Dynamic Base Station Repositioning to Improve Performance of Drone Small Cells

Fotouhi, Azade; Ding, Ming; Hassan, Mahbub

doi:10.1109/glocomw.2016.7848883

Cited by 61 publications

(57 citation statements)

References 11 publications

(13 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Improving resilience of wireless networks is investigated in [12]- [15]. Downlink coverage analysis is conducted for a single drone-BS in [14], and for a 3D drone-BS network in [16]. Although studies discussed so far consider hovering drone-BSs, an energy efficient trajectory is determined for point-to-point communications between a fixed-altitude drone-BS and terrestrial users in [17], and for drone-BSs with a fixed coverage area and altitude in [18].…”

Section: A Related Workmentioning

confidence: 99%

“…Since these users would not be served otherwise, they handover to the drone-BS, if they are in the coverage region of drone-BS. Main factors contributing to handover are better RSSI (due to line-of-sight and dynamic positioning with respect to users' locations) and bandwidth availability (due to orthogonality of resources of the drone-BS) [4], [5], [7], [10], [11], [13], [16], [19], [75]- [79]. Assume the network incorporates a SNC scheme, which suggests certain displacements to each user.…”

Section: System Modelmentioning

confidence: 99%

“…However, JSNC yields a complex MINLP, which is computationally costly. Therefore in this section, we discuss a semi-JSNC method, which locates the drone-BS in 3D by considering the approximate effect of the users in D. Then, optimal incentive is offered to users based on (16). In other words, incentive design is not a completely inherent part of semi-JSNC, yet, it is straight forward to design incentives after carefully placing the drone-BSs.…”

Section: Semi-joint Spatial Network Configurationmentioning

confidence: 99%

See 2 more Smart Citations

Spatial Configuration of Agile Wireless Networks With Drone-BSs and User-in-the-loop

Bor-Yaliniz

El-Keyi

Yanıkömeroğlu

2019

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

Agile networking can reduce over-engineering, costs, and energy waste. Towards that end, it is vital to exploit all degrees of freedom of wireless networks efficiently, so that service quality is not sacrificed. In order to reap the benefits of flexible networking, we propose a spatial network configuration scheme (SNC), which can result in efficient networking; both from the perspective of network capacity, and profitability. First, SNC utilizes the drone-base-stations (drone-BSs) to configure access points. Drone-BSs are shifting paradigms of heterogeneous wireless networks by providing radically flexible deployment opportunities. On the other hand, their limited endurance and potential high cost increase the importance of utilizing drone-BSs efficiently. Therefore, secondly, user mobility is exploited via user-in-the-loop (UIL), which aims at influencing users' mobility by offering incentives. The proposed uncoordinated SNC is a computationally efficient method, yet, it may be insufficient to exploit the synergy between drone-BSs and UIL. Hence, we propose joint SNC, which increases the performance gain along with the computational cost. Finally, semi-joint SNC combines benefits of joint SNC, with computational efficiency. Numerical results show that semi-joint SNC is two orders of magnitude times faster than joint SNC, and more than 15% profit can be obtained compared to conventional systems.Index Terms-Unmanned aerial vehicle, user-in-the-loop, agile network, drone-BS. arXiv:1809.05315v1 [cs.NI]

show abstract

Section: A Related Workmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

Section: Semi-joint Spatial Network Configurationmentioning

confidence: 99%

See 1 more Smart Citation

Spatial Configuration of Agile Wireless Networks With Drone-BSs and User-in-the-loop

Bor-Yaliniz

El-Keyi

Yanıkömeroğlu

2019

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

show abstract

“…Recent study [2] on UAV-BSs mainly focuses on finding the optimal placement of the UAV-BSs while serving the user equipments (UEs) in the target area. However, in most papers [3] [4] [5], few take dynamic scenarios into consideration.…”

Section: Introductionmentioning

confidence: 99%

“…The pseudo-codes of the proposed algorithm1 Function Prediction(V (N )):2 Load ESN-based prediction algorithm and update V (N ) ← [(x predicted (1), y predicted (1)), (x predicted (2), y predicted (2)) , . .…”

mentioning

confidence: 99%

A Predictive On-Demand Placement of UAV Base Stations Using Echo State Network

Peng

Chen

Lai

et al. 2019

2019 IEEE/CIC International Conference on Communications in China (ICCC)

View full text Add to dashboard Cite

The unmanned aerial vehicles base stations (UAV-BSs) have great potential in being widely used in many dynamic application scenarios. In those scenarios, the movements of served user equipments (UEs) are inevitable, so the UAV-BSs needs to be re-positioned dynamically for providing seamless services. In this paper, we propose a system framework consisting of UEs clustering, UAV-BS placement, UEs trajectories prediction, and UAV-BS reposition matching scheme, to serve the UEs seamlessly as well as minimize the energy cost of UAV-BSs' reposition trajectories. An Echo State Network (ESN) based algorithm for predicting the future trajectories of UEs and a Kuhn-Munkres-based algorithm for finding the energy-efficient reposition trajectories of UAV-BSs is designed, respectively. We conduct a simulation using a real open dataset for performance validation. The simulation results indicate that the proposed framework achieves high prediction accuracy and provides the energy-efficient matching scheme.

show abstract