Abstract
This paper investigates the decoding of turbo codes in impulsive symmetric α-stable (SαS) noise. Due to the nonexistence of a closed-form expression for the probability density function (pdf) of α-stable processes, numerical-based SαS pdf is used to derive branch transition probability (btp) for the maximum a posteriori turbo decoder. Results show that in Gaussian noise, the turbo decoder achieves similar performance using both the conventional and the proposed btps, but in impulsive channels, the turbo decoder with the proposed btp substantially outperforms the turbo decoder utilizing the conventional btp. Results also confirm that the turbo decoder incorporating the proposed btp outperforms the existing Cauchy-based turbo decoder in non-Cauchy impulsive noise, while the two decoders accomplish similar performance in Cauchy noise.
Highlights
Turbo codes invented in 1993 [1] have many applications in various fields [2,3,4]
We propose a new branch transition probability for the maximum a posteriori (MAP) turbo decoder which covers all cases of symmetric α-stable (SαS) noise including Gaussian and Cauchy
We have investigated the decoding of turbo codes using the MAP algorithm in environments impaired by impulsive SαS noise
Summary
Turbo codes invented in 1993 [1] have many applications in various fields [2,3,4] They were developed under the assumption of Gaussian noise despite the fact that many practical environments are known through experimental measurements to suffer from frequent occurrence of impulsive noise. In [13], the authors studied soft-decision decoding in SαS noise based on the required side information In their approach, Gaussian and Cauchy pdfs were used to derive closedform soft-decision metrics which lead to exact receivers in Gaussian and Cauchy noise. We propose a new branch transition probability (btp) for the maximum a posteriori (MAP) turbo decoder which covers all cases of SαS noise including Gaussian and Cauchy.
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