1,855 research outputs found
Matching Theory for Future Wireless Networks: Fundamentals and Applications
The emergence of novel wireless networking paradigms such as small cell and
cognitive radio networks has forever transformed the way in which wireless
systems are operated. In particular, the need for self-organizing solutions to
manage the scarce spectral resources has become a prevalent theme in many
emerging wireless systems. In this paper, the first comprehensive tutorial on
the use of matching theory, a Nobelprize winning framework, for resource
management in wireless networks is developed. To cater for the unique features
of emerging wireless networks, a novel, wireless-oriented classification of
matching theory is proposed. Then, the key solution concepts and algorithmic
implementations of this framework are exposed. Then, the developed concepts are
applied in three important wireless networking areas in order to demonstrate
the usefulness of this analytical tool. Results show how matching theory can
effectively improve the performance of resource allocation in all three
applications discussed
Radio Link Enabler for Context-aware D2D Communication in Reuse Mode
Device-to-Device (D2D) communication is considered as one of the key
technologies for the fifth generation wireless communication system (5G) due to
certain benefits provided, e.g. traffic offload and low end-to-end latency. A
D2D link can reuse resource of a cellular user for its own transmission, while
mutual interference in between these two links is introduced. In this paper, we
propose a smart radio resource management (RRM) algorithm which enables D2D
communication to reuse cellular resource, by taking into account of context
information. Besides, signaling schemes with high efficiency are also given in
this work to enable the proposed RRM algorithm. Simulation results demonstrate
the performance improvement of the proposed scheme in terms of the overall cell
capacity
Benchmarking Practical RRM Algorithms for D2D Communications in LTE Advanced
Device-to-device (D2D) communication integrated into cellular networks is a
means to take advantage of the proximity of devices and allow for reusing
cellular resources and thereby to increase the user bitrates and the system
capacity. However, when D2D (in the 3rd Generation Partnership Project also
called Long Term Evolution (LTE) Direct) communication in cellular spectrum is
supported, there is a need to revisit and modify the existing radio resource
management (RRM) and power control (PC) techniques to realize the potential of
the proximity and reuse gains and to limit the interference at the cellular
layer. In this paper, we examine the performance of the flexible LTE PC tool
box and benchmark it against a utility optimal iterative scheme. We find that
the open loop PC scheme of LTE performs well for cellular users both in terms
of the used transmit power levels and the achieved
signal-to-interference-and-noise-ratio (SINR) distribution. However, the
performance of the D2D users as well as the overall system throughput can be
boosted by the utility optimal scheme, because the utility maximizing scheme
takes better advantage of both the proximity and the reuse gains. Therefore, in
this paper we propose a hybrid PC scheme, in which cellular users employ the
open loop path compensation method of LTE, while D2D users use the utility
optimizing distributed PC scheme. In order to protect the cellular layer, the
hybrid scheme allows for limiting the interference caused by the D2D layer at
the cost of having a small impact on the performance of the D2D layer. To
ensure feasibility, we limit the number of iterations to a practically feasible
level. We make the point that the hybrid scheme is not only near optimal, but
it also allows for a distributed implementation for the D2D users, while
preserving the LTE PC scheme for the cellular users.Comment: 30 pages, submitted for review April-2013. See also: G. Fodor, M.
Johansson, D. P. Demia, B. Marco, and A. Abrardo, A joint power control and
resource allocation algorithm for D2D communications, KTH, Automatic Control,
Tech. Rep., 2012, qC 20120910,
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-10205
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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