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Towards Robust and Reliable Communication for Millimeter Wave Networks

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Release : 2022
Genre : Electronic dissertations
Kind : eBook
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Book Synopsis Towards Robust and Reliable Communication for Millimeter Wave Networks by : Masoud Zarifneshat

Download or read book Towards Robust and Reliable Communication for Millimeter Wave Networks written by Masoud Zarifneshat. This book was released on 2022. Available in PDF, EPUB and Kindle. Book excerpt: The future generations of wireless networks benefit significantly from millimeter wave technology (mmW) with frequencies ranging from about 30 GHz to 300 GHz. Specifically, the fifth generation of wireless networks has already implemented the mmW technology and the capacity requirements defined in 6G will also benefit from the mmW spectrum. Despite the attractions of the mmW technology, the mmW spectrum has some inherent propagation properties that introduce challenges. The first is that free space pathloss in mmW is more severe than that in the sub 6 GHz band. To make the mmW signal travel farther, communication systems need to use phased array antennas to concentrate the signal power to a limited direction in space at each given time. Directional communication can incur high overhead on the system because it needs to probe the space for finding signal paths. To have efficient communication in the mmW spectrum, the transmitter and the receiver should align their beams on strong signal paths which is a high overhead task. The second is a low diffraction of the mmW spectrum. The low diffraction causes almost any object including the human body to easily block the mmW signal degrading the mmW link quality. Avoiding and recovering from the blockage in the mmW communications, especially in dynamic environments, is particularly challenging because of the fast changes of the mmW channel. Due to the unique characteristics of the mmW propagation, the traditional user association methods perform poorly in the mmW spectrum. Therefore, we propose user association methods that consider the inherent propagation characteristics of the mmW signal. We first propose a method that collects the history of blockage incidents throughout the network and exploits the historical blockage incidents to associate user equipment to the base station with lower blockage possibility. The simulation results show that our proposed algorithm performs better in terms of improving the quality of the links and blockage rate in the network. User association based only on one objective may deteriorate other objectives. Therefore, we formulate a biobjective optimization problem to consider two objectives of load balance and blockage possibility in the network. We conduct Lagrangian dual analysis to decrease time complexity. The results show that our solution to the biobjective optimization problem has a better outcome compared to optimizing each objective alone. After we investigate the user association problem, we further look into the problem of maintaining a robust link between a transmitter and a receiver. The directional propagation of the mmW signal creates the opportunity to exploit multipath for a robust link. The main reasons for the link quality degradation are blockage and link movement. We devise a learning-based prediction framework to classify link blockage and link movement efficiently and quickly using diffraction values for taking appropriate mitigating actions. The simulations show that the prediction framework can predict blockage with close to 90% accuracy. The prediction framework will eliminate the need for time-consuming methods to discriminate between link movement and link blockage. After detecting the reason for the link degradation, the system needs to do the beam alignment on the updated mmW signal paths. The beam alignment on the signal paths is a high overhead task. We propose using signaling in another frequency band to discover the paths surrounding a receiver working in the mmW spectrum. In this way, the receiver does not have to do an expensive beam scan in the mmW band. Our experiments with off-the-shelf devices show that we can use a non-mmW frequency band's paths to align the beams in mmW frequency.In this dissertation, we provide solutions to the fundamental problems in mmW communication. We propose a user association method that is designed for mmW networks considering challenges of mmW signal. A closed-form solution for a biobjective optimization problem to optimize both blockage and load balance of the network is also provided. Moreover, we show that we can efficiently use the out-of-band signal to exploit multipath created in mmW communication. The future research direction includes investigating the methods proposed in this dissertation to solve some of the classic problems in the wireless networks that exist in the mmW spectrum.

Analysis and Optimization for Robust Millimeter-Wave Communications

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Release : 2021-01-13
Genre : Electronic books
Kind : eBook
Book Rating : 34X/5 ( reviews)

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Book Synopsis Analysis and Optimization for Robust Millimeter-Wave Communications by : Cristian Tatino

Download or read book Analysis and Optimization for Robust Millimeter-Wave Communications written by Cristian Tatino. This book was released on 2021-01-13. Available in PDF, EPUB and Kindle. Book excerpt: Spectrum scarcity is a longstanding problem in mobile telecommunications networks. Specifically, accommodating the ever-growing data rate and communications demand in the extensively used spectrum between 800 MHz and 6 GHz is becoming more challenging. For this reason, in the last years, communications in the millimeterwave (mm-wave) frequency range (30-300 GHz) have attracted the interest of many researchers, who consider mm-wave communications a key enabler for upcoming generations of mobile communications, i.e., 5G and 6G. However, the signal propagation in the mm-wave frequency range is subject to more challenging conditions. High path loss and penetration loss may lead to short-range communications and frequent transmission interruptions when the signal path between the transmitter and the receiver is blocked. In this dissertation, we analyze and optimize techniques that enhance the robustness and reliability of mm-wave communications. In the first part, we focus on approaches that allow user equipment (UE) to establish and maintain connections with multiple access points (APs) or relays, i.e., multi-connectivity (MC) and relaying techniques, to increase link failure robustness. In such scenarios, an inefficient link scheduling, i.e., over or under-provisioning of connections, can lead to either high interference and energy consumption or unsatisfied user’s quality of service (QoS) requirements. In the first paper, we propose a novel link scheduling algorithm for network throughput maximization with constrained resources and quantify the potential gain of MC. As a complementary approach, in the second paper, we solve the problem of minimizing allocated resources while satisfying users’ QoS requirements for mm-wave MC scenarios. To deal with the channel uncertainty and abrupt blockages, we propose a learning-based solution, of which the results highlight the tradeoff between reliability and allocated resource. In the third paper, we perform throughput and delay analysis of a multi-user mm-wave wireless network assisted by a relay. We show the benefits of cooperative networking and the effects of directional communications on relay-aided mm-wave communications. These, as highlighted by the results, are characterized by a tradeoff between throughput and delay and are highly affected by the beam alignment duration and transmission strategy (directional or broadcast). The second part of this dissertation focuses on problems related to mm-wave communications in industrial scenarios, where robots and new industrial applications require high data rates, and stringent reliability and latency requirements. In the fourth paper, we consider a multi-AP mm-wave wireless network covering an industrial plant where multiple moving robots need to be connected. We show how the joint optimization of robots’ paths and the robot-AP associations can increase mm-wave robustness by decreasing the number of handovers and avoiding coverage holes. Finally, the fifth paper considers scenarios where robot-AP communications are assisted by an intelligent reflective surface (IRS). We show that the joint optimization of beamforming and trajectory of the robot can minimize the motion energy consumption while satisfying time and communication QoS constraints. Moreover, the proposed solution exploits a radio map to prevent collisions with obstacles and to increase mm-wave communication robustness by avoiding poorly covered areas.

Millimeter-Wave Communication Systems: Network Analysis and Hybrid Precoding Design

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Release : 2022-02-23
Genre : Technology & Engineering
Kind : eBook
Book Rating : 217/5 ( reviews)

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Book Synopsis Millimeter-Wave Communication Systems: Network Analysis and Hybrid Precoding Design by : Kai Yang

Download or read book Millimeter-Wave Communication Systems: Network Analysis and Hybrid Precoding Design written by Kai Yang. This book was released on 2022-02-23. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates the analytical framework and hybrid precoding scheme in millimeter-wave networks. Millimeter-wave communication is a frontier technology for supporting ultra-high data rate transmissions in future wireless networks due to larger bandwidth and higher spectral efficiency. However, the involved interference characterization and increased energy consumption are two dominant limitations in millimeter-wave network evolution. In this monograph, we develop a unified analytical framework for large-scale millimeter-wave communication networks, which leads to abundant network design insights and guidelines. Under this framework, we design low-complexity hybrid precoding algorithms for millimeter-wave systems, which greatly reduce energy consumption without obvious performance degradation. We would like to highlight that we develop a unified analytical framework and low-complexity hybrid precoding mechanisms for millimeter-wave communication networks, where a variety of millimeter-wave properties and hardware constraints are incorporated. The developed mechanisms can provide abundant insights and guidelines for the hybrid precoding design and analysis in millimeter-wave communication networks. Graduate students, researchers, and engineers in the field of communication networks can benefit from the book.

Robust Communication and Optimization Over Dynamic Networks

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Release : 2018
Genre :
Kind : eBook
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Book Synopsis Robust Communication and Optimization Over Dynamic Networks by : Can Karakus

Download or read book Robust Communication and Optimization Over Dynamic Networks written by Can Karakus. This book was released on 2018. Available in PDF, EPUB and Kindle. Book excerpt: Many types of communication and computation networks arising in modern systems have fundamentally dynamic, time-varying, and ultimately unreliably available resources. Specifically, in wireless communication networks, such unreliability may manifest itself as variability in channel conditions, intermittent availability of undedicated resources (such as unlicensed spectrum), or collisions due to multiple-access. In distributed computing, and specifically in large-scale distributed optimization and machine learning, this phenomenon manifests itself in the form of communication bottlenecks, straggling or failed nodes, or running background processes which hamper or slow down the computational task. In this thesis, we develop information-theoretically-motivated approaches that make progress towards building robust and reliable communication and computation networks built upon unreliable resources. In the first part of the thesis, we focus on three problems in wireless networks which involve opportunistically harnessing time-varying resources while providing theoretical performance guarantees. First, we show that in full-duplex uplink-downlink cellular networks, a simple, low-overhead user scheduling scheme that exploits the variations in channel conditions can be used to optimally mitigate inter-user interference in the many-user regime. Next, we consider the use of intermittently available links over unlicensed spectral bands to enhance communication over the licensed cellular band. We show that channel output feedback over such links, combined with quantize-map-forward relaying, provides generalized-degrees-of-freedom gain in interference networks. We characterize the information-theoretic capacity region of this model to within a constant gap. We finally consider the use of such intermittent links in device-to-device cooperation to aid cellular downlink. We develop an optimal dynamic resource allocation algorithm for such networks using stochastic approximation and graph theory techniques, and show that the resulting scheme results in up to 5-6x throughput gain for cell-edge users. In the second part, we consider the problem of distributed optimization and machine learning over large-scale, yet unreliable clusters. Focusing on a master-worker architecture, where large-scale datasets are distributed across worker nodes which communicate with a central parameter server to optimize a global objective, we develop a framework for embedding redundancy in the dataset to combat node failures and delays. This framework consists of an efficient linear transformation (coding) of the dataset that results in an overcomplete representation, combined with a coding-oblivious application of a distributed optimization algorithm. We show that if the linear transformation is designed to satisfy certain spectral properties resembling the restricted isometry property, nodes that fail or delay their computation can be dynamically left out of the computational process, while still converging to a reasonable solution with fast convergence rates, obviating the need for explicit fault-tolerance mechanisms and significantly speeding up overall computation. We implement the techniques on Amazon EC2 clusters to demonstrate the applicability of the proposed technique to various machine learning problems, such as logistic regression, support vector machine, ridge regression, and collaborative filtering; as well as several popular optimization algorithms including gradient descent, L-BFGS, coordinate descent and proximal gradient methods.

Proceedings of Second International Conference on Intelligent System

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Book Synopsis Proceedings of Second International Conference on Intelligent System by : João Manuel R. S. Tavares

Download or read book Proceedings of Second International Conference on Intelligent System written by João Manuel R. S. Tavares. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt:

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