Investigation of Near Shannon Limit Coding Schemes

TITLE AND SUBTITLE:
Investigation of Near Shannon Limit Coding Schemes

AUTHOR(S):
S.C. Kwatra, J. Kim, and Fan Mo

REPORT DATE:
September 1999

FUNDING NUMBERS:
WU-632-50-5C-00
NAG3-1718

PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES):
The University of Toledo
Department of Electrical Engineering and Computer Science
College of Engineering
Toledo, Ohio 43606

PERFORMING ORGANIZATION REPORT NUMBER:
E-11924

SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES):
National Aeronautics and Space Administration
John H. Glenn Research Center at Lewis Field
Cleveland, Ohio 44135-3191

REPORT TYPE AND DATES COVERED:
Final Contractor Report

SPONSORING/MONITORING AGENCY REPORT NUMBER:
NASA CR-1999-209402

SUPPLEMENTARY NOTES:
Project Manager, R.E. Jones, Communications Technology Division, NASA Glenn Research Center, organization code 5650, (216) 433-3457.

ABSTRACT:
Turbo codes can deliver performance that is very close to the Shannon limit. This report investigates algorithms for convolutional turbo codes and block turbo codes. Both coding schemes can achieve performance near Shannon limit. The performance of the schemes is obtained using computer simulations. There are three sections in this report. First section is the introduction. The fundamental knowledge about coding, block coding and convolutional coding is discussed. In the second section, the basic concepts of convolutional turbo codes are introduced and the performance of turbo codes, especially high rate turbo codes, is provided from the simulation results. After introducing all the parameters that help turbo codes achieve such a good performance, it is concluded that output weight distribution should be the main consideration in designing turbo codes. Based on the output weight distribution, the performance bounds for turbo codes are given. Then, the relationships between the output weight distribution and the factors like generator polynomial, interleaver and puncturing pattern are examined. The criterion for the best selection of system components is provided. The puncturing pattern algorithm is discussed in detail. Different puncturing patterns are compared for each high rate. For most of the high rate codes, the puncturing patten does not show any significant effect on the code performance if pseudo random interleaver is used in the system. For some special rate codes with poor performance, an alternative puncturing algorithm is designed which restores their performance close to the Shannon limit. Finally, in section three, for iterative decoding of block codes, the method of building trellis for block codes, the structure of the iterative decoding system and the calculation of extrinsic values are discussed.

SUBJECT TERMS:
Coding; Modulation; Communications

NUMBER OF PAGES:
82

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