Good error-correcting codes based on very sparse matrices
IEEE Transactions on Information Theory
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
The capacity of low-density parity-check codes under message-passing decoding
IEEE Transactions on Information Theory
Design of capacity-approaching irregular low-density parity-check codes
IEEE Transactions on Information Theory
Analysis of sum-product decoding of low-density parity-check codes using a Gaussian approximation
IEEE Transactions on Information Theory
Turbo decoding as an instance of Pearl's “belief propagation” algorithm
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
Blind estimation of the phase and carrier frequency offsets for LDPC-coded systems
EURASIP Journal on Advances in Signal Processing
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The original sum product algorithms (SPA) of LDPC decoding in AWGN channel require the knowledge of noise variance. Mini-sum algorithm need not the variance estimation but has performance degradation. If the assumed noise variance of SPA algorithm deviates largely from the true value, the performance also degrade seriously. In this paper, an iterative noise variance estimation algorithm using the decoded data is presented. The true noise variance is then substituted by the estimated one. The computational load is analyzed. Performance difference between SPA, Mini-sum algorithm and our algorithm are compared by simulations.