Blind Equalization with Fractional Sampling Metric Combining for Avoiding Channel Estimate Ambiguity in Mobile Radio
Issei Kanno, Hiroshi Suzuki, Kazuhiko Fukawa · 2006
This paper proposes a new blind adaptive equalizer based on maximum-likelihood sequence estimation (MLSE) for frequency selective mobile radio channels. A conventional blind MLSE equalizer with a single fractionally spaced transversal filter can cope with timing offset, but it suffers from a performance degradation due to the ambiguity of blind channel estimation. To avoid this ambiguity, this paper proposes a different type of fractional sampling in which separate symbol-spaced channel estimations are performed in the respective fractional sampling phases. The estimation employs a recursive form using the Moore-Penrose generalized inverse matrix. The equalizer combines the separate channel estimation errors, and provides the sum for the Viterbi algorithm processor as the branch metric, which tremendously reduces the probability that the correct solution is turned into an ambiguous false solution. Computer simulation demonstrates the effectiveness of the proposed equalizer on frequency selective fading channels.