Access Point Selection in Cell-Free Massive Multiple-Input Multiple-Output Non-Orthogonal Multiple Access System Based on Quantum Bacterial Foraging Optimization

Access Point(AP) selection in cell-free massive Multiple-Input Multiple-Output Non-Orthogonal Multiple Access(MIMO-NOMA) system has a great impact on effectively reducing the backhaul overhead and improving the user's downlink achievable rate. In this paper, the expression of the downlink average rate of the user is derived for the cell-free massive MIMO-NOMA system using AP selection. Then, a novel AP selection strategy based on Quantum Bacterial Foraging Optimization(QBFO) is proposed, which encodes the connection relationship between APs and users in the form of qubits. The adaptive quantum rotation gate is used to simulate the chemotaxis of bacteria. By measuring the quantum bacterial population, the selection solution set of APs and the users is obtained, and the dispersal operation is introduced to avoid the algorithm from falling into local optimum. Numerical results show that the proposed scheme can significantly improve the downlink average rate of users while relieving the backhaul burden. Compared with the schemes based on received power and channel estimation mean square error, the proposed scheme has better performance in reducing inter-user interference and improving the total throughput of the system.