1 citations · 1 across the 3 of their papers we have counts for
9 papers
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…
CNNs in the Air via Reconfigurable Intelligent Surfaces
Meng Hua, Haotian Wu, Deniz Gündüz
This paper introduces AirCNN, a novel paradigm for implementing convolutional neural networks (CNNs) via over-the-air (OTA) analog computation. By leveraging multiple reconfigurabl…
Communication via Sensing
Mohammad Kazemi, Tolga M. Duman, Deniz Gündüz
We present an alternative take on the recently popularized concept of `\textit{joint sensing and communications}', which focuses on using communication resources also for sensing.…
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…