Implementation of a HIPERLAN/1 compatible CMF-DFE equaliser

Abstract

The Channel Matched Filter Decision Feedback Equaliser (CMF-DFE) is a high performance equalisation method with reduced computational complexity; which is essential for high-speed communication systems with severe intersymbol interference. The method exploits the fact that matched filtering of a wideband channel results in a symmetrical channel profile centred on a realvalued peak while exploiting multipath diversity. This paper describes the implementation of a HIPERLAN/l compatible equaliser using the CMF-DFE method. The performance of the implemented algorithm and the implementation benchmarks are given for the Hiperladl standard. Results are also given for a number of different modulation schemes.

CMF-DFE Based Adaptive Blind Equalization Using Particle Swarm Optimization

“…The output signal of a typical communication channel can be represented with the convolution v(t) =       The CMF-DFE provides several advantages over the conventional DFE structure [24], [25]. In [24], static calculation of CMF-DFE which provides quite stable and high performance equalizer implementation is studied.…”

“…In [24], static calculation of CMF-DFE which provides quite stable and high performance equalizer implementation is studied. They are calculated blindly by using the autocorrelation function of incoming sequence at the receiver, and run the blind trainings for the CMF which is a linear filter.…”

“…The constants L ff and L fb are the number of feedforward and feedback tap numbers of DFE filter. When a CMF filter is assumed available before equalizer, the DFE coefficients can be directly calculated by the zeroforcing method [24], [26] as…”

“…The components of D matrix are calculated by (9) using only the received data. Equation (11) also corresponds to the Minimum Mean Square Error (MMSE) equalizer as in [27], providing that the CMF presents before DFE [24], [28]. In Fig.…”

“…Thus, the non-convex convergence profile of an equalizer is avoided by only remaining channel coefficients to be estimated, which is turned to be linear filter estimation in order to complete the receiver. In addition, CMF plays a crucial role in equalization by providing a uniform ISI profile and accurate synchronization [24]- [28]. However, the equalization problem has been significantly simplified.…”