Scalable Signal Processing in Cloud Radio Access Networks
Language: English
Published by Springer, Palgrave Macmillan Apr 2019, 2019
Series: Book 190 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 50.59
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Add to basketItem description from seller
This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 112 pp. Englisch.…
Seller Inventory # 9783030158835
- Title
- Scalable Signal Processing in Cloud Radio Access Networks
- Author
- Ying-Jun Angela Zhang
- Publisher
- Springer, Palgrave Macmillan Apr 2019
- Publication year
- 2019
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3030158837
- ISBN 13
- 9783030158835
- Item weight
- 184 grams
- Dimensions
- 235x155x7 mm
- Series
- Book 190 of 209: SpringerBriefs in Electrical and Computer Engineering
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.
"Synopsis" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
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