The Extended-Window Channel Estimator for Iterative Channel-and-Symbol Estimation
1 DSPCom, DECOM, FEEC, University of Campinas (UNICAMP), 400 Albert Einstein Avenue, Sao Paulo 13083-970 Campinas, Brazil
2 School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, USA
EURASIP Journal on Wireless Communications and Networking 2005, 2005:349390 doi:10.1155/WCN.2005.92Published: 28 April 2005
The application of the expectation-maximization (EM) algorithm to channel estimation results in a well-known iterative channel-and-symbol estimator (ICSE). The EM-ICSE iterates between a symbol estimator based on the forward-backward recursion (BCJR equalizer) and a channel estimator, and may provide approximate maximum-likelihood blind or semiblind channel estimates. Nevertheless, the EM-ICSE has high complexity, and it is prone to misconvergence. In this paper, we propose the extended-window (EW) estimator, a novel channel estimator for ICSE that can be used with any soft-output symbol estimator. Therefore, the symbol estimator may be chosen according to performance or complexity specifications. We show that the EW-ICSE, an ICSE that uses the EW estimator and the BCJR equalizer, is less complex and less susceptible to misconvergence than the EM-ICSE. Simulation results reveal that the EW-ICSE may converge faster than the EM-ICSE.