4 papers · 1 filter
Deep Reinforcement Learning-Based Resource Allocation for Hybrid Bit and Generative Semantic Communications in Space-Air-Ground Integrated Networks
Chong Huang, Xuyang Chen, Gaojie Chen +3
In this paper, we introduce a novel framework consisting of hybrid bit-level and generative semantic communications for efficient downlink image transmission within space-air-groun…
Fair Resource Allocation For Hierarchical Federated Edge Learning in Space-Air-Ground Integrated Networks via Deep Reinforcement Learning with Hybrid Control
Chong Huang, Gaojie Chen, Pei Xiao +2
The space-air-ground integrated network (SAGIN) has become a crucial research direction in future wireless communications due to its ubiquitous coverage, rapid and flexible deploym…
Reconfigurable Intelligent Surface Empowered Full Duplex Systems: Opportunities and Challenges
Chong Huang, Yun Wen, Long Zhang +3
Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology in wireless communications. Simultaneously transmitting and reflecting RIS (STAR-RISs) in particul…
Joint Offloading and Resource Allocation for Hybrid Cloud and Edge Computing in SAGINs: A Decision Assisted Hybrid Action Space Deep Reinforcement Learning Approach
Chong Huang, Gaojie Chen, Pei Xiao +3
In recent years, the amalgamation of satellite communications and aerial platforms into space-air-ground integrated network (SAGINs) has emerged as an indispensable area of researc…