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

Patrick Jüschke, A. Pascht, G. Fischer
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Abstract

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.
基于神经网络的可控电源射频功率放大器效率优化方法
在移动无线网络中,不断上升的能源消耗和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。除了降低能耗的需求外,对带宽和网络容量的需求也在增加,从而导致了更多的标准、频带和应用。射频收发器,特别是作为其一部分的功率放大器,是上述要求的瓶颈和固定因素之一。本文提出了一种基于神经网络的电压可控电源射频功率放大器工作点调整能效优化的标准、频率无关概念和方法。该系统基本上是标准独立的,可以根据自己的要求适应某一标准。对系统进行了设计和仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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