Design and Optimization of a UAV-Enabled Non-Orthogonal Multiple Access Edge Computing IoT System

Farha, Yazan Abu; Ismail, Mahmoud H.

doi:10.1109/access.2022.3220264

Cited by 7 publications

(4 citation statements)

References 39 publications

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“…In Fig. 4, we compare our proposed system with a system using orthogonal multiple access (OMA) [66] based on the SCP and SOP values of the UWNMI network obtained in simulation runs performed with varying UAV transmit power to test SNR conditions ranging from 0 to 100 dB. The first observation is that the Monte Carlo simulation results show a strong match with our analysis, confirming the accuracy of our proposed model.…”

Section: Table 2: Simulation Parameterssupporting

confidence: 67%

Secrecy Performance Analysis and Optimization for UAV-Relay-Enabled WPT and Cooperative NOMA MEC in IoT Networks

Nguyen,

Ha,

Truong

et al. 2023

IEEE Access

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This paper investigates a system for unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) and non-orthogonal multiple access (NOMA) mobile edge computing (MEC) in the Internet of Things (IoT) UWNMI, wherein a UAV equipped with an energy transmitter (ET) acts as a relay. In particular, we consider a situation involving two clusters of IoT devices (IDs) that have limited resources and therefore are unable to compute their own tasks and must instead offload them to a base station (BS) via the UAV relay (UR) in the presence of a passive eavesdropper. In the UWNMI system, the effects of imperfect channel state information (ICSI) and imperfect successive interference cancellation (ISIC) are considered, along with the usage of artificial noise (AN) to improve the physical layer security (PLS) of the system. We derive closed-form expressions for the successful computation probability (SCP) and secrecy outage probability (SOP) under the Nakagami-m fading channel model in order to evaluate the performance of the system. Moreover, we present optimization problems with the objectives of optimizing the position and height of the UR, the time switching ratio (TSR), and the power allocation for the AN in order to maximize the SCP and minimize the SOP. These problems are solved using a particle swarm optimization (PSO)based algorithm. In addition, Monte Carlo simulation results are presented to validate the accuracy of our analysis based on simulations of the system performance under different values of the system parameters, including the number of antennas at the BS, the number of IDs in each cluster, the TSR, and the position and height of the UR.INDEX TERMS Internet of Things, unmanned aerial vehicles, energy harvesting, wireless power transfer, non-orthogonal multiple access, mobile edge computing, physical layer security. I. INTRODUCTIONRecent developments in Internet of Things (IoT) technology have inspired a multitude of unique applications, including intelligent grazing, autonomous control, and environmental monitoring [1]- [4]. For an IoT system to collect environmental data, many IoT devices (IDs) must be dis-tributed. Typically, these IDs are powered by limited-capacity batteries that must be routinely updated or recharged. Radio frequency (RF)-signal-based wireless power transfer (WPT), also known as RF energy harvesting (EH), has been widely acknowledged as a promising solution for powering lowpower IDs autonomously, thereby eliminating the need to

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Section: Table 2: Simulation Parameterssupporting

confidence: 67%

Secrecy Performance Analysis and Optimization for UAV-Relay-Enabled WPT and Cooperative NOMA MEC in IoT Networks

Nguyen,

Ha,

Truong

et al. 2023

IEEE Access

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“…IoT has an extensive variety of applications including smart houses, asset tracking, healthcare monitoring, environmental monitoring, and industrial automation. On the other hand, IoT networks rely on wireless transmission technologies like cellular networks, WiFi, Bluetooth, ZigBee, and OWC technologies [143].…”

Section: Opportunities and Applications Of Sduav Networkmentioning

confidence: 99%

Software-Defined UAV Networks for 6G Systems: Requirements, Opportunities, Emerging Techniques, Challenges, and Research Directions

Siddiki Abir,

Chowdhury,

Jang

2023

IEEE Open J. Commun. Soc.

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The ever-increasing demand for wireless communication has driven the development of innovative technologies to address the issues that conventional communication networks meet. To support autonomous devices in the sixth-generation (6G) and provide seamless wireless connectivity in inaccessible and hard-to-reach areas, the combination of software-defined networking (SDN) with unmanned aerial vehicles (UAVs) has already shown promises. As the traditional UAV-based cellular network encompasses challenges such as lack of centralized supervision, robust decision-making ability, and dynamic network management, the SDN platform could be an excellent alternative to offer aerial networking for future 6G ecosystem. However, the SDN-assisted UAV paradigm faces a set of challenges and critical issues. For instance, the network management and orchestration, resource allocation and optimization, handover mechanism, spectrum management, energy efficiency, integration of heterogeneous networks, and reliability, thus causing the decrease of quality of services of the SDN-enables UAV networks. To effectively address all these issues and identify the trends of software-defined UAV (SDUAV) networks, more research activities are needed. Unfortunately, there are not any specific guidelines in the literature that address each of these requirements, enabling technologies, emerging techniques, and future research directions in the context of SDN-based UAV networks to enable next-generation 6G systems. Therefore, motivated by this fact, this paper offers a comprehensive evaluation of the state of the SDUAV network and architecture, highlighting its various requirements and different prospects and applications in 6G systems. Besides, this paper also addresses why the combination of SDN and UAV-enabled networks is becoming essential in the 6G networking context and how it can offer more flexibility, scalability, reliability, and efficient connectivity than the conventional approaches to provide features like intelligence, automation, programmability, and centralized controllability. This paper furthermore outlines the difficulties of implementing SDUAV networks, such as security, adaptability, interference management, interoperability, and lack of standardization. Finally, to accomplish the goals, this article provides a roadmap for future trends and research directions in SDUAV networks to support the 6G systems.INDEX TERMS 6G, aerial base station, SDN, SDUAV, UAV-based cellular network. I. INTRODUCTIONThe growing trend of emerging technologies, such as artificial intelligence (AI), augmented reality (AR), virtual reality (VR), extended reality (XR), automated vehicles, electronic health (e-health), cloud computing, Internet of Things (IoT), and Industry 4.0, is culminating a massive amount of data every day [1]. Recently, the International Telecommunication Union (ITU) estimates that traffic volume will be 5016 EB/month, with traffic volume per person reaching 257.1 GB/month [2]. As a result, there will be 97 billion machine-to-machine (M...

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“…Traditional physical layer security technologies focus on improving the confidentiality of received information [9,10], for example, by changing the coding method, using redundant information in the coding to check and interfere, or changing the amplitude and phase of the transmission signal to carry additional information [11][12][13]. Physical layer security technology can improve the security transmission rate of information through pre-designed policies.…”

Section: Introductionmentioning

confidence: 99%

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

Zhang,

Niu,

Yan

2024

Computer Modeling in Engineering &Amp; Sciences

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In this paper, we consider mobile edge computing (MEC) networks against proactive eavesdropping. To maximize the transmission rate, IRS assisted UAV communications are applied. We take the joint design of the trajectory of UAV, the transmitting beamforming of users, and the phase shift matrix of IRS. The original problem is strong non-convex and difficult to solve. We first propose two basic modes of the proactive eavesdropper, and obtain the closed-form solution for the boundary conditions of the two modes. Then we transform the original problem into an equivalent one and propose an alternating optimization (AO) based method to obtain a local optimal solution. The convergence of the algorithm is illustrated by numerical results. Further, we propose a zero forcing (ZF) based method as sub-optimal solution, and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes. KEYWORDSMobile edge computing (MEC); unmanned aerial vehicle (UAV); intelligent reflecting surface (IRS); zero forcing (ZF)

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Design and Optimization of a UAV-Enabled Non-Orthogonal Multiple Access Edge Computing IoT System

Cited by 7 publications

References 39 publications

Secrecy Performance Analysis and Optimization for UAV-Relay-Enabled WPT and Cooperative NOMA MEC in IoT Networks

Secrecy Performance Analysis and Optimization for UAV-Relay-Enabled WPT and Cooperative NOMA MEC in IoT Networks

Software-Defined UAV Networks for 6G Systems: Requirements, Opportunities, Emerging Techniques, Challenges, and Research Directions

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

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