Architecture Framework of High Throughput for the Soft Decision Decoding

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Ernst Huenges
Mohamed K. Hassan


In this research, we examine the Viterbi method for decoding information that has been convolutionally encoded. Using soft-decision and hard-choice decoding algorithms, we examine potential power-saving techniques that might allow receivers to decode convolutionally coded signals with less power usage. The goal of this study is to only employ the Viterbi decoder when the transmitted message contains errors. A straightforward decoder is employed if there are no mistakes. The MATLAB profiler ® tool was used to research the suggested method. A 2 dB performance gain over the identical solution utilising hard-decision decoding is offered by soft-decision decoding. Digital transmission methods need physical media, such as cables, optical fibres, or even radio channel propagation, which cannot be completely trusted and can modify the data being communicated. The design of computer systems and communication systems now includes error-correcting codes for protection and correction.

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Ernst Huenges, & Mohamed K. Hassan. (2022). Architecture Framework of High Throughput for the Soft Decision Decoding. Acta Energetica, (02), 15–20. Retrieved from