A novel artificial bee colony detection algorithm for massive MIMO system

As a hot-spot of 5G, the research on detection algorithms for massive multiple input multiple output (MIMO) system is significant but difficult. The traditional MIMO detection algorithms or their improvements are not appropriate for large scaled antennas. In this paper, we propose artificial bee colony (ABC) detection algorithm for massive MIMO system. As one advanced technology of swarm intelligence, ABC algorithm is most efficient for large scaled constrained numerical combinatorial optimization problem. Therefore, we employ it to search the optimum solution vector in the modulation alphabet with linear detection result as initial. Simulation and data analysis prove the correctness and efficiency. Versus the scale of massive MIMO systems from 64 × 64 to 1024 × 1024 with uncoded four-quadrature-amplitude-modulation signals, the proposed ABC detection algorithm obtains bit error rate of 10^− 5 at low average received signal-to-noise-ratio of 12 dB with rapid convergence rate, which approximates the optimum bit error rate performance of the maximum likelihood and achieves the theoretical optimum spectral efficiency with low required average received signal-to-noise-ratio of 10 dB in similar increasing regularity, over finite time of low polynomial computational complexity of (N² _T) per symbol, where N_T denotes the transmitting antennas' number. The proposed ABC detection algorithm is efficient for massive MIMO system.