首页>
外国专利>
INTEGRATING VOLTERRA SERIES MODEL AND DEEP NEURAL NETWORKS TO EQUALIZE NONLINEAR POWER AMPLIFIERS
INTEGRATING VOLTERRA SERIES MODEL AND DEEP NEURAL NETWORKS TO EQUALIZE NONLINEAR POWER AMPLIFIERS
展开▼
机译:集成Volterra系列模型和深层神经网络以均衡非线性功率放大器
展开▼
页面导航
摘要
著录项
相似文献
摘要
The nonlinearity of power amplifiers (PAs) has been a severe constraint in performance of modern wireless transceivers. This problem is even more challenging for the fifth generation (5G) cellular system since 5G signals have extremely high peak to average power ratio. Nonlinear equalizers that exploit both deep neural networks (DNNs) and Volterra series models are provided to mitigate PA nonlinear distortions. The DNN equalizer architecture consists of multiple convolutional layers. The input features are designed according to the Volterra series model of nonlinear PAs. This enables the DNN equalizer to effectively mitigate nonlinear PA distortions while avoiding over-fitting under limited training data. The non-linear equalizers demonstrate superior performance over conventional nonlinear equalization approaches.
展开▼