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

TL;DR

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.

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.

Figures (5)

• Figure 1: Uplink RIS-assisted UAV model with one partitioned RIS, where RIS elements are virtually partitioned and coherently aligned (configured) with UAV$_x$ and UAV$_y$.
• Figure 2: Rate performance versus: (left) $\rho_{x}$ and (right) number of RIS elements $N$ for $\rho_{x}=0.8$ and $b=4$.
• Figure 3: Network connectivity versus the number of UAVs $K$ for $N=100$, $\gamma^\text{RIS}_{0}=60$ dB, and $\zeta=0.2$.
• Figure 4: Network connectivity versus the number of RIS elements $N$ for $K=8$, $\gamma^\text{RIS}_{0}=60$ dB, and $\zeta=0.2$.
• Figure 5: Rates of $\text{UE} \rightarrow \text{UAV}_{x}$ and $\text{UE} \rightarrow \text{UAV}_{y}$ links and the corresponding RIS portions versus (a) $\zeta$ for $\gamma^\text{RIS}_{0}=60$ dB and (b) $\gamma^\text{RIS}_{0}$ for $\zeta=0.1$.