3,926 research outputs found
End-to-End Simulation of 5G mmWave Networks
Due to its potential for multi-gigabit and low latency wireless links,
millimeter wave (mmWave) technology is expected to play a central role in 5th
generation cellular systems. While there has been considerable progress in
understanding the mmWave physical layer, innovations will be required at all
layers of the protocol stack, in both the access and the core network.
Discrete-event network simulation is essential for end-to-end, cross-layer
research and development. This paper provides a tutorial on a recently
developed full-stack mmWave module integrated into the widely used open-source
ns--3 simulator. The module includes a number of detailed statistical channel
models as well as the ability to incorporate real measurements or ray-tracing
data. The Physical (PHY) and Medium Access Control (MAC) layers are modular and
highly customizable, making it easy to integrate algorithms or compare
Orthogonal Frequency Division Multiplexing (OFDM) numerologies, for example.
The module is interfaced with the core network of the ns--3 Long Term Evolution
(LTE) module for full-stack simulations of end-to-end connectivity, and
advanced architectural features, such as dual-connectivity, are also available.
To facilitate the understanding of the module, and verify its correct
functioning, we provide several examples that show the performance of the
custom mmWave stack as well as custom congestion control algorithms designed
specifically for efficient utilization of the mmWave channel.Comment: 25 pages, 16 figures, submitted to IEEE Communications Surveys and
Tutorials (revised Jan. 2018
Business Case and Technology Analysis for 5G Low Latency Applications
A large number of new consumer and industrial applications are likely to
change the classic operator's business models and provide a wide range of new
markets to enter. This article analyses the most relevant 5G use cases that
require ultra-low latency, from both technical and business perspectives. Low
latency services pose challenging requirements to the network, and to fulfill
them operators need to invest in costly changes in their network. In this
sense, it is not clear whether such investments are going to be amortized with
these new business models. In light of this, specific applications and
requirements are described and the potential market benefits for operators are
analysed. Conclusions show that operators have clear opportunities to add value
and position themselves strongly with the increasing number of services to be
provided by 5G.Comment: 18 pages, 5 figure
Will SDN be part of 5G?
For many, this is no longer a valid question and the case is considered
settled with SDN/NFV (Software Defined Networking/Network Function
Virtualization) providing the inevitable innovation enablers solving many
outstanding management issues regarding 5G. However, given the monumental task
of softwarization of radio access network (RAN) while 5G is just around the
corner and some companies have started unveiling their 5G equipment already,
the concern is very realistic that we may only see some point solutions
involving SDN technology instead of a fully SDN-enabled RAN. This survey paper
identifies all important obstacles in the way and looks at the state of the art
of the relevant solutions. This survey is different from the previous surveys
on SDN-based RAN as it focuses on the salient problems and discusses solutions
proposed within and outside SDN literature. Our main focus is on fronthaul,
backward compatibility, supposedly disruptive nature of SDN deployment,
business cases and monetization of SDN related upgrades, latency of general
purpose processors (GPP), and additional security vulnerabilities,
softwarization brings along to the RAN. We have also provided a summary of the
architectural developments in SDN-based RAN landscape as not all work can be
covered under the focused issues. This paper provides a comprehensive survey on
the state of the art of SDN-based RAN and clearly points out the gaps in the
technology.Comment: 33 pages, 10 figure
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