Title :
MAP decoding using the EM algorithm
Author_Institution :
Dept. of Commun. Res., AT&T Bell Labs., Florham Park, NJ, USA
Abstract :
The expectation-maximization (EM) algorithm is popular in estimating parameters of various statistical models. We consider applications of the EM algorithm to the maximum a posteriori (MAP) sequence decoding in channels described by hidden Markov models (HMMs). It is well known that HMMs can accurately approximate large variety of communication channels with memory and in particular, wireless fading channels with noise. The direct maximization of the a posteriori probability is too complex. The EM algorithm allows us to obtain the MAP sequence estimation iteratively
Keywords :
Viterbi decoding; block codes; convolutional codes; fading channels; hidden Markov models; maximum likelihood decoding; noise; optimisation; sequential estimation; trellis coded modulation; EM algorithm; HMM; MAP decoding; TCM system; Viterbi algorithm; a posteriori probability; block codes; communication channels; convolutional codes; expectation-maximization algorithm; hidden Markov models; iterative MAP sequence estimation; maximum a posteriori sequence decoding; noise; parameter estimation; statistical models; wireless fading channels; Communication channels; Digital communication; Fading; Hidden Markov models; Iterative algorithms; Iterative decoding; Laboratories; Parameter estimation; Viterbi algorithm; Wireless communication;
Conference_Titel :
Vehicular Technology Conference, 1999 IEEE 49th
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-5565-2
DOI :
10.1109/VETEC.1999.778361
