Joint Relay Assignment and Channel Allocation for Opportunistic UAVs-Aided Dynamic Networks: A Mood-Driven Approach

Abstract

Except for the unmanned aerial vehicles (UAVs) providing specialized communication service, there may be many other UAVs executing various missions in the air. These UAVs may be idle in communication and thus are considered to work as opportunistic relays to enhance the ground device-to-device (D2D) network. On account of the dynamic behaviors and uncontrollable trajectories of the opportunistic UAVs, real-time relay assignment and channel allocation are two main factors that determine the network capacity. Thus, real-time relay assignment and channel allocation are optimized in this article, aiming to maximize the long-term average total transmission rate of this dynamic network. In order to implement relay assignment via the decentralized approach and resist the dynamic network characteristic, a mood-driven online learning relay selection approach is proposed for the D2D pairs, which not only utilizes the immediate transmission rate but also the variation tendency of the transmission rate. As a result, the dynamic network always has a tendency to increase its total transmission rate. For the reason that the characteristic of channel selection in the dynamic network is similar to relay selection, a mood-driven approach that similar to the one used for relay selection is proposed for channel selection. And then, a time slot model is designed for joint relay selection and channel selection. Simulation results show that the opportunistic UAVs can significantly enhance the total transmission rate of the network and the proposed mood-driven approach can adapt to the dynamic characteristic of the network.