Joint User Association and Pairing in Multi-UAV- Assisted NOMA Networks: A Decaying-Epsilon Thompson Sampling Framework

Unmanned aerial vehicles (UAVs) are expected to be integrated into future wireless networks to offer services, especially in unreachable or congested areas. To improve the spectral efficiency, non-orthogonal multiple access (NOMA) scheme can be utilised within the UAV communication to allow more users to be covered and associated. The performance of the NOMA-UAVs network is governed by several factors including power allocation, user association and pairing methods. This paper presents an approach that uses multi-armed bandit (MAB) and two-sided matching frameworks to maximize the throughput of multi-UAV-assisted NOMA networks in a decentralized manner. The approach enables the UAVs to propose to the ground users (GUs) without explicit cooperation among the UAVs while the GUs can accept or reject the proposals. To this end, we propose a modified Thompson sampling algorithm that we named decaying epsilon Thompson sampling (
$\text {D}\epsilon \text {TS}$
) MAB algorithm that is designed to improve the exploration-exploitation tradeoff in the MAB. The performance of the proposed
$\text {D}\epsilon \text {TS}$
MAB algorithm is evaluated against other existing MAB techniques. Simulation results show that the
$\text {D}\epsilon \text {TS}$
algorithm attains faster convergence and improved performance in terms of smaller regret and increased achievable system throughput. The
$\text {D}\epsilon \text {TS}$
MAB algorithm particularly excels in regards of the convergence rate when the number of available action spaces increases.