1,295 research outputs found
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
Design and Experimental Validation of a Software-Defined Radio Access Network Testbed with Slicing Support
Network slicing is a fundamental feature of 5G systems to partition a single
network into a number of segregated logical networks, each optimized for a
particular type of service, or dedicated to a particular customer or
application. The realization of network slicing is particularly challenging in
the Radio Access Network (RAN) part, where multiple slices can be multiplexed
over the same radio channel and Radio Resource Management (RRM) functions shall
be used to split the cell radio resources and achieve the expected behaviour
per slice. In this context, this paper describes the key design and
implementation aspects of a Software-Defined RAN (SD-RAN) experimental testbed
with slicing support. The testbed has been designed consistently with the
slicing capabilities and related management framework established by 3GPP in
Release 15. The testbed is used to demonstrate the provisioning of RAN slices
(e.g. preparation, commissioning and activation phases) and the operation of
the implemented RRM functionality for slice-aware admission control and
scheduling
Design and experimental validation of a software-defined radio access network testbed with slicing support
Network slicing is a fundamental feature of 5G systems to partition a single network into a number of segregated logical networks, each optimized for a particular type of service or dedicated to a particular customer or application. The realization of network slicing is particularly challenging in the Radio Access Network (RAN) part, where multiple slices can be multiplexed over the same radio channel and Radio Resource Management (RRM) functions shall be used to split the cell radio resources and achieve the expected behaviour per slice. In this context, this paper describes the key design and implementation aspects of a Software-Defined RAN (SD-RAN) experimental testbed with slicing support. The testbed has been designed consistently with the slicing capabilities and related management framework established by 3GPP in Release 15. The testbed is used to demonstrate the provisioning of RAN slices (e.g., preparation, commissioning, and activation phases) and the operation of the implemented RRM functionality for slice-aware admission control and scheduling.Peer ReviewedPostprint (published version
Understanding the Computational Requirements of Virtualized Baseband Units using a Programmable Cloud Radio Access Network Testbed
Cloud Radio Access Network (C-RAN) is emerging as a transformative
architecture for the next generation of mobile cellular networks. In C-RAN, the
Baseband Unit (BBU) is decoupled from the Base Station (BS) and consolidated in
a centralized processing center. While the potential benefits of C-RAN have
been studied extensively from the theoretical perspective, there are only a few
works that address the system implementation issues and characterize the
computational requirements of the virtualized BBU. In this paper, a
programmable C-RAN testbed is presented where the BBU is virtualized using the
OpenAirInterface (OAI) software platform, and the eNodeB and User Equipment
(UEs) are implemented using USRP boards. Extensive experiments have been
performed in a FDD downlink LTE emulation system to characterize the
performance and computing resource consumption of the BBU under various
conditions. It is shown that the processing time and CPU utilization of the BBU
increase with the channel resources and with the Modulation and Coding Scheme
(MCS) index, and that the CPU utilization percentage can be well approximated
as a linear increasing function of the maximum downlink data rate. These
results provide real-world insights into the characteristics of the BBU in
terms of computing resource and power consumption, which may serve as inputs
for the design of efficient resource-provisioning and allocation strategies in
C-RAN systems.Comment: In Proceedings of the IEEE International Conference on Autonomic
Computing (ICAC), July 201
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