OPTIMAL SUBBLOCK-BY-SUBBLOCK DETECTION

作     者：HOEHER, P 

作者机构：Institute for Communications Technology German AeroSpace Research Establishment (DLR) Oberpfaffenhofen Germany 

出 版 物：《IEEE TRANSACTIONS ON COMMUNICATIONS》 (IEEE Trans Commun)

年 卷 期：1995年第43卷第2-4期

页      面：714-717页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 

主　　题：Opportunistic software systems development Mutual information Maximum a posteriori estimation Markov processes White noise Convolutional codes 

摘      要：We propose a recursive algorithm to compute the joint maximum a-posteriori (MAP) probability of a subblock of N consecutive symbols (i.e., a sliding window of length N) of a finite-state discrete-time Markov process of length K greater than or equal to N observed in white noise given the whole block is received. This optimal subblock-by-subblock detector (OBBD, vector MAP ) is a generalization of the optimal symbol-by-symbol detector (OSSD, symbol-by-symbol MAP ), which is obtained for N = 1. The new algorithm improves applications with outer stage processing. This is indicated by investigating the average mutual information of a convolutional coding system. An example shows that the gain (in terms of average mutual information) by using joint probabilities could even exceed the gain by delivering soft OSSD outputs instead of hard outputs.