Research on multi-connection network selection algorithm based on SACM-FA

The proposed algorithm in this paper is called the Step-Adaptive Firefly Algorithm (SAFA), which is based on the Cubic Chaotic Mapping and SACM-FA. This algorithm combines the firefly algorithm with chaotic optimization theory. It utilizes chaotic sequences to randomly generate initial positions for fireflies, ensuring the randomness of initial individuals. It also introduces an adaptive search step to enhance the diversity of the population. The algorithm performs optimization operations while satisfying the QoS guarantees of users and obtains the optimal allocation of wireless resources through multiple iterations. The SACM-FA algorithm optimizes bandwidth allocation and power control problems in the uplink environment of ELWA (Enhanced Land Mobile Wireless Access) systems with multiple coexisting service types. It improves user utility and satisfaction. The simulation results demonstrate that the SACM-FA algorithm can improve the throughput of wireless systems and effectively enhance network performance in ELWA systems with multiple coexisting service types. Compared to traditional network selection algorithms, the improved algorithm can effectively balance network load and significantly improve user satisfaction.