Flexible and Reliable Multiuser SWIPT IoT Network Enhanced by UAV-Mounted Intelligent Reflecting Surface

Liu, Yuan; Han, Fengxia; Zhao, Shengjie

doi:10.1109/tr.2022.3161336

Cited by 19 publications

(11 citation statements)

References 47 publications

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“…Additionally, there are 3, 10, or 15 UAVs with an altitude 2 between 200 and 500 m. In downlink and uplink, respectively the UAV requests 1 and 5 RBs. Furthermore, we run 1000 2 It is also worth mentioning that according to 3GPP release 15, for UAVs flying at a high altitude i.e., above 100 m, there is a 100% probability of achieving the LoS. Moreover, LoS path-loss will dominate over the other NLoS components.…”

Section: Numerical Resultsmentioning

confidence: 99%

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Intercell Interference Coordination for UAV Enabled URLLC With Perfect/Imperfect CSI Using Cognitive Radio

Ranjha

Javed

Srivastava

et al. 2023

IEEE Open J. Commun. Soc.

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Ultra-reliable and low latency communications (URLLC) will be the backbone of the upcoming sixth-generation (6G) systems and will facilitate mission-critical scenarios. A design accounting for stringent reliability and latency requirements for URLLC systems poses a challenge for both industry and academia. Recently, unmanned aerial vehicles (UAV) have emerged as a potential candidate to support communications in futuristic wireless systems due to providing favourable channel gains thanks to Lineof-Sight (LoS) communications. However, usage of UAV in cellular infrastructure increases interference in aerial and terrestrial user equipment (UE) limiting the performance gain of UAV-assisted cellular systems. To resolve these issues, we propose low-complexity algorithms for intercell interference coordination (ICIC) using cognitive radio when single and multi-UAVs are deployed in a cellular environment to facilitate URLLC services. Moreover, we model BS-to-UAV (B2U) interference in downlink communication, whereas in the uplink we model UAV-to-BS (U2B), UAV-to-UAV (U2U), and UE-to-UAV (UE2U) interference under perfect/imperfect channel state information (CSI). Results demonstrate that the proposed perfect ICIC accounts for fairness among UAVs especially in downlink communications compared to conventional ICIC algorithms. Furthermore, in general, the proposed UAV-sensing assisted ICIC and perfect ICIC algorithms yield better performance than conventional ICIC for both uplink and downlink for the single and multi-UAV framework.INDEX TERMS URLLC, multi-UAV, cognitive radio, intercell interference coordination (ICIC).

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Section: Numerical Resultsmentioning

confidence: 99%

“…Transmission power of BS j in RB n F j (k, n) Downlink channel power gain from BS j to UAV k in RB n σ 2 Received Gaussian noise power at any UAV I dl (k, n)…”

Section: Introductionmentioning

confidence: 99%

Intercell Interference Coordination for UAV Enabled URLLC With Perfect/Imperfect CSI Using Cognitive Radio

Ranjha

Javed

Srivastava

et al. 2023

IEEE Open J. Commun. Soc.

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“…Meanwhile, as a promising technology, intelligent reflecting surface (IRS)-aided SWIPT in UAV networks has drawn much attention recently [47,48]. In [47], the authors studied a UAV network supported by IRS and SWIPT and proposed an alternating optimization (AO) algorithm to minimize all users' energy consumption.…”

Section: Related Workmentioning

confidence: 99%

Joint Trajectory Planning, Time and Power Allocation to Maximize Throughput in UAV Network

Wang

Li³

et al. 2023

Drones

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Due to the advantages of strong mobility, flexible deployment, and low cost, unmanned aerial vehicles (UAVs) are widely used in various industries. As a flying relay, UAVs can establish line-of-sight (LOS) links for different scenarios, effectively improving communication quality. In this paper, considering the limited energy budget of UAVs and the existence of multiple jammers, we introduce a simultaneous wireless information and power transfer (SWIPT) technology and study the problems of joint-trajectory planning, time, and power allocation to increase communication performance. Specifically, the network includes multiple UAVs, source nodes (SNs), destination nodes (DNs), and jammers. We assume that the UAVs need to communicate with DNs, the SNs use the SWIPT technology to transmit wireless energy and information to UAVs, and the jammers can interfere with the channel from UAVs to DNs. In this network, our target was to maximize the throughput of DNs by optimizing the UAV’s trajectory, time, and power allocation under the constraints of jammers and the actual motion of UAVs (including UAV energy budget, maximum speed, and anti-collision constraints). Since the formulated problem was non-convex and difficult to solve directly, we first decomposed the original problem into three subproblems. We then solved the subproblems by applying a successive convex optimization technology and a slack variables method. Finally, an efficient joint optimization algorithm was proposed to obtain a sub-optimal solution by using a block coordinate descent method. Simulation results indicated that the proposed algorithm has better performance than the four baseline schemes.

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“…Several researchers have demonstrated communication environment achieved by IRS to support existing wireless communication techniques in terms of efficiency, resource allocation, max-min fairness, sum-rates maximization, weighted sum-power etc., to benefit WPT and SWIPT. In [ 79 ], authors reported UAV-IRS assisted SWIPT for IoT networks. The presented results show that using reliable and flexible UAV-IRS, the minimum achievable rate can be effectively enhanced.…”

Section: Emerging Technologiesmentioning

confidence: 99%

“…This study focuses on maximizing the total throughput by join optimization of the transmit power and trajectory of Master-UAV. In [ 79 ], the authors investigate the IRS-UAV-aided SWIPT for IoT networks. Particularly, an IRS carried by UAV is used to transmit information and power from the access point to multiple IoT devices.…”

Section: Emerging Technologiesmentioning

confidence: 99%

Intelligent Reflecting Surfaces Assisted UAV Communications for Massive Networks: Current Trends, Challenges, and Research Directions

Mohsan

Khan

Alsharif

et al. 2022

Sensors

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A intelligent reflecting surface (IRS) can intelligently configure wavefronts such as amplitude, frequency, phase, and even polarization through passive reflections and without requiring any radio frequency (RF) chains. It is predicted to be a revolutionizing technology with the capability to alter wireless communication to enhance both spectrum and energy efficiencies with low expenditure and low energy consumption. Similarly, unmanned aerial vehicle (UAV) communication has attained a significant interest by research fraternity due to high mobility, flexible deployment, and easy integration with other technologies. However, UAV communication can face obstructions and eavesdropping in real-time scenarios. Recently, it is envisaged that IRS and UAV can combine together to achieve unparalleled opportunities in difficult environments. Both technologies can achieve enhanced performance by proactively altering the wireless propagation through maneuver control and smart signal reflections in three-dimensional space. This study briefly discusses IRS-assisted UAV communications. We survey the existing literature on this emerging research topic for both ground and airborne scenarios. We highlight several emerging technologies and application scenarios for future wireless networks. This study goes one step further to elaborate research opportunities to design and optimize wireless systems with low energy footprint and at low cost. Finally, we shed some light on open challenges and future research directions for IRS-assisted UAV communication.

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Flexible and Reliable Multiuser SWIPT IoT Network Enhanced by UAV-Mounted Intelligent Reflecting Surface

Cited by 19 publications

References 47 publications

Intercell Interference Coordination for UAV Enabled URLLC With Perfect/Imperfect CSI Using Cognitive Radio

Intercell Interference Coordination for UAV Enabled URLLC With Perfect/Imperfect CSI Using Cognitive Radio

Joint Trajectory Planning, Time and Power Allocation to Maximize Throughput in UAV Network

Intelligent Reflecting Surfaces Assisted UAV Communications for Massive Networks: Current Trends, Challenges, and Research Directions

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