Research And Simulation Of The Novel Wireless Location Algorithms For Cellular System

An improved immune algorithm is put forward and applied for nonlinear optimization in cellular wireless location. The number of memory base is designed using the 80/20 principle. Then let the memory base compete with the parent population, by which, the search process doesn't shock and speeds up. In this paper, all of our work surrounds the applications of immune algorithm in cellular wireless location.The first part of our paper's work is the basic of the paper. We give the theory and methods of cellular wireless location, and build the mathematical model of location. Then, we introduce a channel model that is used in evaluating performance of location algorithm. The experimental results show that even if the population were not large, the algorithm is robust and can find the coordinates quickly. This part includes chapter 2,3.In the second part of our paper's work, we introduce characteristics and principle of natural immune system, and then put forward a mathematical model of natural immune system. Based on these, an improved immune algorithm is put forward. It has a high accuracy in a bad noise background. This part includes chapter 4.The third part of our paper's work is based on the second part. Two novel algorithms of cellular wireless location are put forward, that's an improved immune algorithm for TDOA-Based Location and a hybrid TDOA/AOA location method based on the improved immune algorithm. It has a high accuracy in a bad noise background. Meanwhile, considering NLOS, we put forward a reducing NLOS's algorithm. The experiment shows that much better location performance can be obtained. This part includes chapter 5,6.The general work of this paper is summarized and the further research direction is pointed out in the last chapter.