2027
GenRF: Reconstruct Any Radio Field in a Feed-Forward Process
Shen Wang, Guosheng Wang, Junyang Liu, Lei Yang
ACM SenSys 2027
A feed-forward framework for reconstructing radio fields from wireless measurements.
GenRF: Reconstruct Any Radio Field in a Feed-Forward Process
Shen Wang, Guosheng Wang, Junyang Liu, Lei Yang
ACM SenSys 2027
A feed-forward framework for reconstructing radio fields from wireless measurements.
2026
City-Scale Radiance-Field Reconstruction via Mixture of Radio Experts
Shen Wang, Guosheng Wang, Donghui Dai, Lei Yang
ACM MobiCom 2026
A city-scale radio radiance-field reconstruction system based on a mixture of radio experts.
City-Scale Radiance-Field Reconstruction via Mixture of Radio Experts
Shen Wang, Guosheng Wang, Donghui Dai, Lei Yang
ACM MobiCom 2026
A city-scale radio radiance-field reconstruction system based on a mixture of radio experts.
Radiance-Field Guided Pretraining: Scaling Localization Models with Unlabeled Wireless Signals
Guosheng Wang, Shen Wang, Lei Yang
ACM IMWUT, UbiComp 2026
RFGP uses a physics-guided RF radiance field to pretrain localization models from unlabeled wireless signals, targeting cross-scene generalization. The published work evaluates the approach on a multi-technology dataset spanning 100 scenes.
Radiance-Field Guided Pretraining: Scaling Localization Models with Unlabeled Wireless Signals
Guosheng Wang, Shen Wang, Lei Yang
ACM IMWUT, UbiComp 2026
RFGP uses a physics-guided RF radiance field to pretrain localization models from unlabeled wireless signals, targeting cross-scene generalization. The published work evaluates the approach on a multi-technology dataset spanning 100 scenes.
SIGN-RF: Self-Adaptive Neural Fields for Scalable Urban Radio Reconstruction
Shen Wang, Guosheng Wang, Junyang Liu, Donghui Dai, Lei Yang
IEEE INFOCOM 2026
SIGN-RF introduces adaptive hierarchical sampling and self-supervised position labeling for scalable urban radio reconstruction, improving data efficiency and convergence when only a limited portion of RF measurements have known positions.
SIGN-RF: Self-Adaptive Neural Fields for Scalable Urban Radio Reconstruction
Shen Wang, Guosheng Wang, Junyang Liu, Donghui Dai, Lei Yang
IEEE INFOCOM 2026
SIGN-RF introduces adaptive hierarchical sampling and self-supervised position labeling for scalable urban radio reconstruction, improving data efficiency and convergence when only a limited portion of RF measurements have known positions.
Scaling Mobile IoT Connectivity with eSIM: A Temporal Event Modeling Approach
Sicong Liao, Fei Yuan, Guosheng Wang, Lei Yang, Xuan Song
IEEE INFOCOM 2026
This work studies the reliability of commercial eSIM systems at large scale and proposes NeSIM, a lookahead-based multi-operator access framework that uses predictive analytics to proactively orchestrate operator switches.
Scaling Mobile IoT Connectivity with eSIM: A Temporal Event Modeling Approach
Sicong Liao, Fei Yuan, Guosheng Wang, Lei Yang, Xuan Song
IEEE INFOCOM 2026
This work studies the reliability of commercial eSIM systems at large scale and proposes NeSIM, a lookahead-based multi-operator access framework that uses predictive analytics to proactively orchestrate operator switches.
WiT: Wireless Tracking With Dual-Modality Transformers
Xiaopeng Zhao*, Guosheng Wang*, Lei Yang (* co-primary)
IEEE Transactions on Mobile Computing 2026
WiT combines RF and IMU signals with cross-modality validation, history-aware tracking, and semi-supervised learning to improve robustness under environmental dynamics while reducing ground-truth label requirements.
WiT: Wireless Tracking With Dual-Modality Transformers
Xiaopeng Zhao*, Guosheng Wang*, Lei Yang (* co-primary)
IEEE Transactions on Mobile Computing 2026
WiT combines RF and IMU signals with cross-modality validation, history-aware tracking, and semi-supervised learning to improve robustness under environmental dynamics while reducing ground-truth label requirements.
Scaling Neural Radio Radiance Fields to City-Scale: A Mixture of Experts Approach
Shen Wang, Guosheng Wang, Donghui Dai, Lei Yang
IEEE Transactions on Mobile Computing 2026
This work studies a mixture-of-experts approach for scaling neural radio radiance fields to city-scale environments.
Scaling Neural Radio Radiance Fields to City-Scale: A Mixture of Experts Approach
Shen Wang, Guosheng Wang, Donghui Dai, Lei Yang
IEEE Transactions on Mobile Computing 2026
This work studies a mixture-of-experts approach for scaling neural radio radiance fields to city-scale environments.
2024
Pushing the Boundaries of High-Precision AoA Estimation With Enhanced Phase Estimation Protocol
Xiaopeng Zhao, Guosheng Wang, Zhenlin An, Qingrui Pan, Qiongzheng Lin, Lei Yang
IEEE Internet of Things Journal 2024
CPE and CPE+ address phase ambiguity and noise in RFID-based AoA estimation, extending accurate centimeter-level localization over longer communication ranges.
Pushing the Boundaries of High-Precision AoA Estimation With Enhanced Phase Estimation Protocol
Xiaopeng Zhao, Guosheng Wang, Zhenlin An, Qingrui Pan, Qiongzheng Lin, Lei Yang
IEEE Internet of Things Journal 2024
CPE and CPE+ address phase ambiguity and noise in RFID-based AoA estimation, extending accurate centimeter-level localization over longer communication ranges.
Understanding Localization by a Tailored GPT
Xiaopeng Zhao*, Guosheng Wang*, Zhenlin An, Qingrui Pan, Lei Yang (* co-primary)
ACM MobiSys 2024
LocGPT repurposes a Transformer-style GPT for indoor localization, improving adaptability across scenarios and reducing the amount of labeled data needed for transfer learning.
Understanding Localization by a Tailored GPT
Xiaopeng Zhao*, Guosheng Wang*, Zhenlin An, Qingrui Pan, Lei Yang (* co-primary)
ACM MobiSys 2024
LocGPT repurposes a Transformer-style GPT for indoor localization, improving adaptability across scenarios and reducing the amount of labeled data needed for transfer learning.