Multi-qubit Bacterial Foraging Optimization Based Pilot Assignment and Access Point Selection in Cell-Free Massive MIMO

Abstract

This paper proposes an innovative approach that employs multi-qubit Bacterial Foraging Optimization (mQBFO) algorithm to solve the pilot assignment and Access Point (AP) selection problems in cell-free massive Multi-Input Multi-Output (MIMO) communication systems. It uses multi qubits to indicate a bacterium, and uses an adaptive quantum rotation gate to simulate the chemotaxis phenomenon in the classical bacterial algorithm to achieve bacterial state update. It also introduces the bacterial health degree, which is used to record the cumulative sum of fitness of each bacterium. To avoid falling into local optimal solutions, the elimination-dispersal operation is considered. Finally, the quantum bacterial population is collapsed into a ground state population by measurement to get the solution of the optimization problem. The numerical results prove that the proposed scheme outperforms the traditional schemes in pilot assignment and AP selection, and can effectively improve the average downlink throughput of the system.