3,072 research outputs found
The 5G Cellular Backhaul Management Dilemma: To Cache or to Serve
With the introduction of caching capabilities into small cell networks
(SCNs), new backaul management mechanisms need to be developed to prevent the
predicted files that are downloaded by the at the small base stations (SBSs) to
be cached from jeopardizing the urgent requests that need to be served via the
backhaul. Moreover, these mechanisms must account for the heterogeneity of the
backhaul that will be encompassing both wireless backhaul links at various
frequency bands and a wired backhaul component. In this paper, the
heterogeneous backhaul management problem is formulated as a minority game in
which each SBS has to define the number of predicted files to download, without
affecting the required transmission rate of the current requests. For the
formulated game, it is shown that a unique fair proper mixed Nash equilibrium
(PMNE) exists. Self-organizing reinforcement learning algorithm is proposed and
proved to converge to a unique Boltzmann-Gibbs equilibrium which approximates
the desired PMNE. Simulation results show that the performance of the proposed
approach can be close to that of the ideal optimal algorithm while it
outperforms a centralized greedy approach in terms of the amount of data that
is cached without jeopardizing the quality-of-service of current requests.Comment: Accepted for publication at Transactions on Wireless Communication
Mobile Computing in Digital Ecosystems: Design Issues and Challenges
In this paper we argue that the set of wireless, mobile devices (e.g.,
portable telephones, tablet PCs, GPS navigators, media players) commonly used
by human users enables the construction of what we term a digital ecosystem,
i.e., an ecosystem constructed out of so-called digital organisms (see below),
that can foster the development of novel distributed services. In this context,
a human user equipped with his/her own mobile devices, can be though of as a
digital organism (DO), a subsystem characterized by a set of peculiar features
and resources it can offer to the rest of the ecosystem for use from its peer
DOs. The internal organization of the DO must address issues of management of
its own resources, including power consumption. Inside the DO and among DOs,
peer-to-peer interaction mechanisms can be conveniently deployed to favor
resource sharing and data dissemination. Throughout this paper, we show that
most of the solutions and technologies needed to construct a digital ecosystem
are already available. What is still missing is a framework (i.e., mechanisms,
protocols, services) that can support effectively the integration and
cooperation of these technologies. In addition, in the following we show that
that framework can be implemented as a middleware subsystem that enables novel
and ubiquitous forms of computation and communication. Finally, in order to
illustrate the effectiveness of our approach, we introduce some experimental
results we have obtained from preliminary implementations of (parts of) that
subsystem.Comment: Proceedings of the 7th International wireless Communications and
Mobile Computing conference (IWCMC-2011), Emergency Management: Communication
and Computing Platforms Worksho
A survey of machine learning techniques applied to self organizing cellular networks
In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future
End to End Performance Analysis of Relay Cooperative Communication Based on Parked Cars
Parking lots (PLs) are usually full with cars. If these cars are formed into
a self-organizing vehicular network, they can be new kind of road side units
(RSUs) in urban area to provide communication data forwarding between mobile
terminals nearby and a base station. However cars in PLs can leave at any time,
which is neglected in the existing studies. In this paper, we investigate relay
cooperative communication based on parked cars in PLs. Taking the impact of the
car's leaving behavior into consideration, we derive the expressions of outage
probability in a two-hop cooperative communication and its link capacity.
Finally, the numerical results show that the impact of a car's arriving time is
greater than the impact of the duration the car has parked on outage
probability.Comment: 7 pages, 7 figures, accepted by ICACT201
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
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