Buffer control for variable complexity Fano decoders

Fano sequential decoders are variable complexity convolutional decoders, which have the desirable property of operating with very low computation at high SNR. In portable mobile communications, it is often desirable to trade BER with decoder complexity/power consumption. However, the variable comple...

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Bibliographic Details
Published in:2001 IEEE Global Telecommunications Conference - Globecom Vol. 1; pp. 176 - 180 vol.1
Main Authors: Wendi Pan, Ortega, A.
Format: Conference Proceeding
Language:English
Published: IEEE 2001
Subjects:
Bit error rate
Convolutional codes
Delay
Electric variables control
Energy consumption
Maximum likelihood decoding
Mobile communication
Power engineering and energy
Size control
Viterbi algorithm
ISBN:0780372069, 9780780372061
Online Access:Get full text
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Summary:Fano sequential decoders are variable complexity convolutional decoders, which have the desirable property of operating with very low computation at high SNR. In portable mobile communications, it is often desirable to trade BER with decoder complexity/power consumption. However, the variable complexity nature of the Fano algorithm means that buffers are required for the Fano decoder due to large variations in processing delays. In this paper, we formulate the buffer control problem as one that seeks to minimize the overall probability of block loss, subject to a finite buffer size constraint. The overall probability of block loss is comprised of two terms, corresponding to loss due to excessive bit errors and decoder buffer overflow, respectively. This leads to an interesting trade-off, as faster decoding often means higher bit error rate. Based on the joint distribution of decoding complexity and BER, at each decoding stage, we find an optimal Fano decoder parameter (/spl Delta/) to minimize block loss. In addition, we propose a simple real-time table lookup algorithm that implements the /spl Delta/ control policy. Simulation results demonstrate the superior performance of the proposed algorithm.
ISBN:0780372069
9780780372061
DOI:10.1109/GLOCOM.2001.965102