| [1] |
ITU-R. Minimum requirements related to technical performance for IMT-2030 radio interface(s)[R]. 2024.
|
| [2] |
Trevlakis S E, Boulogeorgos A A A, Pliatsios D, et al. Localization as a key enabler of 6G wireless systems: A comprehensive survey and an outlook[J]. IEEE open journal of the Communications Society, 2023, 4: 2733-2801.
doi: 10.1109/OJCOMS.2023.3324952
URL
|
| [3] |
3GPP. Study on positioning use cases: 3GPP TR 22.872[R]. 2018.
|
| [4] |
Pan G, Gao Y, Gao Y, et al. AI-driven wireless positioning:fundamentals, standards, state-of-the-art, and challenges[J]. IEEE Communications Surveys & Tutorials, 2025.
|
| [5] |
3GPP. Study on artificial intelligence (AI)/machine learning (ML) for NR air interface: 3GPP TS 38.843[R]. 2024.
|
| [6] |
Fu Y, Tian Z. Cramer-rao bounds for hybrid TOA/DOA-based location estimation in sensor networks[J]. IEEE Signal Processing Letters, 2009, 16(8):655-658.
doi: 10.1109/LSP.2009.2021323
URL
|
| [7] |
Guvenc I, Chong C C. Asurvey on TOA based wireless localization and NLOS mitigation techniques[J]. IEEE Communications Surveys & Tutorials, 2009, 11(3):107-124.
|
| [8] |
Silva B, Hancke G P. Ranging error mitigation for through-the-wall non-line-of sight conditions[J]. IEEE Transactions on Industrial Informatics, 2020, 16(11):6903-6911.
doi: 10.1109/TII.9424
URL
|
| [9] |
Mazuelas S, Lago F A, Blas J, et al. Prior NLOS measurement correction for positioning in cellular wireless networks[J]. IEEE Transactions on Vehicular Technology, 2008, 58(5):2585-2591.
doi: 10.1109/TVT.2008.2009305
URL
|
| [10] |
Güvenç İ, Chong C C, Watanabe F, et al. NLOS identification and weighted least-squares localization for UWB systems using multipath channel statistics[J]. EURASIP Journal on Advances in Signal Processing, 2007, 2008(1):271984.
doi: 10.1155/2008/271984
URL
|
| [11] |
He S, Chan S H G. Wi-Fi fingerprint-based indoor positioning: recent advances and comparisons[J]. IEEE Communications Surveys & Tutorials, 2015, 18(1):466-490.
|
| [12] |
Yang J, Zhao X, Li Z. Updating radio maps without pain:an enhanced transfer learning approach[J]. IEEE Internet of Things Journal, 2020, 8(13):10693-10705.
doi: 10.1109/JIOT.2020.3048253
URL
|
| [13] |
Yin Z, Cui K, Wu Z, et al. Entropy-based TOA estimation and SVM-based ranging error mitigation in UWB ranging systems[J]. Sensors, 2015, 15(5):11701-11724.
doi: 10.3390/s150511701
pmid: 26007726
|
| [14] |
Savic V, Larsson E G, Ferrer-Coll J, et al. Kernel methods for accurate UWB-based ranging with reduced complexity[J]. IEEE Transactions on Wireless Communications, 2015, 15(3):1783-1793.
doi: 10.1109/TWC.2015.2496584
URL
|
| [15] |
Kirmaz A, ŞAhin T, Michalopoulos D S, et al. ToA and TDoA estimation using artificial neural networks for high-accuracy ranging[J]. IEEE Journal on Selected Areas in Communications, 2023, 41(12):3816-3830.
doi: 10.1109/JSAC.2023.3322803
URL
|
| [16] |
Sun H, Kaya A O, Macdonald M, et al. Deep learning based preamble detection and TOA estimation[C]// 2019 IEEE Global Communications Conference (GLOBECOM). IEEE, 2019:1-6.
|
| [17] |
Luo Z, Tao T, Liu J. TOA estimation scheme based on CNN for b-IFDM-based preambles[C]// 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring). IEEE, 2019:1-5.
|
| [18] |
Sun X, Wu C, Gao X, et al. Fingerprint-based localization for massive MIMO-OFDM system with deep convolutional neural networks[J]. IEEE Transactions on Vehicular Technology, 2019, 68(11):10846-10857.
doi: 10.1109/TVT.25
URL
|
| [19] |
Wang X, Gao L, Mao S, et al. CSI-based fingerprinting for indoor localization: a deep learning approach[J]. IEEE Transactions on Vehicular Technology, 2016, 66(1):763-776.
doi: 10.1109/TVT.2016.2545523
URL
|
| [20] |
Liu W, Song X D, Deng Z L. Fingerprint augmentation based on location information consistency in dynamic environment[J]. IEEE Sensors Journal, 2024, 24(24):42440-42447.
doi: 10.1109/JSEN.2024.3486441
URL
|
| [21] |
Ferrand P, Guillaud M, Studer C, et al. Wireless channel charting: theory, practice, and applications[J]. IEEE Communications Magazine, 2023, 61(6):124-130.
|
| [22] |
Lei E, Castañeda Fernández O, Tirkkonen O, et al. Siamese neural networks for wireless positioning and channel charting[C]// 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2019:200-207.
|
| [23] |
Stahlke M, Yammine G, Feigl T, et al. Velocity-based channel charting with spatial distribution map matching[J]. IEEE Journal of Indoor and Seamless Positioning and Navigation, 2024, 2:230-239.
doi: 10.1109/JISPIN.2024.3424768
URL
|
| [24] |
Mazuelas S, Conti A, Allen J C, et al. Soft range information for network localization[J]. IEEE Transactions on Signal Processing, 2018, 66(12):3155-3168.
doi: 10.1109/TSP.78
URL
|
| [25] |
Conti A, Mazuelas S, Bartoletti S, et al. Soft information for localization-of-things[J]. Proceedings of the IEEE, 2019, 107(11):2240-2264.
doi: 10.1109/JPROC.2019.2905854
|
| [26] |
Li Y, Mazuelas S, Shen Y. A deep learning approach for generating soft range information from RF data[C]// 2021 IEEE Globecom Workshops (GC Wkshps). IEEE, 2021:1-5.
|
| [27] |
郭振铭. 基于软信息的无线定位方法研究[D]. 合肥: 中国科学技术大学, 2026.
|
| [28] |
Adam A B M, Lagunas E, Samy M, et al. Generative AI for non-terrestrial networks: design, applications, and challenges[J]. Journal on Wireless Communications and Networking, 2025, 2026(1):12.
doi: 10.1186/s13638-025-02549-7
|
| [29] |
Encinas-Lago G, Sciancalepore V, Wymeersch H, et al. RiLoCo:an ISAC-oriented AI solution to build RIS-empowered networks[J]. IEEE Transactions on Wireless Communications, 2025, 24(10):8221-8235.
doi: 10.1109/TWC.2025.3564832
URL
|
| [30] |
Zhang J, Lu W, Xing C, et al. Intelligent integrated sensing and communication: a survey[J]. Science China Information Sciences, 2025, 68(3):131301.
doi: 10.1007/s11432-024-4205-8
|
| [31] |
Hu J, Valiulahi I, Masouros C. ISAC receiver design: a learning-based two-stage joint data-and-target parameter estimation[J]. IEEE Wireless Communications Letters, 2024, 13(8):2105-2109.
doi: 10.1109/LWC.2024.3402398
URL
|
| [32] |
Qi Q, Chen X, Huang C, et al. DL-based joint waveform and beamforming design for integrated sensing and communication[C]// 2023 IEEE Globecom Workshops (GC Wkshps). IEEE, 2023:110-116.
|
| [33] |
Xu Z, Xue M, Xiong X, et al. Enhancing cross-scenario generalization in indoor localization via feature disentanglement[J]. IEEE Transactions on Mobile Computing, 2026.
|
| [34] |
Etiabi Y, Njima W, Amhoud E M. Federated learning based hierarchical 3D indoor localization[C]// 2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023:1-6.
|
| [35] |
Cheraghinia M, De Poorter E, Fontaine J, et al. Afoundation model for wireless technology recognition and localization tasks[J]. IEEE Open Journal of the Communications Society, 2025,6:9879-9896.
|
| [36] |
Shi X, Xuan X, Huang X, et al. Digital twin empowered wireless positioning: prospects, architecture, and challenges[J]. IEEE Network, 2025.
|
| [37] |
Zhang S, Wijesinghe A, Ding Z. RME-GAN: a learning framework for radio map estimation based on conditional generative adversarial network[J]. IEEE Internet of Things Journal, 2023, 10(20):18016-18027.
doi: 10.1109/JIOT.2023.3278235
URL
|
| [38] |
Lee T, Park J, Kim H, et al. Generating high dimensional user-specific wireless channels using diffusion models[J]. IEEE Transactions on Wireless Communications, 2025.
|