Near ML Performance for Linear Block Codes Using an Iterative Vector SISO Decoder
Konferenz: TURBO - CODING - 2006 - 4th International Symposium on Turbo Codes & Related Topics; 6th International ITG-Conference on Source and Channel Coding
03.04.2006 - 07.04.2006 in Munich, Germany
Tagungsband: TURBO - CODING - 2006
Seiten: 6Sprache: EnglischTyp: PDFPersönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt
Kerr, Ron; Lodge, John (Communications Research Centre Canada, Ottawa ON, Canada)
In this paper, we present an iterative soft-decision decoding algorithm applicable to binary linear block codes. The algorithm uses a modified Vector SISO algorithm that utilizes soft input information to form candidate codewords. A threshold test is used to determine whether the codeword is likely to be the ML codeword. If the codeword is not accepted, the decoder biases the input vector “away” from the candidate codeword and the decoding repeats this process up to a maximum number of decodings. Occasionally, this process does not find an acceptable codeword. When this happens the algorithm perturbs the input vector by modification of the sign of the input values and repeats the decoding process. The average complexity of the algorithm at reasonable Eb=N0 is low and the performance is near ML. A detailed description of the algorithm and simulations results are presented for low rate linear block codes. We present results for (80,40,16), (104,52,20) and (168,84,24) quadratic residue codes and (256,191,18) and (128,29,44) extended BCH codes.