Understand-Before-Talk (UBT): A Semantic Communication Approach to 6G Networks

In Shannon theory, semantic aspects of communication were identified but considered irrelevant to the technical problems. Semantic (SC) techniques have recently attracted renewed research interests in $\rm 6^{th}$ generation (6G) wireless, because they capability support an efficient interpretation significance and meaning intended by a sender (or accomplishment goal) when dealing with multi-modal data such as videos, images, audio, text messages, so on, which would be case for various applications intelligent transportation systems where each autonomous vehicle needs deal real-time videos from number sensors including radars. To this end, most emerging SC works focus on specific types employ sophisticated machine learning models deep neural networks. However, could impractical possibly within constraint, relative purpose communication. A notable difficulty existing frameworks lies handling discrete constraints imposed pursued coding its interaction independent knowledge-base, makes reliable semantic extraction extremely challenging. Therefore, we develop new hashing-based extraction approach framework, our objective is generate one time signatures (hash codes) using supervised low latency, secure management dynamics. We first evaluate proposed framework over large image sets, extend it domain adaptive hashing then demonstrate effectiveness “ xmlns:xlink="http://www.w3.org/1999/xlink">semantics signature ” bulk transmission data.