Techniques for Turbo Decoding Using Parallel Processing, Comparative Analysis

Parallel turbo decoding is becoming mandatory in order to achieve high throughput and to reduce latency, both crucial in emerging digital communication applications. This paper explores and analyzes parallelism techniques in convolution turbo decoding with the vertibi and MAP algorithm. A two-level structured classification of parallelism techniques is proposed and discussed: SISO decoder level parallelism and Turbo-decoder level parallelism. The second level of this classification is thoroughly analyzed on the basis of parallelism efficiency criteria, since it offers the best trade-off between achievable parallelism degree and area overhead. MAP, LOG-MAP and SOVA Algorithms have been studied and their design considerations have been presented. Turbo coding is an advanced error correction technique widely used in the communications industry. Turbo encoders and decoders are key elements in today’s communication systems to achieve the best possible data reception with the fewest possible errors. The basis of turbo coding is to introduce redundancy in the data to be transmitted through a channel. This paper has compared the two techniques LOG-MAP and SOVA based parallel processing in Turbo Codes and an algorithm for Vertibi based decoder and encoder has been proposed.