Parameterizable mobile workloads for adaptable base station optimizations

Recent works on 5G baseband processing systems address the optimization of applications with different require-ments of quality of service (QoS). The volume and heterogeneity of applications that have to be processed on a base station are growing and 5G introduces new use cases that push system designers towards more flexible and adaptable approaches. To investigate future network challenges of mobile communications, a good methodology for the generation of realistic workloads, that allows target optimizations of different traffic scenarios, is required. In this paper, we study the variation of real traffic data on multiple base stations and identify the main sources for the high variation of the 5G workloads. We propose a methodology for parameterizable workload generation for users with different QoS requirements that enables optimization techniques in base-band processing systems. We demonstrate the feasibility of our approach based on a virtual base station using a heterogeneous hardware model and various state-of-the-art mapping policies.