NDLI: Jamming estimation on block-fading channels

Content Provider	IEEE Xplore Digital Library
Author	Jang-Wook Moon Shea, J.M. Wong, T.F.
Copyright Year	2004
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA (Jang-Wook Moon; Shea, J.M.; Wong, T.F.)
Abstract	We consider communication in the presence of hostile jamming and block-fading. The jamming signal is modeled by a Gaussian two-state hidden Markov model. Both the communication signal and the jamming signal experience fading that is constant over each packet transmission. Under this scenario, the performance is very sensitive to errors in detecting which symbols are jammed and in the estimates of the jamming and fading parameters. Thus, it is crucial for the receiver to be able to accurately determine both the set of jammed symbols and the parameters of the jamming and fading. In this paper, we present several techniques to perform this detection and estimation. These problems are made considerably more difficult because we assume that the none of the parameters of the jamming signal are known a priori to the receiver. Maximum a posteriori (MAP) estimation and generalized likelihood ratio tests (GLRT) are considered first. Then a lower complexity ad-hoc technique is developed that is based on estimating the density function of the received symbols. Simulation results are presented to compare the performance of the proposed detection and estimation techniques.
Starting Page	1310
Ending Page	1316
File Size	1313671
Page Count	7
File Format	PDF
ISBN	078038847X
DOI	10.1109/MILCOM.2004.1495133
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-10-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Jamming Fading Hidden Markov models Decoding Binary phase shift keying Moon Testing Density functional theory Signal to noise ratio Research initiatives
Content Type	Text
Resource Type	Article

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