Blind identification of mixed-phase FIR systems with application to mobile communication channels

We investigate the applicability of two algorithms for the blind identification of mixed-phase linear time-invariant FIR systems to the estimation of mobile radio channels on GSM conditions. One approach is based on second order cyclostationary statistics (SOCS), whereas the other exploits higher order stationary statistics (HOSS) of the received signal. While the former class of algorithms suffers from "singular" systems which can not be identified, the latter class is said to require an excessive number of samples of the received signal to achieve comparable performance levels. The purpose of this paper is two-fold: first, we demonstrate that "singular" systems represent a severe limitation to SOCS-based methods when it comes to the estimation of time-variant mobile radio channels from a small number of received samples. Secondly, we reveal that the approach relying on 4th order statistics yields a superior estimation performance: at a signal-to-noise-ratio of 10 dB, all channel examples can be identified from 142 samples of a GSM burst within a normalized mean square error bound of 7 per cent.