In digital communication systems, the error probability in the presence of intersymbol interference (II) and additive noise may be calculated to any desired degree of accuracy by well-known approximation methods which avoid the exponential computation growth (with the number of interferers) inherent in an exhaustive method, on the condition that a fast technique for computing II moments is available. Such a technique is indeed available at present, but it is strongly limited by the assumption that the data symbols are mutually independent. In this paper, this limitation is removed, and a fast procedure is given for computing H moments of correlated digital signals. The computations grow linearly with the number of interferers. The assumption made is that correlated symbols are produced by a general finite-state sequential machine. As illustrative examples, the fast procedure is applied to bipolar and Franaszek MS-43 codes.

Moments of correlated digital signals for error probability evaluation

An approach to evaluate the error probability in conventional PAM digital data transmission systems with correlated symbols in the presence of intersymbol interference and additive noise is formulated in general and it is applied to the Gram-Charlier series expansion method. It is shown that the technique of conditioning few symbols before and/or after the symbol to be detected increases substantially the range of signal-to-noise ratios with an acceptable increase of numerical work. This technique also improves existing bounds on error probability, as, e.g, Glave's bound.

Considerations on Error Probability in Correlated-Symbol Systems

ASK Baseband System

An upper and lower bound to the probability of error is presented for a digital communication system with dependent symbols affected by additive noise and intersymbol interference. Explicitly considered are two systems in which independent binary symbols are encoded into ternary dependent symbols, i.e., a bipolar code and a dicode. The bounds practically coincide under a proper choice of certain integers; hence the true value of probability of error can be computed as a function of signal to noise ratio.

I. Korn

Papers

Probability of error in digital communication systems with intersymbol interference and dependent symbols (Corresp.)