A comprehensive review of AI-native 6G: integrating semantic communications, reconfigurable intelligent surfaces, and edge intelligence for next-generation connectivity

Abstract

This review explores the evolving vision of sixth-generation (6G) networks as a paradigm shift from conventional data-centric communication to intelligence-native architectures, where meaning, context, and adaptive decision-making are central. The convergence of semantic communication, reconfigurable intelligent surfaces (RIS), and edge intelligence enables context-aware, low-latency, and resilient wireless systems. Semantic encoding prioritizes task-relevant information to reduce communication redundancy; RIS dynamically controls the wireless propagation environment to enhance energy-efficiency and coverage; and edge intelligence supports decentralized, AI-driven inference closer to end users. Together, these technologies reframe traditional quality of service (QoS) metrics, moving beyond throughput and latency toward intent-driven and context-aware service delivery. This paper presents a structured analysis of their technical foundations, integration strategies, and mutual synergies. It also highlights open challenges such as joint semantic-environment modelling, cross-layer orchestration, and secure, trustworthy deployment of distributed AI at the network edge. Looking ahead, the review outlines promising directions including quantum-aware semantic channels, bio-inspired cognition for network adaptation, intelligent metasurfaces with embedded AI, and integrated space-air-ground-sea (SAGS) architectures. These advances suggest that 6G is not merely a generational upgrade but a foundational framework for future intelligent infrastructures capable of reasoning, learning, and responding autonomously in real time.