NOMA for STAR-RIS Assisted UAV Networks

TL;DR

This paper introduces a STAR-RIS assisted UAV NOMA network for emergency communications, optimizing UAV trajectory, beamforming, and resource allocation with a novel LRCPPO algorithm, demonstrating improved performance over benchmarks.

Contribution

It proposes a new STAR-RIS assisted UAV NOMA architecture and a LRCPPO algorithm for joint optimization in emergency networks, addressing practical constraints.

Findings

The proposed algorithm effectively improves network throughput.

STAR-RIS assisted UAV NOMA outperforms reflecting-only RIS and OMA schemes.

Numerical results validate the efficiency of the joint optimization approach.

Abstract

This paper proposes a novel simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted unmanned aerial vehicle (UAV) non-orthogonal multiple access (NOMA) emergency communication network. Multiple STAR-RISs are deployed to provide additional and intelligent transmission links between trapped users and UAV-mounted base station (BS). Each user selects the nearest STAR-RIS for uploading data, and NOMA is employed for users located at the same side of the same STAR-RIS. Considering piratical requirements of post-disaster emergency communications, we formulate a throughput maximization problem subject to constraints on minimum average rate and maximum energy consumption, where the UAV trajectory, STAR-RIS passive beamforming, and time and power allocation are jointly optimized. Furthermore, we propose a Lagrange based reward constrained proximal policy optimization (LRCPPO) algorithm, which provides an adaptive method for solving the long-term optimization problem with cumulative constraints. Specifically, using Lagrange relaxation, the original problem is transformed into an unconstrained problem with a two-layer structure. The inner layer is solved by penalized reward based proximal policy optimization (PPO) algorithm. In the outer layer, Lagrange multipliers are updated by gradient descent. Numerical results show the proposed algorithm can effectively improve network performance while satisfying the constraints well. It also demonstrates the superiority of the proposed STAR-RIS assisted UAV NOMA network architecture over the benchmark schemes employing reflecting-only RISs and orthogonal multiple access.