DocumentCode
3413775
Title
Anti-jam distributed MIMO decoding using wireless sensor networks
Author
Farahmand, Shahrokh ; Cano, Alfonso ; Giannakis, Georgios B.
Author_Institution
Dept. of ECE, Univ. of Minnesota, Minneapolis, MN
fYear
2008
fDate
March 31 2008-April 4 2008
Firstpage
2257
Lastpage
2260
Abstract
Consider a set of sensors that wish to consent on the message broadcasted by a multi-antenna transmitter in the presence of white-noise jamming. The jammer´s interference introduces correlation across receivers and destroys the decomposable form of the maximum-likelihood decoder, thus preventing direct application of known distributed detection algorithms. This paper develops distributed detectors that circumvent this problem. Treating the jammer signal as deterministic, we develop two distributed estimation-decoding algorithms. The first algorithm relies on the generalized likelihood ratio test, whereas the second algorithm relies on semi-definite relaxation techniques and is suitable for large alphabet sizes. Both algorithms feature: (i) distributed implementation requiring only single-hop communications; (ii) no constraints on the network topology so long as it is connected; and (iii) performance close to the optimum centralized detector in the presence of severe jamming.
Keywords
MIMO communication; antenna arrays; interference suppression; jamming; maximum likelihood decoding; telecommunication network topology; white noise; wireless sensor networks; anti-jam distributed MIMO decoding; distributed estimation-decoding algorithms; maximum-likelihood decoder; multi-antenna transmitter; network topology; white-noise jamming; wireless sensor networks; Broadcasting; Detectors; Interference; Jamming; MIMO; Maximum likelihood decoding; Maximum likelihood detection; Maximum likelihood estimation; Transmitters; Wireless sensor networks; consensus; distributed algorithm; generalized likelihood ratio test; jamming; semi-definite relaxation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location
Las Vegas, NV
ISSN
1520-6149
Print_ISBN
978-1-4244-1483-3
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2008.4518095
Filename
4518095
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