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The evolution of the fifth-generation (5G)/ beyond 5G (B5G) mobile communication networks greatly depends on the seamless integration of terrestrial and sky networks over advanced multi-tier heterogeneous network (HetNet) infrastructure. By using the huge potential of unmanned aerial vehicles (UAVs) and mm-Wave, we develop a novel and practical multi-UAV assisted multi-tier HetNet model which consists of clustered aerial UAV base stations (U-BSs) and Poisson point process (PPP) based ground BSs (G-BSs) for emergency and crowded hotspot area. In a typical cluster, both ground user equipments (GUEs) and UAVs are modeled as Poisson cluster process (PCP) and scattered around the common cluster center. Specially, the analysis is conducted by adding two additional tiers which consist of multiple intra-cluster U-BSs and single G-BS in representative cluster so that the point sets of U-BSs and G-BSs are partitioned into two sub-sets, respectively, and a 4-tier network model is formed. To find the contribution of the inter-cluster associations on the performance of networks, we construct 2-tier and 4-tier association schemes. The 2-tier association allows a GUE associated only with intra-cluster U-BSs and G-BS, while the 4-tier association allows all inter/intra-cluster U-BSs and G-BSs can be associated. Then, according to stochastic geometry methods, statistical description of the downlink interferences experienced at a typical GUE is derived. This derivation yields the downlink coverage probabilities and total network throughput are obtained. It is achieved that association probabilities greatly depend on the distribution of daughter point process. UAVs' height and the distributions of U-BSs and GUEs impose non-monotonous impact on coverage probabilities. Due to severe inter-cluster interference, the achievable average area throughput is not always increasing with SINR so that there is an optimal SINR threshold. In addition, our analysis finds the proposed 4-tier association scheme outperforms the simple 2-tier one in terms of the average area throughput.

The deployment of low power small base stations (SBSs) in high density user areas enhances the performance of heterogeneous cellular networks (HCNets). Such user-centric SBS deployment (UCSD) is more appropriate as compared with the conventional uniformly deployed user equipment (UE) based HCNets, because it captures the correlation between UEs and SBSs. In the literature, the downlink (DL) performance of UCSD based HCNet (UC-HCNet) has been analyzed under maximum received signal power (MRSP) association strategy. In this paper, we develop and analyze the uplink (UL) performance of UC-HCNets with decoupled UL-DL association (DUDA) using stochastic geometery. We evaluate the total UL interference considering two special cases of Poisson cluster process (PCP), i.e., Matern cluster process (MCP) and Thomas cluster process (TCP), in UC-HCNet. The proposed DUDA scheme enhances the system performance gain by assuming dual connectivity of UE and BSs in the UL and DL directions. Furthermore, fractional power control (FPC) policy is considered to limit the UL power consumption. The system performance is evaluated in terms of outage probability and rate coverage. The numerical results are validated through simulations. Numerical results show that the performance improvement of DUDA in sparse scenario is higher as compared with dense scenario. Furthermore, it is investigated that the performance gain of DUDA is higher for larger UE variance and cluster radius in case of MCP and TCP, respectively.

In this paper, we investigate the uplink transmission performance of low-power wide-area (LPWA) networks with regards to coexisting radio modules. We adopt long range (LoRa) radio technique as an example of the network of focus even though our analysis can be easily extended to other situations. We exploit a new topology to model the network, where the node locations of LoRa follow a Poisson cluster process (PCP) while other coexisting radio modules follow a Poisson point process (PPP). Unlike most of the performance analysis based on stochastic geometry, we take noise into consideration. More specifically, two models, with a fixed and a random number of active LoRa nodes in each cluster, respectively, are considered. To obtain insights, both the exact and simple approximated expressions for coverage probability are derived. Based on them, area spectral efficiency and energy efficiency are obtained. From our analysis, we show how the performance of LPWA networks can be enhanced through adjusting the density of LoRa nodes around each LoRa receiver. Moreover, the simulation results unveil that the optimal number of active LoRa nodes in each cluster exists to maximize the area spectral efficiency., Comment: This paper has been accepted by IEEE Trans. Vehicular Technology (TVT)

This paper focuses on a comprehensive framework design and performance analysis for a large-scale hotspot communication scenario where there exist large number of clustered pico base stations (P-BSs) and femto BSs (F-BSs) working on millimeter-Wave (mm-Wave). For such realistic hotspots’ deployment, to exploit the coupling between user equipments (UEs) and base stations (BSs), we model the geographical centers of UE hotspots as independent PPP around which UEs, P-BSs and F-BSs are scattered and form independent and non-homogeneous Poisson cluster processes (PCPs). However, with clustered P-BSs and F-BSs, the UEs would experience the severer intra-cluster interference so that the performance is degraded greatly. To overcome this problem in clustered networks, an effective interference management scheme is proposed by using the ratio of the first and second nearest distances of a typical UE from P-BSs so that a typical UE can be classified as either cluster-center UEs (CCUEs) or cluster-edge UEs (CEUEs). Correspondingly, the total available spectrum band is divided as CCUE-band and CEUE-band, which are occupied by P-BSs associated with CCUEs and CEUEs, respectively. Unlike P-BSs, the F-BSs randomly access the CEUE-band and CCUE-band with a given access portion factor. By using the method from stochastic geometry and the distinguishing feature of mm-Wave, such as directional beamforming with sectored antenna model and modified line of sight ball model for blockage, the UE association probability and Laplace transforms of interference are derived. This yields the derivations of downlink transmission rates. The numerical results show that the proposed clustered heterogeneous scheme with the cluster-UE classification outperforms the traditional ones without the UE classification. This approach not only captures the UE-BS coupling and the non-homogeneous nature of multi-tier networks, but also restricts the severe intra-cluster interference due to clustered BSs.

The use of unmanned aerial vehicles (UAVs) operating as aerial base stations (BSs) has emerged as a promising solution especially in scenarios requiring rapid deployments (e.g., in the cases of crowded hotspots, sporting events, emergencies, and natural disasters) in order to assist the ground BSs. In this paper, an analytical framework is provided to analyze the signal-to-interference-plus-noise ratio (SINR) coverage probability of UAV assisted cellular networks with clustered user equipments (UEs). Locations of UAVs and ground BSs are modeled as Poison point processes, and UEs are assumed to be distributed according to a Poisson cluster process around the projections of UAVs on the ground. Initially, the complementary cumulative distribution function and probability density function of path losses for both UAV and ground BS tiers are derived. Subsequently, association probabilities with each tier are obtained. SINR coverage probability is derived for the entire network using tools from stochastic geometry. Finally, area spectral efficiency (ASE) of the entire network is determined, and SINR coverage probability expression for a more general model is presented by considering that UAVs are located at different heights. Via numerical results, we have shown that UAV height and path-loss exponents play important roles on the coverage performance. Moreover, coverage probability can be improved with smaller number of UAVs, while better ASE is achieved by employing more UAVs and having UEs more compactly clustered around the UAVs.