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

Jeong, Seon-Geun; Duc, Pham Dang Anh; Do, Quang Vinh; Noh, Dae-Il; Tung, Nguyen Xuan; Van Chien, Trinh; Pham, Quoc-Viet; Hasegawa, Mikio; Sekiya, Hiroo; Hwang, Won-Joo

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

Feb 25, 2025

15 pages

e-Print:

2502.17916 [cs.IT]

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Abstract: (arXiv)

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.

Note:

15 pages, 9 figures, and 2 tables. Accepted by IEEE IoT Journal

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