This document discusses performance evaluation of reconfigurable turbo decoding algorithms for mobile WiMAX standards. It introduces the max-log-MAP (ML-MAP) algorithm and sliding window method for decoding process. The ML-MAP SISO decoder architecture is described, including the branch and state metric units and LLR computation unit. Simulation results are presented and it is concluded that the ML-MAP technique can reduce the critical path of a turbo decoder. Further work is needed to investigate the performance of the ML-MAP SISO decoder architecture in terms of area usage, power consumption, timing delay, and memory usage.

1. Host Network Host
Signal
(or Data)
PERFORMANCE EVALUATION OF
RECONFIGURABLE TURBO DECODING
Dat
a
ALGORITHMS FOR MOBILE WIMAX STANDARDS
Secube Plus Series1
Data (or
Signal)
Data (or
Signal)
conversion conversion
conversion
conversion
Dat
a
BY
AJAL.A.J
Network

2. Iterative decoding
Soft-Input Soft-Output (SISO)
Decoding Algorithms
Trellis-Based
Estimation Algorithms
Viterbi
Algorithm
SOVA
Improved
SOVA
MAP
Algorithm
max-log-MAP
log-MAP
Sequence
Estimation
Symbol-by-symbol
Estimation
Viterbi algorithm
1967 Viterbi
SOVA
1989
Hagenauer/Hoeher
Bi-SOVA
2006
Papke/Robertson/V
illebrun
MAP algorithm
1974
Bahl/Cocke/Jelinek
/Raviv
log-MAP
1994 Villebrun
max-log-MAP
2007 Koch and Baier

3. Outline
• Introduction
• Turbo decoder structure
• ML-MAP algorithm
• SW method decoding process
• ML-MAP SISO decoder
architecture
• Branch and State Metric Units
• LLR Computation Unit
• Simulation results
• Conclusions
Secube Plus Series 3

4. Implemented MAP
decoder
Backdoors

5. Introduction
• Since the Log MAP and ML-MAP
algorithms have been proposed, they are
widely used to implement the turbo
decoders.
• Furthermore, the sliding window (SW)
method provides efficient area usage by
dividing a block of input symbols into a
number of sub-blocks.
• The speed is one of the key factors
beside the power consumption and area
usage for efficient implementation of
turbo decoders.
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6. 6
ML-MAP decoder

7. ML-MAP SISO decoder
architecture
Secube Plus Series7
input
data
symbol
s
LLR
value
s
forward
state
metric

8. ML-MAP (Branch and State
Metric Units)
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9. ML-MAP (LLR Computation
Unit )
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10. Concluding Remarks
• In this paper, we introduce a
technique that can reduce the critical
path of a turbo decoder using
max log MAP successfully
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11. FFUUTTUURREE WWOORRKK
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•ttiimmiinngg ddeellaayy..
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12. THANKS