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Compressive sensing techniques for next-generation wireless communications

Compressive sensing techniques for next-generation wireless communications
Compressive sensing techniques for next-generation wireless communications

A range of efficient wireless processes and enabling techniques are put under a magnifier glass in the quest for exploring different manifestations of correlated processes, where sub-Nyquist sampling may be invoked as an explicit benefit of having a sparse transform-domain representation. For example, wide-band next-generation systems require a high Nyquist-sampling rate, but the channel impulse response (CIR) will be very sparse at the high Nyquist frequency, given the low number of reflected propagation paths. This motivates the employment of compressive sensing based processing techniques for frugally exploiting both the limited radio resources and the network infrastructure as efficiently as possible. A diverse range of sophisticated compressed sampling techniques is surveyed, and we conclude with a variety of promising research ideas related to large-scale antenna arrays, non-orthogonal multiple access (NOMA), and ultra-dense network (UDN) solutions, just to name a few.

5G mobile communication, Bandwidth, Complexity theory, Matching pursuit algorithms, Mathematical model, NOMA, Sparse matrices
1536-1284
144-153
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Dai, Linglong
a3b9a8e1-777f-4196-a388-969444c7239d
Han, Shuangfeng
34086c45-dcfb-4495-baca-4885d7fe7633
Chih-Lin, I.
2555a6d4-fca5-4e0a-874c-74f02f08176d
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Dai, Linglong
a3b9a8e1-777f-4196-a388-969444c7239d
Han, Shuangfeng
34086c45-dcfb-4495-baca-4885d7fe7633
Chih-Lin, I.
2555a6d4-fca5-4e0a-874c-74f02f08176d
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Gao, Zhen, Dai, Linglong, Han, Shuangfeng, Chih-Lin, I., Wang, Zhaocheng and Hanzo, Lajos (2018) Compressive sensing techniques for next-generation wireless communications. IEEE Wireless Communications, 25 (3), 144-153. (doi:10.1109/MWC.2017.1700147).

Record type: Article

Abstract

A range of efficient wireless processes and enabling techniques are put under a magnifier glass in the quest for exploring different manifestations of correlated processes, where sub-Nyquist sampling may be invoked as an explicit benefit of having a sparse transform-domain representation. For example, wide-band next-generation systems require a high Nyquist-sampling rate, but the channel impulse response (CIR) will be very sparse at the high Nyquist frequency, given the low number of reflected propagation paths. This motivates the employment of compressive sensing based processing techniques for frugally exploiting both the limited radio resources and the network infrastructure as efficiently as possible. A diverse range of sophisticated compressed sampling techniques is surveyed, and we conclude with a variety of promising research ideas related to large-scale antenna arrays, non-orthogonal multiple access (NOMA), and ultra-dense network (UDN) solutions, just to name a few.

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More information

e-pub ahead of print date: 8 February 2018
Published date: 1 June 2018
Keywords: 5G mobile communication, Bandwidth, Complexity theory, Matching pursuit algorithms, Mathematical model, NOMA, Sparse matrices

Identifiers

Local EPrints ID: 422606
URI: http://eprints.soton.ac.uk/id/eprint/422606
ISSN: 1536-1284
PURE UUID: 246e60ed-a20f-4cd3-bf54-1e3c4ce54e0f
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 26 Jul 2018 16:30
Last modified: 07 Oct 2020 01:33

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