Further results on the EKF-CRTRL equalizer for fast fading and frequency selective channels

This paper shows further results on the EKF-RTRL (extended Kalman filter-real time recurrent learning) equalizer comparing its performance with the PSP-LMS (per survivor processing-least mean squares) equalizer for fast fading selective frequency channels using the WSS_US (wide sense stationary-uncorrelated scattering) model. The EKF-RTRL is a symbol by symbol neural equalizer and the PSP-LMS equalizer uses the maximum likelihood criterion for symbol sequence estimation and the per survivor processing principle. The performance here presented depicts several scenarios regarding the channel variation speed. The performance considered in this paper is the symbol error rate (SER). A comparison involving the computational complexity of both equalizers is also carried out.