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Scalable Signal Processing in Cloud Radio Access Networks

  • Ying-Jun Angela Zhang
  • Congmin Fan
  • Xiaojun Yuan

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Ying-Jun Angela Zhang, Congmin Fan, Xiaojun Yuan
    Pages 1-7
  3. Ying-Jun Angela Zhang, Congmin Fan, Xiaojun Yuan
    Pages 9-21
  4. Ying-Jun Angela Zhang, Congmin Fan, Xiaojun Yuan
    Pages 23-47
  5. Ying-Jun Angela Zhang, Congmin Fan, Xiaojun Yuan
    Pages 49-65
  6. Ying-Jun Angela Zhang, Congmin Fan, Xiaojun Yuan
    Pages 67-91
  7. Ying-Jun Angela Zhang, Congmin Fan, Xiaojun Yuan
    Pages 93-96
  8. Back Matter
    Pages 97-100

About this book

Introduction

This Springerbreif  introduces a threshold-based channel sparsification approach, and then, the sparsity is exploited for scalable channel training. Last but not least, this brief introduces two scalable cooperative signal detection algorithms in C-RANs.  The authors wish to spur new research activities in the following important question: how to leverage the revolutionary architecture of C-RAN to attain unprecedented system capacity at an affordable cost and complexity.

Cloud radio access network (C-RAN) is a novel mobile network architecture that has a lot of significance in future wireless networks like 5G. the high density of remote radio heads in C-RANs leads to severe scalability issues in terms of computational and implementation complexities. This Springerbrief undertakes a comprehensive study on scalable signal processing for C-RANs, where ‘scalable’ means that the computational and implementation complexities do not grow rapidly with the network size.

This Springerbrief will be target researchers and professionals working in the Cloud Radio Access Network (C-Ran) field, as well as advanced-level students studying electrical engineering.


Keywords

cloud radio access network signal processing channel estimation message passing belief propagation dynamic clustering parallel computing Wireless Communications 5G Systems Cellular Systems MMSE detection Coordinated Multi-point (COMP) Scalable Signal Processing Clustering

Authors and affiliations

  • Ying-Jun Angela Zhang
    • 1
  • Congmin Fan
    • 2
  • Xiaojun Yuan
    • 3
  1. 1.Department of Information EngineeringChinese University of Hong KongShatinHong Kong
  2. 2.Department of Information EngineeringChinese University of Hong KongShatinHong Kong
  3. 3.Center for Intelligent Networking and CommunicationsThe University of Electronic Science and Technology of ChinaChengduChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-15884-2
  • Copyright Information The Author(s), under exclusive license to Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-030-15883-5
  • Online ISBN 978-3-030-15884-2
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • Buy this book on publisher's site