Light-Weight AI Enabled Non-Linearity Compensation Leveraging High Order Modulations

The non-linear distortion caused by non-ideal radio frequency (RF) components especially the power amplifier (PA) limits the applications of higher order modulation and degrades power utilization efficiency. To improve the achievable rate in modern systems, it becomes critical to overcome the non-li...

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Bibliographic Details
Published inIEEE transactions on communications Vol. 72; no. 1; p. 1
Main Authors Yu, Bin, Qian, Chen, Lin, Peng, Lee, Juho, Li, Qi, Park, Seungil, Kim, Suhwook, Yoon, Changbae, Hu, Su, Liu, Lingjia
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptation models
Artificial intelligence
Communications systems
Compensation
Distortion
echo state network
higher order modulation
machine learning
Modulation
neural networks
Non-linear distortion
Nonlinear distortion
Nonlinearity
Power amplifiers
Radio frequency
Training
Uplink
Weight reduction
Wireless communication
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Summary:The non-linear distortion caused by non-ideal radio frequency (RF) components especially the power amplifier (PA) limits the applications of higher order modulation and degrades power utilization efficiency. To improve the achievable rate in modern systems, it becomes critical to overcome the non-linear distortion so that we can maximize the opportunity of using higher order modulation such as 256QAM, 1024QAM and even 4096QAM at high transmission power. In this paper, we introduce an artificial intelligence (AI)-enabled non-linearity compensation scheme (AI-NC) to avoid the "model deficit" problem. The introduced AI-NC adapts the Echo State Network (ESN) to enable fast online training without additional training overhead. Furthermore, it is general enough to be used for any types of power amplifiers (PAs) with different non-linearity characteristics and different channel environments. It can also be used for the communication system using multiple antennas and supporting multiple users simultaneously. Simulation results and hardware-based tests show that the proposed AI-NC can drastically improve the link performance and/or coverage of higher order modulations in practice.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2023.3321735