DocumentCode :
359249
Title :
An architecture for miniaturised low power convolutional decoders
Author :
Demosthenous, Andreas ; Taylor, John
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. Coll. London, UK
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
852
Abstract :
Convolutional decoders have long been important in applications where very noisy channels are encountered. The technique has become more significant with the advent of new application areas such as mobile radio systems of various types and digital magnetic recording systems. The most commonly employed decoding technique is the Viterbi algorithm (VA). This provides an optimum method for realising a convolutional decoder, but requires a large amount of digital memory, typically up to 50% of the total chip area. In this paper we describe an alternative method which we call the modified feedback decoding algorithm (MFDA). This requires no digital path memory and so can be realised entirely using analogue components. Although strictly sub-optimal, the loss of coding gain compared to the VA is only about 0.4 dB for a K=5 code.
Keywords :
analogue integrated circuits; analogue processing circuits; channel coding; codecs; convolutional codes; decoding; 0.4 dB; analogue components; architecture; coding gain; digital magnetic recording; loss; miniaturised low power convolutional decoders; mobile radio systems; modified feedback decoding algorithm; noisy channels; Application software; Circuits; Convolution; Convolutional codes; Decoding; Detectors; Digital magnetic recording; Feedback; Hardware; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference, 2000. MELECON 2000. 10th Mediterranean
Print_ISBN :
0-7803-6290-X
Type :
conf
DOI :
10.1109/MELCON.2000.880067
Filename :
880067
Link To Document :
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