TY - JOUR
T1 - Design and implementation of low-energy turbo decoders
AU - Kaza, Jagadeesh
AU - Chakrabarti, Chaitali
N1 - Funding Information:
Manuscript received December 19, 2002; revised December 19, 2003. This work was supported by the Center for Low Power Electronics under EEC 9523338. J. Kaza is with Texas Instruments Incorporated, Dallas, TX 75243 USA (e-mail: jagadeeshk@ti.com). C. Chakrabarti is with the Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287 USA (e-mail: chaitali@asu.edu). Digital Object Identifier 10.1109/TVLSI.2004.832942
PY - 2004/9
Y1 - 2004/9
N2 - 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.
AB - 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.
KW - Adaptive turbo decoder
KW - Energy quality tradeoffs
KW - Low power
KW - Very large scale integration (VLSI)
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U2 - 10.1109/TVLSI.2004.832942
DO - 10.1109/TVLSI.2004.832942
M3 - Article
AN - SCOPUS:4544344426
SN - 1063-8210
VL - 12
SP - 968
EP - 977
JO - IEEE Transactions on Very Large Scale Integration (VLSI) Systems
JF - IEEE Transactions on Very Large Scale Integration (VLSI) Systems
IS - 9
ER -