5,237 research outputs found
A multi-traffic inter-cell interference coordination scheme in dense cellular networks
This paper proposes a novel semi-distributed and practical ICIC scheme based on the Almost Blank Sub-Frame (ABSF) approach specified by 3GPP. We define two mathematical programming problems for the cases of guaranteed and best-effort traffic, and use game theory to study the properties of the derived ICIC distributed schemes, which are compared in detail against unaffordable centralized schemes. Based on the analysis of the proposed models, we define Distributed Multi-traffic Scheduling (DMS), a unified distributed framework for adaptive interference-aware scheduling of base stations in future cellular networks, which accounts for both guaranteed and best-effort traffic. DMS follows a two-tier approach, consisting of local ABSF schedulers, which perform the resource distribution between the guaranteed and best effort traffic, and a light-weight local supervisor, which coordinates ABSF local decisions. As a result of such a two-tier design, DMS requires very light signaling to drive the local schedulers to globally efficient operating points. As shown by means of numerical results, DMS allows to: (i) maximize radio resources resue; (ii) provide requested quality for guaranteed traffic; (iii) minimize the time dedicated to guaranteed traffic to leave room for best-effort traffic; and (iv) maximize resource utilization efficiency for the best-effort traffic.The work of A. Banchs was supported by the H2020 5GMoNArch project (Grant Agreement No. 761445) and the 5GCity project of the Spanish Ministry of Economy and
Competitiveness (TEC2016-76795-C6-3-R). The work of V. Mancuso has been supported by a Ramon y Cajal grant (ref: RYC-2014-16285) in part by the Spanish Ministry of Science, Innovation and Universities under grant TIN2017-88749-R and by the Madrid Regional Government through the TIGRE5-CM program (S2013/ICE-2919)
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
Energy efficiency in heterogeneous wireless access networks
In this article, we bring forward the important aspect of energy savings in wireless access networks. We specifically focus on the energy saving opportunities in the recently evolving heterogeneous networks (HetNets), both Single- RAT and Multi-RAT. Issues such as sleep/wakeup cycles and interference management are discussed for co-channel Single-RAT HetNets. In addition to that, a simulation based study for LTE macro-femto HetNets is presented, indicating the need for dynamic energy efficient resource management schemes. Multi-RAT HetNets also come with challenges such as network integration, combined resource management and network selection. Along with a discussion on these challenges, we also investigate the performance of the conventional WLAN-first network selection mechanism in terms of energy efficiency (EE) and suggest that EE can be improved by the application of intelligent call admission control policies
Leveraging intelligence from network CDR data for interference aware energy consumption minimization
Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo
Dynamic Time-domain Duplexing for Self-backhauled Millimeter Wave Cellular Networks
Millimeter wave (mmW) bands between 30 and 300 GHz have attracted
considerable attention for next-generation cellular networks due to vast
quantities of available spectrum and the possibility of very high-dimensional
antenna ar-rays. However, a key issue in these systems is range: mmW signals
are extremely vulnerable to shadowing and poor high-frequency propagation.
Multi-hop relaying is therefore a natural technology for such systems to
improve cell range and cell edge rates without the addition of wired access
points. This paper studies the problem of scheduling for a simple
infrastructure cellular relay system where communication between wired base
stations and User Equipment follow a hierarchical tree structure through fixed
relay nodes. Such a systems builds naturally on existing cellular mmW backhaul
by adding mmW in the access links. A key feature of the proposed system is that
TDD duplexing selections can be made on a link-by-link basis due to directional
isolation from other links. We devise an efficient, greedy algorithm for
centralized scheduling that maximizes network utility by jointly optimizing the
duplexing schedule and resources allocation for dense, relay-enhanced OFDMA/TDD
mmW networks. The proposed algorithm can dynamically adapt to loading, channel
conditions and traffic demands. Significant throughput gains and improved
resource utilization offered by our algorithm over the static,
globally-synchronized TDD patterns are demonstrated through simulations based
on empirically-derived channel models at 28 GHz.Comment: IEEE Workshop on Next Generation Backhaul/Fronthaul Networks -
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