Hierarchical Genetic Algorithm For Dynamic Channel Units Allocation in TD-CDMA/TDD System

摘要

Hierarchical Genetic Algorithms (HGA) as a tool for search and optimizing methodology have now reached a mature stage. The minimum resource facility to carry user traffic, termed a channel unit (CU), is composed of a one time-slot and one code in the TD-CDMA/TDD system. The control of the number of CUs depends on the traffic load solves varied and asymmetrical traffic problems in the 3G system. In a cellular network, the call arrival rate, call duration and the communication overhead between the base stations and the control center are vague and uncertain, regardless of whether the criteria of concern are nonlinear, constrained, discrete or NP hard. In this paper, the HGA is used to tackle the neural network (NN) topology as well as the fuzzy logic controller for the dynamic CU allocation scheme in wireless cellular networks. Therefore, we propose a new efficient HGA CUs Allocation (HGACA) in cellular networks. It aims to efficiently satisfy the diverse quality-of-service (QoS) requirements of multimedia traffic. The results show our algorithm has a lower blocking rate, lower dropping rate, less update overhead, and shorter channel-acquisition delay than previous methods.