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SNR-Adaptive Input Quantization for Turbo Decoding

Authors: Injae Yoo; In-Cheol Park;

SNR-Adaptive Input Quantization for Turbo Decoding

Abstract

This paper presents how to control the input bit-width of a turbo decoder according to the signal-to-noise ratio (SNR) adaptively. It is crucial to minimize the input bit-width while maintaining the error-correcting performance. Several quantization schemes have been presented to properly decide the input resolution of turbo decoding, but they all assume a fixed bit-width irrespective of the SNR. This paper proposes a new method to adaptively change the quantization bit-width with respect to the SNR. In addition, this paper suggests a novel method to estimate the frame-error rate (FER) performance of a turbo decoder dealing with quantized channel outputs. As a result, the whole SNR range is divided into a number of regions each of which can be processed with a certain quantization bit-width.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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