Distributed Demand-Aware Channel-Slot Selection for Multi-UAV Networks: A Game-Theoretic Learning Approach

Abstract

Over the past decades, the unmanned aerial vehicle (UAV) has received unprecedented surge of scientific and military interest worldwide. This paper investigates the problem of opportunistic spectrum access for multi-UAV networks from a game-theoretic perspective. Due to the topology of the multi-UAV networks, the interference may be classified into two parts, i.e., the intra-cluster and the inter-cluster interference. Moreover, since the UAVs in the network have different tasks, the communication demand of each UAV should be taken into account. First, we formulate the demand-aware joint channel-slot selection problem as a weighted interference mitigation game, and then, design the utility function considering features of multi-UAV network, e.g., some rewards due to the channel and slots selection. We prove that the formulated game is an exact potential game with at least one pure-strategy Nash equilibrium. Next, we apply the distributed log-linear algorithm to achieve the desired optimization and overcome the constraint of dynamic communication demand of each UAV. To speed up the convergence, we also propose a low-complexity and realistic channel and slot initialization scheme for UAVs. Finally, the simulation results validate the effectiveness of the formulated game.