Optimal Slicing of mmWave Micro Base Stations for 5G and Beyond

Abstract

5G and beyond 5G mobile networks are expected to cater to diverse needs by efficiently allocating network resources based on demand. Network slicing is a fundamental approach that involves segregating and allocating network resources distinctly to a group of users based on their individual needs, and it is widely recognized as an essential concept that caters to various requirements. Allocating such slices will encounter conflicting requests, and effectively implementing network slicing presents multiple challenges. Effective network slicing necessitates efficient management of priority levels among diverse slices. Network slicing necessitates efficient management of priority levels across various slices, specifically focusing on three distinctive categories: Ultra-Reliable Low Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine Type Communications (mMTC). This paper proposes an optimization framework utilizing a Mixed Integer Linear Program (MILP) to allocate network resources for multiple slices efficiently. Our framework aims to maximize user satisfaction while ensuring that the specific requirements of each slice are met. We categorize the slices into three priority levels: the URLLC slice holds the highest priority, followed by the eMBB slice, and finally, the mMTC slice receives the least priority. By leveraging our proposed MILP-based approach, we dynamically assign network resources to different slices, considering their priority levels. This allocation strategy enables us to optimize resource utilization and effectively meet the diverse demands of users across various slices. Our framework provides a balance between meeting the stringent requirements of the URLLC slice, delivering high-quality services to the eMBB slice, and accommodating the massive connectivity needs of the mMTC slice.