Finite Alphabet Iterative Decoding (FAID) of the (155,64,20) Tanner Code
Résumé
It is now well established that iterative decoding approaches the performance of Maximum Likelihood Decoding of sparse graph codes, asymptotically in the block length. For a finite length sparse code, iterative decoding fails on specific subgraphs generically termed as trapping sets. Trapping sets give rise to error floor, an abrupt degradation of the code error performance in the high signal to noise ratio regime. In this paper, we will study a recently introduced class of quantized iterative decoders, for which the messages are defined on a finite alphabet and which sucessfully decode errors on subgraphs that are uncorrectable by conventional decoders such as min-sum or the belief propagation. We will especially study the performance of the proposed finite alphabet iterative decoders on the famous 155,64,20) Tanner code.
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