Download or read book Cross Layer Routing in Cognitive Radio Network Using Deep Reinforcement Learning written by Snehal Sudhir Chitnavis and published by . This book was released on 2018 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Development of 5G technology and Internet of Things (IoT) devices has resulted in higher bandwidth requirements leading to increased scarcity of wireless spectrum. Cognitive Radio Networks (CRNs) provide an efficient solution to this problem. In CRNs, multiple secondary users share the spectrum band that is allocated to a primary network. This spectrum sharing of the primary spectrum band is achieved in this work by using an underlay scheme. In this scheme, the Signal to Interference plus Noise Ratio (SINR) caused to the primary due to communication between secondary users is kept below a threshold level. In this work, the CRNs perform cross-layer optimization by learning the parameters from the physical and the network layer so as to improve the end-to-end quality of experience for video traffic. The developed system meets the design goal by using a Deep Q-Network (DQN) to choose the next hop for transmitting based on the delay seen at each router, while maintaining SINR below the threshold set by primary channel. A fully connected feed-forward Multilayer Perceptron (MLP) is used by secondary users to approximate the action value function. The action value comprises of SINR to the primary user (at the physical layer) and next hop to the routers for each packet (at the network layer). The reward to this neural network is Mean Opinion Score (MOS) for video traffic which depends on the packet loss rate and the bitrate used for transmission. As compared to the implementation of DQN learning at the physical layer only, this system provides 30\% increase in the video quality for routers with small queue lengths and also achieves a balanced load on a network with routers with unequal service rates."--Abstract.
Download or read book Cross Layer Resource Allocation in Cognitive Radio Networks Models Algorithms and Applications written by Hang Qin and published by Scientific Research Publishing, Inc. USA. This book was released on 2017-04-30 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about cognitive radio (CR), a revolution in radio technology and an enabling technology for dynamic spectrum access. Due to the unique characteristics of the wireless networks, it is essential to address the approach of multiple layers (e.g., physical, link, and network) to maximize the network performance. The formulation of this cross-layer problem is usually complicated and challenging, while wireless resource allocation is a vital way to handle the race condition of the limited wireless resources. However, given the intrinsic characteristics of cognitive radio networks (CRN), none of the existing analytical approach could be a direct fit. Therefore, innovative theoretical results, along with the corresponding mathematical techniques, are necessary. In this book, we aim to develop some novel algorithmic design and optimization techniques that provide optimal or near-optimal solutions. Although cross-layer design has been introduced to CRN for many years, there are rarely any books for researchers, engineers, and students, from the engineering perspective. From one hand, most of the existing books primarily focus on the mathematical and economic aspects, which are considerably different from the engineering. On the other hand, all of the books mainly aim to system optimization or control techniques, while the cross-layer algorithm design in the distributed environment is usually ignored. As the result, there is an urgent demand for a reference source, which can provide complete information on how to fully adopt cross-layer resource allocation to the CRN. In this regard, this book not only focuses on the description of the main aspects of cross-layer resource allocation over CRN, but also provides a review of the application solutions. In a nutshell, it provides a specific treatment of cross-layer design in CRN. The topics range from the basic concepts of cross-layer resource allocation, to the state-of-the-art analyses, modelings, and optimizations for CRN.
Download or read book Cognitive Networks written by Jaime Lloret Mauri and published by CRC Press. This book was released on 2014-12-09 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cognitive network makes use of the information gathered from the network in order to sense the environment, plan actions according to the input, and make appropriate decisions using a reasoning engine. The ability of cognitive networks to learn from the past and use that knowledge to improve future decisions makes them a key area of interest for anyone whose work involves wireless networks and communications. Cognitive Networks: Applications and Deployments examines recent developments in cognitive networks from the perspective of cutting-edge applications and deployments. Presenting the contributions of internationally renowned experts, it supplies complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks—together with implementation details. The book includes case studies and detailed descriptions of cognitive radio platforms and testbeds that demonstrate how to build real-world cognitive radio systems and network architectures. It begins with an introduction to efficient spectrum management and presents a survey on joint routing and dynamic spectrum access in cognitive radio networks. Next, it examines radio spectrum sensing and network coding and design. It explores intelligent routing in graded cognitive networks and presents an energy-efficient routing protocol for cognitive radio ad hoc networks. The book concludes by considering dynamic radio spectrum access and examining vehicular cognitive networks and applications. Presenting the latest standards and spectrum policy developments, the book’s strong practical orientation provides you with the understanding you will need to participate in the development of compliant cognitive systems.
Download or read book A Cross Layer Routing Protocol for Cognitive Radio Networks Using Channel Activity Tracking written by Sandeep Gogineni and published by . This book was released on 2012 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multimedia over Cognitive Radio Networks written by Fei Hu and published by CRC Press. This book was released on 2014-12-04 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: With nearly 7 billion mobile phone subscriptions worldwide, mobility and computing have become pervasive in our society and business. Moreover, new mobile multimedia communication services are challenging telecommunication operators. To support the significant increase in multimedia traffic-especially video-over wireless networks, new technological
Download or read book Deep Reinforcement Learning for Wireless Communications and Networking written by Dinh Thai Hoang and published by John Wiley & Sons. This book was released on 2023-06-30 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking. Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design. Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as: Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learning Physical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer security Medium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell association Network layer applications, covering traffic routing, network classification, and network slicing With comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.
Download or read book Developments in Cognitive Radio Networks written by Bodhaswar TJ Maharaj and published by Springer Nature. This book was released on 2021-07-14 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides holistic yet concise information on what modern cognitive radio networks are, how they work, and the possible future directions for them. The authors first present the most generic models of modern cognitive radio networks, taking into consideration their different architectural designs and classifications. While the spectrum resource is shown to be the most important resource for the cognitive radio networks, the book exposes the importance of the other resources that are needed to help drive the technology. The book then discusses in-depth the key tools (such as optimization and queuing theory) and techniques (such as cooperative diversity and relaying) that are being employed to formulate resource problems, investigate solutions, and interpret such solutions for useful and practical modern cognitive radio networks realization. Further, the book studies the impact of modern cognitive radio networks on other emerging technologies -- such as 5G, Internet of Things, and advanced wireless sensor networks -- and discusses the role that cognitive radio networks play in the evolution of smart cities and in the realization of a highly interconnected world. In discussing the future of the cognitive radio networks, the book emphasizes the need to advance new or improved tools, techniques, and solutions to address lingering problems in the aspects of resource realization and utilization, network complexity, network security, etc., which can potentially limit the cognitive radio networks in their stride to becoming one of the most promising technologies for the immediate and near future.
Download or read book Learning for Cross layer Resource Allocaton in the Framework of Cognitive Wireless Networks written by Wenbo Wang and published by . This book was released on 2016 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The framework of cognitive wireless networks is expected to endow wireless devices with a cognition-intelligence ability with which they can efficiently learn and respond to the dynamic wireless environment. In this dissertation, we focus on the problem of developing cognitive network control mechanisms without knowing in advance an accurate network model. We study a series of cross-layer resource allocation problems in cognitive wireless networks. Based on model-free learning, optimization and game theory, we propose a framework of self-organized, adaptive strategy learning for wireless devices to (implicitly) build the understanding of the network dynamics through trial-and-error. The work of this dissertation is divided into three parts. In the first part, we investigate a distributed, single-agent decision-making problem for real-time video streaming over a time-varying wireless channel between a single pair of transmitter and receiver. By modeling the joint source-channel resource allocation process for video streaming as a constrained Markov decision process, we propose a reinforcement learning scheme to search for the optimal transmission policy without the need to know in advance the details of network dynamics. In the second part of this work, we extend our study from the single-agent to a multi-agent decision-making scenario, and study the energy-efficient power allocation problems in a two-tier, underlay heterogeneous network and in a self-sustainable green network. For the heterogeneous network, we propose a stochastic learning algorithm based on repeated games to allow individual macro- or femto-users to find a Stackelberg equilibrium without flooding the network with local action information. For the self-sustainable green network, we propose a combinatorial auction mechanism that allows mobile stations to adaptively choose the optimal base station and sub-carrier group for transmission only from local payoff and transmission strategy information. In the third part of this work, we study a cross-layer routing problem in an interweaved Cognitive Radio Network (CRN), where an accurate network model is not available and the secondary users that are distributed within the CRN only have access to local action/utility information. In order to develop a spectrum-aware routing mechanism that is robust against potential insider attackers, we model the uncoordinated interaction between CRN nodes in the dynamic wireless environment as a stochastic game. Through decomposition of the stochastic routing game, we propose two stochastic learning algorithm based on a group of repeated stage games for the secondary users to learn the best-response strategies without the need of information flooding."--Abstract.
Download or read book Advances in Communication and Applications written by N. R. Shetty and published by Springer Nature. This book was released on 2024-01-06 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the International Conference on Emerging Research in Computing, Information, Communication and Applications (ERCICA) 2023. The conference provides an interdisciplinary forum for researchers, professional engineers and scientists, educators and technologists to discuss, debate and promote research and technology in the upcoming areas of computing, information, communication and their applications. Some of the topics include the Internet of Things (IoT), wireless communications, image and video processing, parallel and distributed computing, and smart grid applications, among others. The book discusses these emerging research areas, providing a valuable resource for researchers and practicing engineers alike.
Download or read book Cross layer Design and Optimization of OFDMA based Cognitive Radio Networks written by Hadi Saki and published by . This book was released on 2014 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to protect the primary service operation from harmful intervention, stochastic transmit and interference power constrains are imposed on the cognitive users. The performance of the proposed stochas¬tic algorithms and their advantages over the conventional hard-decision-based approaches are assessed and demonstrated through simulation results. Finally a specific cross-layer design for multi scalable video application transmis¬sion in an interference-limited spectrum sharing system is proposed. The proposed design jointly considers the parameters from the PHY and the application layers in order to maximize the overall peak signal-to-noise ratio (PSNR). Results indicate that significant improvement in secondary receivers (SRxs) average video quality is achieved through our proposed algorithm over other state-of-the-art non-quality-aware (NQA) designs in the literature. The enhanced performance was obtained whilst guaranteeing SRx minimum quality and primary receiver (PRx) prescribed quality of service (QoS) constraints.
Download or read book Cross layer Framework for Interference Avoidance in Cognitive Radio Ad hoc Networks written by Minh thao Quach and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fixed spectrum assignment scheme has a problem with resource deficiency in a wireless network. In 2002, the US Federal Communication Commission (FCC) reported that the radio spectrum was 20% to 85% under-utilized. The insufficient use of the spectrum is a critical issue for radio communication; as communication grows, a fixed spectrum becomes more limiting. The FCC then changed its spectrum management policy to make it more flexible by investigating the cognitive radio (CR) approach. Cognitive radio is a type of intelligent radio that explores the radio frequency environment, learns, and decides to use the unused portion of the frequency. The main functions of a CR are sensing, decision making, and sharing. However, these radios have to respect the standard wireless infrastructures by ensuring the least impact with their devices, also known as primary radios. Coexistence between CR systems and primary systems requires dedicated observation processes and interference management. In this thesis, observation from a CR point of view is presented. The overlapping area between a CR transmitter and primary radio (PR) transmitter is analysed so that it can be taken into account. The impact of this area is learnt by simulation and presented in Chapter 4. As a consequence, potential interference is envisaged. Along with observation, we investigate a proper mechanism to better prevent perturbation on PR devices using the Grey model and Kalman filter as a prediction model for predicting the density of primary receivers. In addition, we provide a strategy to combine the obtained observations into a metric that can be used in routing design in the context of coexistence between Cognitive Radio Networks (CRNs) and primary networks. The proposed strategy, using fuzzy logic, is presented in Chapter 5. In this chapter, we investigate how the routing layer reacts and makes the right decisions to maximise the spectrum resources, while avoiding interference with the primary receivers. For instance, a CR node can operate in an overlap region if primary receivers are inactive within this area. Also, we propose a routing mechanism based on the DYMO routing protocol that takes into account the observed relative impact. In the same chapter, we provide some practical scenarios illustrating the usefulness of our proposal. Interconnecting the CR nodes in CRNs is also a critical problem for the establishment of the network. We therefore present a beacon-based dissemination process in Chapter 6. In this chapter, we also describe a practical device designed for cognitive radio experiments. Even though our work affects different protocol layers, the designed framework is cross-layered. Indeed, the different components of the proposed framework access the various layers to retrieve information, process it, and react accordingly. Thus, our work constitutes a cross-layer framework for a local cognitive radio that aims to minimise the interference and maximise the network resources in cognitive radio networks.
Download or read book Self Organization and Green Applications in Cognitive Radio Networks written by Al-Dulaimi, Anwer and published by IGI Global. This book was released on 2013-01-31 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-Organization and Green Applications in Cognitive Radio Networks provides recent research on the developments of efficient cognitive network topology. The most current procedures and results are presented to demonstrate how developments in this area can reduce complications, confusion, and even costs. The book also identifies future challenges that are predicted to arrive in the Cognitive Radio Network along with potential solutions. This innovative publication is unique because it suggests green, energy efficient and cost efficient resolutions to the inevitable challenges in the network.
Download or read book Machine Learning enabled Resource Allocation for Underlay Cognitive Radio Networks written by Fatemeh Shah Mohammadi and published by . This book was released on 2020 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources and the way they are regulated. Considering that the radio spectrum is a natural limited resource, supporting the ever increasing demands for higher capacity and higher data rates for diverse sets of users, services and applications is a challenging task which requires innovative technologies capable of providing new ways of efficiently exploiting the available radio spectrum. Consequently, dynamic spectrum access (DSA) has been proposed as a replacement for static spectrum allocation policies. The DSA is implemented in three modes including interweave, overlay and underlay mode [1]. The key enabling technology for DSA is cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems. Unlike conventional radio which is restricted to only operate in designated spectrum bands, a CR has the capability to operate in different spectrum bands owing to its ability in sensing, understanding its wireless environment, learning from past experiences and proactively changing the transmission parameters as needed. These features for CR are provided by an intelligent software package called the cognitive engine (CE). In general, the CE manages radio resources to accomplish cognitive functionalities and allocates and adapts the radio resources to optimize the performance of the network. Cognitive functionality of the CE can be achieved by leveraging machine learning techniques. Therefore, this thesis explores the application of two machine learning techniques in enabling the cognition capability of CE. The two considered machine learning techniques are neural network-based supervised learning and reinforcement learning. Specifically, this thesis develops resource allocation algorithms that leverage the use of machine learning techniques to find the solution to the resource allocation problem for heterogeneous underlay cognitive radio networks (CRNs). The proposed algorithms are evaluated under extensive simulation runs. The first resource allocation algorithm uses a neural network-based learning paradigm to present a fully autonomous and distributed underlay DSA scheme where each CR operates based on predicting its transmission effect on a primary network (PN). The scheme is based on a CE with an artificial neural network that predicts the adaptive modulation and coding configuration for the primary link nearest to a transmitting CR, without exchanging information between primary and secondary networks. By managing the effect of the secondary network (SN) on the primary network, the presented technique maintains the relative average throughput change in the primary network within a prescribed maximum value, while also finding transmit settings for the CRs that result in throughput as large as allowed by the primary network interference limit. The second resource allocation algorithm uses reinforcement learning and aims at distributively maximizing the average quality of experience (QoE) across transmission of CRs with different types of traffic while satisfying a primary network interference constraint. To best satisfy the QoE requirements of the delay-sensitive type of traffics, a cross-layer resource allocation algorithm is derived and its performance is compared against a physical-layer algorithm in terms of meeting end-to-end traffic delay constraints. Moreover, to accelerate the learning performance of the presented algorithms, the idea of transfer learning is integrated. The philosophy behind transfer learning is to allow well-established and expert cognitive agents (i.e. base stations or mobile stations in the context of wireless communications) to teach newly activated and naive agents. Exchange of learned information is used to improve the learning performance of a distributed CR network. This thesis further identifies the best practices to transfer knowledge between CRs so as to reduce the communication overhead. The investigations in this thesis propose a novel technique which is able to accurately predict the modulation scheme and channel coding rate used in a primary link without the need to exchange information between the two networks (e.g. access to feedback channels), while succeeding in the main goal of determining the transmit power of the CRs such that the interference they create remains below the maximum threshold that the primary network can sustain with minimal effect on the average throughput. The investigations in this thesis also provide a physical-layer as well as a cross-layer machine learning-based algorithms to address the challenge of resource allocation in underlay cognitive radio networks, resulting in better learning performance and reduced communication overhead."--Abstract.
Download or read book The Design and Optimisation of Cross Layer Routing and Medium Access Control MAC Protocols in Cognitive Radio Networks written by Miyelani Silence Madiba and published by . This book was released on 2021 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spectrum Management and Cross layer Protocol Design in Cognitive Radio Networks written by Ying Dai and published by . This book was released on 2014 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive radio networks (CRNs) are a promising solution to the channel (spectrum) congestion problem. This dissertation presents work on the two main issues in CRNs: spectrum management and cross-layer protocol design. The objective of spectrum management is to enable the efficient usage of spectrum resources in CRNs, which protects primary users' activities and ensures the effective spectrum sharing among nodes. We consider to improve the spectrum sensing efficiency and accuracy, so that the spectrum sensing cost is reduced. We consider the pre-phase of spectrum sensing and provide structures for sensing assistance. Besides the spectrum sensing phase, the sharing of spectrum, or the channel allocation, among nodes is also the main component in the spectrum management. We provide our approach to achieve a reliable and effective channel assignment. The channel availabilities for different nodes in CRNs are dynamic and inconsistent. This poses challenges on the MAC layer protocols for CRNs. Moreover, due to the lack of knowledge on primary users, they can suddenly become available during the secondary users' data transmission. Therefore, for a end-to-end data transmission in CRNs, the routing algorithm is different from the existing routing algorithms in traditional networks. We consider the cross-layer protocol design, and propose the solutions for efficient data transmission. We propose the novel routing protocol design considering the boundaries of PUs. Also, an effective structure for reliable end-to-end data transmission is presented, which makes use of the area routing protocol. We build a USRP/Gnuradio testbed for the performance evaluation of our protocols.
Download or read book A Cross Layer Approach to Multi Hop Networking with Cognitive Radios written by and published by . This book was released on 2008 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive radio (CR) is an enabling technology for efficient use of available spectrum and promises unprecedented flexibility in multi-hop wireless networking. This paper explores networking related issues associated with CRs. Specifically, we consider how to maximize the rates of a set of user communication sessions in a multi-hop CR-based wireless network. Due to potential interference at the physical layer, we find that it is essential to follow a cross-layer approach, with joint optimization at physical (power control), link (frequency band scheduling) and network (flow routing) layers. We give a mathematical characterization of this cross-layer optimization problem. We develop a centralized solution procedure based on the branchand- bound framework. Using numerical results, we demonstrate the efficacy of the solution procedure and offer quantitative understanding on the joint optimization at different layers.
Download or read book Cognitive Radio Networks written by Yan Zhang and published by CRC Press. This book was released on 2019-08-30 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: While still in the early stages of research and development, cognitive radio is a highly promising communications paradigm with the ability to effectively address the spectrum insufficiency problem. Written by those pioneering the field, Cognitive Radio Networks: Architectures, Protocols, and Standards offers a complete view of cognitive radio--including introductory concepts, fundamental techniques, regulations, standards, system implementations, and recent developments. From the physical layer to protocol layer, world-class editors provide comprehensive technical and regulatory guidance across cognitive radio, dynamic spectrum access, and cognitive wireless networks. The book examines routing, Medium Access Control (MAC), cooperation schemes, resource management, mobility, and game theory approach. Organized into three sections for ease of reference: Introduces and addresses the issues in the physical layer, including sensing, capacity, and power control Examines issues in the protocol layers and supplies practical solutions Explores applications, including cognitive radio systems Complete with illustrative figures that allow for complete cross-referencing, this authoritative reference provides readers with the understanding of the fundamental concepts, principles, and framework of cognitive wireless systems needed to initiate the development of future-generation wireless systems and networks.
