Korkean luotettavuuden verkkohallinteiset laitteiden väliset yhteydet

Fifth generation cellular networks aim to provide new types of services. Prominent amongst these are industrial automation and vehicle-to-vehicle communications. Such new use cases demand lower latencies and higher reliability along with greater flexibility than current and past generations of cellular technologies allow. Enabling these new service types requires the introduction of device-to-device communications (D2D). This work investigated network-controlled D2D schemes wherein cellular base stations retain control over spectrum usage. D2D nodes assemble into clusters. Each D2D cluster then organises itself as it sees fit within the constraints imposed by the cellular network. A review of proposed D2D control schemes was conducted to identify pertinent interference issues. Measurements were then devised to empirically collect quantitative data on the impact of this interference. Measurements were conducted using a software-defined radio (SDR) platform. An SDR based system was selected to enable a low cost and highly flexible iterative approach to development while still providing the accuracy of real-world measurement. D2D functionality was added to the chosen SDR system with the essential parts of Long Term Evolution Release 8 implemented. Two series of measurements were performed. The first aimed to determine the adjacent channel interference impact of a cellular user being located near a D2D receiver. The second measurement series collected data on the co-channel interference of spectrum re-use between a D2D link and a moving cellular transmitter. Based on these measurements it was determined that D2D communications within a cellular system is feasible. Furthermore, the required frequency of channel state information reporting as a function of node velocity was determined.Viidennen sukupolven solukkoverkoilla pyritään mahdollistamaan uudentyyppisiä palveluja kuten teollisuusautomatiikkaa ja ajoneuvojen välistä viestintää. Tämänkaltaiset uudet käyttötarkoitukset vaativat lyhyempien viiveiden ja korkeammat luotettavuuden ohella myös suurempaa joustavuutta kuin minkä nykyisen sukupolven matkapuhelinverkkoteknologiat sallivat. Edellä mainittujen uusien palvelujen toteuttaminen vaatii suoria laitteiden välisiä yhteyksiä (engl. D2D). Tässä diplomityössä keskityttiin tutkimaan verkkohallinteisia D2D-rakenteita, joissa solukkoverkko hallinnoi spektrin käyttöä. D2D-päätteet liittyvät yhteen muodostaakseen klustereita, jotka hallinnoivat sisäistä tietoliikennettään parhaaksi katsomallaan tavalla solukkoverkon asettamien rajoitusten puitteissa. Kirjallisuuskatsauksen avulla selvitettiin aiemmissa tutkimuksissa esitetyille D2D-ratkaisuille yhteiset interferenssiongelmat. Näiden vaikutusta ja suuruutta tutkittiin mittausten avulla. Mittaukset toteutettiin ohjelmistoradioalustan (engl. SDR) avulla. SDR-pohjaisen järjestelmän käyttö mahdollisti edullisen ja joustavan tavan kerätä empiirisiä mittaustuloksia. D2D-toiminnallisuus lisättiin Long Term Evolution Release 8:n olennaiset ominaisuudet omaavaan alustaan. Tällä alustalla toteutettiin kaksi mittaussarjaa. Ensimmäisellä kerättiin tuloksia viereisellä kanavalla toimivan matkapuhelimen D2D-vastaanottimelle aiheuttamasta interferenssistä näiden ollessa toistensa läheisyydessä. Toisella mittaussarjalla selvitettiin samalla kanavalla toimivan D2D-yhteyden ja liikkuvan matkapuhelimen välistä interferenssiä. Mittausten perusteella todettiin D2D-toiminnallisuuden lisäämisen solukkoverkkoon olevan mahdollista. Lisäksi laskettiin vaadittava kanavalaadun päivitystiheys päätteiden nopeuden funktiona

Stochastic Geometry for Modeling, Analysis and Design of Future Wireless Networks

This thesis focuses on the modeling, analysis and design of future wireless networks with smart devices, i.e., devices with intelligence and ability to communicate with one another with/without the control of base stations (BSs). Using stochastic geometry, we develop realistic yet tractable frameworks to model and analyze the performance of such networks, while incorporating the intelligence features of smart devices. In the first half of the thesis, we develop stochastic geometry tools to study arbitrarily shaped network regions. Current techniques in the literature assume the network regions to be infinite, while practical network regions tend to be arbitrary. Two well-known networks are considered, where devices have the ability to: (i) communicate with others without the control of BSs (i.e., ad-hoc networks), and (ii) opportunistically access spectrum (i.e., cognitive networks). First, we propose a general algorithm to derive the distribution of the distance between the reference node and a random node inside an arbitrarily shaped ad-hoc network region, which helps to compute the outage probability. We then study the impact of boundary effects and show that the outage probability in infinite regions may not be a meaningful bound for arbitrarily shaped regions. By extending the developed techniques, we further analyze the performance of underlay cognitive networks, where different secondary users (SUs) activity protocols are employed to limit the interference at a primary user. Leveraging the information exchange among SUs, we propose a cooperation-based protocol. We show that, in the short-term sensing scenario, this protocol improves the network's performance compared to the existing threshold-based protocol. In the second half of the thesis, we study two recently emerged networks, where devices have the ability to: (i) communicate directly with nearby devices under the control of BSs (i.e., device-to-device (D2D) communication), and (ii) harvest radio frequency energy (i.e., energy harvesting networks). We first analyze the intra-cell interference in a finite cellular region underlaid with D2D communication, by incorporating a mode selection scheme to reduce the interference. We derive the outage probability at the BS and a D2D receiver, and propose a spectrum reuse ratio metric to assess the overall D2D communication performance. We demonstrate that, without impairing the performance at the BS, if the path-loss exponent on cellular link is slightly lower than that on D2D link, the spectrum reuse ratio can have negligible decrease while the average number of successful D2D transmissions increases with the increasing D2D node density. This indicates that an increasing level of D2D communication is beneficial in future networks. Then we study an ad-hoc network with simultaneous wireless information and power transfer in an infinite region, where transmitters are wirelessly charged by power beacons. We formulate the total outage probability in terms of the power and channel outage probabilities. The former incorporates a power activation threshold at transmitters, which is a key practical factor that has been largely ignored in previous work. We show that, although increasing power beacon's density or transmit power is not always beneficial for channel outage probability, it improves the overall network performance

A Survey on Security and Privacy of 5G Technologies: Potential Solutions, Recent Advancements, and Future Directions

Security has become the primary concern in many telecommunications industries today as risks can have high consequences. Especially, as the core and enable technologies will be associated with 5G network, the confidential information will move at all layers in future wireless systems. Several incidents revealed that the hazard encountered by an infected wireless network, not only affects the security and privacy concerns, but also impedes the complex dynamics of the communications ecosystem. Consequently, the complexity and strength of security attacks have increased in the recent past making the detection or prevention of sabotage a global challenge. From the security and privacy perspectives, this paper presents a comprehensive detail on the core and enabling technologies, which are used to build the 5G security model; network softwarization security, PHY (Physical) layer security and 5G privacy concerns, among others. Additionally, the paper includes discussion on security monitoring and management of 5G networks. This paper also evaluates the related security measures and standards of core 5G technologies by resorting to different standardization bodies and provide a brief overview of 5G standardization security forces. Furthermore, the key projects of international significance, in line with the security concerns of 5G and beyond are also presented. Finally, a future directions and open challenges section has included to encourage future research.European CommissionNational Research Tomsk Polytechnic UniversityUpdate citation details during checkdate report - A

Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

Performance Evaluation of Ultra-Dense Networks with Applications in Internet-of-Things

The new wireless era in the next decade and beyond would be very different from our experience nowadays. The fast pace of introducing new technologies, services, and applications requires the researchers and practitioners in the field be ready by making paradigm shifts. The stringent requirements on 5G networks, in terms of throughput, latency, and connectivity, challenge traditional incremental improvement in the network performance. This urges the development of unconventional solutions such as network densification, massive multiple-input multiple-output (massive MIMO), cloud-based radio access network (C-RAN), millimeter Waves (mmWaves), non-orthogonal multiple access (NOMA), full-duplex communication, wireless network virtualization, and proactive content-caching to name a few. Ultra-Dense Network (UDN) is one of the preeminent technologies in the racetrack towards fulfilling the requirements of next generation mobile networks. Dense networks are featured by the deployment of abundant of small cells in hotspots where immense traffic is generated. In this context, the density of small cells surpasses the active users’ density providing a new wireless environment that has never been experienced in mobile communication networks. The high density of small cells brings the serving cells much closer to the end users providing a two-fold gain where better link quality is achieved and more spatial reuse is accomplished. In this thesis, we identified the distinguishing features of dense networks which include: close proximity of many cells to a given user, potential inactivity of most base stations (BSs) due to lack of users, drastic inter-cell interference in hot-spots, capacity limitation by virtue of the backhaul bottleneck, and fundamentally different propagation environments. With these features in mind, we recognized several problems associated with the performance evaluation of UDN which require a treatment different from traditional cellular networks. Using rigorous advanced mathematical techniques along with extensive Monte Carlo simulations, we modelled and analytically studied the problems in question. Consequently, we developed several mathematical frameworks providing closed-form and easy-computable mathematical instruments which network designers and operators can use to tune the networks in order to achieve the optimal performance. Moreover, the investigations performed in this thesis furnish a solid ground for addressing more problems to better understand and exploit the UDN technology for higher performance grades. In Chapter 3, we propose the multiple association in dense network environment where the BSs are equipped with idle mode capabilities. This provides the user with a “data-shower,” where the user’s traffic is split into multiple paths, which helps overcoming the capacity limitations imposed by the backhaul links. We evaluate the performance of the proposed association scheme considering general fading channel distributions. To this end, we develop a tractable framework for the computation of the average downlink rate. In Chapter 4, we study the downlink performance of UDNs considering Stretched Exponential Path-Loss (SEPL) to capture the short distances of the communication links. Considering the idle mode probability of small cells, we draw conclusions which better reflect the performance of network densification considering SEPL model. Our findings reveal that the idle mode capabilities of the BSs provide a very useful interference mitigation technique. Another interesting insight is that the system interference in idle mode capable UDNs is upper-bounded by the interference generated from the active BSs, and in turn, this is upper-bounded by the number of active users where more active users is translated to more interference in the system. This means that the interference becomes independent of the density of the small cells as this density increases. In Chapter 5, we provide the derivation of the average secrecy rate in UDNs considering their distinct traits, namely, idle mode BSs and LOS transmission. To this end, we exploit the standard moment generating function (MGF)-based approach to derive relatively simple and easily computable expressions for the average secrecy rate considering the idle mode probability and Rician fading channel. The result of this investigation avoids the system level simulations where the performance evaluation complexity can be greatly reduced with the aid of the derived analytical expressions. In Chapter 6, we model the uplink coverage of mMTC deployment scenario considering a UDN environment. The presented analysis reveals the significant and unexpected impact of the high density of small cells in UDNs on the maximum transmit power of the MTC nodes. This finding relaxes the requirements on the maximum transmit power which in turn allows for less complexity, brings more cost savings, and yields much longer battery life. This investigation provides accurate, simple, and insightful expressions which shows the impact of every single system parameter on the network performance allowing for guided tunability of the network. Moreover, the results signify the asymptotic limits of the impact of all system parameters on the network performance. This allows for the efficient operation of the network by designing the system parameters which maximizes the network performance. In Chapter 7, we address the impact of the coexistence of MTC and HTC communications on the network performance in UDNs. In this investigation, we study the downlink network performance in terms of the coverage probability and the cell load where we propose two association schemes for the MTC devices, namely, Connect-to-Closest (C2C) and Connect-to-Active (C2A). The network performance is then analyzed and compared in both association schemes. In Chapter 8, we model the uplink coverage of HTC users and MTC devices paired together in NOMA-based radio access. Closed-form and easy-computable analytical results are derived for the considered performance metrics, namely the uplink coverage and the uplink network throughput. The analytical results, which are validated by extensive Monte Carlo simulations, reveal that increasing the density of small cells and the available bandwidth significantly improves the network performance. On the other side, the power control parameters has to be tuned carefully to approach the optimal performance of both the uplink coverage and the uplink network throughput

Performance Analysis and Learning Algorithms in Advanced Wireless Networks

Over the past decade, wireless data traffic has experienced an exponential growth, especially with multimedia traffic becoming the dominant traffic, and such growth is expected to continue in the near future. This unprecedented growth has led to an increasing demand for high-rate wireless communications.Key solutions for addressing such demand include extreme network densification with more small-cells, the utilization of high frequency bands, such as the millimeter wave (mmWave) bands and terahertz (THz) bands, where more bandwidth is available, and unmanned aerial vehicle (UAV)-enabled cellular networks. With this motivation, different types of advanced wireless networks are considered in this thesis. In particular, mmWave cellular networks, networks with hybrid THz, mmWave and microwave transmissions, and UAV-enabled networks are studied, and performance metrics such as the signal-to-interference-plus-noise ratio (SINR) coverage, energy coverage, and area spectral efficiency are analyzed. In addition, UAV path planning in cellular networks are investigated, and deep reinforcement learning (DRL) based algorithms are proposed to find collision-free UAV trajectory to accomplish different missions. In the first part of this thesis, mmWave cellular networks are considered. First, K-tier heterogeneous mmWave cellular networks with user-centric small-cell deployments are studied. Particularly, a heterogeneous network model with user equipments (UEs) being distributed according to Poisson cluster processes (PCPs) is considered. Distinguishing features of mmWave communications including directional beamforming and a detailed path loss model are taken into account. General expressions for the association probabilities of different tier base stations (BSs) are determined. Using tools from stochastic geometry, the Laplace transform of the interference is characterized and general expressions for the SINR coverage probability and area spectral efficiency are derived. Second, a distributed multi-agent learning-based algorithm for beamforming in mmWave multiple input multiple output (MIMO) networks is proposed to maximize the sum-rate of all UEs. Following the analysis of mmWave cellular networks, a three-tier heterogeneous network is considered, where access points (APs), small-cell BSs (SBSs) and macrocell BSs (MBSs) transmit in THz, mmWave, microwave frequency bands, respectively. By using tools from stochastic geometry, the complementary cumulative distribution function (CCDF) of the received signal power, the Laplace transform of the aggregate interference, and the SINR coverage probability are determined. Next, system-level performance of UAV-enabled cellular networks is studied. More specifically, in the first part, UAV-assisted mmWave cellular networks are addressed, in which the UE locations are modeled using PCPs. In the downlink phase, simultaneous wireless information and power transfer (SWIPT) technique is considered. The association probability, energy coverages and a successful transmission probability to jointly determine the energy and SINR coverages are derived. In the uplink phase, a scenario that each UAV receives information from its own cluster member UEs is taken into account. The Laplace transform of the interference components and the uplink SINR coverage are characterized. In the second part, cellular-connected UAV networks is investigated, in which the UAVs are aerial UEs served by the ground base stations (GBSs). 3D antenna radiation combing the vertical and horizontal patterns is taken into account. In the final part of this thesis, deep reinforcement learning based algorithms are proposed for UAV path planning in cellular networks. Particularly, in the first part, multi-UAV non-cooperative scenarios is considered, where multiple UAVs need to fly from initial locations to destinations, while satisfying collision avoidance, wireless connectivity and kinematic constraints. The goal is to find trajectories for the cellular-connected UAVs to minimize their mission completion time. The multi-UAV trajectory optimization problem is formulated as a sequential decision making problem, and a decentralized DRL approach is proposed to solve the problem. Moreover, multiple UAV trajectory design in cellular networks with a dynamic jammer is studied, and a learning-based algorithm is proposed. Subsequently, a UAV trajectory optimization problem is considered to maximize the collected data from multiple Internet of things (IoT) nodes under realistic constraints. The problem is translated into a Markov decision process (MDP) and dueling double deep Q-network (D3QN) is proposed to learn the decision making policy