Selected recent publications

Recent publications
  • P.-W. Jiang, C.-K. Wen, S. Jin, and G. Y. Li, “Wireless semantic communications for video conferencing,” IEEE Journal on Selected Areas in Communications. vol. 41, no. 1, pp. 230-244, January 2023.

  • H.-T. He, R. Wang, S. Jin, C.-K. Wen, and G. Y. Li, “Beamspace channel estimation in Terahertz communications: A model-driven unsupervised deep learning approach,” IEEE Transactions on Wireless Communications, vol. 22, no. 3, pp. 1808-1822, March 2023.

  • O.-Y. Wang, J.-B. Gao, and G. Y. Li, “Learning to adapt to current environment from past experience: Few-shot online learning in wireless communications,” IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 2, pp. 373-385, April 2023.

  • S.-L. Zhou and G. Y. Li, “FedGiA: an efficient hybrid algorithm for federated learning,” IEEE Transactions on Signal Processing, vol. 71, pp. 1941-1508, 2023.

  • D. Shi, L.-F. Song, W.-Q. Zhou, X.-Q. Gao, C.-X. Wang, and G. Y. Li, “Channel acquisition for HF skywave massive MIMO-OFDM communications,” IEEE Transactions on Wireless Communications, vol. 22, no. 6, pp. 4074-4089, June 2023.

  • J.-B. Gao, C.-J. Zhong, G. Y. Li, J. B. Soriaga, and A. Behboodi, “Deep learning-based channel estimation for wideband hybrid mmwave massive MIMO,” IEEE Transactions on Communications, vol. 71, no. 6, pp. 3679-3693, June 2023.

  • P.-W. Jiang, C.-K. Wen, J. Shi, and G. Y. Li, “Wireless semantic transmission via revising modules in conventional communications,” IEEE Wireless Communications, vol. 30, no. 3, pp 28-34, June 2023.

  • J.-C. Shi, W. Zhong, X.-Q. Gao, and G. Y. Li, “Robust WMMSE precoder with deep learning design for massive MIMO,” IEEE Transactions on Communications, vol. 71, no. 7, pp. 3963-3976, July 2023.

  • S.-L. Zhou and G. Y. Li, “Federated learning via inexact ADMM,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 8, pp. 9699-9780, August 2023.

  • B.-W. Zhang, H. Sifaou, and G. Y. Li, “CSI-fingerprinting indoor localization via attention-augmented residual convolutional neural network,” IEEE Transactions on Wireless Communications, vol. 22, no. 8, pp. 5583-5597, August 2023.
  • B.-W. Zhang, Z.-J. Qin, and G. Y. Li, “Semantic communications with variable-length coding for extended reality,” IEEE Journal on Selected Topics in Signal Processing, vol. 17, no. 5, pp. 1038-1051, September 2023.
  • X.-L. Yu, X.-Q. Gao, A.-A. Liu, J.-L. Zhang, H.-B. Wu, and G. Y. Li, “Robust precoding for HF skywave massive MIMO,” IEEE Transactions on Wireless Communications, vol. 22, no. 10, pp. 6691-6705, October 2023.
  • K.-D. Xu, H. Nguyen, and G. Y. Li, “Distributed-training-and-execution multi-agent reinforcement learning for power control in HetNet,” IEEE Transactions on Communications. vol. 71, no. 10, pp. 5893-5903, October 2023.
  • C.-T. Guo. X.-J. Wang, L. Liang, G. Y. Li, “Age of information, latency, and reliability in intelligent vehicular networks,” IEEE Network Magazine, vol. 37, no. 6, pp. 109-116, November/December 2023.
  • Q. Hu, F.-F. Gao, H. Zhang, G. Y. Li, and Z.-B. Xu, “Understanding deep MIMO detection,” IEEE Transactions on Wireless Communications, vol. 22, no. 12, pp. 9626-9639, December 2023.
  • J.-B. Gao, C.-J. Zhong, G. Y. Li, J. B. Soriaga, and A. Behboodi, “Spatially sparse precoding in wideband hybrid terahertz massive MIMO systems,” IEEE Transactions on Wireless Communications, vol. 23, no. 3, pp. 1871-1885, March 2024.
  • X.-Y. Wei, B.-H. F. Juang, O.-Y. Wang, S.-L. Zhou, and G. Y. Li, “Accretionary learning with deep neural networks with application,” IEEE Transactions on Cognitive Communications and Networking, vol. 10, no. 2, pp. 660-673, April 2024.
  • K.-J. Chen, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Simultaneous beam training and target sensing in ISAC systems with RIS,” IEEE Transactions on Wireless Communications, vol. 23, no. 4, pp. 2696-2710, April 2024.
  • Y.-Y. Guo, Z.-J. Qin, X.-M. Tao, and G. Y. Li, “Federated multi-view synthesizing for metaverse,” IEEE Journal on Selected Areas in Communications, vol. 42, no. 4, pp. 867-879, April 2024.
  • B. Zhang, Z, Qin, and G. Y. Li “Compression ratio learning and semantic communications for video imaging,” IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 3, pp. 312 – 324, April 2024.
  • H. Sifaou and G. Y. Li, “Over-the-air federated learning over scalable cell-free massive MIMO,” IEEE Transactions on Wireless Communications, vol. 23, no. 5, pp. 4214-4227, May 2024
  • K.-J. Chen, C.-H. Qi, C.-X. Wang, and G. Y. Li, “Beam training and tracking for extremely large-scale MIMO communications,” IEEE Transactions on Wireless Communications, vol. 23, no. 5, pp. 5048-5062, May 2024.
  • K.-J. Chen, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Near-field multiuser communications based on sparse arrays,” Journal of Selected Topics in Signal Processing, vol. 18, no. 4, pp. 619-632, May 2024.
  • J.-Y. Liao, J.-H. Zhao, F.-F. Gao, and G. Y. Li, “Deep learning aided low complex breath-first tree search for MIMO detection,” IEEE Transactions on Wireless Communications, vol. 23, no. 6, pp. 6266-6278, June 2024.
  • J. Guo, H. Chen, B. Song, Y.-H. Chi, C. Yuan, F. R. Yu, G. Y. Li, and D. Niyato “Distributed task-oriented communication networks with multimodal semantic relay and edge intelligence,” IEEE Communications Magazine, vol. 62, no. 6, pp. 82-89, June 2024.
  • S. Zargari, C. Tellambura, A. Maaref, and G. Y. Li, “Deep conditional generative adversarial networks for efficient channel estimation in AmBC systems,” IEEE Transactions on Machine Learning in Communications and Networking, vol. 2, no. 6, pp. 805-822, 2024.
  • D. Galappaththige, S. Zargari, C. Tellambura, and G. Y. Li, “Near-field ISAC: beamforming for multi-target detection,” IEEE Wireless Communications Letters, vol. 13, no. 7, pp. 1938-1942, July 2024.
  • P.-W. Jiang, C.-K. Wen, S. Jin, and G. Y. Li, “RIS-enhanced semantic communications adaptive to user requirements,” IEEE Transactions on Communications, vol. 72, no. 7, pp. 4134-4148, July 2024.
  • Z.-J. Qin, L. Liang, Z.-J. Wang, S. Jin, X.-M. Tao, W. Tong, G. Y. Li, “AI empowered wireless communications: from bits to semantics,” Proceedings of the IEEE, vol. 112, no. 7, pp. 621-652, July 2024.
  • S.-X. Wang, W. Dai, H.-W. Wang, and G. Y. Li, “Robust waveform design for integrated sensing and communication,” IEEE Transactions on Signal Processing, vol. 72, no. 7, pp. 3122-3138, 2024.
  • K.-J. Chen, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Triple-refine hybrid-field beam training for mmWave extremely large-scale MIMO,” IEEE Transactions on Wireless Communications, vol. 23, no. 8, pp. 8556-8570, August 2024.
  • C. Xu, L.-P. Xiang, S. Sugiura, R. G. Maunder, L.-L. Yang, D. Niyato, G. Y. Li, R. Schober, and L. Hanzo, “Noncoherent orthogonal time frequency space modulation,” IEEE Transactions on Wireless Communications, vol. 23, no. 8, pp. 10072-10090, August 2024.
  • M. A. ElMossallamy, Z. Han, M. Pan, R. Jantti, K. G. Seddik, G. Y. Li, “Noncoherent frequency shift keying for ambient backscatter over OFDM signals,” IEEE Open Journal of the Communications Society, vol. 5, pp. 5219-5231, 2024.
  • Y.-Z. Liu Z.-J. Qin, and G. Y. Li, “Energy-efficient distributed spiking neural network for wireless edge intelligence,” IEEE Transactions on Wireless Communications, vol. 23, no. 9, pp. 10683-10697, September 2024.
  • B. Lin, C.-B. Zhao, F.-F. Gao, G. Y. Li, J. Qian, and H. Wang, “Environment reconstruction based on multi-user selection and multi-modal fusion in ISAC,” IEEE Transactions on Wireless Communications, vol. 23, no. 10, pp. 15083-15095, October 2024.
  • Z.-X. Chen, W.-Q. Yi, A. Nallanathan, and G. Y. Li, “Efficient wireless federated learning with partial model aggregation,” IEEE Transactions on Communications, vol. 72, no. 10, pp. 6271-6286, October 2024.
  • D. Shi, L.-F. Song, X.-Q. Gao, J.-H. Wang, M. Bengtsson, G. Y. Li, and X.-G. Xia, “Beam structured channel estimation for HF skywave massive MIMO-OFDM communications,” IEEE Transactions on Wireless Communications, vol. 23, no. 11, pp. 16301-16315, November 2024.
  • S.-Z. Hu, Y.-P. Duan, X.-M. Tao, G. Y. Li, J.-H. Lu, G.-Y. Liu, and Z.-M. Zheng, C.-K. Pan, “Brain-inspired image perceptual quality assessment based on EEG: A QoE perspective,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 12, pp. 8424-8441, December 2024.
  • H. Zhang, S.-L. Zhou, G. Y. Li, and N.-H. Xiu “0/1 constrained optimization solving SAA for CCP,” to appear in Mathematics of Operations Research.
  • K.-J. Chen, C.-H. Qi, J.-J. Huang, O. A. Dobre, and G. Y. Li, “Near-field communications for extremely large-scale MIMO: A beamspace perspective,” to appear in IEEE Communications Magazine.
  • K.-D. Xu, S.-L. Zhou, and G. Y. Li, “Rescale-invariant federated reinforcement learning for resource allocation in V2X networks,” to appear in IEEE Communications Letters.
  • H. Zhang, S.-L. Zhou, G. Y. Li, and N.-H. Xiu “A step function based recursion method for 0/1 deep neural networks,” to appear in Applied Mathematics and Computation.
  • J.-J. Huang, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Beam switching based beam design for high-speed train mmWave communications,” to appear in IEEE Transactions on Wireless Communications.
  • K.-D. Xu, S.-L. Zhou, and G. Y. Li, “Federated reinforcement learning for resource allocation in V2X networks,” to appear in IEEE Journal of Selected Topics in Signal Processing.
Overview
  • B.-L. Wang, F.-F. Gao, S. Jin, G. Y. Li, S. Sun, and T. S. Rappaport, “Spatial-wideband effect in massive MIMO with application to mmWave systems”, IEEE Communications Magazine, vol. 56, no. 12, pp. 134-141, December 2018.
  • W.-K. Tang, X.-Y. Chen, M.-Z. Chen, J.-Y. Dai, Y. Han, S. Jin, Q. Cheng, G. Y. Li, and T.-J. Cui, “On channel reciprocity in reconfigurable intelligent surface assisted wireless networks”, to appear in IEEE Wireless Communications.
  • L. Liang, H.-X. Peng, G. Y. Li, and X. M. Shen, “Vehicular communications: a physical layer perspective”, IEEE Transactions on Vehicular Technology, vol. 66, no. 12, pp. 10647-10659, December 2017.
  • H.-X. Peng, L. Liang, X.-M. Shen, and G. Y. Li, “Vehicular communications: a network layer perspective”, IEEE Transactions on Vehicular Technology, vol. 68, no. 2, pp. 1064-1078, February 2019.
  • Y.-W. Liu, Z.-J. Qin, Y.-L. Cai, Y. Gao, G. Y. Li, and A. Nallanathan, “UAV communications based on non-orthogonal multiple access”, IEEE Wireless Communications, vol. 26, no. 1, pp. 52-57, February 2019.
  • S.-Q. Zhang, S.-G. Xu, G. Y. Li, and E. Ayanoglu, “First 20 years of green radios”, IEEE Transactions on Green Communications and Networks, vol. 4, no. 1, pp.1-15, March 2020.
  • Z.-J. Qin, X.-W. Zhou, L. Zhang, Y. Gao, Y.-C. Liang, and G. Y. Li, “20 years of evolution from cognitive to intelligent communications”, IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 1, pp. 6-20, March 2020.
  • Z.-J. Qin, H. Ye, G. Y. Li, and B.-H. Juang, “Deep learning in physical layer communications”, IEEE Wireless Communications, vol. 26, no. 2, pp. 93-99, April 2019.
  • H.-T. He, S. Jin, C.-K. Wen, F.-F. Gao, G. Y. Li, and Z.-B. Xu, “Model-driven deep learning for physical layer communications”, IEEE Wireless Communications, vol. 26, no. 5, pp. 77-83, October 2019.
  • L. Liang, H. Ye, G.-D. Yu, and G. Y. Li, “Deep learning based wireless resource allocation with application in vehicular networks”, the Proceedings of the IEEE, vol. 108, no. 2, pp. 341-356, February 2020.
  • J.-J. Gao, J.-H. Wang, C.-K. Wen, S. Jin, and G. Y. Li, “Compression and acceleration of neural networks for communications”, IEEE Wireless Communications, vol. 27, no. 4, pp. 110-117, August 2020.
  • C.-H. Qi, P.-H. Dong, W.-Y. Ma, H. Zhang, Z.-C. Zhang, and G. Y. Li, “Acquisition of channel state information for mmWave massive MIMO: traditional and machine learning-based approaches”, Science China - Information Science, vol. 64, no. 8, August 2021.
  • Z.-J. Qin, G. Y. Li, and H. Ye “Federated learning and wireless communications,” IEEE Wireless Communications, vol. 28, no. 5, pp. 134 – 140, October 2021.

  • W.-K. Tang, X.-Y. Chen, M.-Z. Chen, J.-Y. Dai, Y. Han, S. Jin, Q. Cheng, G. Y. Li, and T.-J. Cui, “On channel reciprocity in reconfigurable intelligent surface assisted wireless networks,” IEEE Wireless Communications, vol. 28, no. 6, pp. 94 – 101, December 2021.

  • Tong and G. Y. Li “Nine critical issues in AI and wireless communications to ensure successful 6G,” IEEE Wireless Communications, vol. 29, no. 4, pp. 140 – 145, August 2022.

  • M.-Y. Lee, G.-D. Yu, H.-Y. Dai, and G. Y. Li, “Graph neural networks meet wireless communications: motivation, applications, and future directions,” IEEE Wireless Communications, vol. 29, no. 5, pp. 12 – 19, October 2022.

  • J.-J. Guo, C.-K. Wen, S. Jin, and G. Y. Li, “Overview of deep learning-based CSI feedback in massive MIMO systems,” IEEE Transactions on Communications, vol. 70, no. 12, pp. 8017-8045, December 2022.

  • Y.-C. Liang, Q.-Q. Zhang, E. G. Larsson, and G. Y. Li, “Symbiotic radio: Cognitive backscattering communications for future wireless networks”, IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 6, pp. 1242-1255, December 2020. 
  • P.-W. Jiang, C.-K. Wen, J. Shi, and G. Y. Li, “Wireless semantic transmission via revising modules in conventional communications,” IEEE Wireless Communications, vol. 30, no. 3, pp 28-34, June 2023.

  • C.-T. Guo. X.-J. Wang, L. Liang, G. Y. Li, “Age of information, latency, and reliability in intelligent vehicular networks,” IEEE Network Magazine, vol. 37, no. 6, pp. 109-116, November/December 2023.
  • J. Guo, H. Chen, B. Song, Y.-H. Chi, C. Yuan, F. R. Yu, G. Y. Li, and D. Niyato “Distributed task-oriented communication networks with multimodal semantic relay and edge intelligence,” IEEE Communications Magazine, vol. 62, no. 6, pp. 82-89, June 2024.
  • Z.-J. Qin, L. Liang, Z.-J. Wang, S. Jin, X.-M. Tao, W. Tong, G. Y. Li, “AI empowered wireless communications: from bits to semantics,” Proceedings of the IEEE, vol. 112, no. 7, pp. 621-652, July 2024.

 

Deep learning for physical layer processing in communications
  • H. Ye, G. Y. Li, and B.-H. F. Juang, “Power of deep learning for channel estimation and signal detection in OFDM systems”, IEEE Wireless Communications Letters, vol. 7, no. 1, pp. 114 – 117, February 2018.
  • H.-T. He, C.-K. Wen, S. Jin, and G. Y. Li, “Deep learning-based channel estimation for beamspace mmwave massive MIMO systems”, IEEE Wireless Communications Letters, vol. 7, no. 5, pp. 852 – 855, October 2018. 
  • T-Q. Wang, C.-K. Wen, S. Jin, and G. Y. Li, “Deep learning-based CSI feedback approaches for time-varying massive MIMO channels”, IEEE Wireless Communications Letters, vol. 8, No. 2, pp. 416-419, April 2019. 
  • P.-H. Dong, H. Zhang, G. Y. Li, N. Naderializadeh, and I. S. Gaspar, “Deep CNN based channel estimation for mmwave massive MIMO Systems”, IEEE Journal on Selected Topics in Signal Processing, vol. 13, no. 5, pp. 989 - 1000, September 2019. 
  • H.-T. He, C.-K. Wen, S. Jin, and G. Y. Li, “Model-driven deep learning for MIMO detection”, IEEE Transactions on Signal Processing, vol. 68, pp. 1702-1715, March 2020. 
  • J-J. Gao, C.-K. Wen, S. Jin, and G. Y. Li, “Convolutional neural network based multiple-rate compressive sensing for massive MIMO CSI feedback: design, simulation, and analysis”, IEEE Transactions on Wireless Communications, vol. 19, no. 4, pp. 2827-2840, April 2020. 
  • H. Ye, L. Liang, G. Y. Li, and B.-H. F. Juang, “Deep learning-based end-to-end wireless communication systems with GAN as unknown channels”, IEEE Transactions on Wireless Communications, vol. 19, no. 5, pp. 3133-3143, May 2020.
  • Y.-F. He, J. Zhang, S. Jin, C.-K. Wen, and G. Y. Li, “Model-driven DNN decoder for turbo codes: Design, simulation and experimental results”, IEEE Transactions on Communications, vol.68, no. 10, pp.6127-6140, October 2020. 
  • Q. Hu, F.-F. Gao, H. Zhang, Shi Jin, and G. Y. Li, “Deep learning for channel estimation: interpretation, performance, and comparison”, IEEE Transactions on Wireless Communications, vol. 20, no. 4, pp. 2398-2412, April 2021. 
  • H.-Q. Xie, Z.-J. Qin, G. Y. Li, and B.-H. F. Juang “Deep learning enabled semantic communication systems,” IEEE Transactions on Signal Processing, vol. 69, pp. 2663-2675, 2021. (Web of Science highly cited paper, in best readings at https://www.comsoc.org/publications/best-readings)

  • C.-H. Qi, P.-H. Dong, W.-Y. Ma, H. Zhang, Z.-C. Zhang, and G. Y. Li, “Acquisition of channel state information for mmWave massive MIMO: traditional and machine learning-based approaches,” Science China - Information Science, vol. 64, no. 8, August 2021.

  • H. Ye, L. Liang, G. Y. Li, and B.-H. F. Juang, “Deep learning based end-to-end wireless communication systems without pilots,” IEEE Transactions on Cognitive Communications and Networking, vol. 7, no. 3, pp. 702 – 714, September 2021.

  • P.-W. Jiang, S. Jin, C.-K. Wen, and G. Y. Li, “Dual CNN based channel estimation for MIMO-OFDM systems,” IEEE Transactions on Communications, vol. 69, no. 9, pp. 5859 – 5872, September 2021.

  • A. Mohammadian, C. Tellambura, and G. Y. Li, “Deep learning-based phase noise compensation in multicarrier systems,” to appear in IEEE Wireless Communications Letters, vol. 10, no. 10, pp. 2110 – 2114, October 2021.

  • C.-J. Wang, C.-K. Wen, S.-H. Tsai, S. Jin, and G. Y. Li, “Phase retrieval using expectation consistent signal recovery algorithm based on hypernetwork,” IEEE Transactions on Signal Processing, vol. 69, pp. 5770 – 5783, 2021.

  • J.-C. Shi, W.-J. Wang, X.-P. Yi, X.-Q. Gao, and G. Y. Li, “Deep learning-based robust precoding for massive MIMO,” IEEE Transactions on Communications, vol. 69, no. 11, pp. 7429 – 7443, November 2021.

  • P.-W. Jiang, T.-Q. Wang, B. Han, X.-X. Gao, J. Zhang, C.-K. Wen, S. Jin, and G. Y. Li, “AI-aided online adaptive OFDM receiver: Design and experimental results,” IEEE Transactions on Wireless Communications, vol. 20, no. 11, pp. 7756 – 7768, November 2021.

  • A. Mohammadian, C. Tellambura, and G. Y. Li, “Deep learning LMMSE joint channel, PN, and IQ imbalance estimator for multicarrier MIMO full-duplex systems,” IEEE Wireless Communications Letters, vol. 11, no. 1, pp. 111 – 115, January 2022.

  • M.-H. Chen, J.-J. Gao, C.-K. Wen, S. Jin, and G. Y. Li, “Deep learning-based implicit CSI feedback in massive MIMO,” IEEE Transactions on Communications, vol. 70, no. 2, pp. 935 – 950, February 2022.

  • H.-Q. Xie, Z.-J. Qin, and G. Y. Li, “Task-oriented multi-user semantic communications for VQA tasks,” IEEE Wireless Communications Letters, vol. 11, no. 3, pp. 553 – 557, March 2022.

  • J.-B. Gao, M. Hu, C.-J. Zhong, G. Y. Li, and Z.-Y. Zhang, “An attention-aided deep learning framework for massive MIMO channel estimation,” IEEE Transactions on Wireless Communications, vol. 21, no. 3, pp. 1823 – 1835, March 2022.

  • J.-B. Gao, C.-J. Zhong, G. Y. Li, and Z.-Y. Zhang, “Online deep neural network for optimization in wireless communications,” IEEE Wireless Communications Letters, vol. 11, no. 5, pp. 933 – 937, May 2022.

  • Y.-Z. Liu, O.-Y. Hu, Y.-L. Cai, G.-D. Yu, and G. Y. Li, “Deep-unfolding beamforming for intelligent reflecting surface assisted full-duplex systems,” IEEE Transactions on Wireless Communications, vol. 21, no. 7, pp. 4784 – 4800, July 2022.

  • J.-B. Gao, C.-J. Zhong, G. Y. Li, and Z.-Y. Zhang, “Deep learning-based channel estimation for massive MIMO with hybrid transceiver,” IEEE Transactions on Wireless Communications, vol. 21, no. 7, pp. 5162 – 5174, July 2022.

  • P.-W. Jiang, C.-K. Wen, S. Jin, and G. Y. Li, “Deep source-channel coding for sentence semantic transmission with HARQ,” IEEE Transactions on Communications, vol. 70, no. 8, pp. 5225 – 5240, August 2022.

  • Y.-Q. Zhang, J.-Y. Sun, J. Xue, Z.-B. Xu, and G. Y. Li, “Deep expectation-maximization for joint MIMO channel estimation and signal detection,” IEEE Transactions on Signal Processing, vol. 70, pp. 4483 – 4497, 2022.

  • W. Tong and G. Y. Li “Nine critical issues in AI and wireless communications to ensure successful 6G,” IEEE Wireless Communications, vol. 29, no. 4, pp. 140 – 145, August 2022.

  • S. Z. Hu, Y.-P. Duan, X.-M. Tao, G. Y. Li, and J.-H. Lu, “Facial image compression strategy based on human perception,” IEEE Signal Processing Letters, vol. 29, no. 20, pp. 2148 – 2152, 2022.

  • N. V. Huynh and G. Y. Li, “Transfer learning for signal detection in wireless networks,” IEEE Wireless Commun. Letters, vol. 11, no. 11, November 2022. 

  • J.-J. Guo, C.-K. Wen, S. Jin, and G. Y. Li, “Overview of deep learning-based CSI feedback in massive MIMO systems,” IEEE Transactions on Communications, vol. 70, no. 12, pp. 8017-8045, December 2022.

  • J.-Y. Liao, J.-H. Zhao, F.-F. Gao, and G. Y. Li, “Deep learning aided low complexity sphere decoding for MIMO detection,” IEEE Transactions on Communications. vol. 70, no. 12, pp. 8046-8059, December 2022.

  • P.-W. Jiang, C.-K. Wen, S. Jin, and G. Y. Li, “Wireless semantic communications for video conferencing,” IEEE Journal on Selected Areas in Communications. vol. 41, no. 1, pp. 230-244, January 2023.

  • F. Mirkarimi, C. Tellambura, and G. Y. Li, “Deep MMSE estimation for data detection,” IEEE Communications Letters, vol. 27, no. 1, pp. 180-184, January 2023.

  • H.-T. He, R. Wang, S. Jin, C.-K. Wen, and G. Y. Li, “Beamspace channel estimation in Terahertz communications: A model-driven unsupervised deep learning approach,” IEEE Transactions on Wireless Communications, vol. 22, no. 3, pp. 1808-1822, March 2023.

  • O.-Y. Wang, J.-B. Gao, and G. Y. Li, “Learning to adapt to current environment from past experience: Few-shot online learning in wireless communications,” IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 2, pp. 373-385, April 2023.

  • J.-B. Gao, C.-J. Zhong, G. Y. Li, J. B. Soriaga, and A. Behboodi, “Deep learning-based channel estimation for wideband hybrid mmwave massive MIMO,” IEEE Transactions on Communications, vol. 71, no. 6, pp. 3679-3693, June 2023.

  • P.-W. Jiang, C.-K. Wen, J. Shi, and G. Y. Li, “Wireless semantic transmission via revising modules in conventional communications,” IEEE Wireless Communications, vol. 30, no. 3, pp 28-34, June 2023.

  • J.-C. Shi, W. Zhong, X.-Q. Gao, and G. Y. Li, “Robust WMMSE precoder with deep learning design for massive MIMO,” IEEE Transactions on Communications, vol. 71, no. 7, pp. 3963-3976, July 2023.

  • B.-W. Zhang, H. Sifaou, and G. Y. Li, “CSI-fingerprinting indoor localization via attention-augmented residual convolutional neural network,” IEEE Transactions on Wireless Communications, vol. 22, no. 8, pp. 5583-5597, August 2023.
  • B.-W. Zhang, Z.-J. Qin, and G. Y. Li, “Semantic communications with variable-length coding for extended reality,” IEEE Journal on Selected Topics in Signal Processing, vol. 17, no. 5, pp. 1038-1051, September 2023.
  • Q. Hu, F.-F. Gao, H. Zhang, G. Y. Li, and Z.-B. Xu, “Understanding deep MIMO detection,” IEEE Transactions on Wireless Communications, vol. 22, no. 12, pp. 9626-9639, December 2023.
  • B. Zhang, Z, Qin, and G. Y. Li “Compression ratio learning and semantic communications for video imaging,” IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 3, pp. 312 – 324, April 2024.
  • J.-Y. Liao, J.-H. Zhao, F.-F. Gao, and G. Y. Li, “Deep learning aided low complex breath-first tree search for MIMO detection,” IEEE Transactions on Wireless Communications, vol. 23, no. 6, pp. 6266-6278, June 2024.
  • S. Zargari, C. Tellambura, A. Maaref, and G. Y. Li, “Deep conditional generative adversarial networks for efficient channel estimation in AmBC systems,” IEEE Transactions on Machine Learning in Communications and Networking, vol. 2, no. 6, pp. 805-822, 2024.
  • Y.-Z. Liu Z.-J. Qin, and G. Y. Li, “Energy-efficient distributed spiking neural network for wireless edge intelligence,” IEEE Transactions on Wireless Communications, vol. 23, no. 9, pp. 10683-10697, September 2024.
  • B. Lin, C.-B. Zhao, F.-F. Gao, G. Y. Li, J. Qian, and H. Wang, “Environment reconstruction based on multi-user selection and multi-modal fusion in ISAC,” IEEE Transactions on Wireless Communications, vol. 23, no. 10, pp. 15083-15095, October 2024.
  • S.-Z. Hu, Y.-P. Duan, X.-M. Tao, G. Y. Li, J.-H. Lu, G.-Y. Liu, and Z.-M. Zheng, C.-K. Pan, “Brain-inspired image perceptual quality assessment based on EEG: A QoE perspective,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 12, pp. 8424-8441, December 2024.
Intelligent wireless resource allocation
  • M.-Y. Lee, Y.-H. Xiong, G.-D. Yu, and Y. G. Li, “Deep neural networks for linear sum assignment problems”, IEEE Wireless Communications Letters, vol. 7, no. 6, pp. 962 – 965, December 2018.
  • H. Ye, G. Y. Li, B.-H. F. Juang, “Deep reinforcement learning based resource allocation for V2V communications”, IEEE Transactions on Vehicular Technology, vol. 68, no. 4, pp. 3163-3173, April 2019. 
  • L. Liang, H. Ye, and G. Y. Li, “Spectrum sharing in vehicular networks based on multi-agent reinforcement learning”, IEEE Journal on Selected Areas in Communications, vol. 37, no. 10, pp. 2282 - 2292, October 2019.
  • M.-Y. Lee, G.-D. Yu, and G. Y. Li, “Learning to branch: Accelerating resource allocation in wireless networks”, IEEE Transactions on Vehicular Technology, vol. 69, no. 1, pp. 958 - 970, January 2020.
  • L. Wang, H. Ye, L. Liang, and G. Y. Li, “Learn to compress CSI and allocate resources in vehicular networks”, IEEE Transactions on Communications, vol. 68, no. 6, pp. 3640 – 3653, June 2020. 
  • J.-C. Shi, W.-N. Wang, X.-P. Yi, J.-H. Wang, X.-Q. Gao, Q. Liu, and G. Y. Li, “Learning to compute ergodic rate for multi-cell scheduling massive MIMO”, IEEE Transactions on Wireless Communications, vol. 20, no. 2, pp. 785-797, February 2021. 
  • M.-Y. Lee, G.-D. Yu, and G. Y. Li, “Graph embedding based wireless link scheduling with few training samples”, IEEE Transactions on Wireless Communications, vol. 20, no. 4, pp. 2282-2294, April 2021.
  • L. Yan, Z.-J. Qin, Y.-Z. Li, R. Zhang, and G. Y. Li, “Resource allocation for semantic-aware networks,” IEEE Wireless Communications Letters, vol. 11, no. 7, pp. 1394 – 1398, July 2022.

  • M.-Y. Lee, G.-D. Yu, H.-Y. Dai, and G. Y. Li, “Graph neural networks meet wireless communications: motivation, applications, and future directions,” IEEE Wireless Communications, vol. 29, no. 5, pp. 12 – 19, October 2022.

  • C.-T. Guo. X.-J. Wang, L. Liang, G. Y. Li, “Age of information, latency, and reliability in intelligent vehicular networks,” IEEE Network Magazine, early access.

  • K.-D. Xu, H. Nguyen, and G. Y. Li, “Distributed-training-and-execution multi-agent reinforcement learning for power control in HetNet,” IEEE Transactions on Communications. vol. 71, no. 10, pp. 5893-5903, October 2023.
  • C.-T. Guo, Z.-C. Li, L. Liang, and G. Y. Li, “Reinforcement learning based dynamic power control for reliable wireless transmission,” IEEE Internet of Things Journal, vol. 10, no. 23, pp. 20868-20883, December 2023.
Distributed learning and federated learning
  •  Z-J. Qin, G. Y. Li, and H. Ye “Federated learning and wireless communications,” IEEE Wireless Communications, vol. 28, no. 5, pp. 134 – 140, October 2021. 
  • Ye, L. Liang, and G. Y. Li, “Decentralized learning with unreliable communications,” IEEE Journal on Selected Topics in Signal Processing, vol. 16, no. 3, pp. 487 – 500, April 2022.
  • S.-L. Zhou and G. Y. Li, “FedGiA: an efficient hybrid algorithm for federated learning,” IEEE Transactions on Signal Processing, vol. 71, pp. 1941-1508, 2023.

  • S-L. Zhou and G. Y. Li, “Federated learning via inexact ADMM,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 8, pp. 9699-9780, August 2023.

  • S-L. Zhou and G. Y. Li, “Exact penalty method for federated learning,” https://arxiv.org/abs/2111.10857.
  • Y.-Y. Guo, Z.-J. Qin, X.-M. Tao, and G. Y. Li, “Federated multi-view synthesizing for metaverse,” IEEE Journal on Selected Areas in Communications, vol. 42, no. 4, pp. 867-879, April 2024.
  • H. Sifaou and G. Y. Li, “Over-the-air federated learning over scalable cell-free massive MIMO,” IEEE Transactions on Wireless Communications, vol. 23, no. 5, pp. 4214-4227, May 2024
  • Z.-X. Chen, W.-Q. Yi, A. Nallanathan, and G. Y. Li, “Efficient wireless federated learning with partial model aggregation,” IEEE Transactions on Communications, vol. 72, no. 10, pp. 6271-6286, October 2024.
Few-short learning/fast adaptation
  • H. He, C.-K. Wen, S. Jin, and G. Y. Li, “Model-driven deep learning for MIMO detection,” IEEE Trans. Signal Process, vol. 68, pp. 1702–1715, Mar. 2020.
  • O.-Y. Wang, J.-B. Gao, and G. Y. Li, “Learning to adapt to current environment from past experience: Few-shot online learning in wireless communications,” IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 2, pp. 373-385, April 2023.
  • X.-Y. Wei, B.-H. F. Juang, O.-Y. Wang, S.-L. Zhou, and G. Y. Li, “Accretionary learning with deep neural networks with application,” IEEE Transactions on Cognitive Communications and Networking, vol. 10, no. 2, pp. 660-673, April 2024.
  • O. Wang, S. Zhou, and G. Y. Li, “Effective adaptation into new environment with few shots: Applications to OFDM receiver design,” Proc. IEEE MLSP’2023, Rome, Italy, 2023.
  • O. Wang, S. Zhou, and G. Y. Li, “New environment adaptation with few shots for OFDM receiver and mmWave beamforming,”arXiv preprint arXiv:2310.12343, 2023.
Other topics
  • B.-L. Wang, F.-F. Gao, S. Jin, H. Lin, and G. Y. Li, “Spatial- and frequency-wideband effects in massive MIMO”, IEEE Transactions on Signal Processing, vol. 66, no. 13, pp. 3393 – 3406, July 2018. 
  • B.-L. Wang, X. Li, F.-F. Gao, and G. Y. Li, “Power leakage elimination for wideband mmwave massive MIMO: An energy focusing window approach”, IEEE Transactions on Signal Processing, vol. 67, no. 21, pp. 5479 - 5494, November 2019. 
  • B.-L. Wang, M.-N. Jian, F.-F. Gao, G. Y. Li, and H. Lin, “Beam squint and channel estimation for millimeter-wave massive MIMO-OFDM systems”, IEEE Transactions on Signal Processing, vol. 67, no. 23, pp. 5893 – 5908, December 2019.
  • F.-F. Gao, B.-L. Wang, C.-W. Xing, J.-P. An, and G. Y. Li, “Wideband beamforming for hybrid massive MIMO terahertz communications”, IEEE Journal on Selected Areas in Communications, vol. 39, no. 6, pp. 1725-1740, June 2021. 
  • W.-Q. Wu, X.-Q. Gao, C. Sun, and G. Y. Li, “Shallow underwater acoustic massive MIMO communications”, IEEE Transactions on Signal Processing, vol. 20, no. 2, pp. 1124-1139, 2021.
  • J.-K. Ren, G.-D. Yu, Y.-H. He, and G. Y. Li, “Collaborative cloud and edge computing for latency minimization”, IEEE Transactions on Vehicular Technology, vol. 68, no. 5, pp. 5031-5044, May 2019. 
  • Q.-Y. Hu, Y.-L. Cai, G.-D. Yu, Z.-J. Qin, M.-J. Zhao, and G. Y. Li, “Joint offloading and trajectory design for UAV-enabled mobile edge computing systems”, IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1897-1892, April 2019. 
  • Y.-C. Liang, Q.-Q. Zhang, E. G. Larsson, and G. Y. Li, “Symbiotic radio: Cognitive backscattering communications for future wireless networks”, IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 6, pp. 1242-1255, December 2020. 
  • W.-Q. Wu, X.-Q. Gao, C. Sun, and G. Y. Li, “Shallow underwater acoustic massive MIMO communications,” IEEE Transactions on Signal Processing, vol. 20, no. 2, pp. 1124-1139, 2021.

  • R. Liu, G.-D. Yu, J.-T. Yuan, G. Y. Li, “Resource management for millimeter-wave ultra-reliable and low-latency communications,” IEEE Transactions on Communications, vol. 69, no. 2, pp. 1094-1108, February 2021.

  • C.-T. Guo, W. He, and G. Y. Li, “Optimal fairness-award resource supply and demand management for mobile edge computing,” IEEE Wireless Communications Letters, vol. 10, no. 3, pp. 678-682, March 2021.

  • F.-F. Gao, B.-L. Wang, C.-W. Xing, J.-P. An, and G. Y. Li, “Wideband beamforming for hybrid massive MIMO terahertz communications,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 6, pp. 1725-1740, June 2021.

  • M. A. ElMossallamy, K. G. Seddik, W. Chen, L. Wang, G. Y. Li, and H. Zhu, “RIS optimization on complex circle manifold for interference mitigation in interference channels,” IEEE Transactions on Vehicular Technology, vol. 70, no. 6, pp. 6184 – 6189, June 2021.

  • X. Yang, S. Jin, G. Y. Li, and X. Li, “Asymmetrical uplink and downlink transceivers in massive MIMO systems,” IEEE Transactions on Vehicular Technology, vol. 70, no. 11, pp. 11632 – 11647, November 2021.

  • W.-K. Tang, X.-Y. Chen, M.-Z. Chen, J.-Y. Dai, Y. Han, S. Jin, Q. Cheng, G. Y. Li, and T.-J. Cui, “On channel reciprocity in reconfigurable intelligent surface assisted wireless networks,” IEEE Wireless Communications, vol. 28, no. 6, pp. 94 – 101, December 2021.

  • S.-L. Zhou, Z.-Y. Luo, N.-H. Xiu, and G. Y. Li, “Computing one-bit compressive sensing via double-sparsity constrained optimization,” IEEE Transactions on Signal Processing, vol. 70, pp. 1593 – 1608, 2022.

  • X.-L. Yu, A.-A. Lu, X.-Q. Gao, G. Y. Li G.-R. Ding, and C.-X. Wang, “HF skywave massive MIMO communication,” IEEE Transactions on Wireless Communications, vol. 21, no. 4, pp. 2769 – 2785, April 2022.

  • C.-H. Qi, Q. Liu, X.-H. Yu, and G. Y. Li, “Hybrid precoding for mixture use of phase shifters and switches in mmWave massive MIMO,” IEEE Transactions on Communications, vol. 70, no. 6, pp. 4121 – 4133, June 2022.

  • D. Shi, L.-F. Song, W.-Q. Zhou, X.-Q. Gao, C.-X. Wang, and G. Y. Li, “Channel acquisition for HF skywave massive MIMO-OFDM communications,” IEEE Transactions on Wireless Communications, vol. 22, no. 6, pp. 4074-4089, June 2023.

  • X.-L. Yu, X.-Q. Gao, A.-A. Liu, J.-L. Zhang, H.-B. Wu, and G. Y. Li, “Robust precoding for HF skywave massive MIMO,” IEEE Transactions on Wireless Communications, vol. 22, no. 10, pp. 6691-6705, October 2023.
  • X.-L. Yu, A.-A. Lu, C. Sun, X.-Q. Gao, and G. Y. Li, “Downlink transmitter design with statistical CSI for HF skywave massive MIMO communication,” IEEE Transactions on Vehicular Technology, vol. 72, no. 11, pp. 14396-14410, November 2023.
  • S.-X. Wang, W. Dai, H.-W. Wang, and G. Y. Li, “Robust waveform design for integrated sensing and communication,” IEEE Transactions on Signal Processing, vol. 72, no. 7, pp. 3122-3138, 2024.
  • K.-J. Chen, C.-H. Qi, C.-X. Wang, and G. Y. Li, “Beam training and tracking for extremely large-scale MIMO communications,” IEEE Transactions on Wireless Communications, vol. 23, no. 5, pp. 5048-5062, May 2024.
  • K.-J. Chen, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Near-field multiuser communications based on sparse arrays,” Journal of Selected Topics in Signal Processing, vol. 18, no. 4, pp. 619-632, May 2024.
  • K.-J. Chen, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Triple-refine hybrid-field beam training for mmWave extremely large-scale MIMO,” IEEE Transactions on Wireless Communications, vol. 23, no. 8, pp. 8556-8570, August 2024.
  • C. Xu, L.-P. Xiang, S. Sugiura, R. G. Maunder, L.-L. Yang, D. Niyato, G. Y. Li, R. Schober, and L. Hanzo, “Noncoherent orthogonal time frequency space modulation,” IEEE Transactions on Wireless Communications, vol. 23, no. 8, pp. 10072-10090, August 2024.
  • M. A. ElMossallamy, Z. Han, M. Pan, R. Jantti, K. G. Seddik, G. Y. Li, “Noncoherent frequency shift keying for ambient backscatter over OFDM signals,” IEEE Open Journal of the Communications Society, vol. 5, pp. 5219-5231, 2024.
  • D. Shi, L.-F. Song, X.-Q. Gao, J.-H. Wang, M. Bengtsson, G. Y. Li, and X.-G. Xia, “Beam structured channel estimation for HF skywave massive MIMO-OFDM communications,” IEEE Transactions on Wireless Communications, vol. 23, no. 11, pp. 16301-16315, November 2024.

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London SW7 2AZ, UK
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London W12 7TA, UK

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