Wireless Network Localization
Research summary
Locationawareness plays a crucial role in many wireless network applications, such as localization services in next generation cellular networks, InternetofThings, autonomous vehicles, and searchandrescue operations. The global positioning system (GPS) is the most important technology to provide locationawareness 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 fullduplex radios
Beamspace direct localization;
Tensorbased multipath estimation
Joint active and passive localization framework against clock drifts
Passive anchor assisted localization scheme
Bluetooth indoor localization algorithm design
Localizability of largescale networks
Algorithm design and hardware implementation of indoor localization for WiFi devices based on tensor decomposition
Representative research works

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 75611 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. 16.
X. Shen, L. Xu, Y. Liu, and Y. Shen, ’'A Theoretical Framework for Relative Localization,’’ submitted to IEEE Trans. Inf. Theory.






Tensorbased network localization: We explore the inherent structure in the measurements and the uniqueness of tensor factorization to achieve highaccuracy network localization in multipath environments. By formulating the localization problem as a lowrank tensor decomposition problem, we develop a tensor decompositionbased direct localization algorithm using the designed beamspaces to significantly enhance the estimation accuracy with low complexity and data associationfree methods.
H. Zhao, M. Huang, and Y. Shen, ’'Highaccuracy localization in multipath environments via spatiotemporal feature tensorization,’’ IEEE Trans. Wireless Commun., To Appear.
M. Huang, H. Zhao, and Y. Shen, ’'A multipath estimation method via block term decomposition for multicarrier systems,’’ in Proc. IEEE Global Commun. Conf., Madrid, Spain, Dec. 2021, pp. 16.


Signalmultiplexing network measuring: We design a signalmultiplexing network measuring scheme, which can measure all nodepair 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 Nnode network.
Z. Zhang, H. Zhao, J. Wang, and Y. Shen, ’'Signalmultiplexing 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 signalmultiplexing ranging scheme for integrated localization and sensing,’’ IEEE Wireless Commun. Lett., vol. 11, no. 8, pp. 16091613, Aug. 2022.
Z. Zhang, H. Zhao, and Y. Shen, “Highefficient ranging algorithms for wireless sensor network,” in Proc. Int. Conf. on Wireless Commun. and Signal Process., Xi'an, China, Oct. 2019, pp. 16.






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, ’'Threedimensional cooperative localization via spaceairground integrated networks’’ China Commun., vol. 19, no. 1, pp. 253–263, Jan. 2022.

