599 research outputs found
Downlink and Uplink Cell Association with Traditional Macrocells and Millimeter Wave Small Cells
Millimeter wave (mmWave) links will offer high capacity but are poor at
penetrating into or diffracting around solid objects. Thus, we consider a
hybrid cellular network with traditional sub 6 GHz macrocells coexisting with
denser mmWave small cells, where a mobile user can connect to either
opportunistically. We develop a general analytical model to characterize and
derive the uplink and downlink cell association in view of the SINR and rate
coverage probabilities in such a mixed deployment. We offer extensive
validation of these analytical results (which rely on several simplifying
assumptions) with simulation results. Using the analytical results, different
decoupled uplink and downlink cell association strategies are investigated and
their superiority is shown compared to the traditional coupled approach.
Finally, small cell biasing in mmWave is studied, and we show that
unprecedented biasing values are desirable due to the wide bandwidth.Comment: 30 pages, 9 figures. Submitted to IEEE Transactions on Wireless
Communication
User Transmit Power Minimization through Uplink Resource Allocation and User Association in HetNets
The popularity of cellular internet of things (IoT) is increasing day by day
and billions of IoT devices will be connected to the internet. Many of these
devices have limited battery life with constraints on transmit power. High user
power consumption in cellular networks restricts the deployment of many IoT
devices in 5G. To enable the inclusion of these devices, 5G should be
supplemented with strategies and schemes to reduce user power consumption.
Therefore, we present a novel joint uplink user association and resource
allocation scheme for minimizing user transmit power while meeting the quality
of service. We analyze our scheme for two-tier heterogeneous network (HetNet)
and show an average transmit power of -2.8 dBm and 8.2 dBm for our algorithms
compared to 20 dBm in state-of-the-art Max reference signal received power
(RSRP) and channel individual offset (CIO) based association schemes
A Data-Aided Channel Estimation Scheme for Decoupled Systems in Heterogeneous Networks
Uplink/downlink (UL/DL) decoupling promises more flexible cell association
and higher throughput in heterogeneous networks (HetNets), however, it hampers
the acquisition of DL channel state information (CSI) in time-division-duplex
(TDD) systems due to different base stations (BSs) connected in UL/DL. In this
paper, we propose a novel data-aided (DA) channel estimation scheme to address
this problem by utilizing decoded UL data to exploit CSI from received UL data
signal in decoupled HetNets where a massive multiple-input multiple-output BS
and dense small cell BSs are deployed. We analytically estimate BER performance
of UL decoded data, which are used to derive an approximated normalized mean
square error (NMSE) expression of the DA minimum mean square error (MMSE)
estimator. Compared with the conventional least square (LS) and MMSE, it is
shown that NMSE performances of all estimators are determined by their
signal-to-noise ratio (SNR)-like terms and there is an increment consisting of
UL data power, UL data length and BER values in the SNR-like term of DA method,
which suggests DA method outperforms the conventional ones in any scenarios.
Higher UL data power, longer UL data length and better BER performance lead to
more accurate estimated channels with DA method. Numerical results verify that
the analytical BER and NMSE results are close to the simulated ones and a
remarkable gain in both NMSE and DL rate can be achieved by DA method in
multiple scenarios with different modulations
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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