On turbo code decoder performance in optical-fiber communication systems with dominating ASE noise

Abstract

In this paper, we study the effects of different ASE noise models on the performance of turbo code (TC) decoders. A soft-decoding algorithm, the Bahl, Cocke, Jelinek, and Raviv (BCJR) decoding algorithm [1], is generally used in the TC decoders. The BCJR algorithm is a maximum a posteriori probability (MAP) algorithm, and is very sensitive to the noise statistics. The Gaussian approximation of the ASE noise is widely used in the study of optical-fiber communication systems [2]-[8], and there exist standard TCs for additive white Gaussian noise (AWGN) channels. We show that using a MAP decoding algorithm based on the Gaussian noise assumptions, however, may significantly degrade the TC decoder performance in an optical-fiber channel with non-Gaussian ASE noise. To take full advantage of TC, the accurate noise statistics in optical-fiber transmissions should be used in the MAP decoding algorithm.

Optical signal quality metric based on statistical moments and Laguerre expansion

“…Therefore the Laguerre expansion should be used in applications, which require a good estimation of the general shape of the pdfs and of the optimum threshold. For example, as discussed in (Cai et al 2003;Bosco et al 2003), poor estimation of the decision threshold may significantly degrade the performance of TC decoders and in this case the new model is expected to perform much better. If the model presented here is applied to a channel with dispersion, the presence of dispersion effectively splits the two logical levels into a number of sublevels.…”

“…The inaccuracy of determining the optimum threshold cannot however be removed from the Gaussian approximation. Therefore this approximation is deficient for applications when good estimation of the optimum threshold is needed, for example for optimizing some forward error correction codes, like Turbo Codes (TC) (Cai et al 2003). In (Cai et al 2003) the effect of different noise models on the performance of the TC decoders was investigated and it was shown that the use of Gaussian approximation may severely degrade this performance.…”

“…Therefore this approximation is deficient for applications when good estimation of the optimum threshold is needed, for example for optimizing some forward error correction codes, like Turbo Codes (TC) (Cai et al 2003). In (Cai et al 2003) the effect of different noise models on the performance of the TC decoders was investigated and it was shown that the use of Gaussian approximation may severely degrade this performance. Similarly, it was found in (Bosco et al 2003) that the use of Gaussian approximation leads to very significant degradation in the performance of soft decoders based on turbo-product error correction codes.…”

New generation FTTH ONU and OLT design for upstream transmission in WDM PON including optimized combination of electronics and optics

“…In systems where ASE noise is dominant and with ideal filtering processes, the detected signal statistics is (as shown in section 2.3.1) chi-square [Marcuse 1991, Humblet 1991, Cai 2003, Bosco 2001]. Applying square root (SQRT) mathematical function over the detected signal, the signal is transformed into a Rice distribution, which is more similar to the Gaussian, so the resulting eye diagram is more symmetrical, as shown before.…”