Weighted Sum-Rate Maximization for RIS-UAV-assisted Space-Air-Ground Integrated Network with RSMA
Jian He, Cong Zhou, Shuo Shi

TL;DR
This paper proposes a joint optimization framework for RIS-UAV-assisted SAGIN to maximize weighted sum-rate using advanced algorithms for beamforming, deployment, and phase shifts.
Contribution
It introduces a novel RSMA-based optimization approach for SAGIN, integrating multiple algorithms to handle the non-convex problem effectively.
Findings
Proposed algorithm outperforms existing methods in sum-rate performance.
Joint optimization significantly improves network throughput.
Effective deployment of RIS-UAV enhances signal quality and interference management.
Abstract
In this paper, a rate-splitting multiple access (RSMA) based joint optimization framework for the space-air-ground integrated network (SAGIN) is proposed, where the satellite and base stations employ uniform planar array (UPA) antennas for signal transmission, and unmanned aerial vehicles (UAVs) relay the satellite signals. Earth stations (ESs) and user equipments (UEs) receive signals from satellite and base stations (BSs), respectively, resulting in mutual interference. We first model the channels and signals in this scenario and analyse the interference at BSs and UEs. Then, We formulate a joint optimization problem aimed at maximizing the weighted sum-rate, involving beamforming, RIS-UAV deployment and phase shifts, and rate splitting. However, this problem is highly non-convex. To tackle this challenge, we apply a block coordinate descent (BCD) approach to decompose the problem and…
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