Understanding before Transmission (UBT): Hashing-based Semantic Communication Model

In Shannon's theory, semantic aspects of communication were identified but considered irrelevant to the technical communication problems. However, semantic communication techniques have recently attracted renewed research interests in 6G because they have the capability to support an efficient interpretation of the meaning intended by the sender (or accomplishment of the goal) when dealing with multi-dimensional data such as videos, images, audio, sentences, documents etc. We propose a new hashing-based semantic communication, where our learning objective is the "semantic extraction"to produce optimal binary signatures (hash codes) by supervised learning. We evaluate the proposed framework over large image data sets and demonstrate its effectiveness in bulk transmission.