Improving Connectivity of RIS-Assisted UAV Networks using RIS Partitioning and Deployment

TL;DR

This paper introduces a novel RIS deployment and partitioning strategy to enhance connectivity in UAV networks, optimizing RIS placement and virtual partitioning to improve communication reliability beyond existing methods.

Contribution

It proposes a joint RIS deployment and virtual partitioning framework with closed-form SNR expressions and an optimization approach using simulated annealing for improved UAV network connectivity.

Findings

Significant improvement in network connectivity over RIS-free benchmarks.

Effective RIS partitioning enhances cascaded channel formation.

Optimized 3D RIS deployment outperforms single-beam RIS configurations.

Abstract

Reconfigurable intelligent surface (RIS) is pivotal for beyond 5G networks in regards to the surge demand for reliable communication in unmanned aerial vehicle (UAV) networks. This paper presents an innovative approach to maximize connectivity of UAV networks using RIS deployment and virtual partitioning, wherein an RIS is deployed to assist in the communications between an user-equipment (UE) and blocked UAVs. Closed-form (CF) expressions for signal-to-noise ratio (SNR) of the two-UAV setup are derived and validated. Then, an optimization problem is formulated to maximize network connectivity by optimizing the 3D deployment of the RIS and its partitioning subject to predefined quality-of-service (QoS) constraints. To tackle this problem, we propose a method of virtually partitioning the RIS given a fixed 3D location, such that the partition phase shifts are configured to create cascaded channels between the UE and the blocked two UAVs. Then, simulated-annealing (SA) method is used to find the 3D location of the RIS. Simulation results demonstrate that the proposed joint RIS deployment and partitioning framework can significantly improve network connectivity compared to benchmarks, including RIS-free and RIS with a single narrow-beam link.