A Class of Soft Decision Error Detectors for the Gaussian Channel

The main idea of this concise paper is to use symbol reliability information for improving the performance of error detectors. A class of soft decision error detectors (SDED´s) is presented, where low weight error patterns are selectively corrected. The reliability numbers govern which error pattern to correct. Asymptotic performance and bounds are derived for the Gaussian channel. It is shown that singleerror correcting SDED´s without thresholds have an exponentially lower repeat request probability than the hard decision error detector, but the same exponent in the probability of undetected errors. Detectors with thresholds are also considered. In this case it is possible to contruct an error detector with both better probability of undetected errors and better probability of repeat request than for the hard decision error detector (HDED). Bounds and computer simulations are presented and SDED´s are compared to HDED´s.