Abstract
This paper focuses on the issue of pilot assignment in cell-free massive multiple-input multiple-output systems to efficiently mitigate pilot contamination. A novel pilot assignment strategy based on quantum bacterial foraging optimization (QBFO) is proposed. The quantum bacterial population collapses to the ground state population by measuring to obtain the pilot assignment solutions. In this scheme, we first utilize adaptive quantum rotation gate to imitate chemotaxis. Then, the health of bacterium is introduced to record the cumulative fitness sum of each bacterium. Moreover, we consider elimination-dispersal operation in order to avoid being trapped in the local optimum. Numerical results show the superiority of the proposed scheme to other traditional schemes and validate that the proposed scheme can significantly improve system's average downlink throughput.
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