Immune optimization algorithm for solving joint call admission control problem in next-generation wireless network
The integration of radio access networks with different radio access technologies (RATs) is one of the remarkable characteristics of the next-generation wireless networks (NGWNs). In NGWN, the users with multi-network interface terminals should be able to select independently radio access network to obtain the best service. Therefore, joint call admission control (JCAC) schemes are required to select the most appropriate radio access network (RAN) for incoming calls. We propose an immune algorithm-based JCAC (IA-JCAC) scheme with users centric in order to enhance user's satisfaction. However, JCAC algorithms with users centric can lead to highly unbalanced traffic load among the available RANs in NGWN because users act independently, and most of them may prefer to be connected through a particular RAN. Highly unbalanced traffic load in NGWN will result in high overall call blocking/dropping probability and poor radio result utilization. To solve this problem, we employ dynamic pricing for balancing traffic load among available RANs in heterogeneous wireless networks where users' preferences are considered in decision-making on RAT selection. The proposed IA-based JCAC scheme is compared with another scheme that does not use the dynamic pricing on the performance. The simulation result shows the effectiveness of the proposed IA-JCAC scheme is improved significantly.
immune optimization algorithm joint call admission control next-generation wireless network dynamic pricing load balance user's preference