Stochastic geometric analysis of energy efficiency in two-tier heterogeneous networks

The exponential growth in the number of users of cellular mobile networks (and their requirements) has created a massive challenge for network operators to cope with demands for coverage and data rates. Among the possible solutions for the ever increasing user needs, the deployment of Heterogeneous Networks (HetNets) constitutes both a practical and an economical solution. Moreover, while the typical approach for network operators has been to consider the coverage and data rates as design parameters in a network, a major concern for next generation networks is the efficiency in the power usage of the network. Therefore, in recent years the energy efficiency parameter has gathered a great deal of attention in the design of next generation networks. In the context of HetNets, while the densification of the network in terms of the number of base stations deployed can potentially increase the coverage and boost the data rates, it can also lead to a huge power consumption as the energy used escalates with the number of base stations deployed. To this end, the purpose of this thesis is to investigate the energy efficiency performance of different deployment strategies in a HetNet consisting of macro- and femtocells. We make use of well established tools from stochastic geometry to model the different strategies, as it provides a theoretical framework from which the scalability of the network in terms of the design parameters can be taken into account. Those strategies consisted first, on the analysis of the effect of using multiple antennas and diversity schemes on both, the throughput and the energy efficiency of the network. The optimum diversity schemes and antenna configurations were found for an optimal energy efficiency while keeping constraints on the quality of Service of both tiers. Then, the effect of the vertical antenna tilt was analyzed for both, a traditional macrocell only network and a two-tier network. The optimum antenna tilt in terms of energy efficiency was found while keeping constraints on the Quality of Service required. Finally, an energy efficient deployment of femtocells was proposed where the smart positioning of femtocells derived into improvements of coverage probability, effective throughput and energy efficiency of the network. The proposed model also improved in general the performance of the cell edge user which in turn resulted in a more balanced network in terms of the overall performance

Enhancing physical layer security in wireless networks with cooperative approaches

Motivated by recent developments in wireless communication, this thesis aims to characterize the secrecy performance in several types of typical wireless networks. Advanced techniques are designed and evaluated to enhance physical layer security in these networks with realistic assumptions, such as signal propagation loss, random node distribution and non-instantaneous channel state information (CSI). The first part of the thesis investigates secret communication through relay-assisted cognitive interference channel. The primary and secondary base stations (PBS and SBS) communicate with the primary and secondary receivers (PR and SR) respectively in the presence of multiple eavesdroppers. The SBS is allowed to transmit simultaneously with the PBS over the same spectrum instead of waiting for an idle channel. To improve security, cognitive relays transmit cooperative jamming (CJ) signals to create additional interferences in the direction of the eavesdroppers. Two CJ schemes are proposed to improve the secrecy rate of cognitive interference channels depending on the structure of cooperative relays. In the scheme where the multiple-antenna relay transmits weighted jamming signals, the combined approach of CJ and beamforming is investigated. In the scheme with multiple relays transmitting weighted jamming signals, the combined approach of CJ and relay selection is analyzed. Numerical results show that both these two schemes are effective in improving physical layer security of cognitive interference channel. In the second part, the focus is shifted to physical layer security in a random wireless network where both legitimate and eavesdropping nodes are randomly distributed. Three scenarios are analyzed to investigate the impact of various factors on security. In scenario one, the basic scheme is studied without a protected zone and interference. The probability distribution function (PDF) of channel gain with both fading and path loss has been derived and further applied to derive secrecy connectivity and ergodic secrecy capacity. In the second scenario, we studied using a protected zone surrounding the source node to enhance security where interference is absent. Both the cases that eavesdroppers are aware and unaware of the protected zone boundary are investigated. Based on the above scenarios, further deployment of the protected zones at legitimate receivers is designed to convert detrimental interference into a beneficial factor. Numerical results are investigated to check the reliability of the PDF for reciprocal of channel gain and to analyze the impact of protected zones on secrecy performance. In the third part, physical layer security in the downlink transmission of cellular network is studied. To model the repulsive property of the cellular network planning, we assume that the base stations (BSs) follow the Mat´ern hard-core point process (HCPP), while the eavesdroppers are deployed as an independent Poisson point process (PPP). The distribution function of the distances from a typical point to the nodes of the HCPP is derived. The noise-limited and interference-limited cellular networks are investigated by applying the fractional frequency reuse (FFR) in the system. For the noise-limited network, we derive the secrecy outage probability with two different strategies, i.e. the best BS serve and the nearest BS serve, by analyzing the statistics of channel gains. For the interference-limited network with the nearest BS serve, two transmission schemes are analyzed, i.e., transmission with and without the FFR. Numerical results reveal that both the schemes of transmitting with the best BS and the application of the FFR are beneficial for physical layer security in the downlink cellular networks, while the improvement du

Inter-Vehicle Communication at Intersections : An Evaluation of Ad-Hoc and Cellular Communication

This book evaluates the ability of ad-hoc and cellular communication to enable cross-traffic assistance at intersections. Potential issues like Non-Line-Of-Sight (NLOS) reception with ad-hoc and limited capacity, higher latency and costs with cellular technology are investigated in two individual evaluations. A method for efficient information delivery via cellular systems and an inter-vehicle NLOS radio propagation model are proposed. Finally, the suitability of both technologies is compared

NOVEL USER-CENTRIC ARCHITECTURES FOR FUTURE GENERATION CELLULAR NETWORKS: DESIGN, ANALYSIS AND PERFORMANCE OPTIMIZATION

Ambitious targets for aggregate throughput, energy efficiency (EE) and ubiquitous user experience are propelling the advent of ultra-dense networks. Inter-cell interference and high energy consumption in an ultra-dense network are the prime hindering factors in pursuit of these goals. To address this challenge, we investigate the idea of transforming network design from being base station-centric to user-centric. To this end, we develop mathematical framework and analyze multiple variants of the user-centric networks, with the help of advanced scientific tools such as stochastic geometry, game theory, optimization theory and deep neural networks. We first present a user-centric radio access network (RAN) design and then propose novel base station association mechanisms by forming virtual dedicated cells around users scheduled for downlink. The design question that arises is what should the ideal size of the dedicated regions around scheduled users be? To answer this question, we follow a stochastic geometry based approach to quantify the area spectral efficiency (ASE) and energy efficiency (EE) of a user-centric Cloud RAN architecture. Observing that the two efficiency metrics have conflicting optimal user-centric cell sizes, we propose a game theoretic self-organizing network (GT-SON) framework that can orchestrate the network between ASE and EE focused operational modes in real-time in response to changes in network conditions and the operator's revenue model, to achieve a Pareto optimal solution. The designed model is shown to outperform base-station centric design in terms of both ASE and EE in dense deployment scenarios. Taking this user-centric approach as a baseline, we improve the ASE and EE performance by introducing flexibility in the dimensions of the user-centric regions as a function of data requirement for each device. So instead of optimizing the network-wide ASE or EE, each user device competes for a user-centric region based on its data requirements. This competition is modeled via an evolutionary game and a Vickrey-Clarke-Groves auction. The data requirement based flexibility in the user-centric RAN architecture not only improves the ASE and EE, but also reduces the scheduling wait time per user. Offloading dense user hotspots to low range mmWave cells promises to meet the enhance mobile broadband requirement of 5G and beyond. To investigate how the three key enablers; i.e. user-centric virtual cell design, ultra-dense deployments and mmWave communication; are integrated in a multi-tier Stienen geometry based user-centric architecture. Taking into account the characteristics of mmWave propagation channel such as blockage and fading, we develop a statistical framework for deriving the coverage probability of an arbitrary user equipment scheduled within the proposed architecture. A key advantage observed through this architecture is significant reduction in the scheduling latency as compared to the baseline user-centric model. Furthermore, the interplay between certain system design parameters was found to orchestrate the ASE-EE tradeoff within the proposed network design. We extend this work by framing a stochastic optimization problem over the design parameters for a Pareto optimal ASE-EE tradeoff with random placements of mobile users, macro base stations and mmWave cells within the network. To solve this optimization problem, we follow a deep learning approach to estimate optimal design parameters in real-time complexity. Our results show that if the deep learning model is trained with sufficient data and tuned appropriately, it yields near-optimal performance while eliminating the issue of long processing times needed for system-wide optimization. The contributions of this dissertation have the potential to cause a paradigm shift from the reactive cell-centric network design to an agile user-centric design that enables real-time optimization capabilities, ubiquitous user experience, higher system capacity and improved network-wide energy efficiency

Advanced Technologies Enabling Unlicensed Spectrum Utilization in Cellular Networks

As the rapid progress and pleasant experience of Internet-based services, there is an increasing demand for high data rate in wireless communications systems. Unlicensed spectrum utilization in Long Term Evolution (LTE) networks is a promising technique to meet the massive traffic demand. There are two effective methods to use unlicensed bands for delivering LTE traffic. One is offloading LTE traffic toWi-Fi. An alternative method is LTE-unlicensed (LTE-U), which aims to directly use LTE protocols and infrastructures over the unlicensed spectrum. It has also been pointed out that addressing the above two methods simultaneously could further improve the system performance. However, how to avoid severe performance degradation of the Wi-Fi network is a challenging issue of utilizing unlicensed spectrum in LTE networks. Specifically, first, the inter-system spectrum sharing, or, more specifically, the coexistence of LTE andWi-Fi in the same unlicensed spectrum is the major challenge of implementing LTE-U. Second, to use the LTE and Wi-Fi integration approach, mobile operators have to manage two disparate networks in licensed and unlicensed spectrum. Third, optimization for joint data offloading to Wi-Fi and LTE-U in multi- cell scenarios poses more challenges because inter-cell interference must be addressed. This thesis focuses on solving problems related to these challenges. First, the effect of bursty traffic in an LTE and Wi-Fi aggregation (LWA)-enabled network has been investigated. To enhance resource efficiency, the Wi-Fi access point (AP) is designed to operate in both the native mode and the LWA mode simultaneously. Specifically, the LWA-modeWi-Fi AP cooperates with the LTE base station (BS) to transmit bearers to the LWA user, which aggregates packets from both LTE and Wi-Fi. The native-mode Wi-Fi AP transmits Wi-Fi packets to those native Wi-Fi users that are not with LWA capability. This thesis proposes a priority-based Wi-Fi transmission scheme with congestion control and studied the throughput of the native Wi-Fi network, as well as the LWA user delay when the native Wi-Fi user is under heavy traffic conditions. The results provide fundamental insights in the throughput and delay behavior of the considered network. Second, the above work has been extended to larger topologies. A stochastic geometry model has been used to model and analyze the performance of an MPTCP Proxy-based LWA network with intra-tier and cross-tier dependence. Under the considered network model and the activation conditions of LWA-mode Wi-Fi, this thesis has obtained three approximations for the density of active LWA-mode Wi-Fi APs through different approaches. Tractable analysis is provided for the downlink (DL) performance evaluation of large-scale LWA networks. The impact of different parameters on the network performance have been analyzed, validating the significant gain of using LWA in terms of boosted data rate and improved spectrum reuse. Third, this thesis also takes a significant step of analyzing joint multi-cell LTE-U and Wi-Fi network, while taking into account different LTE-U and Wi-Fi inter-working schemes. In particular, two technologies enabling data offloading from LTE to Wi-Fi are considered, including LWA and Wi-Fi offloading in the context of the power gain-based user offloading scheme. The LTE cells in this work are subject to load-coupling due to inter-cell interference. New system frameworks for maximizing the demand scaling factor for all users in both Wi-Fi and multi-cell LTE networks have been proposed. The potential of networks is explored in achieving optimal capacity with arbitrary topologies, accounting for both resource limits and inter-cell interference. Theoretical analyses have been proposed for the proposed optimization problems, resulting in algorithms that achieve global optimality. Numerical results show the algorithms’ effectiveness and benefits of joint use of data offloading and the direct use of LTE over the unlicensed band. All the derived results in this thesis have been validated by Monte Carlo simulations in Matlab, and the conclusions observed from the results can provide guidelines for the future unlicensed spectrum utilization in LTE networks

Analytical Performance Evaluation of Cooperative and Multi-Radio Concepts in Emerging Wireless Networks

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Research on Reliable Low-Power Wide-Area Communications Utilizing Multi-RAT LPWAN Technologies for IoT Applications

Předkládaná disertační práce je zaměřena na „Výzkum spolehlivé komunikace pro IoT aplikace v bezdrátových sítích využívajících technologie Multi-RAT LPWAN“. Navzdory značnému pokroku v oblasti vývoje LPWA technologií umožňující masivní komunikace mezi zařízeními (mMTC), nemusí tyto technologie výkonnostně dostačovat pro nově vznikající aplikace internetu věcí. Hlavním cílem této disertační práce je proto nalezení a vyhodnocení limitů současných LPWA technologií. Na základě těchto dat jsou nevrženy nové mechanismy umožňující snazší plánování a vyhodnocování síťového pokrytí. Navržené nástroje jsou vyladěny a validovány s využitím dat získaných z rozsáhlých měřících kampaních provedených v zákaznických LPWA sítích. Tato disertační práce dále obsahuje návrh LPWA zařízení vybavených více komunikačními rozhraními (multi-RAT) které mohou umožnit překonání výkonnostních limitů jednotlivých LPWA technologií. Současná implementace se zaměřuje zejména na snížení spotřeby zařízení s více rádiovými rozhraními, což je jejich největší nevýhodou. K tomuto účelu je využito algoritmů strojového učení, které jsou schopné dynamicky vybírat nejvhodnější rozhraní k přenosu.This doctoral thesis addresses the “Research on Reliable Low-Power Wide-Area Communications Utilizing Multi-RAT LPWAN Technologies for IoT Applications”. Despite the immense progress in massive Machine-Type Communication (mMTC) technology enablers such as Low-Power Wide-Area (LPWA) networks, their performance does not have to satisfy the requirements of novelty Internet of Things (IoT) applications. The main goal of this Ph.D. work is to explore and evaluate the limitations of current LPWA technologies and propose novel mechanisms facilitating coverage planning and assessment. Proposed frameworks are fine-tuned and cross-validated by the extensive measurement campaigns conducted in public LPWA networks. This doctoral thesis further introduces the novelty approach of multi-RAT LPWA devices to overcome the performance limitation of individual LPWA technologies. The current implementation primarily focuses on diminishing the greatest multi-RAT solutions disadvantage, i.e., increased power consumption by employing a machine learning approach to radio interface selection.

Network Management and Decision Making for 5G Heterogeneous Networks

Heterogeneous networks (HetNets) will form an integral part of future cellular communications. With the proper management of network resources and decisions, the coexistence of small cells with macro base stations will improve coverage, data rate and quality of service for users. This thesis investigates critical issues that will arise in HetNets. The first half of this thesis studies major consequences of the disparity between HetNet tier transmit powers, namely that of interference and load balancing. To reduce the effects of harmful interference to small cell users arising from powerful macro transmissions, we first design a precoding matrix in the form of a generalized inverse, which, unlike conventional precoding methods, allows the base station to target a user specifically to reduce its own interference to that user. Even with a transmit power constraint, the affected user can achieve significant improvement in its interference reduction at the slightly compromise of existing macro users. Next, we study load balancing by showing the benefits of a dynamic biasing function for cell range expansion over a static bias value. Our findings indicate that a dynamic bias is a more intuitive way to prevent small cell overloading, and that associating closest users first is a preferred association order. We conclude our study into load balancing by proposing a new notion of network balance. We describe how network balance is different to user fairness, and subsequently define a new metric called the network balance index which measures the deviation of the actual base station load distribution with the expected load distribution. We show using an algorithm that the network balance index is more useful than fairness in improving sum rate for clustered networks. The second half of this thesis explores more advanced user-centric issues for HetNets. Chapter 5 proposes a user association scheme that achieves high fairness, and considers user association behaviour with network dynamics. In order to reduce the computation needed to re-associate a large network, we study the probabilities that each user will have to switch associations when a user or base station enters or leaves. In the process, we find that a shrinking network has more effect on user association than a growing one. Finally, Chapter 6 extends the conventional idea of HetNets to include device-to-device (D2D) communications. We propose a D2D decision making framework that more suitably selects D2D modes for potential D2D pairs by using a two-stage criteria that leads to fewer incorrect D2D mode selections. Once a suitable D2D mode is selected, we demonstrate how to determine optimal or near-optimal power and resource parameters for each mode in order to maximize sum rate. We present a geometric approach to solving the co-channel power control problem, and closed form expressions where possible for orthogonal frequency allocation. Our comprehensive study validates the potential for D2D integration in future cellular communications. The proposed techniques and insights gained from this thesis aims to illustrate how networks can be better managed and improve their decision making processes in order to successfully serve future users

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