This paper considers joint power allocation and sub-carrier assignment (J-PA-SA) in uplink clustered multi-carrier non-orthogonal multiple-access (NOMA) networks. Specifically, the goal is to maximize the network sum-rate subject to users' minimum rate requirements. A novel network-coded (NC) many-to-one subcarrier assignment scheme is proposed to improve bandwidth utilization over the conventional one-to-one subcarrier assignment. In general, the J-PA-SA problem is non-convex and NP-hard. To efficiently solve it, it is split into two sub-problems: (1) power allocation per (user cluster, subcarrier) combination, and (2) subcarrier assignment. A solution procedure is devised to efficiently solve the J-PA-SA problem for the network-coded SA scheme. Simulation results revealed that the proposed solution procedure efficiently yields the optimal network sum-rate solution, while satisfying the minimum rate requirement per user. More importantly, the proposed network-coded SA scheme is shown to be superior to the conventional SA scheme.

This paper considers joint antenna selection and power allocation (J-AS-PA) for Alamouti space-time block coding (STBC)-based clustered non-orthogonal multiple-access (NOMA) networks. Essentially, the aim is to assign a pair of antennas to each user cluster and perform power allocation to maximize the network sum-rate, while satisfying quality-of-service requirements. However, the problem is non-convex and computationally-expensive. In turn, it is split into two sub-problems; antenna selection, and power allocation over each (user cluster, antenna pairs) combination, and then solved using a two-stage algorithm. In Stage 1, antenna selection is solved using the stable marriage matching algorithm, whereas the power allocation problem is reformulated as a concave maximization problem. In Stage 2, a swap matching algorithm is devised to ensure stability and improve the network sum-rate. Simulation results illustrate that the proposed solution procedure achieves a near-optimal network sum-rate, and is superior to the OMA-based network.

This paper considers resource allocation for network-coded clustered uplink non-orthogonal multiple-access (NOMA) networks with simultaneous wireless information and power transfer (SWIPT)-enabled relays. In particular, the goal is to perform joint power allocation, power-splitting, and relay selection (J-PA-PS-RS) to maximize the network sum-rate, subject to quality-of-service requirements. The formulated problem happens to be a non-convex and excessively complex. Thus, it is split into two sub-problems: (1) joint power allocation and power-splitting per relay, and (2) relay selection. Particularly, a solution procedure is proposed, where the joint user and relay power allocation, and power-splitting per relay is solved via a low-complexity iterative three-layer algorithm, and then followed by optimal relay selection. Simulation results have revealed that the proposed solution procedure achieves near-optimal solutions as well as being superior to the OMA-based network.

In this paper, the problem of joint relay selection, power-splitting, and power allocation (J-RS-PS-PA) for network sum-rate maximization in non-orthogonal multiple-access (NOMA)-based multicast cognitive radio networks is considered. Specifically, the primary and secondary transmitters communicate—via simultaneous wireless information and power transfer (SWIPT)-enabled relays—with their respective receivers, subject to minimum rate requirements. Due to the non-convexity (and hence the excessive computational-complexity) of the formulated problem, it is decoupled and solved via a low-complexity solution procedure over two stages: (1) J-PS-PA, and (2) RS. For the first stage, an iterative two-layer algorithm is devised to maximize the sum-rate over each relay, while in the second stage, the optimal relay is selected. Simulation results revealed that the proposed solution procedure efficiently yields near-optimal network sum-rate as well as being superior to other benchmark schemes, while satisfying the minimum rate requirements of all primary and secondary receivers.

This paper considers the problem of joint power allocation and antenna selection (J-PA-AS) for downlink clustered non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to perform antenna selection for each user cluster and allocate transmit power to its users so as to maximize the network sum-rate, while satisfying quality-of-service (QoS) requirements. The formulated problem happens to be non-convex and NP-hard, and thus, there is no computationally-efficient approach to solve it directly. In turn, a low-complexity two-stage algorithm is proposed, where the first stage optimally solves the sum-rate maximizing power allocation problem for each (antenna, user cluster) pair. In the second stage, antenna selection is optimally solved in polynomial-time complexity via the Kuhn-Munkres with backtracking (KMB) algorithm. Simulation results are provided to validate the proposed algorithm, which is shown to efficiently yield the optimal network sum-rate, and in comparison to the optimal J-PA-AS scheme (solved via a global optimization package), and superior to other benchmark schemes. The impact of spatial-diversity on the network sum-rate is also highlighted, where it is shown that the greater the number of antennas at the base-station is, the higher the network sum-rate, and the lower the outage events.

This article proposes a downlink/uplink decoupled (DUDe) access scheme for cellular-enabled unmanned aerial vehicle (UAV) communication systems. To minimize interference, the proposed scheme separates the control and data links of UAVs, as well as the uplinks (ULs) and downlinks (DLs) of ground users (GUEs), onto different serving base stations and operating frequencies. Since power availability is a major constraint in UAV communications, two power allocation schemes based on$Q$-learning (QL) and deep$Q$-learning (DQL) are proposed to optimize the communication energy efficiency (EE) of this DUDe network. To quantify the improvements achieved, the proposed schemes are compared with the fractional power control (FPC) scheme used in 4G and 5G networks, as well as a convex optimization-based optimal power allocation scheme. The results demonstrate that the proposed DUDe scheme can achieve up to several times higher sum rates and EE in the UL direction than its coupled counterparts. Moreover, it is shown that the EE performance of the QL and DQL power allocation schemes approach the optimal performance and surpass the conventional FPC scheme by 80%–100% in the UHF band, and by 160%–170% in the mmWave band.

This paper considers the optimization of a dual-functional radar and communication (RadCom) system with the objective is to maximize its sum-rate (SR) and energy-efficiency (EE) while satisfying certain radar target detection and data rate per user requirements. To this end, novel RadCom precoder schemes that can exploit downlink radar interference are devised for massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. First, the communication capacity and radar detection performance metrics of these schemes are analytically evaluated. Then, using the derived results, optimum beam power allocation schemes are deduced to maximize SR and EE with modest computational complexity. The validity of the analytical results is confirmed via matching computer simulations. It is also shown that, compared to benchmark techniques, the devised precoders can achieve substantial improvements in terms of both SR and EE.

Ultra-reliable and low-latency (UR-LL) communications are considered as a key feature in many application scenarios. Particularly, the 5th generation (5G) cellular networks are the main candidate for the implementation of UR-LL communications, by exploiting short packet transmissions. On the other hand, energy-harvesting (EH) solutions are envisaged to provide sustainable and self-sufficient green networks. In this paper, the tradeoffs between reliability and packet latency in a multi-user random access UR-LL-EH-5G network with finite blocklength codes is studied, while incorporating energy- and data-causality constraints. Analytical derivations for reliability and packet latency are provided to investigate the effect of diversity transmission, and the number of resource blocks allocated to user equipments (UEs). The derived analytical expressions are then numerically evaluated to shed light on different tradeoffs.

The global market for unmanned aerial vehicles (UAVs) has grown substantially over the past decade and has become a high point for economic growth in many countries. Hence integrating UAVs with cellular networks is considered pivotal to tapping into new business opportunities for cellular operators, especially as the smartphone market is almost saturated. In this paper, we propose a new scheme for efficiently integrating UAVs within 5G cellular systems. To this end, we separate the UAV control and non-payload communication links (CNPC) from high-capacity data communication links-by decoupling the uplink (UL) and downlink (DL) access-to allow user equipments (UEs) to connect to different base-stations (BSs) and transmit over different frequency bands in the UL and DL, such that the interference between ground UEs (GUEs) and UAVs is significantly reduced. The ground UE-BS links are also decoupled in a similar fashion to further minimize interference and maximize energy-efficiency. The numerical results validate the effectiveness of the proposed scheme and quantify the improvement in terms of the data rate of UAVs and GUEs in comparison to coupled benchmarks.

This study analyses the performance of downlink non‐orthogonal multiple‐access (NOMA) networks over independent but not necessarily identically distributed Rayleigh fading channels by deriving closed‐form expressions for the average signal‐to‐interference‐plus‐noise ratio (SINR), average achievable rate, and outage probability of all network users. Moreover, SINR‐based power allocation strategies are studied. Specifically, the optimisation problems of max–min SINR, multi‐objective SINR, sum‐SINR and proportional‐fairness‐SINR maximisation under minimum SINR constraints are formulated and shown to be non‐convex. Additionally, the problems of total power and sum‐SINR minimisation are also formulated. Particularly, the formulated problems take the form of linear‐fractional programming problems. By applying intelligent reformulation techniques, these problems have been reformulated into convex optimisation problems, and thus efficiently solved. Numerical evaluations are presented to validate the derived closed‐form expressions for the different performance metrics, which are found to be in agreement with the network simulation results. More importantly, it has been demonstrated that the user with the best channel conditions achieves full diversity order, whereas all the other users achieve diversity orders equivalent to their ordered channel conditions. Finally, the reformulated power allocation strategies are evaluated, and shown to coincide with the original problem formulations.

In this study, the problem of joint relay selection and power allocation (J‐RS‐PA) for NOMA‐based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximise the end‐to‐end SINR/SNR of the primary and secondary transmitter–receiver (TR) pairs, subject to quality‐of‐service (QoS) constraints. Communication between the primary and secondary TR pairs is performed over two‐phases, namely, the broadcasting phase, and the cooperation phase. In the broadcasting phase, the primary and secondary transmitters broadcast their data symbols; while in the cooperation phase, the selected relay forwards the decoded symbols to their intended receivers. However, the formulated J‐RS‐PA problem happens to be non‐convex, resulting in computationally‐prohibitive complexity. Consequently, an optimal low‐complexity two‐stage relay selection and power allocation (TS‐RS‐PA) algorithm is devised, which is based on the solution of linear programming problem reformulations. Simulation results are presented to validate the proposed TS‐RS‐PA algorithm, which is shown to yield the optimal SINR/SNR values in comparison to the J‐RS‐PA scheme, but with lower computational complexity, while satisfying QoS constraints.

This paper studies the problem of stable node matching for distributed simultaneous wireless information and power transfer in multi-user amplify-and-forward (AF) ad-hoc wireless networks. Particularly, each source node aims to be paired with another node that acts an AF relay to forward its signal to the destination, such that the achievable rate is improved, in return for some payment. In turn, a matching-theoretic solution based on the one-to-one Stable Marriage Matching game is considered, and a distributed polynomial-time complexity algorithm is proposed to pair each source node with its best potential relaying node based on the power-splitting ratios. Simulation results are presented to validate the proposed matching algorithm, and show that it yields sum-utility and sum-payment that are comparable to those of centralized schemes, with the added merits of low-complexity, and network stability.

In this paper, the problem of joint subcarrier assignment and weighted-sum energy-efficient power allocation (J-SA-WSEE-PA) in multi-carrier uplink NOMA relay networks is considered. Specifically, the aim is to assign subcarriers to network users, while maximizing the weighted-sum energy-efficiency, subject to quality-of-service (QoS) constraints. The J-SA-WSEE-PA problem is shown to be non-convex, and thus is computationally-intensive. In turn, it is split into two subproblems: (1) WSEE maximizing power allocation per subcarrier, and (2) matching-theoretic subcarrier assignment. For the first sub-problem, a low-complexity iterative solution procedure is devised to optimally solve the WSEE-maximizing power allocation problem per subcarrier. As for the second sub-problem, a linear time-complexity stable matching algorithm based on the hospitals-residents matching problem is proposed to assign subcarriers to network users. Simulation results are presented to validate the devised solution procedure and the proposed stable matching algorithm, where it has been shown they yield comparable network sum energy-efficiency to the J-SA-WSEE-PA scheme, while satisfying QoS constraints.

In this paper, the problem of joint relay selection and power allocation (J-RS-PA) for NOMA-based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximize the SINR/SNR of the primary and secondary transmitter-receiver (TR) pairs, subject to quality-of-service (QoS) constraints. Communication between the primary and secondary TR pairs is performed over two-phases, namely, the broadcasting phase, and the cooperation phase. In the broadcasting phase, the primary and secondary transmitters broadcast their data symbols to the intermediate relays; while in the cooperation phase, the selected relay forwards the decoded symbols to their intended receivers. However, the J-RS-PA problem happens to be non-convex (i.e. computationally-prohibitive). Alternatively, an optimal low-complexity two-stage relay selection and power allocation (TS-RS-PA) algorithm is devised, which is based on the solution of intelligent linear programming problem formulations. Simulation results are presented to validate the proposed TS-RS-PA algorithm, which has been shown to yield the optimal SINRlSNR values for the primary and secondary TR pairs in comparison to the J-RS-PA scheme, but with lower computational complexity, while satisfying QoS constraints.

In this paper, the problem of joint relay selection and global energy-efficient power allocation in energy-harvesting cooperative non-orthogonal multiple-access (NOMA) networks is studied. In particular, a base-station communicates with multiple users via a selected energy-harvesting relay, such that network global energy-efficiency (GEE) is maximized, subject to quality-of-service (QoS) constraints. To that end, the problem of joint-relay selection and global energy-efficient power allocation (J-RS-GEE-PA) is formulated, which happens to be non-convex (i.e. computationally-expensive). In turn, the J-RS-GEE-PA problem is decoupled into two sub-problems: (1) relay selection, and (2) GEE power allocation. Different relay selection schemes are explored, and then a computationally-efficient algorithm is devised to optimally solve the GEE power allocation problem for the selected relay. In addition, a low-complexity solution procedure is proposed to solve the J-RS-GEE-PA problem, so as to achieve the global optimal solution. Simulation results are presented to evaluate the resulting network GEE for the different relay selection schemes, and the proposed solution procedure. More importantly, the proposed solution procedure is shown to yield the optimal network GEE when compared to the J-RS-GEE-PA, and superiority to the other relay selection schemes, while maintaining QoS.

This paper studies device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for the interference caused by pairing users with D2D groups. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. Then, a polynomial-time complexity stable matching algorithm is proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithm, and compare it to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. The proposed algorithm is shown to efficiently yield comparable SINR-per user and D2D receiver-to the J-GA-CA-PA scheme, while maintaining QoS requirements.

This paper considers joint relay selection and maxmin energy-efficient power allocation (J-RS-MMEE-PA) in downlink multi-cell non-orthogonal multiple-access (NOMA) networks. Particularly, the aim is to perform relay selection for each user within each cell, so as to achieve max-min energy-efficiency, while satisfying quality-of-service (QoS) constraints. However, the J-RS-MMEE-PA problem happens to be non-convex (i.e. computationally-intensive). In turn, a solution procedure for maxmin energy-efficient power allocation is devised to determine the energy-efficiency per potential relay, while meeting the target minimum rate per user. After that, the relay selection problem is modeled as a student-project allocation with preferences over projects matching problem, where a polynomial-time complexity stable matching algorithm is proposed to pair users with relays within each cell. Simulation results are presented to validate the proposed stable matching algorithm, where it is demonstrated that it efficiently yields comparable energy-efficiency per user to the J-RS-MMEE-PA scheme, while satisfying QoS constraints.

This paper studies joint device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. Particularly, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for negative network externality due to the interference caused by pairing a user with a D2D group. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. More specifically, two polynomial-time complexity stable matching algorithms are proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithms when combined with the devised solution procedure, and compare them to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. More importantly, the proposed algorithms are shown to efficiently yield comparable SINR-per user and D2D receiver-to the J-GA-CA-PA scheme, while maintaining QoS requirements.

In this paper, the problem of distributed multirelay selection in energy-harvesting cooperative wireless networks is studied and modeled as an Indian Buffet Game (IBG). Particularly, the IBG is utilized to model the multi-relay selection decisions of network source nodes, while taking into account the negative network externality. Since the relays are energy-harvesting (and thus intermittently harvest random amounts of energy), the accumulated energy at each relay is unknown to the source nodes, leading to uncertain relays' energy states. In turn, a non-Bayesian learning algorithm is devised for source nodes to learn the relays' energy states. After that, a distributed best-response multi-relay selection (BR-MRS) recursive algorithm is proposed to allow source nodes to make multi-relay selections, while guaranteeing subgame perfect Nash equilibrium. Simulations results are presented to verify the efficacy of the proposed algorithm when compared to other multi-relay selection schemes, and illustrate that it yields comparable rate improvement (and utility) to the centralized multi-relay selection.

This paper analyzes the performance of downlink non-orthogonal multiple-access (NOMA) networks over independent but not necessarily identically distributed Rayleigh fading channels for arbitrary number of network users. Specifically, closed-form expressions for the average SNR, average achievable rate, and outage probability are derived, where it has been shown that network users achieve diversity orders equivalent to their ordered channel gains. Numerical evaluations are presented to validate the derived closed-form expressions for the different performance metrics, which are found to be in agreement with the network simulation results.

This paper studies power allocation and relay selection strategies in energy harvesting cooperative wireless networks for end-to-end signal-to-noise ratio (SNR) maximization. Energy cooperation via wireless energy transfer is also considered to efficiently utilize harvested energy. Particularly, different optimal strategies are formulated as optimization problems, which are non-convex. Intelligent transformations are applied to transform non-convex problems into convex ones, and polynomial-time solution procedures are proposed. Simulation results illustrate that power allocation strategies achieve higher end-to-end SNR than relay selection ones. Finally, energy cooperation is shown to be effective in improving the end-to-end SNR.

In this paper, power allocation over time-varying multi-user multi-relay amplify-and-forward networks is studied. Specifically, stochastic network sum-rate and max-min rate power allocation problems are formulated. However, solving such stochastic problems relies on perfect global instantaneous channel state information (CSI), and thus entails complex computations and excessive communication overheads. To circumvent these issues, second-order statistics of the CSI (i.e. partial CSI) are utilized to transform the stochastic formulations into deterministic optimization problems in terms of ergodic capacity while satisfying quality-of-service constraints via target outage probability. The obtained optimal deterministic problems are non-convex and thus are computationally prohibitive. However, at high enough signal-to-noise ratio, such problems can be transformed into asymptotically convex ones, and thus solved efficiently. Simulation results illustrate that the proposed approximate deterministic power allocation reformulations coincide with their optimal exact deterministic and dynamic counterparts.

This paper proposes a resource allocation technique for distributed and uncoordinated femtocell networks. We focus on enhancing the Quality of Service (QoS) and throughput by relying only on feedback from the base-station's (BS) users in addition to locally estimated information from the surrounding environment. A novel algorithm is developed to analyze the uplink (UL) interference in order to estimate the number of neighboring users in the vicinity of a femtocell without requiring any information exchange with a central unit or neighboring femtocells. The downlink inter-cell interference is reduced by utilizing the variability in the interference conditions of femtocells and restricting the resource usage of individual cells based on the detected nearby users. The performance of the algorithm is evaluated and compared with state-of-art techniques and benchmarks. The simulation results show that the proposed scheme outperforms other techniques and can provide an improvement in the QoS and overall performance. and overall performance.

In this paper, we present a power allocation technique that improves the sum rate and energy efficiency without reducing the minimum data rate of an established resource block allocation technique. To achieve this, the technique is implemented in two stages where the first is for ensuring that the minimum data rate remains unchanged. The second stage is for increasing the sum rate by ensuring that more resource blocks are reused by the femtocells that reduce their power. The algorithm is iterative with changes in transmit power resulting in changes in resource block allocation. It will be shown that at the expense of some delay, the proposed technique can result in significant energy savings while maintaining the minimum data rate when compared to equal power allocation. Further, relative to optimal allocation techniques, the proposed technique results in better fairness.

In this paper, the problem of distributed multi-relay selection in cooperative wireless networks is studied via a political coalition formation game approach. Specifically, a sum-rate maximizing distributed coalition formation algorithm is proposed, in which a winning coalition eventually emerges, which is also self-enforcing (and hence stable). In addition, the proposed algorithm offers a sum-rate performance/stability tradeoff through formation of political parties, which also reduces complexity and overheads. The proposed algorithm is compared with centralized multi-relay selection as well as other multi-relay selection algorithms from literature, and is shown to provide comparable network sum-rate with the added advantage of network stability.

In this paper, power allocation over time-varying multiple-access interference channels is studied. Particularly, a stochastic network sum-rate maximizing power allocation problem is formulated, capturing the random nature of communication channels. Typically, a centralized controller must have perfect knowledge of global instantaneous channel state information (CSI) for dynamic optimal power allocation; however, this may not be possible, due to the computational complexity and communication overheads/delays involved. Based on the second-order statistics of the CSI, the stochastic problem formulation is transformed into an optimal deterministic representation in terms of ergodic capacity, while ensuring satisfactory quality of service via target outage probability. However, such deterministic reformulation happens to be non-convex and thus is computationally expensive. In turn, a sub-optimal reformulation is derived and solved via an iterative low-complexity algorithm. Simulation results demonstrate that the proposed deterministic sub-optimal power allocation reformulation coincides with its optimal deterministic counterpart, with the proposed algorithm converging in a finite number of iterations.

In this study, power allocation over time‐varying multi‐user multi‐relay amplify‐and‐forward networks is studied. Specifically, stochastic network sum‐rate, max–min rate power allocation and total power minimisation problems are formulated. However, solving such stochastic problems relies on perfect global instantaneous channel state information (CSI), and thus entails complex computations and excessive communication overheads. To circumvent these issues, second‐order statistics of the CSI (i.e. partial CSI) are utilised to transform the stochastic formulations into deterministic optimisation problems in terms of ergodic capacity while satisfying quality‐of‐service constraints via target outage probability. The obtained optimal deterministic problems are non‐convex and thus are computationally prohibitive. However, at high enough signal‐to‐noise ratio, such problems can be transformed into asymptotically convex ones, and thus solved efficiently. Simulation results illustrate that the proposed approximate deterministic power allocation reformulations closely agree with their optimal exact deterministic and dynamic counterparts.

Abstract In this paper, optimal power allocation and relay selection strategies in energy harvesting cooperative wireless networks are studied. In particular, signal‐to‐noise ratio (SNR)‐maximizing based power allocation and relay selection without and with energy cooperation—via wireless energy transfer—are considered. Moreover, total relay power minimization subject to target end‐to‐end SNR is investigated. The different optimal strategies are formulated as optimization problems, which are non‐convex. Thus, intelligent transformations are applied to transform non‐convex problems into convex ones, and polynomial‐time solution procedures are proposed. Simulation results illustrate that power allocation strategies achieve higher end‐to‐end SNR than relay selection ones. Finally, energy cooperation is shown to be effective in improving end‐to‐end SNR, while total relay power minimization balances end‐to‐end SNR, transmit power consumption, and harvested energy. Copyright © 2016 John Wiley & Sons, Ltd.

ABSTRACT In this paper, distributed single relay selection in cooperative wireless networks is modeled as a Chinese restaurant game (CRG). Specifically, the CRG is used to model strategic relay selection decisions of source nodes, taking into account negative network externality due to the potential sharing of relay nodes among source nodes. Two cases are studied as follows: (i) perfect relay transmit power (RTP) knowledge and (ii) imperfect RTP knowledge. Under the first case, a distributed relay selection algorithm is proposed and shown to converge to a Nash equilibrium grouping. Under the second case, a reinforcement learning algorithm is proposed and combined with the distributed relay selection algorithm to allow network nodes to select rate‐maximizing relays. Simulation results verify the efficiency of the proposed distributed relay selection algorithm when compared with other relay selection schemes and demonstrate that it yields a network sum‐rate that is comparable with that of centralized relay selection. Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, the problem of stable energy-efficient partner selection in cooperative wireless networks is studied. Each node aims to be paired with another node so as to minimize the total energy consumption required to meet a target end-to-end SNR requirement and thus maintain quality-of-service (QoS). Specifically, each node ranks every other node in the network according to their energy saving achievable through cooperation. Two polynomial-time algorithms based on the stable roommates matching problem are proposed through which nodes are paired according to their preference lists. The first algorithm, denoted Irving's stable matching (ISM), may not always have a stable solution. Thus, the second algorithm, denoted maximum stable matching (MSM), is proposed to find the maximum number of stable pairs. Simulation results validate the efficiency of the proposed algorithms in comparison with other matching algorithms, yielding a tradeoff between stability and total energy consumption.

In this paper, the problem of multi-relay selection in one-to-many cooperative wireless networks is studied via a political coalition formation game approach. Specifically, each relay node is endowed with some coalitional strength, and the selected coalition consists of a subset of the available relays in the network that is powerful enough to win against any other potential coalition. In addition, the formed “ruling” coalition must be self-enforcing (and hence stable) such that none of its members would split and become the new ruling coalition. A distributed ruling coalition formation algorithm is proposed that selects such stable set of relays with a marginal compromise on network sum-rate performance. Moreover, our proposed algorithm offers a network sum-rate performance/stability tradeoff through formation of political parties of relays, which also reduces complexity and communication overheads. The proposed algorithm is compared with centralized multi-relay selection, as well as other multi-relay selection algorithms from the literature, and is shown to provide comparable network sum rate with the added advantage of network stability.

In this paper, distributed relay selection in cooperative wireless networks is modeled as a Chinese restaurant game (CRG). Specifically, the CRG is used to model strategic relay selection decisions of source nodes, taking into account negative network externality due to the potential sharing of relay nodes among source nodes. In turn, a distributed relay selection algorithm is proposed and shown to converge to a Nash Equilibrium grouping. Simulation results verify the efficiency of the proposed distributed algorithm when compared with other relay selection schemes, and demonstrate that it yields a network sum-rate that is comparable with that of centralized relay selection.

A game‐theoretic framework based on the iterated prisoner's dilemma (IPD) is proposed to model the repeated dynamic interactions of multiple source nodes when communicating with multiple destinations in an ad hoc wireless network. In such networks where nodes are autonomous, selfish and not familiar with other nodes’ strategies, fully cooperative behaviours cannot be assumed. Therefore reinforcement learning is studied to relate the utility function of each source node to actions previously taken in order to learn a strategy that maximises their expected future reward. Particularly, a Q‐learning algorithm is proposed to allow network nodes to adapt to and play the IPD game against opponents with a variety of known and unknown strategies. Simulation results illustrate that the proposed Q‐learning algorithm allows network nodes to play optimally and achieve their maximum expected return values.

In this paper, a game-theoretic framework based on the iterated prisoner's dilemma (IPD) is proposed to model the repeated dynamic interactions of multiple source nodes when communicating with multiple destinations in ad-hoc wireless networks. In such networks where nodes are autonomous, selfish, and not familiar with other nodes' strategies, fully cooperative behaviors cannot be assumed. Thus, a Q-learning algorithm is proposed to allow network nodes to adapt to and play the IPD game against opponents with a variety of known and unknown strategies. Simulation results illustrate that the proposed Q-learning algorithm allows network nodes to play optimally and achieve their maximum expected return values.

In this paper, altruistic coalition formation in cooperative relay networks is studied. The communication is performed over two phases, the broadcasting phase and the cooperation phase. In the broadcasting phase, each node broadcasts its signal in its time-slot, while in the cooperation phase, all the nodes within their coalitions simultaneously relay each others' signals. A distributed merge-and-split algorithm is proposed to allow nodes to form coalitions and improve their total achievable rate. Moreover, the impact of different power allocation criteria is studied, where the sum-of-rates maximizing power allocation is shown to promote altruistic coalition formation and results in the largest coalitions among the different power allocation criteria. Finally, the proposed algorithm is compared with centralized power allocation and coalition formation, and shown to yield a good tradeoff between network sum-rate and computational complexity.

In this paper, a comparative study of network-coded bi-directional amplify-and-forward (BD-AF) relaying is presented. In bi-directional relay networks, communication is performed over two phases: the broadcasting phase, and the cooperation phase. In the broadcasting phase, both source nodes broadcast their signals simultaneously to the N relay nodes, while in the cooperation phase, transmission is based on one of two modes: (1) time-division (TD), or (2) multiple-access (MA). In the TD-BD-AF scheme, each relay node is allocated a time-slot to transmit its processed signal, while in the MA-BD-AF scheme, all the N relay nodes simultaneously transmit network-coded signals to both source nodes, in a single time-slot. Moreover, a suboptimal relay selection (i.e. SRS-BD-AF) that approximately maximizes the sum-of-rates is proposed. Optimal and suboptimal sum-of-rates maximizing power allocations are studied under the TD-BD-AF and MA-BD-AF schemes, respectively, where it is shown that the MA-BD-AF scheme reduces to the SRS-BD-AF scheme. Symbol error rate performance analysis is provided, where it is shown that both the TD-BD-AF and SRS-BD-AF schemes achieve full diversity. Imperfect timing synchronization is analyzed and it is demonstrated that the SRS-BD-AF outperforms the other schemes in terms of the achievable rate. Simulation results are provided to complement the theoretical analysis.

In this paper, a performance analysis of network-coded bidirectional amplify-and-forward (BD-AF) multi-relay networks is presented. In such networks, communication is performed over two phases: the broadcasting phase, and the cooperation phase. In the broadcasting phase, both source nodes broadcast their signals simultaneously to the intermediate JV relay nodes. The cooperation phase is based on one of two schemes: (1) multiple-access (MA) and (2) single relay selection (RS) transmission. In the MA-BD-AF scheme, all N relay nodes simultaneously transmit linearly coded signals to both source nodes. A simple suboptimal relay selection scheme (i.e. SRS-BD-AF) is proposed such that the relay that maximizes the sum-of-rates is selected to transmit its network coded signal to both source nodes. Finally, a suboptimal sum-of-rates maximizing relay power allocation under the MA-BD-AF scheme is formulated and shown to reduce to the SRS-BD-AF scheme. Also, a symbol error rate performance analysis is provided, where it is shown that the SRS-BD-AF scheme achieves full diversity. Simulation results are provided to complement the theoretical analysis.

In this paper, the impact of cooperative power allocation on distributed altruistic coalition formation in cooperative relay networks is studied. Particularly, equal power allocation (EPA), maxmin rate (MMR) and sum-of-rates maximizing (SRM) power allocation criteria are considered. A distributed merge-and-split algorithm is proposed to allow network nodes to form coalitions and improve their total achievable rate. The proposed algorithm is compared with that of centralized power control and coalition formation, and is shown to yield a good tradeoff between network sum-rate and computational complexity. Finally, numerical results illustrate that the SRM power allocation criterion promotes altruistic coalition formation and results in the largest coalitions among the different power allocation criteria.

In this paper, power allocation for multi-source multi-relay cooperative wireless networks is considered. An ascending-clock auction algorithm is proposed to efficiently allocate cooperative relay power among multiple source nodes in a distributed fashion. In particular, each source node reports its optimal power demand to each relay node based on the relays' announced prices. It is proven that the proposed auction algorithm enforces truthful power demands and converges in a finite number of time-steps to the unique Walrasian Equilibrium allocation that maximizes the sum of utilities. Numerical results are presented to supplement the theoretical analysis and demonstrate the efficiency of the proposed distributed relay power allocation algorithm.

In a wireless network with multiple amplify-and-forward (AF) nodes, the many-to-many cooperative communication is achieved through the novel concept of space-time network coding with optimal node selection (STNC-ONS). The communication under the STNC-ONS scheme is split into two phases: 1) the broadcasting phase (BP) in which each node in its allocated time-slot broadcasts its data symbol to all the other nodes in the network, and 2) the cooperation phase (CP) in which the optimal node corresponding to each desired data symbol is selected for relaying it to the destination node in its own time-slot. The optimal node selection is based on the maximum harmonic mean value of the source, intermediate, and destination nodes' scaled instantaneous channel gains. An approximate symbol-error-rate (SER) expression for M-ary phase shift keying (M-PSK) modulation is derived along with an upper bound SER approximation which is shown to be asymptotic at high signal-to-noise ratio. The derived analytical expressions verify that for a network of N nodes, a full diversity order of (N - 1) per node is achieved by the STNC-ONS scheme. It is concluded that the STNC-ONC scheme is a potential many-to-many cooperative communication scheme with applications spanning sensor and mobile wireless networks.

In this paper, multi-source multi-relay power allocation in cooperative wireless networks is considered. An ascending-clock auction is proposed to efficiently allocate cooperative relay power among multiple source nodes in a distributed fashion. In particular, each source node reports its optimal power demand to each relay node based on the relays' announced prices. It is proven that the proposed auction algorithm enforces truthful power demands and converges in a finite number of time- steps to the unique Walrasian Equilibrium allocation that maximizes the social welfare. Numerical results are presented to supplement the theoretical analysis and demonstrate the efficiency of the proposed distributed relay power allocation algorithm.

In this paper, a distributed efficient power allocation game-theoretic framework in wireless ad-hoc networks is proposed where multiple source nodes communicate with a single destination node via a relay node. The power allocation among the source nodes is formulated as an alternative ascending-clock auction (A-ACA) and achieved using a distributed algorithm that converges in a finite number of clocks and is proven to enforce truthful power demands at every clock and maximize the social welfare. Analytical and numerical results are presented to verify the efficient power allocation, truth-telling and social welfare maximization properties of the proposed A-ACA. It is concluded that the proposed A-ACA lends itself to practical implementation in wireless ad-hoc networks.

In this paper, the mutual cooperative communication between multiple nodes in a wireless network is efficiently achieved through a novel concept of Space-Time Network Coding (STNC). Unlike the conventional point-to-point cooperative communications between two nodes with N relay nodes deployed in between, simultaneous transmissions from the different N nodes acting as source/relay nodes are performed within 2N time-slots. In particular, the communication is split into two phases: 1) Broadcasting Phase and 2) Cooperation Phase. In the Broadcasting Phase, each node broadcasts its data symbol to the other nodes in the network in its own time-slot, alternatively; while in the Cooperation Phase, in each time-slot, a set of (N-1) nodes transmit while a single destination node receives the other nodes' transmissions. Specifically, each node employing a selective Decode-and-Forward (DF) cooperative protocol, performs a linear combination of the other nodes data symbols and all the (N-1) nodes simultaneously transmit their signals to a single receiving node; which then performs joint multiuser detection to separate the different nodes' symbols. Exact symbol-error-rate (SER) expressions for arbitrary order M-ary Phase Shift Keying (M-PSK) modulation are derived. In addition, an asymptotic SER approximation is also provided which is shown to be tight at high signal-to-noise ratio (SNR). Finally, the analytical results confirm that for a network of N nodes, a full diversity order of (N-1) per node is achieved by the proposed STNC cooperative communication scheme.

In this paper, a binary hypothesis distributed detection problem in correlated wireless sensor networks with cooperative relays deployment is considered. In particular, the effect of correlation between sensor nodes is modeled and analyzed in Rayleigh flat fading channels in order to explore the natural tradeoffs between the number of sensor/relay nodes and the detection error performance in the network. Specifically, two communication protocols are utilized; in protocol I, each sensor node communicates its observation directly to the fusion center while in protocol II, amplify-and-forward (AF) cooperative relays are deployed and a fewer number of sensors is used. Based on the theoretical analysis and simulations, it is revealed that employing less sensor nodes and instead deploying relay nodes results in significant performance gains under strict network power constraint It is concluded that with cooperative distributed detection and exploitation of spatial diversity, better detection error performance is achieved as well as reduction in the required number of sensor nodes.

In this paper, we investigate the application of a unipolar non-coherent M-ary orthogonal keying (NC-MOK) for OFDM system that does not require channel estimation and compare its performance with that of bipolar Coherent MOK where for the latter phase information is obtained via pilot-based channel estimation. The performance of the orthogonal M-ary schemes concatenated with Reed-Solomon (RS) codes is investigated over Rayleigh frequency selective and fast time-varying fading channels characterized by high Doppler spreads. Simulation results for the unipolar non-coherent MOK compared with its bipolar coherent counterpart show that the non-coherent MOK performs significantly better in terms of packet error rate at high vehicle velocities. With NC-MOK, a performance gain is achieved as well as a simpler receiver implementation.

The use of pilot signals for the purpose of channel estimation in multicarrier systems does not only consume bandwidth but also signal power that could otherwise be invested in the information symbols to be transmitted. The aim of this paper is to investigate the issue of optimal transmitter power distribution between the pilot and information signals and evaluate its impact on the performance of multicarrier systems. It will be shown that the optimal power distribution is primarily influenced by the ratio of number of pilots to the total number of subcarriers used. An optimal pilot power allocation as a function of this ratio will be proposed for both MPSK and MQAM systems taking into account channel estimation errors