Maximum likelihood DE coding of convolutional codes using viterbi algorithm with improved error correction capability

Abstract

Convolutional codes are applied in applications that require good performance with low implementation cost. It is a finite state machine, processing information bits in a series manner. Viterbi algorithm [1] can be applied to a host of problems encountered in digital communication systems. The Viterbi algorithm cannot detect any error but can sometimes correct it, while calculating one survivor path with minimum metric value. The maximum likelihood decoding of convolutional encoder with Viterbi algorithm is a good forward error correction [3] method suitable for single and double bit error correction by means of finding the code branch in the code trellis that was most likely to transmit. The modified decoding process proposed in this paper, we shall use a different approach to derive the exact bit, double bit, burst error and a symbol error correction process. It will detect and correct the errors by means of connecting and comparing the metric values at the present, previous and next states of the Viterbi decoding. also it is offering 30-36% better than the Viterbi and 99.9% of error correction, but the computational complexity is decreases and time are increases about 20-40%.