysis framework for these devices have been formulated. Simple closed form solutions for user performance metrics without ignoring noise have been precisely derived which relate user performance with HetNet densities. Devised distributions are employed to compare
Muhammad Nadeem Sial
added a project goal
Analysis of 5G Heterogeneous cellular networks
 
Muhammad Nadeem Sial
added a research item
Smallcells deployment in heterogeneous networks (HetNets) introduce uplink (UL) downlink (DL) asymmetry, backhaul bottleneck, cell load imbalances, increased core network signaling, interference and mobility management problems. In order to address these issues, concept of dual connectivity has been introduced in 3rd generation partnership project (3GPP) release 12. In dual connectivity, a given user equipment can consume radio resources of at least two different network points connected through non-ideal backhaul for spectrum aggregation and cooperative access mechanisms in dense 5G HetNets. Alternatively, another concept of downlink and uplink decoupling (DUDe) has also been recently introduced in 3GPP to improve uplink performance, load balancing and cell capacity. In order to take advantage of the strengths of these latest developments, this paper significantly advances prior work by analyzing K-tier 5G HetNets having dual connectivity and decoupled access (joint DUDe dual-connectivity) for spectrum aggregation in UL and DL. In the preceding works, K-tiers as per present-day heterogeneity, uplink power control and receiver noise have not been considered for joint DUDe dual-connectivity. With the use of stochastic geometry, we have developed closed form solutions for association, coverage and outage probabilities along with average throughput for joint DUDe dual-connectivity by considering uplink power control, receiver noise and K-tiers of HetNets. The resultant performance metrics are evaluated in terms of achieved gains over conventional downlink received power access policies. Results show that cell association technique based on joint DUDe dual-connectivity can significantly improve load balancing, mobility management and UL performance for forthcoming 5G HetNets.