Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

In the existing work of unmanned aerial vehicle base station (UAV-BS) deployment, where serving radius (SR) is fixed regardless of resource waste and overlapping interference, dynamic tunability of SR has not been considered. In this letter, a dynamic tunable model where SR can be properly adjusted is proposed, based on which a semi-progressive offloading deployment scheme devoted to UAV number and overlapping interference optimization is raised. Specifically, UAV is deployed around macro base stations (MBSs), where a certain proportion ( $\gamma $ ) of the ground terminals (GTs) are covered first with the principle of minimum overlap and maximum coverage, then through tunability of SR, the rest GTs are covered without increasing UAV number. Moreover, the base station expands its SR to cover the closest uncovered GT through fine adjustment of power (MBS) or antenna down-tilt (UAV), after which surrounding UAVs are also adjusted to reduce overlapping interference. The results show our proposed scheme reduces 17.26% UAV quantity compared with the cluster method and decreases 71.75% interference compared with the core-set method.

Deployment Optimization of UAV-Aided Networks Through a Dynamic Tunable Model

To reduce strong mutual interference between unmanned aerial vehicles (UAVs) and ground base stations (GBSs) and to balance the quality of service (QoS) of cell-center and cell-edge users, in UAV-assisted millimeter wave (mmWave) cellular networks we let the UAVs serving as aerial base stations (ABSs) keep a certain distance from the GBSs. It is assumed that GBSs are distributed by a Poisson point process (PPP) on the ground, and the location of UAVs is modeled as a Poisson hole process (PHP) at a certain altitude. Based on the preserving neighbor hole approximation method, the nearest distance distribution functions are derived. With the strongest average received power association policy, we provide the distribution functions of serving distances and the user association probabilities. Then, the coverage probability of the considered network is derived. The coverage performance of two special cases, the mmWave terrestrial cellular network and the UAV-assisted mmWave cellular network with PPP model, are also derived. In addition, the analysis framework is extended into the scenario where UAVs have different altitudes. Through simulations, optimal key ABS parameters maximizing the coverage probability are demonstrated. It also unveils that the proposed UAV-assisted mmWave cellular network can enhance the coverage probability via carefully designing of system parameters.

Coverage Analysis for UAV-Assisted mmWave Cellular Networks Using Poisson Hole Process

Line-of-sight (LOS) probability is a key component of system-level simulations that are required for creating new standards and recommendations for wireless systems. In particular, for millimeter-wave systems, an unobstructed view between the base station at an elevation and a user at ground level is important to ensure high-throughput service. While statistical models for LOS blockage by buildings exist, such models for blockage by multiple small objects, such as trees and street signs, are currently lacking. In this work, we present a Poisson point process-based analytic solution in a form of an algorithm for evaluating LOS probability in the presence of any combination of arbitrarily shaped shadowing objects, taking into account carrier frequency. The algorithm is validated against the LOS probability obtained from ray tracing in a realistic urban microcell scenario. 

Line-of-Sight Probability in Cluttered Urban Microcells: Analyses Using Poisson Point Process and Point Cloud

Performance analysis of UAV multiple antenna-assisted small cell network with clustered users

Unmanned aerial vehicle (UAV) networks hold tremendous potential to provide on-demand wireless services for hotspots in city scenario. However, densely located buildings will cause the spatial constraints for UAV distribution and affect the network connectivity. This letter proposes a tractable model of UAV networks with 3D blockage effects and analyzes system coverage probability via stochastic geometry, where buildings are distributed according to Poisson point process (PPP) with heights ( $H_{k}$ ) followed Rayleigh distribution. Specifically, cell selection is considered with the blockage effects instead of distance-based, thus distance distribution of typical UE to the closest visible UAV is modified. In addition, the probability of establishing a line-of-sight (LOS) link is proven to decay exponentially with the horizontal distance between the typical user and the object UAV. Theoretical results show that with the deployment of UAVs, coverage probability can be improved by $5.3\times $ in ultra dense city scenario ( ${p}=$ 0.8) when signal-to-interference ratio (SIR) threshold equals 0dB, compared with terrestrial BSs.

Tractable Modelling and Performance Analysis of UAV Networks With 3D Blockage Effects

In urban UAV networks, UAVs deployment locations and air-to-ground (AtG) communication links will possibly conflict with densely located buildings, which exacerbate network irregularity and make interference management more complicated. This paper proposes interference coordination via power control under 3D blockage effects in urban environment, where building blockages are formed a Boolean model with independent heights (Hk) followed Rayleigh distribution, and analyzes system performance using tools from stochastic geometry. Specifically, a dynamic UAV group (UAVG) is organized to serve each user for interference coordination, which consists several nearest visible UAVs with line-of-sight (LOS) connections considering buildings blockage effects, and the modified distribution from user to its nearest unblocked UAV is derived. Power control is executed in UAVG where adjacent interfering UAVs within the group will mute their transmission for interference mitigation, and optimal UAVG radius coefficient is obtained, which reveals the trade off between interference mitigation and resource utilization. Leveraging stochastic geometry, theoretical expressions of network metrics are derived with Nakagami-m fading assumption, including network coverage probability and network connectivity. Analytical results show that in urban city scenario, comparing with traditional terrestrial networks, coverage performance can achieve 4.1 gain by deploying UAVs with optimal height, and achieve additional 26% gain.

Performance Analysis of Power Control in Urban UAV Networks with 3D Blockage Effects

Existing researches on UAV networks mostly adopt omni-directional antenna pattern, which results in overlapping between coverage areas and bringing severe co-channel interference due to air-to-ground dominant line-of-sight (LOS) channels. Considering directional antennas that concentrate transmission power to small cells, this letter analyzes system performance of UAV-assisted networks with conic directional antenna model by deriving network coverage probability via stochastic geometry, where UAVs and macro base stations (MBSs) are deployed according to independent Poisson point process. Specifically, realistic and mathematically tractable directional antenna pattern is adopted that radiation gain is modeled by a continuous function of the elevation angle <inline-formula> <tex-math notation="LaTeX">$\varphi $ </tex-math></inline-formula> and the directivity factor <inline-formula> <tex-math notation="LaTeX">$\omega $ </tex-math></inline-formula>. In addition, the tradeoff between cell association and interference isolation is exploited by adjusting <inline-formula> <tex-math notation="LaTeX">$\omega $ </tex-math></inline-formula> and UAV LOS/NLOS probabilities. Theoretical results show that, system coverage probability could be improved by 41% in urban environment when <inline-formula> <tex-math notation="LaTeX">$\omega =6.2$ </tex-math></inline-formula> and UAV density <inline-formula> <tex-math notation="LaTeX">$\lambda _{u}=300/k{m^{2}}$ </tex-math></inline-formula>.

Wenfei Tang

Papers

Tractable Modelling and Performance Analysis of UAV Networks With 3D Blockage Effects

Performance Analysis of Power Control in Urban UAV Networks with 3D Blockage Effects

Directional Antennas Modeling and Coverage Analysis of UAV-Assisted Networks