Compressive Sensing Techniques for Next-Generation Wireless Communications

Zhen Gao, Linglong Dai*, Shuangfeng Han, I. Chih-Lin, Zhaocheng Wang, Lajos Hanzo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

203 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)144-153
Number of pages10
JournalIEEE Wireless Communications
Volume25
Issue number3
DOIs
Publication statusPublished - Jun 2018

Keywords

  • 5G mobile communication
  • Bandwidth
  • Complexity theory
  • Matching pursuit algorithms
  • Mathematical model
  • NOMA
  • Sparse matrices

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