QoE-Aware and Secure UAV-Aided Rate-Splitting Multiple Access Based Communications

TL;DR

This paper proposes a novel framework for optimizing QoE in UAV-assisted multiuser RSMA networks, focusing on secure communications by jointly optimizing beamforming, rate allocation, and UAV trajectory.

Contribution

It introduces a comprehensive optimization approach that combines convexification techniques for beamforming, rate allocation, and UAV trajectory under secrecy constraints.

Findings

The proposed method improves QoE in UAV-assisted RSMA networks.

Convexification techniques effectively handle nonconvex constraints.

Simulation results demonstrate the framework's efficiency.

Abstract

In this work, we address the issue of quality of experience (QoE) in unmanned aerial vehicle (UAV) aided multiuser rate-splitting multiple access (RSMA) networks under secrecy constraints. The problem is formulated as maximization of sum mean opinion scores (MOSs) of the users. The problem is decomposed into two subproblems, beamforming and rate allocation and UAV trajectory subproblem. For, beamforming and rate allocation subproblem, we use the epigraph method, property of polynomials, and the norm-bounded error of channels, we linearize the objective function. Then, applying second-order conic (SOC) and first Taylor expansion, we convexify the remaining nonconvex constraints. For the highly nonconvex UAV trajectory, we unroll the constraints and we apply first Taylor expansion on the unrolled constraints. The simulation results demonstrate the efficiency of the proposed framework.