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Yan Guo

Researcher at University College Dublin

Publications -  13
Citations -  341

Yan Guo is an academic researcher from University College Dublin. The author has contributed to research in topics: Amplifier & RF power amplifier. The author has an hindex of 7, co-authored 11 publications receiving 224 citations.

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Journal ArticleDOI

Highly Efficient Broadband Continuous Inverse Class-F Power Amplifier Design Using Modified Elliptic Low-Pass Filtering Matching Network

TL;DR: In this paper, a modified elliptic low-pass filtering (LPF) matching network (MN) was proposed to provide a sharp impedance transition from the higher end of the fundamental frequency band to the lower end of second harmonic band.
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A Broadband High-Efficiency Doherty Power Amplifier With Integrated Compensating Reactance

TL;DR: In this paper, a gallium nitride Doherty power amplifier (DPA) using an integrated compensating reactance (CR) for broadband operation is presented, where an additional quarterwavelength transmission line is integrated in the peaking amplifier output to compensate the load impedance of the carrier amplifier in the low power region and thus enhance the backoff efficiency over a wide frequency range without affecting the Doherty load modulation at saturation.
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Power Adaptive Digital Predistortion for Wideband RF Power Amplifiers With Dynamic Power Transmission

TL;DR: In this article, a power adaptive digital predistortion (DPD) technique is proposed to reduce the power consumption of wireless transmitters, where the transmission power level of RF power amplifiers (PAs) dynamically change according to real-time data traffic.
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Digital Compensation for Transmitter Leakage in Non-Contiguous Carrier Aggregation Applications With FPGA Implementation

TL;DR: Experimental results demonstrated that excellent suppression performance can be achieved with very low implementation complexity by employing the proposed GDES distortion model structure.
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Output-Controllable Partial Inverse Digital Predistortion for RF Power Amplifiers

TL;DR: The proposed approach largely expands the capability of DPD and thus provides more flexibility for system designers to effectively use DPD to manipulate the PA output in order to handle more application scenarios and objectively conduct further system optimization.