Linearity-Enhanced Doherty Power Amplifier Using Output Combining Network With Predefined AM–PM Characteristics

线性 放大器 邻道 邻道功率比 电子工程 dBc公司 电气工程 调幅 预失真 阻抗匹配 CMOS芯片 电阻抗 工程类 频率调制 无线电频率
作者
Xiaohu Fang,Arthur Chung,Slim Boumaiza
出处
期刊:IEEE Transactions on Microwave Theory and Techniques [IEEE Microwave Theory and Techniques Society]
卷期号:67 (1): 195-204 被引量:55
标识
DOI:10.1109/tmtt.2018.2870830
摘要

In this paper, a new method is proposed to synthesize a linearity-enhanced Doherty power amplifier (DPA) without deteriorating its efficiency. This method determines the combiner network parameters so that a predefined amplitude-to-phase (AM-PM) characteristic is produced while maintaining proper load modulation and consequently good back-off efficiency. The predefined AM-PM characteristic is chosen to be the inverse of the main transistor to enhance the overall DPA linearity. For proof-of-concept validation purposes, a linearity-enhanced DPA circuit prototype is designed to provide linear overall AM-PM characteristics over the frequency band of 4.7-5.3 GHz. Meanwhile, its input matching network is designed to minimize the amplitude-to-amplitude (AM-AM) distortion by properly selecting the source impedances. The measurement results of the DPA prototype under continuous-wave stimuli reveal AM-PM and AM-AM characteristics with maximum phase and gain compression/expansion below ±1° and ±0.25 dB, respectively, when the input power level is swept up to a saturation level of 39 dBm over 4.9-5.3 GHz. Furthermore, when driven with carrier aggregated signals with modulation bandwidths of up to 160 MHz and a peak-to-average power ratio equal to 7.4 dB, the DPA prototype maintains an adjacent channel leakage ratio of better than -40 dBc with a drain efficiency in the excess of 40% and an average output power of 32 dBm, without resorting to any additional linearization schemes. The proposed DPA methodology paves the road for the application of the DPA technique to 5G massive multiple-input and multiple-output transmitters with relaxed linearity requirements as it avoids the extra complexity and power consumption overhead associated with dedicated linearization schemes.

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