Advances and challenges in semantic communications: A systematic review

Abstract

Inspired by the recent success of machine learning (ML), the concept of semantic communication introduced by Weaver in 1949 has gained significant attention and has become a promising research direction. Unlike conventional communication systems, semantic communication emphasizes the precise retrieval of conveyed meaning from the source to the receiver, rather than focusing on the accurate transmission of symbols. Thus, semantic communication can achieve a significant gain in source data compression, alleviate communication bandwidth pressure, and support new intelligent services, which is envisioned as a crucial enabler of future sixth-generation (6G) networks. In this review, we critically summarize the advances made in semantic information and semantic communications, including theory, architecture, and potential applications. Moreover, we deeply explore the major challenges in developing semantic communications and present the development prospects, aiming to prompt further scientific and industrial advances in semantic communications.

Keywords

• semantic communications
• semantic information
• 6G
• artificial intelligence
• deep learning