UAV and Relay Cooperation Based on RSS for Extending Smart Environments Coverage Area in B5G

Saif, Abdu; Dimyati, Kaharudin; Noordin, Kamarul Ariffin; Alsamhi, Saeed Hamood; Mosali, Najmaddin Abo; Gupta, Sachin Kumar

doi:10.21203/rs.3.rs-2002265/v1

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…However, current devices typically have poor processing power, and the centralized architecture of traditional cloud computing networks may result in poor transmission latency [4]. With the development of the Internet of Things (IoT) [5][6][7][8][9][10], information data is extracted in a timely manner using big data technologies, and edge computing servers are deployed at the edge of the network through mobile edge computing (MEC) [11][12][13]. This can effectively solve the problems of sensitive transmission delay and insufficient computing power of mobile terminals [14], and facilitate the provision of sufficient information for smart city construction [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Learning Dual-Domain Calibration and Distance-Driven Correlation Filter: A Probabilistic Perspective for UAV Tracking

Yan,

Cao,

et al. 2023

CMC

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Unmanned Aerial Vehicle (UAV) tracking has been possible because of the growth of intelligent information technology in smart cities, making it simple to gather data at any time by dynamically monitoring events, people, the environment, and other aspects in the city. The traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking operations. But these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization terms. In light of the aforementioned issues, this work suggests a dual-domain Jensen-Shannon divergence correlation filter (DJSCF) model address the probability-based distance measuring issue in the event of filter degradation. The two-domain weighting matrix and JS divergence constraint are combined to lessen the impact of sample imbalance and distortion. Two new tracking models that are based on the perspectives of the actual probability filter distribution and observation probability filter distribution are proposed to translate the statistical distance in the online tracking model into response fitting. The model is roughly transformed into a linear equality constraint issue in the iterative solution, which is then solved by the alternate direction multiplier method (ADMM). The usefulness and superiority of the suggested strategy have been shown by a vast number of experimental findings.

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Section: Introductionmentioning

confidence: 99%

Learning Dual-Domain Calibration and Distance-Driven Correlation Filter: A Probabilistic Perspective for UAV Tracking

Yan,

Cao,

et al. 2023

CMC

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“…UAVs have comprehensive and specific applications in modern society. In daily life, in intelligent environments, UAVs can use intelligence edge platform to collect data to undertake the function of relay station cited in [1] , and are often used as mobile base station to monitor specific areas and provide services as in paper [2] . In disasters, drones shoulder the important functions of evacuating crowds, guiding escape, and helping rescue in paper [3] .…”

Section: Introductionmentioning

confidence: 99%

UAV assisted communication for ground users using machine learning and optimization

Prakash¹,

Zang²,

Scott³

et al. 2022

J Smart Environ Green Comput

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Aim: Among a large number of products that support communication, there is one called space air ground integrated networks (SAGIN's), which is the most commonly used to support users in rural and emergency situations. Typicaly in emergency situations SAGIN's use unmanned aerial vehicles (UAVs) in their air layer to temporarily support the ground users. Although the cost of UAVs is lower than that of traditional base stations, and their actions are more flexible, but their battery life problems lead to frequent charging of drones, resulting in many resource losses and unable to provide communication support. In order to mitigate the issues, novel optimization algorithms need to be developed to support the ground users. Methods: In this work, we develop a grid-based deep learning method using the LSTM model to estimate the number of ground users as vehicles in each area, and developed an optimization algorithm to minimize the number of UAVs needed to the user's and meanwhile to satisfy quality of service (QoS) requirements. For optimization, we mainly use the Linear Optimization Tools and an objective function has been developed using density predicted and SINR data to achieve acceptable QoS. Results: The simulation results shows that this approach has improved the quality of the communication by 50%. Conclusion: Using unique grid technique and the LSTM machine learning model, the user densities on each partitioned grid is determined. Finally, a linear optimization algorithm is developed based on the user density to determine the lowest number of UAVs to support the users in each grid while maintaining the QoS.

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“…Connectivity analysis is one of the critical success factors that enables highly reliable transmissions over long distances by Line of Sight (LoS) while guaranteeing maximum cell coverage and improving energy efficiency 7 . On the other hand, UAV energy efficiency can be achieved by optimizing the trajectory and a blind beam tracking approach to minimize the total required to transmit power according to the rate requirements of the SARs 12,13,14 …”

Section: Introductionmentioning

confidence: 99%

Multi‐UAV and SAR collaboration model for disaster management in B5G networks

Saif

Dimyati

Noordin

et al. 2021

Internet Technology Letters

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Ensuring communication infrastructures always alive during disaster mitigation and recovery is of paramount importance. In this case, Unmanned Aerial vehicle (UAV) will be the ideal substitute for the malfunctioning ground base station due to disaster. Henceforth, we suggest a multi‐UAV and Search and Rescue (SAR) collaboration model in this letter. To improve its connectivity, we propose an optimal SAR elevation angle for the multi‐UAV and SARs to administer larger disaster areas effectively and efficiently. We evaluate the performance of the proposed model in terms of path loss, throughput, and coverage probability. The results demonstrate that the proposed model achieves a significant enhancement in serving the SARs.

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UAV and Relay Cooperation Based on RSS for Extending Smart Environments Coverage Area in B5G

Cited by 5 publications

References 23 publications

Learning Dual-Domain Calibration and Distance-Driven Correlation Filter: A Probabilistic Perspective for UAV Tracking

Learning Dual-Domain Calibration and Distance-Driven Correlation Filter: A Probabilistic Perspective for UAV Tracking

UAV assisted communication for ground users using machine learning and optimization

Multi‐UAV and SAR collaboration model for disaster management in B5G networks

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