Adaptive adjustment of receiver for distorted digital signals

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Abstract
The paper presents the results of an initial feasibility study into a novel technique for the adaptive adjustment of the receiver in a digital data-transmission system, operating with additive noise and severe inter-symbol interference in the received signal. The technique is an iterative process and can be used for the adjustment of the linear feedforward transversal filter that is employed ahead of a near-maximum-likelihood detector, and at the same time for the estimation of the sampled impulse response of the channel and filter, to give the information on the received signal needed by the detector. The latter two operations are equivalent to the adjustment of the feedforward and feedback transversal filters, respectively, in the corresponding nonlinear (decision-feedback)equaliser. The equaliser is, of course, a degenerate form of a near-maximum-likelihood detector, being obtained when the latter is reduced to its simplest possible form. The adaptive system operates directly on the estimate of the sampled impulse response of the channel, that must be provided at the receiver, and it requires no other input signals. It employs a root-finding algorithm that determines some of the roots (zeros) of the z-transform of the sampled impulse response of the channel. It then uses a knowledge of these roots to determine the tap gains of the linear feedforward transversal filter and to form an estimate of the sampled impulse response of the channel and filter. The technique can exploit the high tolerance to signal distortion of a near-maximum-likelihood detector in order to reduce the amount of processing of the received signal that is carried out by the adaptive filter to a level appreciably below that required by a conventional nonlinear equaliser. Thus a more cost-effective design of the receiver can be obtained. The paper describes the method of operation of two versions of the adaptive system and presents the results of computer-simulation tests over four different channels, showing both the rate and accuracy of convergence of the iterative process in each case.

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