English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

With growing popularity, unmanned aerial vehicles (UAVs) are pivotally extending conventional terrestrial Internet of Things (IoT) into the sky. To enable high-performance two-way communications of UAVs with their ground pilots/users, cellular network-connected UAV has drawn significant interests recently. Among others, an important issue is whether the existing cellular network, designed mainly for terrestrial users, is also able to effectively cover the new UAV users in the three-dimensional (3-D) space for both uplink and downlink communications. Such 3-D coverage analysis is challenging due to the unique air–ground channel characteristics, the resulted interference issue with terrestrial communication, and the nonuniform 3-D antenna gain pattern of ground base station (GBS) in practice. Particularly, high-altitude UAV often possesses a high probability of line-of-sight (LoS) channels with a large number of GBSs, while their random binary (LoS/non-LoS) channel states and (on/off) activities give rise to exponentially large number of discrete UAV-GBS association/interference states, rendering coverage analysis more difficult. This paper presents a new 3-D system model to incorporate UAV users and proposes an analytical framework to characterize their uplink/downlink 3-D coverage performance. To tackle the above exponential complexity, we introduce a generalized Poisson multinomial (GPM) distribution to model the discrete interference states, and a novel lattice approximation (LA) technique to approximate the nonlattice GPM variable and obtain the interference distribution efficiently with high accuracy. The 3-D coverage analysis is validated by extensive numerical results, which also show effects of key system parameters, such as cell loading factor, GBS antenna downtilt, UAV altitude, and antenna beamwidth.

Network-Connected UAV: 3-D System Modeling and Coverage Performance Analysis