Detection schemes for weak signals in first-order moving average of impulsive noise

Cited 7 time in webofscience Cited 0 time in scopus
  • Hit : 669
  • Download : 443
In this paper, the detection of weak signals in additive noise described by the first-order moving average (FOMA) of an impulsive process is considered. Specifically, decision regions of the maximum likelihood (ML) and suboptimum NIL (S-ML) detectors are derived in the FOMA noise model, and specific examples of the ML and S-NIL decision regions are obtained. The ML and S-ML detectors are employed in the antipodal signaling system and compared in terms of bit error rate in an impulsive noise environment. Numerical results show that the S-ML detector, despite its reduced complexity and simpler structure, exhibits practically the same performance as the optimum ML detector. It is also observed that the performance gap between detectors for FOMA and independent and identically distributed noise becomes larger as the degree of noise impulsiveness increases.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2007-01
Language
English
Article Type
Article
Keywords

OPTIMUM BAYES DETECTION; NON-GAUSSIAN NOISE; DEPENDENT NOISE; MODELS

Citation

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.56, pp.126 - 133

ISSN
0018-9545
DOI
10.1109/TVT.2006.883727
URI
http://hdl.handle.net/10203/955
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 7 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0