The Improvement of ACSU of Viterbi Decoder for a Long Constraint Length with Soft-decision

Abstract

The Viterbi algorithm is a method based on the maximum-likelihood principle to decode convolutional codes. This decoder is considered as an optimal method. In this decoder, there are two ways to enhance the error-correct capability, such as the use of soft-decision and the increasing of constraint length. However, both ways will also increase the system complexity. It has found that an Add-Compare-Select Unit (ACSU) in the decoder is the most complex module using soft-decision. The increasing rate in area of an ACSU module is also proportional to the constraint length. Therefore, the area reduction of ACSU is the most effective strategy to reducing the size of a Viterbi decoder. This system is aiming to reduce the size of the critical module using soft-decision with constraint length, Q=8. In this paper, a new architecture that is free from the absolute value comparison is proposed to reduce the hardware complexity from original ACSUs. So, the proposed ACSU can effectively reduce the hardware and the cost of a Viterbi decoder with larger constraint length.