Joint Phase Shift and Deployment Optimization for Multi-RIS-aided Emergency Communications

In post-disaster scenario, the irregular and scattered distribution of obstacles usually poses challenges to emergency communications. As a promising technology, reconfigurable intelligence surfaces (RISs) can reduce the impact of obstacles and expand the coverage of the base station (BS) by optimizing their phase-shift and deployment. However, the existing work has only applied RISs to barrier-free or simple-barrier scenarios. In this paper, multi-RIS-aided emergency communications are studied under the complex-barrier scenario after disasters, where strong coupling between RISs is introduced. Specifically, we jointly optimize the phase-shift and deployment of multiple RISs to maximize the weight sum-rate (WSR) with ensuring communications fairness for post-disaster users. An alternating iterative algorithm for this multi-RIS-aided complex-barrier scenario (AI-MRCB) is proposed, which is based on the successive convex approximation (SCA) and the alternating direction method of multipliers (ADMM). Simulation results show that the proposed AI-MRCB method can deploy RISs appropriately and improve users’ WSR than the existing work.