Title :
Blind Identification of Nonbinary LDPC Codes Using Average LLR of Syndrome a Posteriori Probability
Author :
Tian Xia ; Hsiao-Chun Wu
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Louisiana State Univ., Baton Rouge, LA, USA
Abstract :
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.
Keywords :
Galois fields; Monte Carlo methods; adaptive codes; adaptive modulation; maximum likelihood estimation; parity check codes; quadrature amplitude modulation; AMC transceivers; APP; GF; Galois field; Monte Carlo simulation; adaptive modulation and coding techniques; blind nonbinary low-density parity-check encoder identification; candidate set; dynamic channel quality; log-likelihood ratios; maximum average LLR; nonbinary LDPC codes; q-QAM signals; q-ary quadrature amplitude modulation signals; syndrome a posteriori probability; Encoding; Frequency modulation; Parity check codes; Receivers; Transceivers; Transmitters; Blind encoder identification; log-likelihood ratio; nonbinary low-density parity-check codes;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2013.051313.130462