Association and spectrum sharing in cellular networks

Many models have been proposed to evaluate performance of cellular communication systems. However, the emergence of new technologies have changed cellular systems significantly, and requires new modeling and analysis approaches. This dissertation studies network level optimization concerning cell association and spectrum sharing. As the first contribution, the dissertation presents a framework to investigate downlink multi-antenna heterogeneous networks with flexible cell selection and shows that a simple selection bias-based cell selection criterion closely approximates more complex selection rules to maximize mean the signal-to-interference-plus-noise- ratio (SINR). Under this simpler cell selection rule, the exact expressions for coverage probability and achievable rate of a typical user are derived along with an approximation of the coverage optimal cell selection bias. In the second contribution, the dissertation considers a cellular system where users are simultaneously connected to multiple base stations (BSs) to decrease blockage sensitivity and proposes a framework to analyze the correlation in blocking among multiple links. It evaluates the gains of macro-diversity in the presence of random blockages along with the impact of the blockage size. In the third contribution, the dissertation considers spectrum sharing among millimeter wave (mmWave) operators. A two-level architecture is proposed to model a mmWave multi-operator system and the SINR and per-user rate distribution are derived in the presence of spectrum and infrastructure sharing. It is shown that due to narrow beams, license sharing among operators improves system performance by increasing the per-user rate, even when there is no explicit coordination. In the fourth contribution, this analysis is extended to include static coordination among operators in the form of secondary licensing. A framework is developed to model a mmWave cellular system with a primary operator that has an ``exclusive-use'' license with a provision to sell a restricted secondary license to another operator that has a maximum allowable interference threshold. This licensing approach provides a way of differentiating the spectrum access for the different operators. Results show that compared to uncoordinated sharing, a reasonable gain can be achieved using the proposed secondary licensing, especially for edge rates.Electrical and Computer Engineerin

Correlated Blocking in mmWave Cellular Networks: Macrodiversity, Outage, and Interference

In this paper, we provide a comprehensive analysis of macrodiversity for millimeter wave (mmWave) cellular networks. The key issue with mmWave networks is that signals are prone to blocking by objects in the environment, which causes paths to go from line-of-sight (LOS) to non-LOS (NLOS). We identify macrodiversity as an important strategy for mitigating blocking, as with macrodiversity the user will attempt to connect with two or more base stations. Diversity is achieved because if the closest base station is blocked, then the next base station might still be unblocked. However, since it is possible for a single blockage to simultaneously block the paths to two base stations, the issue of correlated blocking must be taken into account by the analysis. Our analysis characterizes the macrodiverity gain in the presence of correlated random blocking and interference. To do so, we develop a framework to determine distributions for the LOS probability, Signal to Noise Ratio (SNR), and Signal to Interference and Noise Ratio (SINR) by taking into account correlated blocking. We validate our framework by comparing our analysis, which models blockages using a random point process, with an analysis that uses real-world data to account for blockage. We consider a cellular uplink with both diversity combining and selection combining schemes. We also study the impact of blockage size and blockage density along with the effect of co-channel interference arising from other cells. We show that the assumption of independent blocking can lead to an incorrect evaluation of macrodiversity gain, as the correlation tends to decrease macrodiversity gain

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