Transformer-Based Predistortion Linearizer for High Linearity and High Modulation Efficiency in mm-Wave 5G CMOS Power Amplifiers

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Abstract

This paper presents a new predistortion linearization technique for high linearity and high modulation efficiency in millimeter-wave (mm-wave) CMOS power amplifiers (PA) for fifth-generation (5G) mobile communications. Our proposed linearizer adopts a transformer-based (i.e., inductive) self-compensated predistortion network at the input of the PA whose amplitude-modulation to phase-modulation (AM-PM) response is opposite compared with the AM-PM response of a CMOS PA, resulting in an AM-PM cancellation effect. This proposed inductive linearization method mitigates the large gain reduction problem in traditional capacitor-based linearization approaches while consuming no extra dc power or without introducing additional control circuitry. As a result, a significant improvement in power-efficiency and linearity is achieved with high-order complex modulation signals. To validate the proposed linearization method, a PA prototype in 65-nm CMOS technology was fabricated and tested, and it exhibited <1° of \vert AM-PM \vert distortion at P-{\mathrm {o,1\, dB}} over 4 GHz of bandwidth (27-31 GHz). At 28 GHz, the measured saturated P-{\mathrm {o}} and peak power-added-efficiency (PAE) was 15.6 dBm and 41%, respectively, while achieving a 6-dB P-{\mathrm {o}} back-off PAE of 25%. To assess PA's large-signal performance for 5G communications, the prototype was measured with the 64-quadratic-amplitude modulation (QAM) signal at 2-Gb/s data rates at 28 and 30 GHz, and the PA achieves modulated-PAE of 18.2%/17.6% and average- P-{\mathrm {o}} of 9.8 dBm/10 dBm, respectively, while maintaining

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APA

Ali, S. N., Agarwal, P., Gopal, S., & Heo, D. (2019). Transformer-Based Predistortion Linearizer for High Linearity and High Modulation Efficiency in mm-Wave 5G CMOS Power Amplifiers. IEEE Transactions on Microwave Theory and Techniques, 67(7), 3074–3087. https://doi.org/10.1109/TMTT.2019.2914900

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