Fast Subspace-based Adaptive Channel Shortening for Multicarrier Systems

In cyclic-prefixed communication systems, if the delay spread of the channel is longer than the cyclic prefix (CP) a channelshortening equalizer (CSE) can be used to restore the desired operation of such systems. Since in time-varying environment we are interested in fast adaptive equalizer with tracking capability, the aim of this paper is to propose RLS-type algorithm for channel shortening. In this paper, we first propose an RLS-type algorithm to estimate the eigenvector corresponding to the smallest eigenvalue of a matrix and based on this algorithm we develop an RLS-type blind channel shortener. We also, based on the novel RLS-based adaptive algorithm for generalized eigen-decomposition [8], extend an update rule which allow for the use of more data, as well as for shortening to different channel length. Furtheremore, based on PAST algorithm, we propose an RLS-type training based update rule to shorten the channel under MMSE criterion. Simulations show the speed advantage of the proposed algorithms.

Keywords:

blind , channel shortening , cyclic prefix , orthogonal-frequency-division multiplexing (OFDM) , subspace tracking