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Multiuser Detection Technology Based On Intelligent Optimization Algorithms In CDMA Communication System

Posted on:2006-03-13Degree:MasterType:Thesis
Country:ChinaCandidate:J L ChenFull Text:PDF
GTID:2168360152994258Subject:Computer application technology
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CDMA is a key technology for the third generation (3G) and the future mobile communication system. Compared with other communication systems, CDMA has many important advantages, but it is an interference-limited system, that is, the system will be degraded in performance and limited in capacity because of multiple access interference (MAI), multipath interference and near-far effects in mobile environment. Multiuser detection (MUD) is one of the key technologies for solving the above-mentioned problems. To study how to obtain a multiuser detector which is fast, high-efficient, and easy to realize practically will has important theoretic and realistic meanings.The optimum detector proposed foremost is hardly implemented practically for its exponential-rank computational complexity, so the detectors studied now are all suboptimal ones which have lower computational complexity but good performance close to the optimum one. The suboptimal algorithms can be divided into two classes of linear detection and nonlinear detection. In the dissertation, we mainly studied the nonlinear multiuser detection based on computational intelligence (CI) which is a new hot spot in the suboptimal algorithm study for multiuser detection in recent years. Generally speaking, the main work of the dissertation is as follows:1) We introduced and analyzed the existing multiuser detection technologies and the correlative techniques. Based on CI, we studied the geneticalgorithm (GA) and its application in multiuser detection. This detection method optimizes the objective function step by step and then obtains an optimal solution by simulating nature's evolution procedure. The simulation results show that GA-based multiser detector well performs in resisting MAI and near-far disturbance, however, its computational complexity is much lower than the optimal detector and easy to realize practically, but GA has disadvantage of easily getting into part extremum, so it limits the further improvement of the detector's performance.2) We studied chaos optimization theory. Based on the particular characters of chaos , we designed the chaos-assisted multiuser detector by adding a penalty section to the objective function. Simulation results show that chaos is inferior to GA in overall searching performance because there is blind searching area in chaos model. But because of its ergodicity, chaos has better local searching performance and is easy to jump out of the part extremum.3) Based on the study of the above-mentioned detectors, we proposed anew multiuser detection algorithm--parallel chaos genetic algorithm (PCGA)which combines the advantages of GA and chaos and adopts the parallel searching mechanism with transfer strategy. It applies chaos algorithm to make up GA's disadvantages, that is to say, in every generation of genetic evolution, it can generates better individuals by chaos searching, which makes it not easily get into part extremum, and the parallel searching mechanism further improves the algorithm's efficiency. Simulation results show that our method's performance of resisting the muti-path interference and the near-far disturbance outperforms 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.
Keywords/Search Tags:code division multiple access (CDMA), multiuser detection (MUD), genetic algorithm (GA), chaos optimization algorithm (COA), parallel chaos genetic algorithm (PCGA)
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