Abstract
It is usually assumed that all state metric values are necessary in the maximum a posteriori (MAP) algorithm in order to compute the a posteriori probability (APP) values. This paper extends the mathematical derivation of the original MAP algorithm and shows that the log likelihood values can be computed using only partial state metric values. By processing N stages in a trellis concurrently, the proposed algorithm results in savings in the required memory size and leads to a power efficient implementation of the MAP algorithm in channel decoding. The computational complexity analysis for the proposed algorithm is presented. Especially for the N = 2 case, we show that the proposed algorithm halves the memory requirement without increasing the compuational complexity.
Original language | English |
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Pages (from-to) | 1147-1150 |
Number of pages | 4 |
Journal | IEEE Transactions on Signal Processing |
Volume | 53 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2005 Mar |
Bibliographical note
Funding Information:Manuscript received June 28, 2003; revised April 5, 2004. This work was supported in part by the Korea Science and Engineering Foundation under Grant R08-2003-000-10761-0 and in part by the University IT Research Center Project. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Dennis R. Morgan.
Keywords
- MAP algorithm
- Memory savings
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering