Area/power efficient implementation of a Log-MAP decoder for turbo codes through memory optimization

Author(s):  
I. Atluri ◽  
T. Arslan
2003 ◽  
Vol 1 ◽  
pp. 259-263 ◽  
Author(s):  
F. Kienle ◽  
H. Michel ◽  
F. Gilbert ◽  
N. Wehn

Abstract. Maximum-A-Posteriori (MAP) decoding algorithms are important HW/SW building blocks in advanced communication systems due to their ability to provide soft-output informations which can be efficiently exploited in iterative channel decoding schemes like Turbo-Codes. Multi-standards demand flexible implementations on programmable platforms. In this paper we analyze a quantized turbo-decoder based on a Max-Log-MAP algorithm with Extrinsic Scaling Factor (ESF). Its communication performance approximate to a Turbo-Decoder with a Log-MAP algorithm and is less sensitive to quantization effects. We present Turbo-Decoder implementations on state-of-the-art DSPs and show that only a Max-Log-MAP implementation fulfills a throughput requirement of ~2 Mbit/s. The negligible overhead for the ESF implementation strengthen the use of Max-Log-MAP with ESF implementation on programmable platforms.


Author(s):  
Shiyamala S. ◽  
Vijay Soorya J. ◽  
Sanjay P. S. ◽  
Sathappan K.

With different constraint length (K), time scale, and code rate, modified MAP (maximum a posteriori) decoder architecture using folding technique, which has a linear life time chart, is developed, and dedicated turbo codes will be placed in a network-on-chip for various wireless applications. Folded techniques mitigated the number of latches used in interleaving and deinterleaving unit by adopting forward and backward resource utilizing method to M-2, where M is the number of rows and end-to-end delay get reduced to 2M. By replacing conventional full adder by high speed adder using 2 x 1 multiplexer to calculate the forward state metrics and reverse state metrics will minimize the power consumption utilization in an effective manner. In s similar way, CORDIC (Coordinated ROtation DIgital Computer) algorithm is used to calculate the LLR value and confer a highly precise value with less computational complexity by means of only shifting and adding methods.


2004 ◽  
Vol 40 (4) ◽  
pp. 251 ◽  
Author(s):  
S.-J. Park
Keyword(s):  

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