Quantum Annealing-Based Sum Rate Maximization for Multi-UAV-Aided Wireless Networks

TL;DR

This paper explores the use of quantum annealing to optimize sum rate in multi-UAV wireless networks by jointly addressing clustering, sub-channel assignment, and power allocation, demonstrating improved performance and efficiency.

Contribution

It introduces a novel QA-based framework for joint optimization in UAV-assisted wireless networks, including a new QUBO formulation and a tailored QA algorithm.

Findings

Enhanced sum rate performance in simulations.

Reduced computational time compared to traditional methods.

Effective joint optimization of clustering and resource allocation.

Abstract

In wireless communication networks, it is difficult to solve many NP-hard problems owing to computational complexity and high cost. Recently, quantum annealing (QA) based on quantum physics was introduced as a key enabler for solving optimization problems quickly. However, only some studies consider quantum-based approaches in wireless communications. Therefore, we investigate the performance of a QA solution to an optimization problem in wireless networks. Specifically, we aim to maximize the sum rate by jointly optimizing clustering, sub-channel assignment, and power allocation in a multi-unmanned aerial vehicle-aided wireless network. We formulate the sum rate maximization problem as a combinatorial optimization problem. Then, we divide it into two sub-problems: 1) a QA-based clustering and 2) sub-channel assignment and power allocation for a given clustering configuration. Subsequently, we obtain an optimized solution for the joint optimization problem by solving these two sub-problems. For the first sub-problem, we convert the problem into a simplified quadratic unconstrained binary optimization (QUBO) model. As for the second sub-problem, we introduce a novel QA algorithm with optimal scaling parameters to address it. Simulation results demonstrate the effectiveness of the proposed algorithm in terms of the sum rate and running time.