Multiobjective Optimization in 5G Hybrid Networks

The increasing adoption of the Internet of Things has led to the need for systems with higher spectral and energy efficiency (EE) in order to enable communication. Larger data rate demands had led researchers to look at millimeter wave (mmWave) bands to boost network rates. This paper investigates the downlink performance of a three-tier heterogeneous network that consists of sub-6 GHz macrocells overlaid with small cells operating on both the mmWave and sub-6 GHz bands. A model is developed using tools from stochastic geometry to analyze the coverage, rate, area spectral efficiency, and EE of such a network. Various deployment strategies and their impacts on the considered metrics are studied. Simulation results are used to verify the validity of the proposed model

A Stochastic Geometry approach towards Green Communications in 5G

In this dissertation, we investigate two main research directions towards net- work efficiency and green communications in heterogeneous cellular networks (HetNets) as a promising network structure for the fifth generation of mobile systems. In order to analyze the networks, we use a powerful mathematical tool, named stochastic geometry. In our research, first we study the performance of MIMO technology in single-tier and two-tier HetNets. In this work, we apply a more realistic network model in which the correlation between tiers is taken into account. Comparing the obtained results with the commonly used model shows performance enhancement and greater efficiencies in cellular networks. As the second part of our research, we apply two Cell Zooming (CZ) techniques to HetNets. With focus on green communications, we present a K−tier HetNet in which BSs are only powered by energy har- vesting. Despite the uncertain nature of energy arrivals, combining two CZ techniques, namely telescopic and ON/OFF scenarios, enables us to achieve higher network performance in terms of the coverage and blocking probabilities while reducing the total power consumption and increasing the energy and spectral efficiencies

User Association in 5G Networks: A Survey and an Outlook

26 pages; accepted to appear in IEEE Communications Surveys and Tutorial

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

Resource Optimization in Multi-Tier HetNets Exploiting Multi-Slope Path Loss Model

Current resource allocation techniques in cellular networks are largely based on single-slope path loss model, which falls short in accurately capturing the effect of physical environment. The phenomenon of densification makes cell patterns more irregular; therefore, the multi-slope path loss model is more realistic to approximate the increased variations in the links and interferences. In this paper, we investigate the impacts of multi-slope path loss models, where different link distances are characterized by different path loss exponents. We propose a framework for joint user association, power and subcarrier allocation on the downlink of a heterogeneous network (HetNet). The proposed scheme is formulated as a weighted sum rate maximization problem, ensuring the users' quality-of-service requirements, namely users' minimum rate, and the base stations' (BSs) maximum transmission power. We then compare the performance of the proposed approach under different path loss models with demonstrate the effectiveness of dual-slope path loss model in comparison to the single-slope path loss model. Simulation results show that the dual-slope model leads to significant improvement in network's performance in comparison to the standard single-slope model by accurately approximating the path loss exponent dependence on the link distance. Moreover, it improves the user offloading from macrocell BS to small cells by connecting the users to nearby BSs with minimal attenuation. It has been shown that the path loss exponents significantly influence the user association lying across the critical radius in the case of the dual-slope path loss model

Computationally Intelligent Techniques for Resource Management in MmWave Small Cell Networks

Ultra densification in HetNets and the advent of mmWave technology for 5G networks have led researchers to redesign the existing resource management techniques. A salient feature of this activity is to accentuate the importance of CI resource allocation schemes offering less complexity and overhead. This article overviews the existing literature on resource management in mmWave-based Het- Nets with a special emphasis on CI techniques and further proposes frameworks that ensure quality of service requirements for all network entities. More specifically, HetNets with mmWave-based small cells pose different challenges compared to an all-microwave- based system. Similarly, various modes of small cell access policies and operations of base stations in dual mode, that is, operating both mmWave and microwave links simultaneously, offer unique challenges to resource allocation. Furthermore, the use of multi-slope path loss models becomes inevitable for analysis due to irregular cell patterns and blocking characteristics of mmWave communications. This article amalgamates the unique challenges posed because of the aforementioned recent developments and proposes various CI-based techniques, including game theory and optimization routines, to perform efficient resource management