Sub-Array Hybrid Beamforming for Sustainable Largescale mmWave-MIMO Communications

Hybrid beamforming has recently received substantial attention as a substitute to fully digital beamforming. The current hybrid beamforming structures can be categorized into two classes: fully-connected and sub-connected phase shifters. The former type includes a large number of phase shifters which results in an excessive energy consuming, while the later arrangement endures a serious spectral performance loss although of low energy consuming. This paper considers a low complexity algorithm to fulfill a sub-connected hybrid-BF which leverages an iterative optimization algorithm matrix vectorization property to update the baseband-BF and leverages the property of the feasible set for the passband-BF to drop the unit-modulus limits from the optimization task, and hence transform the matrix-problem into a simpler phase-rotated vector-problem to update the passband-BF. In addition, the initial beamforming vectors for the iterative process, i.e., the algorithm starting point, is determined from the optimal fully digital-BF according to the lest square error approach which assist in improving the convergence speed of the algorithm. We investigate the effects of different scheme parameters on the performance, which offer good insights for HP systems. The numerical results demonstrate the superior performance of the suggested designs compared to the some of the benchmark reference approaches. The simulation results show that the spectral efficiency of this algorithm is at least 54% higher than the traditional fully-analog algorithms at 5 dB SNR. Additionally, it increases energy efficiency by at least 36% compared with the orthogonal matching pursuit algorithm for number of RF-chain of 18.