Cooperative Multi-Monostatic Sensing for Object Localization in 6G Networks
Abstract: Enabling passive sensing of the environment using cellular base stations (BSs) will be one of the disruptive features of the sixth-generation (6G) networks. However, accurate localization and positioning of objects are challenging to achieve as multipath significantly degrades the reflected echos. Existing localization techniques perform well under the assumption of large bandwidth available but perform poorly in bandwidth-limited scenarios. To alleviate this problem, in this work, we introduce a 5G New Radio (NR)-based cooperative multi-monostatic sensing framework for passive target localization that operates in the Frequency Range 1 (FR1) band. We propose a novel fusion-based estimation process that can mitigate the effect of multipath by assigning appropriate weight to the range estimation of each BS. Extensive simulation results using ray-tracing demonstrate the efficacy of the proposed multi-sensing framework in bandwidth-limited scenarios.
- 3GPP TR 38.855, “Study on NR positioning support,” Mar. 2019.
- 3GPP TR 38.857, “Study on NR positioning enhancements,” Mar. 2021.
- 3GPP WID RP-222616, “Revised SID on Study on expanded and improved NR positioning,” Sept. 2022.
- I. Guvenc and C.-C. Chong, “A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques,” IEEE Commun. Surveys Tuts., vol. 11, no. 3, pp. 107–124, 2009.
- F. Perez-Cruz, C.-K. Lin, and H. Huang, “BLADE: A Universal, Blind Learning Algorithm for ToA Localization in NLOS Channels,” in Proc. IEEE GC Wkshps, 2016, pp. 1–7.
- S. Venkatraman, J. Caffery, and H.-R. You, “A Novel ToA Location Algorithm Using LoS Range Estimation for NLoS Environments,” IEEE Trans. Veh. Technol., vol. 53, no. 5, pp. 1515–1524, 2004.
- Q. Shi, L. Liu, S. Zhang, and S. Cui, “Device-Free Sensing in OFDM Cellular Network,” IEEE J. Sel. Areas Commun., vol. 40, no. 6, pp. 1838–1853, 2022.
- J. Shen and A. F. Molisch, “Estimating Multiple Target Locations in Multi-Path Environments,” IEEE Trans. Wireless Commun., vol. 13, no. 8, pp. 4547–4559, 2014.
- K. M. Braun, “OFDM Radar Algorithms in Mobile Communication Networks,” Ph.D. dissertation, 2014.
- L. Pucci, E. Paolini, and A. Giorgetti, “System-Level Analysis of Joint Sensing and Communication Based on 5G New Radio,” IEEE J. Sel. Areas Commun., vol. 40, no. 7, pp. 2043–2055, 2022.
- F. H. C. Tivive, A. Bouzerdoum, and M. G. Amin, “A Subspace Projection Approach for Wall Clutter Mitigation in Through-the-Wall Radar Imaging,” IEEE Trans. Geosci. Remote Sens., vol. 53, no. 4, pp. 2108–2122, 2015.
- T. M. Inc., “RF Propagation Toolbox version: 9.12.0.1884302 (R2022a),” Natick, Massachusetts, United States, 2022. [Online]. Available: https://www.mathworks.com
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.