Exploiting Movable Antennas in NOMA Networks: Joint Beamforming, Power Allocation and Antenna Position Optimization

TL;DR

This paper proposes a joint optimization framework for movable antenna positions, beamforming, and power allocation in NOMA networks, significantly improving throughput by exploiting antenna mobility at both the base station and users.

Contribution

It introduces an efficient alternating optimization algorithm for joint antenna position, beamforming, and power control in MA-assisted NOMA networks, a novel approach to enhance system throughput.

Findings

Proposed method outperforms benchmarks in throughput.

Joint optimization of antenna positions and power improves performance.

Algorithm converges to a stable, locally optimal solution.

Abstract

This paper investigates the movable antenna (MA)- assisted downlink non-orthogonal multiple access (NOMA) network to maximize system throughput. In the considered scenario, both the base station (BS) and users are equipped with MA, and a predetermined successive interference cancellation (SIC) decoding order is adopted. Based on the field-response channel model, we formulate a complex, non-convex problem to jointly optimize the BS beamforming, power allocation, and MA positions at both the transmitter and receivers. To address this, we propose an efficient algorithm based on an alternating optimization (AO) framework, which decomposes the original problem into three distinct subproblems. By employing sequential parametric convex approximation (SPCA) and successive convex approximation (SCA) techniques, the non-convex constraints within each subproblem are transformed into tractable. This methodology ensures the algorithm converges to a stable, locally optimal solution. Numerical results validate that the proposed system, which fully exploits the degrees of freedom from antenna mobility at both ends, significantly outperforms benchmarks in terms of throughput.