Progressive edge growth LDPC Encoder with spiral search algorithm

  • Authors

    • Anand Anbalgan
    • Senthil Kumar.P
    2017-12-31
    https://doi.org/10.14419/ijet.v7i1.3.10673
  • PEG LDPC, Trapping set, Neighbourhoods search, Spiral search

  • Abstract

    Trapping set causes the drop of performance in error floor region. Identification of TS is done by graphical method and enumerators. The lowest odd degree (minimal) TS is increasing the formation of more unsaturated nodes in iterative decoding. Progressive edge growth (PEG) Low-density parity check code (LDPC) [2] avoidance of trapping sets are mainly based on the distance and degree calculation of successive CN. This simple tool is used to eliminate TS when the encoder ensemble designs itself. Non-zero neighborhood search also made an influence on error floor. The spiral search method is used for Non-zero codeword search (NZCW) search for the first time in this research, at the decoder part. So, Non-zero codeword spiral search (NZCSS) converge fast with less number iteration, and this reduces the iteration of the decoder.

  • References

    1. [1] Gallager, RG 1962, ‘Low density parity check codes’, IRE Trans.inf.Theory IT-8, pp. 21-28.

      [2] Sharon, E &Litsyn, S 2008, ‘Constructing LDPC codes by error minimization progressive edge growth’, IEEE Trans. Commun.,vol. 56, no. 3, pp. 359-368.

      [3] Landner, S & Milenkovic, O 2005,‘Algorithmic and combinatorial analysis of trapping sets in structured LDPC codes’, in: IEEE International Conference on Wireless Networks, Communications and Mobile, Computing, vol. 1, pp. 630-635.

      [4] Vasic, B, Chilappagari, SK, Nguyen, DV & Planjery, SK 2009, ‘Trapping set ontology’, in: Proceedings of the 47th IEEE Annual Allerton Conference on Communication, Control, and Computing, pp. 1–7.

      [5] Savin, V 2007, ‘Iterative LDPC decoding using neighborhood reliabilities’, in: IEEE International Symposium on Information Theory (ISIT), pp. 221-225.

      [6] Chilappagari, SK, Nguyen, DV,Vasi´c, B & Marcellin, MW 2010,‘On trapping sets and guaranteed error correction capability of LDPC codes and GLDPC codes, IEEE Trans. Inf., Theory, vol. 56, no. 4, pp. 1600-1611.

      [7] McGregor, A & Milenkovic, O 2010,‘On the hardness of approximating stopping and trapping sets’, IEEE Trans. Inf. Theory vol. 56, no. 4, pp. 1640-165

      [8] Richter, G & Hof, A 2006, ‘On a construction method of irregular LDPC codes without small stopping sets’, in: Proceedings of the 2006 IEEE International Conference on Communications, Istanbul, Turkey,pp. 1119-1124.

      [9] Michael Chertkov& Mikhail Stepanov, G 2007, ‘An efficient pseudocodeword search algorithm for linear programming decoding of LDPC Code’, IEEE Transactions on Information Theory.

      [10] Zheng, X, Lau, F &Tse, C 2010,‘Constructing short-length irregular LDPC codes with low error floor’, IEEE Trans. Commun. vol. 58, no. 10, pp. 2823-2834.

      [11] Pankaj Agarwal, K 2012, ‘Duke University, ‘Nearest Neighbor Searching Under Uncertainty II’. Duke University,

      [12] Anand, A&Senthil Kumar, P 2015, ‘An efficient non-binary LDPC decoder with layer dynamic scheduling’,J. Comput.Theor. Nanosci,vol. 12, no. 12, pp. 5066-5070

      [13] Tian, T, Jones, C, Villasenor, J & Wesel, R 2004, ‘Selective avoidance of cycles in irregular LDPC code constructions’, IEEE Trans. Commun. vol. 52, no. 8, pp. 1242-1247.

      [14] Mitchell, DGM &Pusane, AE 2013, ‘Costello, D.J.Minimum distance and trapping set analysis of protograph-based LDPC convolutional codes’, IEEE Trans. Inf. Theory vol. 59, no. 1, pp. 254-281.

  • Downloads

  • How to Cite

    Anbalgan, A., & Kumar.P, S. (2017). Progressive edge growth LDPC Encoder with spiral search algorithm. International Journal of Engineering & Technology, 7(1.3), 198-202. https://doi.org/10.14419/ijet.v7i1.3.10673

    Received date: 2018-03-26

    Accepted date: 2018-03-26

    Published date: 2017-12-31