Multi-user Detection Techniques Based On Dna Computing And Genetic Algorithms

DNA computing is a new computing model. Compared to the traditional electronic computer, DNA computer has more advantages such as high degree of parallelism, computing speed and storage capacity, and low consumption with rich DNA molecules resource. In some areas it is expected to make up the deficiencies of the existing computer. Genetic algorithm (GA) is a natural mimic biological evolution of the random global search and optimization method. It draws on Darwinism and Mendelism and its nature is a highly efficient, parallel, global search method. Genetic Algorithm and DNA computing have natural similarities, but achieve in different ways.As the multiple access program of the 3^rd generation mobile systems, code-division multiple access (CDMA), which is a multiple access technology, is based on orthogonal codes, correlation receiver theory and spread-spectrum communication technology. Because of the random access of different users, it is difficult to create completely orthogonal spreading codes. CDMA system inevitably has multiple access interference (MAI). Multi-user detection (MUD) is one of the key techniques of CDMA system. Based on the conventional detection (CD), MUD makes full use of the signal information of all users for joint detection to effectively inhibit MAI, eliminate or mitigate "near-far" effect, improve system performance and increase system capacity.This thesis firstly introduces the concept of DNA computing to MUD technology. The integration of DNA computing and the traditional genetic algorithm is applied to solve the combinatorial optimization problems of MUD. The discussion is focused on the DNA coding and the fitness function selection. Then, DNA computing and micro-genetic algorithm (μGA) are also combined to solve MUD problem. DNA-μGA is improved aiming at the number of the individuals in the DNA population. Finally, the idea of memetic is brought into DNA-μGA. And a new local optimization strategy based on the user ID priority and DNA mutation is proposed and used to optimize a DNA-μGA multi-user detector which has only 2 individuals in its initial population. Through computer simulation analysis, the feasibility of solving MUD problem using DNA computing is verified. Compared with CD, decorrelating detector (DEC), optimal detector (OD), the DNA-μGA detector with memetic strategy is proved to have better performances. This thesis provides a new route of development of CDMA MUD.