Yuyang Wang Email: yuywang AT utexas DOT edu
I was born in the summer of 1994 in Jiangsu, China. I received my B.S. degree in 2015 from Southeast University, Nanjing, China. During my undergraduate study, I was supervised by Prof. Shi Jin and my research was on the performance analysis of D2D communication with antenna selection. In 2015, I joined WNCG and WSIL in the University of Texas at Austin. I received my M.S.E. degree in 2017 and am pursuing my Ph.D. degree supervised by Prof. Robert W. Heath Jr. My research lies in the broad area of "Connected Vehicles". I am interested in the system level simulation of mmWave V2I and the values brought by wireless infrastructures in avoiding potential collisions.
My recent research interest is more about how to implement mmWave V2I in real fields. Still faced with great challenges, mmWave is vulnerable in highly mobile vehicular contexts. I am now leveraging machine learning tools to break the bottleneck of implementation issues of mmWave V2X. Driven by data, the system is shown to be more efficient and robust.
Vehicular beam alignment using deep learning leveraging channel structures [J7]
Online mmWave vehicular sensing codebook learning [J6]
MmWave vehicular beam training with situational awareness [J5] [C10] [C8] [C7] [C6]
Analysis of mmWave vehicle-to-infrastructure (V2I) performance in urban microcellular networks [J3] [C5] [C4]
Antenna selection for device-to-device (D2D) communication underlaying cellular networks
[J1] [J2] [J4] [C2] [C3]
1. [J7] Y. Wang, Nitin Jonathan Myers, Nuria Gonzalez-Prelcic, and Robert W. Heath Jr., "Deep Learning-based Beam Alignment in MmWave Vehicular Communication", in preparation for submission, July 2020
2. [J6] Y. Wang, Nitin Jonathan Myers, Nuria Gonzalez-Prelcic, and Robert W. Heath Jr., "Site-specific online compressive beam codebook learning in mmWave vehicular communications", submitted to IEEE Trans. Wireless Commun., May 2020.
3. [J5] Y. Wang, Aldebaro Klautau, Monica Ribero, Anthony C.K. Soong, and Robert W. Heath Jr., "MmWave vehicular beam training with situational awareness using machine learning", accepted to. IEEE Access, May, 2019.
4. [C10] Y. Wang, Murali Narasimha, and Robert W. Heath Jr., "Towards Robustness: Machine Learning for MmWave V2X with Situational Awareness", in Proc. Asilomar, Pacific Grove, CA, Oct, 2018
5. [C9] Jide Yuan, Qi He, Michail Matthaiou, Y. Wang, Tony Q. S. Quek, Shi jin, "A weighted MMSE approach to amorphous cell for mixed-ADC distributed massive MIMO", in Proc. Asilomar, Pacific Grove, CA, Oct, 2019.
6. [C8] Y. Wang, Aldebaro Klautau, Monica Ribero, Murali Narasimha, and Robert W. Heath Jr., "MmWave vehicular beam training with situational awareness by machine learning", in Proc. IEEE GLOBECOM workshops, Abu Dhabi, UAE, Dec, 2018
7. [C7] Y. Wang, Murali Narasimha, and Robert W. Heath Jr., "MmWave Beam Prediction with Situational Awareness: A Machine Learning Approach", in Proc. IEEE SPAWC, 2018 (invited paper)
8. [C6] A. Klautau, P. Batista, N. G. Prelcic, Y. Wang and R. W. Heath Jr. , "5G MIMO data for machine learning: Application to beam selection using deep learning", in Proc. ITA, Feb, 2018
9. [J4] S. Zhang, Y. Wang, Z. He and S. Jin, "Ergodic rate analysis on applying antenna selection in D2D communication underlaying cellular networks", China Communications, 2017.
10. [J3] Y. Wang, K. Venugopal, Andreas F. Molisch and Robert W. Heath Jr., " MmWave vehicle-to-infrastructure communication: Analysis of urban microcellular networks", in IEEE Trans. Vehicular Technology, Apr, 2018.
11. [C5] Y. Wang, K. Venugopal, Andreas F. Molisch and Robert W. Heath Jr., "Blockage and coverage analysis with mmWave cross street BSs near urban intersections" in Proc. International Conference on Communications (ICC'17), Paris, France.
12. [C4] Y. Wang, K. Venugopal, Andreas F. Molisch and Robert W. Heath Jr., Analysis of Urban Millimeter Wave Microcellular Networks, in Proc. Vehicular Technology Conference (VTC'16, fall), Montreal, Canada, Sep, 2016. (invited paper)
13. [J2] Y. Wang, S. Jin, Y. Ni and K.-K Wong, Interference mitigation scheme by antenna selection in device-to-device communication underlaying cellular network, Journal of Communication and Network, Apr, 2016.
14. [C3] Y. Wang, S. Jin, Y. Ni and K.-K. Wong, Interference mitigation based antenna selection scheme in device-to-device communication underlaying cellular networks, in Proc. IEEE WCSP, Hefei, China, Oct. 2014.
15. [C2] Y. Wang, D. Qiao, S. Jin, Y. Huang and K.-K. Wong, On antenna selection for D2D communication underlaying cellular networks, in Proc. IEEE International Conference on Communications (ICC'15), London, UK, Jun. 2015.
16. [J1] Y. Ni, S. Jin, W. Xu, Y. Wang, M. Matthaiou and H. Zhu, "Beamforming and Interference Cancellation for D2D Communication Underlaying Cellular Networks," in IEEE Trans. Communications, vol. 64, no. 2, pp. 832-846, Feb. 2016.
17. [C1] Z. Wu, Y. Wang and L. Chen, A FHE public key compression scheme based on pairwise multiplication of PK element, in Proc. 8th International Collaboration Symposium on Information Production and Systems (ISIPS'14), Kitakyushu, Japan, Nov. 2014
1. Md Saifur Rahman, Yuyang Wang, Eko Onggosanusi, "Method and apparatus for wideband CSI reporting in an advanced wireless communication system", granted, US10644828B2, May, 2020.
2. Yuyang Wang, Murali Narasimha, "Method and device for communications in millimeter-wave networks", granted, US10616774B2, April, 2020
Samsung Research America Richardson, TX 2018
Develop 5G system-level simulator.
Add gNB/UE side hybrid precoding/beam sweeping features
Develop scheduling algorithms for mmWave MU-MIMO hybrid precoding
Huawei Technologies Rolling Meadows, IL, 2017
Develop machine learning assisted vehicular beam training solution leveraging embedded situational awareness information in autonomous driving.
US Qualcomm Innovation Fellowship Finalist 2018
QamCom Travel Grant for IEEE SPS summer school 2017
Exemplary reviewer for IEEE Wireless Communications Letters (WCL) 2016
Outstanding graduate of Southeast University 2015
National Scholarship 2015
Outstanding Award (O prize) of the American Mathematical Contest in Modeling (MCM) 2014