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Hardware-efficient hybrid precoding for millimeter wave systems with multi-feed reflectarrays

Hardware-efficient hybrid precoding for millimeter wave systems with multi-feed reflectarrays
Hardware-efficient hybrid precoding for millimeter wave systems with multi-feed reflectarrays
Current hybrid precoding schemes for large-scale antenna array aided millimeter wave (mmWave) wireless systems adopt either full-connected or sub-connected architectures based on phased array antennas (PAAs). The former achieves excellent precoding performance but imposes considerably high hardware complexity, while the latter is relatively simple but suffers from high performance loss. In this paper, we exploit the new technology of reflectarray antennas, which among other advantages offers significant hardware efficiency gain, and propose a novel hybrid precoding architecture based on multi-feed reflectarray antennas (MRAs) for mmWave wireless systems, which is capable of achieving considerable hardware efficiency gain even over the low-hardware-complexity sub-connected architecture with PAAs. The mathematical model is provided for this novel hybrid precoding architecture, and an efficient alternating descent algorithm is developed to jointly design the analog and digital precoders for the proposed hybrid precoding scheme. Numerical results obtained demonstrate that our proposed precoding scheme with MRAs achieves much better precoding performance than its sub-connected counterpart with PAAs.
Hardware, hardware complexity, hybrid precoding, Millimeter wave, mutual information, phased array antennas, Phased arrays, Precoding, precoding performance, Radio frequency, re?ectarray antennas, Transmitting antennas
2169-3536
6795-6806
Zhou, Zhengyi
f5dab14d-9ed8-4842-bb66-af63472391e5
Ne, Ning
d6b856e3-1a5f-4357-8a48-60a3d1a69334
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhou, Zhengyi
f5dab14d-9ed8-4842-bb66-af63472391e5
Ne, Ning
d6b856e3-1a5f-4357-8a48-60a3d1a69334
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Zhou, Zhengyi, Ne, Ning, Wang, Zhaocheng and Chen, Sheng (2018) Hardware-efficient hybrid precoding for millimeter wave systems with multi-feed reflectarrays. IEEE Access, 6, 6795-6806. (doi:10.1109/ACCESS.2018.2793223).

Record type: Article

Abstract

Current hybrid precoding schemes for large-scale antenna array aided millimeter wave (mmWave) wireless systems adopt either full-connected or sub-connected architectures based on phased array antennas (PAAs). The former achieves excellent precoding performance but imposes considerably high hardware complexity, while the latter is relatively simple but suffers from high performance loss. In this paper, we exploit the new technology of reflectarray antennas, which among other advantages offers significant hardware efficiency gain, and propose a novel hybrid precoding architecture based on multi-feed reflectarray antennas (MRAs) for mmWave wireless systems, which is capable of achieving considerable hardware efficiency gain even over the low-hardware-complexity sub-connected architecture with PAAs. The mathematical model is provided for this novel hybrid precoding architecture, and an efficient alternating descent algorithm is developed to jointly design the analog and digital precoders for the proposed hybrid precoding scheme. Numerical results obtained demonstrate that our proposed precoding scheme with MRAs achieves much better precoding performance than its sub-connected counterpart with PAAs.

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More information

Accepted/In Press date: 12 January 2018
e-pub ahead of print date: 15 January 2018
Published date: 9 March 2018
Keywords: Hardware, hardware complexity, hybrid precoding, Millimeter wave, mutual information, phased array antennas, Phased arrays, Precoding, precoding performance, Radio frequency, re?ectarray antennas, Transmitting antennas

Identifiers

Local EPrints ID: 417828
URI: http://eprints.soton.ac.uk/id/eprint/417828
ISSN: 2169-3536
PURE UUID: e30444b7-f513-460d-b535-38eed37517ad

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Date deposited: 15 Feb 2018 17:30
Last modified: 15 Mar 2024 18:27

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Contributors

Author: Zhengyi Zhou
Author: Ning Ne
Author: Zhaocheng Wang
Author: Sheng Chen

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