Coverage Analysis of UAVs in Millimeter Wave Networks: A Stochastic Geometry Approach

Boschiero, Matilde; Giordani, Marco; Polese, Michele; Zorzi, Michele

doi:10.1109/iwcmc48107.2020.9148550

Cited by 25 publications

(18 citation statements)

References 36 publications

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“…It ensures that the mmWave supports a high data rate when utilized at A-BSs. In addition to the performance in terms of high data rate, the mmWave assisted aerial networks are analyzed for coverage performance [23]. Also, the coverage and spectral efficiency analysis for the mmWave-assisted aerial network are presented in [24].…”

Section: A Related Workmentioning

confidence: 99%

“…A stochastic geometry has emerged as a tractable approach to model and analyze the performance of wireless systems via spatial processes, such as the Poisson Point Process (PPP) [31], [32]. Along with ensuring the tractability of mathematical analysis, the PPP assumption assures accuracy in approximating the actual cellular network topology.…”

Section: A Related Workmentioning

confidence: 99%

“…Along with ensuring the tractability of mathematical analysis, the PPP assumption assures accuracy in approximating the actual cellular network topology. Most prior work on terrestrial and aerial networks also model the location of T-BSs and A-BSs, respectively, based on PPP [32]- [39]. A similar stochastic geometry analysis via PPP may also be conducted to model the location of T-BSs and A-BSs in aerial-terrestrial networks.…”

Section: A Related Workmentioning

confidence: 99%

“…Antenna Model: We assume that the A-BSs use directive beamforming to minimize co-channel interference and counterbalance the high path loss [23]. In this work, the antenna array for A-BSs are modeled as a uniform planar array with N A elements to achieve directive beamforming.…”

Section: ) Air-to-ground Channelmentioning

confidence: 99%

“…In this work, the antenna array for A-BSs are modeled as a uniform planar array with N A elements to achieve directive beamforming. It is worth mentioning that for the tractability of the analysis, these antenna patterns can be well approximated by a sectored antenna model [23], [47]. Accordingly, the effective antenna gain of A-BS antenna (denoted by G A ) is modeled as follows:…”

Section: ) Air-to-ground Channelmentioning

confidence: 99%

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Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

et al. 2021

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The exploitation of aerial base stations (A-BSs) in conjunction with terrestrial base stations (T-BSs) is envisioned as a promising solution to provide connectivity to devices and user-equipment (UE) in crowded situations (viz. in the sports event) and emergency situations (viz. in the disaster management). However, the use of A-BSs with existing terrestrial networks intensifies the inter-cell interference (ICI) to the devices and UEs, therefore leading to a degraded signal-to-interference-ratio (SIR). This paper addresses this issue by exploiting different radio access technology (RAT) (mmWave/microwave) for aerial and terrestrial networks. Indeed, the network connectivity is always a top priority for all applications. However, there are also some applications such as remote patient monitoring, and remote working, which requires both coverage and high data-rates. But, most of the existing research claims the trade-off between the coverage and the data-rate performance. Whereas this paper aims to improve coverage and rate simultaneously in an aerial-terrestrial networks by employing an optimal combination of mmWave and microwave RAT based on the proposed association strategy. The essential analysis of such an integrated network involves the evaluation of parameters based on the analytic model. Hence, this paper analytically obtains the coverage probability (CP) and average rate expressions for the proposed integrated aerial-terrestrial networks. The analysis is supported by probabilistic models-based simulations that agree closely with analytical results. The results claim that the proposed model leads to improved performance in terms of both CP and average rate. Also, the paper provides parametric analysis for CP and rate with A-BSs height and A-BSs density to enable its practical implementation in 5G/6G technologies.INDEX TERMS Aerial-terrestrial networks, millimeter-wave RAT, microwave RAT, coverage probability, average rate, stochastic geometry.

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Section: ) Air-to-ground Channelmentioning

confidence: 99%

Section: ) Air-to-ground Channelmentioning

confidence: 99%

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Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

et al. 2021

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Pilot and data power optimization problems in multiple Aerial Relay Stations cell‐free communication systems

Duc,

Hoang,

Phuong

et al. 2024

Int J Communication

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SummaryA cell‐free (CF) technology and unmanned aerial vehicles (UAVs) acting as aerial relay stations (ARSs) are gradually viewed as viable technologies for usage in sixth‐generation (6G) wireless networks owing to their outstanding advantages, such as large coverage, uniform service quality, huge connections, flexible deployment in all geographical areas, and high line‐of‐sight (LoS) probability. As a result, the combination of the CF model and UAVs is suitable for densely populated urban areas, shopping malls, festivals, and locations with complex geography. Furthermore, the integration of the CF model and UAV communication can improve system quality and is considered an entirely new research direction as there is no comprehensive investigation of this combined model. In this study, we investigate the quality of the multi‐ARS CF communication system, where ARSs are equipped with multiple antennas and stochastic distribution within a specific region to simultaneously serve numerous ground users. We establish a closed‐form formulation for the uplink and downlink throughput of individual users by using the matched filtering method and conjugate beamforming technology, respectively. Moreover, we propose a novel method to optimize the pilot and data transmission power coefficients for improving channel estimation and increasing throughput per user, thereby ensuring a high quality of service. The power optimization method is executed via the successive convex approximation (SCA) method, second‐order cone program (SOCP), and linear program. We evaluate system performance according to the cumulative distribution function (CDF) of user throughput based on various parameters, such as the number of users, the number of ARSs, and the length of pilot sequences. The analytical findings also reveal that the system with the proposed power optimization method is always superior to the system without the proposed method in both uplink and downlink.

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6G Enabling Technologies

Polese

Giordani

Mezzavilla

et al. 2021

Computer Communications and Networks

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Coverage Analysis of UAVs in Millimeter Wave Networks: A Stochastic Geometry Approach

Cited by 25 publications

References 36 publications

Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

Design and Analysis of Aerial-Terrestrial Network: A Joint Solution for Coverage and Rate

Pilot and data power optimization problems in multiple Aerial Relay Stations cell‐free communication systems

6G Enabling Technologies

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