Abstract:

The shallow water acoustic channel is characterized as a complex time, space and frequency- variant channel with several negative factors, e. g. narrow band, high ambient noise, multipath distortion and polytropic multipath time delay which pose serious difficulty for the underwater acoustic communication. A novel two-parameter adjustable least mean square (LMS) equalization algorithm is presented based on the classic parallel filter banks LMS (PFB-LMS) algorithm. The new algorithm enables hybrid adjustment of step-size and tap-length so that the sensitivity of step-size and tap-length parameter selections is alleviated. Simulation results show that the new algorithm outperforms the traditional LMS and PFB-LMS algorithms in parameter robustness under time varying channels.

Key words: information processing, shallow water acoustic channel, adaptive equalization, two- parameter adjustable least mean square equalization algorithm