Semantic Communications with Variable-Length Coding for Extended Reality
Bowen Zhang, Zhijin Qin, Geoffrey Ye Li
备注：
1. Update the performance of VL-SCC in Fig8. under new rate allocation architecture 2. Give a fair comparison between VL-SCC and SCC in Fig9. 3. fix the typo of LDPC rate (1/3 changed to 2/3) 4. Reduce L=32 to 16, and update the bpp
Wireless extended reality (XR) has attracted wide attentions as a promising technology to improve users' mobility and quality of experience. However, the ultra-high data rate requirement of wireless XR has hindered its development for many years. To overcome this challenge, we develop a semantic communication framework, where semantically-unimportant information is highly-compressed or discarded in semantic coders, significantly improving the transmission efficiency. Besides, considering the fact that some source content may have less amount of semantic information or have higher tolerance to channel noise, we propose a universal variable-length semantic-channel coding method. In particular, we first use a rate allocation network to estimate the best code length for semantic information and then adjust the coding process accordingly. By adopting some proxy functions, the whole framework is trained in an end-to-end manner. Numerical results show that our semantic system significantly outperforms traditional transmission methods and the proposed variable-length coding scheme is superior to the fixed-length coding methods.
Integrated Sensing and Semantic Communication with Adaptive Source-Channel Coding
Guangdong Provincial Key Laboratory of Future Networks of Intelligence, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳） 广东省未来网络智能重点实验室）；Shenzhen Future Network of Intelligence Institute（深圳未来网络智能 institute）
Adaptive Source-Channel Coding for Semantic Communications
Shenzhen Future Network of Intelligence Institute（深圳未来网络智能研究所）；School of Science and Engineering（科学与工程学院）；Guangdong Provincial Key Laboratory of Future Networks of Intelligence（广东省未来网络智能重点实验室）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Department of Electrical and Electronic Engineering（电子与电气工程系）；University of Hong Kong（香港大学）；School of Information and Communication Engineering（信息与通信工程学院）；State Key Laboratory of Networking and Switching Technology（网络与交换技术国家重点实验室）；Beijing University of Posts and Telecommunications（北京邮电大学）
Adaptive Source-Channel Coding for Bi-static Integrated Sensing and Semantic Communications
Beijing University of Posts and Telecommunications（北京邮电大学）；Pengcheng Laboratory（鹏城实验室）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Institute for Advanced Study, the University of Electronic Science and Technology of China（电子科技大学深圳高等研究院）；Shenzhen Future Network of Intelligence Institute（深圳未来网络智能研究所）
Deep Joint Semantic Coding and Beamforming for Near-Space Airship-Borne Massive MIMO Network
School of Information and Electronics, Beijing Institute of Technology（北京理工大学信息与电子学院）；Beijing National Research Center for Information Science and Technology（北京信息科学与技术国家研究中心）；Tsinghua University（清华大学）；Tsinghua Shenzhen International Graduate School（清华大学深圳国际研究生院）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）；Aristotle University of Thessaloniki（亚里士多德大学）；Artificial Intelligence & Cyber Systems Research Center, Lebanese American University (LAU)（黎巴嫩美国大学人工智能与网络系统研究中心）；School of Electronics and Computer Science, University of Southampton（南安普顿大学电子与计算机科学学院）
Joint Semantic-Channel Coding and Modulation for Token Communications
Department of Electronic Engineering, Tsinghua University（电子工程系，清华大学）；State Key Laboratory of Space Network and Communications（空间网络与通信国家重点实验室）；State Key Laboratory of Mobile Network and Mobile Multimedia Technology（移动网络与移动多媒体技术国家重点实验室）；ZTE Corporation（中兴通讯）；School of Computer Science and Technology, Xinjiang University（计算机科学与技术学院，新疆大学）
