Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity

By Mohammad Mahdi Azari, Fernando Rosas, Kwang-Cheng Chen, Sofie Pollin. IEEE Transactions on Communications, 2017

391 citations recorded by the source corpus.

The use of unmanned aerial vehicles (UAVs) serving as aerial base stations is expected to become predominant in the next decade. However, in order, for this technology, to unfold its full potential, it is necessary to develop a fundamental understanding of the distinctive features of air-to-ground (A2G) links. As a contribution in this direction, this paper proposes a generic framework for the analysis and optimization of the A2G systems. In contrast to the existing literature, this framework incorporates both height-dependent path loss exponent and small-scale fading, and unifies a widely used ground-to-ground channel model with that of A2G for the analysis of large-scale wireless networks. We derive analytical expressions for the optimal UAV height that minimizes the outage probability of an arbitrary A2G link. Moreover, our framework allows us to derive a height-dependent closed-form expression for the outage probability of an A2G cooperative communication network. Our results suggest that the optimal location of the UAVs with respect to the ground nodes does not change by the inclusion of ground relays. This enables interesting insights about the deployment of future A2G networks, as the system reliability could be adjusted dynamically by adding relaying nodes without requiring changes in the position of the corresponding UAVs. Finally, to optimize the network for multiple destinations, we derive an optimum altitude of the UAV for maximum coverage region by guaranteeing a minimum outage performance over the region.

View Paper: https://www.semanticscholar.org/paper/55362a2dd71753d2ddf039e14dd137ac44e419f5

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Citations in the corpus

3D Trajectory Optimization in Rician Fading for UAV-Enabled Data Harvesting (2019, methodology): “This issue can be addressed by approximating the inverse Marcum-Q function as derived in [36].”
Energy-Efficient UAV Control for Effective and Fair Communication Coverage: A Deep Reinforcement Learning Approach (2018, methodology): “[27] proposed a method to figure out an altitude for maximizing coverage region, which can guarantee a minimum outage performance.”
Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey (2021, background): “(1d)) are flexible platforms that can adjust their 3D locations and employ 5G communication technologies to serve the target users [54], [55].”
UAV assistance paradigm: State-of-the-art in applications and challenges (2020, background): “Consequently, the accurate channel design while considering the aforementioned factors is of great importance, and more importantly when UAVs are deployed to enhance the coverage of terrestrial networks [46], to assist cellular networks [47], and to participate in IoT communications [48].”
Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond (2019, methodology): “1) Static UAV Platform: xx Deterministic modelling of UAV location: In this case, the number as well as locations of UAVs are deterministic and known a priori [41,48,91]–[93], whereas their associated ground nodes could be modelled either deterministically or stochastically.”
Distributed Drone Base Station Positioning for Emergency Cellular Networks Using Reinforcement Learning (2018, background): “…of drones in emergency situations [1, 8], other works covering the deployment of drones with backhaul limitations [11, 13, 15], and others considering the positioning of aerial platforms [3, 5–7, 9–11, 14], only [3] proposes an intelligent solution in order to determine the best position of DSCs.”
UAV-Assisted Relaying and Edge Computing: Scheduling and Trajectory Optimization (2018, background): “Recently, [18] proposed a generic framework for the analysis and optimization of the air-to-ground systems, and an optimum altitude for UAV in maximizing the coverage region with a guaranteed minimum outage performance was derived.”