Selected recent publications

Recent publications

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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, early access.

  • Z.-Z. Wang, Z.-J. Qin, X.-M. Tao, C.-K. Pan, G.-Y. Liu, and G. Y. Li, “Deep learning enabled semantic communications with speech recognition and synthesis,” IEEE Transactions on Wireless Communications, early access.

  • 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, early access.

  • Q.-Y. Hu, G.-Y. Zhang, Z.-J. Qin, Y.-L. Cai, G.-D. Yu, and G. Y. Li, “Robust semantic communications with masked VQ-VAE enabled codebook,” IEEE Transactions on Wireless Communications, early access.

  • Q. Hu, F.-F. Gao, H. Zhang, G. Y. Li, and Z.-B. Xu, “Understanding deep MIMO detection,” IEEE Transactions on Wireless Communications, early access.

  • 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, early access.

  • 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, 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. early access.

  • K.-J. Chen, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Simultaneous beam training and target sensing in ISAC systems with RIS,” to appear in IEEE Transactions on Wireless Communications.

  • 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,”  https://arxiv.org/abs/2111.10857.

  • Z.-J. Qin, X.-M. Tao, J.-H. Lu, W. Tong, and G. Y. Li, “Semantic communications: Principles and challenges,”  https://arxiv.org/abs/2201.01389.

Overview

  • Z.-J. Qin, J.-C. Fan, Y.-W. Liu, Y. Gao, and G. Y. Li, “Sparse representation for wireless communications, a compressive sensing approach”, IEEE Signal Processing Magazine, vol. 35, no. 3, pp. 40-58, May 2018.
  • Y.-L. Cai, Z.-J. Qin, F.-Y. Cui, G. Y. Li, and J. A. McCann, “Modulation and multiple access for 5G networks”, IEEE Communications Surveys and Tutorials, vol. 20, no. 1, pp. 629-646, First Quarter, 2018.
  • 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.

  • 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, early access.

  • Y.-M. Ge, J.-C. Fan, G. Y. Li, and L.-C. Wang, “Intelligent reflecting surface enhanced UAV communications: advances, challenges, and prospects,” IEEE Wireless Communications, early access.

  • Z.-J. Qin, X.-M. Tao, J.-H. Lu, W. Tong, and G. Y. Li, “Semantic communications: Principles and challenges,”  https://arxiv.org/abs/2201.01389.

 

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, early access.

  • Z.-Z. Wang, Z.-J. Qin, X.-M. Tao, C.-K. Pan, G.-Y. Liu, and G. Y. Li, “Deep learning enabled semantic communications with speech recognition and synthesis,” IEEE Transactions on Wireless Communications, early access.

  • Q.-Y. Hu, G.-Y. Zhang, Z.-J. Qin, Y.-L. Cai, G.-D. Yu, and G. Y. Li, “Robust semantic communications with masked VQ-VAE enabled codebook,” IEEE Transactions on Wireless Communications, early access.

  • Q. Hu, F.-F. Gao, H. Zhang, G. Y. Li, and Z.-B. Xu, “Understanding deep MIMO detection,” IEEE Transactions on Wireless Communications, early access.

  • 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, early access.

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, early access.

  • C.-T. Guo, Z.-C. Li, L. Liang, and G. Y. Li, “Reinforcement learning based dynamic power control for reliable wireless transmission,” to appear in IEEE Internet of Things Journal.

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.

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, early access.

  • 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, early access.

  • K.-J. Chen, C.-H. Qi, O. A. Dobre, and G. Y. Li, “Simultaneous beam training and target sensing in ISAC systems with RIS,” to appear in IEEE Transactions on Wireless Communications.