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Compressive Sensing with Applications to Millimeter-wave Architectures
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems Engineering.ORCID iD: 0000-0002-9442-671X
Univ Kansas, Dept EECS, Lawrence, KS 66045 USA..
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems Engineering.ORCID iD: 0000-0001-9810-3478
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-7926-5081
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2019, p. 7834-7838Conference paper, Published paper (Refereed)
Abstract [en]

To make the system available at low-cost, millimeter-ave (mmWave) multiple-input multiple-output (MIMO) architectures employ analog arrays, which are driven by a limited number of radio frequency (RF) chains. One primary challenge of using large hybrid analog-digital arrays is that the digital baseband cannot directly access the signal to/from each antenna. To address this limitation, recent research has focused on retransmissions, iterative precoding, and subspace decomposition methods. Unlike these approaches that exploited the channel's low-rank, in this work we exploit the sparsity of the received signal at both the transmit/receive antennas. While the signal itself is de facto dense, it is well-known that most signals are sparse under an appropriate choice of basis. By delving into the structured compressive sensing (CS) framework and adapting them to variants of the mmWave hybrid architectures, we provide methodologies to recover the analog signal at each antenna from the (low-dimensional) digital signal. Moreover, we characterizes the minimal numbers of measurement and RF chains to provide this recovery, with high probability. We discuss their applications to common variants of the hybrid architecture. By leveraging the inherent sparsity of the received signal, our analysis reveals that a hybrid MIMO system can be " turned into" a fully digital one: the number of needed RF chains increases logarithmically with the number of antennas.

Place, publisher, year, edition, pages
IEEE , 2019. p. 7834-7838
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-261067DOI: 10.1109/ICASSP.2019.8683604ISI: 000482554008014Scopus ID: 2-s2.0-85069003459ISBN: 978-1-4799-8131-1 (print)OAI: oai:DiVA.org:kth-261067DiVA, id: diva2:1356416
Conference
44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 12-17, 2019, Brighton, ENGLAND
Note

QC 20191001

Available from: 2019-10-01 Created: 2019-10-01 Last updated: 2019-10-01Bibliographically approved

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Ghauch, HadiFischione, CarloSkoglund, Mikael

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