Massive MIMO-NOMA Networks With Imperfect SIC: Design and Fairness Enhancement

Abstract

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high,

What Role Do Intelligent Reflecting Surfaces Play in Multi-Antenna Non-Orthogonal Multiple Access?

“…This above achievement can be visualized in the simulation results presented in Fig. 3, where we employ to MIMO-NOMA and IRS-NOMA both fixed and the fair power allocation policy developed in [11]. Here, we consider the existence of two users per NOMA group, one located at 100 m and another at 200 m from the BS.…”

Beamforming Optimization and Power Allocation for User-Centric MIMO-NOMA IoT Networks

“…Then, The authors in [17] derive an exact closedform expression for the outage probability through carrying out the in-depth analytical analysis. [18] addresses multi-user multi-cluster massive MIMO systems with NOMA. In [18], the power optimization is simplified to a convex problem, and then an iterative algorithm is proposed to provide fairness also among different sub-groups.…”

“…[18] addresses multi-user multi-cluster massive MIMO systems with NOMA. In [18], the power optimization is simplified to a convex problem, and then an iterative algorithm is proposed to provide fairness also among different sub-groups.…”

Two-Way Relaying Non-Orthogonal Multiple Access With Imperfect Successive Interference Cancellation in Power Line Communications

“…3 The imperfect SIC coefficient characterizes the total error propagation due to imperfect signal decoding, synchronization, imperfect CSI, and high signal attenuation issues [22]. Through long-term measurements, the imperfect SIC coefficient can be estimated by comparing the power of the residual interference term to the power of the received signal [34], [35].…”