Cognitive semantic communications in 6G wireless networks using a digital twin approach

Abstract

This paper introduces an advanced Cognitive Semantic Communication (CSC) framework enhanced through Digital Twin (DT) technology to meet the evolving demands of intelligent and adaptive communication in sixth-generation (6G) wireless networks. Unlike traditional semantic systems that depend on static knowledge representations, the proposed DT-Based CSC incorporates real-time system modeling, dynamic knowledge graphs, and entropy-based reasoning to support predictive optimization and context-aware decision-making. Each communication node is paired with a digital twin that continuously reflects it's physical, cognitive, and network states, allowing for proactive adjustments based on current conditions. A multi-objective optimization approach is used to balance semantic accuracy, energy efficiency, security, and latency. The framework emphasizes the transmission of meaningful and relevant information rather than raw data, thereby improving overall communication effectiveness. Simulation results confirm that the proposed approach offers substantial improvements over existing methods in terms of semantic precision, system reliability, adaptability, and secure information exchange. The digital twin integration enables the system to maintain stability even under dynamic network conditions, making it particularly well-suited for real-world applications. In conclusion, the DT-Based CSC framework offers a transformative advancement for future 6G communication systems, supporting intelligent services such as autonomous vehicles, smart infrastructure, and decentralized artificial intelligence.