OFDM Performance Assessment for Traffic Surveillance in Drone Small Cells

Vahidi, Vahid; Saberinia, E.; Morris, Brendan

doi:10.1109/tits.2018.2868761

Cited by 16 publications

(10 citation statements)

References 24 publications

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“…Unmanned Aerial Vehicles (UAVs) (also referred to as drones or flying robots) are quickly becoming more and more important in numerous real life applications [1], including ground traffic surveillance [2,3], precision agriculture and inspection of agricultural fields [4], aerial goods delivery [5,6,7], infrastructure monitoring and inspection [8,9,10,11], 3D surface reconstruction [12], providing wireless communication [13,14,15,16,17,18,19,20,21], natural disaster areas surveillance [22], rescue missions, and ground monitoring for security purposes [23,24,25,26,27,28,29,30,31,32,33]. A significant class of such UAV problems consists of various drone placement problems.…”

Section: Introductionmentioning

confidence: 99%

Asymptotically Optimal Deployment of Drones for Surveillance and Monitoring

Savkin

Huang

2019

Sensors

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This paper studies the problem of placing a set of drones for surveillance of a ground region. The main goal is to determine the minimum number of drones necessary to be deployed at a given altitude to monitor the region. An easily implementable algorithm to estimate the minimum number of drones and determine their locations is developed. Moreover, it is proved that this algorithm is asymptotically optimal in the sense that the ratio of the number of drones required by this algorithm and the minimum number of drones converges to one as the area of the ground region tends to infinity. The proof is based on Kershner’s theorem from combinatorial geometry. Illustrative examples and comparisons with other existing methods show the efficiency of the developed algorithm.

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Section: Introductionmentioning

confidence: 99%

Asymptotically Optimal Deployment of Drones for Surveillance and Monitoring

Savkin

Huang

2019

Sensors

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“…Such scenarios can occur in future 5G systems where the expected centre frequency is between 27 and 71 GHz [1]. One of the conditions that high Doppler shift occurs is the utilisation of the drone small cells (DSCs) for both communication systems and traffic surveillance simultaneously as we discussed in [2]. This is the scenario that we considered in the current paper too; however, by considering a very higher Doppler shift of the 5G communication systems and MIMO condition in contrast to the single-input single-output condition of [2].…”

Section: Introductionmentioning

confidence: 99%

“…One of the conditions that high Doppler shift occurs is the utilisation of the drone small cells (DSCs) for both communication systems and traffic surveillance simultaneously as we discussed in [2]. This is the scenario that we considered in the current paper too; however, by considering a very higher Doppler shift of the 5G communication systems and MIMO condition in contrast to the single-input single-output condition of [2]. Owing to the timevarying nature of channels in the presence of the Doppler shift, channel estimation (CE), which is essential for the data demodulation of any communication systems that uses OFDM signals, is challenging and usually requires a lot of pilot data to be transmitted.…”

Section: Introductionmentioning

confidence: 99%

MIMO–OFDM communication systems for traffic data transmission in 5G drone small cells

Vahidi

Saberinia

2019

IET Communications

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“…Micro unmanned aircraft systems (micro UAS) [1] equipped with a camera [2][3][4] have been used in applications such as traffic surveillance and hobby filming. In addition, data collected from the micro UAS is used to perform real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, precision agriculture, and civil infrastructure inspection for various civil applications [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

End-To-End Controls Using K-Means Algorithm for 360-Degree Video Control Method on Omnidirectional Camera-Equipped Autonomous Micro Unmanned Aircraft Systems

Kwak¹,

Sung²

2019

Applied Sciences

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Micro unmanned aircraft systems (micro UAS)-related technical research is important because micro UAS has the advantage of being able to perform missions remotely. When an omnidirectional camera is mounted, it captures all surrounding areas of the micro UAS. Normal field of view (NFoV) refers to a view presented as an image to a user in a 360-degree video. The 360-degree video is controlled using an end-to-end controls method to automatically provide the user with NFoVs without the user controlling the 360-degree video. When using the end-to-end controls method that controls 360-degree video, if there are various signals that control the 360-degree video, the training of the deep learning model requires a considerable amount of training data. Therefore, there is a need for a method of autonomously determining the signals to reduce the number of signals for controlling the 360-degree video. This paper proposes a method to autonomously determine the output to be used for end-to-end control-based deep learning model to control 360-degree video for micro UAS controllers. The output of the deep learning model to control 360-degree video is automatically determined using the K-means algorithm. Using a trained deep learning model, the user is presented with NFoVs in a 360-degree video. The proposed method was experimentally verified by providing NFoVs wherein the signals that control the 360-degree video were set by the proposed method and by user definition. The results of training the convolution neural network (CNN) model using the signals to provide NFoVs were compared, and the proposed method provided NFoVs similar to NFoVs of existing user with 24.4% more similarity compared to a user-defined approach.

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OFDM Performance Assessment for Traffic Surveillance in Drone Small Cells

Cited by 16 publications

References 24 publications

Asymptotically Optimal Deployment of Drones for Surveillance and Monitoring

Asymptotically Optimal Deployment of Drones for Surveillance and Monitoring

MIMO–OFDM communication systems for traffic data transmission in 5G drone small cells

End-To-End Controls Using K-Means Algorithm for 360-Degree Video Control Method on Omnidirectional Camera-Equipped Autonomous Micro Unmanned Aircraft Systems

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