ComAI: The Convergence of Communication and Artificial Intelligence

Ping Zhang, Kai Niu, Xiaoyun Wang, Yiming Liu, Zijian Liang, Chen Dong, Jincheng Dai, Xiaodong Xu, Wenjun Xu, Zhi Zhang, Guangyu Wang, Yanlu Li, Di Wu, Hequan Wu

Abstract: The convergence of communication and artificial intelligence (AI) is transforming next-generation wireless networks. Inspired by natural intelligence, particularly in how data, information, and knowledge are processed for cognition, reasoning, learning, decision-making, and environmental interaction, we introduce a new paradigm called ComAI. This paradigm is expected to play a key role in future wireless networks. In this paper, we highlight the motivations behind the convergence of communications and AI and present a roadmap that outlines the evolution of wireless communications alongside advancements in AI. Then, we introduce the key idea of ComAI and provide a general framework of ComAI, which includes information sensing and data collection, information cognition through intellicise semantic communication networks, and information decision with large-scale models. In particular, intellicise semantic communication networks refer to intelligent and concise communication systems that leverage semantic-level information to simplify and restructure signal processing, information cognition, and network organization. We further discuss the foundational theories and key techniques for the convergence of communication and AI. Additionally, we provide experimental validations, including insights from the 6G test network, and highlight potential application scenarios such as embodied AI robots and multi-agent collaborative communications. Finally, we outline the future directions and open issues in the development of ComAI, sharing our thoughts and insights on potential solutions.

External IDs:dblp:journals/comsur/ZhangNWLLDDXXZWLWW26