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Zhen Gao 高镇 Assistant Professor Advanced Research Institute for Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China Address: Room 6-29C, Central Teaching Building (中心教学楼), Beijing Institute of Technology, Beijing 100081, China Tel: +86-10-68913011 E-mail: gaozhen16@bit.edu.cn Research Interests: Massive MIMO, Channel Estimation, Sparse Signal Processing
Homepage: http://oa.ee.tsinghua.edu.cn/dailinglong/members/zhengao |
Biography
Zhen Gao (S’14) received the B.S. degree (with the highest honor) from Beijing Institute of Technology, Beijing, China, in 2011, the Ph. D. degree (with the highest academic honor) from Tsinghua University, Beijing, China, in 2016. From June 2014 to September 2014 and from January 2015 to July 2015, he visited the Communications and Signal Processing Group in Imperial College London, where Dr. Wei Dai was the host. He has been an Assistant Professor in Beijing Institute of Technology, Beijing, China, since July 2016. His research interests are in wireless communications, with a focus on multi-carrier modulations, multiple antenna systems, sparse signal processing. He was the recipient of IEEE Broadcast Technology Society 2016 Scott Helt Memorial Award, the recipient of Academic Star of Tsinghua University in 2016, and the recipient of the National Ph D Scholarship in 2015. He currently serves as the TPC Member of IEEE WCNC'16 and IEEE VTC'17-Spring.
Publications
Book Chapters
[BC3] Xinyu Gao, Linglong Dai, Zhen Gao, Tian Xie, Zhaocheng Wang, and Shahid Mumtaz,“Precoding for mmWave Massive MIMO,” in MmWave Massive MIMO: A Paradigm for 5G, Chapter 5, pp. 79-111, Academic Press, Elsevier, 2016.
[BC2] Zhen Gao, Linglong Dai, Chen Hu, Xinyu Gao, Shahid Mumtaz, and Zhaocheng Wang, “Channel Estimation for mmWave Massive MIMO” in MmWave Massive MIMO: A Paradigm for 5G, Chapter 6, pp. 113-139, Academic Press, Elsevier, 2016.
[BC1] Zhen Gao, Linglong Dai, Xinyu Gao, Muhammad Zeeshan Shakir, and Zhaocheng Wang, “Fronthaul Design for mmWave Massive MIMO,” in MmWave Massive MIMO: A Paradigm for 5G, Chapter 12, pp. 289-312, Academic Press, Elsevier, 2016.
Journal Papers
[J13] Z. Gao, C. Zhang, and Z. Wang, “Robust preamble design for synchronization, signaling transmission, and channel estimation,” IEEE Trans. Broadcasting, vol. 61, no. 1, pp. 98–104, Mar. 2015. (IEEE Broadcast Technology Society 2016 Scott Helt Memorial Award)
[J12] Z. Gao, C. Zhang, Z. Wang, and S. Chen “Priori-information aided iterative hard threshold: A low-complexity high-accuracy compressive sensing based channel estimation for TDS-OFDM,” IEEE Trans. Wireless Commun., vol. 14, no. 1, pp. 242–251, Jan. 2015.
[J11] Z. Gao, L. Dai, C. Qi, C. Yuen, and Z. Wang, “Near-optimal signal detector based on structured compressive sensing for massive SM-MIMO,” IEEE Trans. Veh. Technol., vol. 66, no. 2, pp. 1860 - 1865, Feb. 2017. (IF: 2.642)
[J10] Z. Gao, L. Dai, Z. Wang, S. Chen, and L. Hanzo, “Compressive sensing based multi-user detector for large-scale SM-MIMO uplink,” IEEE Trans. Veh. Technol., vol. 65, no. 10, pp. 8725-8730, Oct. 2016. (IF: 2.642)
[J9] Z. Gao, L. Dai, C. Hu, and Z. Wang, “Channel estimation for millimeter-Wave massive MIMO with hybrid precoding over frequency-selective fading channels,” IEEE Commun. Lett., vol. 20, no. 6, pp. 1259-1262, Jun. 2016.
[J8] Z. Gao, L. Dai, W. Dai, B. Shim, and Z. Wang, “Structured compressive sensing based spatio-temporal joint channel estimation for FDD massive MIMO,” IEEE Trans. Commun., vol. 64, no. 2, pp. 601-617, Feb. 2016. (IF: 1.992)
[J6] Z. Gao, L. Dai, Z. Wang, and S. Chen, “Spatially common sparsity based adaptive channel estimation and feedback for FDD massive MIMO”, IEEE Trans. Signal Process., vol. 63, no. 23, pp. 6169-6183, Dec. 2015. (IF: 3.198)
[J5] Z. Gao, L. Dai, D. Mi, Z. Wang, M. A. Imran, and M. Z. Shakir, “MmWave massive MIMO based wireless backhaul for 5G ultra-dense network,” IEEE Wireless Commun., vol. 22, no. 5, pp. 13-21, Oct. 2015. (IF: 6.524)
[J4] Z. Gao, L. Dai, C. Yuen, and Z. Wang, “Asymptotic orthogonality analysis of time-domain sparse massive MIMO channels,” IEEE Commun. Lett., vol. 19, no. 10, pp. 1826-1829, Oct. 2015.
[J3] W. Shen, L. Dai, Z. Gao, and Z. Wang, “Spatially correlated channel estimation based on block iterative support detection for massive MIMO,” Electron. Lett., vol. 51, no.7, pp. 587-588, Apr. 2015.
[J2] Z. Gao, L. Dai, Z. Lu, C. Yuen, and Z. Wang, “Super-resolution sparse MIMO-OFDM channel estimation based on spatial and temporal correlations,” IEEE Commun. Lett., vol. 18, no. 7, pp. 1266-1269, Jul. 2014.
[J1] Z. Gao, L. Dai, and Z. Wang, “Structured compressive sensing based superimposed pilot design in downlink large-scale MIMO systems,” Electron. Lett., vol. 50, no. 12, pp. 896-898, Jun. 2014.
Conference Papers
[C7] Z. Gao, L. Dai, and Z. Wang, “Channel estimation for mmWave massive MIMO based access and backhaul in ultra-dense network,” in Proc. IEEE Int. Conf. Commun. (IEEE ICC’16), Kuala Lumpur, Malaysia, May 2016.
[C6] W. Shen, L. Dai, Y. Shi, Z. Gao, and Z. Wang, “Massive MIMO channel estimation based on block iterative support detection,” in Proc. IEEE Wireless Commun. Netw. Conf. (IEEE WCNC’16), Doha, Qatar, Apr. 2016.
[C5] L. Dai, Z. Gao, and Z. Wang, “Joint channel estimation and feedback with low overhead for FDD massive MIMO systems,” in Proc. IEEE/CIC Int. Conf. Commun. China (IEEE/CIC ICCC'15), Shenzhen, China, Nov. 2015. (Invited Paper)
[C4] Z. Gao, L. Dai, W. Shen, and Z. Wang, “Temporal correlation based sparse channel estimation for TDS-OFDM in high-speed scenarios,” in Proc. IEEE Military Commun. Conf. (IEEE MILCOM’15), Tampa, USA, Oct. 2015. (IEEE MILCOM 2015 Student Travel Grant)
[C3] Z. Gao, L. Dai, W. Dai, and Z. Wang, “Block compressive channel estimation and feedback for FDD massive MIMO,” in Proc. IEEE Int. Conf. Computer Commun. (IEEE INFOCOM’15) Workshop, Hong Kong, Apr. 2015.
[C2] W. Shen, L. Dai, Z. Gao, and Z. Wang, “Joint CSIT acquisition based on low-rank matrix recovery for FDD massive MIMO systems,” in Proc. IEEE Int. Conf. Computer Commun. (IEEE INFOCOM’15) Workshop, Hong Kong, Apr. 2015.
[C1] L. Dai, Z. Gao, Z. Wang, and Z. Yang, “Spectrum-efficient superimposed pilot design based on structured compressive sensing for large-scale MIMO systems” in Proc. URSI General Assembly Scientific Symp. (URSI GASS’14), Beijing, China, Aug. 2014. (URSI Young Scientist Award 2014)