257 research outputs found
Performance Analysis for 5G cellular networks: Millimeter Wave and UAV Assisted Communications
Recent years have witnessed exponential growth in mobile data and traffic. Limited available spectrum in microwave (Wave) bands does not seem to be capable of meeting this demand in the near future, motivating the move to new frequency bands. Therefore, operating with large available bandwidth at millimeter wave (mmWave) frequency bands, between 30 and 300 GHz, has become an appealing choice for the fifth generation (5G) cellular networks. In addition to mmWave cellular networks, the deployment of unmanned aerial vehicle (UAV) base stations (BSs), also known as drone BSs, has attracted considerable attention recently as a possible solution to meet the increasing data demand. UAV BSs are expected to be deployed in a variety of scenarios including public safety communications, data collection in Internet of Things (IoT) applications, disasters, accidents, and other emergencies and also temporary events requiring substantial network resources in the short-term. In these scenarios, UAVs can provide wireless connectivity rapidly.
In this thesis, analytical frameworks are developed to analyze and evaluate the performance of mmWave cellular networks and UAV assisted cellular networks. First, the analysis of average symbol error probability (ASEP) in mmWave cellular networks with Poisson Point Process (PPP) distributed BSs is conducted using tools from stochastic geometry. Secondly, we analyze the energy efficiency of relay-assisted downlink mmWave cellular networks. Then, we provide an stochastic geometry framework to study heterogeneous downlink mmWave cellular networks consisting of tiers of randomly located BSs, assuming that each tier operates in a mmWave frequency band. We further study the uplink performance of the mmWave cellular networks by considering the coexistence of cellular and potential D2D user equipments (UEs) in the same band. In addition to mmWave cellular networks, the performance of UAV assisted cellular networks is also studied. Signal-to-interference-plus-noise ratio (SINR) coverage performance analysis for UAV assisted networks with clustered users is provided. Finally, we study the energy coverage performance of UAV energy harvesting networks with clustered users
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
Modeling and Analysis of D2D Millimeter-Wave Networks With Poisson Cluster Processes
This paper investigates the performance of millimeter wave (mmWave)
communications in clustered device-to-device (D2D) networks. The locations of
D2D transceivers are modeled as a Poisson Cluster Process (PCP). In each
cluster, devices are equipped with multiple antennas, and the active D2D
transmitter (D2D-Tx) utilizes mmWave to serve one of the proximate D2D
receivers (D2D-Rxs). Specifically, we introduce three user association
strategies: 1) Uniformly distributed D2D-Tx model; 2) Nearest D2D-Tx model; 3)
Closest line-of-site (LOS) D2D-Tx model. To characterize the performance of the
considered scenarios, we derive new analytical expressions for the coverage
probability and area spectral efficiency (ASE). Additionally, in order to
efficiently illustrating the general trends of our system, a closed-form lower
bound for the special case interfered by intra-cluster LOS links is derived. We
provide Monte Carlo simulations to corroborate the theoretical results and show
that: 1) The coverage probability is mainly affected by the intra-cluster
interference with LOS links; 2) There exists an optimum number of
simultaneously active D2D-Txs in each cluster for maximizing ASE; and 3)
Closest LOS model outperforms the other two scenarios but at the cost of extra
system overhead.Comment: This paper has been published in IEEE Transactions on Communications.
Please cite the formal version of this pape
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