RIS Alignment via Virtual Partitioning for Resilient Uplink Multi-RIS-Assisted UAV Communications

The integration of reconfigurable intelligent surfaces (RISs) and unmanned aerial vehicle (UAV) communications has emerged as a promising solution for improving link quality and massive connectivity for beyond 5G wireless networks. This paper presents an innovative approach to maximizing connectivity of uplink multi-RIS-assisted UAV networks enabled by RIS placement and virtual partitioning, wherein RISs are deployed to assist in the communications between user-equipment (UEs) and UAVs. In the considered model, the UEs intend to transmit data to the UAVs, and RISs can assist in improving network connectivity by connecting the UEs to the blocked UAVs. First, exact and approximated closed-form (CF) expressions for signal-to-noise ratio (SNR) are derived based on aligned and non-aligned portions of the RISs. Then, we formulate the problem of maximizing the network connectivity that jointly considers 1) UE-RIS-UAV link selection and 2) RIS placement and virtual partitioning. This problem is a computationally expensive combinatorial optimization. Using the block coordinate descent (BCD) approach, we propose novel UE-RIS-UAV selection and RIS placement and partitioning methods. Specifically, we develop clustering and perturbation methods for UE-RIS-UAV selection, and derive a closed-form solution for the partitioning of the RISs. Moreover, for optimizing the RISs placement, Adam optimizer is used. Simulation results demonstrate that the proposed approaches yield a gain in the range of 12% to 45% compared to benchmark schemes. The finding emphasizes the potential of integrating RIS with UAV communications as a robust and reliable connectivity solution for future wireless communication systems.