Efficient Low-Complexity Encoding and Decoding Algorithms for Global Navigation Satellite Systems

Global Navigation Satellite Systems (GNSS) are a crucial technology that provides accurate Positioning, Navigation, and Timing (PNT) data, which is significantly important in various applications such as aviation, autonomous vehicles, and smart transportation, among others. Concerning limitations of current GNSS implementations include the computational complexities in the encoding and decoding processes. Conventional methods, such as Forward Error Correction (FEC) and Turbo Codes (TC), require significant computational resources, leading to inefficiencies such as increased power consumption and longer processing times, particularly in real-time applications. These issues limit GNSS performance, especially in systems that need fast and accurate data transmission. This study addresses these challenges by proposing an Efficient, Low-Complexity Encoding and Decoding Algorithm (ELCEDA) to decrease computational burden without compromising data accuracy. ELCEDA uses advanced techniques, such as LDPC and SDA, to optimize signal processing. The proposed approach yields enhanced results, reducing the computation time by 0.30%, decreasing the power consumption by 0.25%, and even reducing the error rate to 0.15%, ensuring reliable PNT data. These features make ELCEDA a promising solution to improve the efficiency and effectiveness of GNSS in modern technological applications, particularly in mobile and battery-powered devices.