Analogue decoding of tail-biting convolutional codes based on Tanner graph

Abstract

A scheme is proposed to decode a tail-biting convolutional code based on its Tanner graph, which is traditionally done using a forward–backward MAP algorithm. Therefore, decoding may be performed using a standard sum–product algorithm. With respect to decoding based on trellis, all variables in a Tanner graph are binary, which may lead to complexity reduction. A min-sum algorithm is used to decrease the analogue circuit complexity. Simulation shows there is no significant degradation compared with more complex traditional methods.