The article discusses soft-decision decoding of binary linear block codes using the t-algorithm and its variants. New variants of the basic algorithm are presented that reduce the decoding complexity using a threshold adaptive to the signal-to-noise ratio and address the variable decoding complexity by either limiting the memory or using a generalized M-algorithm with a nonconstant state profile.

This paper proposes a new and computationally efficient soft-decision decoding algorithm for binary linear block codes. It uses the tree representation of a systematically encoded block code. The tree representation is traversed through in a breadth-first fashion and it is adaptively pruned during the decoding using the following principle: if the metric difference between the best partial path and any other partial path at the same level is greater than a threshold value, then such a path is not extended any further. The threshold value is chosen based on a signal-to-noise ratio estimate. The efficiency of the pruning procedure is enhanced by constructing the tree so that the most reliable symbols are processed first. We show that practically optimum bit error rate performance in the additive white Gaussian noise channel can be efficiently achieved.

Floating-point arithmetic offers several benefits in digital signal processing. Floating-point A/D- and D/A-converters are needed in the realization of true floating-point signal processing systems. Novel, simple floating-point A/D- and D/A-conversion methods, based on the close resemblance of floating-point and logarithmic number representations, are introduced in this paper. These methods are easy to tailor to different specifications, and they offer a simple trade-off between dynamic range and accuracy.>

The effects of coefficient quantization to the response of a digital filter are studied. Easy-to-use expressions for the required coefficient word length, with which the filter response deviations are within specified bounds, are derived for filters realized with floating-point or logarithmic arithmetic. The required coefficient word lengths of floating-point and fixed-point realizations of filters are compared with simulations.>