Optimal Spectrum Reuse of V2V Communications for Maximizing Average Throughput in Vehicular Ad Hoc Networks. - Yang Yang 007; Honglin Xiang; Gang He; Jingfei Huang; Qing Yan (ICCC, 2021)

Multi-Agent Power and Resource Allocation for D2D Communications: A Deep Reinforcement Learning Approach. - Honglin Xiang; Jingyi Peng; Zhen Gao 001; Lingjie Li; Yang Yang 007 (VTC Fall, 2022)

Hybrid Spectrum Access for V2V Heterogeneous Networks with Deep Reinforcement Learning. - Jingfei Huang; Jingyi Peng; Honglin Xiang; Lingjie Li; Yang Yang 007 (WCSP, 2022)

Multi-Agent Deep Reinforcement Learning-Based Power Control and Resource Allocation for D2D Communications. - Honglin Xiang; Yang Yang 007; Gang He; Jingfei Huang; Dazhong He (IEEE Wirel. Commun. Lett., 2022)

Satellite-Based Analysis of Spatiotemporal Wildfire Pattern in the Mongolian Plateau. - Yulong Bao; Masato Shinoda; Kunpeng Yi; Xiaoman Fu; Long Sun; Elbegjargal Nasanbat; Na Li; Honglin Xiang; Yan Yang; Bulgan Davdai; Banzragch Nandintsetseg (Remote. Sens., 2023)

Deep Reinforcement Learning-Based Downlink Beamforming and Phase Optimization for RIS-Aided Communication System. - Lingjie Li; Yang Yang 007; Lingyan Bao; Zhen Gao 001; Yongpeng Wu 001; Honglin Xiang (IEEE Wirel. Commun. Lett., 2023)

Deep Reinforcement Learning-Based Energy Consumption Optimization for Peer-to-Peer (P2P) Communication in Wireless Sensor Networks. - Jinyu Yuan; Jingyi Peng; Qing Yan; Gang He; Honglin Xiang; Zili Liu (Sensors, 2024)

Frequency transformer with local feature enhancement for improved vehicle re-identification. - Honglin Xiang; Jiahao Wang; Yulong Sun; Ming Ye (J. Supercomput., 2025)