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To alleviate the time overhead of the handover and beam reselection caused by user mobility, a velocity-based association policy has been adopted in heterogeneous networks. However, it might introduce severe interference from cross-tier interfering base stations which are closer to the users than the serving one. To deal with this problem, we propose two cross-tier interference coordination (CTIC) schemes for mobile users in heterogeneous networks: one jointly considers the transmit power and path loss (TPL-CTIC), and the other further incorporates the directional antenna gain (TPG-CTIC). Considering the beam misalignment and the time overhead caused by user mobility, we derive the overall coverage probability and the average effective Shannon rate (ESR) of mobile users to characterize the user-perceived performance. Taking the cost of the proposed CTIC schemes into account, we further derive the average normalized throughput to evaluate the overall network performance. Numerical results demonstrate that compared with the case without CTIC, the proposed schemes significantly improve the overall coverage probability in the low signal-to-interference-plus-noise ratio regime and the average ESR. To capture the expense of proposed schemes, we define the average normalized throughput. Although TPL-CTIC performs better in terms of the overall coverage probability and the average ESR, TPG-CTIC outperforms in terms of the average normalized throughput.

Combining intelligent reflecting surface (IRS) with an unmanned aerial vehicle to form aerial IRS (AIRS) swarms is an effective way to enable panoramic full-angle reflection, high configuration flexibility and reliable air-ground line-of-sight (LoS) connections, especially in millimeter wave (mmWave) bands. In this paper, we use stochastic geometry to provide a performance analytical framework for AIRS swarm-assisted mmWave cellular networks, where each base station (BS) has an AIRS swarm to assist downlink communications. To capture the swarm property of AIRSs and the dependence between AIRS swarms and BSs, the AIRSs in each swarm are uniformly and randomly distributed in a finite circular area centered on their assisting BS. Incorporating different LoS/non-LoS propagation characteristics, a two-step user association policy is proposed to pursue an efficient communication link between the BS and its users with the assistance of AIRS swarm. We derive the coverage probability and area spectral efficiency (ASE) by considering three types of interference which are directly from interfering BSs, reflected by active AIRSs of other swarms and reflected by the assisting AIRS for the typical user, respectively. The results reveal that AIRS swarms enhance both coverage and ASE performance and have the optimal height and density that maximize the coverage probability in mmWave cellular networks.

Intelligent reflecting surface (IRS) is a promising technology to provide line-of-sight (LOS) links for blocked paths, especially in millimeter wave (mmWave) cellular networks. However, in practice, it is difficult for IRSs to arbitrarily adjust the reflection angle to align served users. A promising solution is to deploy distributed IRSs to increase the probability that the users lie in the reflection directions. This paper develops a stochastic geometry-based approach for studying the coverage enhancement in mmWave cellular networks via distributed IRSs. Specifically, the locations of IRSs are modeled through a binomial point process centered at a base station, and the reflection beam of each IRS is pointed to a certain direction. Considering the difference between LOS and non-LOS mmWave transmissions, we propose a received signal strength indicator based association strategy to guarantee that the users receive the strongest average power. After characterizing the association probabilities and distance distributions, we derive the coverage probability for an arbitrary user and perform simplifications for enhancing the computation efficiency. The results are validated by simulations and reveal that distributed deployment of IRSs can achieve a better coverage probability than that of the centralized deployment, which validates the feasibility of enhancing system performance through distributed IRSs.