( en | de | ru )

 

Disambiguation of "Fang, Xuming"

Author of the publication

copydeleteadd this publication to your clipboard
Reliable transmission schemes for train control information in high-speed railway.

, and . IWSDA, page 150-153. IEEE, (2013)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Xuming Luan

Xuming Zhang

Xuming Wang

Fang-Fang Tang

Xing Fang

 

Other publications of authors with the same name

Joint Optimization of Resource Allocation and Trajectory Control for Mobile Group Users in Fixed-Wing UAV-Enabled Wireless Network., , , and . IEEE Trans. Wirel. Commun., 23 (2): 1608-1621 (February 2024)Utility-based dynamic revenue pricing scheme for wireless operators., , and . WCNC, page 4612-4617. IEEE, (2013)Dynamic channel selections and performance analysis for High-Speed Train WiFi network., , , , and . HMWC, page 31-35. IEEE, (2015)Multi-connectivity Enabled User-centric Association in Ultra-Dense mmWave Communication Networks., , , , , and . VTC2023-Spring, page 1-6. IEEE, (2023)A Suboptimal Resource Allocation Algorithm for OFDMA-Based Multi-hop Cellular Networks., , and . MSN, page 396-402. IEEE Computer Society, (2009)A spectrum etiquette protocol and interference coordination for LTE in unlicensed bands (LTE-U)., and . ICC Workshops, page 2338-2343. IEEE, (2015)Cross-Layer Routing with Link Quality and Stability-Aware in ITS Hybrid Wireless Mesh Networks., and . ALPIT, page 304-308. IEEE Computer Society, (2007)Learning-Based mmWave V2I Environment Augmentation through Tunable Reflectors., , , , and . GLOBECOM, page 1-6. IEEE, (2019)Coalition game for user association and bandwidth allocation in ultra-dense mmWave networks., , , and . ICCC, page 1-5. IEEE, (2017)Collaborative Optimization of Wireless Communication and Computing Resource Allocation based on Multi-Agent Federated Weighting Deep Reinforcement Learning., and . CoRR, (2024)