Simultaneous Multi-Beam Training for Millimeter-Wave Communication System

Millimeter-wave communication is regarded as a promising technology for the next generation communication system, where beamforming and beam training are essential for power concentration and coverage extension. In this paper, we propose an angular domain separation based multi-beam training (ADS-MB...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2022-10, Vol.71 (10), p.10631-10645
Main Authors: Zhuo, Yinxiao, Sha, Ziyuan, Wang, Zhaocheng, Chen, Sheng
Format: Article
Language:English
Subjects:
angular domain separation
Array signal processing
beam training
Beamforming
Communications systems
Data transmission
Delays
Domains
initial access
Machine learning
Millimeter wave communication
Millimeter waves
Millimeter-wave
Multipath channels
Radio frequency
Separation
Training
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Summary:Millimeter-wave communication is regarded as a promising technology for the next generation communication system, where beamforming and beam training are essential for power concentration and coverage extension. In this paper, we propose an angular domain separation based multi-beam training (ADS-MBT) scheme and an angular domain separation based hierarchical multi-beam training (ADS-HMBT) scheme, which enable simultaneous multi-beam training under the single data stream constraint. We provide theoretical analysis on the performance of the proposed schemes and optimize the non-orthogonal codebook used in the proposed schemes accordingly. With this appropriate design, our proposed ADS-MBT scheme can achieve almost the same beamforming gain as the exhaustive scheme but only imposing half or less time slot consumption. The proposed ADS-HMBT scheme further reduces the training overhead, and it outperforms the existing two-layer hierarchical search, in terms of training overhead and beamforming gain in the multiple feedback beam training case. Simulation results show the effectiveness and superior performance of our both proposed schemes over the existing state-of-the-arts.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2022.3185739