Traditional wireless communication systems, based on Shannon’s information theory, are designed to ensure that every transmitted bit is received exactly as sent. This bit-level accuracy is efficient when channels are stable and bandwidth is enough, but it becomes inefficient in real environments where noise, fading, interference, or low bandwidth can distort signals. In many modern applications, such as Internet of Things (IoT) sensors, unmanned aerial vehicles (UAVs), or edge computing nodes, what truly matters is the meaning of the message. Semantic communication aligns perfectly with this shift in focus, which transitions from bit accuracy to message preservation. Instead of sending every word or symbol, the system seeks to transmit an encoded compact representation of the underlying meaning, which can then be reconstructed at the receiver using shared models of language and knowledge.