Average Error Probability Analysis in mmWave Cellular Networks

In this paper, a mathematical framework for the analysis of average symbol error probability (ASEP) in millimeter wave (mmWave) cellular networks with Poisson Point Process (PPP) distributed base stations (BSs) is developed using tools from stochastic geometry. The distinguishing features of mmWave communications such as directional beamforming and having different path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) links are incorporated in the average error probability analysis. First, average pairwise error probability (APEP) expression is obtained by averaging pairwise error probability (PEP) over fading and random shortest distance from mobile user (MU) to its serving BS. Subsequently, average symbol error probability is approximated from APEP using the nearest neighbor (NN) approximation. ASEP is analyzed for different antenna gains and base station densities. Finally, the effect of beamforming alignment errors on ASEP is investigated to get insight on more realistic cases.Comment: Presented at IEEE VTC2015-Fal

Modeling and Analysis of Cellular Networks Using Stochastic Geometry: A Tutorial

This paper presents a tutorial on stochastic geometry (SG)-based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. This paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of this paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. This paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, this paper highlights the state-of-the-art research and points out future research directions

Performance Analysis for 5G cellular networks: Millimeter Wave and UAV Assisted Communications

Recent years have witnessed exponential growth in mobile data and traffic. Limited available spectrum in microwave ($\mu$Wave) bands does not seem to be capable of meeting this demand in the near future, motivating the move to new frequency bands. Therefore, operating with large available bandwidth at millimeter wave (mmWave) frequency bands, between 30 and 300 GHz, has become an appealing choice for the fifth generation (5G) cellular networks. In addition to mmWave cellular networks, the deployment of unmanned aerial vehicle (UAV) base stations (BSs), also known as drone BSs, has attracted considerable attention recently as a possible solution to meet the increasing data demand. UAV BSs are expected to be deployed in a variety of scenarios including public safety communications, data collection in Internet of Things (IoT) applications, disasters, accidents, and other emergencies and also temporary events requiring substantial network resources in the short-term. In these scenarios, UAVs can provide wireless connectivity rapidly. In this thesis, analytical frameworks are developed to analyze and evaluate the performance of mmWave cellular networks and UAV assisted cellular networks. First, the analysis of average symbol error probability (ASEP) in mmWave cellular networks with Poisson Point Process (PPP) distributed BSs is conducted using tools from stochastic geometry. Secondly, we analyze the energy efficiency of relay-assisted downlink mmWave cellular networks. Then, we provide an stochastic geometry framework to study heterogeneous downlink mmWave cellular networks consisting of $K$ tiers of randomly located BSs, assuming that each tier operates in a mmWave frequency band. We further study the uplink performance of the mmWave cellular networks by considering the coexistence of cellular and potential D2D user equipments (UEs) in the same band. In addition to mmWave cellular networks, the performance of UAV assisted cellular networks is also studied. Signal-to-interference-plus-noise ratio (SINR) coverage performance analysis for UAV assisted networks with clustered users is provided. Finally, we study the energy coverage performance of UAV energy harvesting networks with clustered users