| Summary: | 碩士 === 國立臺灣大學 === 電機工程學研究所 === 95 === The channel ideality make it a big challenge in developing wireless communication system. The distortion of received signals may result from nonlinear power amplifier or iter-symbol interference. Besides, the distortion is getting worse due to the limted bandwidth for transmission.
The dissertation is mainly aimed at the compensation from the power amplifier nonlinearity which is one of the nonlinear effects of the channel. The power amplifier pre-distortion is used to compensate for distortion based on the error back-propagation algorithm in neural networks. Two techniques of pre-distortion are proposed. The neural network of first technique includes only one node in input layer; while the neural network of the second technique includes two nodes in input layer. The floating point simulation shows that the performance of the first technique is better than that of the second technique. In hardware implementation, the group signed power-of-two (GSPT) number system is used to reduce hardware complexity in error back-propagation algorithm.
Next, the iter-symbol interference is also considered in the channel. It is necessary to seek appropriate equalizer. In the dissertation, there are two proposed equalizers available. They are multilayer perceptron (MLP) equalizer and Chebyshev equalizer. The floating point simulations of these two equalizer show good performance in compensation from nonlinear distortion. In hardware implementation, GSPT-based error back-propagation algorithm is also applied to MLP equalizer. The simulation results show the proposed methods can combat with distortions, such as power amplifier nonlinearity and inter-symbol interference.
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