DocumentCode :
1748505
Title :
Blind equalization for fast frequency selective fading channels
Author :
Galdino, Juraci Ferreira ; De Alencar, Marcelo Sampaio
Author_Institution :
DEE, Inst. Militar de Engenharia, Rio de Janeiro, Brazil
Volume :
10
fYear :
2001
fDate :
2001
Firstpage :
3082
Abstract :
This paper addresses the issue of blind adaptive maximum likelihood sequence estimation (BMLSE) using per survivor processing (PSP) over a fast frequency selective fading (FFSF) channel. Special care is dedicated to the choice of the adaptive filtering (AF) algorithm used and its influence on the receiver symbol error rate (SER) performance. An in-depth investigation of least mean square (LMS) and Kalman filtering (KF) performance is attempted. Regarding the KF algorithm two channel models were considered: first-order autoregressive (AR1) and second-order autoregressive (AR2) models. Three reception BMLSE schemes are discussed: BPSP-LMS, which uses LMS, and BPSP-KF1 and BPSP-KF2, which employ KF, according to the channel model used. For all the simulations accomplished in this work, the M-algorithm was used to obtain the survivors path. Results of several simulations, under varying signal-to-noise ratio (SNR) conditions and maximum Doppler shift (fD), are reported
Keywords :
adaptive Kalman filters; adaptive equalisers; autoregressive processes; blind equalisers; error statistics; fading channels; least mean squares methods; maximum likelihood sequence estimation; AR1 model; AR2 model; BPSP-KF1; BPSP-KF2; BPSP-LMS; Kalman filtering; M-algorithm; MLSE schemes; SER performance; SNR conditions; adaptive filtering algorithm; blind adaptive maximum likelihood sequence estimation; blind equalization; channel models; fast frequency selective fading channels; first-order autoregressive mode; least mean square performance; maximum Doppler shift; per survivor processing; receiver symbol error rate; second-order autoregressive model; signal-to-noise ratio; Adaptive filters; Blind equalizers; Error analysis; Fading; Filtering algorithms; Frequency estimation; Kalman filters; Least squares approximation; Maximum likelihood estimation; Signal to noise ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, 2001. ICC 2001. IEEE International Conference on
Conference_Location :
Helsinki
Print_ISBN :
0-7803-7097-1
Type :
conf
DOI :
10.1109/ICC.2001.937239
Filename :
937239
Link To Document :
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