Title :
An ML/MMSE estimation approach to blind equalization
Author :
Shao, Min ; Nikias, Chrysostomos L.
Author_Institution :
Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
Blind equalization of a communication channel is achieved by jointly estimating the deterministic channel coefficients and the random data sequence. The EM algorithm is used to determine the ML estimate of the channel. To implement the EM algorithm, one needs the MMSE estimate of the data sequence for the given estimate of the channel at each step. To reduce computational complexity, a suboptimum procedure is suggested for the MMSE estimation of the data. Preliminary simulations show that the proposed algorithm converges rapidly for a short length of data even when the channel has deep nulls
Keywords :
computational complexity; error analysis; estimation theory; maximum likelihood estimation; random processes; signal processing; telecommunication channels; EM algorithm; ML estimation; MMSE estimation; algorithm; blind equalization; communication channel; computational complexity; deterministic channel coefficients; random data sequence; simulations; suboptimum procedure; Blind equalizers; Communication channels; Computational modeling; Costs; Filtering; Finite impulse response filter; Frequency response; Image processing; Maximum likelihood estimation; Signal processing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389753
