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Neural network based efficiency optimization method for RF Power Amplifiers with controllable power supply

机译:基于神经网络的电源可控射频功率放大器效率优化方法

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Rising energy consumption and thus equipment operating cost as well as the parallel environmental need to reduce the carbon footprint is a very important issue in mobile radio networks. Beside the needs to reduce the energy consumption, the demand for bandwidth and network capacity is increasing and leading to more standards, frequency bands and applications. The RF transceiver, especially the Power Amplifier as a part of it, is one of the bottlenecks and setscrews for the requirements mentioned. The following paper presents a standard and frequency independent concept as well as a method for energy efficiency optimization of RF Power Amplifiers with voltage controllable power supply to adjust the operating point based on Neural Networks. The system is basically standard independent and can adapt itself to a certain standard with its requirements. The system was designed and simulated.
机译:在移动无线电网络中,不断增加的能耗以及由此带来的设备运行成本以及减少碳足迹的并行环境需求是一个非常重要的问题。除了减少能耗的需求之外,对带宽和网络容量的需求也在增加,并导致更多的标准,频带和应用。 RF收发器,特别是功率放大器的一部分,是满足上述要求的瓶颈和固定螺丝之一。以下论文介绍了一种基于神经网络的标准和频率无关的概念,以及一种采用电压可控电源来调节工作点的射频功率放大器的能效优化方法。该系统基本上是独立于标准的,并且可以根据要求适应特定的标准。该系统经过设计和仿真。

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