Stochastic Geometry Analysis of Multiple Access, Mobility, and Learning in Cellular Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Geometry Analysis of Multiple Access, Mobility, and Learning in Cellular Networks write by Mohammad Salehi. This book was released on 2021. Stochastic Geometry Analysis of Multiple Access, Mobility, and Learning in Cellular Networks available in PDF, EPUB and Kindle. Use cases of future wireless networks (e.g. fifth-generation [5G] networks and beyond [B5G]) will have service-quality requirements including higher data rates than today's networks for enhanced mobile broadband (eMBB), minimal latency and high network availability for ultra-reliability low-latency connection (URLLC), and massive access support for machine-type communications (mMTC). Also, 5G and B5G are expected to support communications for highly mobile scenarios with applications in new vertical sectors such as unmanned aerial vehicle (UAV) and autonomous car. Therefore, 5G and B5G cellular systems require a set of new technology enablers and solutions. In this thesis, we address some of the challenges of future wireless networks. In particular, we develop novel analytical models as well as methods, which will enable us to obtain insights into the performance of large-scale cellular networks and optimize network parameters. Non-orthogonal multiple access (NOMA) is a promising multiple access technique that enables massive connectivity and reduces the delay. We develop an analytical framework to derive the distribution of transmission success probabilities, meta distribution, for uplink and downlink NOMA. We also investigate the accuracy of distance-based ranking, instead of instantaneous signal power-based ranking, in the successive interference cancellation (SIC) at the NOMA receiver. Sojourn time, the time duration that a mobile user stays within a cell, is a mobility-aware parameter that can significantly impact the performance of mobile users and it can also be exploited to improve resource allocation and mobility management methods in the network. We derive the distribution and mean of the sojourn time in multi-tier cellular networks. Future wireless networks will exploit data-driven machine learning techniques for improving network management as well as service provisioning. Due to privacy and communication issues, learning at a centralized location (for example, at a base station) by collecting data from the mobile devices may not be always feasible. Federated learning is a machine learning setting where the centralized location trains a learning model using remote devices. Federated learning algorithms cannot be employed in real-world scenarios unless they consider unreliable and resource-constrained nature of the wireless medium. We propose a federated learning algorithm that is suitable for wireless networks.
Stochastic Geometry and Wireless Networks
Stochastic Geometry and Wireless Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Geometry and Wireless Networks write by François Baccelli. This book was released on 2009. Stochastic Geometry and Wireless Networks available in PDF, EPUB and Kindle. This volume bears on wireless network modeling and performance analysis. The aim is to show how stochastic geometry can be used in a more or less systematic way to analyze the phenomena that arise in this context. It first focuses on medium access control mechanisms used in ad hoc networks and in cellular networks. It then discusses the use of stochastic geometry for the quantitative analysis of routing algorithms in mobile ad hoc networks. The appendix also contains a concise summary of wireless communication principles and of the network architectures considered in the two volumes.
Stochastic Geometry Analysis of Cellular Networks
Stochastic Geometry Analysis of Cellular Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Geometry Analysis of Cellular Networks write by Bartłomiej Błaszczyszyn. This book was released on 2018-04-19. Stochastic Geometry Analysis of Cellular Networks available in PDF, EPUB and Kindle. Achieve faster and more efficient network design and optimization with this comprehensive guide. Some of the most prominent researchers in the field explain the very latest analytic techniques and results from stochastic geometry for modelling the signal-to-interference-plus-noise ratio (SINR) distribution in heterogeneous cellular networks. This book will help readers to understand the effects of combining different system deployment parameters on key performance indicators such as coverage and capacity, enabling the efficient allocation of simulation resources. In addition to covering results for network models based on the Poisson point process, this book presents recent results for when non-Poisson base station configurations appear Poisson, due to random propagation effects such as fading and shadowing, as well as non-Poisson models for base station configurations, with a focus on determinantal point processes and tractable approximation methods. Theoretical results are illustrated with practical Long-Term Evolution (LTE) applications and compared with real-world deployment results.
Modeling and Analyzing the Evolution of Cellular Networks Using Stochastic Geometry
Modeling and Analyzing the Evolution of Cellular Networks Using Stochastic Geometry - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Modeling and Analyzing the Evolution of Cellular Networks Using Stochastic Geometry write by Yingzhe Li (Ph. D.). This book was released on 2017. Modeling and Analyzing the Evolution of Cellular Networks Using Stochastic Geometry available in PDF, EPUB and Kindle. The increasing complexity of cellular network due to its continuous evolution has made the conventional system level simulations time consuming and cost prohibitive. By modeling base station (BS) and user locations as spatial point processes, stochastic geometry has recently been recognized as a tractable and efficient analytical tool to quantify key performance metrics. The goal of this dissertation is to leverage stochastic geometry to develop an accurate spatial point process model for the conventional homogeneous macro cellular network, and to address the design and analysis challenges for the emerging cellular networks that will explore new spectrum for cellular communications. First, this dissertation proposes to use the repulsive determinantal point processes (DPPs) as an accurate model for macro BS locations in a cellular network. Based on three unique computational properties of the DPPs, the exact expressions of several fundamental performance metrics for cellular networks with DPP configured BSs are analytically derived and numerically evaluated. Using hypothesis testing for various performance metrics of interest, the DPPs are validated to be more accurate than the Poisson point process (PPP) or the deterministic grid model. Then the focus of this dissertation shifts to emerging networks that exploit new spectrum for cellular communications. One promising option is to allow the centrally scheduled cellular system to also access the unlicensed spectrum, wherein a carrier sensing multiple access with collision avoidance (CSMA/CA) protocol is usually used, as in Wi-Fi. A stochastic geometry-based analytical framework is developed to characterize the performance metrics for neighboring Wi-Fi and cellular networks under various coexistence mechanisms. In order to guarantee fair coexistence with Wi-Fi, it is shown that the cellular network needs to adopt either a discontinuous transmission pattern or its own CSMA/CA like mechanisms. Next, this dissertation considers cellular networks operating in the millimeter wave (mmWave) band, where directional beamforming is required to establish viable connections. Therefore, a major design challenge is to learn the necessary beamforming directions through the procedures that establish the initial connection between the mobile user and the network. These procedures are referred to as initial access, wherein cell search on the downlink and random access on the uplink are the two major steps. Stochastic geometry is again utilized to develop a unified analytical framework for three directional initial access protocols under a high mobility scenario where users and random blockers are moving with high speed. The expected delay for a user to succeed in initial access, and the average user-perceived downlink throughput that accounts for the initial access overhead, are derived for all three protocols. In particular, the protocol that has low beam-sweeping overhead during cell search is found to achieve a good trade-off between the initial access delay and user-perceived throughput performance. Finally, in contrast to the high mobility scenario for initial access, the directional cell search delay in a slow mobile network is analyzed. Specifically, the BS and user locations are fixed for long period of time, and therefore a strong temporal correlation for SINR is experienced. A closed-form expression for the expected cell search delay is derived, indicating that the expected cell search delay is infinite for noise-limited networks (e.g., mmWave) whenever the non-line-of-sight path loss exponent is larger than 2. By contrast, the expected cell search delay for interference-limited networks is proved to be infinite when the number of beams to search at the BS is smaller than a certain threshold, and finite otherwise.
Stochastic Geometry and Wireless Networks: Applications
Stochastic Geometry and Wireless Networks: Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Geometry and Wireless Networks: Applications write by François Baccelli. This book was released on 2010-02. Stochastic Geometry and Wireless Networks: Applications available in PDF, EPUB and Kindle. This volume bears on wireless network modeling and performance analysis. The aim is to show how stochastic geometry can be used in a more or less systematic way to analyze the phenomena that arise in this context. It first focuses on medium access control mechanisms used in ad hoc networks and in cellular networks. It then discusses the use of stochastic geometry for the quantitative analysis of routing algorithms in mobile ad hoc networks. The appendix also contains a concise summary of wireless communication principles and of the network architectures considered in the two volumes.
