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.     

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.     

Intelligent radio resource management in reconfigurable IRS-enabled NOMA networks

Intelligent reflecting surfaces (IRSs) are anticipated to provide reconfigurable propagation environment for next generation communication systems. In this paper, we investigate a downlink IRS-aided multi-carrier (MC) non-orthogonal multiple access (NOMA) system, where the IRS is deployed to especially assist the blocked users to establish communication with the base station (BS). To maximize the system sum rate under network quality-of-service (QoS), rate fairness and successive interference cancellation (SIC) constraints, we formulate a problem for joint optimization of IRS elements, sub-channel assignment and power allocation. The formulated problem is mixed non-convex. Therefore, a novel three stage algorithm is proposed for the optimization of IRS elements, sub-channel assignment and power allocation. First, the IRS elements are optimized using the bisection method based iterative algorithm. Then, the sub-channel assignment problem is solved using one-to-one stable matching algorithm. Finally, the power allocation problem is solved under the given sub-channel and optimal number of IRS elements using Lagrangian dual-decomposition method based on Lagrangian multipliers. Moreover, in an effort to demonstrate the low-complexity of the proposed resource allocation scheme, we provide the complexity analysis of the proposed algorithms. The simulated results illustrate the various factors that impact the optimal number of IRS elements and the superiority of the proposed resource allocation approach in terms of network sum rate and user fairness. Furthermore, we analyze the proposed approach against a new performance metric called computational efficiency (CE).     

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.     

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.     

Secrecy performance analysis of IRS-assisted D2D communication underlaying cellular network

In this paper, we evaluate the secrecy performance of an intelligent reflecting surface (IRS)-assisted device-to-device (D2D) communication in spectrum-shared cellular networks. To this end, we derive novel closed-form expressions for the secrecy outage probability (SOP) and the asymptotic SOP in the presence of multiple eavesdroppers. In the continue, in order to dynamically access the spectrum band of the licensed users, we define the optimization problem of secrecy spectrum resource allocation to minimize the SOP as a mixed-integer linear programming (MILP) problem. Then, the globally optimal solutions to this problem are obtained by using the Hungarian algorithm. Numerical analyses show that increasing the reflective elements of IRS can improve the secrecy performance.     

On the security of K-tier heterogeneous cellular networks

Motivated by recent developments in heterogeneous cellular networks and physical-layer security, we aim to characterize the fundamental limits of secure communication in networks. Based on a general model in which both transmitters and receivers are randomly scattered in space, we model the locations of K-tier base stations, users, and potential eavesdroppers as independent two-dimensional Poisson point processes. Using the proposed model, we analyze the achievable secrecy rates for an arbitrarily located mobile user. Assuming that the cell selection is based on achievable-secrecy-rate threshold, we obtain approximations for: (a) secrecy coverage probability and (b) average secrecy load per tier. We also investigate how the network performance is affected by secrecy rate threshold, eavesdropper density, and different access strategies are analyzed, respectively. Finally, our theoretical claims are confirmed by the numerical results.     

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.     

Robust secrecy rate maximization in IRS-assisted cognitive radio networks

In this paper, we focus on the secrecy rate maximization problem in intelligent reflecting surface (IRS)-assisted cognitive radio (CR) networks. In order to improve the security, there is a common scheme to add artificial noise (AN) to the transmitted signal, which is also applied in this paper. Further, in CR networks, the secondary users always cannot obtain accurate channel state information (CSI) about the primary user and eavesdropper. By taking jointly design for the IRS phase shift matrix, the transmitted beamforming of the secondary base station (BS), and the covariance matrix of AN, our objective is to maximize the minimal secrecy rate of all secondary users. Due to the serious coupling among the designed variables, it cannot be solved by conventional methods. We propose an alternating optimization (AO) algorithm. In simulation results, we apply primary users and secondary users randomly distributed in the communication area, which numerically demonstrate the superiority of our proposed scheme.     

Intelligent resource allocation for transmission security on IRS-assisted spectrum sharing systems with OFDM

In this paper, intelligent reflecting surface (IRS) technology is employed to enhance physical layer security (PLS) for spectrum sharing communication systems with orthogonal frequency division multiplexing (OFDM). Aiming to improve the secondary users’ secrecy rates, a design problem for jointly optimizing the transmission beamforming of secondary base station (SBS), the IRS’s reflecting coefficient and the channel allocation is formulated under the constraints of the requirements of minimum data rates of primary users and the interference between users. As the scenario is highly complex, it is quite challenging to address the non-convexity of the optimization problem. Thus, a deep reinforcement learning (DRL) based approach is taken into consideration. Specifically, we use dueling double deep Q networks (D3QN) and soft Actor–Critic (SAC) to solve the discrete and continuous action space optimization problems, respectively, taking full advantage of the maximum entropy RL algorithm to explore all possible optimal paths. Finally, simulation results show that our proposed approach has a great improvement in security transmission rate compared with the scheme without IRS and OFDM, and our proposed D3QN-SAC approach is more effective than other approaches in terms of maximum security transmission rate.     

Beyond Equal-Power Sparse NOMA: Two User Classes and Closed-Form Bounds on the Achievable Region

Non-orthogonal multiple access (NOMA) is a promising technology for future beyond-5G wireless networks, whose fundamental information-theoretic limits are yet to be fully explored. Considering regular sparse code-domain NOMA (with a fixed and finite number of orthogonal resources allocated to any designated user and vice versa), this paper extends previous results by the authors to a setting comprising two classes of users with different power constraints. Explicit rigorous closed-form analytical inner and outer bounds on the achievable rate (total class throughput) region in the large-system limit are derived and comparatively investigated in extreme-SNR regimes. The inner bound is based on the conditional vector entropy power inequality (EPI), while the outer bound relies on a recent strengthened version of the EPI. Valuable insights are provided into the potential performance gains of regular sparse NOMA in practically oriented settings, comprising, e.g., a combination of low-complexity devices and broadband users with higher transmit power capabilities, or combinations of cell-edge and cell-center users. The conditions for superior performance over dense code-domain NOMA (taking the form of randomly spread code-division multiple access), as well as a relatively small gap to the ultimate performance limits, are identified. The proposed bounds are also applicable for the analysis of interference networks, e.g., Wyner-type cellular models.     

Intelligent Reflecting Surface Assisted Secure Transmission in UAV-MIMO Communication Systems

This paper studies the intelligent reflecting surface (IRS) assisted secure transmission in unmanned aerial vehicle (UAV) communication systems, where the UAV base station, the legitimate receiver, and the malicious eavesdropper in the system are all equipped with multiple antennas. By deploying an IRS on the facade of a building, the UAV base station can be assisted to realize the secure transmission in this multiple-input multiple-output (MIMO) system. In order to maximize the secrecy rate (SR), the transmit precoding (TPC) matrix, artificial noise (AN) matrix, IRS phase shift matrix, and UAV position are jointly optimized subject to the constraints of transmit power limit, unit modulus of IRS phase shift, and maximum moving distance of UAV. Since the problem is non-convex, an alternating optimization (AO) algorithm is proposed to solve it. Specifically, the TPC matrix and AN covariance matrix are derived by the Lagrange dual method. The alternating direction method of multipliers (ADMM), majorization-minimization (MM), and Riemannian manifold gradient (RCG) algorithms are presented, respectively, to solve the IRS phase shift matrix, and then the performance of the three algorithms is compared. Based on the proportional integral (PI) control theory, a secrecy rate gradient (SRG) algorithm is proposed to iteratively search for the UAV position by following the direction of the secrecy rate gradient. The theoretic analysis and simulation results show that our proposed AO algorithm has a good convergence performance and can increase the SR by 40.5% compared with the method without IRS assistance.     

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.     

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.     

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 efficiency maximization for IRS-assisted NOMA networks

In this paper, we consider a non-orthogonal multiple access (NOMA) system assisted by intelligent reflecting surface (IRS). As an emerging technology that has received widespread attention, IRS can reconfigure the wireless channel environment by adjusting the relationship between the incident angle and the exit angle, thereby improving system performance. Our goal is to use the flexible assistance of IRS to achieve the maximum energy efficiency of the NOMA system. Our design objects are the beam vector design of the base station and the phase matrix design of the IRS. The original problem is highly non-convex. We consider using the block coordinate descent method to design the phase matrix and beam vector separately. Simulation results show that our proposed scheme has better performance than traditional OMA and systems without IRS assistance.     

Delay-Sensitive NOMA-HARQ for Short Packet Communications

This paper investigates the two-user uplink non-orthogonal multiple access (NOMA) paired with the hybrid automatic repeat request (HARQ) in the finite blocklength regime, where the target latency of each user is the priority. To limit the packet delivery delay and avoid packet queuing of the users, we propose a novel NOMA-HARQ approach where the retransmission of each packet is served non-orthogonally with the new packet in the same time slot. We use a Markov model (MM) to analyze the dynamics of the uplink NOMA-HARQ with one retransmission and characterize the packet error rate (PER), throughput, and latency performance of each user. We also present numerical optimizations to find the optimal power ratios of each user. Numerical results show that the proposed scheme significantly outperforms the standard NOMA-HARQ in terms of packet delivery delay at the target PER.     

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.     

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.     

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.