Performances of Punctured Tail-Biting Convolutional Codes Using Initial State Estimation

Abstract

Performances of punctured tail-biting convolutional codes are studied using a novel initial state estimation technique. The initial states of a tail-biting trellis are estimated as soft initial metrics by channel observations and code configurations for improving the performance of the circular Viterbi decoding of tail-biting convolutional codes. The initial state estimation is applied for any kind of systematic and a special form of nonsystematic tail-biting convolutional codes. Through simulations, it is observed that the initial state estimation improves the decoding performances of punctured tail-biting convolutional codes in the circular Viterbi decoder with delay constraints.