76 research outputs found
A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches
Wireless communication networks have been witnessing an unprecedented demand
due to the increasing number of connected devices and emerging bandwidth-hungry
applications. Albeit many competent technologies for capacity enhancement
purposes, such as millimeter wave communications and network densification,
there is still room and need for further capacity enhancement in wireless
communication networks, especially for the cases of unusual people gatherings,
such as sport competitions, musical concerts, etc. Unmanned aerial vehicles
(UAVs) have been identified as one of the promising options to enhance the
capacity due to their easy implementation, pop up fashion operation, and
cost-effective nature. The main idea is to deploy base stations on UAVs and
operate them as flying base stations, thereby bringing additional capacity to
where it is needed. However, because the UAVs mostly have limited energy
storage, their energy consumption must be optimized to increase flight time. In
this survey, we investigate different energy optimization techniques with a
top-level classification in terms of the optimization algorithm employed;
conventional and machine learning (ML). Such classification helps understand
the state of the art and the current trend in terms of methodology. In this
regard, various optimization techniques are identified from the related
literature, and they are presented under the above mentioned classes of
employed optimization methods. In addition, for the purpose of completeness, we
include a brief tutorial on the optimization methods and power supply and
charging mechanisms of UAVs. Moreover, novel concepts, such as reflective
intelligent surfaces and landing spot optimization, are also covered to capture
the latest trend in the literature.Comment: 41 pages, 5 Figures, 6 Tables. Submitted to Open Journal of
Communications Society (OJ-COMS
Computational efficiency maximization for UAV-assisted MEC network with energy harvesting in disaster scenarios
Wireless networks are expected to provide unlimited connectivity to an increasing number of heterogeneous devices. Future wireless networks (sixth-generation (6G)) will accomplish this in
three-dimensional (3D) space by combining terrestrial and aerial networks. However, effective
resource optimization and standardization in future wireless networks are challenging because of
massive resource-constrained devices, diverse quality-of-service (QoS) requirements, and a high
density of heterogeneous devices. Recently, unmanned aerial vehicle (UAV)-assisted mobile edge
computing (MEC) networks are considered a potential candidate to provide effective and efficient
solutions for disaster management in terms of disaster monitoring, forecasting, in-time response,
and situation awareness. However, the limited size of end-user devices comes with the limitation
of battery lives and computational capacities. Therefore, offloading, energy consumption and computational efficiency are significant challenges for uninterrupted communication in UAV-assisted
MEC networks. In this thesis, we consider a UAV-assisted MEC network with energy harvesting (EH). To achieve this, we mathematically formulate a mixed integer non-linear programming
problem to maximize the computational efficiency of UAV-assisted MEC networks with EH under
disaster situations. A power splitting architecture splits the source power for communication and
EH. We jointly optimize user association, the transmission power of UE, task offloading time, and
UAV’s optimal location. To solve this optimization problem, we divide it into three stages. In the
first stage, we adopt k-means clustering to determine the optimal locations of the UAVs. In the
second stage, we determine user association. In the third stage, we determine the optimal power of
UE and offloading time using the optimal UAV location from the first stage and the user association
indicator from the second stage, followed by linearization and the use of interior-point method to
solve the resulting linear optimization problem. Simulation results for offloading, no-offloading,
offloading with EH, and no-offloading no-EH scenarios are presented with a varying number of
UAVs and UEs. The results show the proposed EH solution’s effectiveness in offloading scenarios compared to no-offloading scenarios in terms of computational efficiency, bits computed, and
energy consumptio
Ruin Theory for User Association and Energy Optimization in Multi-access Edge Computing
In this letter, a novel framework is proposed for analyzing data offloading
in a multi-access edge computing system. Specifically, a two-phase algorithm,
is proposed, including two key phases: \emph{1) user association phase} and
\emph{2) task offloading phase}. In the first phase, a ruin theory-based
approach is developed to obtain the users association considering the users'
transmission reliability. Meanwhile, in the second phase, an optimization-based
algorithm is used to optimize the data offloading process. In particular, ruin
theory is used to manage the user association phase, and a ruin
probability-based preference profile is considered to control the priority of
proposing users. Here, ruin probability is derived by the surplus buffer space
of each edge node at each time slot. Giving the association results, an
optimization problem is formulated to optimize the amount of offloaded data
aiming at minimizing the energy consumption of users. Simulation results show
that the developed solutions guarantee system reliability under a tolerable
value of surplus buffer size and minimize the total energy consumption of all
users.Comment: This paper has been submitted to IEEE Wireless Communications Letter
Blockchain-based distributive auction for relay-assisted secure communications
Physical layer security (PLS) is considered as a promising technique to prevent information eavesdropping in wireless systems. In this context, cooperative relaying has emerged as a robust solution for achieving PLS due to multipath diversity and relatively lower transmission power. However, relays or the relay operators in the practical environment are unwilling for service provisioning unless they are incentivized for their cost of services. Thus, it is required to jointly consider network economics and relay cooperation to improve system efficiency. In this paper, we consider the problem of joint network economics and PLS using cooperative relaying and jamming. Based on the double auction theory, we model the interaction between transmitters seeking for a particular level of secure transmission of information and relay operators for suitable relay and jammer assignment, in a multiple source-destination networks. In addition, theoretical analyses are presented to justify that the proposed auction mechanism satisfies the desirable economic properties of individual rationality, budget balance, and truthfulness. As the participants in the traditional centralized auction framework may take selfish actions or collude with each other, we propose a decentralized and trustless auction framework based on blockchain technology. In particular, we exploit the smart contract feature of blockchain to construct a completely autonomous framework, where all the participants are financially enforced by smart contract terms. The security properties of the proposed framework are also discussed
Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing
Wireless communication at the terahertz (THz) frequency bands (0.1-10THz) is
viewed as one of the cornerstones of tomorrow's 6G wireless systems. Owing to
the large amount of available bandwidth, THz frequencies can potentially
provide wireless capacity performance gains and enable high-resolution sensing.
However, operating a wireless system at the THz-band is limited by a highly
uncertain channel. Effectively, these channel limitations lead to unreliable
intermittent links as a result of a short communication range, and a high
susceptibility to blockage and molecular absorption. Consequently, such
impediments could disrupt the THz band's promise of high-rate communications
and high-resolution sensing capabilities. In this context, this paper
panoramically examines the steps needed to efficiently deploy and operate
next-generation THz wireless systems that will synergistically support a
fellowship of communication and sensing services. For this purpose, we first
set the stage by describing the fundamentals of the THz frequency band. Based
on these fundamentals, we characterize seven unique defining features of THz
wireless systems: 1) Quasi-opticality of the band, 2) THz-tailored wireless
architectures, 3) Synergy with lower frequency bands, 4) Joint sensing and
communication systems, 5) PHY-layer procedures, 6) Spectrum access techniques,
and 7) Real-time network optimization. These seven defining features allow us
to shed light on how to re-engineer wireless systems as we know them today so
as to make them ready to support THz bands. Furthermore, these features
highlight how THz systems turn every communication challenge into a sensing
opportunity. Ultimately, the goal of this article is to chart a forward-looking
roadmap that exposes the necessary solutions and milestones for enabling THz
frequencies to realize their potential as a game changer for next-generation
wireless systems.Comment: 26 pages, 6 figure
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Robust, Resilient Networked Communication in Challenged Environments
In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication
Reconfigurable Intelligent Surfaces Aided Multi-Cell NOMA Networks: A Stochastic Geometry Model
By activating blocked users and altering successive interference cancellation (SIC) sequences, reconfigurable intelligent surfaces (RISs) become promising for enhancing non-orthogonal multiple access (NOMA) systems. To evaluate the benefits between RISs and NOMA, a downlink RIS-aided multi-cell-NOMA network is investigated via stochastic geometry. We first introduce the unique path loss model for RIS reflecting channels. Then, we evaluate the angle distributions based on a Poisson cluster process (PCP) model, which theoretically demonstrates that the angles of incidence and reflection are uniformly distributed. Additionally, we derive closed-form analytical and asymptotic expressions for coverage probabilities of the paired NOMA users. Lastly, we derive the analytical expressions of the ergodic rate for both of the paired NOMA users and calculate the asymptotic expressions for the typical user. The analytical results indicate that 1) the achievable rates reach an upper limit when the length of RIS increases; 2) exploiting RISs can enhance the path loss intercept to improve the performance without influencing the bandwidth. The simulation results show that 1) RIS-aided networks have superior performance than the networks without RISs; and 2) the SIC order in NOMA systems can be altered since RISs are able to change the channel quality of NOMA users
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