Low-Complexity Decoding Algorithms for Distributed Space-Time Coded Regenerative Relay Systems
Joint Authors
Source
International Journal of Distributed Sensor Networks
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-09-19
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Telecommunications Engineering
Information Technology and Computer Science
Abstract EN
We examine decoding structure for distributed space-time coded regenerative relay networks.
Given the possible demodulation error at the regenerative relays, we provide a general framework of error aware decoder, where the receiver exploits the demodulation error probability of relays to improve the system performance.
Considering the high computational complexity of optimal Maximum Likelihood (ML) decoder, we also propose two low-complexity decoders, Max-Log decoder and Max-Log-Sphere decoder.
Computational complexities of these three decoders are also analyzed.
Simulation results show that error aware decoders can improve system performance greatly without high system overload and Max-Log decoder and Max-Log-Sphere decoder can drastically reduce the decoding complexity with negligible performance degradation.
American Psychological Association (APA)
Zhang, Chao& Yin, Huarui. 2012. Low-Complexity Decoding Algorithms for Distributed Space-Time Coded Regenerative Relay Systems. International Journal of Distributed Sensor Networks،Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-510720
Modern Language Association (MLA)
Zhang, Chao& Yin, Huarui. Low-Complexity Decoding Algorithms for Distributed Space-Time Coded Regenerative Relay Systems. International Journal of Distributed Sensor Networks No. 2012 (2012), pp.1-10.
https://search.emarefa.net/detail/BIM-510720
American Medical Association (AMA)
Zhang, Chao& Yin, Huarui. Low-Complexity Decoding Algorithms for Distributed Space-Time Coded Regenerative Relay Systems. International Journal of Distributed Sensor Networks. 2012. Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-510720
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-510720