System design issues in dense urban millimeter wave cellular networks

Upcoming deployments of cellular networks will see an increasing use of millimeter wave (mmWave) frequencies, roughly between 20-100 GHz. The goal of this dissertation is to investigate some key design issues in dense urban mmWave cellular networks by developing mathematical models that are representative of these networks. In the first contribution, stochastic geometry (SG) is used to study the per user rate performance of multi-user MIMO (MU-MIMO) in downlink mmWave cellular network incorporating the impact of a spatially sparse blockage dependent multipath channel and hybrid precoding. Performance of MU-MIMO is then compared with single-user beamforming and spatial multiplexing in different network scenarios considering coverage, rate and power consumption tradeoffs to suggest when to use which MIMO scheme. The second contribution reconsiders a popular received signal power model used in system capacity analysis of MIMO wireless networks employing single user beamforming. A modification is suggested to the model by introducing a correction factor. An approximate analysis is done to justify incorporating such a factor and simulations are performed to validate it's importance. Although this contribution does not study a new system design issue for mmWave cellular, it highlights a shortcoming with using the popular received signal power model to study design issues in mmWave cellular networks. The third and fourth contributions investigate resource allocation in self-backhauled mmWave cellular networks. In order to enable affordable initial deployments of mmWave cellular, self-backhauling is envisioned as a cost-saving solution. The third contribution investigates how to divide resources between uplink and downlink for access and backhaul in self-backhauled networks with single hop wireless backhauling. The performance of dynamic time division duplexing (TDD) and integrated access-backhaul (IAB) is compared with static TDD and orthogonal access backhaul (OAB) strategies using a SG based model. The last contribution of this dissertation addresses the following key question for self-backhauled networks. What is the maximum extended coverage area that a single fiber site can support using multi-hop relaying, while still achieving a minimum target per user data rate? The problem of maximizing minimum per user rates is studied considering a series of deployments with a single fiber site and varying number of relays. Several design guidelines for multi-hop mmWave cellular networks are provided based on the analytical and empirical results.Electrical and Computer Engineerin

A Millimeter Wave based Sensor Data Broadcasting Scheme for Vehicular Communications

In recent years, vehicles are becoming smart with the aid of various onboard sensing, communication and computing capability, which is helpful to improve road safety and driving experiments. With data fusion technique, a vehicle can even increase the driving safety by obtaining sensor data from other vehicles. The millimeter Wave (mmWave) based Vehicle-to-Vehicle (V2V) communication technology has become a promising technology to transmit sensor data in huge size such as video streams. However, the high radio frequency of mmWave makes it vulnerable to obstacles. Furthermore, the directional propagation property is not efficient to broadcast information among vehicles. In this paper, we propose a broadcasting scheme to guarantee each vehicle to get the sensor data of all other vehicles. Head vehicles are selected to gather the information on the environment and decide those transmission vehicles and receiving vehicles in each time slot. A graph-based routing selection algorithm is proposed with relatively low complexity. Moreover, the upper bound of broadcasting delay for one dimensional platoon is analyzed based on the network calculus theory. Simulation results indicate that the proposed scheme has faster delivery rate compared to the traditional First-In-First-Out (FIFO) scheme. The maximum broadcasting delay of the proposed scheme is less than the traditional schemes about 30% in different scenarios

Multi-hop Transmission in Millimeter Wave WPAN with Directional Antenna

Millimeter-wave (mmWave) communications is a promising enabling technology for high rate (Giga-bit) multimedia applications. However, because oxygen absorption peaks at 60 GHz, mmWave signal power degrades significantly over long distances. Therefore, a traffic flow transmitting over multiple short hops is preferred to improve the flow throughput. In this thesis, we first design a hop selection metric for the piconet controller (PNC) to select appropriate relay hops for a traffic flow, aiming to improve the flow throughput and balance the traffic loads across the network. We then propose a multi-hop concurrent transmission (MHCT) scheme to exploit the spatial diversity of the mmWave WPAN by allowing multiple communication links to transmit simultaneously. By deriving the probability that two links can transmit simultaneously as a function of link length, the MHCT scheme is capable of improving spatial multiplexing gain in comparison with the single hop concurrent transmission (SHCT) scheme. We theoretically demonstrate that by properly breaking a single long hop into multiple short hops, the time resource can be utilized more efficiently, thus supporting more traffic flows in the network within the same time interval. In addition, the per-flow throughput is obtained analytically. Extensive simulations are conducted to validate the analysis and demonstrate that the proposed MHCT scheme can significantly improve the average traffic flow throughput

Five Facets of 6G: Research Challenges and Opportunities

Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components

A Comprehensive Survey on Resource Allocation for CRAN in 5G and Beyond Networks

The diverse service requirements coming with the advent of sophisticated applications as well as a large number of connected devices demand for revolutionary changes in the traditional distributed radio access network (RAN). To this end, Cloud-RAN (CRAN) is considered as an important paradigm to enhance the performance of the upcoming fifth generation (5G) and beyond wireless networks in terms of capacity, latency, and connectivity to a large number of devices. Out of several potential enablers, efficient resource allocation can mitigate various challenges related to user assignment, power allocation, and spectrum management in a CRAN, and is the focus of this paper. Herein, we provide a comprehensive review of resource allocation schemes in a CRAN along with a detailed optimization taxonomy on various aspects of resource allocation. More importantly, we identity and discuss the key elements for efficient resource allocation and management in CRAN, namely: user assignment, remote radio heads (RRH) selection, throughput maximization, spectrum management, network utility, and power allocation. Furthermore, we present emerging use-cases including heterogeneous CRAN, millimeter-wave CRAN, virtualized CRAN, Non- Orthogonal Multiple Access (NoMA)-based CRAN and fullduplex enabled CRAN to illustrate how their performance can be enhanced by adopting CRAN technology. We then classify and discuss objectives and constraints involved in CRAN-based 5G and beyond networks. Moreover, a detailed taxonomy of optimization methods and solution approaches with different objectives is presented and discussed. Finally, we conclude the paper with several open research issues and future directions