Research On Digital Signal Processing Techniques At Transmitter In High Speed Data Transmission System Of DRSS

Data Relay Satellite System (DRSS) is a promising research area in the field of spaceflight thanks to its near-world wide coverage, large capacity and agile controllability. High speed data transmission of the satellite communication in the backward channel is one major service of DRSS. There are many signal processing problems such as high speed operation, a great quantity of computation at the transmitter of high speed data transmission system. And nonideal factors in RF equipments may cause wide-band signal distortion, spectrum spead and system performance degradation. To solve these problems, the key techniques such as high speed pulse shaping filter, predistortion of wide-band I/Q modulator mismatch and adaptive predistortion of High Power Amplifier(HPA) are mainly researched in this thesis.Firstly, the design and implementation of high speed pulse shaping filter is investigated. The filter's parameters are well-chosen based on bit error rate(BER) performance and realization possibility. The filter is implemented using look-up tables in FPGA, and realized I/Q auto-synchronization with the filter's polyphase structure.Secondly, the predistortion technique of wide-band I/Q mismatch is investigated. The I/Q mismatch model for wide-band I/Q modulator is studied and a measure method is given. The performances of TCM-8PSK such as signal constellation and BER are analyzed in the situation of I/Q mismatch. One predistortion technique is realized in FPGA by modifing the coefficients of pulse shaping filter, which saves some handware resources.Thirdly, the nonlinearity with memory effects and the linearization techniques of HPA are inverstigated. An extended Volterra-Wiener model based on parallel filters bank is proposed after considering various nonlinearity models. The performances of TCM-8PSK such as signal constellation, power spectrum density(PSD) and BER are analyzed in the situation of nonlinearity with memory effects. The usual HPA linearization techniques are introduced, and comparing their principles, advantages and disadvantages.Finally, the adaptive predistortion techniques of HPA in baseband are inverstigated. The adaptive predistorted algorithms based on Volterra and extended Volterra-Wiener are deduced and simulated. The simulation results show that the convergence speeds of the two algorithms are slow. The Discrete Wavelet Transform(DWT) is proposed to use in the predistortion model to reduce the correlation of input sequences. The simulation results show that DWT can make the convergence speed faster. An adaptive predistorted algorithm based on Discrete Wavelet Neural Network(DWNN) is proposed for strong nonlinear HPA, which makes use of the learning and approaching capabilities of neural network. The simulation results show that the DWNN method can make the convergence speed faster, reduce the computation complexity and improve the linearization performance when compared to the RBF method.