Deployment of mmWave multi-UAV mounted RISs using budget constraint Thompson sampling with collision avoidance

Abstract

In this paper, we will consider the problem of multi-unmanned aerial vehicles (UAVs) deployment among users’ hotspots. UAVs carry reconfigurable intelligent surface (RIS) boards to strengthen millimeter wave (mmWave) coverage at these hotspots. UAVs should maximize hotspots’ sum data rates while minimizing their flights’ cost, i.e., hovering and flying energy consumptions. Moreover, collisions should be avoided among UAVs, i.e., one hotspot should be served by only one UAV at a time. In this paper, this problem is considered as a multi-player multi-armed bandit (MP-MAB) game with budget constraint and collision avoidance. In this context, budget constraint Thompson sampling (TS) with collision avoidance MAB algorithm (BTSCA-MAB) is proposed to efficiently implement the formulated MP-MAB game. Numerical analysis confirms the superior performance of the proposed BTSCA-MAB over other benchmarks.

Keywords

• Millimeter wave
• Reconfigurable intelligent surface
• Unmanned aerial vehicles
• Multi-armed bandit