Semantic Communications for Wireless Sensing: RIS-aided Encoding and Self-supervised Decoding
Published: IEEE Journal on Selected Areas in Communications
We propose the inverse semantic communications as a new paradigm. Instead of extracting semantic information from messages, we aim to encode the taskrelated source messages into a hyper-source message for data transmission or storage. Following this paradigm, we design an inverse semantic-aware wireless sensing framework with three algorithms for data sampling, reconfigurable intelligent surface (RIS)-aided encoding, and self-supervised decoding, respectively. Using the sensing data collected from real-world, we show that our framework can reduce the data volume by 95% compared to that before encoding, without affecting the accomplishment of sensing tasks.
Citation: Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, and Junshan Zhang. "Semantic Communications for Wireless Sensing: RIS-aided Encoding and Self-supervised Decoding." IEEE Journal on Selected Areas in Communications, arXiv:2211.12727 (2022).
Paper Link: https://arxiv.org/abs/2211.12727