Výsledky vyhľadávania - "joint source channel coding"

A Deep Variational Approach to Multiterminal Joint Source-Channel Coding Based on Information Bottleneck Principle

Autori: Shayan Hassanpour Matthias Hummert Dirk Wübben a ďalší

Zdroj: IEEE Open Journal of the Communications Society, Vol 6, Pp 4462-4475 (2025)

Predmety: information bottleneck, Telecommunication, auto-encoders, deep learning, joint source-channel coding, TK5101-6720, Transportation and communications, 6G, HE1-9990

Prístupová URL adresa: https://doaj.org/article/c32e49cb262e4f2c87bf9119b8db9ef5

Rateless Deep Joint Source Channel Coding for 3D Point Cloud

Autori: Shoichi Ibuki Tsubasa Okamoto Takuya Fujihashi a ďalší

Zdroj: IEEE Access, Vol 13, Pp 39585-39599 (2025)

Predmety: Point cloud, deep joint source-channel coding, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Prístupová URL adresa: https://doaj.org/article/3ca81d66e6c94dc0bce5808581aebfea

Joint Source-Channel Coding for Multi-Channel Vibrotactile Sensors

Autori: Tom Ogura Shogo Kitamura Takuya Fujihashi a ďalší

Zdroj: IEEE Access, Vol 13, Pp 7736-7745 (2025)

Predmety: Electrical engineering. Electronics. Nuclear engineering, Multi-channel vibrotactile signal, joint source-channel coding (JSCC), TK1-9971

Prístupová URL adresa: https://doaj.org/article/9ebde4d9d23d4b05a3895ad08d5f47d5

Visually Secure Deep Joint Source-Channel Coding with Chaotic Map Against Deep Known-Plaintext Attack

Autori: Yuyang Fu Katsuya Suto

Zdroj: IEEE Open Journal of the Communications Society, Vol 6, Pp 1847-1858 (2025)

Predmety: Chaotic map encryption, Telecommunication, image transmission, deep joint source-channel coding, TK5101-6720, visual security, Transportation and communications, known-plaintext attack, HE1-9990

Prístupová URL adresa: https://doaj.org/article/440ad10f799b45a693f7cf187b8208c2

Universal Joint Source-Channel Coding for Modulation-Agnostic Semantic Communication

Autori: Yoon Huh Hyowoon Seo Wan Choi

Zdroj: IEEE Journal on Selected Areas in Communications. 43:2560-2574

Predmety: Signal Processing (eess.SP), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing

Prístupová URL adresa: http://arxiv.org/abs/2405.10749

Residual Cross-Attention Transformer-Based Multi-User CSI Feedback With Deep Joint Source-Channel Coding

Autori: Hengwei Zhang Minghui Wu Li Qiao a ďalší

Zdroj: IEEE Wireless Communications Letters. 14:2481-2485

Predmety: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/2505.19465

A Deep Joint Source-Channel Coding Scheme for Hybrid Mobile Multi-Hop Networks

Autori: Chenghong Bian Yulin Shao Deniz Gündüz

Zdroj: IEEE Journal on Selected Areas in Communications. 43:2543-2559

Predmety: Signal Processing (eess.SP), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing

Prístupová URL adresa: http://arxiv.org/abs/2405.09698

Adaptive Deep Joint Source-Channel Coding for One-to-Many Wireless Image Transmission

Autori: Lei Luo Ziyang He Junjie Wu a ďalší

Zdroj: IEEE Transactions on Broadcasting. 71:914-929

Transformer-Based Task-Oriented Joint Source-Channel Coding for Edge AI Agent

Autori: Jian Du Changyang She Zhaoquan Geng a ďalší

Zdroj: 2025 IEEE/CIC International Conference on Communications in China (ICCC Workshops). :1-6

A Learning-based Joint Source-Channel Coding Approach for Wireless Covert Image Transmission

Autori: Chao Qi Yi Si Shuo Shao

Zdroj: 2025 IEEE/CIC International Conference on Communications in China (ICCC Workshops). :1-6

A Novel Lightweight Deep Joint Source-Channel Coding Framework: Using 1D-CNN for SNR and Compression Rate Adaptation

Autori: Teng Guo Shushi Gu Yaonan Wu a ďalší

Zdroj: 2025 IEEE/CIC International Conference on Communications in China (ICCC). :1-6

Deep Joint Source-Channel Coding Based on Signal Space Diversity and Correlation Interleaving

Autori: Qinglin Liu Haotai Liang Yucheng Liu a ďalší

Zdroj: 2025 IEEE/CIC International Conference on Communications in China (ICCC Workshops). :1-6

Enhancing Deep Joint Source-Channel Coding in Varying Wireless Channels via MoE Approach

Autori: Yuecheng Cao Tianjian Dang Shuo Shao a ďalší

Zdroj: 2025 IEEE/CIC International Conference on Communications in China (ICCC). :1-6

Robust OFDM-Guided Joint Source-Channel Coding for Multipath High-Mobility Channels

Autori: Feng Shi Haiwen Niu Luhan Wang a ďalší

Zdroj: IEEE Communications Letters. 29:1764-1768

Efficient Joint Source Channel Coding and Decoding Method for Remote Sensing Image Transmission

Autori: Zhongqiang Zhang Qi Qiu Fanyang Meng a ďalší

Zdroj: 2025 4th International Conference on Electronics, Integrated Circuits and Communication Technology (EICCT). :436-440

Learning Joint Source-Channel Coding for Wireless Image Transmission: A Benchmark

Autori: Tianjian Dang Sixian Wang Zhenyu Liu a ďalší

Zdroj: 2025 IEEE 26th International Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC). :1-5

Deep Joint Source Channel Coding with Semantic Precoder for Multi-Task Multi-User MIMO Systems

Autori: Weiran Jiang Wei Chen Bo Ai

Zdroj: 2025 IEEE 26th International Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC). :1-5

Homomorphic Encryption-Based Joint Source-Channel Coding for Semantic Communications

Autori: Yifan Yuan Bizhu Wang Rui Meng a ďalší

Zdroj: 2025 IEEE 26th International Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC). :1-5

A Progressive Approach to Joint Source-Channel Coding for Image Super-Resolution Task in Semantic Communications

Autori: Zhen Huang Yunjian Jia Wanli Wen a ďalší

Zdroj: IEEE Wireless Communications Letters. 14:2099-2103

DD-JSCC: Dynamic Deep Joint Source-Channel Coding for Semantic Communications

Autori: Raha, Avi Deb Adhikary, Apurba Gain, Mrityunjoy a ďalší

Zdroj: ICC 2025 - IEEE International Conference on Communications. :3754-3759

Predmety: Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Networking and Internet Architecture

Prístupová URL adresa: http://arxiv.org/abs/2507.20467