Methods to reduce memory requirements in turbo decoding

Vahid Garousi; Amir K. Khandani

Methods to reduce memory requirements in turbo decoding

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Since the introduction of turbo codes in 1993, researchers have turned their attention to the design, performance evaluation and practical application of these codes. The practical implementation of turbo decoding algorithms faces two major challenges: (1) heavy computations for the α and the β values, and (2) huge memory requirement. Using powerful fast processors, which are in hand nowadays, one can somehow compensate the former. However, incorporating a large amount of memory in the practical turbo code devices is still a problem. Hence, it is desirable to find methods to reduce the memory requirement in the turbo decoding algorithm. In this work, two novel approaches are investigated to reduce the memory usage in turbo decoding: (1) α-inverse matrix calculation, and (2) proper quantization of α and β values.

Original language	English
Title of host publication	Antem 2002 - International Symposium on Antenna Technology and Applied Electromagnetics, Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9780969256380
Publication status	Published - 01 Jan 2002
Externally published	Yes
Event	2002 International Symposium on Antenna Technology and Applied Electromagnetics, Antem 2002 - St. Hubert, Canada Duration: 31 Jul 2002 → 02 Aug 2002

Conference

Conference	2002 International Symposium on Antenna Technology and Applied Electromagnetics, Antem 2002
Country/Territory	Canada
City	St. Hubert
Period	31/07/2002 → 02/08/2002

ASJC Scopus subject areas

Computer Networks and Communications
Hardware and Architecture
Electrical and Electronic Engineering

Cite this

@inproceedings{dca7cf63d353452a8390325f2af380ae,

title = "Methods to reduce memory requirements in turbo decoding",

abstract = "Since the introduction of turbo codes in 1993, researchers have turned their attention to the design, performance evaluation and practical application of these codes. The practical implementation of turbo decoding algorithms faces two major challenges: (1) heavy computations for the α and the β values, and (2) huge memory requirement. Using powerful fast processors, which are in hand nowadays, one can somehow compensate the former. However, incorporating a large amount of memory in the practical turbo code devices is still a problem. Hence, it is desirable to find methods to reduce the memory requirement in the turbo decoding algorithm. In this work, two novel approaches are investigated to reduce the memory usage in turbo decoding: (1) α-inverse matrix calculation, and (2) proper quantization of α and β values.",

author = "Vahid Garousi and Khandani, {Amir K.}",

year = "2002",

month = jan,

day = "1",

language = "English",

booktitle = "Antem 2002 - International Symposium on Antenna Technology and Applied Electromagnetics, Conference Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2002 International Symposium on Antenna Technology and Applied Electromagnetics, Antem 2002 ; Conference date: 31-07-2002 Through 02-08-2002",

}

Garousi, V & Khandani, AK 2002, Methods to reduce memory requirements in turbo decoding. in Antem 2002 - International Symposium on Antenna Technology and Applied Electromagnetics, Conference Proceedings., 7864633, Institute of Electrical and Electronics Engineers Inc., 2002 International Symposium on Antenna Technology and Applied Electromagnetics, Antem 2002, St. Hubert, Canada, 31/07/2002.

TY - GEN

T1 - Methods to reduce memory requirements in turbo decoding

AU - Garousi, Vahid

AU - Khandani, Amir K.

PY - 2002/1/1

Y1 - 2002/1/1

N2 - Since the introduction of turbo codes in 1993, researchers have turned their attention to the design, performance evaluation and practical application of these codes. The practical implementation of turbo decoding algorithms faces two major challenges: (1) heavy computations for the α and the β values, and (2) huge memory requirement. Using powerful fast processors, which are in hand nowadays, one can somehow compensate the former. However, incorporating a large amount of memory in the practical turbo code devices is still a problem. Hence, it is desirable to find methods to reduce the memory requirement in the turbo decoding algorithm. In this work, two novel approaches are investigated to reduce the memory usage in turbo decoding: (1) α-inverse matrix calculation, and (2) proper quantization of α and β values.

AB - Since the introduction of turbo codes in 1993, researchers have turned their attention to the design, performance evaluation and practical application of these codes. The practical implementation of turbo decoding algorithms faces two major challenges: (1) heavy computations for the α and the β values, and (2) huge memory requirement. Using powerful fast processors, which are in hand nowadays, one can somehow compensate the former. However, incorporating a large amount of memory in the practical turbo code devices is still a problem. Hence, it is desirable to find methods to reduce the memory requirement in the turbo decoding algorithm. In this work, two novel approaches are investigated to reduce the memory usage in turbo decoding: (1) α-inverse matrix calculation, and (2) proper quantization of α and β values.

UR - http://www.scopus.com/inward/record.url?scp=85016732089&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85016732089

BT - Antem 2002 - International Symposium on Antenna Technology and Applied Electromagnetics, Conference Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2002 International Symposium on Antenna Technology and Applied Electromagnetics, Antem 2002

Y2 - 31 July 2002 through 2 August 2002

ER -

Methods to reduce memory requirements in turbo decoding

Abstract

Conference

ASJC Scopus subject areas

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