A Network Segmentation in Next Generation Wireless Systems with the Help of Ai Techniques

Abstract

The integration of communications with specific scales, various radio get right of entry to technologies, and diverse network assets renders next-era wireless networks (NGWNs) tremendously heterogeneous and dynamic. Emerging use instances and applications, together with system to machine communications, self sufficient driving, and factory automation, have stringent necessities in terms of reliability, latency, throughput, and so on. Such necessities pose new demanding situations to structure design, community control, and useful resource orchestration in NGWNs. Starting from illustrating these challenges, this paper presents at imparting an excellent know-how of the overall structure of NGWNs and 3 particular research problems under this structure.

First, we introduce a network-slicing based totally architecture and give an explanation for why and in which artificial intelligence (AI) need to be integrated into this structure. Second, the motivation, studies challenges, present works, and potential future instructions related to applying AI-based totally processes in three studies troubles are defined in detail, i.e., bendy radio access community slicing, computerized radio access generation selection, and cell facet caching and content shipping. In summary, this paper highlights the benefits and potentials of AI-primarily based tactics in the research of NGWNs.