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The expectation-maximization (EM) algorithm is popular in estimating the parameters of various statistical models. We consider applications of the EM algorithm to the maximum a posteriori (MAP) sequence decoding assuming that sources and channels are described by hidden Markov models (HMMs). The HMMs can accurately approximate a large variety of communication channels with memory and, in particular, wireless fading channels with noise. The direct maximization of the a posteriori probability (APP) is too complex. The EM algorithm allows us to obtain the MAP sequence estimation iteratively. Since each step of the EM algorithm increases the APP, the algorithm can improve the performance of any decoding procedure
Published in:
Communications, IEEE Transactions on
(Volume:48
,
Issue:
5
)
Date of Publication: May 2000
- Page(s):
- 757 - 763
- ISSN :
- 0090-6778
- INSPEC Accession Number:
- 6619196
- Digital Object Identifier :
- 10.1109/26.843188
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- May 2000
- Sponsored by :
- IEEE Communications Society
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