Implementing Cloud Radio Access on a Multi-Core System
In this article, we propose the implementation of a Cloud Radio Access Network (C-RAN) on a multicore unified device that facilitates the processing of multiple distributed antennas in the base band. In order to decrease their runtime, we present a parallel processing model based on both functional and data decomposition of virtualized Base Band Unit (BBU) functions. We are investigating two parallel running BBU work scheduling techniques, where computational resources can be distributed by user equipment (UE) or by code blocks (CB). We implement a batch queuing model by using data obtained while running an open source RAN code to determine the necessary processing power in a data center while following tight latency criteria in the downlink and uplink directions. When processing a hundred LTE-cells in a multicore device, the proposed model is validated by simulation. The findings provide useful advice on the sizing and implementation of Cloud-RAN applications such as cryptography [9].
Figure 1
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the latest manuscript can be downloaded and accessed as a PDF.
Posted 04 Jan, 2021
Implementing Cloud Radio Access on a Multi-Core System
Posted 04 Jan, 2021
In this article, we propose the implementation of a Cloud Radio Access Network (C-RAN) on a multicore unified device that facilitates the processing of multiple distributed antennas in the base band. In order to decrease their runtime, we present a parallel processing model based on both functional and data decomposition of virtualized Base Band Unit (BBU) functions. We are investigating two parallel running BBU work scheduling techniques, where computational resources can be distributed by user equipment (UE) or by code blocks (CB). We implement a batch queuing model by using data obtained while running an open source RAN code to determine the necessary processing power in a data center while following tight latency criteria in the downlink and uplink directions. When processing a hundred LTE-cells in a multicore device, the proposed model is validated by simulation. The findings provide useful advice on the sizing and implementation of Cloud-RAN applications such as cryptography [9].
Figure 1
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the latest manuscript can be downloaded and accessed as a PDF.