An Energy Efficient Framework for UAV-Assisted Millimeter Wave 5G Heterogeneous Cellular Networks

Chakareski, Jacob; Naqvi, Syed Ahsan Raza; Mastronarde, Nicholas; Xu, Jie; Afghah, Fatemeh; Razi, Abolfazl

doi:10.1109/tgcn.2019.2892141

Cited by 86 publications

(47 citation statements)

References 22 publications

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“…The problem of resource management has been broadly involved in several network scenarios [36], [164]- [168], but not well explored in UAV-assisted wireless networks with mmWave communications. In what follows, the related research progress on resource management in our considered scenario will be summarized from two aspects according to what kind of network resources to be managed, i.e., power and subcarrier allocation [169], [170] and caching optimization [37], [171].…”

Section: E Resource Managementmentioning

confidence: 99%

“…In order to efficiently exploit the advantages of 5G HetNets assisted by UAVs, Chakareski et al [169] and Naqvi et al [170] envisaged a novel HetNet architecture that employed the dual operational frequency bands in comparison with traditional HetNets. Specifically, the HetNet architecture consisted of a macro ground BS operating at microwave band, multiple dual-mode small ground BSs operating at two kinds of mmWave bands, and multiple UAV-based flying small BSs operating at microwave band.…”

Section: ) Power and Subcarrier Allocationmentioning

confidence: 99%

“…Additionally, ground users can be served by three kinds of cases: i) microwave ground macro BS, ii) microwave flying small BSs (SBSs), and iii) ground SBSs with lower mmWave bands represented by L and higher mmWave bands denoted by H . Under this scenario of interest, Chakareski et al [169] and Naqvi et al [170] designed an efficient radio resource management optimization framework for mmWave 5G Het-Nets empowered by flying SBSs. For the case of microwave ground macro BS, joint optimization of achievable rate and energy efficiency of all ground users was formulated as an optimization problem to maximize the sum rate and minimize the total power consumption for ground users simultaneously, while satisfying the minimum QoS and the maximum transmit power constraints.…”

Section: ) Power and Subcarrier Allocationmentioning

confidence: 99%

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A Survey on 5G Millimeter Wave Communications for UAV-Assisted Wireless Networks

et al. 2019

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In recent years, unmanned aerial vehicles (UAVs) have received considerable attention from regulators, industry and research community, due to rapid growth in a broad range of applications. Particularly, UAVs are being used to provide a promising solution to reliable and cost-effective wireless communications from the sky. The deployment of UAVs has been regarded as an alternative complement of existing cellular systems, to achieve higher transmission efficiency with enhanced coverage and capacity. However, heavily utilized microwave spectrum bands below 6 GHz utilized by legacy wireless systems are insufficient to attain remarkable data rate enhancement for numerous emerging applications. To resolve the spectrum crunch crisis and satisfy the requirements of 5G and beyond mobile communications, one potential solution is to use the abundance of unoccupied bandwidth available at millimeter wave (mmWave) frequencies. Inspired by the technique potentials, mmWave communications have also paved the way into the widespread use of UAVs to assist wireless networks for future 5G and beyond wireless applications. In this paper, we provide a comprehensive survey on current achievements in the integration of 5G mmWave communications into UAV-assisted wireless networks. More precisely, a taxonomy to classify the existing research issues is presented, by considering seven cutting-edge solutions. Subsequently, we provide a brief overview of 5G mmWave communications for UAV-assisted wireless networks from two aspects, i.e., key technical advantages and challenges as well as potential applications. Based on the proposed taxonomy, we further discuss in detail the state-of-the-art issues, solutions, and open challenges for this newly emerging area. Lastly, we complete this survey by pointing out open issues and shedding new light on future directions for further research on this area. INDEX TERMSMillimeter wave (mmWave) communications, unmanned aerial vehicle (UAV), mmWave UAV communications, UAV-assisted wireless networks, 5G and beyond.HAITAO XU received the B.E. degree in communication engineering from Sun Yat-sen University, Guangzhou, China, in 2007, the M.E. degree in communication system and signal processing from the University of Bristol, U.K., in 2009, and the Ph.D. degree in communication and information systems from the

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Section: E Resource Managementmentioning

confidence: 99%

Section: ) Power and Subcarrier Allocationmentioning

confidence: 99%

Section: ) Power and Subcarrier Allocationmentioning

confidence: 99%

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A Survey on 5G Millimeter Wave Communications for UAV-Assisted Wireless Networks

et al. 2019

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“…The authors claimed that there is a need to find the optimal balancing point between the tradeoff of spectral and energy efficiency. Energy-efficient scheduling techniques were proposed by the authors of [26,27] for conventional small-cell cellular networks and unmanned aerial vehicle (UAV) assisted small-cell communications [28]. In a similar manner, the user association problem was investigated by the authors of [29].…”

Section: Related Workmentioning

confidence: 99%

Efficient Power Control Framework for Small-Cell Heterogeneous Networks

Alsafasfeh

Saraereh

Ali

et al. 2020

Sensors

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Heterogeneous networks are rapidly emerging as one of the key enablers of beyond fifth-generation (5G) wireless networks. It is gradually becoming clear to the network operators that existing cellular networks may not be able to support the traffic demands of the future. Thus, there is an upsurge in the interest of efficiently deploying small-cell networks for accommodating a growing number of user equipment (UEs). This work further extends the state-of-the-art by proposing an optimization framework for reducing the power consumption of small-cell base stations (BSs). Specifically, a novel algorithm has been proposed which dynamically switches off the redundant small-cell BSs based on the traffic demands of the network. Due to the dynamicity of the formulated problem, a new UE admission control policy has been presented when the problem becomes infeasible to solve. To validate the effectiveness of the proposed solution, the simulation results are compared with conventional techniques. It is shown that the proposed power control solution outperforms the conventional approaches both in terms of accommodating more UEs and reducing power consumption.

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“…Khuwaja et al characterized the impact of ground user mobility, propagation environment and channel fading on the outage performance of UAV communication [16]. Chakareski et al designed an efficient resource management framework for enhanced coverage and throughput of UAVbased aerial small cells [17]. Energy limitation is a major bottleneck in UAV communication.…”

Section: A Motivationmentioning

confidence: 99%

NOMA-Aided UAV Data Collection System: Trajectory Optimization and Communication Design

et al. 2020

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Unmanned aerial vehicle (UAV) communication has been deemed as a promising technology to collect data for the Internet of Things (IoT) in inaccessible areas. However, due to the limited UAV flight time, traditional UAV communication may not be competent for large-scale IoT data collection. This paper considers integrating non-orthogonal multiple access (NOMA) into UAV communication systems to collect data for large-scale IoT devices within UAV flight time. We aim to minimize the total energy consumption of IoT devices while ensuring data collection, by jointly optimizing UAV trajectory, IoT device scheduling and transmit power. The formulated problem is a mixed integer non-convex problem, which is challenging to solve in general. We propose a data collection optimization algorithm (DCOA) to solve it by applying the Generalized Benders Decomposition (GBD) and successive convex approximation (SCA) techniques. Then, a greedy algorithm (GA) is also proposed to reduce complexity by simplifying the optimization of UAV trajectory and IoT device scheduling. Finally, the numerical results demonstrate that, compared with traditional UAV communication systems, the NOMA-aided UAV system performs better in terms of data collection and lower total energy consumption of IoT devices can be achieved by DCOA. INDEX TERMS Unmanned aerial vehicle (UAV) communication, non-orthogonal multiple access (NOMA), data collection, Internet of Things (IoT), energy consumption minimization.

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An Energy Efficient Framework for UAV-Assisted Millimeter Wave 5G Heterogeneous Cellular Networks

Cited by 86 publications

References 22 publications

A Survey on 5G Millimeter Wave Communications for UAV-Assisted Wireless Networks

A Survey on 5G Millimeter Wave Communications for UAV-Assisted Wireless Networks

Efficient Power Control Framework for Small-Cell Heterogeneous Networks

NOMA-Aided UAV Data Collection System: Trajectory Optimization and Communication Design

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