Publication | Closed Access
Blind Identification of Nonbinary LDPC Codes Using Average LLR of Syndrome a Posteriori Probability
30
Citations
16
References
2013
Year
Wireless CommunicationsEngineeringGeneticsPrevalent Adaptive ModulationDiagnosisIterative DecodingDisease Gene IdentificationBlind IdentificationJoint Source-channel CodingAdaptive ModulationNonbinary Ldpc EncoderBiostatisticsDynamic Channel QualityPosteriori ProbabilityCoding TheoryMolecular DiagnosticsComputer EngineeringBioinformaticsError Correction CodeSignal ProcessingModulation CodingMedicineChannel Estimation
Prevalent adaptive modulation and coding (AMC) techniques can facilitate the flexible strategies subject to the dynamic channel quality. It would be quite intriguing for one to build a blind encoder identification technique without spectrum-efficiency sacrifice for AMC transceivers. In this paper, we make the first-ever attempt to tackle the blind nonbinary low-density parity-check (LDPC) encoder identification given a predefined encoder candidate set over the Galois field GF(q) for q-ary quadrature amplitude modulation (q-QAM) signals. Our proposed method establishes the log-likelihood ratios (LLRs) of syndrome a posteriori probabilities (APPs), which specify the potential correctness of the underlying parity-check relations, and identifies the nonbinary LDPC encoder leading to the maximum average LLR over the candidate set. Monte Carlo simulation results verify the effectiveness of our proposed new scheme.
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