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One of the key aspects of turbo codes is that they use soft-input and soft-output values in the decoding stage. Thus no information is discarded until the algorithm has iteratively converged to a solution, at which time a hard decision is taken. The soft-input soft-output concept refers to infinite quantized or analog values in a natural form. This research work proposes CMOS integrated circuit implementations of both the encoding and the decoding algorithms. In particular it explores an all-analog decoder implementation that will naturally exploit the continuous nature of the received signals.The proposed analog decoder is based on the additive soft-input soft-output algorithm that can be naturally mapped into a multiple input floating gate transistors implementation. By taking advantage of the symmetric structure of the trellis generated by convolutional codes, every node in the trellis can have a direct analog counterpart that will mathematically solve the decoding algorithm in the analog domain.

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Antonio F. Mondragon-Torres received the Ph.D. degree (Fullbright) from Texas A&M University, College Station. From 2002 through 2009 he was with the DSPS R&D Center s at Texas Instruments Dallas, TX. His research interests are analog and digital integrated circuit implementation of communications systems, and System-on-a-Chip methodologies.

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