Energy-Efficient Design of STAR-RIS Aided MIMO-NOMA Networks

Simultaneous transmission and reflection-reconfigurable intelligent surface (STAR-RIS) can provide expanded coverage compared with the conventional reflection-only RIS. This paper exploits the energy efficient potential of STAR-RIS in a multiple-input and multiple-output (MIMO) enabled non-orthogonal multiple access (NOMA) system. Specifically, we mainly focus on energy-efficient resource allocation with MIMO technology in the STAR-RIS assisted NOMA network. To maximize the system energy efficiency, we propose an algorithm to optimize the transmit beamforming and the phases of the low-cost passive elements on the STAR-RIS alternatively until the convergence. Specifically, we first decompose the formulated energy efficiency problem into beamforming and phase shift optimization problems. To efficiently address the non-convex beamforming optimization problem, we exploit signal alignment and zero-forcing precoding methods in each user pair to decompose MIMO-NOMA channels into single-antenna NOMA channels. Then, the Dinkelbach approach and dual decomposition are utilized to optimize the beamforming vectors. In order to solve non-convex phase shift optimization problem, we propose a successive convex approximation (SCA) based method to efficiently obtain the optimized phase shift of STAR-RIS. Simulation results demonstrate that the proposed algorithm with NOMA technology can yield superior energy efficiency performance over the orthogonal multiple access (OMA) scheme and the random phase shift scheme

Performance Evaluation of Massive MIMO with Beamforming and Non Orthogonal Multiple Access based on Practical Channel Measurements

International audienceThis paper presents a comprehensive performance analysis of a massive multiple-input multiple-output (MIMO) system using non-orthogonal multiple access (NOMA) in both indoor and outdoor environments, based on practical channel measurements. The latter are performed using frequency-domain channel sounding experiments conducted at 3.5 GHz with 18 MHz bandwidth. Multiuser beamforming and NOMA clustering are used in the massive MIMO system. The system performance is evaluated in terms of sum-rate capacity for two precoding schemes: zero-forcing (ZF) and maximum ratio transmission (MRT). Two inter-beam power allocation (PA) schemes are investigated: equal PA and water filling. Fractional transmit PA (FTPA) is used to perform intra-cluster PA between paired users. The study allows the identification of practical scenarios that are propitious to NOMA with beamforming. Results show that NOMA is particularly interesting with MRT, compared to ZF, especially when combined with water filling. However, ZF generally outperforms MRT for all system configurations

Operating multi-user transmission for 5G and beyond cellular systems

Every decade, a new generation of cellular networks is released to keep up with the ever-growing demand for data and use cases. Traditionally, cellular networks rely on partitioning radio resources into a set of physical resource blocks (PRBs). Each PRB is used by the base-station to transmit exclusively to one user, which is referred to as single-user transmission. Recently, multi-user transmission has been introduced to enable the base-station to simultaneously serve multiple users using the same PRB. While multi-user transmission can be much more efficient than its single-user counterpart, it is significantly more challenging to operate. Thus, in this thesis we study the operation, i.e., the Radio Resource Management (RRM), for two popular multi-user transmission technologies; namely, 1) Non-Orthogonal Multiple Access (NOMA) and 2) Multi-User Multiple-Input Multiple-Output (MU-MIMO). For NOMA RRM, we study a multi-cell, multi-carrier downlink system. First, we formulate and solve a centralized proportional fair scheduling genie problem that jointly performs user selection, power allocation and power distribution, and Modulation and Coding Scheme (MCS) selection. While such a centralized schedule is practically infeasible, it upper bounds the achievable performance. Then, we propose a simple static coordinated power allocation scheme across all cells for NOMA using a simple power map that is easily calibrated offline. We find that using a simple static coordinated power allocation scheme improves performance by 80% compared to equal power allocation. Finally, we focus on online network operation and study practical schedulers that perform user-selection, power distribution, and MCS selection. We propose a family of practical scheduling algorithms, each of them exhibiting a different trade-off between complexity (i.e., run-time) and performance. The one we selected sacrifices a maximum of 10% performance while reducing the computation time by a factor of 45 with respect to the optimal user scheduler. For MU-MIMO RRM, we focus on the study of the downlink of an OFDMA massive MU-MIMO single cell assuming ZFT (Zero Forcing Transmission) precoding. An offline study is initiated with the goal of finding the best achievable performance by jointly optimizing user-selection, power distribution and MCS selection. The best performance is analyzed by using both Branch-Reduce-and-Bound (BRB) global optimization technique for upper-bounding the achievable performance and a set of different greedy searches for lower bounding the achievable performance to find good feasible solutions. The results suggest that a specific search strategy referred to as greedy-down-all-the-way (GDAW) with full-drop (FD) is quasi-optimal. Afterwards, we design a simple practical scheduler that achieves 97% of the performance to GDAW with FD and has comparable runtime to that of the state-of-the-art benchmark that selects all users, performs ZFT precoding followed by power distribution using water-filling. The proposed scheme performs a simple round robin grouping to select users, followed by ZFT precoding and joint power distribution and MCS selection via a novel greedy algorithm with a possible additional iteration to take zero-rate users into account. Our solution outperforms the benchmark by 281%

Beamforming and non-orthogonal multiple access for rate and secrecy enhancement of fifth generation communication system

The fifth-generation (5G) communication systems have many anticipated functionalities and requirements such as high data rate, massive connectivity, wide coverage area, low latency and enhanced secrecy performance. In order to meet these criteria, communication schemes that combine 5G key enabling technologies need to be investigated. In this thesis, a novel communication system that merges non-orthogonal multiple access (NOMA), energy harvesting, beamforming, and full-duplex (FD) techniques in order to enhance both capacity and secrecy of 5G system is introduced. In the capacity improving scheme, NOMA is first combined with beamforming to serve more than one user in each beamforming vector. Next, simultaneous wireless information and power transfer (SWIPT) technique is exploited to encourage the strong user (user with better channel condition) to relay the information messages of the weak user (user with poor channel condition) in FD manner. The total sum rate maximisation problem is formulated and solved by means of convex-concave procedure. The system performance is also analysed by deriving the outage probability of both users. Additionally, the model is extended to a more general case wherein the users are moving, and the outage probability of this dynamic topology is provided by means of the stochastic geometry framework. Novel secure schemes are also introduced to safeguard legitimate users’ information from internal and external eavesdroppers. In the internal eavesdropper’s case, artificial signal concept is adopted to protect NOMA’s weak user’s information from being intercepted by the strong user. The secrecy outage probability of theweak user is derived and validated. In addition, game theory discipline is exploited to provide an efficient eavesdropping avoidance algorithm. Null-steering beamforming is adopted in the external eavesdropper’s case in two different schemes namely self and nonself-cooperative jamming. In self-cooperative strategy, the base station applies the null-steering jamming to impair the eavesdropper channel, while sending the information-bearing signals to the intended legitimate users. Whereas in the nonself-cooperative jamming scheme, the base station provides the helpers with the required information and power by means of SWIPT technique in the first phase. The helpers deploy null-steering beamforming to jam the eavesdropper during the information exchange between the base station and the intended users in the second phase. The secrecy outage probability of the legitimate users is derived in both jamming schemes. Game theory is also introduced to the nonself-cooperative jamming scheme for further improvements on the secrecy outage behaviour and the economic revenue of the system. The proposed capacity enhancing scheme demonstrates about 200% higher sum rate when compared with the non-cooperative and half-duplex cooperative NOMA systems. In addition, the novel secure scheme in the internal eavesdropper case is proven to enhance the information security of the weak user without compromising the functionalities of the strong user or NOMA superiority over orthogonal multiple access systems. Null-steering based jamming system also illustrates improved secrecy performance in the external eavesdropper case when compared to the conventional jamming schemes. Numerical simulations are carried out in order to validate the derived closed-form expressions and to illustrate the performance enhancement achieved by the proposed schemes where the rate is increased by 200% and the secrecy outage probability is decreased by 33% when compared to the baseline systems

Robust beamforming and user clustering for guaranteed fairness in downlink NOMA with partial feedback

In this paper, a downlink multiuser non-orthogonal multiple access (NOMA) with full and partial channel state information (CSI) feedback is considered. We investigate beam design and user clustering from the throughput-fairness trade-off perspective. To enhance this trade-off, two proportional fairness (PF) based scheduling algorithms are proposed, each has two stages. The first algorithm is based on integrating the maximum product of effective channel gains and the maximum signal to interference ratio with the PF principle (PF-MPECG-SIR), to select the strong users in the first stage and the weak users in the second stage. This algorithm is designed to maximize the throughput with moderate fairness enhancement. Whereas, in the second algorithm, the MPECG and the maximum correlation are combined within the PF selection criterion (PF-MPECG-CORR) in order to maximize the fairness with a slight degradation in the total throughput. In addition, we present an optimal power allocation that can achieve a high data rate for the overall system without sacrificing the sum-rate of weak users under full and partial CSI. Simulation results show that the proposed PF-MPECG-CORR can significantly improve the fairness up to 50.82% and 44.90% with only 0.42% and 1.13% degradation in the total throughput, for full and partial CSI, respectively. All these performance gains are achieved without increasing the computational complexity

Subcarrier and Power Allocation for the Downlink of Multicarrier NOMA Systems

International audienceThis paper investigates the joint subcarrier and power allocation problem for the downlink of a multi-carrier non-orthogonal multiple access (MC-NOMA) system. A novel three-step resource allocation framework is designed to deal with the sum rate maximization problem. In Step 1, we relax the problem by assuming each of the users can use all subcarriers simultaneously. With this assumption, we prove the convexity of the resultant power control problem and solve it via convex programming tools to get a power vector for each user; In Step 2, we allocate subcarriers to users by a heuristic greedy manner with the obtained power vectors in Step 1; In Step 3, the proposed power control schemes used in Step 1 are applied once more to further improve the system performance with the obtained sub-carrier assignment of Step 2. To solve the maximization problem with fixed subcarrier assignments in both Step 1 and Step 3, a centralized power allocation method based on projected gradient descent algorithm and two distributed power control strategies based respectively on pseudo-gradient algorithm and iterative waterfilling algorithm are investigated. Numerical results show that our proposed three-step resource allocation algorithm could achieve comparable sum rate performance to the existing near-optimal solution with much lower computational complexity and outperforms power controlled OMA scheme. Besides, a tradeoff between user fairness and sum rate performance can be achieved via applying different user power constraint strategies in the proposed algorithm