Blind Recognition of LDPC Codes Over Candidate Set

Adaptive modulation and coding (AMC) techniques have attracted more attention recently because of flexible strategies and dynamic channel quality. Blind recognition of encoder is an important technology for AMC systems because it can improve communication efficiency very well. In this letter, we pre...

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Veröffentlicht in:IEEE communications letters Jg. 24; H. 1; S. 11 - 14
Hauptverfasser: Wu, Zhaojun, Zhang, Limin, Zhong, Zhaogen, Liu, Renxin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.01.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Adaptive modulation and coding (AMC)
Adaptive systems
Algorithms
blind recognition
Coders
Codes
Computer simulation
Conditional probability
cosine conformity (CC)
Encoding
Error correcting codes
Extraterrestrial measurements
Heuristic algorithms
low-density parity-check codes (LDPC)
Modulation
Parity
Parity check codes
Recognition
Transmitters
ISSN:1089-7798, 1558-2558
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Zusammenfassung:Adaptive modulation and coding (AMC) techniques have attracted more attention recently because of flexible strategies and dynamic channel quality. Blind recognition of encoder is an important technology for AMC systems because it can improve communication efficiency very well. In this letter, we present a new algorithm to tackle blind low-density parity-check (LDPC) encoder identification over a given candidate set. Our proposed scheme establishes a cosine conformity (CC) of syndrome, which is a posterior probability that can measure the probability that all parity check relations of the codes are satisfied, and classifies the LDPC encoder leading to maximum average CC over the candidate set. Simulations show that the new method is effective for LDPC encoder identification; the theoretical correct ratio of recognition is consistent with the simulation results, and its performance is improved by nearly 1.5 dB when compared with the existing algorithm.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2019.2953229