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.