Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G
Walid Saad, Omar Hashash, Christo Kurisummoottil Thomas, Christina, Chaccour, Merouane Debbah, Narayan Mandayam, and Zhu Han

TL;DR
This paper proposes a roadmap for developing AGI-native wireless systems beyond 6G, integrating common sense, perception, reasoning, and planning to support advanced use cases like digital twins and holographic experiences.
Contribution
It introduces a novel framework for AGI-native wireless systems that incorporate cognitive abilities such as perception, analogy, and reasoning, advancing beyond current AI-native networks.
Findings
Proposes a perception module based on abstracted real-world representations.
Introduces a world model founded on causality and hyper-dimensional computing.
Discusses how AGI-native systems enable advanced use cases like digital twins and holographic teleportation.
Abstract
Building future wireless systems that support services like digital twins (DTs) is challenging to achieve through advances to conventional technologies like meta-surfaces. While artificial intelligence (AI)-native networks promise to overcome some limitations of wireless technologies, developments still rely on AI tools like neural networks. Such tools struggle to cope with the non-trivial challenges of the network environment and the growing demands of emerging use cases. In this paper, we revisit the concept of AI-native wireless systems, equipping them with the common sense necessary to transform them into artificial general intelligence (AGI)-native systems. These systems acquire common sense by exploiting different cognitive abilities such as perception, analogy, and reasoning, that enable them to generalize and deal with unforeseen scenarios. Towards developing the components of…
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Taxonomy
TopicsWireless Body Area Networks · Energy Efficient Wireless Sensor Networks · Satellite Communication Systems
MethodsSparse Evolutionary Training
