A low complexity decision feedback equalization for sparse wireless channels [articol]

Abstract

In this paper, a low complexity decision feedback equalizer (DFE) appropriate for channels with long and sparse impulse response (IR) is studied. Such channels are encountered in many high-speed wireless communications applications. It is shown that, in cases of sparse channels, the feedforward and feedback (FB) filters of the DFE have a particular structure, which can be exploited to derive efficient implementations of the DFE, provided that the time delays of the channel IR multipath components are known. This latter task is accomplished by other technique, which estimates the time delays based on the form of the channel input-output cross-correlation sequence in the frequency domain. A distinct feature of the resulting DFE is that the involved FB filter consists of a reduced number of active taps that implies some computational savings than conventional DFE. The resulting DFE also exhibits, improved tracking capabilities and faster convergence as compared with the conventional DFE, that implies a shorter training sequence . Moreover, the new algorithm has a simple form and its steady-state performance is almost identical to that of the conventional DFE.