Combined channel estimation and data decoding based on fuzzy logic

A simple method that detects the data sequence and at the same time estimates the channel condition is proposed using the Viterbi algorithm and fuzzy logic for the convolutional code. After a fixed number of decoding steps, the fuzzy logic unit reads the branch metric value of the survivor and the d...

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Published in:IEEE transactions on instrumentation and measurement Vol. 51; no. 2; pp. 342 - 346
Main Authors: Young-Bae Byun, Takama, Y., Hirota, K.
Format: Journal Article
Language:English
Published: New York IEEE 01.04.2002
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Channel estimation
Channels
Convolution
Convolutional codes
Decoding
Demodulators
Estimates
European Space Agency
Fuzzy logic
Intersymbol interference
Matched filters
Maximum likelihood decoding
Maximum likelihood detection
Modulators
Noise levels
Signal to noise ratio
Viterbi algorithm
ISSN:0018-9456, 1557-9662
Online Access:Get full text
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Abstract A simple method that detects the data sequence and at the same time estimates the channel condition is proposed using the Viterbi algorithm and fuzzy logic for the convolutional code. After a fixed number of decoding steps, the fuzzy logic unit reads the branch metric value of the survivor and the difference between maximum and minimum survivor path metric values at the Viterbi decoder and estimates the channel condition with the signal-to-noise ratio. The proposed method enables the channel estimation regardless of what kinds of modulator and demodulator are used. In the experiment, constraint length 7 and code rate 1/2 convolutional code that is standardized by the European Space Agency (ESA) is used. The effective movement range of the proposed channel estimation method is from 0.0 dB to 25 dB.
AbstractList A simple method that detects the data sequence and at the same time estimates the channel condition is proposed using the Viterbi algorithm and fuzzy logic for the convolutional code. After a fixed number of decoding steps, the fuzzy logic unit reads the branch metric value of the survivor and the difference between maximum and minimum survivor path metric values at the Viterbi decoder and estimates the channel condition with the signal-to-noise ratio. The proposed method enables the channel estimation regardless of what kinds of modulator and demodulator are used. In the experiment, constraint length 7 and code rate 1/2 convolutional code that is standardized by the European Space Agency (ESA) is used. The effective movement range of the proposed channel estimation method is from 0.0 dB to 25 dB.
A simple method that detects the data sequence and at the same time estimates the channel condition is proposed using the Viterbi algorithm and fuzzy logic for the convolutional code. After a fixed number of decoding steps, the fuzzy logic unit reads the branch metric value of the survivor and the difference between maximum and minimum survivor path metric values at the Viterbi decoder and estimates the channel condition with the signal-to-noise ratio. The proposed method enables the channel estimation regardless of what kinds of modulator and demodulator are used. In the experiment, constraint length 7 and code rate 1/2 convolutional code that is standardized by the European Space Agency (ESA) is used. The effective movement range of the proposed channel estimation method is from 0.0 dB to 25 dB
Author Young-Bae Byun
Takama, Y.
Hirota, K.
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SubjectTerms Channel estimation
Channels
Convolution
Convolutional codes
Decoding
Demodulators
Estimates
European Space Agency
Fuzzy logic
Intersymbol interference
Matched filters
Maximum likelihood decoding
Maximum likelihood detection
Modulators
Noise levels
Signal to noise ratio
Viterbi algorithm
Title Combined channel estimation and data decoding based on fuzzy logic
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