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Book Cover
E-book
Author Zhang, Ying Jun, author.

Title Scalable signal processing in cloud radio access networks / Ying-Jun Angela Zhang, Congmin Fan and Xiaojun Yuan
Published Cham, Switzerland : Springer, [2019]

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Description 1 online resource
Series Springer briefs in electrical and computer engineering, 2191-8120
SpringerBriefs in electrical and computer engineering.
Summary 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
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (EBSCO, viewed April 25, 2019)
Subject Signal processing.
Signal detection.
Cloud computing.
TECHNOLOGY & ENGINEERING -- Mechanical.
Cloud computing
Signal detection
Signal processing
Form Electronic book
Author Fan, Congmin, author
Yuan, Xiaojun, author
ISBN 9783030158842
3030158845
3030158837
9783030158835
9783030158859
3030158853