Coverage Probability Analysis of UAV Cellular Networks in Urban Environments

Zhou, Lai; Yang, Zhi; Zhou, Shidong; Zhang, Wei

doi:10.1109/iccw.2018.8403633

Cited by 61 publications

(41 citation statements)

References 18 publications

(24 reference statements)

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“…Nakagami-m fading is a general fading model suitable under various conditions [12], and hence we assume all transmission links experience independent Nakagami-m fading 1 . Denoted by h s , the small-scale fading gains (i.e., magnitude-squares of fading coefficients) follow Gamma distributions 1 Note that Nakagami fading specializes to Rayleigh fading when m " 1.…”

Section: E Small-scale Fadingmentioning

confidence: 99%

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Coverage Analysis for Energy-Harvesting UAV-Assisted mmWave Cellular Networks

Wang

Gursoy

2019

IEEE J. Select. Areas Commun.

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In this paper, we jointly consider the downlink simultaneous wireless information and power transfer (SWIPT) and uplink information transmission in unmanned aerial vehicle (UAV)-assisted millimeter wave (mmWave) cellular networks, in which the user equipment (UE) locations are modeled using Poisson cluster processes (e.g., Thomas cluster processes or Matérn cluster processes). Distinguishing features of mmWave communications, such as different path loss models for line-of-sight (LOS) and non-LOS (NLOS) links and directional transmissions are taken into account. In the downlink phase, the association probability, and energy coverages of different tier UAVs and ground base stations (GBSs) are investigated. Moreover, we define a successful transmission probability to jointly present the energy and signal-to-interference-plus-noise ratio (SINR) coverages and provide general expressions. In the uplink phase, we consider the scenario that each UAV receives information from its own cluster member UEs. We determine the Laplace transform of the interference components and characterize the uplink SINR coverage. In addition, we formulate the average uplink throughput, with the goal to identify the optimal time division multiplexing between the donwlink and uplink phases. Through numerical results we investigate the impact of key system parameters on the performance. We show that the network performance is improved when the cluster size becomes smaller. In addition, we analyze the optimal height of UAVs, optimal power splitting value and optimal time division multiplexing that maximizes the network performance.The authors are with the [7]. In conventional wireless power transfer (WPT) systems, energy transmitters are deployed at fixed locations, and therefore due to the RF signal propagation over potentially long distances, such systems can suffer from low end-to-end energy transfer efficiency [4]. In general, RF WPT is considered in the context of two key application scenarios, namely simultaneous wireless information and power transfer (SWIPT) and wireless powered communication networks (WPCNs). SWIPT explores the dual use of microwave signals to achieve WPT and wireless information transfer (WIT) both in downlink direction [8], while downlink WPT and uplink WIT are performed in WPCNs [9]. Unmanned aerial vehicles (UAVs) have emerged as key enablers of seamless wireless connectivity in diverse scenarios such as large-scale temporary events, military operations and disaster scenarios, and of capacity enhancement in the occasional demand of super dense base stations (BSs), and UAVs are anticipated to be part of future generation wireless networks [10][11][12][13]. More specifically, in order to take advantage of flexible deployment opportunities [12], and high possibility of line-of-sight (LoS) connections with a ground user equipment (UE) [14], BSs can be mounted on UAVs to support wireless connectivity and improve the performance of cellular networks [13]. The flexibility of UAV BSs allows them to adapt their locations ...

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Section: E Small-scale Fadingmentioning

confidence: 99%

“…In [12], the downlink coverage probability was explored, as well as the influence of UAV height and density. In [13], different path loss models for high-altitude, low-altitude and ultra-low-altitude models were discussed.…”

Section: Introductionmentioning

confidence: 99%

Coverage Analysis for Energy-Harvesting UAV-Assisted mmWave Cellular Networks

Wang

Gursoy

2019

IEEE J. Select. Areas Commun.

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“…In [20], Zhang et al optimized the DBS density in DBS network to maximize the network throughput while satisfying the efficiency requirements of the cellular network. Zhou et al studied the downlink coverage features of DBS using Nakagami-m fading models, and calculated the optimal height and density of multiple DBSs to achieve maximal coverage probability [21]. Although various works have investigated the static DBS deployments in different scenarios with different methods, the D2B link quality constraint is simplified or ignored by most works.…”

Section: A Static Dbs Deploymentmentioning

confidence: 99%

Multi-Drone 3-D Trajectory Planning and Scheduling in Drone-Assisted Radio Access Networks

Shi

Cheng

et al. 2019

IEEE Trans. Veh. Technol.

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Drone base station (DBS) is a promising technique to extend wireless connections for uncovered users of terrestrial radio access networks (RAN). To improve user fairness and network performance, in this paper, we design 3D trajectories of multiple DBSs in the drone assisted radio access networks (DA-RAN) where DBSs fly over associated areas of interests (AoIs) and relay communications between the base station (BS) and users in AoIs. We formulate the multi-DBS 3D trajectory planning and scheduling as a mixed integer non-linear programming (MINLP) problem with the objective of minimizing the average DBS-to-user (D2U) pathloss. The 3D trajectory variations in both horizontal and vertical directions, as well as the stateof-the-art DBS-related channel models are considered in the formulation. To address the non-convexity and NP-hardness of the MINLP problem, we first decouple it into multiple integer linear programming (ILP) and quasi-convex sub-problems in which AoI association, D2U communication scheduling, horizontal trajectories and flying heights of DBSs are respectively optimized. Then, we design a multi-DBS 3D trajectory planning and scheduling algorithm to solve the sub-problems iteratively based on the block coordinate descent (BCD) method. A k-meansbased initial trajectory generation and a search-based start slot scheduling are considered in the proposed algorithm to improve trajectory design performance and ensure inter-DBS distance constraint, respectively. Extensive simulations are conducted to investigate the impacts of DBS quantity, horizontal speed and initial trajectory on the trajectory planning results. Compared with the static DBS deployment, the proposed trajectory planning can achieve 10-15 dB reduction on average D2U pathloss, and reduce the D2U pathloss standard deviation by 68%, which indicate the improvements of network performance and user fairness.

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“…[9], discuss the prospect of delivering cellular coverage using UAVs. Motivated by this, [10] and [11] use stochastic geometry to analyze coverage probabilities in an A2G scenario. In [10], a model is analyzed where some users receive downlink service from a single UAV, while others communicate over device-to-device links.…”

Section: Introductionmentioning

confidence: 99%

“…The coverage analysis is used to design mission plans for a single mobile airborne platform. Similarly, [11] models downlink intercell interference in a network where UAVs serve as cellular base stations. While attention has been paid to the air-to-ground aspects of UAV delivered cellular service, our work is applicable to the inherently necessary wireless backhaul [11].…”

Section: Introductionmentioning

confidence: 99%

MmWave MU-MIMO for Aerial Networks

Cuvelier

Heath

2018

2018 15th International Symposium on Wireless Communication Systems (ISWCS)

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Millimeter wave offers high bandwidth for air-toair (A2A) communication. In this paper, we evaluate the rate performance of a multiuser MIMO (MU-MIMO) configuration where several aircraft communicate with a central hub. We consider a hybrid subarray architecture, single path channels, and realistic atmospheric attenuation effects. We propose a mathematical framework for the analysis of millimeter wave (mmWave) MU-MIMO networks. Via Monte Carlo simulation, we demonstrate that mmWave is a promising technology for delivering gigabit connectivity in next-generation aerial networks.

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Coverage Probability Analysis of UAV Cellular Networks in Urban Environments

Cited by 61 publications

References 18 publications

Coverage Analysis for Energy-Harvesting UAV-Assisted mmWave Cellular Networks

Coverage Analysis for Energy-Harvesting UAV-Assisted mmWave Cellular Networks

Multi-Drone 3-D Trajectory Planning and Scheduling in Drone-Assisted Radio Access Networks

MmWave MU-MIMO for Aerial Networks

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