940 research outputs found
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
Novel Intercell Interference Mitigation Algorithms for Multicell OFDMA Systems with Limited Base Station Cooperation
Resource allocation in multicell downlink orthogonal frequency division multiple-access (OFDMA) systems is investigated, where BSs first independently carry out subcarrier-allocation and then mitigate intercell interference (InterCI) with the aid of very limited base station (BS) cooperation. Two novel InterCI mitigation algorithms are proposed. The first one is the distributed decision making assisted cooperation (DDMC) algorithm, and the second one is the centralized decision making assisted cooperation (CDMC) algorithm. When employing the DDMC algorithm, each BS independently makes the InterCI mitigation decisions. By contrast, when employing the CDMC algorithm, the centralized InterCI mitigation decisions are made with the aid of the cell-edge users’ discrete InterCI information sharing among BSs. While both the algorithms motivate to maximize the spectral-efficiency (sum rate), the CDMC algorithm also aims to maximize the frequency reuse factor. In this paper, we study and compare the performance, including spectral-efficiency of cell-edge users, frequency reuse factor, overhead, etc., of the multicell downlink OFDMA systems employing the proposed and other InterCI mitigation algorithms. Our studies show that both the DDMC and CDMC algorithms can achieve better spectral-efficiency performance than the existing on-off power (OOP) algorithm. Moreover, the CDMC algorithm is capable of achieving the performance close to the upper-bound attained by the so-called full InterCI information assisted decision making (FIIDM) algorithm, which uses exhaustive search to determine the InterCI mitigation decisions. Additionally, the CDMC algorithm is demonstrated to have the highest frequency reuse factor in addition to its spectral-efficiency advantage
A Distributed Approach to Interference Alignment in OFDM-based Two-tiered Networks
In this contribution, we consider a two-tiered network and focus on the
coexistence between the two tiers at physical layer. We target our efforts on a
long term evolution advanced (LTE-A) orthogonal frequency division multiple
access (OFDMA) macro-cell sharing the spectrum with a randomly deployed second
tier of small-cells. In such networks, high levels of co-channel interference
between the macro and small base stations (MBS/SBS) may largely limit the
potential spectral efficiency gains provided by the frequency reuse 1. To
address this issue, we propose a novel cognitive interference alignment based
scheme to protect the macro-cell from the cross-tier interference, while
mitigating the co-tier interference in the second tier. Remarkably, only local
channel state information (CSI) and autonomous operations are required in the
second tier, resulting in a completely self-organizing approach for the SBSs.
The optimal precoder that maximizes the spectral efficiency of the link between
each SBS and its served user equipment is found by means of a distributed
one-shot strategy. Numerical findings reveal non-negligible spectral efficiency
enhancements with respect to traditional time division multiple access
approaches at any signal to noise (SNR) regime. Additionally, the proposed
technique exhibits significant robustness to channel estimation errors,
achieving remarkable results for the imperfect CSI case and yielding consistent
performance enhancements to the network.Comment: 15 pages, 10 figures, accepted and to appear in IEEE Transactions on
Vehicular Technology Special Section: Self-Organizing Radio Networks, 2013.
Authors' final version. Copyright transferred to IEE
A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling
This paper presents a novel framework for modeling the uplink intercell
interference (ICI) in a multiuser cellular network. The proposed framework
assists in quantifying the impact of various fading channel models and
state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a
semianalytical expression for the distribution of the location of the scheduled
user in a given cell considering a wide range of scheduling schemes. Based on
this, we derive the distribution and moment generating function (MGF) of the
uplink ICI considering a single interfering cell. Consequently, we determine
the MGF of the cumulative ICI observed from all interfering cells and derive
explicit MGF expressions for three typical fading models. Finally, we utilize
the obtained expressions to evaluate important network performance metrics such
as the outage probability, ergodic capacity, and average fairness numerically.
Monte-Carlo simulation results are provided to demonstrate the efficacy of the
derived analytical expressions.Comment: IEEE Transactions on Wireless Communications, 2013. arXiv admin note:
substantial text overlap with arXiv:1206.229
Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks
The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter
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