• DocumentCode
    640285
  • Title

    Gaussian sampling based lattice decoding

  • Author

    Datta, Tanmoy ; Chockalingam, A. ; Viterbo, Emanuele

  • Author_Institution
    Dept. of ECE, Indian Inst. of Sci., Bangalore, India
  • fYear
    2013
  • fDate
    7-12 July 2013
  • Firstpage
    2244
  • Lastpage
    2248
  • Abstract
    The problem of searching the closest lattice point in large dimensional lattices finds many applications in single and/or multiple antenna communications. In this paper, we propose a Gaussian sampling based lattice decoding algorithm (GSLD). The algorithm iteratively updates each coordinate by sampling from a continuous Gaussian distribution and then quantizes the sampled value to the nearest alphabet point. The algorithm complexity per iteration is independent of the size of the alphabet, and hence is of high interest in higher order modulation schemes. We show that the algorithm is able to achieve near-optimal performance in polynomial complexity in different wireless communication system models.
  • Keywords
    Gaussian distribution; communication complexity; decoding; radiocommunication; sampling methods; GSLD; Gaussian sampling based lattice decoding algorithm; algorithm complexity; alphabet point; closest lattice point; continuous Gaussian distribution; dimensional lattices; higher order modulation schemes; multiple antenna communications; near-optimal performance; polynomial complexity; single antenna communications; wireless communication system models; Bit error rate; Complexity theory; Decoding; Lattices; MIMO; Signal to noise ratio; Vectors; Gaussian sampling; Gibbs sampling; Lattice decoder; large dimensional codes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on
  • Conference_Location
    Istanbul
  • ISSN
    2157-8095
  • Type

    conf

  • DOI
    10.1109/ISIT.2013.6620625
  • Filename
    6620625