Title :
Tuned turbo codes
Author :
Koller, Christian ; Graell i Amat, Alexandre ; Kliewer, Joerg ; Vatta, Francesca ; Costello, Daniel J.
Author_Institution :
Dept. of Electr. Eng., Univ. of Notre Dame, Notre Dame, IN
Abstract :
As implied by previous studies, there exists a fundamental trade-off between the minimum distance and the iterative decoding convergence behavior of a turbo code. While capacity achieving code ensembles typically are asymptotically bad in the sense that their minimum distance does not grow linearly with block length and they therefore exhibit an error floor at medium to high signal to noise ratios, asymptotically good codes usually converge further away from channel capacity. In this paper we present so-called tuned turbo codes, a family of asymptotically good hybrid concatenated code ensembles, where minimum distance growths and convergence thresholds can be traded-off using a tuning parameter lambda. By decreasing lambda, the asymptotic minimum distance growth rate coefficient is reduced for the sake of improved iterative decoding convergence behavior, and thus the code performance can be tuned to fit the desired application.
Keywords :
channel capacity; channel coding; concatenated codes; iterative decoding; turbo codes; asymptotic hybrid concatenated code ensemble; asymptotic minimum distance growth rate coefficient; channel capacity; iterative decoding convergence behavior; tuned turbo code ensemble; Concatenated codes; Convergence; Convolution; Convolutional codes; Information theory; Iterative decoding; Polynomials; Power generation; Signal to noise ratio; Turbo codes;
Conference_Titel :
Information Theory and Its Applications, 2008. ISITA 2008. International Symposium on
Conference_Location :
Auckland
Print_ISBN :
978-1-4244-2068-1
DOI :
10.1109/ISITA.2008.4895619