An Efficient Dynamic Orthogonal Variable Spreading Factor Code Allocation Approach in WCDMA through Modified Adaptive Genetic Algorithm

Orthogonal Variable Spreading Factor (OVSF) codes would give variable data rate transmissions for different bandwidth supplies in Wideband CDMA (WCDMA) networks. These OVSF codes are used for the channelization of codes in WCDMA. In WCDMA, effective utilization of OVSF codes has become an active area of research as the number of codes is very limited. It is a fact that the successor and predecessor codes of OVSF cannot be used simultaneously when a specific code is used in OVSF as their encoded sequences become indistinguishable. Consequently, OVSF code tree has inadequate number of available codes. Thus, this research study uses Adaptive Genetic Algorithm (AGA) based approach for dynamic OVSF code assignment in WCDMA networks. Different from existing Conventional Code Assignment (CCA) and dynamic code assignment schemes, population is adaptively constructed according to existing traffic density in the OVSF code-tree. In existing technique in order to improve the ability of the GA, ‘‘dominance and diploidy’’ structure is employed to adapt to changing traffic conditions. Because in SGA algorithm cannot convergence if the new user is included into the existing OVSF code tree while SGA is running to find optimum OVSF code tree, SGA cannot adapt its structure to this unexpected variation. This problem can be overcome by the Modified Adaptive Genetic Algorithm (MAGA). Performance of the proposed MAGA approach is evaluated in terms of blocking probability and spectral efficiency and is compared with SGA, D&D GA.