Multi-user Detection Algorithm Based On Immune Clonal Algorithm

With the social progress and development, mobile communication technology has been rapid development. People's work and daily life is more and more convenient because of the step-by-step use of the Third Generation Mobile Communication System. However, with multimedia services and high-speed data services continue to enrich, which requires the new generation of mobile communication system must have higher wireless capacity.Because of Multiple Access Interference (MAI), the CDMA mobile communication systems, which have been used in life, have been limited in performance and capacity. Multi-user detection technology, make use of the MAI as users'information, rather than clear it as noise only, joint detect information with maximizing the use of the correlation between users, effectively inhibited MAI, improve the detection performance of the system, So as to improve performance and capacity of system. Therefore multi-user detection has become one of the key technologies for the CDMA mobile communication system.Artificial Immune System (AIS) is a new intelligent method simulating natural immune system, AIS aims at using ideas gleaned from immunology in order to develop systems capable of performing a wide range of tasks in various research areas such as noise tolerance, self-learning, self-organization and memory, thus having enormous potential supplying novel methods to solve complex problems. AIS has been used in cybernation, data processing, optimization anomaly detection and so on. It is becoming another research hotspot in the artificial intelligent techniques after neural network, fuzzy system and evolutionary computation.Intelligence computation has shown many advantages over conventional optimization algorithm. MUD problem can be viewed as a combinational optimization problem. In this paper, according to clone selection algorithm in artificial immune system, a new algorithm is proposed based on intelligent multi-user detection scheme, Immune Clone Algorithm for Multi-User Detection (CAMUD). Theoretical analysis and simulation experiments showed that CAMUD significantly reduced complexity, had better performance in anti-near-far effect and anti-interference ability, and also had lest effected by the number of users and data length, compared with the best multi-purpose detection (OMD), standard genetic algorithm for multi-user detection (GAMUD) and immune algorithm multi-user detection (IAMUD).It had been validated that the artificial immune system genetic algorithm has better global convergence and faster convergence speed than clone algorithm. This is also the artificial immune system mechanism in the algorithm on a concrete manifestation of superiority.