Quantum-Accelerated Nash Equilibrium Search for Optimal Relay Selection in Wireless Networks

In wireless networks, optimizing relay selection is crucial for enhancing efficiency and improving user experience. Traditional methods often struggle to adapt to dynamic network conditions, leading to sub-optimal performance. Nash Equilibrium, where no user can unilaterally improve its Quality of Experience (QoE), offers a stable solution but is computationally demanding, especially in large networks. To address this challenge, we propose a novel approach leveraging quantum computing techniques, specifically quantum game theory, to efficiently achieve Nash Equilibrium in relay selection. Our method promises significant reductions in computational complexity while offering more robust and optimal relay selection strategies. By capturing the intricate dynamics of relay selection using quantum mechanics, we aim to advance network optimization and improve overall performance. Potential applications include scenarios where rapid adaptation to changing network conditions is essential for maintaining high-quality communication.

I. Introduction

In the fast-paced landscape of modern wireless communication, the demand for efficient and reliable data transmission has become increasingly paramount. Traditional cellular networks face challenges in delivering seamless connectivity, particularly in scenarios where direct communication between devices is hindered by obstacles or long distances[1]. Device-to-Device (D2D) communication and relaying emerge as indispensable solutions to overcome these hurdles. Facilitating direct communication between nearby devices and extending network coverage [2]. By leveraging relaying, users can by-pass the traditional infrastructure of base stations, reducing latency, enhancing network throughput, and conserving en-ergy. Moreover, relay communications holds the potential to alleviate network congestion and improve overall Quality of Experience (QoE) for users, making it a promising avenue for advancing wireless communication systems[3].