9 papers
Resolving Multi-Target Association in OFDM-based ISAC via Vision-aided Multi-Modal Learning
Meng Hua, Chenghong Bian, Deniz Gunduz
Orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems commonly extract target parameters by peak-searching a delay-Doppler map…
In-Context Learning for Deep Joint Source-Channel Coding Over MIMO Channels
Meng Hua, Wenjing Zhang, Chenghong Bian +1
Large language models have demonstrated the ability to perform \textit{in-context learning} (ICL), whereby the model performs predictions by directly mapping the query and a few ex…
Unsourced Random Access: A Comprehensive Survey
Mert Ozates, Mohammad Javad Ahmadi, Mohammad Kazemi +2
Multiple access communication systems enable numerous users to share common communication resources, playing a crucial role in wireless networks. With the emergence of the sixth ge…
Multimodal LLM Integrated Semantic Communications for 6G Immersive Experiences
Yusong Zhang, Yuxuan Sun, Lei Guo +3
6G networks promise revolutionary immersive communication experiences including augmented reality (AR), virtual reality (VR), and holographic communications. These applications dem…
Zero-Shot Semantic Communication with Multimodal Foundation Models
Jiangjing Hu, Haotian Wu, Wenjing Zhang +4
Most existing semantic communication (SemCom) systems use deep joint source-channel coding (DeepJSCC) to encode task-specific semantics in a goal-oriented manner. However, their re…
Deep Joint Source Channel Coding for Privacy-Aware End-to-End Image Transmission
Mehdi Letafati, Seyyed Amirhossein Ameli Kalkhoran, Ecenaz Erdemir +3
Deep neural network (DNN)-based joint source and channel coding is proposed for privacy-aware end-to-end image transmission against multiple eavesdroppers. Both scenarios of collud…