Next-generation cellular systems like fifth generation (5G) are expected to experience tremendous traffic growth. To accommodate such traffic demand, there is a need to increase the network capacity that eventually requires the deployment of more base stations (BSs). Nevertheless, BSs are very expensive and consume a lot of energy. With growing complexity of signal processing, baseband units are now consuming a significant amount of energy. As a result, cloud radio access networks (C-RAN) have been proposed as an energy efficient (EE) architecture that leverages cloud computing technology where baseband processing is performed in the cloud. This paper proposes an energy reduction technique based on baseband workload consolidation using virtualized general purpose processors (GPPs) in the cloud. The rationale for the cloud based workload consolidation model is to switch off idle baseband units (BBUs) to reduce the overall network energy consumption. The power consumption model for C-RAN is also formulated with considering radio side, fronthaul and BS cloud power consumption. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution (LTE) RAN system. The proposed scheme saves up to 80% of energy during low traffic periods and 12% during peak traffic periods compared to baseline LTE system. Moreover, the proposed scheme saves 38% of energy compared to the baseline system on a daily average.
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications