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Personal profile

Research Interests

Professor Guo's research interests lie in blockchain technologies, wireless communications, information theory, communication networks, and signal processing. His current projects concern blockchain analysis and design, next generation cellular networks, the Internet of Things, and applications of deep learning in wireless networks.

Education/Academic qualification

Electrical Engineering, PhD, Princeton University

… → 2004

Electrical Engineering, MA, Princeton University

… → 2001

Electrical Engineering, MEng, National University of Singapore

… → 1999

Electrical Engineering & Information Science, BEng, University of Science and Technology of China

… → 1995

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Grants

  • Research Output

    Joint Routing and Resource Allocation for Millimeter Wave Picocellular Backhaul

    Rasekh, M. E., Guo, D. & Madhow, U., Feb 2020, In : IEEE Transactions on Wireless Communications. 19, 2, p. 783-794 12 p., 8886731.

    Research output: Contribution to journalArticle

  • Asynchronous Neighbor Discovery Using Coupled Compressive Sensing

    Amalladinne, V. K., Narayanan, K. R., Chamberland, J. F. & Guo, D., May 1 2019, 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 4569-4573 5 p. 8682935. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2019-May).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 2 Scopus citations

    Beam Acquisition and Training in Millimeter Wave Networks with Narrowband Pilots

    Zhou, H., Guo, D. & Honig, M. L., Dec 2019, In : IEEE Journal on Selected Areas in Communications. 37, 12, p. 2759-2771 13 p., 8876700.

    Research output: Contribution to journalArticle

  • 2 Scopus citations

    Initial Access and Beamforming in Multi-cell mmWave Networks Using Narrowband Pilots

    Zhou, H., Guo, D. & Honig, M. L., Feb 19 2019, Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. Matthews, M. B. (ed.). IEEE Computer Society, p. 582-586 5 p. 8645144. (Conference Record - Asilomar Conference on Signals, Systems and Computers; vol. 2018-October).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 1 Scopus citations

    Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks

    Nasir, Y. S. & Guo, D., Oct 2019, In : IEEE Journal on Selected Areas in Communications. 37, 10, p. 2239-2250 12 p., 8792117.

    Research output: Contribution to journalArticle

  • 8 Scopus citations