Research Of Multiuser Detection Technology Based On Chaos Genetic Algorithms

The CDMA communication system with the high frequency spectrum operating factor,the big system capacity,the power soft switch with lower radiated,the high signal path transmission rate and so on , represents the new generation mobile communication. It will be act an extremely important role in the future wireless communication system. But in the practical communication the address codes are so hard completely orthogonal that it will exist inevitably serious multiple access interference when the number of the users is bigger and immensely reduce the quality of the communication service. Only adopt the multi-user detection technology,it can real eliminate multiple access interference and improve the capacity of the system of a big drop.MUD problem can be viewed as a combinational optimization problem. The CI optimization strategy is applied to the search process of the MUD. First, in this text it mainly introduced the use of the CDMA communication and reasearched some existing multi-user detection technologies to aim at the traits of the CDMA communication system.By the research of the genetic algorithm,with the trates of treating a large number value mode at the same time, it could great improve the resisting MAI and near-far disturbance,and had lower computational complexity. Second, it studied chaos optimization theory. Because of its ergodicity, chaos has better local searching performance and is easy to jump out of the part extremum. Last, Based on the study of the above-mentioned detectors, according to the differences of the two arithmetic, it proposed a new multi-user detection by combining the two. It applies chaos algorithm to make up GA's disadvantages, that is to say, it can generates better individuals by chaos searching, which makes it not easily get into part extremum. In this text, mixed arithmetic adopted the chaos crossover and the chaos mutation and threw off the repeat steps, which made the system performance have a more obvious improvement than that of the GA-based detector because it synthesizes the stronger overall searching ability of GA and the more effective local searching power of chaos, moreover, it converges much quicker and is easy to realize practically. Simulation results show that this improved mixed algorithm has a good performance and are superior to the tradition detection. And result indicates this detection is effectual and realizable.