Analysis of Millimeter-Wave Networks: Blockage, Antenna Directivity, Macrodiversity, and Interference

Due to its potential to support high data rates at low latency with reasonable interference isolation because of signal blockage at these frequencies, millimeter-wave (mmWave) communications has emerged as a promising solution for next-generation wireless networks. MmWave systems are characterized by the use of highly directional antennas and susceptibility to signal blockage by buildings and other obstructions, which significantly alter the propagation environment. The received power of each transmission depends on the direction the corresponding antennas point and whether the signal’s path is line-of-sight (LOS), non-LOS (i.e., partially blocked), or completely blocked. A key challenge in modeling blocking in mmWave networks is that, in actual networks, the blocking might be correlated. Such correlation arises, for example, when single transmitter tries to broadcast to pair of receivers that are close to each other, or more generally when they have a similar angle to the transmitter. In this situation, if the first receiver is blocked, it is likely that the second one is blocked, too. This dissertation explores four related but distinct issues associated with mmWave networks: 1) Analytical modeling of networks consisting of user devices and blockages with fixed or random, but independent, locations, 2) The careful characterization of correlated blocking and analysis of its impact on the performance of mmWave networks, 3) The proposed use of macrodiversity as an important strategy to mitigating correlated blocking in mmWave networks and the corresponding analysis, and 4) The proposed use of networks of unmanned aerial vehicles (UAVs) to provide connectivity in urban deployments. This work provides insight into the performance of variety of applications of mmWave communications, ranging from wireless personal area networks (WPAN), device-to-device networks, traditional terrestrial, cellular networks, and the UAV-based networks where the UAVs act as the cellular base stations. A common thread throughout this dissertation is the development of new tools based on stochastic geometry and their application to modeling and analysis. The analysis presented in this dissertation is general enough to find application beyond mmWave networks, for instance the results may also be applicable to systems that use free-space optical (FSO) signaling technologies