The current decades have witnessed the explosive increase of traffic-data demand. It is predicted that indoor wireless communications will be one of the fastest growing markets, since the vast majority (over 80%) of data demand occurs in indoors. Facing such a huge data demand, the dense deployment of small cells (SCs) in indoor environments is boosted, which brings breakthroughs of throughput for in-building communications. However, the densification of indoor small-cell (SC) networks also poses new challenges, such as complex propagating environments, severe blockage effects and short link distances, which significantly influence the evaluation of network performance. This thesis mainly investigates the performance analysis of indoor dense SC networks.
Firstly, the probability of Line-of-Sight (LOS) propagation is crucial to model the real signal propagation channels and to evaluate the performance of cellular networks. However, existing LOS probability models are oversimplified to provide the exact LOS probability in indoor scenarios. By considering the realistic layout of building structures, this thesis proposes a novel and analytical LOS probability model for downlink radio propagations in typical indoor scenarios, which have rectangular rooms and corridors. Through the proposed model, the LOS probability can be calculated directly without the measurement and simulation.
Next, in terms of the impact of LOS and Non-Line-of-Sight (NLOS) transmissions, the traditional works do not distinguish them, which is not practical for dense cellular networks. Thus, a tractable path loss model considering both LOS and NLOS propagations is proposed for the performance analysis of indoor dense SC networks. Based on the theory of stochastic geometry, the performance metrics, such as coverage probability, spectral
efficiency (SE) and area spectral efficiency (ASE), are analytically derived. The analytical results provide insights into the design of indoor dense SC networks in the future.
Thirdly, regarding the severe effects of blockages in indoor environments, the traditional approach that simply considers it as a log-normal shadowing is too simple. Therefore, a wall blockage model is developed to characterize the impact of blockages based on the stochastic geometry. Furthermore, the mathematical expression of coverage probability for the case of impenetrable blockages is derived, which employs a path loss model incorporating both the blockage-based and distance-based path loss
