Download or read book Optimization in Next Generation Wireless Networks HETNET written by Mazen Habchy and published by . This book was released on 2015 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Design and Optimization of Next generation Wireless Networks written by Devu Manikantan Shila and published by . This book was released on 2011 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book GRT597 QoS based Optimization Solution for Next Generation Wireless Networks HetNet written by Salim Moodad and published by . This book was released on 2017 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data driven Optimization of Next Generation High density Wireless Networks written by Sami Khairy and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Performance Optimization of Next generation Data driven Wireless Networks written by Merima Kulin and published by . This book was released on 2020 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Towards Machine Learning Enabled Future generation Wireless Network Optimization written by Peizhi Yan and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We anticipate that there will be an enormous amount of wireless devices connected to the Internet through the future-generation wireless networks. Those wireless devices vary from self-driving vehicles to smart wearable devices and intelligent house- hold electrical appliances. Under such circumstances, the network resource optimization faces the challenge of the requirement of both flexibility and performance. Current wireless communication still relies on one-size-fits-all optimization algorithms, which require meticulous design and elaborate maintenance, thus not flexible and cannot meet the growing requirements well. The future-generation wireless networks should be "smarter", which means that the artificial intelligence-driven software-level design will play a more significant role in network optimization. In this thesis, we present three different ways of leveraging artificial intelligence (AI) and machine learning (ML) to design network optimization algorithms for three wireless Internet of things network optimization problems. Our ML-based approaches cover the use of multi-layer feed-forward artificial neural network and the graph convolutional network as the core of our AI decision-makers. The learning methods are supervised learning (for static decision-making) and reinforcement learning (for dynamic decision-making). We demonstrate the viability of applying ML in future- generation wireless network optimizations through extensive simulations. We summarize our discovery on the advantage of using ML in wireless network optimizations as the following three aspects: 1. Enabling the distributed decision-making to achieve the performance that near a centralized solution, without the requirement of multi-hop information; 2. Tackling with dynamic optimization through distributed self-learning decision- making agents, instead of designing a sophisticated optimization algorithm; 3. Reducing the time used in optimizing the solution of a combinatorial optimization problem. We envision that in the foreseeable future, AI and ML could help network service designers and operators to improve the network quality of experience swiftly and less expensively.

Download or read book Virtualized Wireless Networks written by Tho Le-Ngoc and published by Springer. This book was released on 2017-08-01 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: There have been recent advancements in wireless network technologies such as wireless virtualization to accommodate the exponential growth in demand, as well as to increase energy and infrastructure efficiencies. This SpringerBrief discusses the user-association and resource-allocation aspects in Virtualized Wireless Networks (VWNs) and highlights key technology innovations to meet their requirements. Various issues in practical implementation of VWNs are discussed along with potential techniques such as Massive MIMO, Cloud-Radio Access Network (C-RAN), and non-orthogonal multiple access (NOMA). This SpringerBrief will target researchers and professionals working on current and next-generation wireless networks. The content is also valuable for advanced-level students interested in wireless communications and signal processing for communications.

Download or read book Handbook of Research on Heterogeneous Next Generation Networking Innovations and Platforms written by Kotsopoulos, Stavros and published by IGI Global. This book was released on 2008-10-31 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents state-of-the-art research, developments, and integration activities in combined platforms of heterogeneous wireless networks"--Provided by publisher.

Download or read book Communication Efficient Federated Learning for Wireless Networks written by Mingzhe Chen and published by Springer Nature. This book was released on with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Improving Next generation Wireless Network Performance and Reliability with Deep Learning written by Faris Bassam Mismar and published by . This book was released on 2019 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: A rudimentary question whether machine learning in general, or deep learning in particular, could add to the well-established field of wireless communications, which has been evolving for close to a century, is often raised. While the use of deep learning based methods is likely to help build intelligent wireless solutions, this use becomes particularly challenging for the lower layers in the wireless communication stack. The introduction of the fifth generation of wireless communications (5G) has triggered the demand for “network intelligence” to support its promises for very high data rates and extremely low latency. Consequently, 5G wireless operators are faced with the challenges of network complexity, diversification of services, and personalized user experience. Industry standards have created enablers (such as the network data analytics function), but these enablers focus on post-mortem analysis at higher stack layers and have a periodicity in the time scale of seconds (or larger). The goal of this dissertation is to show a solution for these challenges and how a data-driven approach using deep learning could add to the field of wireless communications. In particular, I propose intelligent predictive and prescriptive abilities to boost reliability and eliminate performance bottlenecks in 5G cellular networks and beyond, show contributions that justify the value of deep learning in wireless communications across several different layers, and offer in-depth analysis and comparisons with baselines and industry standards. First, to improve multi-antenna network reliability against wireless impairments with power control and interference coordination for both packetized voice and beamformed data bearers, I propose the use of a joint beamforming, power control, and interference coordination algorithm based on deep reinforcement learning. This algorithm uses a string of bits and logic operations to enable simultaneous actions to be performed by the reinforcement learning agent. Consequently, a joint reward function is also proposed. I compare the performance of my proposed algorithm with the brute force approach and show that similar performance is achievable but with faster run-time as the number of transmit antennas increases. Second, in enhancing the performance of coordinated multipoint, I propose the use of deep learning binary classification to learn a surrogate function to trigger a second transmission stream instead of depending on the popular signal to interference plus noise measurement quantity. This surrogate function improves the users' sum-rate through focusing on pre-logarithmic terms in the sum-rate formula, which have larger impact on this rate. Third, performance of band switching can be improved without the need for a full channel estimation. My proposal of using deep learning to classify the quality of two frequency bands prior to granting the band switching leads to a significant improvement in users' throughput. This is due to the elimination of the industry standard measurement gap requirement—a period of silence where no data is sent to the users so they could measure the frequency bands before switching. In this dissertation, a group of algorithms for wireless network performance and reliability for downlink are proposed. My results show that the introduction of user coordinates enhance the accuracy of the predictions made with deep learning. Also, the choice of signal to interference plus noise ratio as the optimization objective may not always be the best choice to improve user throughput rates. Further, exploiting the spatial correlation of channels in different frequency bands can improve certain network procedures without the need for perfect knowledge of the per-band channel state information. Hence, an understanding of these results help develop novel solutions to enhancing these wireless networks at a much smaller time scale compared to the industry standards today

Download or read book Optimization and Applications of Modern Wireless Networks and Symmetry written by Pingping Chen and published by Mdpi AG. This book was released on 2022-10-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the future demands of wireless communications, this book focuses on channel coding, multi-access, network protocol, and the related techniques for IoT/5G. Channel coding is widely used to enhance reliability and spectral efficiency. In particular, low-density parity check (LDPC) codes and polar codes are optimized for next wireless standard. Moreover, advanced network protocol is developed to improve wireless throughput. This invokes a great deal of attention on modern communications.

Download or read book Wireless Systems and Network Architectures in Next Generation Internet written by Matteo Cesana and published by Springer Science & Business Media. This book was released on 2006-05-12 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-proceedings of the second international joint workshops on Wireless and Mobility and on New Trends in Network Architectures and Services organized by the European Network of Excellence on Next Generation Internet, EURO-NGI 2005. The 19 revised full research papers presented together with 1 invited talk are organized in topical sections on wireless solutions, QoS support in next generation networks, and peer to peer architectures and algorithms.

Download or read book Green Heterogeneous Wireless Networks written by Muhammad Ismail and published by John Wiley & Sons. This book was released on 2016-08-23 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the emerging research topic "green (energy efficient) wireless networks" which has drawn huge attention recently from both academia and industry. This topic is highly motivated due to important environmental, financial, and quality-of-experience (QoE) considerations. Specifically, the high energy consumption of the wireless networks manifests in approximately 2% of all CO2 emissions worldwide. This book presents the authors’ visions and solutions for deployment of energy efficient (green) heterogeneous wireless communication networks. The book consists of three major parts. The first part provides an introduction to the "green networks" concept, the second part targets the green multi-homing resource allocation problem, and the third chapter presents a novel deployment of device-to-device (D2D) communications and its successful integration in Heterogeneous Networks (HetNets). The book is novel in that it specifically targets green networking in a heterogeneous wireless medium, which represents the current and future wireless communication medium faced by the existing and next generation communication networks. The book focuses on multi-homing resource allocation, exploiting network cooperation, and integrating different and new network technologies (radio frequency and VLC), expanding the network coverage and integrating new device centric communication paradigms such as D2D Communications. Whilst the book discusses a significant research topic supported with advanced mathematical analysis, the resulting algorithms and solutions are explained and summarized in a way that is easy to follow and grasp. This book is suitable for networking and telecommunications engineers, researchers in industry and academia, as well as students and instructors.

Download or read book Protocol Design and Optimization for Wireless Networks written by Monchai Lertsutthiwong and published by . This book was released on 2010 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate a number of techniques for increasing throughput and quality of media applications over wireless networks. A typical media communication application such as video streaming imposes strict requirements on the delay and throughout of its packets, which unfortunately, cannot be guaranteed by the underlying wireless network due inherently to the multi-user interference and limited bandwidth of wireless channels. Therefore, much recent research has been focused on the joint design of network layers in order to guarantee some pre-specified Quality of Service (QoS). In this thesis, we investigate three specific settings to address the general problem of media transmission over wireless networks. In the first setting, we propose a distributed admission control algorithm in one-hop wireless network to decide whether or not a new flow should be injected into the network, in order to guarantee the QoS of the current flows. Next, a novel medium access control protocol and a scheduling packet algorithm are proposed for jointly optimizing the quality of video streaming applications. In the second setting, we extend the framework of the proposed admission control from a one-hop network to linear wireless networks, consisting of multiple nodes. In the third and final setting, we present an approach for increasing the throughput of wireless access networks by integrating network coding and beamforming techniques.

Download or read book Optimization in Multi radio Multi channel Wireless Networks with Directional Antennas written by Lei Zhou and published by . This book was released on 2018 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On Efficiency and Intelligence of Next generation Wireless Networks written by Pedram Kheirkhah Sangdeh and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-increasing demand for data-hungry wireless services and rapid proliferation of wireless devices in sub-6 GHz band have pushed the current wireless technologies to a breaking point, necessitating efficient and intelligent strategies to utilize scarce communication resources. This thesis aims at leveraging novel communication frameworks, artificial intelligence techniques, and synergies between them in bringing efficiency and intelligence to the next generation of wireless networks.In the first chapter of this thesis, we propose a novel spectrum sharing scheme to address spectrum shortage, a fundamental issue in current and future wireless networks. Our proposed scheme enables transparent spectrum utilization for a small cognitive radio network by leveraging two interference management techniques that are not reliant on inter-network coordination, fine-grained synchronization, and knowledge about other occupants of the spectrum. We further extend this idea in the second chapter of this thesis and enable concurrent device-to-device and cellular communications in cellular networks where the base station and wireless devices exploit interference management techniques to avoid causing interference to each other, making concurrent spectrum utilization possible for both cellular and device-to-device communications. In the third chapter, to enhance spectral efficiency, connectivity, and throughput of Wireless Local Area Networks (WLAN), we propose a non-orthogonal multiplexing scheme (NOMA). In our proposed scheme, the access point (AP) is equipped with a novel precoder design and user grouping which are tailored based on the requirements of power-domain NOMA. Also, a novel successive interference cancellation technique is designed for users which does not require channel estimation to decode the signals and is more resilient to interference compared to the existing techniques. The second part of this thesis focuses on taking advantage of artificial intelligence for solving communication and networking challenges and also taking advantage of novel communication frameworks to let future wireless networks indulge intelligence-oriented networking and resource management. In the fourth chapter, we propose a new solution to solve a long-standing issue ahead of multi-user multiple-input multiple-output (MU-MIMO) communications in WLANs, which is the large sounding overhead for acquiring the channel state information (CSI). Our learning-based solution includes an automated mechanism that enables access points to collect, clear, and balance dataset, and also deep neural networks to compress CSI and reduce the airtime overhead for channel acquisition. However, with provisioning concurrent MU-MIMO and orthogonal frequency division multiple access (OFDMA) in the new generation of WLANs, not only the sounding overhead problem becomes more acute, but it also marries with a complex resource allocation problem which makes designing a practical enabler of MU-MIMO-OFDMA transmissions necessary for WLANs. In the fifth chapter of this thesis, we propose DeepMux, which comprises a deep-learning-based channel sounding and a deep-learning-based resource allocation both of which reside in access points and impose no computational/communication burden on users, enabling efficient downlink MU-MIMO-OFDMA transmissions in WLANs. We finally design a communication framework for accelerating federated learning in future intelligent transportation systems, where heterogeneous capabilities and mobility of users along with limited available bandwidth for communications are huge obstacles toward making the network intelligent in a distributed manner. With the aid of a deadline-driven scheduler and asynchronous uplink multi-user MIMO, our proposed solution reduces data loss at vehicles in a dynamic vehicular environment, making a concrete step toward the practical adoption of federated learning in future transportation systems.

Download or read book Optimization of Heterogeneous Wireless Networks with Massive MIMO written by Shitong Yuan and published by . This book was released on 2019 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the next generation wireless communication system, multi-layers of Heterogeneous Networks (HetNets) are required to provide high efficiency bandwidth usage and high speed data throughput. Users distribution and their quality of service (QoS) request are random, and the number of users may vary through the time. In order to deal with this problem, this thesis builds two games models to optimize the resource allocation corresponding to different situations in the first chapter. The spectrum efficiency is analyzed and compared between two games. By playing those games, cells can serve more users inside one cell, and all users are fair to share the bandwidth according to their requests and locations. The whole system becomes more flexible and performance has been enhanced.Further, we consider massive MIMO in a two-layer Heterogeneous Cellular Net-work. The system has a large self-interference and co-channel interference due to full-duplex mode operation. A two-layer HetNets system model is proposed with Massive MIMO in Full-duplex mode. By using Game Theory, an optimized system sum-rate is achieved. We investigate the potential sum-rate before and after the optimization under the power constraints(both single user power constraint and power constrain at base station). It is shown that after the game theoretical method applied, the system performed a very good access scheduling compare to random access. Com-pared to non-optimized model, game theoretical method can achieve higher sum-rate. A novel antenna placement scheme at base station is proposed based on 2-D nested array. We utilize the difference co-array to model and generate all antennas (virtual antennas) in the covariance matrix of channel (virtual channel) coefficients. We also model a Massive MIMO antenna system with nested configuration and list all mathematical procedures to calculate its performance with achievable rate. A zero forcing detector is applied to this Massive MIMO system and the spectral efficiency is given at the end. Given the same number of antennas, the proposed method could achieve higher sum-rate capacity and better spectral efficiency.The Massive MIMO usually considers the azimuth angle only. However, in a 3D distributed antenna system, the elevation angle cannot be ignored. Nested array as a two dimensional arrays was firstly proposed to perform array processing with increased degree of freedom, using less number of sensors at the same time. A novel 3D MIMO antenna deployment is also proposed based on nested co-array. We model a 3D nested distributed MIMO system and analyze its performance with achievable sum rate.