462 research outputs found
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Survey of Spectrum Sharing for Inter-Technology Coexistence
Increasing capacity demands in emerging wireless technologies are expected to
be met by network densification and spectrum bands open to multiple
technologies. These will, in turn, increase the level of interference and also
result in more complex inter-technology interactions, which will need to be
managed through spectrum sharing mechanisms. Consequently, novel spectrum
sharing mechanisms should be designed to allow spectrum access for multiple
technologies, while efficiently utilizing the spectrum resources overall.
Importantly, it is not trivial to design such efficient mechanisms, not only
due to technical aspects, but also due to regulatory and business model
constraints. In this survey we address spectrum sharing mechanisms for wireless
inter-technology coexistence by means of a technology circle that incorporates
in a unified, system-level view the technical and non-technical aspects. We
thus systematically explore the spectrum sharing design space consisting of
parameters at different layers. Using this framework, we present a literature
review on inter-technology coexistence with a focus on wireless technologies
with equal spectrum access rights, i.e. (i) primary/primary, (ii)
secondary/secondary, and (iii) technologies operating in a spectrum commons.
Moreover, we reflect on our literature review to identify possible spectrum
sharing design solutions and performance evaluation approaches useful for
future coexistence cases. Finally, we discuss spectrum sharing design
challenges and suggest future research directions
Integrated Wireless Backhaul Over Optical Access Networks
Recent technological advances and deployments are creating a new landscape in access networks, with an integration of wireless and fiber technologies a key supporting technology. In the past, a separation between those with fiber in the access networks and those with wireless networks, the relatively low data-rate requirements of backhaul and the relatively large cell sites, have all combined to keep fiber deployment low in wireless backhaul. As fiber has penetrated the access network and the latest wireless standards have demanded smaller, higher bandwidth cells, fiber connectivity has become key. Choices remain as to where the demarcation between key elements should be in the network and whether fiber should be used as just a high data-rate backhaul path or if a transition to radio-over-fiber techniques can afford benefits. This paper will explore the network options available in particular those demonstrated in recent European Union (EU) projects, how they can be integrated with existing access networks and how techniques such as radio-over-fiber can be deployed to offer increased functionality
Performance Comparison of Dual Connectivity and Hard Handover for LTE-5G Tight Integration in mmWave Cellular Networks
MmWave communications are expected to play a major role in the Fifth
generation of mobile networks. They offer a potential multi-gigabit throughput
and an ultra-low radio latency, but at the same time suffer from high isotropic
pathloss, and a coverage area much smaller than the one of LTE macrocells. In
order to address these issues, highly directional beamforming and a very
high-density deployment of mmWave base stations were proposed. This Thesis aims
to improve the reliability and performance of the 5G network by studying its
tight and seamless integration with the current LTE cellular network. In
particular, the LTE base stations can provide a coverage layer for 5G mobile
terminals, because they operate on microWave frequencies, which are less
sensitive to blockage and have a lower pathloss. This document is a copy of the
Master's Thesis carried out by Mr. Michele Polese under the supervision of Dr.
Marco Mezzavilla and Prof. Michele Zorzi. It will propose an LTE-5G tight
integration architecture, based on mobile terminals' dual connectivity to LTE
and 5G radio access networks, and will evaluate which are the new network
procedures that will be needed to support it. Moreover, this new architecture
will be implemented in the ns-3 simulator, and a thorough simulation campaign
will be conducted in order to evaluate its performance, with respect to the
baseline of handover between LTE and 5G.Comment: Master's Thesis carried out by Mr. Michele Polese under the
supervision of Dr. Marco Mezzavilla and Prof. Michele Zorz
Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions
The ever-increasing number of resource-constrained Machine-Type Communication
(MTC) devices is leading to the critical challenge of fulfilling diverse
communication requirements in dynamic and ultra-dense wireless environments.
Among different application scenarios that the upcoming 5G and beyond cellular
networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the
unique technical challenge of supporting a huge number of MTC devices, which is
the main focus of this paper. The related challenges include QoS provisioning,
handling highly dynamic and sporadic MTC traffic, huge signalling overhead and
Radio Access Network (RAN) congestion. In this regard, this paper aims to
identify and analyze the involved technical issues, to review recent advances,
to highlight potential solutions and to propose new research directions. First,
starting with an overview of mMTC features and QoS provisioning issues, we
present the key enablers for mMTC in cellular networks. Along with the
highlights on the inefficiency of the legacy Random Access (RA) procedure in
the mMTC scenario, we then present the key features and channel access
mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT.
Subsequently, we present a framework for the performance analysis of
transmission scheduling with the QoS support along with the issues involved in
short data packet transmission. Next, we provide a detailed overview of the
existing and emerging solutions towards addressing RAN congestion problem, and
then identify potential advantages, challenges and use cases for the
applications of emerging Machine Learning (ML) techniques in ultra-dense
cellular networks. Out of several ML techniques, we focus on the application of
low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss
some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future
publication in IEEE Communications Surveys and Tutorial
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