Volume 31 Issue 2
Mar.  2022
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YAN Siyuan, YANG Xianzhen, WANG Xiaoru, LI Fu. Predicting the Power Spectrum of Amplified OFDM Signals Using Higher-Order Intercept Points[J]. Chinese Journal of Electronics, 2022, 31(2): 213-219. doi: 10.1049/cje.2020.00.299
Citation: YAN Siyuan, YANG Xianzhen, WANG Xiaoru, LI Fu. Predicting the Power Spectrum of Amplified OFDM Signals Using Higher-Order Intercept Points[J]. Chinese Journal of Electronics, 2022, 31(2): 213-219. doi: 10.1049/cje.2020.00.299

Predicting the Power Spectrum of Amplified OFDM Signals Using Higher-Order Intercept Points

doi: 10.1049/cje.2020.00.299
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  • Author Bio:

    received the B.S. degree in electrical engineering from North University of China (China) in 2012, the M.S. degree in electrical engineering from Stevens Institute of Technology (USA) in 2014, and the Ph.D. degree in electrical and computer engineering at Portland State University (USA) in 2021. His research interests include the signal processing and wireless communications. (Email: syan@pdx.edu)

    received the B.S. degree in electrical engineering from Beijing Jiaotong University (China) in 2014, and the M.S. degree in electrical and computer engineering at Portland State University (USA) in 2018. He is currently pursuing the Ph.D. degree in electrical and computer engineering at Portland State University (USA). His research interests include the wireless communications and signal processing. (Email: xianzhen@pdx.edu)

    received the M.S. and Ph.D. degrees in computer science and technology from the Beijing University of Posts and Telecommunications, in 2001 and 2015, respectively. She was a Visiting Scholar to Portland State University from 2009 to 2010, hosted by Professor LI Fu. She is currently an Associate Professor and a Ph.D. Tutor with the School of Computer Science and Technology, Beijing University of Posts and Telecommunications. She is also the Director of the Big Data Center, Beijing University of Posts and Telecommunications University. Her research interests include image processing and understanding, computer vision, and pattern recognition. (Email: wxr@bupt.edu.cn)

    (corresponding author) received the B.S. and M.S. degrees in physics from Sichuan University (China) in 1982 and 1985, respectively, and the Ph.D. degree in electrical engineering from University of Rhode Island (USA) in 1990. Since then, he has been with Portland State University where he is currently a full professor of Electrical and Computer Engineering. He was an associate editor of the IEEE Transactions on Signal Processing (1993-96) and a column associate editor of the IEEE Signal Processing Magazine (2002). He was the general chair of the 9th IEEE-SP Workshop on Statistical Signal and Array Processing (SSAP-1998). His research interests include signal, image, and video processing, as well as wireless, network, and multimedia communications. He has published over one hundred papers in the refereed journals and international conferences. (Email: lif@pdx.edu)

  • Received Date: 2020-09-15
  • Accepted Date: 2021-10-29
  • Available Online: 2021-11-15
  • Publish Date: 2022-03-05
  • Orthogonal frequency-division multiplexing (OFDM) has been developed into a popular modulation scheme for wireless communication systems, used in applications such as LTE and 5G. In wireless communication systems, nonlinearity caused by radio frequency (RF) amplifiers will generate distortions to both passband and adjacent channels such that the transmission quality is degraded. The study of this article aims to predict the power spectrum for OFDM based signals at the output of an RF amplifier due to the nonlinearity. In this article, based on Taylor polynomial coefficients, a power spectrum expression for amplified OFDM signals in terms of intercept points (up to ${\boldsymbol{n}} $th-order) is derived. This model is useful to RF engineers in choosing and testing RF amplifiers with appropriate specifications, such as intercept points and gain, to meet the requirements of wireless standards. Measurements are carried out to confirm the results of the proposed model.
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