Interference modeling and analysis in 3-dimensional directional UAV networks based on stochastic geometry

Chu, Eunmi; Kim, Jong Min; Jung, Bang Chul

doi:10.1016/j.icte.2019.09.006

Cited by 7 publications

(9 citation statements)

References 9 publications

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“…where 2 F 1 is a Gaussian hypergeometric function. Substituting (14) and (15) into (12) and taking the expectation of the beam gains, (16) is given by including the probability mass function of beam patterns p G c and p G s . Finally, the success probability at the FES where the satellite and cellular networks coexist is derived as (17).…”

Section: Performance Analysis Of the Success Probabilit Ymentioning

confidence: 99%

“…The interference from each (terrestrial) cellular BS to the FSS in general depends on the distance between the BS and FSS as well as the beam orientation (boresight direction) of both stations with directional antennas. A stochastic geometry (SG) framework has been adopted to model geometric properties in analyzing the effect of interference in wireless networks [12–15]. In the SG framework, the Poisson point process (PPP) is typically utilized to model the locations of the transmitter.…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis of satellite and terrestrial spectrum‐shared networks with directional antenna

et al. 2020

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Recently, to make the best use of limited and precious spectrum resources, spectrum sharing between satellite and cellular networks has received much interest. In this study, we mathematically analyze the success probability of a fixed (satellite) earth station (FES) based on a stochastic geometry framework. Both the FES and base stations (BSs) are assumed to be equipped with a directional antenna, and the location and the number of BSs are modeled based on the Poisson point process. Furthermore, an exclusion zone is considered, in which the BSs are prohibited from locating in a circular zone with a certain radius around the FES to protect it from severe interference from the cellular BSs. We validate the analytical results on the success probability of the cognitive satellite‐terrestrial network with directional antennas by comparing it using extensive computer simulations and show the effect of the exclusion zone on the success probability at the FES. It is shown that the exclusion zone‐based interference mitigation technique significantly improves the success probability as the exclusion zone increases.

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Section: Performance Analysis Of the Success Probabilit Ymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance analysis of satellite and terrestrial spectrum‐shared networks with directional antenna

et al. 2020

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“…Nonetheless, these studies failed to systematically model the interference from UAVs in nearby cells. A more comprehensive modeling on the sum interference assuming UAVs uniformly distributed in a spherical area is conducted in [22]. In this work, the authors propose a theoretical model for instantaneous interference signals without characterizing the ergodicity, and no analytical solution is provided.…”

Section: Related Workmentioning

confidence: 99%

“…Based on the above analysis, the total intercell interference is difficult to model. To the best of the author's knowledge, most research works in this area conduct only empirical measurements on the signals from a single or multiple UAVs [15]- [21], while theoretical studies are lacking sufficient analysis with closed-form solutions [22]. A theoretical model with analytically solvable methods to precisely estimate the system-level interference remains an open issue.…”

Section: Introductionmentioning

confidence: 99%

Enabling Capacity Estimation With Ergodic Interference Power in Cellular-Based Multiple UAV Systems

Zhao

Zhou

et al. 2020

IEEE Access

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The integration of unmanned aerial vehicles (UAVs) into cellular networks as aerial user equipment (aUE) has attracted increasing interest from both academia and industry in recent years. To ensure stable uplink (UL) service performance, the potential UL capacity must be determined for a variety of communication techniques to guide the system design or to obtain an optimized solution. Unlike traditional interferences from ground UEs, which contribute to only local and nearby cells, UAV systems involve strong LoS paths to even far side base stations (BSs) due to higher altitude. As a result, intercell interference becomes the dominating factor in the estimation of the potential capacity. In this paper, we propose a theoretical model on the ergodic sum power of the interference arising from all UAVs maintaining LoS paths with the target BS. The solution to this model is difficult to obtain, and is essentially rooted in the dynamic trajectories of interfering UAVs within a vast geological range. To address this problem, we divide the model into noncorrelated parts, where each part contains the interfering UAVs that are independently and identically distributed (i.i.d.). Then we utilize the ergodic method to solve the interference power of each part. Based on this, the original nonanalytical expression for the ergodic sum interference power is transformed into a solvable integration problem, and the closed-form solution is successfully derived. Simulation based experiments are conducted on both rural macro (RMa) cell and urban macro (UMa) cell scenarios. The results validate the feasibility and accuracy of the proposed model, and confirm the severe influence of the intercell interference on the UL capacity. INDEX TERMS Unmanned aerial vehicles, cellular network, base station, uplink capacity , ergodic sum interference power.

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“…Moreover, one UAV could achieve multiple complex functions, as in [13], the UAV jointly optimises and performs sensing tasks and data transmission to the BS. However, the strong LOS links also cause severe and extensive interference, leading to widespread performance degradation and design complication [14,15]. Fortunately, a variety of researches have been carried out for interference coordination.…”

Section: Introductionmentioning

confidence: 99%

Interference coordination and throughput maximisation in an unmanned aerial vehicle‐assisted cellular: User association and three‐dimensional trajectory optimisation

et al. 2021

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Unmanned aerial vehicles in wireless communications have caught great attention in unmanned aerial vehicle assisted communications and cellular-connected unmanned aerial vehicles. However, the unmanned aerial vehicle's advantage of strong line-of-sight channels also brings about severe and extensive interference between unmanned aerial vehicle and the terrestrial communication networks and between multiple unmanned aerial vehicles. This paper jointly optimises the unmanned aerial vehicle's three-dimensional trajectory and ground users' association schemes with the unmanned aerial vehicle and ground base station to reduce interference. In consideration of fairness, the authors formulate the optimisation problem as maximising the minimum average throughput among all ground users, a mixed-integer non-convex problem that is challenging to tackle. To ease the difficulties, the authors have the optimisation problem relaxed and propose a suboptimal solution in the framework of the block successive upper-bound minimisation algorithm. Furthermore, an improved block successive upper-bound minimisation based penalty algorithm is obtained to avoid the local maximum point problem. Numerical simulations have validated our schemes.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Interference modeling and analysis in 3-dimensional directional UAV networks based on stochastic geometry

Cited by 7 publications

References 9 publications

Performance analysis of satellite and terrestrial spectrum‐shared networks with directional antenna

Performance analysis of satellite and terrestrial spectrum‐shared networks with directional antenna

Enabling Capacity Estimation With Ergodic Interference Power in Cellular-Based Multiple UAV Systems

Interference coordination and throughput maximisation in an unmanned aerial vehicle‐assisted cellular: User association and three‐dimensional trajectory optimisation

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