Deep Learning Based Joint Hybrid Precoding and Combining Design for mmWave MIMO Systems

Liu, Fulai; Li, Xiaoyu; Yang, Xianghuan; Shi, Huiyang; Shi, Baozhu; Du, Ruiyan

doi:10.1109/jsyst.2024.3357712

IEEE Systems Journal

2024

DOI: 10.1109/jsyst.2024.3357712

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Deep Learning Based Joint Hybrid Precoding and Combining Design for mmWave MIMO Systems

Fulai Liu,

Xiaoyu Li,

Xianghuan Yang

et al.

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A Survey on Maximum Ratio Combination: Applications, Evaluation and Future Directions

Feng,

Tian,

Wang

et al. 2024

Electronics

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With the rapid development of wireless communications, the occupation of time and frequency resources becomes more crowded. The exploitation of space resources is necessary and the diversity combining techniques have substantial applications. Diversity combining achieves great diversity gains and improves the ability to combat multipath fading, among which the maximum ratio combining (MRC) performs as the optimal linear combining approach. However, MRC suffers from detrimental factors such as channel fading and no Gaussian noise in practical scenarios. In this paper, we focus on a comprehensive investigation of MRC. Starting from the MRC principle and system model, we summarize typical scenarios and analyze the channel fading statistics. For the influential factors, we further review related literature on channel correlation, cochannel interference (CCI) and impulsive noise. Major performance criteria and performance bounds are derived and compared. MRC confronts new developing challenges and the major development directions are reviewed. The paper finally discusses recent works and open problems for MRC applications and development. Emerging techniques such as artificial intelligence provide novel solutions for MRC performance improvements. The paper aims to present a summarized insight to assist readers in clarifying the analyzed methodology of MRC, so as to motivate new technology integration and extensive applications of advanced communication systems.

show abstract

A Survey on Maximum Ratio Combination: Applications, Evaluation and Future Directions

Feng,

Tian,

Wang

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

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Deep Learning Based Joint Hybrid Precoding and Combining Design for mmWave MIMO Systems

Cited by 1 publication

References 22 publications

A Survey on Maximum Ratio Combination: Applications, Evaluation and Future Directions

A Survey on Maximum Ratio Combination: Applications, Evaluation and Future Directions

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