| Summary: | 博士 === 國立中央大學 === 通訊工程研究所 === 97 === Abstract
The research in this dissertation introduces fuzzy-based and ANFIS-based downlink power control schemes into fixed broadband wireless access (FBWA) systems to provide the system a robust and efficient operation on both clear sky and rainy conditions. Local multipoint distribution services (LMDS) system is a representative of FBWA, operating at millimeter-wave frequencies above 10 GHz, which offers abundant available bandwidth access to multimedia service for the subscriber without demanding the extending of coaxial cable or fiber to the subscriber plant. Intercell interference and rain attenuation are the major factors limiting capacity in LMDS systems and the impacts of these factors on LMDS system are vague, uncertain, and hard to give a crisp mathematical definition. Fuzzy logic control with the advantages of robustness, fault tolerance, and adaptability can deal with the uncertain problem. Neural network has the significant self-adapting, self-learning and anti-noise characteristics, in which a desired input-output mapping can be obtained by learning a lot of training data. Moreover, the ANFIS system integrates neural network into fuzzy inference system can automatically learn a proper network structure and a set of parameters, simultaneously. Hence, we propose fuzzy-based and ANFIS-based power control schemes, in which fuzzy logic control and ANFIS are employed to evaluate the channel quality by using the environment factors to be as the input variables, and then channel quality is applied to adjust the power control region. Presented and analyzed are fuzzy-based and ANFIS-based downlink power control schemes to show that the proposed power control schemes are appropriate for improving the performance of CDMA-based LMDS systems and can provide the system a robust and efficient operation both on clear sky and rainy conditions.
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