Quantum-inspired evolutionary algorithm for large-scale MIMO detection

Mohammed A. Teeti, Rui Wang, Hua Chen, Yingzhuang Liu, Qiang Ni

Abstract: In this paper we propose a novel evolutionary detection algorithm for large-scale multiple-input multiple-output (MIMO) systems, utilizing the concepts of quantum bit and quantum rotation gate in quantum computing. Specifically, we consider the detection of BPSK and 4-QAM signals, and the uncertainty on the information bits at the receiver is modeled as a sequence of quantum bits, which is referred to as a quantum particle. The proposed algorithm begins with a population of such particles, each initialized randomly. Then by the aid of quantum rotation gate along with a fitness function, a simple mechanism is proposed to allow all quantum particles to evolve in a guided manner towards a potentially optimal area and finally converges. It is shown by simulations that the proposed algorithm can achieve near-optimal performance.