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Sparse Signal Processing for Massive MIMO Communications

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...

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Bibliographic Details
Main Authors: Gao, Zhen, Mei, Yikun (Author), Qiao, Li (Author)
Format: eBook
Language:English
Published: Singapore Springer Nature Singapore 2024, 2024
Edition:1st ed. 2024
Subjects:
Communications Engineering, Networks
Telecommunication
Signal Processing
Signal, Speech And Image Processing
Microwaves, Rf Engineering And Optical Communications
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 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 MIMOTechnology

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