Abstract

The project focuses on the development of a tool for identifying and extracting Forward Error Correction (FEC) schemes from unknown demodulated signals. FEC is a vital communication technique that ensures error-free data transmission without the need for retransmission, particularly in satellite communications, digital broadcasting, and deepspace applications. The proposed solution involves using Python to preprocess signals, detect FEC schemes, and then extract the specific coding parameters. Different FEC schemes such as BCH, Convolutional Codes, Turbo Codes, and LDPC codes are explored for their unique characteristics and error correction capabilities. The tool aims to automate the detection and extraction of FEC schemes, thus improving the accuracy and efficiency of signal processing in communication systems.