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Traceback-Based Optimizations for Maximum a Posteriori Decoding Algorithms
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Traceback-Based Optimizations for Maximum a Posteriori Decoding Algorithms
Curt Schurgers1, 2 and Anantha Chandrakasan2
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Present address: Electrical and Computer Engineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093-0407, USA |
| (2) |
Microsystems Technology Laboratories, Massachusetts Institute of Technogy, Cambridge, MA 02139, USA |
Received: 7 May 2007 Accepted: 7 December 2007 Published online: 28 May 2008
Abstract Maximum A Posteriori (MAP) decoding is a crucial enabler of turbo coding and other powerful feedback-based algorithms. To
allow pervasive use of these techniques in resources constrained systems, it is important to limit their implementation complexity,
without sacrificing the superior performance they are known for. We show that introducing traceback information into the MAP
algorithm, thereby leveraging components that are also part of Soft-Output Viterbi Algorithms (SOVA), offers two unique possibilities
to simplify the computational requirements. Our proposed enhancements are effective at each individual decoding iteration
and therefore provide gains on top of existing techniques such as early termination and memory optimizations. Based on these
enhancements, we will present three new architectural variants for the decoder. Each one of these may be preferable depending
on the decoder memory hardware requirements and number of trellis states. Computational complexity is reduced significantly,
without incurring significant performance penalty.
Keywords error correction coding - MAP estimation - very-large-scale integration
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