A Nonlinear Distortion Removal Based on Deep Neural Network for Underwater Acoustic OFDM Communication with the Mitigation of Peak to Average Power Ratio
【作者】Xuefei Ma，Waleed Raza，Zhiqiang Wu，Muhammad Bilal，Ziqi Zhou，Amir Ali
【作者单位】College of Engineering, Tibet University, Lhasa 850000, China College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001,China Department of Electrical Engineering, School of Engineering and Computers, Wright State University, Dayton, OH 45435-0001, USA College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001,China College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001,China College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001,China
【年份】2020
【卷号】Vol.10 No.4986
【页码】4986
【ISSN】2076-3417
【关键词】Underwater acoustic OFDM communication Machine learning Neural networks Peak to average power ratio Power amplifier Clipping
【摘要】 Machine learning and deep learning algorithms have proved to be a powerful tool for developing data-driven signal processing algorithms for challenging engineering problems. This paper studies the modern machine learning algorithm for modeling nonlin...
