Blind identification using ARMA model second order

摘要

This thesis addresses the problem of blind identification for high speed wireless digitalcommunication systems, they are always subject to intersymbol interference (ISI) caused bychannel amplitude and phase distortions. In order to improve the capacity of the channel, blindIdentification without the use of pilot sequences is used.In this theses we investigate new results that address the identification of linear rational channelsbased on the use of second order cyclic statistics (SOCS). It is shown that channel identificationis achievable for a class of linear channels without the need for a pilot tone or training periods.Moreover, channel identification based on cyclic statistics does not preclude Gaussian or nearGaussian inputs. SNR with Gaussian distribution was possible to handle.We also investigate the identification of linear time-invariant (LTI) ARMA systems based onsecond order cyclic statistics using IIR filter. We present a parametric method. The parametricmethod we use directly identifies the zeros and poles of ARMA channels with a mixed phase.Computer simulation illustrates the effectiveness of our methods in identifying ARMA systemimpulse responses, compared by the traditionally used CMA method.We also investigated blind equalization using SOCS in order to peruse phase and speed theconvergence