Effective capacity analysis of NOMA with transceiver hardware and SIC imperfections

In this paper, we study the performance of the non-orthogonal multiple access (NOMA) networks. By considering two practical factors of residual hardware impairments (RHIs) and imperfect serial interference cancellation (ipSIC), we adopt effective capacity as a metric to characterize the effects of latency on the performance of NOMA networks and derive the analytical expressions of the effective capacity for the near user (NU) and the far user (FU). For further insights, we provide asymptotic analysis by invoking high signal-to-noise ratio (SNR) slope and high SNR power offset. Numerous analytical and simulated results have shown that: (1) The effective capacities of NU and FU are positively proportional to the SNR at low SNR, while at high SNR, the effective capacities approach to the constants; (2) Comparing the two users of the considered NOMA network, the effective capacity of NU shows pronounced advantages under the requirements of low quality of service. (3) RHIs are detrimental to the effective capacities of both NU and FU, especially for the high SNR regime. (4) The effective capacity of NU is limited by ipSIC.     

System throughput maximization in IRS-assisted phase cooperative NOMA networks

This work investigates performance of system throughput in intelligent reflecting surfaces (IRSs)-enabled phase cooperative non-orthogonal multiple access (NOMA) framework. By exploiting heterogeneous cognitive radio networks concept the aim is to maximize the sum rate of secondary users in the proposed phase cooperative downlink network configuration via optimization solutions. However, the optimization problem comes out to be NP-hard and precludes direct solution. Hence, an alternating optimization is applied at the primary network to solve the maximization problem by exploiting the transmit beamforming (BF) at the power station (PS) and phase shift optimization at the IRS. Later, sum rate maximization for secondary network is performed by utilizing phase shifts of primary network via phase cooperation. In order to find global optimal solutions for active beamformers at both PSs, a branch-reduce-and-bound (BRnB) method is used whereas, passive phase shift optimization at the primary PS is performed via a simple iterative solution, i.e., the element-wise block coordinate descent method. For the proposed framework, Monte-Carlo simulations are performed where the optimality of the global solution is compared with heuristic BF methods including minimum-mean-square-error/regularized zero-forcing-beamforming (ZFBF) and ZFBF. The BRnB algorithm sets an upper performance bound by improving the sum rate of users in comparison with the conventional heuristic BF schemes. This work signifies the utilization of phase cooperation in IRS-assisted NOMA networks for a multi-user environment.     

Deep transfer reinforcement learning for resource allocation in hybrid multiple access systems

This paper proposes a resource allocation scheme for hybrid multiple access involving both orthogonal multiple access and non-orthogonal multiple access (NOMA) techniques. The proposed resource allocation scheme employs multi-agent deep reinforcement learning (MA-DRL) to maximize the sum-rate for all users. More specifically, the MA-DRL-based scheme jointly allocates subcarrier and power resources for users by utilizing deep Q networks and multi-agent deep deterministic policy gradient networks. Meanwhile, an adaptive learning determiner mechanism is introduced into our allocation scheme to achieve better sum-rate performance. However, the above deep reinforcement learning adopted by our scheme cannot optimize parameters quickly in the new communication model. In order to better adapt to the new environment and make the resource allocation strategy more robust, we propose a transfer learning scheme based on deep reinforcement learning (T-DRL). The T-DRL-based scheme allows us to transfer the subcarrier allocation network and the power allocation network collectively or independently. Simulation results show that the proposed MA-DRL-based resource allocation scheme can achieve better sum-rate performance. Furthermore, the T-DRL-based scheme can effectively improve the convergence speed of the deep resource allocation network.     

Game theory-based radio resource allocation in NOMA vehicular communication networks supported by UAV

Vehicular communication networks are emerging as a promising technology to provide high-quality internet service such as entertainment for road users via infrastructure-to-vehicle (I2V) communication, and to guarantee road users’ safety via vehicle-to-vehicle (V2V) communication. Some technical issues that impact the performance of these networks are the lack of or poor communication paths between vehicles, and the limitation of radio resources. Unmanned aerial vehicles (UAVs) as promising solutions for supporting vehicular networks could provide communication coverage in hazardous environments and areas with no capacities for installation or maintenance of ground base stations (BSs). Also, non-orthogonal multiple access (NOMA) methods can improve spectral and energy efficiency and thereby allow more users to be connected to the desired network. In this paper, exploring the NOMA, we develop a scheme for optimum resource allocation in presence of a UAV that supports vehicular communications. Resource allocation for this scenario is formulated as a mixed-integer non-linear programming (MINLP) problem. Due to the high complexity of such problems, we propose two low-complexity near-optimal methods. First, we apply difference-of-concave-functions (DC) approximations to solve the problem in an iterative process. Next, we use Stackelberg game-based method for efficient solving, and then, closed-form expressions of optimal power allocations using KKT-conditions are derived. Simulations illustrate the effectiveness of the proposed scheme along with the Stackelberg game-based method.     

A matching-theoretic approach to resource allocation in D2D-enabled downlink NOMA cellular networks

This paper investigates the resource allocation problem in non-orthogonal multiple-access (NOMA) cellular networks underlaid with OMA-based device-to-device (D2D) communication. This network architecture enjoys the intrinsic features of NOMA and D2D communications; namely, spectral efficiency, massive connectivity, and low-latency. Despite these indispensable features, the combination of NOMA and D2D communications exacerbates the resource allocation problem in cellular networks due to the tight coupling among their constraints and conflict over access to shared resources. The aim of our work is to maximize the downlink network sum-rate, while meeting the minimum rate requirements of the cellular tier and underlay D2D communication, and incorporating interference management as well as other practical constraints. To this end, many-to-many matching and difference-of-convex programming are employed to develop a holistic sub-channels and power allocation algorithmic solution. In addition to analyzing the properties of the proposed solution, its performance is benchmarked against an existing solution and the traditional OMA-based algorithm. The proposed solution demonstrates superiority in terms of network sum-rate, users’ connectivity, minimum rate satisfaction, fairness, and interference management, while maintaining acceptable computational complexity.     

Subchannel and power optimization for sum rate maximization in downlink multicarrier NOMA networks

In a multicarrier NOMA system, the subchannel allocation (SA) and power allocation (PA) are intricately linked and essential for improving system throughput. Also, for the successful execution of successive interference cancellations (SIC) at the receiver, a minimum power gap is required among users. As a result, this research comes up with optimization of the SA and PA to maximize the sum rate of the NOMA system while sticking to the minimum power gap constraint in addition to minimum user rate, maximum number of users in a subchannel and power budget constraints for downlink transmission in multicarrier NOMA networks. To ensure that the formulated problem can be solved in polynomial time, we propose solving it in two stages; SA followed by PA. To obtain SA, we investigate four algorithms: Greedy, WSA, WCA, and WCF. For PA, we propose a low-complexity algorithm. We compare the performance of the proposed method with benchmark method that does not consider the minimum power gap constraint. We conclude that employing WCF algorithm with the PA algorithm gives the best sum rate performance.     

Secrecy communications of intelligent reflecting surfaces aided NOMA networks

This paper investigates the physical layer security of an intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks, where a remote user is regarded as an eavesdropper to intercept the information of nearby user. To evaluate the security performance of IRS-aided NOMA networks, a problem of maximizing achievable secrecy rate is formulated via jointly optimizing the beamforming and phase shifting. More specifically, we aim to tackle the non-convex problem by optimizing beamforming vector as well as phase shifting matrix with the assistance of block coordinate descent (BCD) and minorization maximization (MM) algorithms. Numerical results illustrate that: 1) The secrecy rates of IRS-aided NOMA with BCD and MM algorithms are superior to that of orthogonal multiple access schemes; 2) With increasing the number of reflecting elements, the secrecy rates of IRS-aided NOMA networks are achieved carefully; and 3) The IRS-aided NOMA networks are capable of relieving the transmission pressure of base station.     

Matching theory based user-grouping for indoor non-orthogonal multiple access visible light communication heterogeneous networks

This Letter proposes a model of indoor visible light communication(VLC) heterogeneous networks entirely based on LEDs with different specifications and applies non-orthogonal multiple access(NOMA) to it because of the narrow modulation bandwidth of LEDs. Moreover, a user-grouping scheme that is based on matching theory is proposed to improve the network achievable sum rate. Simulation results indicate that when each NOMA cluster contains 6 users, the proposed scheme has a 49.54% sum-rate enhancement compared with the traditional user-grouping scheme. As the number of users in each NOMA cluster increases, the proposed scheme performs better at the cost of computational complexity.     

Joint user grouping and power allocation in VLC-NOMA system

With the energy consumption of wireless networks increasing, visible light communication (VLC) has been regarded as a promising technology to realize energy conservation. Due to the massive terminals access and increased traffic demand, the implementation of non-orthogonal multiple access (NOMA) technology in VLC networks has become an inevitable trend. In this paper, we aim to maximize the energy efficiency in VLC-NOMA networks. Assuming perfect knowledge of the channel state information of user equipment, the energy efficiency maximization problem is formulated as a mixed integer nonlinear programming problem. To solve this problem, the joint user grouping and power allocation (JUGPA) is proposed including user grouping and power allocation. In user grouping phase, we utilize the average of channel gain among all user equipment and propose a dynamic user grouping algorithm with low complexity. The proposed scheme exploits the channel gain differences among users and divides them into multiple groups. In power allocation phase, we proposed a power allocation algorithm for maximizing the energy efficiency for a given NOMA group. Thanks to the objective function is fraction form and non-convex, we firstly transform it to difference form and convex function. Then, we derive the closed-form optimal power allocation expression that maximizes the energy efficiency by Dinkelbach method and Lagrange dual decomposition method. Simulation results show that the JUGPA can effectively improve energy efficiency of the VLC-NOMA networks.     

Deployment and trajectory design of fixed-wing UAVs in NOMA assisted wireless networks

This paper proposes a deployment and trajectory scheme for fixed-wing unmanned aerial vehicles (UAVs) deployed as flying base stations in multi-UAV enabled non-orthogonal multiple access (NOMA) downlink communication. Specifically, the deployment of UAVs and power allocation of users are jointly optimized to maximize the sum-rate. Thereafter, the energy efficiency maximization problem is formulated to optimize the trajectory of UAVs by jointly considering the quality of service (QoS) requirement of users, various flight constraints, limited on-board energy, and users’ mobility. Initially, the existing users are divided into clusters by k-means clustering, where each cluster is served by a single UAV. Then, the clusters are further divided into multiple sub-clusters, each having a pair of near and far users. Orthogonal multiple access (OMA) is applied among sub-clusters and NOMA is applied to intra sub-cluster users. Lastly, the Balanced-grey wolf optimization (B-GWO) algorithm is proposed for solving the non-convex optimization problems. Simulation results prove the superiority of the B-GWO based deployment and trajectory algorithms compared to the benchmarks. In addition, the proposed B-GWO based trajectory algorithm achieves a near-optimal performance with an optimality gap of less than 1.5% compared to the exhaustive search.     

Physical layer secrecy analysis of HS-UAV NOMA network with spatially random eavesdroppers

This work investigates the physical layer secrecy performance of a hybrid satellite/unmanned aerial vehicle (HS-UAV) terrestrial non-orthogonal multiple access (NOMA) network, where one satellite source intends to make communication with destination users via a UAV relay using NOMA protocol in the existence of spatially random eavesdroppers. All the destination users randomly distributed on the ground comply with a homogeneous Poisson point process in the basis of stochastic geometry. Adopting Shadowed-Rician fading in satellite-to-UAV and satellite-to-eavesdroppers links while Rayleigh fading in both UAV-to-users and UAV-to-eavesdroppers links, the theoretical expressions for the secrecy outage probability (SOP) of the paired NOMA users are obtained based on the distance-determined path-loss. Also, the asymptotic behaviors of SOP expressions at high signal-to-noise ratio (SNR) regime are analyzed and the system throughputs of the paired NOMA users are examined for gaining further realization of the network. Moreover, numerical results are contrasted with simulation to validate the theoretical analysis. Investigation of this work shows the comparison of SOP performance for the far and near user, pointing out the SOP performance of the network depends on the channel fading, UAV coverage airspace, distribution of eavesdroppers and some other key parameters.     

On the performance of a virtual user pairing scheme to efficiently utilize the spectrum of unpaired users in NOMA

This paper evaluates the performance of a virtual user pairing scheme that efficiently utilizes the spectrum of unpaired users in non-orthogonal multiple access (NOMA), termed as VP-NOMA. The scheme aims at utilizing the frequency bands of those users which remain unpaired due to the non-uniform distribution of users in a cellular area. We consider a case where the cell edge users are more than the cell center users, so that complete one-to-one correspondence does not exist between all cell center and cell edge users to be accommodated/paired using conventional NOMA (C-NOMA) user pairing. Thus, some cell edge users remain unpaired, and are served using conventional multiple access (OMA) schemes. In such scenario, VP-NOMA pairs a single cell center user with two or more clustered (closely located) cell edge users over non-overlapping frequency bands, thus enabling the cell center user to efficiently use the frequency bands of these previously unpaired cell edge users. Performance of VP-NOMA in terms of ergodic sum capacity (ESC), outage probability (OP), and outage sum capacity (OSC), is analyzed through comprehensive mathematical derivations and simulations for a generalized system model. Moreover, the mathematical analysis is validated through close concordance between analytical and simulation results of ESC, OP, and OSC.     

Performance analysis of overlay cognitive NOMA network with imperfect SIC and imperfect CSI

In this paper, we investigate a multiple users cooperative overlay cognitive radio non-orthogonal multiple access (CR-NOMA) network in the presence of imperfect successive interference cancellation (SIC) and imperfect channel state information (CSI). In the context of cellular network, cell-center cognitive secondary users act as relays to assist transmission from the primary user (PU) transmitter to the cell-edge PU receiver via NOMA. According to the received signals between the primary transmitter and multiple cognitive secondary center users, the best cell-center cognitive SU with the maximum signal to noise ratio (SNR) is selected to transmit the PU’s signals and its own signal to cell-edge users through NOMA principle. Then, the PU cell-edge user combine the signals received from direct transmission in the first phase and relay transmission from the best cell-center cognitive SU in the second phase by selection combining (SC). To measure the performance of the system quantitatively, we derive the end-to-end outage probability and capacity for the primary and secondary networks by taking the imperfect SIC and CSI into consideration. Finally, the performance analysis is validated by the simulations, and show that serious interference caused by imperfect SIC and (or) imperfect CSI reduce the system performance.     

Energy efficient collaborative computation for double-RIS assisted mobile edge networks

Computation offloading in mobile edge computing (MEC) systems emerges as a novel paradigm of supporting various resource-intensive applications. However, the potential capabilities of MEC cannot be fully unleashed when the communication links are blocked by obstacles. This paper investigates a double-reconfigurable-intelligent-surfaces (RISs) assisted MEC system. To efficiently utilize the limited frequency resource, the users can partially offload their computational tasks to the MEC server deployed at base station (BS) by adopting non-orthogonal multiple access (NOMA) protocol. We aim to minimize the energy consumption of users with limited resource by jointly optimizing the transmit power of users, the offloading fraction of users and the phase-shifts of RISs. Since the problem is non-convex with highly coupled variables, the block coordinate descent (BCD) method is leveraged to alternatively optimize the decomposed four subproblems. Specifically, we invoke successive convex approximation for low complexity (SCALE) and Dinkelbach technique to tackle the fractional programming of power optimization. Then the offloading fraction is obtained by closed-form solution. Further, we leverage semidefinite relaxation (SDR) and bisection method to address the phase-shifts design of double RISs. Finally, numerical results illustrate that the proposed double-RIS assisted NOMA scheme is capable of efficiently reducing the energy consumption and achieves significant performance gain over the benchmark schemes.     

Secrecy sum rate maximization for a MIMO-NOMA uplink transmission in 6G networks

Non-orthogonal multiple access (NOMA), as a well-qualified candidate for sixth-generation (6G) mobile networks, has been attracting remarkable research interests due to high spectral efficiency and massive connectivity. The aim of this study is to maximize the secrecy sum rate (SSR) for a multiple-input multiple-output (MIMO)-NOMA uplink network under the maximum total transmit power and quality of service (QoS) constraints. Thanks to the generalized singular value decomposition method, the SSR of NOMA is compared with conventional orthogonal multiple access and other baseline algorithms in different MIMO scenarios. Due to the subtractive and non-convex nature of the SSR problem, the first-order Taylor approximation is exploited to transform the original problem into a suboptimal concave problem. Simulation results are provided and compared with some other benchmarks to evaluate the efficacy of the proposed method.     

Performance analysis of PDMA-based hybrid satellite–terrestrial networks with decode-and-forward relaying

As one of the most promising non-orthogonal multiple access (NOMA) technologies in 5G communication, pattern division multiple access (PDMA) has theoretically higher spectrum utilization and a larger communication capacity than conventional orthogonal multiple access (OMA) technologies. In this letter, PDMA is applied to hybrid satellite–terrestrial networks with decode-and-forward (DF) relaying in the downlink, and an in-depth study on the performance of outage probability (OP), ergodic capacity and system throughput is performed. For a more comprehensive analysis, hybrid satellite–terrestrial relay networks (HSTRNs) with conventional OMA technology are used in the comparative analysis. Analysis and simulation results show that PDMA-based hybrid satellite–terrestrial relay networks outperform the other system in terms of OP and ergodic capacity.     

DRL-Assisted Resource Allocation for NOMA-MEC Offloading with Hybrid SIC

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) are regarded as promising technologies to improve the computation capability and offloading efficiency of mobile devices in the sixth-generation (6G) mobile system. This paper mainly focused on the hybrid NOMA-MEC system, where multiple users were first grouped into pairs, and users in each pair offloaded their tasks simultaneously by NOMA, then a dedicated time duration was scheduled to the more delay-tolerant user for uploading the remaining data by orthogonal multiple access (OMA). For the conventional NOMA uplink transmission, successive interference cancellation (SIC) was applied to decode the superposed signals successively according to the channel state information (CSI) or the quality of service (QoS) requirement. In this work, we integrated the hybrid SIC scheme, which dynamically adapts the SIC decoding order among all NOMA groups. To solve the user grouping problem, a deep reinforcement learning (DRL)-based algorithm was proposed to obtain a close-to-optimal user grouping policy. Moreover, we optimally minimized the offloading energy consumption by obtaining the closed-form solution to the resource allocation problem. Simulation results showed that the proposed algorithm converged fast, and the NOMA-MEC scheme outperformed the existing orthogonal multiple access (OMA) scheme.     

特种截面传输线特性阻抗计算的一种方法

本文提出用圆或椭圆图形逼近多角形边界、计及其角形外导体边界的电荷角效应影响和取截面边界尺寸上、下限几何平均值的方法,计算特种截面传输线特性阻抗,得到了矩形外导体-椭圆内导体、圆形外导体-正三角形内导体、圆形外导体-正五边形内导体、圆形外导体-正六边形内导体、椭圆外导体-矩形内导体等五种新型传输线和九种现有传输线特性阻抗的初等函数计算公式,通过计算数值与有关文献的精确值比较,证实了本文方法及其特性阻抗计算公式的准确性。 关键词：     

Contract Theory-Based Incentive Mechanism for Full Duplex Cooperative NOMA with SWIPT Communication Networks

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can not only effectively improve the spectrum efficiency and energy efficiency of wireless networks but also extend their coverage. An important design issue is to incentivize a full duplex (FD) relaying center user to participate in the cooperative process and achieve a win–win situation for both the base station (BS) and the center user. Some private information of the center users are hidden from the BS in the network. A contract theory-based incentive mechanism under this asymmetric information scenario is applied to incentivize the center user to join the cooperative communication to maximize the BS’s benefit utility and to guarantee the center user’s expected payoff. In this work, we propose a matching theory-based Gale–Shapley algorithm to obtain the optimal strategy with low computation complexity in the multi-user pairing scenario. Simulation results indicate that the network performance of the proposed FD cooperative NOMA and SWIPT communication is much better than the conventional NOMA communication, and the benefit utility of the BS with the stable match strategy is nearly close to the multi-user pairing scenario with complete channel state information (CSI), while the center users get the satisfied expected payoffs.     

Bit error rate evaluation of relay-aided cooperative NOMA with energy harvesting under imperfect SIC and CSI

In this paper, we investigate a decode-and-forward relay-assisted cooperative non-orthogonal multiple access (NOMA) scheme, where the relay implements a time-switching (TS) based energy harvesting (EH). The impacts of the imperfect channel state information (CSI), inter-cell interference (ICI) and imperfect successive interference cancellation (SIC) are taken into account. We derive the end-to-end bit error rate (BER) expressions under imperfect CSI and ICI for both users. The effect of the EH parameters under the imperfect CSI on users’ BER performance is also examined. Furthermore, we discuss the impact of ICI on BER performance. Computer simulations are used for numerical analysis validation. The results reveal that the CSI deterioration reduces the SIC performance in each node despite the increase in EH parameters and causes an error floor at the higher signal-to-noise ratio (SNR). Furthermore, the BER performance of the users increases by increasing the EH parameters. Also, the ICI affects the SIC and degrades the BER of users.