Optimal LAP Altitude for Maximum Coverage

By Akram Al-Hourani, Kandeepan Sithamparanathan, Simon Lardner. IEEE Wireless Communications Letters, 2014

2,785 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/65753ff3e5ab97d0d6fd85c826cc0251c1eefae9

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In Aerospace Engineering

Citations in the corpus

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles (2018, methodology): “where PLLOS and PLNLOS are the PL in LOS and NLOS conditions, respectively, P(LOS) denotes the probability of having a LOS link between the UAV and the ground node, given by [48], [140]:”
Energy Minimization for Wireless Communication With Rotary-Wing UAV (2018, methodology): “In particular, it was shown that as the UAV altitude increases, the LoS probability between the UAV and GNs also increases [13].”
A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning (2021, background): “For ground-to-air channels, the value of P oneLoS depends on the elevation angle according to the following expression [178], [179]: where θ u is the elevation angle of the user, and φ e and ψ e are two constants, which depends on the communication environment, such as suburban, urban, dense urban,…”
Multi-Tier Drone Architecture for 5G/B5G Cellular Networks: Challenges, Trends, and Prospects (2017, methodology): “…used for the analysis of sophisticated altitude optimization and deployment of static/mobile drones in several research studies with the objective to either maximizing the coverage for users or to minimizing network delays or to minimize the power consumption of drones [5], [6], [8], [10], [14].”
Physical-Layer Security of 5G Wireless Networks for IoT: Challenges and Opportunities (2019, background): “Compared favorably with terrestrial systems, UAVs can overcome the propagation and blockage constraints due to terrain characteristics, especially for mmWave, and augment the coverage area by optimizing the UAVs’ location (e.g., altitude) in the 3D model [91].”
Modeling air-to-ground path loss for low altitude platforms in urban environments (2014, background): “Accordingly, Radio Frequency (RF) planning should be carried out for the target area that can produce an estimation for the (i) the required number of Aerial Base Stations, (ii) the optimum altitude of the platforms [10], and (iii) the expected service level.”
Wireless communications with unmanned aerial vehicles: opportunities and challenges (2016, background): “Such a tradeoff has been characterized in [12], [13], based on which the optimal UAV altitude has been obtained.”
Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey (2018, background): “[5] determine an optimal altitude of a drone, positioned at given x, y-coordinates, to maximize radio coverage.”
Designing and implementing future aerial communication networks (2016, methodology): “An A2G channel model was developed for low-altitude platforms for different environment conditions using ray tracing simulations [9].”
Internet of vehicles in big data era (2018, methodology): “Based on the path-loss model in [67], Mozaffari et al.”
Energy Tradeoff in Ground-to-UAV Communication via Trajectory Design (2017, background): “It is observed that for both cases, as the UAV’s energy consumption E2 increases, the GT’s energy consumption E1 decreases correspondingly, which demonstrates the fundamental trade-off for the GT-UAV energy consumptions, and such a trade-off relationship is more substantial for smaller Pc.”
Drone Small Cells in the Clouds: Design, Deployment and Performance Analysis (2014, background): “As discussed in [4] and [11], the ground receiver receives three groups of signals including LOS, strong reflected signals (NLOS) and multiple reflected components which cause multipath fading.”
Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity (2017, methodology): “Therefore, α(θ) can be characterized using the notion of probability of line of sight (LoS) PLoS(θ) between the UAV and the ground node [15].”
A Survey of Channel Modeling for UAV Communications (2018, methodology): “Hence the propagation conditions [8], [9] can provide coverage analysis and indicate the optimal UAV position [10]–[12].”
Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs (2015, methodology): “As discussed in [5] and [9], the ground receiver can receive three groups of signals including LoS, strong reflected NLoS signals, and multiple reflected components which cause multipath fading.”
Trajectory Design for Completion Time Minimization in UAV-Enabled Multicasting (2018, background): “In the former case, one typical application is UAV-enabled ubiquitous coverage, where UAVs are deployed to assist the existing ground BSs, if any, to ensure seamless wireless coverage for the GTs within a service area [6], [7].”
Efficient 3-D placement of an aerial base station in next generation cellular networks (2016, methodology): “Both issues are addressed in [6], which provides fundamental results on the optimal altitude of a drone-cell, and the channel model to be utilized in urban environments.”
Downlink Coverage Analysis for a Finite 3-D Wireless Network of Unmanned Aerial Vehicles (2017, methodology): “An approach to optimize the altitude of UAVs to maximize coverage on the ground was proposed in [11].”
3-D Placement of an Unmanned Aerial Vehicle Base Station for Maximum Coverage of Users With Different QoS Requirements (2017, background): “The work in [7] evaluated the optimal UAV-BS altitude that maximizes the coverage region.”