Wireless Network Localization

Research summary

Location-awareness plays a crucial role in many wireless network applications, such as localization services in next generation cellular networks, Internet-of-Things, autonomous vehicles, and search-and-rescue operations. The global positioning system (GPS) is the most important technology to provide location-awareness around the globe through a constellation of at least 24 satellites. However, the effectiveness of GPS is limited in harsh environments, such as in buildings, in urban canyons, and under tree canopies, due to the inability of satelite signals to penetrate most obstacles. Hence, new localization techniques are required to meet the increasing need for accurate localization in such harsh environments.
Our research interests revolve around following directions:

  • Theoretical framework, distributed algorithm and resource allocation for network localization

  • Localization techniques based on polarization sensitive array

  • Single satellite positioning system based on Doppler information

  • 5G positioning system based on SRS signal

  • Network localization and synchronization using full-duplex radios

  • Beamspace direct localization;

  • Tensor-based multipath estimation

  • Joint active and passive localization framework against clock drifts

  • Passive anchor assisted localization scheme

  • Bluetooth indoor localization algorithm design

  • Localizability of large-scale networks

  • Algorithm design and hardware implementation of indoor localization for Wi-Fi devices based on tensor decomposition

Representative research works

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  • Relative localization: A theoretical analysis framework in terms of the constraint CRLB of EFIM is derived, and the geometry merging and geometry transforming algorithms for relative localization are designed. We further analyze the characteristics of resource allocation for relative localization, and design a corresponding resource allocation algorithm.

    • Y. Liu, Y. Wang, J. Wang, and Y. Shen, “Distributed 3D relative localization of UAVs,” IEEE Trans. Veh. Technol., vol. 69, no. 10, pp. 11 756-11 770, Oct. 2020.

    • X. Shen, Y. Liu, and Y. Shen, ’'On the spatial information coupling in relative localization networks,’’ in Proc. IEEE Int. Conf. Commun., Montreal, Canada, Jun. 2021, pp. 1-6.

    • X. Shen, L. Xu, Y. Liu, and Y. Shen, ’'A Theoretical Framework for Relative Localization,’’ submitted to IEEE Trans. Inf. Theory.

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  • Network localization and synchronization using full-duplex radios: We propose NLS schemes using full-duplex radios, where internode distances and clock offsets can be estimated through only two frames of transmission.

    • Y. Liu, Y. Shen, D. Guo, and M. Z. Win, “Network localization and synchronization using full-duplex radios,” IEEE Trans. Signal Process., vol. 66, no. 3, pp. 714-728, Feb 2018.

    • Y. Liu, Y. Shen, and M. Z. Win, ’'Single-anchor localization and synchronization of full-duplex agents,’’ IEEE Trans. Commun., vol. 67, no. 3, pp. 2355–2367, Mar. 2019.

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  • Beamspace direct localization: We prove that the high-dimensional array signal can be represented in a low-dimensional beamspace without information loss and further propose a robust beamspace design strategy.

    • H. Zhao, N. Zhang, and Y. Shen, “Beamspace direct localization for large-scale antenna array systems,” IEEE Trans. Signal Process., vol. 68, pp. 3529-3544, May 2020.

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  • Tensor-based network localization: We explore the inherent structure in the measurements and the uniqueness of tensor factorization to achieve high-accuracy network localization in multipath environments. By formulating the localization problem as a low-rank tensor decomposition problem, we develop a tensor decomposition-based direct localization algorithm using the designed beamspaces to significantly enhance the estimation accuracy with low complexity and data association-free methods.

    • H. Zhao, M. Huang, and Y. Shen, ’'High-accuracy localization in multipath environments via spatio-temporal feature tensorization,’’ IEEE Trans. Wireless Commun., To Appear.

    • M. Huang, H. Zhao, and Y. Shen, ’'A multipath estimation method via block term decomposition for multi-carrier systems,’’ in Proc. IEEE Global Commun. Conf., Madrid, Spain, Dec. 2021, pp. 1-6.

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  • Signal-multiplexing network measuring: We design a signal-multiplexing network measuring scheme, which can measure all node-pair distances with a minimum number of signal transmissions. In this way, the signal overhead is reduced from O(N^2) to N+1 for a N-node network.

    • Z. Zhang, H. Zhao, J. Wang, and Y. Shen, ’'Signal-multiplexing ranging for network localization,’’ IEEE Trans. Wireless Commun., vol. 21, no. 3, pp. 1694–1709, Mar. 2022.

    • H. Zhao, Z. Zhang, Z. Zhang, and Y. Shen, ’'A signal-multiplexing ranging scheme for integrated localization and sensing,’’ IEEE Wireless Commun. Lett., vol. 11, no. 8, pp. 1609-1613, Aug. 2022.

    • Z. Zhang, H. Zhao, and Y. Shen, “High-efficient ranging algorithms for wireless sensor network,” in Proc. Int. Conf. on Wireless Commun. and Signal Process., Xi'an, China, Oct. 2019, pp. 1-6.

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  • Polarization-sensitive-array-based BLE localization system: We design and implement a real-time single anchor polarization-sensitive-array-based BLE localization system using angular information, which achieves a median accuracy of 30 cm.

    • B. Wang, Y. Wang, X. Qiu, and Y. Shen, “BLE localization with polarization sensitive array,” IEEE Wireless Commun. Lett., pp. 1-4, 2021.

    • X. Qiu and B. Wang and J. Wang and Y. Shen,“AOA-based BLE localization with carrier frequency offset mitigation,” in Proc. IEEE Int. Conf. Commun. Workshop, Dublin, Ireland, Jun. 2020, pp. 1-5.

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  • We introduce the Percolation Theory in the cooperative network localization problem, prove the existence of the critical node intensity for the localizability of large-scale network.

    • F. Yang and Y. Shen, “Critical intensity for unbounded sequential localizability,” IEEE/ACM Trans. Netw., vol.29, no.3, pp.1321-1334, Jun. 2021.

    • F. Yang, F. Zhou, and Y. Shen, ’'On the existence of infinite localizable nodes in stochastic networks,’’ in Proc. IEEE Int. Conf. Commun., Kansas city, MO, USA, May 2018, pp. 1–5.

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  • We propose a 5G cooperative localization scheme and a distributed cooperative localization algorithm based on maximum likelihood principle. The superiority of the proposed scheme is verified by comparing with the theoretical limit of positioning error. Finally, we explore the factors affecting the stability of the cooperative localization technology in 5G vehicle networks, and provide ideas for the future research of localization scheme in vehicle networks.

    • W. Li, Y. Liu, X. Li, and Y. Shen, ’'Three-dimensional cooperative localization via space-air-ground integrated networks’’ China Commun., vol. 19, no. 1, pp. 253–263, Jan. 2022.