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Introduction
Turbo codes for channel coding were presented by Berrou et al. in 1993, which brought a drastic development in channel coding. They gave superior Forward Error Correction (FEC) performance than other codes. By achieving half a decibel of Shannon's Limit, Berrou and Glavieux (2003) provide reliable data transmission. The turbo codes have been applied in different standards and various generations of cellular systems like 4G and 5G (Lin et al. 2018; Morgado et al. 2018; Schaich et al. 2016; Zhan et al. 2015).
Among the two decoding algorithms used for Turbo decoding, the implementation process is tedious in the Maximum A-posteriori Probability (MAP) algorithm. A modified version of the MAP algorithm, called the Log-MAP algorithm was developed, which avoids complex numerical computations. Further simplification to Log-MAP algorithm was made using 'max' operator and Max-Log-MAP algorithm is obtained. The second algorithm for Turbo decoding called, Soft-Output Viterbi Algorithm (SOVA), has some deprivation in performance with moderate complexity (Aarthi et al. 2020).
This paper proposes optimization based on Correction Factor approach to be applied to a Turbo decoder's extrinsic information. This CF-based optimization reduces the overestimation of reliability values. The work also provides a mathematical relation between CF and SNR. The rest of the paper has been structured as follows: Sect. 2 gives the related works about turbo decoding algorithms. Section 3 describes the proposed Correction factor approach for DOCF- Max-Log-MAP algorithm. Simulation results and analysis of the proposed system has been shown in Sect. 4. Section 5 gives the conclusion of the work.
Related works
Many research works were carried out to improve the performance of Log-MAP, Max-Log-MAP and SOVA algorithms. Among these, SOVA has got much attention because of its widespread applications (Sklar 1997). So, various modifications have been developed and presented. Among different methods used to improve these practical decoding algorithms' performance, correction factor (CF) methods were significant because it is easy to implement and is effective. The traditional SOVA tends to overestimate the reliability values. Hence, the extrinsic information's normalization based on the CF approach was first taken by El Gamal and Hammons (2001). Here the soft output of SOVA is based on the assumption that it is Gaussian distributed. The use of CF on the extrinsic information was shown by Xiang...