Resource Allocation and Placement for Tethered Flying Platform-Aided IAB Network: Distributed DQN Approach

Abstract

The integration of the integrated access and back-haul (IAB) network and tethered flying platform (TFP) solves the performance degradation problem of airborne base stations (ABS) due to battery constraints and provides flexibility in topology. Therefore, this study proposes a distributed deep Q-Network (DQN)-based resource allocation and tethered unmanned aerial vehicles (TUAVs) placement control (RAPC) joint optimization scheme to maximize the total sum rate of IAB network supported by TUAVs and tethered balloon (TB). Simulations demonstrate that the RAPC achieves a high aggregate total sum rate compared to several benchmarks, and has robust performance maintained in various ground users (GUs) moving speed environments.