Design and implementation of low-energy turbo decoders

Turbo codes have been chosen in the third generation cellular standard for high-throughput data communication. These codes achieve remarkably low bit error rates at the expense of high-computational complexity. Thus for hand held communication devices, designing energy efficient Turbo decoders is of great importance. In this paper, we present a suite of MAP-based Turbo decoding algorithms with energy-quality tradeoffs for additive white Gaussian noise (AWGN) and fading channels. We derive these algorithms by applying approximation techniques such as pruning the trellis, reducing the number of states, scaling the extrinsic information, applying sliding window, and early termination on the MAP-based algorithm. We show that a combination of these techniques can result in energy savings of 53.2% (50.0%) on a general purpose processor and energy savings of 80.66% (80.81%) on a hardware implementation for AWGN (fading) channels if a drop of 035 dB in SNR can be tolerated, at a bit error rate (BER) of 10^-5. We also propose an adaptive Turbo decoding technique that is suitable for low power operation in noisy environments.