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

TL;DR

This paper introduces a low complexity hybrid precoding and diversity combining method for mmWave IoT systems, leveraging spatial lobes division to enhance spectral efficiency and BER performance with reduced computational complexity.

Contribution

It proposes a novel spatial lobes division (SLD) technique and hybrid precoding scheme (HYP-SLD), along with a diversity combining method (HYP-SLD-MRC), for efficient mmWave IoT communication.

Findings

HYP-SLD reduces complexity compared to OMP.

HYP-SLD-MRC improves BER performance.

Proposed methods outperform traditional schemes in simulations.

Abstract

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. Firstly, 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, where the paths in each spatial lobe form a low-rank sub-channel. Secondly, based on the SLD operation, we propose a low complexity hybrid precoding scheme, named HYP-SLD. Specifically, for each low-rank sub-channel, 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 (OMP) scheme. Moreover, the proposed HYP-SLD-MRC scheme achieves great improvement in BER performance compared with the fully digital precoding scheme.