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The application of non-orthogonal multiple access (NOMA) to multi-layer multicast video streaming is envisioned to address the explosively growing demand for capacity which is dominated mostly by multimedia content. In this paper, a joint power allocation and subgrouping scheme is developed to enhance the performance of NOMA-based multi-layer multicast systems. An optimization problem is formulated to maximize the overall sum multicast rate whilst satisfying the maximum transmission power and proportional rate constraints. Due to the complexity of the optimization problem, we first derive two power allocation techniques for the 2-layer case considering arbitrary subgrouping which are based on the iterative implementation and closed-form analysis, respectively. We then generalize the low-complexity closed-form solution for the general multi-layer case. This scheme successively allocates power to each layer stream while assuring that the minimum target rate and proportionality are guaranteed, particularly for the transmission rate of the high-priority base layer stream. A sub-optimal joint power allocation and subgrouping scheme is also designed by incorporating the power allocation scheme into the proposed iterative subgrouping techniques. Simulation results show the effectiveness of the power allocation and subgrouping schemes in enhancing the sum multicast rate performance. In addition, the proposed power allocation scheme ensures substantially higher rates for the base layer stream, which is crucial in robust delivery of standard quality video to all users. [ABSTRACT FROM AUTHOR]

With low-cost energy consumption, the reconfigurable intelligent surface (RIS) technique is a potential solution to the real-time data processing for intelligent transportation systems (ITSs). In this paper, an intelligent transmissive surface is introduced into the vehicular communications, enabling vehicle-to-infrastructure (V2I) signals to penetrate the intelligent RIS to access the base station (BS) on the opposite side of the vehicle. Considering that the vehicle-to-vehicle (V2V) communication reuses the spectrum spanned for V2I link, we investigate the ergodic capacity optimization problem for the vehicle performing V2I communications with the assistance of RIS, while meeting the low-latency and high-reliability requirements of the V2V link. The RIS transmission coefficients and power allocation of vehicles are jointly optimized, for the management of the desired and undesired vehicular communication links. Moreover, the expression of optimal phase shifts is derived in a closed-form, which reveals that the performance gain brought by RIS is proportional to the number of intelligent elements, while inversely proportional to the distance from vehicle-to-BS, in a quadratic form. Moreover, in the case of discrete phase shifts, an intelligent algorithm is proposed for the beamforming design at RIS. Afterwards, with the objective to maximize the ergodic capacity of the V2I link, the optimal power allocation is also proposed. Simulation results confirm the accuracy of the proposed resource allocation strategy, and that the system performance in terms of the ergodic V2I capacity can be significantly improved by the RIS. [ABSTRACT FROM AUTHOR]

In this paper, we consider an energy efficient resource allocation technique for a hybrid time division multiple access (TDMA) - non-orthogonal multiple access (NOMA) system. In such a hybrid system, the available time for transmission is divided into several sub-time slots, and a sub-time slot is allocated to serve a group of users (i.e., cluster). Furthermore, signals for the users in each cluster are transmitted based on the NOMA approach. With NOMA, multiple users can be served simultaneously through utilizing power domain multiplexing at transmitter and successive interference cancellation (SIC) at receiver. In this paper, to maximize the energy efficiency (EE), we jointly allocate both the available time slots and the available transmit power in the hybrid TDMA-NOMA system. In particular, we formulate an EE maximization (EE-Max) problem aiming to maximize the overall EE of the system with a per-user minimum rate and transmit power constraints. However, this joint optimization problem is non-convex in nature, and thus, cannot be solved directly. Therefore, we develop an iterative algorithm by approximating the original problem into a convex one with sequential convex approximation (SCA) and a novel second-order cone (SOC) approach. Simulation results demonstrate that the performance of the proposed hybrid TDMA-NOMA system with joint resource allocation outperforms the system with equal time allocation in terms of the overall EE. Simulation results further confirm that the proposed iterative approaches with SCA and SOC techniques converge within a few number of iterations while yielding the solution to the original non-convex problem. [ABSTRACT FROM AUTHOR]

Efficient connectivity in cellular-connected unmanned aerial vehicles (UAV)s is limited by scarcity of the radio spectrum and strong inter-cell interference (ICI). To address these issues, we propose an aerial-terrestrial network non-orthogonal multiple access (ATN-NOMA) scheme. In this proposed scheme, we pair the aerial user (AU) and terrestrial user (TU) in a NOMA setting to leverage their asymmetric channel gains and rate demands in downlink communications. In ATN-NOMA, the strong ICI issue at the AU receiver is further managed by an elevation-angle based user association, equipping the AU with an adjustable beamwidth directional antenna, and forming a beamforming among the coordinated terrestrial base stations (BS)s. We then obtain the optimal beamwidth and suboptimal power allocation so that the TUs’ sum-rate is maximized subject to the AU’s Quality-of-Service (QoS) requirement. The corresponding optimization problem is non-convex in which we exploit the structure of the problem and apply successive convex approximation (SCA) to obtain a suboptimal solution. We then derive the statistical properties, which consequently enable us to estimate the aggregated ICI. In cases where no interfering BSs have the same elevation angle as the coordinated BSs, we further approximate the AU’s outage probability. We then compare the TUs’ sum-rate and the outage probability of the ATN-NOMA with multiple existing schemes. Extensive simulation results show that our proposed ATN-NOMA scheme outperforms existing schemes by 52-91% in terms of the sum-rate, and its analytical outage probability can be as low as the order of $10^{-17}$. Furthermore, we show that the pairing of AU and TU in multi-cell networks remains beneficial, subject to effective mitigation of ICI. [ABSTRACT FROM AUTHOR]

The combination of time division multiple access (TDMA) and non-orthogonal multiple access (NOMA), referred to as hybrid TDMA-NOMA system, is considered as a potential solution to meet the unprecedented requirements for future wireless networks. While recent resource allocation techniques aiming to individually maximize either spectral efficiency (SE) or energy efficiency (EE), this paper considers an SE-EE trade-off based technique for a hybrid TDMA-NOMA system. This design offers an additional degree of freedom in resource allocation. The proposed design is formulated as a non-convex multi-objective optimization (MOO) problem. The MOO framework is reformulated as a single-objective optimization (SOO) problem by combining the multi-objectives through a weighted-sum objective function. With this, each of the original objectives is assigned with a weight factor to reflect its importance in the design. Then, the sequential convex approximation (SCA) and a second-order cone (SOC) approach are jointly utilized to deal with the non-convexity issues of the SOO problem. Simulation results reveal that the proposed trade-off based design strikes a good balance between the objective functions, while meeting the instantaneous requirements of the system. [ABSTRACT FROM AUTHOR]

This paper investigates a novel joint content caching and energy harvesting scheme to enhance unmanned aerial vehicle (UAV) communications in Internet of Things non-orthogonal multiple access (NOMA) network, where a UAV is acted as an aerial relay to serve users on demand. In particular, a neoteric gravitational search-based multi-constraint optimization algorithm is designed to maximize the throughput of the served users by jointly optimizing power allocation, energy harvesting, and time scheduling schemes. The algorithm engages two main characteristics: 1) classification of multiple constraints, which is for reducing the complexity of the problem solving process due to multiple iterations, and 2) design of force sets, which aims to enhance the global search for the optimal solution at the feasible region boundary. Finally, simulations are provided to show the effective convergence and superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The combination of non-orthogonal multiple access (NOMA) and intelligent reflecting surface (IRS) is an efficient solution to significantly enhance the energy efficiency of the wireless communication system. In this paper, a downlink multi-cluster NOMA network is considered, where each cluster is supported by one IRS. This paper aims to minimize the transmit power by jointly optimizing the beamforming, the power allocation and the phase shift of each IRS. The formulated problem is non-convex and challenging to be solved due to the coupled variables, i.e., the beamforming vector, the power allocation coefficient and the phase shift matrix. To address this non-convex problem, an alternating optimization based algorithm is proposed. Specifically, the primal problem is divided into two subproblems for beamforming optimization and phase shifting feasiblity, where the two subproblems are solved iteratively. Moreover, to guarantee the feasibility of the beamforming optimization problem, an iterative algorithm is proposed to search the feasible initial points. To reduce the complexity, a simplified algorithm based on partial exhaustive search for this system model is also proposed. Simulation results demonstrate that the proposed alternating algorithm can yield a better performance gain than the partial exhaustive search algorithm, NOMA with random IRS phase shift scheme and OMA-IRS scheme. [ABSTRACT FROM AUTHOR]

This paper investigates unmanned aerial vehicle (UAV) data collection systems with different multiple access schemes, where a rotary-wing UAV is dispatched to collect data from multiple ground nodes (GNs). Our goal is to maximize the minimum UAV data collection throughput from GNs for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) transmission, subject to the energy budgets at both the UAV and GNs, namely double energy limitations. 1) For OMA, we propose an efficient algorithm by invoking alternating optimization (AO) method, where each subproblem is alternately solved by applying successive convex approximation (SCA) technique. 2) For NOMA, we first handle subproblems with fixed decoding order using SCA technique. Then, we develop a penalty-based algorithm to solve the decoding order design subproblem. Numerical results show that: i) The proposed algorithms are capable of improving the max-min throughput performance compared with other benchmark schemes; and ii) NOMA yields a higher performance gain than OMA when GNs have sufficient energy. [ABSTRACT FROM AUTHOR]

To support ultra-reliable and low-latency communication (URLLC) in vehicular networks, the virtual cells, where multiple access points (APs) cooperatively serve one mobile node, have been proposed to reduce the end-to-end latency in the downlink. The latency can be further reduced by eliminating the need for retransmission and feedback control, i.e., open-loop communications. However, it is difficult to achieve a high reliability of the uplink via virtual cells, because of multiple access interference and collisions from other virtual cells nearby. In this paper, we formulate the proactive radio resource allocation in the open-loop uplink of vehicular networks as a stochastic optimization problem with the objective to maximize the uplink reliability while ensuring the network stability. The optimal resource allocation policies are obtained solving the optimization problem using the Lyapunov optimization technique in a distributed manner. To reduce the computational and to improve the challenges of the Lyapunov optimization, we propose a virtual resource slicing algorithm that maps radio resource units to virtual resource blocks. Simulation results exhibit that both ultra-low latency and ultra high reliability are guaranteed in the open-loop uplink of vehicular networks. Based on the theoretical performance analysis and simulations, the uplink radio access procedure is summarized for the URLLC in vehicular networks. [ABSTRACT FROM AUTHOR]

The cooperative non-orthogonal multiple access (NOMA) networks with one pair primary user and one pair cognitive user share the same spectrum resource via a common relay is considered in this paper. We propose a dynamic power transmission scheme for both uplink and downlink NOMA transmission in cognitive relay networks, which preserves the quality of service for the primary user. The closed-form expressions of overall outage probability and average sum rate for the proposed dynamic power transmission scheme of cognitive relay NOMA networks are derived. Both developed analytical results and Monte Carlo simulations show that the proposed dynamic power control scheme can dramatically enhance performance gain for the proposed networks, compared to other existing NOMA power allocation schemes. [ABSTRACT FROM AUTHOR]

In this paper we investigate downlink performance in a non-orthogonal multiple access (NOMA) based vehicular communication network. In contrast to the previous works wherein the vehicles are simply assumed to be located anywhere in the coverage area, we consider practical cases where vehicles are located on a system of roads. We then adopt a system model based on Poisson Line Cox Point (PLC) processes, where the road system is represented through a Poisson Line (PL) Process. Vehicles ordered according to their distances to their corresponding roadside units (RSUs) are then served by using power domain NOMA. Adopting analytical tools from the stochastic geometry, we then analyse the outage performance of the system. Numerical results corroborate our analysis and demonstrate how the system settings influence the considered NOMA based V2X network. [ABSTRACT FROM AUTHOR]

In this paper, weighted sum energy efficiency (WSEE) in uplink and downlink of a multi-user non-orthogonal multiple access (NOMA) system is considered. we adopt a more realistic power consumption model where signal processing power is modeled as a linear function of transmit power. Rather than the well-known network-centric global energy efficiency (GEE) metric, which is a pseudo-concave (PC) function, the weighted sum energy efficiency metric is considered, which is not PC in general. To find the optimum user power allocation Dinkelbach-like algorithm is adopted, by which each individual fractional EE function is converted to a parametric function where under some conditions on the weights falls into a class of convex optimization problems and it is solved in the dual domain. The dual variables are updated using a sub-gradient and cutting plane-based algorithm, which here ellipsoid method is used. Since the optimum solution restricts user weights, a low complexity suboptimum algorithm that does not consider any condition on user's weights is proposed. The problem is non-convex in general; hence, epigraph form followed by successive convex approximation (SCA) is used to deal with that problem. Results demonstrate that with the user-oriented metric, one can provide different priorities to users, and by choosing proper weights entail fairness among users. [ABSTRACT FROM AUTHOR]

In this article, a comprehensive strategy of user clustering and power allocation is investigated in downlink hybrid non-orthogonal multiple access (NOMA) networks. More particularly, users in the same cluster can receive signals simultaneously by using NOMA techniques, while time-division multiple access (TDMA) schemes are utilized among different clusters. By employing the weight factor, a weighted sum rate maximization problem is formulated and decoupled into user clustering and power allocation problems, where two different schemes for time slot allocation are proposed. The formulated user clustering problems with user-based and cluster-based time slot allocation schemes are respectively considered as coalitional games in characteristic and partition formations, and solved by two different algorithms, where both low-complexity and global optimal methods are proposed. The properties, including complexity, convergence, stability and optimality, are analyzed. To further improve the system performance, the formulated power allocation problem is solved by a successive convex approximation (SCA) based iterative algorithm. Simulation results reveal that: i) the proposed hybrid NOMA system is capable of achieving promising gains over centralized NOMA-based and conventional TDMA-based frameworks; and ii) the developed algorithms can significantly improve the weighted sum rate compared with the random user structure and the fixed power allocation. [ABSTRACT FROM AUTHOR]

In this paper, resource allocation for a multi-carrier uplink non-orthogonal multiple access (NOMA) system is studied. Unlike the existing works on multi-carrier uplink NOMA, in which each user is assumed to access only one subcarrier, we consider a more general scenario where the number of subcarriers allocated to a single user is not constrained. We first aim to maximize the system's sum rate, which requires selecting the appropriate subcarriers for each user and distribute the transmission power. The formulated non-convex problem is transformed into a convex one, and further, an optimal and low-complexity iterative water-filling solution is proposed. Nonetheless, it is shown that maximum transmit power is employed by each user to maximize the sum rate. Motivated by the fact that the users are power constrained, the energy efficiency (EE) maximization problem is also studied. Based on fractional programming, the EE maximization problem is transformed into a series of sum rate maximization subproblems, and the proposed iterative water-filling solution is applied to each subproblem. The proposed schemes are compared with other NOMA-based and orthogonal multiple access based algorithms, and its superiority is fully validated. [ABSTRACT FROM AUTHOR]

Based on a hierarchical cloud-fog computing-enabled paradigm, fog radio access networks (F-RANs) can provide abundant resource to support the future mobile artificial intelligent services. However, due to the differences of computation and communication capabilities at the cloud computing center, the fog computing based access points (F-APs), and the user devices, it is challenging to propose efficient computation offloading strategies to fully explore the potential of F-RANs. In this paper, we study the design of computation offloading in F-RANs to minimize the total cost with respect to the energy consumption and the offloading latency. In particular, a joint optimization problem is formulated to optimize the offloading decision, the computation and the radio resources allocation. To solve this non-linear and non-convex problem, an iterative algorithm is designed, which can be proved to converge a stationary optimal solution with polynomial computational complexity. Finally, the simulation results are provided to show the performance gains of our proposed joint optimization algorithm. [ABSTRACT FROM AUTHOR]

This correspondence considers non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC), where the power and time allocation is jointly optimized to reduce the energy consumption of computation offloading. Closed-form expressions for the optimal power and time allocation solutions are obtained and used to establish the conditions for determining whether the conventional orthogonal multiple access (OMA), pure NOMA or hybrid NOMA should be used for MEC offloading. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been considered as a key technology in the fifth-generation mobile communication networks due to its superior spectrum efficiency. Since the heterogeneous network has been emerged to satisfy users’ explosive data rate requirements and large connectivity of mobile Internet, implementing NOMA policy in heterogeneous networks (HetNets) has become an inevitable trend to enhance the 5G system throughput and spectrum efficiency. In this paper, we aim to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation. By considering the co-channel interference and cross-tier interference, the energy efficient resource allocation problem is formulated as a mixed integer nonconvex optimization problem. It is challenging to obtain the optimal solution; therefore, a suboptimal algorithm is proposed to alternatively optimize the macrocell and the small cells resource allocation. Specifically, convex relaxation and dual-decomposition techniques are exploited to optimize the subchannel allocation and power allocation. Moreover, optimal closed-form power allocation expressions are derived for small cell and macrocell user equipments by the Lagrangian approach. Simulations results show that the proposed algorithms can converge within ten iterations and can also attain higher system energy efficiency than the reference schemes. [ABSTRACT FROM AUTHOR]

An optimum user power allocation solution to maximize the energy efficiency (EE) in a non-orthogonal multiple access (NOMA) system with imperfect channel state information at transmitter (CSIT) and user quality of service constraint is proposed. The EE objective function is a non-convex nonlinear function that leads to a fractional programming problem. To deal with this problem, an auxiliary variable is defined, which converts the problem into a convex one. A closed form optimal solution for the power allocated to each user is found using the Karush–Kuhn–Tucker conditions. Furthermore, difference of two concave functions—DC—programming and Dinkelbach structure are used to find close-to-optimal total power value (sum of powers being allocated to all users) for the multiuser NOMA system. Simulation results show that in terms of EE, for users with low rate requirement and with CSIT error, NOMA has a better performance compared with conventional orthogonal multiple access (OMA). [ABSTRACT FROM AUTHOR]

To improve the secrecy performance of the untrusted relay system with a multiple-antenna destination, a novel full-duplex destination jamming scheme with optimal antenna selection (FDJ-OAS) is proposed in this paper. The approximate closed-form expressions of the average achievable secrecy rate are derived for the proposed scheme. To attain more insightful results, the approximated closed-form expressions for the average achievable secrecy rate and the optimal power allocation factor for FDJ-OAS are derived in the case with a large-scale antenna array, and simple power allocation solutions are also provided in the high and low SNR regimes, respectively. Furthermore, we derive the asymptotic expressions for the secrecy outage probability under different asymptotic conditions for the proposed scheme, and the analysis results indicate that the secrecy diversity order of FDJ-OAS is significantly superior to that of the comparable schemes. Simulation results show that the analytical curves match well with the simulation results, and the advantage of FDJ-OAS is also clearly demonstrated through performance comparison. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the outage performance of hybrid automatic repeat request with chase combining (HARQ-CC) assisted downlink non-orthogonal multiple access (NOMA) systems. A closed-form expression of the individual outage probability and the diversity gain are obtained firstly. Based on the developed analytical outage probability, a tradeoff between the minimum number of retransmissions and the transmit power allocation coefficient is then provided for a given target rate. The provided simulation results demonstrate the accuracy of the developed analytical results. Moreover, it is shown that NOMA combined with the HARQ-CC can achieve a significant advantage when only average channel state information is known at the transmitter. Particularly, the performance of the user with less transmit power in NOMA systems can be efficiently improved by utilizing HARQ-CC. [ABSTRACT FROM AUTHOR]

It is a promising solution for real-time multitarget tracking to implement particle cardinality balanced multitarget multi-Bernoulli (CBMeMBer) filters in hardware platforms. However, this solution is difficult to materialize since there is a contradiction between the time-varying number of Bernoulli intensity components in CBMeMBer filters and the limited number of particles in hardware platforms. Moreover, real-time hardware implementation requires a resampling procedure that is suitable for parallel processing, while the existing parallel resampling algorithms oversimplify this procedure, resulting in estimation performance degradation. In this paper, we propose an optimization algorithm of particle allocation to overcome the above-mentioned contradiction, and a parallel resampling algorithm to improve the estimation performance. Numerical experiments demonstrate the effectiveness of the proposed algorithms in multitarget tracking. [ABSTRACT FROM AUTHOR]

This correspondence paper investigates relay selection (RS) schemes for cooperative downlink nonorthogonal multiple access (NOMA) networks with multiple relays. Two optimal RS schemes, termed as the two-stage weighted-max-min (WMM) and max-weighted-harmonic-mean (MWHM) schemes, are proposed for cooperative NOMA with fixed and adaptive power allocations (PAs) at the relays, respectively. Then, the outage probabilities of the two proposed RS schemes are analyzed, and their diversity gains are also determined. The provided simulation results show that the proposed optimal two-stage WMM and MWHM schemes outperform the existing suboptimal RS schemes for cooperative NOMA networks with fixed and adaptive PAs at the relays, respectively. [ABSTRACT FROM AUTHOR]

This paper considers the antenna selection (AS) problem for a multiple-input multiple-output nonorthogonal multiple access system. In particular, we develop new computationally efficient AS algorithms for two commonly used scenarios: NOMA with fixed power allocation (F-NOMA) and NOMA with cognitive radio-inspired power allocation (CR-NOMA). For the F-NOMA scenario, a new max–max–max AS (A$^3$ -AS) scheme is first proposed to maximize the system sum-rate. This is achieved by selecting one antenna at the base station (BS) and corresponding best receive antenna at each user that maximizes the channel gain of the resulting strong user. To improve the user fairness, a new max–min–max AS (AIA-AS) scheme is subsequently developed, in which we jointly select one transmit antenna at BS and corresponding best receive antennas at users to maximize the channel gain of the resulting weak user. For the CR-NOMA scenario, we propose another new AS algorithm, termed maximum-channel-gain-based antenna selection (MCG-AS), to maximize the achievable rate of the secondary user, under the condition that the primary user's quality-of-service requirement is satisfied. The asymptotic closed-form expressions of the average sum-rate for A $^3$-AS and AIA-AS and that of the average rate of the secondary user for MCG-AS are derived. Numerical results demonstrate that the AIA-AS provides better user fairness, whereas the A$^3$-AS achieves a near-optimal sum-rate in F-NOMA systems. For the CR-NOMA scenario, MCG-AS achieves a near-optimal performance in a wide signal-to-noise-ratio regime. Furthermore, all the proposed AS algorithms yield a significant computational complexity reduction, compared to exhaustive search-based counterparts. [ABSTRACT FROM PUBLISHER]

This paper considers the performance analysis of sparse code multiple access (SCMA) with receive diversity arrays and randomly deployed users in a cellular uplink scenario. The impact of path loss on the performance of SCMA is characterized, by assuming independent Rayleigh fading and joint maximum likelihood (ML) receivers. A tight upper bound on the probability of symbol detection error is derived, and the achievable diversity and coding gains are investigated. The analytical results are validated by using simulations, and show that a diversity order which is equal to the product of the number of receive antennas and the signal-space diversity can be achieved, and the large-scale path-loss decreases only the coding gain. [ABSTRACT FROM AUTHOR]

Power allocation is a critical issue in the physical layer of power-domain nonorthogonal multiple access (NOMA) systems. However, existing power allocation schemes have not considered the delay quality of service (QoS) requirement in the datalink layer of users, and hence may not ensure the desired delay QoS requested by the services in the upper layers. Different from existing works, we apply the statistical QoS theory into NOMA systems and formulate the physical-datalink cross-layer power allocation problem as a stochastic optimization problem under different delay QoS constraints. Also, we show that the formulated problem is quasi-concave and propose a bisection-based cross-layer power allocation algorithm. Simulation results show that the proposed algorithm is able to converge to the optimal solution obtained by exhaustive search. Also, the proposed scheme outperforms existing fixed NOMA and time-division multiple access based schemes in terms of max–min effective capacity. [ABSTRACT FROM AUTHOR]

In this paper, we consider non-orthogonal multiple access (NOMA) relaying networks, where one base station communicates with two mobile users with the aid of multiple relays. We propose a two-stage relay selection strategy for NOMA networks with decode-and-forward (DF) and amplify-and-forward (AF) relaying protocols with different quality of service requirements at the users, respectively. Then, the outage probabilities of the NOMA two-stage DF and AF schemes are obtained in closed-form expressions, and the diversity order is determined based on their asymptotic expressions at high signal-to-noise ratio. Both of the developed analytical results and carried out computer simulations show that NOMA two-stage DF (AF) relaying is superior to existing relay selection strategies developed for cooperative NOMA and orthogonal multiple access networks. [ABSTRACT FROM PUBLISHER]

This paper studies the secrecy rate maximization problem of a secure wireless communication system in the presence of multiple eavesdroppers. The security of the communication link is enhanced through cooperative jamming with the help of multiple jammers. First, a feasibility condition is derived to achieve a positive secrecy rate at the destination. Then, we solve the original secrecy rate maximization problem, which is not convex in terms of power allocation at the jammers. To circumvent this nonconvexity, the achievable secrecy rate is approximated for a given power allocation at the jammers, and the approximated problem is formulated into a geometric programming one. Based on this approximation, an iterative algorithm has been developed to obtain the optimal power allocation at the jammers. Next, we provide a bisection approach, based on 1-D search, to validate the optimality of the proposed algorithm. In addition, by assuming Rayleigh fading, the secrecy outage probability (SOP) of the proposed cooperative jamming scheme is analyzed. More specifically, a single-integral form expression for the SOP is derived for the most general case, as well as a closed-form expression for the special case of two cooperative jammers and one eavesdropper. Simulation results have been provided to validate the convergence and the optimality of the proposed algorithm, as well as the theoretical derivations of the presented SOP analysis. [ABSTRACT FROM AUTHOR]

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm that integrates the advantages of cloud radio access networks and heterogeneous networks. In this paper, we study joint congestion control and resource optimization to explore the energy efficiency (EE)-guaranteed trade-off between throughput utility and delay performance in a downlink slotted H-CRAN. We formulate the considered problem as a stochastic optimization problem, which maximizes the utility of average throughput and maintains the network stability subject to the required EE constraint and transmit power consumption constraints by traffic admission control, user association, resource block allocation, and power allocation. Leveraging on the Lyapunov optimization technique, the stochastic optimization problem can be transformed and decomposed into three separate subproblems that can be concurrently solved at each slot. The third mixed-integer nonconvex subproblem is efficiently solved by utilizing the continuity relaxation of binary variables and the Lagrange dual decomposition method. Theoretical analysis shows that the proposal can quantitatively control the throughput–delay performance trade-off with the required EE performance. Simulation results consolidate the theoretical analysis and demonstrate the advantages of the proposal from the prospective of queue stability and power consumption. [ABSTRACT FROM PUBLISHER]

In this paper, nonorthogonal multiple access (NOMA) is applied to large-scale underlay cognitive radio (CR) networks with randomly deployed users. To characterize the performance of the considered network, new closed-form expressions of the outage probability are derived using stochastic geometry. More importantly, by carrying out the diversity analysis, new insights are obtained under the two scenarios with different power constraints: 1) fixed transmit power of the primary transmitters (PTs); and 2) transmit power of the PTs being proportional to that of the secondary base station. For the first scenario, a diversity order of $m$ is experienced at the $m$th-ordered NOMA user. For the second scenario, there is an asymptotic error floor for the outage probability. Simulation results are provided to verify the accuracy of the derived results. A pivotal conclusion is reached that by carefully designing target data rates and power allocation coefficients of users, NOMA can outperform conventional orthogonal multiple access in underlay CR networks. [ABSTRACT FROM PUBLISHER]

Nonorthogonal multiple access (NOMA) represents a paradigm shift from conventional orthogonal multiple-access (MA) concepts and has been recognized as one of the key enabling technologies for fifth-generation mobile networks. In this paper, the impact of user pairing on the performance of two NOMA systems, i.e., NOMA with fixed power allocation (F-NOMA) and cognitive-radio-inspired NOMA (CR-NOMA), is characterized. For F-NOMA, both analytical and numerical results are provided to demonstrate that F-NOMA can offer a larger sum rate than orthogonal MA, and the performance gain of F-NOMA over conventional MA can be further enlarged by selecting users whose channel conditions are more distinctive. For CR-NOMA, the quality of service (QoS) for users with poorer channel conditions can be guaranteed since the transmit power allocated to other users is constrained following the concept of cognitive radio networks. Because of this constraint, CR-NOMA exhibits a different behavior compared with F-NOMA. For example, for the user with the best channel condition, CR-NOMA prefers to pair it with the user with the second best channel condition, whereas the user with the worst channel condition is preferred by F-NOMA. [ABSTRACT FROM AUTHOR]

We consider multiple-input–multiple-output (MIMO) two-way relaying channels where a pair of multiantenna users wishes to exchange information with the help of a nonregenerative multiantenna relay. A low-complexity joint beamforming and power management scheme is proposed. The proposed beamformers first align the channel matrices of the user pair and then decompose the aligned channel into parallel subchannels. Two power management issues, i.e., power allocation and power control, are addressed in this paper. First, sum-rate optimizing power allocation is proposed to allocate power between all subchannels and nodes. Second, quality of service (QoS) satisfying power control is proposed to minimize the total transmission power in the network. Simulation results justify that the proposed joint beamforming and power management scheme delivers better sum-rate performance or consumes lower transmission power when compared with existing schemes. [ABSTRACT FROM PUBLISHER]