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

Unmanned aerial vehicles (UAVs) for wireless communication and networks : potentials and design challenges

Unmanned aerial vehicles (UAVs) are mostly considered by the military for surveillance and reconnaissance operations, and by hobbyists for aerial photography. However, in recent years, the UAV operations have been extended for civilian and commercial purposes due to their agile and cost-effective deployment. UAVs appear to be more prolific platforms to enable wireless communication due to their better line-of-sight (LOS) channel conditions as compared with the fixed base stations (BSs) in terrestrial communication which suffer from severe path loss, shadowing, and multipath fading in more challenging propagation environments. In UAV-enabled wireless communications, the UAV can either act as a complementary aerial BS to provide on-demand communication or as an aerial user equipment (UE) which is operated by the existing cellular network. Several challenges exist in the design of UAV communications which include but not limited to channel modeling, optimal deployment, interference generation, performance analysis, limited on-board battery lifetime, trajectory optimization, and unavailability of regulations and standards which are specific for UAV communication and networking. This thesis particularly investigates some important design challenges for safe and reliable functionalities of UAV for wireless communication and networking. UAV communication has its own distinctive channel characteristics compared to the widely used cellular or satellite systems. However, several challenges exist in UAV channel modeling. For example, the propagation characteristics of UAV channels are under explored for spatial and temporal variations in non-stationary channels. Therefore, first and foremost, this thesis provides an extensive review of the measurement methods proposed for UAV channel modeling and discusses channel modeling efforts for air-to-ground and air-to-air channels. Furthermore, knowledge-gaps are identified to realize accurate UAV channel models. The efficient deployment strategy is imperative to compensate the adverse impact of interference on the coverage area performance of multiple UAVs. As a result, this thesis proposes an optimal deployment strategy for multiple UAVs in presence of downlink co-channel interference in the worst-case scenario. In particular, this work presents coordinated multi-UAV strategy in two schemes. In the first scheme, symmetric placement of UAVs is assumed at a common optimal altitude and transmit power. In the second scheme, asymmetric deployment of UAVs with different altitudes and transmit powers is assumed. The impact of various system parameters, such as signal-to interference-plus-noise ratio (SINR) threshold, separation distance between UAVs, and the number of UAVs and their formations are carefully studied to achieve the maximum coverage area inside and to reduce the unnecessary coverage expansion outside the target area. Fundamental analysis is required to obtain the optimal trade-off between the design parameters and performance metrics of any communication systems. This thesis particularly considers two emerging scenarios for evaluating performance of UAV communication systems. In the first scenario, the uplink UAV communication system is considered where the ground user follows the random waypoint (RWP) model for user mobility, the small-scale channel fading follows the Nakagami-m model, and the uplink interference is modeled by Gamma approximation. Specifically, the closed-form expressions for the probability density function (PDF), the cumulative distribution function (CDF), the outage probability, and the average bit error rate (BER) of the considered UAV system are derived as performance metrics. In the second scenario, the downlink hybrid caching system is considered where UAVs and ground small-cell BSs (SBSs) are distributed according to two independent homogeneous Poisson point processes (PPPs), and downlink interference is modeled by the Laplace transforms. Specifically, the analytical expressions of the successful content delivery probability and energy efficiency of the considered network are derived as performance metrics. In both scenarios, results are presented to demonstrate the interplay between the communication performance and the design parameters

Integrating Drones and Wireless Power Transfer into Beyond 5G Networks

As fifth generation (5G) standards have been established and 5G commercial products are just around the corner, both academia and industry have started to look at requirements for beyond 5G networks. Network flexibility and long battery life are among the key requirements for beyond 5G wireless communication systems. These critical requirements, which have not been sufficiently addressed in the previous generations, are the focus of this thesis. The first half of this thesis explores two important use cases of drones to provide flexible communication networks. First, the performance of a cellular network with underlay drone cell for temporary events inside a stadium is studied. Using stochastic geometry, a general analytical framework is proposed to analyze the uplink and the downlink coverage probabilities for both the aerial and the terrestrial systems. Our results show that for urban environment and dense urban environment, the drone is best deployed at a low height (e.g., 200 m or lower), regardless of the distance between the center of the stadium and the terrestrial base station. However, for suburban environment and high-rise urban environment, the best drone altitude varies. Second, the performance of emergency information dissemination in public safety scenarios using drone is studied. A drone-assisted multihop multicast device-to-device (D2D) network is considered, where an emergency alert message broadcasted by a drone at the first time slot is multicasted by the D2D users that have successfully received the message through multihop. The impact of different system parameters on the link and the network performance is investigated. Our results demonstrate that a higher drone altitude provides better link and network coverage probabilities and lower mean local delay. Under practical setups, the cell edge user located 2 km from the ground projection of the drone has a link coverage probability around 90% after 5 time slots and a mean local delay of 2.32 time slots with a drone height as low as 200 m. The second half of this thesis investigates wireless power transfer networks. Specifically, the use of power beacons in a millimeter wave wireless ad hoc network is considered, where transmitters adopt the harvest-then-transmit protocol. First, the characteristic of the aggregate received power from power beacons is analyzed and the lognormal distribution is found to provide the best complementary cumulative distribution function approximation compared to other distributions considered in the literature. Then, a tractable model with discrete transmit power for each transmitter is proposed to compute the channel coverage probability and the total coverage probability. Our results show that our model provides a good accuracy and reveal the impact of different system parameters on the total coverage probability. Our results also illustrate that under practical setups, for power beacon transmit power of 50 dBm and transmitters with maximum transmit power between 20 - 40 dBm, which are safe for human exposure, the total coverage probability is around 90%. Thus, it is feasible and safe to power transmitters in a millimeter wave ad hoc network using power beacons

Efficient resource allocation for 5G hybrid wireless networks

This thesis explores three directions of energy-efficiency(EE) and spectral efficiency(SE) under 5G wireless networks. Firstly, we study the optimization of power control for the small (two-user) interference channel in which the terminals are time-switched between the signal-processing and energy-harvesting phases. Both energy harvesting and signal-processing processes are during the downlink. The objective is to maximize the sum-rate, subject to the minimum data and harvested energy constraints at the receivers, assuming a fixed time-switching coefficient. The key contribution is using a geometric approach that analyzes the feasible region governed by the constraints, which gives rise to the optimal power control solution. Another topic focuses on the performance analysis of two user association schemes for wireless power transfer (WPT) in heterogeneous networks (HetNets) massive multiple-input multiple-output (MIMO) antennas, downlink for the WPT in the first phase and uplink for wireless information transfer (WIT) in the second phase. The two user association schemes considered in the analysis are the Downlink received signal power (DRSP) based approach for maximizing the harvested energy; and the uplink received signal power (URSP) based approach for minimizing the uplink path loss. In the downlink, we adopt a low-complexity approach for massive MIMO power transfer to recharge users. Then we derive the average uplink achievable rate with the harvested energy. The last topic analyses a large-scale mmWave ad hoc network in the randomly located eavesdroppers area, where eavesdroppers can still intercept the confidential messages, since they may reside in the signal beam. This chapter explores the potential of physical layer security in mmWave ad hoc networks. Specifically, we characterize the impact of mmWave channel characteristics, random blockages, and antenna gains on the secrecy performance. For the special case of the uniform linear array (ULA), a tractable approach is proposed to evaluate the average achievable secrecy rate

New Approaches Using Cognitive Radio in Green Networking

The green networks are energy-efficient network architectures and we consider them as the basis of the wireless communication optimizing energy usage. Indeed, future communication technologies are moving in this direction, meaning that they will be less energy-intensive and, in some cases, even energy self-sufficient. Specifically, cognitive radio (CR) networks, cooperative relay networks, and non-orthogonal multiple access (NOMA) techniques have been considered as effective means to facilitate energy harvesting (EH) and a power spectrum allocation for the minimization of total transmit power, hence, making the wireless communication greener. The dissertation consists of three research sections corresponding to the aims. The first aim deals with an radio frequency (RF) wireless energy transfer model for D2D systems. In order to harvest more energy, a multiple-antenna base station and a power beacon are adopted for the D2D transmission network. We derive expressions outage probability in closed-forms. Further, independent simulations are used to validate the exactness of the theoretical expressions. In the second aim, new cooperative system models are proposed and studied. To reach the second aim, the secondary source acts as a relay and employs Amplify and Forward (AF) mode to serve distant NOMA users under a given interference constraint. To provide a detailed examination of the system performance metrics, we derived closed-form formulas for the outage probability and average throughput of the multi-users in the presence of interference constraints. In the last aim of the dissertation, we designed a new system model for a hybrid satellite-terrestrial cognitive network (HSTCN) relying on NOMA interconnecting a satellite and multiple terrestrial nodes. Reliability and security of transmission were studied to minimize the total transmit power. To reach the third aim, we examined the following performance factors: outage probability, hardware impairment, intercept probability, and average throughput. The novel closed-forms expressions of these performance factors are derived. The last but not at least, we simulated the new HSTCN system model. The achieved results figured that the new proposed approaches make it possible to take into account service quality requirements and are applicable in future green networking.Zelené sítě jsou energeticky efektivní síťové architektury a považujeme je za základ bezdrátové komunikace optimalizující spotřebu energie. Tímto směrem se ubírají budoucí komunikační technologie, což znamená, že budou méně energeticky náročné a v některých případech dokonce energeticky soběstačné. Kognitivní rádiové (CR) sítě, kooperativní relay sítě a neortogonální vícenásobné přístupové (NOMA) techniky jsou považovány za účinný prostředek k usnadnění získávání energie (EH) a přidělování výkonového spektra pro minimalizaci celkového vysílacího výkonu, díky čemuž je bezdrátová komunikace zelenější. Disertační práce se skládá ze tří výzkumných částí odpovídajících cílům. První cíl se zabývá modelem bezdrátového přenosu radiofrekvenční (RF) energie pro systémy D2D. Aby bylo možné získat více energie, jsou pro přenosovou D2D síť použity základnové stanice s více anténami a napájecím radiomajákem. Pro navržený model jsou odvozeny pravděpodobnosti výpadků, kdy tyto výrazy jsou v uzavřené formě. Dále jsou k ověření platnosti získaných teoretických výrazů použity nezávislé simulace. Ve druhém cíli jsou navrženy a zkoumány nové modely kooperativního systému. Aby bylo dosaženo druhého cíle, sekundární zdroj funguje jako relay uzel a využívá režim AF (Amplify and Forward), který slouží vzdáleným NOMA uživatelům za specifických interferenčních podmínek. Abychom poskytli podrobné zhodnocení výkonnostních metrik systému, odvodili jsme vztahy v uzavřené formě pro pravděpodobnost výpadků a průměrnou propustnost více uživatelů za přítomnosti interferenčních omezení. V posledním cíli disertační práce jsme navrhli nový systémový model pro hybridní satelitně-terestrickou kognitivní síť (HSTCN) založenou na neortogonálním vícenásobném přístupu (NOMA) propojující satelit a více terestrických uzlů. Zkoumána byla spolehlivost a zabezpečení přenosu s důrazem na minimalizaci celkového vysílacího výkonu. Pro dosažení třetího cíle jsme zkoumali následující výkonnostní faktory: pravděpodobnost výpadku, poškození hardwaru, pravděpodobnost zachycení a průměrnou propustnost. Pro tyto výkonnostní faktory jsou odvozeny v uzavřených formách nové výrazy. V neposlední řadě jsme rovněž simulovali nový systémový HSTCN model. Dosažené výsledky potvrdily, že nově navržené přístupy umožňují zohledňovat požadavky na kvalitu služeb a jsou použitelné v budoucích zelených sítích.440 - Katedra telekomunikační technikyvyhově

Mathematical Modelling and Analysis of Spatially Correlated Heterogeneous and Vehicular Networks - A Stochastic Geometry Approach

Heterogeneous Cellular Networks (HCNs) and vehicular communications are two key ingredients of future 5G communication networks, which aim at providing high data rates on the one former case and high reliability on the latter one. Nevertheless, in these two scenarios, interference is the main limiting factor, which makes achieving the required performance, i.e., data rate or reliability, a challenging task. Hence, in order to cope with such issue, concepts like uplink/downlink (UL/DL) decoupling, Interference-Aware (IA) strategies or cooperative communications with Cloud Radio Access Networks (CRANs) has been introduced for new releases of 4G and future 5G networks. Additionally, for the sake of increasing the data rates, new multiple access schemes like Non-Orthogonal Multiple Access (NOMA) has been proposed for 5G networks. All these techniques and concepts require accurate and tractable mathematical modelling for performance analysis. This analysis allows us to obtain theoretical insights about key performance indicators leading to a deep understanding about the considered techniques. Due to the random and irregular nature that exhibits HCNs, as well as vehicular networks, stochastic geometry has appeared recently as a promising tool for system-level modelling and analysis. Nevertheless, some features of HCNs and vehicular networks, like power control, scheduling or frequency planning, impose spatial correlations over the underlying point process that complicates significantly the mathematical analysis. In this thesis, it has been used stochastic geometry and point process theories to investigate the performance of these aforementioned techniques. Firstly, it is derived a mathematical framework for the analysis of an Interference-Aware Fractional Power Control (IAFPC) for interference mitigation in the UL of HCNs. The analysis reveals that IAFPC outperforms the classical FPC in terms of Spectral Efficiency (SE), average transmitted power, and mean and variance of the interference. Then, it is investigated the performance of a scheduling algorithm where the Mobile Terminals (MTs) may be turned off if they cause a level of interference greater than a given threshold. Secondly, a multi-user UL model to assess the coverage probability of different MTs in each cell is proposed. Then, the coverage probability of cellular systems under Hoyt fading (Nakagami-q) is studied. This fading model, allows us to consider more severe fading conditions than Rayleigh, which is normally the considered fading model for the sake of tractability. Thirdly, a novel NOMA-based scheme for CRANs is proposed, modelled and analyzed. In this scheme, two users are scheduled in the same resources according to NOMA; however the performance of cell-edge users is enhanced by means of coordinated beamforming. Finally, the performance of a decentralized Medium Access Control (MAC) algorithm for vehicular communications is investigated. With this strategy, the cellular network provides frequency and time synchronization for direct Vehicle to Vehicle (V2V) communication, which is based on its geographical information. The analysis demonstrates that there exists an operation regime where the performance is noise-limited. Then, the optimal transmit power that maximizes the Energy Efficiency (EE) of the system subject to a minimum capture probability constraint is derived

Power Beacon-Assisted Millimeter Wave Ad Hoc Networks

Deployment of low cost power beacons (PBs) is a promising solution for dedicated wireless power transfer (WPT) in future wireless networks. In this paper, we present a tractable model for PB-assisted millimeter wave (mmWave) wireless ad hoc networks, where each transmitter (TX) harvests energy from all PBs and then uses the harvested energy to transmit information to its desired receiver. Our model accounts for realistic aspects of WPT and mmWave transmissions, such as power circuit activation threshold, allowed maximum harvested power, maximum transmit power, beamforming and blockage. Using stochastic geometry, we obtain the Laplace transform of the aggregate received power at the TX to calculate the power coverage probability. We approximate and discretize the transmit power of each TX into a finite number of discrete power levels in log scale to compute the channel and total coverage probability. We compare our analytical predictions to simulations and observe good accuracy. The proposed model allows insights into effect of system parameters, such as transmit power of PBs, PB density, main lobe beam-width and power circuit activation threshold on the overall coverage probability. The results confirm that it is feasible and safe to power TXs in a mmWave ad hoc network using PBs.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications

An introduction of intelligent interconnectivity for people and things has posed higher demands and more challenges for sixth-generation (6G) networks, such as high spectral efficiency and energy efficiency, ultra-low latency, and ultra-high reliability. Cell-free (CF) massive multiple-input multiple-output (mMIMO) and reconfigurable intelligent surface (RIS), also called intelligent reflecting surface (IRS), are two promising technologies for coping with these unprecedented demands. Given their distinct capabilities, integrating the two technologies to further enhance wireless network performances has received great research and development attention. In this paper, we provide a comprehensive survey of research on RIS-aided CF mMIMO wireless communication systems. We first introduce system models focusing on system architecture and application scenarios, channel models, and communication protocols. Subsequently, we summarize the relevant studies on system operation and resource allocation, providing in-depth analyses and discussions. Following this, we present practical challenges faced by RIS-aided CF mMIMO systems, particularly those introduced by RIS, such as hardware impairments and electromagnetic interference. We summarize corresponding analyses and solutions to further facilitate the implementation of RIS-aided CF mMIMO systems. Furthermore, we explore an interplay between RIS-aided CF mMIMO and other emerging 6G technologies, such as next-generation multiple-access (NGMA), simultaneous wireless information and power transfer (SWIPT), and millimeter wave (mmWave). Finally, we outline several research directions for future RIS-aided CF mMIMO systems.Comment: 30 pages, 15 figure