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Sparse signal processing for massive MIMO communications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Sparse signal processing for massive MIMO communications/ by Zhen Gao, Yikun Mei, Li Qiao.
Author:	Gao, Zhen.
other author:	Mei, Yikun.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xiv, 217 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Massive MIMO Performance Analysis and Channel Estimation Scheme in Sparse Channels -- Channel Estimation Based on Structured Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Feedback Based on Distributed Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Estimation and Beamforming Based on Compressed Sensing Theory in mmWave Massive MIMO Systems -- Sparse Channel Estimation Based on Spectral Estimation Theory for mmWave Massive MIMO Systems -- Quasi-Optimal Signals Detection for Massive Spatial Modulation MIMO Systems Based on Structured Compressed Sensing -- Multiuser Signal Detection Based on Compressed Sensing for Massive Media Modulation MIMO Systems -- Compressed Sensing Mass Access Techniques in Medium Modulation Assisted IoT Machine Type Communication -- Time-varying Channel Estimation Based on Compressed Sensing Theory for TDS-OFDM Systems -- Summary and Prospects for Massive MIMO Technology.
Contained By:	Springer Nature eBook
Subject:	MIMO systems. -
Online resource:	https://doi.org/10.1007/978-981-99-5394-3
ISBN:	9789819953943

Sparse signal processing for massive MIMO communications
Gao, Zhen.

Sparse signal processing for massive MIMO communications[electronic resource] /by Zhen Gao, Yikun Mei, Li Qiao. - Singapore :Springer Nature Singapore :2024. - xiv, 217 p. :ill., digital ;24 cm.

Introduction -- Massive MIMO Performance Analysis and Channel Estimation Scheme in Sparse Channels -- Channel Estimation Based on Structured Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Feedback Based on Distributed Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Estimation and Beamforming Based on Compressed Sensing Theory in mmWave Massive MIMO Systems -- Sparse Channel Estimation Based on Spectral Estimation Theory for mmWave Massive MIMO Systems -- Quasi-Optimal Signals Detection for Massive Spatial Modulation MIMO Systems Based on Structured Compressed Sensing -- Multiuser Signal Detection Based on Compressed Sensing for Massive Media Modulation MIMO Systems -- Compressed Sensing Mass Access Techniques in Medium Modulation Assisted IoT Machine Type Communication -- Time-varying Channel Estimation Based on Compressed Sensing Theory for TDS-OFDM Systems -- Summary and Prospects for Massive MIMO Technology.

The book focuses on utilizing sparse signal processing techniques in designing massive MIMO communication systems. As the number of antennas has been increasing rapidly for years, extremely high-dimensional channel matrix and massive user access urge for algorithms with much higher efficiency. This book provides in-depth discussions on compressive sensing techniques and simulates the performance on wireless systems. The easy-to-understand instructions with detailed simulations and open-sourced codes provide convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.

ISBN: 9789819953943

Standard No.: 10.1007/978-981-99-5394-3doiSubjects--Topical Terms:

811587
MIMO systems.

LC Class. No.: TK5103.4836 / .G36 2024

Dewey Class. No.: 621.3822

Sparse signal processing for massive MIMO communications
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245 1 0 $a Sparse signal processing for massive MIMO communications $h [electronic resource] / $c by Zhen Gao, Yikun Mei, Li Qiao.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2024.
300 $a xiv, 217 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Massive MIMO Performance Analysis and Channel Estimation Scheme in Sparse Channels -- Channel Estimation Based on Structured Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Feedback Based on Distributed Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Estimation and Beamforming Based on Compressed Sensing Theory in mmWave Massive MIMO Systems -- Sparse Channel Estimation Based on Spectral Estimation Theory for mmWave Massive MIMO Systems -- Quasi-Optimal Signals Detection for Massive Spatial Modulation MIMO Systems Based on Structured Compressed Sensing -- Multiuser Signal Detection Based on Compressed Sensing for Massive Media Modulation MIMO Systems -- Compressed Sensing Mass Access Techniques in Medium Modulation Assisted IoT Machine Type Communication -- Time-varying Channel Estimation Based on Compressed Sensing Theory for TDS-OFDM Systems -- Summary and Prospects for Massive MIMO Technology.
520 $a The book focuses on utilizing sparse signal processing techniques in designing massive MIMO communication systems. As the number of antennas has been increasing rapidly for years, extremely high-dimensional channel matrix and massive user access urge for algorithms with much higher efficiency. This book provides in-depth discussions on compressive sensing techniques and simulates the performance on wireless systems. The easy-to-understand instructions with detailed simulations and open-sourced codes provide convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.
650 0 $a MIMO systems. $3 811587
650 0 $a Signal processing. $3 533904
650 1 4 $a Signal, Speech and Image Processing. $3 3592727
650 2 4 $a Microwaves, RF Engineering and Optical Communications. $3 3538694
650 2 4 $a Communications Engineering, Networks. $3 891094
700 1 $a Mei, Yikun. $3 3711408
700 1 $a Qiao, Li. $3 1279450
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-99-5394-3
950 $a Engineering (SpringerNature-11647)