Turbo-Like Beamforming Based on Tabu Search Algorithm for Millimeter-Wave Massive MIMO Systems

摘要

For millimeter-wave (mmWave) massive MIMO systems, the codebook-based analogbeamforming (including transmit precoding and receive combining) is usuallyused to compensate the severe attenuation of mmWave signals. However,conventional beamforming schemes involve complicated search among pre-definedcodebooks to find out the optimal pair of analog precoder and analog combiner.To solve this problem, by exploring the idea of turbo equalizer together withtabu search (TS) algorithm, we propose a Turbo-like beamforming scheme based onTS, which is called Turbo-TS beamforming in this paper, to achieve thenear-optimal performance with low complexity. Specifically, the proposedTurbo-TS beamforming scheme is composed of the following two key components: 1)Based on the iterative information exchange between the base station and theuser, we design a Turbo-like joint search scheme to find out the near-optimalpair of analog precoder and analog combiner; 2) Inspired by the idea of TSalgorithm developed in artificial intelligence, we propose a TS-basedprecoding/combining scheme to intelligently search the best precoder/combinerin each iteration of Turbo-like joint search with low complexity. Analysisshows that the proposed Turbo-TS beamforming can considerably reduce thesearching complexity, and simulation results verify that it can achieve thenear-optimal performance.