This paper outlines our approach to solving the amplitude modulation-to-amplitude modulation (AM-AM), and amplitude modulation-to-phase modulation (AM-PM) distortions caused by the onboard high-power amplifier (HPA) operating at the saturation point. The approach employs machine learning and artificial intelligence (ML-AI) to predistort the input signal such that the output of the post-HPA pre-distorted signal is identical to the original. The proposed ML-AI approach utilizes an existing MATLAB reinforcement learning technique using Deep Deterministic Policy Gradient (DDPG). The bulk of the research was to incorporate the proposed DDPG pre-distorter into the newly developed GNSS Single Side Band-Multi-Carrier Broadband Waveforms (SSB-MCBBW) and tune the pre-distorter’s hyper-parameters. The fine-tuning process was achieved efficiently by utilizing the parallel computing offered by a computer cluster at California State University Fullerton (CSUF) and has produced promising results in our simulated environment. The performance results of the proposed ML-AI pre-distorter using MATLAB DDPG algorithm are compared with the ideal pre-distorter for various HPA input back-off power (IPBO).
In satellite communication (SATCOM) system, a simple “bent-pipe” transponder is widely adopted to convert uplink carrier frequencies to downlink carrier frequencies for transmission of information without having on-board processing capability. The transponders are equipped with high power amplifiers (HPAs), which like other amplifier modules in communication systems, cause nonlinear distortions to transmitted signals, when HPAs are operated at or close to their saturation points to maximize power efficiency. These nonlinearities can be characterized as amplitude modulation-toamplitude modulation (AM-AM), and amplitude modulation-to-phase modulation (AM-PM) effects, which degrade the transmission performance of the system. Therefore, additional processing techniques such as predistortion (PD) has applied to maximize the transponder throughput along with the HPA power efficiency. In this paper, we first propose an accurate HPA modelling method, which leads to an outstanding agreement with the measured HPA AM-AM and AM-PM characteristics data. Then, a close-form PD is derived with respect to the power and phase compensation for the corresponding output signals of HPA. Finally, simulation results are provided to evaluate and verify the bit error rate (BER) improvement for the considered SATCOM system by applying our proposed PD technique.
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