Publication Details

Abstract

The received signal strength, or RSS, is a critically important factor in the reliability and effectiveness of radio communication systems. Alterations to signals caused by changes in the transmission of signals in the real world can often influence threshold-based decision-making systems. In order to compare and improve RSS limits, this study shows an approach that may be used with a range of filtering approaches, including the moving average filter, the Kalman filter, and the Gaussian filter. Reducing signal noise, improving threshold accuracy, and making the network more efficient in data transfer, handoff, and connection are all necessary to achieve the goals. The suggested technique enhances the responsiveness and stability of RSS-based evaluations across a range of wireless network circumstances. It is grounded in real-world testing and simulations. The results support the use of adaptive filtering algorithms for reliable data processing and optimal network resource consumption.