摘要
在传统无线通信系统中,射频功率放大器的非线性是信号失真与频谱再生的主要原因。目前正在大规模建设的第五代移动通信系统(俗称5G)具有非常宽的调制带宽和非常高的调制度,使功放的非线性失真变得更加严重。因此,宽带功率放大器的线性化问题成为了5G通信系统的研究重点。本文针对5G功放的非线性,分别采用动态偏差减少(Dynamic deviation reduction,DDR)模型、记忆多项式(Memory Polynomial,MP)模型和广义记忆多项式(Generalized Memory Polynomial,GMP)模型对5G宽带射频功放建立数字预失真器。最后,使用100MHz带宽的5G-NR信号,对中心频率3.5GHz的AB类功放进行预失真线性化实验验证。实验结果表明DDR、MP以及GMP三个数字预失真模型均能对5G功放进行线性化,而且被测功放的相邻信道功率比(ACPR)改善最高可达12dB。DDR、MP和GMP数字预失真器对5G功放的非线性具有显著的抑制作用,因此以上三个模型均可应用于5G功放的线性化。
In the traditional wireless communication system,the nonlinearity of the radio frequency power amplifier(RF PA)is the main reason of the signal distortion and the spectrum regeneration.The fifth-generation mobile communication system(5 G)is constructed on a large scale with very wide modulation bandwidth and very high modulation system,which makes the nonlinear distortion of RF PAs more serious.Therefore,the linearization of RF PAs becomes the focus of the 5 G communication system.Aiming at the nonlinearity of the 5 G RF PA,this paper uses the dynamic deviation reduction(DDR),the memory polynomial(MP),and the generalized memory polynomial(GMP)models to build digital predistorters(DPD)for the 5 G broadband RF PAs.Finally,the DPD linearization experiment is carried out on a class AB PA with a center frequency of 3.5 GHz and a 5 G-NR signal with 100 MHz bandwidth.The experimental results show that the DDR,MP,and GMP can linearize the 5 G RF PA,and the ACPR of the PA under the test can be improved by over 12 dB.The DDR,MP,and GMP DPDs can significantly suppress the nonlinearity of the 5 G PA under the test,so the above three models can be applied to the linearization of the 5 G RF PAs.
作者
詹军
许高明
ZHAN Jun;XU Gao-ming(Faculty of Electrical Engineering and Computer Science,Ningbo University,Ningbo 315211,China;State Key Laboratory of Millimeter Waves,Nanjing 210096,China)
出处
《无线通信技术》
2020年第3期1-6,共6页
Wireless Communication Technology
基金
国家自然科学基金联合基金(U1809203)
浙江省省属高校基本科研业务费专项资金资助(SJLY2020013)
关键词
5G
功率放大器
非线性
数字预失真
5G
power amplifier
nonlinearity
digital predistortion