Multi-user hybrid precoding for mmWave massive MIMO systems with sub-connected structure

Author:

Du JianheORCID,Wang Zekun,Zhang Yang,Guan Yalin,Jin Libiao

Abstract

AbstractHybrid precoding achieves a compromise between the sum rate and hardware complexity of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. However, most prior works on multi-user hybrid precoding only consider the full-connected structure. In this paper, a novel multi-user hybrid precoding algorithm is proposed for the sub-connected structure. Based on the improved successive interference cancellation (SIC), the analog precoding matrix optimization problem is decomposed into multiple analog precoding sub-matrix optimization problems. Further, a near-optimal analog precoder is designed through factorizing the precoding sub-matrix for each sub-array. Furthermore, digital precoding is designed according to the block diagonalization (BD) technology. Finally, the water-filling power allocation method is used to further improve the communication quality. The extensive simulation results demonstrate that the sum rate of the proposed algorithm is higher than the existing hybrid precoding methods with the sub-connected structure, and has higher energy efficiency compared with existing approaches. Moreover, the proposed algorithm is closer to the state-of-the-art optimization approach with the full-connected structure. In addition, the simulation results also verify the effectiveness of the proposed hybrid precoding design of the uniform planar array (UPA).

Funder

The National Natural Science Foundation of China

The National Key Research and Development Program of China

The Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Signal Processing

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1. Mmwave massive MIMO: one joint beam selection combining cuckoo search and ant colony optimization;EURASIP Journal on Wireless Communications and Networking;2023-07-21

2. Multi-User mmWave Massive-MIMO Hybrid Beamforming: A Quantize Deep Learning Approach;2023 National Conference on Communications (NCC);2023-02-23

3. Deep Learning Aided Multi-user mmWave massive-MIMO Hybrid Beamforming;2022 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS);2022-12-18

4. Spectral-efficient hybrid precoding for multi-antenna multi-user mmWave massive MIMO systems with low complexity;EURASIP Journal on Wireless Communications and Networking;2022-07-26

5. Hybrid Precoding Algorithm for Millimeter-Wave Massive MIMO-NOMA Systems;Electronics;2022-07-13

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