2,659 research outputs found
Spectral Efficient and Energy Aware Clustering in Cellular Networks
The current and envisaged increase of cellular traffic poses new challenges
to Mobile Network Operators (MNO), who must densify their Radio Access Networks
(RAN) while maintaining low Capital Expenditure and Operational Expenditure to
ensure long-term sustainability. In this context, this paper analyses optimal
clustering solutions based on Device-to-Device (D2D) communications to mitigate
partially or completely the need for MNOs to carry out extremely dense RAN
deployments. Specifically, a low complexity algorithm that enables the creation
of spectral efficient clusters among users from different cells, denoted as
enhanced Clustering Optimization for Resources' Efficiency (eCORE) is
presented. Due to the imbalance between uplink and downlink traffic, a
complementary algorithm, known as Clustering algorithm for Load Balancing
(CaLB), is also proposed to create non-spectral efficient clusters when they
result in a capacity increase. Finally, in order to alleviate the energy
overconsumption suffered by cluster heads, the Clustering Energy Efficient
algorithm (CEEa) is also designed to manage the trade-off between the capacity
enhancement and the early battery drain of some users. Results show that the
proposed algorithms increase the network capacity and outperform existing
solutions, while, at the same time, CEEa is able to handle the cluster heads
energy overconsumption
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
Framework for Content Distribution over Wireless LANs
Wireless LAN (also called as Wi-Fi) is dominantly considered as the most pervasive
technology for Intent access. Due to the low-cost of chipsets and support for high data
rates, Wi-Fi has become a universal solution for ever-increasing application space
which includes, video streaming, content delivery, emergency communication,
vehicular communication and Internet-of-Things (IoT).
Wireless LAN technology is defined by the IEEE 802.11 standard. The 802.11
standard has been amended several times over the last two decades, to incorporate the
requirement of future applications. The 802.11 based Wi-Fi networks are
infrastructure networks in which devices communicate through an access point.
However, in 2010, Wi-Fi Alliance has released a specification to standardize direct
communication in Wi-Fi networks. The technology is called Wi-Fi Direct. Wi-Fi
Direct after 9 years of its release is still used for very basic services (connectivity, file
transfer etc.), despite the potential to support a wide range of applications. The reason
behind the limited inception of Wi-Fi Direct is some inherent shortcomings that limit
its performance in dense networks. These include the issues related to topology
design, such as non-optimal group formation, Group Owner selection problem,
clustering in dense networks and coping with device mobility in dynamic networks. Furthermore, Wi-Fi networks also face challenges to meet the growing number of Wi
Fi users. The next generation of Wi-Fi networks is characterized as ultra-dense
networks where the topology changes frequently which directly affects the network
performance. The dynamic nature of such networks challenges the operators to design
and make optimum planifications.
In this dissertation, we propose solutions to the aforementioned problems. We
contributed to the existing Wi-Fi Direct technology by enhancing the group formation
process. The proposed group formation scheme is backwards-compatible and
incorporates role selection based on the device's capabilities to improve network
performance. Optimum clustering scheme using mixed integer programming is
proposed to design efficient topologies in fixed dense networks, which improves
network throughput and reduces packet loss ratio. A novel architecture using
Unmanned Aeriel Vehicles (UAVs) in Wi-Fi Direct networks is proposed for
dynamic networks. In ultra-dense, highly dynamic topologies, we propose cognitive
networks using machine-learning algorithms to predict the network changes ahead of
time and self-configuring the network
Fundamental Limits of Caching in Wireless D2D Networks
We consider a wireless Device-to-Device (D2D) network where communication is
restricted to be single-hop. Users make arbitrary requests from a finite
library of files and have pre-cached information on their devices, subject to a
per-node storage capacity constraint. A similar problem has already been
considered in an ``infrastructure'' setting, where all users receive a common
multicast (coded) message from a single omniscient server (e.g., a base station
having all the files in the library) through a shared bottleneck link. In this
work, we consider a D2D ``infrastructure-less'' version of the problem. We
propose a caching strategy based on deterministic assignment of subpackets of
the library files, and a coded delivery strategy where the users send linearly
coded messages to each other in order to collectively satisfy their demands. We
also consider a random caching strategy, which is more suitable to a fully
decentralized implementation. Under certain conditions, both approaches can
achieve the information theoretic outer bound within a constant multiplicative
factor. In our previous work, we showed that a caching D2D wireless network
with one-hop communication, random caching, and uncoded delivery, achieves the
same throughput scaling law of the infrastructure-based coded multicasting
scheme, in the regime of large number of users and files in the library. This
shows that the spatial reuse gain of the D2D network is order-equivalent to the
coded multicasting gain of single base station transmission. It is therefore
natural to ask whether these two gains are cumulative, i.e.,if a D2D network
with both local communication (spatial reuse) and coded multicasting can
provide an improved scaling law. Somewhat counterintuitively, we show that
these gains do not cumulate (in terms of throughput scaling law).Comment: 45 pages, 5 figures, Submitted to IEEE Transactions on Information
Theory, This is the extended version of the conference (ITW) paper
arXiv:1304.585
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