A5102602531- Radar Systems and Signal Processing
- Cognitive Computing and Networks
- Satellite Communication Systems
- Telecommunications and Broadcasting Technologies
- Cognitive Radio Networks and Spectrum Sensing
- Wireless Communication Networks Research
- Image and Signal Denoising Methods
- Robotics and Automated Systems
- Advanced Data Compression Techniques
- Indoor and Outdoor Localization Technologies
- Image and Video Quality Assessment
- Advanced Image Processing Techniques
Tsinghua University
2023-2024
Semantic communication has shown great potential in boosting the effectiveness and reliability of communications. However, its systems to date are mostly enabled by deep learning, which requires demanding computing resources. This article proposes a framework for networks semantic system, aiming offer sufficient resources processing transmission. Key techniques including sampling reconstruction, semantic-channel coding, semantic-aware resource allocation optimization introduced based on...
The sixth-generation (6G) network is expected to provide both communication and sensing (C&S) services. However, spectrum scarcity poses a major challenge the harmonious coexistence of C&S systems. Without effective cooperation, interference resulting from sharing impairs performance This paper addresses within distributed network. Different traditional schemes that require pilot-based high-frequency interactions between systems, we introduce third party named radio map large-scale channel...
The enormous data volume of video poses a significant burden on the network. Particularly, transferring high-definition surveillance videos to cloud consumes amount spectrum resources. To address these issues, we propose transmission system enabled by end-cloud computing. Specifically, cameras actively down-sample original and then redundant frame elimination module is employed further reduce videos. Then develop key-frame assisted super-resolution model reconstruct high-quality at side....
Semantic communication has shown great potential in boosting the effectiveness and reliability of communications. However, its systems to date are mostly enabled by deep learning, which requires demanding computing resources. This article proposes a framework for networks semantic system, aiming offer sufficient resources processing transmission. Key techniques including sampling reconstruction, semantic-channel coding, semantic-aware resource allocation optimization introduced based on...
The enormous data volume of video poses a significant burden on the network. Particularly, transferring high-definition surveillance videos to cloud consumes amount spectrum resources. To address these issues, we propose transmission system enabled by end-cloud computing. Specifically, cameras actively down-sample original and then redundant frame elimination module is employed further reduce videos. Then develop key-frame assisted super-resolution model reconstruct high-quality at side....