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 $\varphi $ and the directivity factor $\omega $ . In addition, the tradeoff between cell association and interference isolation is exploited by adjusting $\omega $ and UAV LOS/NLOS probabilities. Theoretical results show that, system coverage probability could be improved by 41% in urban environment when $\omega =6.2$ and UAV density $\lambda _{u}=300/k{m^{2}}$ .

Exploiting multiple-input multiple-output (MIMO) technology in UAV networks will mine the potential of spatial multiplexing. However, considering UAVs 3D distribution and line-of-sight (LOS)/non-line-of-sight (NLOS) channel dynamics, multi-antenna transmission will exacerbate network irregularity and render interference management a complicated problem to solve. This paper proposes 3D coordination model for interference management via multi-cell beamforming and signal-level cooperation in multi-antenna UAV networks, and analyzes system performance by deriving semi-closed expression of coverage probability using stochastic geometry. Specifically, UAVs are deployed according to 3D Poisson point process (PPP) with maximum height limit $L$ , and user-centric cell group selection is considered according to specific signal threshold $\eta $ for interference coordination with the consideration of LOS/NLOS channel conditions. Zero-forcing beamforming and joint transmission is performed within the UAV cluster for interference mitigation with limited channel state information feedback taken account. In addition, considering the irregularity of UAV group, system performance is construed as three scenarios and coverage probability is derived by Gamma approximation with proposed novel coordinate system transformation. Numerical results match well with simulations and provide optimal deployment parameters for UAV deployments, where coverage probability can reach 92% when SIR threshold $T=0$ dB.

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× in ultra dense city scenario (p = 0.8) when signal-to-interference ratio (SIR) threshold equals 0dB, compared with terrestrial BSs.

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 environments, where buildings are distributed according to Boolean model with heights ($H_k$) followed Rayleigh distribution. 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 $\mu$ 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 with respect to scenarios where power control is disabled.

In existing research of cache-enabled UAV networks, cell association is content-centric regardless of UAV line-of-sight (LOS)/non-line-of-sight (NLOS) channel dynamics, and the fixed content distribution hinders system performance. This paper proposes user-centric cooperation for cache-enabled UAV networks to exploit both contents and transmission diversity, and optimizes the probabilistic caching distribution to minimize system outage probability considering UAV interference topology dynamics. Specifically, user-centric UAV group (UAVG) is formed for each user to increase both aggregated cache size and transmission resources, considering UAVs can’t realize inter-nodes cache file transform due to limited wireless backhaul. Users will search the required content within the UAVG and associate to the cache hit UAV that provides the strongest signal-to-interference ratio (SIR), thus the intrinsic gain of transmission diversity can be achieved. If the required content can’t be successfully transmitted by UAVG, the macro base stations (MBSs) will help transmit the target content. In addition, based on analytical results, the optimal content distribution (OCD) probability is optimized by Lagrange multiplier, thus the tradeoff between content diversity gain and limited cache size is exploited. Analytical results show that, compared with caching the most popular contents policy, our proposed OCD model can decrease system average outage probability by 44.8%.

In the existing works on performance analysis of cache-enabled unmanned aerial vehicle (UAV) networks, caching distribution is fixed, and the joint cache-level and transmission-level cooperation has not been analyzed in literature. Considering UAVs agility and line-of-sight (LOS)/non-line-of-sight (NLOS) channel characteristics, this article proposes a tunable caching distribution model, where content placement and transmission can be flexibly adjusted to match interference topology dynamics and derives semi-closed expression of caching coverage probability via stochastic geometry. Specifically, UAVs will take the partition coefficient $\rho $ to determine caching distribution, where the most popular content files are reserved in every UAV within the cooperation group and jointly transmit to the user, while other files are probabilistic stored in the remaining cache space to achieve content diversity. In addition, when requiring the less popular files, the user will always connect to the UAV with the best signal-to-interference (SIR) ratio among cache hit UAVs within the cooperation group. The theoretical analysis investigates the effects of various system parameters such as UAVs height, cooperative radius, and content popularity on the caching coverage probability and optimal $\rho $ for can be found. It can be seen that optimal $\rho $ will be decreased first and then increased along with the increase of UAVs height, which reveals the tradeoff between cache hit probability and transmission reliability. Analytical results show that our proposed cache and transmission policy can achieve 34% gain of coverage probability compared to the policy of probabilistic cached.