Design and Performance Analysis of Next Generation Heterogeneous Cellular Networks for the Internet of Things

The Internet of Things (IoT) is a system of inter-connected computing devices, objects and mechanical and digital machines, and the communications between these devices/objects and other Internet-enabled systems. Scalable, reliable, and energy-efficient IoT connectivity will bring huge benefits to the society, especially in transportation, connected self-driving vehicles, healthcare, education, smart cities, and smart industries. The objective of this dissertation is to model and analyze the performance of large-scale heterogeneous two-tier IoT cellular networks, and offer design insights to maximize their performance. Using stochastic geometry, we develop realistic yet tractable models to study the performance of such networks. In particular, we propose solutions to the following research problems: -We propose a novel analytical model to estimate the mean uplink device data rate utility function under both spectrum allocation schemes, full spectrum reuse (FSR) and orthogonal spectrum partition (OSP), for uplink two-hop IoT networks. We develop constraint gradient ascent optimization algorithms to obtain the optimal aggregator association bias (for the FSR scheme) and the optimal joint spectrum partition ratio and optimal aggregator association bias (for the OSP scheme). -We study the performance of two-tier IoT cellular networks in which one tier operates in the traditional sub-6GHz spectrum and the other, in the millimeter wave (mm-wave) spectrum. In particular, we characterize the meta distributions of the downlink signal-to-interference ratio (sub-6GHz spectrum), the signal-to-noise ratio (mm-wave spectrum) and the data rate of a typical device in such a hybrid spectrum network. Finally, we characterize the meta distributions of the SIR/SNR and data rate of a typical device by substituting the cumulative moment of the CSP of a user device into the Gil-Pelaez inversion theorem. -We propose to split the control plane (C-plane) and user plane (U-plane) as a potential solution to harvest densification gain in heterogeneous two-tier networks while minimizing the handover rate and network control overhead. We develop a tractable mobility-aware model for a two-tier downlink cellular network with high density small cells and a C-plane/U-plane split architecture. The developed model is then used to quantify effect of mobility on the foreseen densification gain with and without C-plane/U-plane splitting

Taming and Leveraging Directionality and Blockage in Millimeter Wave Communications

To cope with the challenge for high-rate data transmission, Millimeter Wave(mmWave) is one potential solution. The short wavelength unlatched the era of directional mobile communication. The semi-optical communication requires revolutionary thinking. To assist the research and evaluate various algorithms, we build a motion-sensitive mmWave testbed with two degrees of freedom for environmental sensing and general wireless communication.The first part of this thesis contains two approaches to maintain the connection in mmWave mobile communication. The first one seeks to solve the beam tracking problem using motion sensor within the mobile device. A tracking algorithm is given and integrated into the tracking protocol. Detailed experiments and numerical simulations compared several compensation schemes with optical benchmark and demonstrated the efficiency of overhead reduction. The second strategy attempts to mitigate intermittent connections during roaming is multi-connectivity. Taking advantage of properties of rateless erasure code, a fountain code type multi-connectivity mechanism is proposed to increase the link reliability with simplified backhaul mechanism. The simulation demonstrates the efficiency and robustness of our system design with a multi-link channel record.The second topic in this thesis explores various techniques in blockage mitigation. A fast hear-beat like channel with heavy blockage loss is identified in the mmWave Unmanned Aerial Vehicle (UAV) communication experiment due to the propeller blockage. These blockage patterns are detected through Holm\u27s procedure as a problem of multi-time series edge detection. To reduce the blockage effect, an adaptive modulation and coding scheme is designed. The simulation results show that it could greatly improve the throughput given appropriately predicted patterns. The last but not the least, the blockage of directional communication also appears as a blessing because the geometrical information and blockage event of ancillary signal paths can be utilized to predict the blockage timing for the current transmission path. A geometrical model and prediction algorithm are derived to resolve the blockage time and initiate active handovers. An experiment provides solid proof of multi-paths properties and the numeral simulation demonstrates the efficiency of the proposed algorithm

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Optimization of Handover, Survivability, Multi-Connectivity and Secure Slicing in 5G Cellular Networks using Matrix Exponential Models and Machine Learning

Title from PDF of title page, viewed January 31, 2023Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 173-194)Dissertation (Ph.D.)--Department of Computer Science and Electrical Engineering. University of Missouri--Kansas City, 2022This works proposes optimization of cellular handovers, cellular network survivability modeling, multi-connectivity and secure network slicing using matrix exponentials and machine learning techniques. We propose matrix exponential (ME) modeling of handover arrivals with the potential to much more accurately characterize arrivals and prioritize resource allocation for handovers, especially handovers for emergency or public safety needs. With the use of a ‘B’ matrix for representing a handover arrival, we have a rich set of dimensions to model system handover behavior. We can study multiple parameters and the interactions between system events along with the user mobility, which would trigger a handoff in any given scenario. Additionally, unlike any traditional handover improvement scheme, we develop a ‘Deep-Mobility’ model by implementing a deep learning neural network (DLNN) to manage network mobility, utilizing in-network deep learning and prediction. We use the radio and the network key performance indicators (KPIs) to train our model to analyze network traffic and handover requirements. Cellular network design must incorporate disaster response, recovery and repair scenarios. Requirements for high reliability and low latency often fail to incorporate network survivability for mission critical and emergency services. Our Matrix Exponential (ME) model shows how survivable networks can be designed based on controlling numbers of crews, times taken for individual repair stages, and the balance between fast and slow repairs. Transient and the steady state representations of system repair models, namely, fast and slow repairs for networks consisting of multiple repair crews have been analyzed. Failures are exponentially modeled as per common practice, but ME distributions describe the more complex recovery processes. In some mission critical communications, the availability requirements may exceed five or even six nines (99.9999%). To meet such a critical requirement and minimize the impact of mobility during handover, a Fade Duration Outage Probability (FDOP) based multiple radio link connectivity handover method has been proposed. By applying such a method, a high degree of availability can be achieved by utilizing two or more uncorrelated links based on minimum FDOP values. Packet duplication (PD) via multi-connectivity is a method of compensating for lost packets on a wireless channel. Utilizing two or more uncorrelated links, a high degree of availability can be attained with this strategy. However, complete packet duplication is inefficient and frequently unnecessary. We provide a novel adaptive fractional packet duplication (A-FPD) mechanism for enabling and disabling packet duplication based on a variety of parameters. We have developed a ‘DeepSlice’ model by implementing Deep Learning (DL) Neural Network to manage network load efficiency and network availability, utilizing in-network deep learning and prediction. Our Neural Network based ‘Secure5G’ Network Slicing model will proactively detect and eliminate threats based on incoming connections before they infest the 5G core network elements. These will enable the network operators to sell network slicing as-a-service to serve diverse services efficiently over a single infrastructure with higher level of security and reliability.Introduction -- Matrix exponential and deep learning neural network modeling of cellular handovers -- Survivability modeling in cellular networks -- Multi connectivity based handover enhancement and adaptive fractional packet duplication in 5G cellular networks -- Deepslice and Secure5G: a deep learning framework towards an efficient, reliable and secure network slicing in 5G networks -- Conclusion and future scop

AI and IoT Meet Mobile Machines

Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)

AI and IoT Meet Mobile Machines: Towards a Smart Working Site

Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)

5G network slicing for rural connectivity: multi-tenancy in wireless networks

As the need for wireless broadband continues to grow around the world, there is an increasing focus to minimise the existing digital divide and ensuring that everyone receives high-quality internet services, especially the inhabitants of rural areas. As a result, different technological solutions are being studied and trialled for improving rural connectivity, such as 5G with dynamic spectrum access. One of the architectures of 5G is network slicing, which supports network virtualisation and consists of independent logical networks, called slices, on the 5G network. Network slicing supports the multi-tenancy of different operators on the same physical network, and this feature is known as neutral host networks (NHN). It allows multiple operators to co-exist on the same physical network but on different virtual networks to serve end users. Generally, the 5G NHN deployment is handled by an infrastructure provider (InP), who could be a mobile network operator (MNO), an Internet service provider, a third-party operator, etc. At the same time, potential tenants would lease slices from the InP. The NHN strategy would help reduce resource duplication and increase the utilisation of existing resources. The existing research into NHN for small cells, in-building connectivity solutions, and other deployment scenarios help to understand the technological and business requirements. End-to-end sharing across operators to provide services to their end users is another innovative application of 5G NHN that has been tested for dense areas. Meanwhile, the feasibility and policy impact of NHN is not studied extensively for the rural scenario. The research in this thesis examines the use of NHN in macro- and small-cell networks for 5G communication systems to minimise the digital divide, with a special focus on rural areas. The study also presents and analyses the 5G multi-tenancy system design for the rural wireless scenario, focusing mainly on exploring suitable business cases through network economics, techno-economic study, and game theory analysis. The results obtained from the study, such as cost analysis, business models, sensitivity analysis, and pricing strategies, help in formulating the policy on infrastructure sharing to improve rural connectivity. The contributions of the thesis are useful for stakeholders and policymakers to assess the suitability of the rural 5G NHN by exploring state-of-the-art technologies, techno-economic analysis, sensitivity analysis, newer business models, investment assessment, cost allocation, and risk sharing. Initially, the research gap is highlighted through the extensive literature review and stakeholders’ views on rural connectivity collected from discussions with them. First, the in-depth discussion on the network economics of the rural 5G NHN includes the study of potential future scenarios, value network configurations, spectrum access strategy models, and business models. Secondly, the techno-economic analysis studies the key performance indicators (KPI), cost analysis, return on investment, net present value, and sensitivity analysis, with the application for the rural parts of the UK and India. Finally, the game theory framework includes the study of strategic interaction among the two key stakeholders, InP and the MNO, using models such as investment games and pricing strategies during multi-tenancy. The research concludes by presenting the contribution towards the knowledge and future work.As the need for wireless broadband continues to grow around the world, there is an increasing focus to minimise the existing digital divide and ensuring that everyone receives high-quality internet services, especially the inhabitants of rural areas. As a result, different technological solutions are being studied and trialled for improving rural connectivity, such as 5G with dynamic spectrum access. One of the architectures of 5G is network slicing, which supports network virtualisation and consists of independent logical networks, called slices, on the 5G network. Network slicing supports the multi-tenancy of different operators on the same physical network, and this feature is known as neutral host networks (NHN). It allows multiple operators to co-exist on the same physical network but on different virtual networks to serve end users. Generally, the 5G NHN deployment is handled by an infrastructure provider (InP), who could be a mobile network operator (MNO), an Internet service provider, a third-party operator, etc. At the same time, potential tenants would lease slices from the InP. The NHN strategy would help reduce resource duplication and increase the utilisation of existing resources. The existing research into NHN for small cells, in-building connectivity solutions, and other deployment scenarios help to understand the technological and business requirements. End-to-end sharing across operators to provide services to their end users is another innovative application of 5G NHN that has been tested for dense areas. Meanwhile, the feasibility and policy impact of NHN is not studied extensively for the rural scenario. The research in this thesis examines the use of NHN in macro- and small-cell networks for 5G communication systems to minimise the digital divide, with a special focus on rural areas. The study also presents and analyses the 5G multi-tenancy system design for the rural wireless scenario, focusing mainly on exploring suitable business cases through network economics, techno-economic study, and game theory analysis. The results obtained from the study, such as cost analysis, business models, sensitivity analysis, and pricing strategies, help in formulating the policy on infrastructure sharing to improve rural connectivity. The contributions of the thesis are useful for stakeholders and policymakers to assess the suitability of the rural 5G NHN by exploring state-of-the-art technologies, techno-economic analysis, sensitivity analysis, newer business models, investment assessment, cost allocation, and risk sharing. Initially, the research gap is highlighted through the extensive literature review and stakeholders’ views on rural connectivity collected from discussions with them. First, the in-depth discussion on the network economics of the rural 5G NHN includes the study of potential future scenarios, value network configurations, spectrum access strategy models, and business models. Secondly, the techno-economic analysis studies the key performance indicators (KPI), cost analysis, return on investment, net present value, and sensitivity analysis, with the application for the rural parts of the UK and India. Finally, the game theory framework includes the study of strategic interaction among the two key stakeholders, InP and the MNO, using models such as investment games and pricing strategies during multi-tenancy. The research concludes by presenting the contribution towards the knowledge and future work

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods