Optimisation of Numerology and Packet Scheduling in 5G Networks

Abstract

Network slicing has been introduced in 5G networks as an enabling feature for the effective Quality of Service (QoS) provisioning to multiple service classes with distinct performance requirements. When applied in the Radio Access Network (RAN), a class-specific slice is assigned a set of radio resources and can furthermore be optimally configured in terms of the applied numerology and packet scheduler. As both the optimal numerology and the most suitable packet scheduler may be different for e.g. a class of Latency-Constrained (LC) and a class of Throughput-Oriented (TO) services, the potential of slicing is clear. However, the inherent trunking loss incurred when applying slicing with dedicated resources provides an argument against such slicing. In this paper we demonstrate that the performance and traffic handling capacity in an optimally configured non-sliced scenario may exceed that attained when using segregated individually optimised slices. To that end, we use simulations to assess the best-performing numerology and packet scheduler for a sliced scenario with LC and TO services. We then compare the thus optimised sliced scenario with an optimal non-sliced scenario and show that the non-sliced scenario can serve about 20% more traffic than the sliced scenario while satisfying the same class-specific QoS requirements.