Research Of Td-Scdma Frequency And Scrambling Code Planning Based On The Data Of Frequency Scanning

TD-SCDMA is the third generation mobile communication system that is firstly proposed by China, with independent intellectual property. According to the operation data in the first three quarters of2012that has been announced by the China Mobile, the number of China Mobile’s TD-SCDMA subscribers has reached75.6million by September30,2012, accounting for37%of China’s3G market. From2007when the trial commercial began up to now, TD-SCDMA has been conducted into the fifth period project. The deployment of China Mobile’s TD-SCDMA base stations has reached228,000by the end of April2012, and the number will be400,000by2014. With the rapid growth of the numbers of users and different traffic, network capacity and quality problems have become more and more prominent. And the solution to these problems is largely dependent on reasonable and effective planning of network’s frequency and scrambling code.This paper mainly studied the method of TD-SCDMA system’s frequency and scrambling code planning, which is based on the TD-SCDMA scrambling code planning research project of my laboratory as well as the TD-SCDMA frequency scrambling code project that I participated in during the one year internship in China Mobile Group Design Institute(CMDI).According to the defects of traditional planning, this paper detailedly analyzes the way of frequency and scrambling planning based on the data of frequency scanning and genetic algorithm. The article starts from the analysis of the compound code correlation, combining with the current network’data and channel allocation rules and fully considering the scrambling code correlation and using probability under different time delay. Then it builds the interference matrix and correlation matrix, and gives the total cost functions of frequency optimization and scrambling code optimization. In order to minimize interference of the whole network, it is necessary to calculate the fitness function continuously and iteratively using genetic algorithm. And finally it output the optimal solution that meets the convergence condition, namely the optimal frequency and scrambling code planning scheme. In order to verify the reliability of the method, this paper takes the actual planning project as a case and gives concrete planning process. At last it makes a detailed comparison of Drive Test index and network management system OMC index, before and after the cutover. Results of the analysis showed that the network performance has been greatly improved after planning.