Communication recovery with emergency aerial networks

Mekikis, Prodromos-Vasileios; Antonopoulos, Angelos; Kartsakli, Elli; Alonso, Luis; Verikoukis, Christos

doi:10.1109/tce.2017.014904

Cited by 35 publications

(15 citation statements)

References 16 publications

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“…However, note that there are only LOS BSs for 2 nd tier. Finally, by inserting (14), (15), (16), (21), (22), (23) into (19), coverage probability expression in (20) can be obtained.…”

Section: Proof Of Theoremmentioning

confidence: 99%

Downlink Analysis in Unmanned Aerial Vehicle (UAV) Assisted Cellular Networks With Clustered Users

Turgut

Gursoy

2018

IEEE Access

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The use of unmanned aerial vehicles (UAVs) operating as aerial base stations (BSs) has emerged as a promising solution especially in scenarios requiring rapid deployments (e.g., in the cases of crowded hotspots, sporting events, emergencies, natural disasters) in order to assist the ground BSs. In this paper, an analytical framework is provided to analyze the signalto-interference-plus-noise ratio (SINR) coverage probability of unmanned aerial vehicle (UAV) assisted cellular networks with clustered user equipments (UEs). Locations of UAVs and ground BSs are modeled as Poison point processes (PPPs), and UEs are assumed to be distributed according to a Poisson cluster process (PCP) around the projections of UAVs on the ground. Initially, the complementary cumulative distribution function (CCDF) and probability density function (PDF) of path losses for both UAV and ground BS tiers are derived. Subsequently, association probabilities with each tier are obtained. SINR coverage probability is derived for the entire network using tools from stochastic geometry. Finally, area spectral efficiency (ASE) of the entire network is determined, and SINR coverage probability expression for a more general model is presented by considering that UAVs are located at different heights. Via numerical results, we have shown that UAV height and path-loss exponents play important roles on the coverage performance. Moreover, coverage probability can be improved with smaller number of UAVs, while better area spectral efficiency is achieved by employing more UAVs and having UEs more compactly clustered around the UAVs.Index Terms-Unmanned aerial vehicle (UAV), cellular networks, SINR coverage probability, Poisson point process, Poisson cluster process, Thomas cluster process, stochastic geometry.

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“…However, note that there are only LOS BSs for 2 nd tier. Finally, by inserting (14), (15), (16), (21), (22), (23) into (19), coverage probability expression in (20) can be obtained.…”

Section: Proof Of Theoremmentioning

confidence: 99%

Downlink Analysis in Unmanned Aerial Vehicle (UAV) Assisted Cellular Networks With Clustered Users

Turgut

Gursoy

2018

IEEE Access

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“…To account for these issues, recent studies proposed the deployment of access points (APs) mounted on unmanned aerial vehicles (UAVs) [3], [6]. This kind of APs is expected to be a crucial part of the future communication systems as they are flexible, fast, autonomous, and able to provide a drastic solution to the aforementioned issues.…”

Section: Introductionmentioning

confidence: 99%

Breaking the Boundaries of Aerial Networks with Charging Stations

Mekikis

Antonopoulos

2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Considering that cities are typically divided in residential and business districts, massive population migrations between different areas introduce considerable discrepancies in the traffic distribution. However, although novel technologies are constantly introduced to fulfill the 5G requirements, the current cellular networks raise some limitations due to their static deployment. Aerial networks with unmanned aerial vehicles (UAVs) that carry access points can flexibly overcome this issue by controlling this traffic effectively in an ad hoc manner, but their limited power storage is their major drawback. In this paper, we propose the use of solar-powered charging stations to satisfy the energy needs of UAVs and formulate a theoretic matching problem to ensure the best performance in terms of energy, communication, and safety. Then, we evaluate the network performance by comparing the coverage and utilization between the two scenarios: i) the static infrastructure, and ii) the aerial network, and we present useful insights regarding the benefits of aerial networks.

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“…In Reference [23], a multi-UAV swarm senses and allocates subchannels for UAV-to-X communication in a collaborative manner in order to maximize the sum-rate of uplinks while optimizing the speed of UAVs. In Reference [24], a multi-UAV swarm, which consists of flexible aerial nodes, is deployed to form an emergency network that can recover communication rapidly in a catastrophic area. In Reference [25], UAVs embedded with solar panels, together with solar-powered charging stations, are deployed to overcome energy constraint in order to fulfill the energy, communication, and safety requirements of 5G.…”

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confidence: 99%

Routing Schemes in FANETs: A Survey

Khan

Yau

Noor

et al. 2019

Sensors

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Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues.

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Communication recovery with emergency aerial networks

Cited by 35 publications

References 16 publications

Downlink Analysis in Unmanned Aerial Vehicle (UAV) Assisted Cellular Networks With Clustered Users

Downlink Analysis in Unmanned Aerial Vehicle (UAV) Assisted Cellular Networks With Clustered Users

Breaking the Boundaries of Aerial Networks with Charging Stations

Routing Schemes in FANETs: A Survey

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