Performance analysis of Adaptive Decision Feedback Turbo Equalization (ADFTE) using Recursive Least Square (RLS) algorithm over least mean square (LMS) algorithm

In modern digital communication noise plays an important role. It essential to minimise the amount of noise added in the communication channel. The signal quality can be enhanced, by modelling the channel at the receiver, by means of equalization. Given large number of users employed in the system over multipath channels causing significant Multiple-Access Interference (MAI) & Inter Symbol Interference (ISI), the optimal MUD is thus prohibitively complex. Hence the sub-optimal detectors such as low-complexity linear & non-linear equalizers have to be considered. In this paper, Recursive Least Square (RLS) adaptation algorithm for Adaptive Decision Feedback Turbo Equalizer (ADFTE) is proposed. Along with the application of the adaptive method to the DFE-RLS equalizer, turbo-principle can easily be applied The performance of the system is improved in the fashion of exchanging the extrinsic information iteratively among the Soft-Input/Soft-Output (SISO) equalizer & SISO channel decoder Until convergence is achieved. The proposed turbo equalization implements the LOG-MAP (Maximum A Posterior) exclusively for both equalization & decoding. At each iteration, the estimated symbol is then saved as a priori information for next iteration. The simulation results shows that the proposed algorithm for DFE & turbo decoding offers performance gain improvement of 0.7dB over the DFE-LMS.