Enhancing quality of service in wireless systems using iterative weighted least squares with fuzzy logic integration algorithm

Effective quality of service (QoS) management is essential to the smooth running of wireless networks and to guarantee peak performance. This study suggests a unique method for enhancing QoS in wireless networks that combines fuzzy logic with iterative weighted least squares (IWLS). Performance of the system is anticipated to be improved by dynamically modifying system settings depending on network input. When handling the uncertainties and imprecisions present in wireless contexts, fuzzy logic is used, allowing for adaptive decision-making depending on the state of the network. By adding network input, IWLS is also used to repeatedly adjust system parameters. To further improve QoS performance, an adaptive neural fuzzy iterative weighted least squares (ANFIWLS) method is presented. Fuzzy logic, neural networks, and IWLS work together to provide more precise inference and decision-making skills. According to a comparison, ANFIWLS beats fuzzy logic alone, resulting in a QoS increase of around 32.8%. This gain is most noticeable in settings with moderate loss rate, low jitter, medium latency, and high throughput. Fuzzy logic is used with ANFIWLS and IWLS to allow for the adaptive modification of QoS parameters in wireless networks, improving user experience and system performance as a whole. The results of this research aid in the creation of QoS management systems for wireless communication networks that are more dependable and efficient.

Automated summary

This study proposes a method that combines fuzzy logic, neural networks, and IWLS to enhance QoS performance in wireless networks. By dynamically modifying system settings and adjusting parameters, the system improves network performance. The addition of ANFIWLS to fuzzy logic provides more precise inference and decision-making capabilities, resulting in a 32.8% increase in QoS. The results of this research contribute to the development of more dependable and efficient QoS management systems for wireless communication networks.