Zhaorui WANG 王兆瑞
Research Assistant Professor
School of Science and Engineering
The Chinese University of Hong Kong, Shenzhen
Office: CD 501, CUHKSZ
E-mails: wangzhaorui [at] cuhk.edu.cn, zrwang2009 [at] gmail.com
Dr. Zhaorui WANG received the Ph.D. degree in Information Engineering from The Chinese University of Hong Kong (CUHK) in 2019, supervised by Prof. Soung-Chang LIEW, and the B.S. degree from University of Electronic Science and Technology of China (UESTC) in 2015. He was a Postdoctoral Research Associate at The Hong Kong Polytechnic University from 2019 to 2020, and a Postdoctoral Research Associate at CUHK from 2021 to 2022. He was a visiting scholar at Shenzhen University and at State Key Laboratory of Scientific and Engineering Computing (LSEC), Chinese Academy of Sciences, from 2020 to 2021. He is a recipient of the Hong Kong PhD Fellowship from 2015 to 2018.
Note: I have moved to CUHK-Shenzhen as a Research Asssitant Professor. Please click HERE for my new website.
- Intelligent Reflecting Surface (IRS) Assisted Communications
- Massive Machine Type Communications
- Physical-Layer Network Coding (PNC)
- Rui WANGPh.D. Student at PolyU
Research Topic: Intelligent Reflecting Surface Assisted Communications
Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis
(ESI Hot Paper, ESI Highly Cited Paper)
Z. Wang, L. Liu, and S. Cui
IEEE Transactions on Wireless Communications (TWC), 2020arXivIEEEE XploreCode
In intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information (CSI) is a crucial impediment for achieving the beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-assisted communications, KMN+KM channel coefficients should be estimated, where K, N, and M denote the numbers of users, IRS reflecting elements, and antennas at the BS, respectively. In this paper, we argue that since the BS-IRS channels are common channels among users, the number of channel coefficients being estimated can be reduced greatly by exploiting this special channel structure. Building on this observation, we propose a three-phase channel estimation framework for IRS-assisted uplink multiuser communications. Under this framework, we analytically prove that a time duration consisting of K+N+max(K−1,⌈(K−1)N/M⌉) pilot symbols is sufficient for the BS to recover all the channel coefficients.
PNC Enabled IIoT: A General Framework for Channel-Coded Asymmetric Physical-Layer Network Coding
(Funded by Huawei for PNC 5G Standardization in 3GPP)
Z. Wang, L. Liu, S. Zhang, P. Dong, Q. Yang, and T. Wang
IEEE Transactions on Wireless Communications (TWC)arXivIEEEE Xplore
This paper investigates a two-way relay channel operated with PNC between a controller and a robot. We particularly focus on a scenario
where 1) the controller has more information to transmit than the robot; 2) the channel of the controller is stronger than that of
the robot, and both users have nearly the same transmit power. To reduce the communication latency, we put forth an asymmetric PNC transmission
scheme in which the controller transmits more information than the robot by exploiting its stronger channel gain. However,
the current channel-coded PNC requires the two users to transmit the same amount of source information in order to preserve the linearity of
the two users’ channel codes at the relay for successful decoding. To fill this gap, we propose a lattice-based encoding and modulation scheme. Our design is versatile on that the controller and the robot
can freely choose their modulation orders based on their channel power, and the design is applicable for arbitrary channel codes,
not just for one particular channel code.
Noncoherent Detection for Physical-Layer Network Coding
Z. Wang, S. C. Liew, and L. Lu
IEEE Transactions on Wireless Communications (TWC), 2018arXivIEEEE Xplore
This paper investigates noncoherent detection in a two-way relay channel operated with PNC.
For noncoherent detection, the detector has access to the
magnitude but not the phase of the received signal. For conventional communication in which a receiver receives the
signal from a transmitter only, the phase does not affect the magnitude, hence the performance of the noncoherent detector
is independent of the phase. PNC, however, is a multiuser system in which a receiver receives signals from multiple
transmitters simultaneously. The relative phase of the signals from different transmitters affects the received signal
magnitude through constructive-destructive interference. In particular, for good performance, the noncoherent detector
in PNC must take into account the influence of the relative phase on the signal magnitude. Building on this observation,
this paper delves into the fundamentals of PNC noncoherent detector design. To avoid excessive overhead, we do away from
preambles. We show how the relative phase can be deduced directly from the magnitudes of the received data symbols.
- [08/2022] I joined CUHK-Shenzhen as a Rsearch Assistant Professor.
- [07/2021] Our paper "Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis" published in the IEEE Transactions on Wireless Communications in Oct., 2020, has been listed as an ESI highly cited paper.
- [04/2021] Our paper "Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis" published in the IEEE Transactions on Wireless Communications in Oct., 2020, has been listed as an ESI hot paper (top 0.1% by citations for the field and age). More information can be found at here.
- [06/2020] We have released our Matlab codes of the paper "Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis". If you have any questions or find any bugs, please drop me an email.