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See detailUAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory Optimization
Tran Dinh, Hieu UL; Nguyen, van Dinh UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2021)

Unmanned aerial vehicle (UAV) communication hasemerged as a prominent technology for emergency communi-cations (e.g., natural disaster) in the Internet of Things (IoT)networks to enhance the ability of ... [more ▼]

Unmanned aerial vehicle (UAV) communication hasemerged as a prominent technology for emergency communi-cations (e.g., natural disaster) in the Internet of Things (IoT)networks to enhance the ability of disaster prediction, damageassessment, and rescue operations promptly. A UAV can bedeployed as a flying base station (BS) to collect data from time-constrained IoT devices and then transfer it to a ground gateway(GW). In general, the latency constraint at IoT devices and UAV’slimited storage capacity highly hinder practical applicationsof UAV-assisted IoT networks. In this paper, full-duplex (FD)radio is adopted at the UAV to overcome these challenges. Inaddition, half-duplex (HD) scheme for UAV-based relaying isalso considered to provide a comparative study between twomodes (viz., FD and HD). Herein, a device is considered tobe successfully served iff its data is collected by the UAV andconveyed to GW timely during flight time. In this context,we aim to maximize the number of served IoT devices byjointly optimizing bandwidth, power allocation, and the UAVtrajectory while satisfying each device’s requirement and theUAV’s limited storage capacity. The formulated optimizationproblem is troublesome to solve due to its non-convexity andcombinatorial nature. Towards appealing applications, we firstrelax binary variables into continuous ones and transform theoriginal problem into a more computationally tractable form.By leveraging inner approximation framework, we derive newlyapproximated functions for non-convex parts and then develop asimple yet efficient iterative algorithm for its solutions. Next,we attempt to maximize the total throughput subject to thenumber of served IoT devices. Finally, numerical results showthat the proposed algorithms significantly outperform benchmarkapproaches in terms of the number of served IoT devices andsystem throughput. [less ▲]

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See detailBackscatter-Assisted Data Offloading inOFDMA-based Wireless Powered Mobile EdgeComputing for IoT Networks
Nguyen, Xuan Phu; Tran Dinh, Hieu UL; Onireti, ‪Oluwakayode et al

in IEEE Internet of Things Journal (2021)

Mobile edge computing (MEC) has emerged as a prominent technology to overcome sudden demands on computation-intensive applications of the Internet of Things (IoT) with finite processing capabilities ... [more ▼]

Mobile edge computing (MEC) has emerged as a prominent technology to overcome sudden demands on computation-intensive applications of the Internet of Things (IoT) with finite processing capabilities. Nevertheless, the limited energy resources also seriously hinders IoT devices from offloading tasks that consume high power in active RF communications. Despite the development of energy harvesting (EH) techniques, the harvested energy from surrounding environments could be inadequate for power-hungry tasks. Fortunately, Backscatter communications (Backcom) is an intriguing technology to narrow the gap between the power needed for communication and harvested power. Motivated by these considerations, this paper investigates a backscatter-assisted data offloading in OFDMA-based wireless-powered (WP) MEC for IoT systems. Specifically, we aim at maximizing the sum computation rate by jointly optimizing the transmit power at the gateway (GW), backscatter coefficient, time-splitting (TS) ratio, and binary decision-making matrices. This problem is challenging to solve due to its non-convexity. To find solutions, we first simplify the problem by determining the optimal values of transmit power of the GW and backscatter coefficient. Then, the original problem is decomposed into two sub-problems, namely, TS ratio optimization with given offloading decision matrices and offloading decision optimization with given TS ratio. Especially, a closedform expression for the TS ratio is obtained which greatly enhances the CPU execution time. Based on the solutions of the two sub-problems, an efficient algorithm, termed the fast-efficient algorithm (FEA), is proposed by leveraging the block coordinate descent method. Then, it is compared with exhaustive search (ES), bisection-based algorithm (BA), edge computing (EC), and local computing (LC) used as reference methods. As a result, the FEA is the best solution which results in a near-globally-optimal solution at a much lower complexity as compared to benchmark schemes. For instance, the CPU execution time of FEA is about 0.029 second in a 50-user network, which is tailored for ultralow latency applications of IoT networks. [less ▲]

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See detailResource Allocation for UAV Relay-Assisted IoT Communication Networks
Tran Dinh, Hieu UL; Nguyen, van Dinh UL; Gautam, Sumit UL et al

Scientific Conference (2020, October 06)

This work studies unmanned aerial vehicle (UAV) relay-assisted Internet of Things (IoT) communication networks in which a UAV is deployed as an aerial base station (BS) to collect time-constrained data ... [more ▼]

This work studies unmanned aerial vehicle (UAV) relay-assisted Internet of Things (IoT) communication networks in which a UAV is deployed as an aerial base station (BS) to collect time-constrained data from IoT devices and transfer information to a ground gateway (GW). In this context, we jointly optimize the allocated bandwidth, transmission power, as well as the UAV trajectory to maximize the total system throughput while satisfying the user’s latency requirement and the UAV’s limited storage capacity. The formulated problem is strongly nonconvex which is very challenging to solve optimally. Towards an appealing solution, we first introduce new variables to convert the original problem into a computationally tractable form, and then develop an iterative algorithm for its solution by leveraging the inner approximation method. Numerical results are given to show [less ▲]

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See detailUAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory Optimization
Tran Dinh, Hieu UL; Nguyen, van Dinh UL; Gautam, Sumit UL et al

E-print/Working paper (2020)

Unmanned aerial vehicle (UAV) communication has emerged as a prominent technology for emergency communications (e.g., natural disaster) in Internet of Things (IoT) networks to enhance the ability of ... [more ▼]

Unmanned aerial vehicle (UAV) communication has emerged as a prominent technology for emergency communications (e.g., natural disaster) in Internet of Things (IoT) networks to enhance the ability of disaster prediction, damage assessment, and rescue operations promptly. In this paper, a UAV is deployed as a flying base station (BS) to collect data from time-constrained IoT devices and then transfer the data to a ground gateway (GW). In general, the latency constraint at IoT users and the limited storage capacity of UAV highly hinder practical applications of UAV-assisted IoT networks. In this paper, full-duplex (FD) technique is adopted at the UAV to overcome these challenges. In addition, half-duplex (HD) scheme for UAV-based relaying is also considered to provide a comparative study between two modes (viz., FD and HD). Herein, a device is successfully served iff its data is collected by UAV and conveyed to GW within the flight time. In this context, we aim at maximizing the number of served IoT devices by jointly optimizing bandwidth and power allocation, as well as the UAV trajectory, while satisfying the requested timeout (RT) requirement of each device and the UAV’s limited storage capacity. The formulated optimization problem is troublesome to solve due to its non-convexity and combinatorial nature. Toward appealing applications, we first relax binary variables into continuous values and transform the original problem into a more computationally tractable form. By leveraging inner approximation framework, we derive newly approximated functions for non-convex parts and then develop a simple yet efficient iterative algorithm for its solutions. Next, we attempt to maximize the total throughput subject to the number of served IoT devices. Finally, numerical results show that the proposed algorithms significantly outperform benchmark approaches in terms of the number of served IoT devices and the amount of collected data. [less ▲]

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See detailCoarse Trajectory Design for Energy Minimization in UAV-enabled Wireless Communications with Latency Constraints
Tran Dinh, Hieu UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Vehicular Technology (2020)

In this paper, we design the UAV trajectory to minimize the total energy consumption while satisfying the requested timeout (RT) requirement and energy budget, which is accomplished via jointly optimizing ... [more ▼]

In this paper, we design the UAV trajectory to minimize the total energy consumption while satisfying the requested timeout (RT) requirement and energy budget, which is accomplished via jointly optimizing the path and UAV’s velocities along subsequent hops. The corresponding optimization problem is difficult to solve due to its non-convexity and combinatorial nature. To overcome this difficulty, we solve the original problem via two consecutive steps. Firstly, we propose two algorithms, namely heuristic search, and dynamic programming (DP) to obtain a feasible set of paths without violating the GU’s RT requirements based on the traveling salesman problem with time window (TSPTW). Then, they are compared with exhaustive search and traveling salesman problem (TSP) used as reference methods. While the exhaustive algorithm achieves the best performance at a high computation cost, the heuristic algorithm exhibits poorer performance with low complexity. As a result, the DP is proposed as a practical trade-off between the exhaustive and heuristic algorithms. Specifically, the DP algorithm results in near-optimal performance at a much lower complexity. Secondly, for given feasible paths, we propose an energy minimization problem via a joint optimization of the UAV’s velocities along subsequent hops. Finally, numerical results are presented to demonstrate the effectiveness of our proposed algorithms. The results show that the DP-based algorithm approaches the exhaustive search’s performance with a significantly reduced complexity. It is also shown that the proposed solutions outperform the state-of-theart benchmarks in terms of both energy consumption and outage performance. [less ▲]

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See detailEnergy-efficient Trajectory Design for UAV-enabled Wireless Communications with Latency Constraints
Tran Dinh, Hieu UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

Scientific Conference (2019, November 03)

This paper studies a new energy-efficient unmanned aerial vehicle (UAV)-enabled wireless communications, where the UAV acts as a flying base station (BS) to serve the ground users (GUs) within some ... [more ▼]

This paper studies a new energy-efficient unmanned aerial vehicle (UAV)-enabled wireless communications, where the UAV acts as a flying base station (BS) to serve the ground users (GUs) within some predetermined latency limitations, e.g., requested timeout (RT). Our goal is to design the UAV trajectory to minimize the total energy consumption while satisfying the RT requirement from every GU, which is accomplished via two consecutive subproblems: traveling time minimization and energy minimization problems. Firstly, we propose two exhaustive search and heuristic algorithms based on the traveling salesman problem with time window (TSPTW) in order to minimize the UAV’s traveling time without violating the GUs’ RT requirements. While the exhaustive algorithm achieves the best performance at a high computation cost, the heuristic algorithm achieves a trade-off between the performance and complexity. Secondly, we minimize the total energy consumption, for a given trajectory, via a joint optimization of the UAV’s velocity along subsequent hops. Finally, numerical results are presented to demonstrate the effectiveness of our proposed algorithms. In particular, it is shown that the proposed solutions outperform the reference in terms of both energy consumption and outage performance. [less ▲]

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See detailPerformance Enhancement for Multihop Harvest-to-Transmit WSNs With Path-Selection Methods in Presence of Eavesdroppers and Hardware Noises
Tran Dinh, Hieu UL; Tran, Trung Duy; Kim, Bung-Seo

in IEEE Sensors Journal (2018), 18(12), 5173-5186

Energy-harvesting-based physical layer security (PLS) has become a promising technique, as it not only secures information from eavesdropping without upper layer data encryption, but it also improves the ... [more ▼]

Energy-harvesting-based physical layer security (PLS) has become a promising technique, as it not only secures information from eavesdropping without upper layer data encryption, but it also improves the energy efficiency of wireless networks. However, it imposes new challenges, as adversary parties can overhear the transmission of confidential information between the source and destination via a relay. Therefore, the transmit power of the signals must be large enough for energy harvesting, but it must also be small enough to avoid eavesdropping. This is even more challenging with multi-hop multi-path wireless networks. Motivated by these observations, this paper proposes three innovative protocols, namely, the shortest path selection (SPS) protocol, random path selection (RPS) protocol, and best path selection (BPS) protocol. These will enhance the security of multi-hop multi-path randomize-and-forward (RF) cooperative wireless sensor networks (WSNs) under the presence of eavesdroppers and hardware impairment, wherein the source node and relay nodes are capable of harvesting energy from beacon for data transmission. Furthermore, we derive exact closed-form expressions and the asymptotic outage probability for each protocol under multiple eavesdropping attacks. The simulation results validate the theoretical results. [less ▲]

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