Improving Power Amplifier Performance Based On Digital Pre-distortion Method

With continuous development of the telecommunications industry, high-efficiency linear modulation is widely used in modern wireless communication system, the linearity of the transmitter is proposed ever-increasing demands. Moreover, in order to improve the efficiency, the RF power amplifiers work in close to saturation point. As a result the non-linearity of power amplifier has become very serious, induces intermodlation distortion (IMD) and expansion of spectrum, causes increasing of adjacent channel power ratio (ACPR). It decreases then receiver's bit error rate and causes the adjacent-channel interference. Linearization technology is particularly important to solve the conflict between power efficiency and spectrum efficiency. Among the Linearization technology, the digital baseband pre-distortion has high precision, adaptability, relatively simple to achieve. In this dissertation, we work over of digital pre-distortion technologies which improve performance of power amplifier, major work including:1. Memoryless power amplifier models and several memory power amplifier models e.g. Wiener, Hammerstein, Wiener-Hammerstein, Parallel Wiener and memory polynomial model are analyzed in this dissertation. Because of obtaining the inverse of a nonlinear system with memory is generally a difficult task, indirect learning architecture is used to design the pre-distorter directly. The advantage of this type of approaches is that it eliminates the need for model assumption and parameter estimation of the power amplifier.2. In reality, the performance of pre-distortion can also be affected by the analog imperfections in the transmitter, which are introduced by the analog components, mostly analog filters and quadrature modulators. For a direct up conversion transmitter, we develop a model to describe the frequency-dependent gain/phase imbalance and dc offset. We then develop two methods to construct compensators. These compensation techniques help to correct for the analog imperfections, which in turn improve the overall pre-distortion performance.3. A parameter extraction algorithm of the memory polynomial pre-distorter is proposed in this dissertation. Flowchart of the algorithms is designed, and the method of estimating the computation complexity is proposed.Finally, the memory polynomial pre-distorter's performance in Wiener-Hammerstein and parallel Wiener power amplifier models are simulated. Results of simulation show that the memory polynomial pre-distorter can correct both the nonlinear distortions and the linear frequency response that may exist in the power amplifier. The memory polynomial pre-distorter can increase ACPR of those power amplifiers more than 20dB.