Spatial Lobes Division-Based Low Complexity Hybrid Precoding and Diversity Combining for mmWave IoT Systems

This paper focuses on the design of low complexity hybrid analog/digital precoding and diversity combining in millimeter wave (mmWave) Internet of Things (IoT) systems. First, by exploiting the sparseness property of the mmWave in the angular domain, we propose a spatial lobes division (SLD) to group the total paths of the mmWave channel into several spatial lobes (SLs), where the paths in each SLs form a low-rank subchannel. Second, based on the SLD operation, we propose a low complexity hybrid precoding scheme, named hybrid precoding based on SLD (HYP-SLD). Specifically, for each low-rank subchannel, we formulate the hybrid precoding design as a sparse reconstruction problem and separately maximizes the spectral efficiency. Finally, we further propose a maximum ratio combining-based diversity combining scheme, named HYP-SLD-MRC, to improve the bit error rate (BER) performance of mmWave IoT systems. Simulation results demonstrate that, the proposed HYP-SLD scheme significantly reduces the complexity of the classic orthogonal matching pursuit scheme. Moreover, the proposed HYP-SLD-MRC scheme achieves great improvement in BER performance compared with the fully digital precoding scheme.