Enhanced Reed-Solomon Error Correction Framework for Reliable Data Transmission in Noisy Communication Systems

In modern communication systems, reliable data transmission in noisy, and interference environments is a tough problem. However, conventional error control techniques, like Reed-Solomon (RS) codes, often fail to achieve performance under high dimensional noise and burst errors. To overcome these limitations, this study presents a new framework that incorporates advanced optimization algorithms and adaptive error correction techniques, to extend the RS method. The improved RS encoding scheme starts with multi-layered encoding, adaptive symbol interleaving, and list decoding to increase resilience against severe noise. We use a multi-verse optimizer (MVO) for global exploration and a differential evolution with adaptive chaos (DEAC) algorithm for local refinement of the system parameters to optimize the system parameters. The hybrid optimization approach proposed here achieves an appropriate trade-off between exploration and exploitation, avoiding local optima risk and enhancing convergence. Turbo-enhanced Reed-Soloman decoding is realized with the optimized parameters to decode corrupted data in a challenging communication environment. On multiple noisy transmission scenarios, the proposed framework was found to outperform conventional RS methods and hybrid error correction schemes. Experimental results show that the proposed approach reduces bit error rate (BER) by 30% and decoding latency by 25% versus baseline methods. In addition, the system demonstrated higher throughput and more robust error correction in the presence of varying noise levels. Finally, a highly efficient and reliable error correction solution in modern communication systems is achieved by integrating MVO and DEAC with the improved RS method for parameter optimization.