4,015 research outputs found
Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolution
MIMO processing plays a central part towards the recent increase in spectral
and energy efficiencies of wireless networks. MIMO has grown beyond the
original point-to-point channel and nowadays refers to a diverse range of
centralized and distributed deployments. The fundamental bottleneck towards
enormous spectral and energy efficiency benefits in multiuser MIMO networks
lies in a huge demand for accurate channel state information at the transmitter
(CSIT). This has become increasingly difficult to satisfy due to the increasing
number of antennas and access points in next generation wireless networks
relying on dense heterogeneous networks and transmitters equipped with a large
number of antennas. CSIT inaccuracy results in a multi-user interference
problem that is the primary bottleneck of MIMO wireless networks. Looking
backward, the problem has been to strive to apply techniques designed for
perfect CSIT to scenarios with imperfect CSIT. In this paper, we depart from
this conventional approach and introduce the readers to a promising strategy
based on rate-splitting. Rate-splitting relies on the transmission of common
and private messages and is shown to provide significant benefits in terms of
spectral and energy efficiencies, reliability and CSI feedback overhead
reduction over conventional strategies used in LTE-A and exclusively relying on
private message transmissions. Open problems, impact on standard specifications
and operational challenges are also discussed.Comment: accepted to IEEE Communication Magazine, special issue on LTE
Evolutio
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
Traffic Offloading/Onloading in Multi-RAT Cellular Networks
We analyze next generation cellular networks, offering connectivity to mobile users through multiple radio access technologies (RATs), namely LTE and WiFi. We develop a framework based on the Markovian agent formalism, which can model several aspects of the system, including user traffic dynamics and radio resource allocation. In particular, through a mean-field solution, we show the ability of our framework to capture the system behavior in flash-crowd scenarios, i.e., when a burst of traffic requests takes place in some parts of the network service area. We consider a distributed strategy for the user RAT selection, which aims at ensuring high user throughput, and investigate its performance under different resource allocation scheme
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