RAN Slicing in Multi-MVNO Environment Under Dynamic Channel Conditions

• Published in: IEEE internet of things journal Vol. 9; no. 6; pp. 4748 - 4757
• Main Authors: Ravi, Darshan A., Shah, Vijay K., Li, Chengzhang, Hou, Y. Thomas, Reed, Jeffrey H.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.03.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G and beyond networks; 5G mobile communication; Computer architecture; dynamic channel conditions; Greedy algorithms; Heuristic algorithms; Internet of Things; Nonlinear programming; performance bound; Performance evaluation; Quality of service; Quality of service architectures; radio access network (RAN) slicing; Resource management; Segments; Slicing; Upper bounds; User requirements; Virtual networks; Wireless communication; Wireless networks
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2021.3108145

With the increasing diversity in the requirement of wireless services with guaranteed Quality of Service (QoS), radio access network (RAN) slicing becomes an important aspect in implementation of next-generation wireless systems (5G). RAN slicing involves the division of network resources into many logical segments where each segment has specific QoS and can serve users of the mobile virtual network operator (MVNO) with these requirements. This allows the network operator (NO) to provide service to multiple MVNOs each with different service requirements. Efficient allocation of the available resources to slices becomes vital in determining the number of users and therefore, the number of MVNOs that a NO can support. In this work, we study the problem of the modulation and coding scheme (MCS)-aware RAN slicing (MaRS) in the context of a wireless system having MVNOs which have users with minimum data rate requirement. Channel quality indicator (CQI) report sent from each user in the network determines the MCS selected, which in turn determines the achievable data rate. But the channel conditions might not remain the same for the entire duration of a user being served. For this reason, we consider the channel conditions to be dynamic where the choice of the MCS level varies at each time instant. We model the MaRS problem as a NonLinear Programming problem and show that it is NP-Hard. Next, we propose a solution based on the greedy algorithm paradigm. We then develop an upper performance bound for this problem and finally evaluate the performance of the proposed solution by comparing it against the upper bound under various channel and network configurations.