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Publications

Patent Applications

  1. Moe Z. Win, Tianyi Peng, Wenhan Dai, Zehao Yu, “Efficient and Robust Physical Layer Key Generation,” M.I.T. Case No. 21962, Nov. 12, 2019.

  2. Moe Z. Win, Wenhan Dai, Mohamed-Slim Alouini, and Hesham ElSawy, “Base station ordering technique (BoLT) for localization in dense cellular networks,” U.S. Provisional Patent Application 62/564 385, Sep. 28, 2017.

  3. Moe Z. Win, Stefania Bartoletti, Wenhan Dai, and Andrea Conti, “Wideband ranging system,” U.S. Utility Patent Application US 2018/0 356 494 A1, Dec. 13, 2018.

  4. Moe Z. Win, Wenhan Dai, and Yuan Shen, “Variable resource allocation for localization,” U.S. Patent 10,228,448, Mar. 12, 2019.

Journal Papers

  1. Wenhan Dai, Tianyi Peng, and Moe Z. Win, “Optimal remote entanglement distribution with imperfect quantum repeaters,” IEEE J. Sel. Areas Commun., vol. 38, no. 3, pp. 540–556, Mar. 2020.

  2. Wenhan Dai, Tianyi Peng, and Moe Z. Win, “Quantum queuing delay,” IEEE J. Sel. Areas Commun., vol. 38, no. 3, pp. 605–618, Mar. 2020.

  3. Moe Z. Win, Florian Meyer, Zhenyu Liu, Wenhan Dai, Stefania Bartoletti, and Andrea Conti,“Efficient multi-sensor localization for the Internet-of-Things,” IEEE Signal Process. Mag., vol. 35, Sep. 2018.

  4. Moe Z. Win, Wenhan Dai, Yuan Shen, George Chrisikos, and H. Vincent Poor, “Network operation strategies for efficient localization and navigation,” Proc. IEEE, vol. 106, no. 7, pp. 1224–1254, Jul. 2018, special issue on Foundations and Trends in Localization Technologies, Invited Paper.

  5. Moe Z. Win, Yuan Shen, and Wenha Dai, “A theoretical foundation of network localization and navigation,” Proc. IEEE, vol. 106, no. 7, pp. 1136–1165, Jul. 2018, special issue on Foundations and Trends in Localization Technologies, Invited Paper.

  6. Stefania Bartoletti, Andrea Conti, Wenhan Dai, and Moe Z. Win, “Threshold profiling for wideband ranging,” IEEE Signal Process. Lett., vol. 25, no. 6, pp. 873–877, Jun. 2018.

  7. Liangzhong Ruan, Wenhan Dai, and Moe Z. Win, “Adaptive recurrence quantum entanglement distillation for two-Kraus-operator channels,” Phys. Rev. A, vol. 97, no. 5, p. 052332, May 2018.

  8. Hesham ElSawy, Wenhan Dai, Mohamed-Slim Alouini, and Moe Z. Win, “Base station ordering for emergency call localization in ultra-dense cellular networks,” IEEE Access, vol. 6, pp. 301–315, 2018.

  9. Zhenyu Liu, Wenhan Dai, and Moe Z. Win, “Mercury: An infrastructure-free system for network localization and navigation,” IEEE Trans. Mobile Comput., vol. 17, no. 5, pp. 1119–1133, May 2018.

  10. Wenhan Dai, Yuan Shen, and Moe Z. Win, “A computational geometry framework for efficient network localization,” IEEE Trans. Inf. Theory, vol. 64, no. 2, pp. 1317–1339, Feb. 2018.

  11. Junting Chen, Wenhan Dai, Yuan Shen, Vincent K. Lau, and Moe Z. Win, “Resource management games for distributed network localization,” IEEE J. Sel. Areas Commun., vol. 35, no. 2, pp. 317–329, Feb. 2017.

  12. Junting Chen, Wenhan Dai, Yuan Shen, Vincent K. Lau, and Moe Z. Win, “Power management for cooperative localization: A game theoretical approach,” IEEE Trans. Signal Process., vol. 64, no. 24, pp. 6517–6532, Dec. 2016.

  13. Wenhan Dai, Yuan Shen, and Moe Z. Win, “Energy-efficient network navigation algorithms,” IEEE J. Sel. Areas Commun., vol. 33, no. 7, pp. 1418–1430, Jul. 2015.

  14. Stefania Bartoletti, Wenhan Dai, Andrea Conti, and Moe Z. Win, “A mathematical model for wideband ranging,” IEEE J. Sel. Topics Signal Process., vol. 9, no. 2, pp. 216–228, Mar. 2015.

  15. Wenhan Dai, Yuan Shen, and Moe Z. Win, “Distributed power allocation for cooperative wireless network localization,” IEEE J. Sel. Areas Commun., vol. 33, no. 1, pp. 28–40, Jan. 2015.

  16. Yuan Shen, Wenhan Dai, and Moe Z. Win, “Power optimization for network localization,” IEEEACM Trans. Netw./, vol. 22, no. 4, pp. 1337–1350, Aug. 2014.

Conference Papers

  1. Wenhan Dai, Tianyi Peng, and Moe Z. Win, “Queuing delay for quantum networks,” in Proc. IEEE Int. Conf. Comput. Netw., and Commun., Honolulu, Hawaii, Feb. 2020, pp. 1–6.

  2. Wenhan Dai, Tianyi Peng, and Moe Z. Win, “Optimal protocols for entanglement swapping and distribution,” in Proc. IEEE Int. Conf. Comput. Netw., and Commun., Honolulu, Hawaii, Feb. 2020, pp. 1–6, Best Paper Award.

  3. Tianyi Peng, Wenhan Dai, and Moe Z. Win, “Efficient and robust physical layer key generation,” in Proc. Military Commun. Conf., Norfolk, VA, Nov. 2019, pp. 1–6.

  4. Wenhan Dai, Tianyi Peng, and Moe Z. Win, “Remote state preparation for multiple parties,” in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Process., Brighton, UK, May 2019, pp. 1–5, Invited Paper.

  5. Wenhan Dai, William C. Lindsey, and Moe Z. Win, “Accuracy of OFDM ranging systems in the presence of processing impairments,” in Proc. IEEE Int. Conf. on Ubiquitous Wireless Broadband, Salamanca, Spain, Sep. 2017, pp. 1–6, Marconi-BISITE Best Paper Award.

  6. Wenhan Dai and Moe Z. Win, “On protecting location secrecy,” in Proc. IEEE Int. Symp. on Wireless Commun. Systems, Bologna, Italy, Aug. 2017, pp. 1–6.

  7. Wenhan Dai, and Moe Z. Win, “A theoretical foundation for location secrecy,” in Proc. IEEE Int. Conf. Commun., Paris, France, May 2017.

  8. Zhenyu Liu, Wenhan Dai,and Moe Z. Win,“Node placement for localization networks,”in Proc. IEEE Int. Conf. Commun., Paris, France, May 2017.

  9. Liangzhong Ruan, Wenhan Dai, and Moe Z. Win, “Analysis of efficient recurrence quantum entanglement distillation,” in Proc. IEEE Global Telecomm. Conf., Washington, DC, USA, Dec. 2016.

  10. Liangzhong Ruan, Wenhan Dai, and Moe Z. Win, “Efficient quantum entanglement distillation for phase-damping channel,” in Proc. IEEE Global Telecomm. Conf., San Diego, CA, Dec. 2015.

  11. Stefania Bartoletti, Wenhan Dai, Andrea Conti, and Moe Z. Win, “Wideband localization via range likelihood based on reduced dataset,” in Proc. IEEE Canadian Workshop on Inf. Theory, St. John’s, NL, Canada, Jul. 2015, pp. 93–96, Student Paper Award (first place).

  12. Kaiqing Zhang, Hong Hu, Wenhan Dai, Yuan Shen, and Moe Z. Win, “An area state-aided indoor localization algorithm and its implementation,” in Proc. IEEE Int. Conf. Commun. Workshop, London, UK, Jun. 2015, pp. 736–741.

  13. Junting Chen, Wenhan Dai, Yuan Shen, Vincent K. N. Lau, and Moe Z. Win, “Power management game for cooperative localization in asynchronous networks,” in Proc. IEEE Int. Conf. Commun., London, UK, Jun. 2015, pp. 1506–1511.

  14. Wenhan Dai, Yuan Shen, and Moe Z. Win, “A computational geometry method for optimal resource allocation in network localization,” in Proc. IEEE Wireless Commun. and Networking Conf., New Or- leans, LA, Mar. 2015, pp. 765–770.

  15. Wenhan Dai, Yuan Shen, and Moe Z. Win, “Network navigation algorithms with power control,” in Proc. IEEE Wireless Commun. and Networking Conf., New Orleans, LA, Mar. 2015, pp. 1231–1236.

  16. Wenhan Dai, Yi Gai, and Bhaskar Krishnamachari, “Online learning for multi-channel opportunistic access over unknown Markovian channels,” in Proc. IEEE Conf. on Sensor and Ad Hoc Commun. and Networks, Singapore, Singapore, Jul. 2014, pp. 64–71.

  17. Wenhan Dai, Yuan Shen, and Moe Z. Win, “Energy efficient cooperative network localization,” in Proc. IEEE Int. Conf. Commun., Sydney, Australia, Jun. 2014, pp. 4969 – 4974.

  18. Wenhan Dai, Yuan Shen,and Moe Z. Win,“Sparsity-inspired power allocation algorithms for network localization,” in Proc. IEEE Int. Conf. Commun., Budapest, Hungary, Jun. 2013, pp. 1378–1383.

  19. Yuan Shen, Wenhan Dai, and Moe Z. Win, “Robust power allocation for active and passive localization,” in Proc. IEEE Int. Conf. Commun., Budapest, Hungary, Jun. 2013, pp. 3395–3400.

  20. Yuan Shen, Wenhan Dai, and Moe Z. Win, “Optimal power allocation for active and passive localization,” in Proc. IEEE Global Telecomm. Conf., Anaheim, CA, Dec. 2012, pp. 3713–3718.

  21. Wenhan Dai, Yuan Shen, and Moe Z. Win, “On the minimum number of active anchors for optimal localization,” in Proc. IEEE Global Telecomm. Conf., Anaheim, CA, Dec. 2012, pp. 4951–4956.

  22. Wenhan Dai, Yi Gai, and Bhaskar Krishnamachari, “Efficient online learning for opportunistic spec- trum access,” in Proc. IEEE Conf. on Computer Commun., Orlando, FL, USA, Mar. 2012, pp. 3086–3090.

  23. Wenhan Dai, Yi Gai, and Bhaskar Krishnamachari, “The non-Bayesian restless multi-armed bandit: A case of near-logarithmic regret,” in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Process., Prague, Czech Republic, May 2011, pp. 2940–2943.