Joint resource allocation of IRS-aided massive MIMO system with Quantum Water Strider Algorithm

Leveraging the characteristics of intelligent reflecting surface (IRS), the data transmission rate and channel capacity of massive MIMO system are significantly improved. In this paper, a model of IRS-aided massive MIMO communication system containing a number of base station antennas, receiving terminal antennas, and an intelligent reflecting surface containing a number of passive reflecting elements is established. For IRS-aided massive MIMO system, in order to resolve channel capacity optimization problem which is a non-convex optimization problem and is difficult to effectively obtain an exact solution, we propose a novel algorithm which is called quantum-inspired water strider algorithm (QWSA). A novel quantum swarm intelligence mechanism derived from quantum theory of computation has been newly designed in this algorithm, namely the quantum water strider adjusts its quantum position not only according to global best of population but also according to the main idea of the quantum water striders within the same group. In IRS-aided massive MIMO system, through joint resource allocation of reflection matrix and transmit covariance matrix, QWSA is applied to solve the optimization problem of channel capacity. Through simulation experiments for the engineering application problem, it is verified that the algorithm significantly improves channel capacity of IRS-aided massive MIMO system.