03326nam a22004695i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001300153072001600166072001600182072002300198072001500221072001500236100007200251245012000323250001800443264007200461300006500533336002600598337002600624338003600650347002400686505096300710520063701673650002302310650002302333650004102356650005902397650004202456700007302498700007102571710003402642773002602676776003602702776003602738776003602774856004602810978-981-99-5394-3DE-He21320251030110823.0cr nn 008mamaa231017s2024    si |    s    |||| 0|eng d  a97898199539437 a10.1007/978-981-99-5394-32doi 4aTK5102.9 7aTJF2bicssc 7aUYS2bicssc 7aTEC0670002bisacsh 7aTJF2thema 7aUYS2thema1 aGao, Zhen.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aSparse Signal Processing for Massive MIMO Communicationsh[electronic resource] /cby Zhen Gao, Yikun Mei, Li Qiao.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXVI, 217 p. 87 illus., 69 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aIntroduction -- 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 MIMOTechnology.  aThe 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. 0aSignal processing. 0aTelecommunication.14aSignal, Speech and Image Processing.24aMicrowaves, RF Engineering and Optical Communications.24aCommunications Engineering, Networks.1 aMei, Yikun.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut1 aQiao, Li.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981995393608iPrinted edition:z978981995395008iPrinted edition:z978981995396740uhttps://doi.org/10.1007/978-981-99-5394-3