DocumentCode
2881379
Title
Recovery of unknown constraint length and generator polynomials for linear convolutional encoders in noise
Author
Boyd, Phillip L. ; Robertson, R. Clark
Author_Institution
Dept. of Electr. & Comput. Eng., Naval Postgraduate Sch., Monterey, CA, USA
Volume
2
fYear
2000
fDate
2000
Firstpage
952
Abstract
In cases where the parameters of a forward error correcting encoder (the constraint length K and the generator polynomials) are unknown, they must be obtained before the message data can be recovered. The synthetic impulse response sequence (SIRS) algorithm, through observation and manipulation of the encoded output, composes a synthetic impulse response and from this sequence performs encoder parameter recovery. With these parameters in hand, selection of a suitable (Viterbi) decoder and recovery of message data is straightforward. We apply the SIRS algorithm in a noisy environment. The elements of the algorithm are extended to accommodate erroneous encoded data, and the impact of noise upon the probability of a correct solution are considered
Keywords
Viterbi decoding; convolutional codes; error statistics; forward error correction; linear codes; noise; polynomials; transient response; BER; SIRS algorithm; Viterbi decoder; correct solution probability; encoded output; encoder parameter recovery; erroneous encoded data; forward error correcting encoder; linear convolutional encoders; message data recovery; noise; noisy environment; synthetic impulse response sequence algorithm; unknown constraint generator polynomials recovery; unknown constraint length recovery; Computer errors; Convolutional codes; Decoding; Error correction; Noise generators; Polynomials; Protection; US Government; Viterbi algorithm; Working environment noise;
fLanguage
English
Publisher
ieee
Conference_Titel
MILCOM 2000. 21st Century Military Communications Conference Proceedings
Conference_Location
Los Angeles, CA
Print_ISBN
0-7803-6521-6
Type
conf
DOI
10.1109/MILCOM.2000.904071
Filename
904071
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