Abstract:

Particularly under challenging signal environments, identification and mitigation of blocking effects significantly enhance cellular communication performance. Enhancing signal robustness in such environments relies heavily on Direct Sequence Spread Spectrum (DSSS). Current methods do tend to be plagued by dynamic interference and respond inadequately to rapidly varying channel conditions, thus degrading data throughput and increasing error rates. Through the integration of layer-wise real-time interference detection and adaptive filtering techniques to mitigate the impact of blocking, the presented framework, Cross-Layer Interference Analysis and Adaptive Filtering (CLIA-AF), alleviates these limitations. The approach ensures more effective and trustworthy communication by allowing cellular systems to respond dynamically to various interference patterns. The proposed approach is applied in a DSSS-based system to enhance signal reliability and clarity. By reducing interference, increasing data accuracy, and maintaining stable connection in high-interference environments, CLIA-AF obviously improves quality of communication.