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
Link To Document :
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