Iterative Decoding of Concatenated Convolutional Codes: Implementation Issues The speed of decoding can be increased by raising the decoder clock frequency, increasing the use of parallel hardware, and judiciously limiting the number of decoding iterations.

This tutorial paper gives an overview of the implementation aspects related to turbo decoders, where the term turbo generally refers to iterative decoders intended for parallel concatenated convolutional codes as well as for serial concatenated convolutional codes. We start by considering the general structure of iterative decoders and the main features of the soft-input soft-output algorithm that forms the heart of iterative decoders. Then, we show that very efficient parallel architectures are available for all types of turbo decoders allowing high-speed implementations. Other implementation aspects like quantization issues and stopping rules used in conjunction with buffering for increasing throughput are considered. Finally, we perform an evaluation of the complex- ities of the turbo decoders as a function of the main parameters of the code.