Name: Ping Zhao

Title: Associate Professor

Affiliation: School of Electronic Engineering

National Key Laboratory of Antennas and Microwave Technology

Xidian University

Subject: Microwave Engineering

Address: No. 2 Taibai South Road, Xi an, China, 710071

Email: pingzhao@xidian.edu.cn

Tel: (029)88202662

Ping Zhao received B. Sc degree from the School of Electronic Science and Engineering, Nanjing Univerisity, Nanjing, China, in 2012, and the Ph. D. degree from the Department of Electronic Enigineering, Chinese University of Hong Kong, in 2017. From 2017 to 2019, he was a Post-doc Research Fellow in the Department of Electrical Engineering, Ecole Polytechnique de Montreal, Montreal, Canada. In 2020, He joined the National Key Laboratory of Antennas and Microwave Technology, School of Electronic Engineering, Xidian University as an associate professor. His research interests include microwave filter theory, couping matrix synthesis, computer-aided design and tuning techniques, and artificial neural network.

Educational Background：

2012.8 - 2017.8     Department of Electronic Engineering, Chinese University of Hong Kong - Ph. D.

2010.9 - 2011.1     College of Electrical and Computer Engineering, National Chiao Tong University - Visiting Student

2008.9 - 2012.6     School of Electronic Science and Engineering, Nanjing University - B. Sc.

Working Experience：

2020.1 -  now        School of Electronic Engineering, Xidian University - Associate Professor

2017.11 - 2019.8   Department of Electrical Engineering, Ecole Polytechnique de Montreal - Postdoc Research Fellow

1．Coupling Matrix Synthesis for Filters in Advanced Coupling Topologies

A coupling matrix is an important tool in the synthesis and design of high-performance narrowband microwave filters. Since there is a one-to-one correspondence between entries in the coupling matrix and the physical tuning elements, the coupling matrix can be used to guide the design and tuning of filters. Conventional coupling matrix theory assumes all the internal nodes are resonant nodes and all the coupling coefficients are constant. With this assumption, we need to introduce multiple cross-couplings to create transmission zeros, which may lead to complicated coupling topologies. Recently, some new coupling configurations containing frequency-dependent couplings and non-resonant nodes have emerged. The new theory extends the classical coupling matrix theory and provides more flexibility in designing high-performance filters. The study of coupling matrix theory involves the knowledge of microwave networks, complex analysis, and matrix computations. Coupling matrix theory is the foundation of exploring new filter designs and computer-aided tuning techniques.

2．Novel Microwave Filter Design

Microwave and millimeter-wave filters are indispensable components in wireless communication systems. With the fast development of 5G, the wireless industry has imposed new constraints on the performance of filters, including low cost, compact size, and decent insertion loss. This research is deeply rooted in the basic principles of EM fields and aimed at designing competitive new microwave and millimeter-wave filter products.

3．Computer-Aided Tuning Techniques

The electrical performance of microwave filters is extremely sensitive to dimensional errors. Therefore, post-production tuning of filters is necessary for industrial applications. However, the structures of practical filtering devices are often complicated. There are numerous tuning elements in a single device. Tuning the filter based merely on the direct observation of the measurement results is very challenging. This research employs the EM theory, circuit model, and numerical techniques to develop robust computational methods to extract a coupling matrix from measured or simulated S-parameters. This program can be used together with commercial EM simulation software to aid the design of filters. It can also be used with a robot to realize tuning automation.

4．Computer-Aided Design Based on Aritificial Neural Network

An artificial neural network is a high-efficient surrogate model. With sufficient neurons and connections, an artificial neuron network can approximate any complicated multi-input-multi-output functions with arbitrary precision. After an artificial neural network is trained with data, it can provide fast and accurate answers to the problem it has learned. Therefore, artificial neural networks are often used in optimizations and computer-aided designs of RF components. This research aims to develop fast and efficient algorithms for the computer-aided design of microwave filters.

2020 Second Prize in Northwest Division of the "Advanced Communication+" Theme Contest

         Third prize in the final of the "Advanced Communication+" Theme Contest

2016 HKIE Best Transactions Paper Prize

2014 IEEE Hong Kong Section AP/MTT Postgraduate Conference Student Paper Competition Champion

2014 IEEE MTT-S IMS Student Paper Competition Honorable Mention

Undergraduate Courses: Data Structures

Graduate Courses: Design Theory of Microwave Filters

1. Model-Based Vector Fitting [5][8][18] for Filters：Coupling Matrix Extraction by Model-based Vector Fitting v1.0

2. Synthesis of Star-Junction Diplexers [2]：Iterative Diplexer Synthesis v1.0

3. Coupling Matrix Synthesis of Filters With FDCs [10][21]: FDC Filter Synthesis v1.0

[1] Ping Zhao and Ke-Li Wu, “A direct synthesis approach of bandpass filters with extracted-poles,” Proc. Asia-Pacific Microwave Conf., Seoul, Nov. 2013, pp. 25-27.

[2] Ping Zhao and Ke-Li Wu, “An iterative and analytical approach to optimal synthesis of a multiplexer with a star-junction,” IEEE Trans. Microw. Theory Techn., vol.62, no.12, pp.3362-3369, Dec. 2014.

[3] Ping Zhao and Ke-Li Wu, “A new computer-aided tuning scheme for general lossy coupled-resonator bandpass filters based on the Cauchy method,” HKIE Transactions., vol. 23, no.1, pp. 52-62, Mar. 2016.

[4] Ping Zhao, Zhiliang Li, Jianhua Wu, Ke-Li Wu, and Yanan Cui, “A compact wideband UHF helical resonator diplexer,” IEEE MTT-S Int. Microw. Symp. Dig., San Francisco, May 2016.

[5] Ping Zhao and Ke-Li Wu, “Model-based vector-fitting method for circuit model extraction of coupled-resonator diplexer,” IEEE Trans. Microw. Theory Techn., vol.64, no.6, pp.1787-1797, Jun. 2016.

[6] Huan Meng, Ping Zhao, Ke-Li Wu, and Giuseppe Macchiarella “Direct synthesis of complex loaded Chebyshev filters in a complex filtering network,” IEEE Trans. Microw. Theory Techn., vol. 64, no. 12, pp. 4455-4462, Dec. 2016.

[7] Ping Zhao and Ke-Li Wu, “Adaptive computer-aided tuning of coupled-resonator diplexer with wire T-junction,” IEEE Trans. Microw. Theory Techn., vol. 65, no. 10, pp. 3856-3865, Oct. 2017.

[8] Ping Zhao and Ke-Li Wu, “Circuit model extraction of parallel-connected dual-passband coupled-resonator filters,” IEEE Trans. Microw. Theory Techn., vol. 66, no. 2, pp. 822-830, Feb. 2018.

[9] Zhiliang Li, Ping Zhao, and Ke-Li Wu, “An I/O coupling multiplier circuit and its application to wideband filters and diplexers,” IEEE Trans. Compon., Packag., Manuf. Technol., vol. 8, no. 5, pp. 858-866, May 2018.

[10] Ping Zhao and Ke Wu, “Cascading fundamental building blocks with frequency-dependent couplings in microwave filters,” IEEE Trans. Microw. Theory Techn., vol. 67, no. 4, pp. 1432-1440, Apr. 2019.

[11] Ping Zhao and Ke Wu, “Iterative synthesis of equi-ripple dual-band filtering functions with one additional transmission zero,” IEEE MTT-S Int. Microw. Symp., Boston, Jun. 2019, pp. 1351-1354. 

[12] Ping Zhao and Ke Wu, “Homotopy optimization of microwave and millimeter-wave filters based on neural network model,” IEEE Trans. Microw. Theory Techn., vol. 68, no. 4, pp. 1390-1400, Apr. 2020.

[13] Ping Zhao and Ke Wu, “Waveguide filters with central-post resonators,” IEEE Microw. Wireless Compon. Lett., vol. 30, no. 7, pp. 657-660, Jul. 2020.

[14] Minglei Rao, Ping Zhao, and Luyu Zhao, “An adaptive synthesis and design approach of extracted-pole filters,” Proc. Asia-Pacific Microwave Conf., Brisbane, Nov. 2021, pp. 85-87.

[15] Ping Zhao and Minglei Rao, “Design and tuning of extracted-pole filters with non-resonant nodes by circuit model extraction,” IEEE Trans. Microw. Theory Techn., vol. 70, no. 4, pp. 2174-2184, Apr. 2022.

[16] Ping Zhao, “Direct coupling matrix synthesis for filters with cascaded singlets,” IEEE Trans. Microw. Theory Techn., vol. 70, no. 6, pp. 3141-3153, Jun. 2022.

[17] Ping Zhao, “Matrix synthesis for filters with cascaded extracted-pole sections,” IEEE Microw. Wireless Compon. Lett., vol. 32, no. 12, pp. 1383-1386, Dec. 2022. 

[18] Ping Zhao, “Phase de-embedding of narrowband coupled-resonator networks by vector fitting,” IEEE Trans. Microw. Theory Techn., vol. 71, no. 4, pp. 1439-1446, Apr. 2023.

[19] Ping Zhao, “Matrix Synthesis for filters with internal dual extracted-pole sections,” IEEE Trans. Microw. Theory Techn., vol. 71, no. 5, pp. 2139-2149, May 2023.

[20] Ping Zhao and Zhi-Ang Xiong, “Fast synthesis of elliptic prototype filters,” IEEE Microw. Wireless Techn. Lett., vol. 33, no. 8, pp. 1127-1130, Aug. 2023.

[21] Ping Zhao and Ke Wu, “Filters with linear frequency-dependent couplings: matrix synthesis and applications,” IEEE Microw. Mag., vol. 24, no. 9,  pp. 30-45, Sep. 2023.