Optimized compressive sensing-based direction-of-arrival estimation in massive MIMO

Yujie Gu, Yimin D. Zhang, Nathan A. Goodman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

64 Scopus citations

Abstract

As a new emerging technology for wireless communications, massive multiple-input multiple-output (MIMO) faces a significant challenge to deploy a separate receiver chain of front-end circuits in a dense circuit board. In this paper, we apply the compressive sensing technique to reduce the required number of front-end circuits and the overall computational complexity. Unlike the commonly adopted random projections, we utilize the a priori probability distribution of the directions-of-arrival (DOAs) of the signals to optimize compressive sensing kernels for massive MIMO systems, such that the mutual information between the compressed measurement and the DOA is maximized. With the optimized sensing matrix, we present a compressive sensing spatial spectrum estimator under the minimum variance distortionless response criterion. Simulation results demonstrate performance advantages of the proposed optimal sensing kernel over random sensing kernels.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3181-3185
Number of pages5
ISBN (Electronic)9781509041176
DOIs
StatePublished - 16 Jun 2017
Externally publishedYes
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country/TerritoryUnited States
CityNew Orleans
Period5/03/179/03/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Funding

The work of Y. Gu and Y. D. Zhang is supported in part by the National Science Foundation (NSF) under grant AST-1547420. The work of Y. Gu and N. A. Goodman is supported in part by the Defense Advanced Research Projects Agency (DARPA) via grant #N66001-10-1-4079.

FundersFunder number
National Science Foundation1547420, AST-1547420
Defense Advanced Research Projects Agency66001-10-1-4079

    Keywords

    • Compressive sensing
    • DOA estimation
    • kernel optimization
    • massive MIMO
    • spatial spectrum

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