Title :
Recursive blind estimation and equalization of time-varying channel based on parametric model
Author_Institution :
Inst. of Microelectron., Singapore, Singapore
Abstract :
This paper proposes a new technique for recursive blind equalization of a time-varying IIR communication channel to obtain simultaneous estimation of channel impulse response and input symbols. The received sequences are represented as the output of a noisy non-Gaussian time-varying parametric model. A pseudo maximum likelihood estimation algorithm is proposed for the identification of channel parameters. The blind equalization is implemented by three algorithms: the recursive channel estimation algorithm, the Gaussian-mixture parameter estimation algorithm and the standard Kalman filtering algorithm. The equalization results are good even on low SNR received sequence and fast fading channel.
Keywords :
Gaussian processes; Kalman filters; blind equalisers; fading channels; filtering theory; maximum likelihood estimation; recursive estimation; time-varying channels; transient response; 16-QAM signal; Gaussian-mixture parameter estimation algorithm; Kalman filtering algorithm; channel parameters identification; fast fading channel; impulse response estimation; input symbols estimation; low SNR received sequence; noisy nonGaussian time-varying parametric model; parametric model; pseudo maximum likelihood estimation algorithm; received sequences; recursive blind equalization; recursive blind estimation; recursive channel estimation algorithm; time-varying IIR channel; Blind equalizers; Channel estimation; Communication channels; Filtering algorithms; Gaussian channels; Maximum likelihood estimation; Parameter estimation; Parametric statistics; Recursive estimation; Time-varying channels;
Conference_Titel :
Communication Systems, 2002. ICCS 2002. The 8th International Conference on
Print_ISBN :
0-7803-7510-6
DOI :
10.1109/ICCS.2002.1182443