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Overview of Cognitive Radio Networks
Cognitive radio (CR) allows the best use of dynamic access to spectrum and wide spectrum diversity to mitigate spectrum depletion issues and fulfil huge wireless networking requirements. This paper also illustrates, discusses, and focuses on some essential applications, a proactive spectrum sharing strategy using full-duplex (FD) in the cooperative Cognitive Radio Networks (CRN).
Journal Article
Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms
This book focuses on Television White Space (TVWS) opportunities and regulatory aspects for cognitive radio applications, and includes case studies for the exploitation of TVWS depending on user's mobility, and the geo-location between user and the Base Station.
eBook
A survey of dynamic spectrum allocation based on reinforcement learning algorithms in cognitive radio networks
Cognitive radio is an emerging technology that is considered to be an evolution for software device radio in which cognition and decision-making components are included. The main function of cognitive radio is to exploit “spectrum holes” or “white spaces” to address the challenge of the low utilization of radio resources. Dynamic spectrum allocation, whose significant functions are to ensure that cognitive users access the available frequency and bandwidth to communicate in an opportunistic manner and to minimize the interference between primary and secondary users, is a key mechanism in cognitive radio networks. Reinforcement learning, which rapidly analyzes the amount of data in a model-free manner, dramatically facilitates the performance of dynamic spectrum allocation in real application scenarios. This paper presents a survey on the state-of-the-art spectrum allocation algorithms based on reinforcement learning techniques in cognitive radio networks. The advantages and disadvantages of each algorithm are analyzed in their specific practical application scenarios. Finally, we discuss open issues in dynamic spectrum allocation that can be topics of future research.
Journal Article
Principles of Cognitive Radio
Widely regarded as one of the most promising emerging technologies for driving the future development of wireless communications, cognitive radio has the potential to mitigate the problem of increasing radio spectrum scarcity through dynamic spectrum allocation. Drawing on fundamental elements of information theory, network theory, propagation, optimisation and signal processing, a team of leading experts present a systematic treatment of the core physical and networking principles of cognitive radio and explore key design considerations for the development of new cognitive radio systems. Containing all the underlying principles you need to develop practical applications in cognitive radio, this book is an essential reference for students, researchers and practitioners alike in the field of wireless communications and signal processing.
eBook
Pricing Policy for a Dynamic Spectrum Allocation Scheme with Batch Requests and Impatient Packets in Cognitive Radio Networks
In cognitive radio networks (CRNs), multiple secondary users may send out requests simultaneously and one secondary user may send out multiple requests at one time, i.e., request arrivals usually show an aggregate manner. Moreover, a secondary user packet waiting in the buffer may leave the system due to impatience before it is transmitted, and this impatient behavior inevitably has an impact on the system performance. Aiming to investigate the influence of the aggregate behavior of requests and the likelihood of impatience on a dynamic spectrum allocation scheme in CRNs, in this paper a batch arrival queueing model with possible reneging and potential transmission interruption is established. By constructing a Markov chain and presenting a transition rate matrix, the steady-state distribution of the queueing model along with a dynamic spectrum allocation scheme is derived to analyze the stochastic behavior of the system. Accordingly, some important performance measures such as the loss rate, the balk rate and the average delay of secondary user packets are given. Moreover, system experiments are carried out to show the change trends of the performance measures with respect to batch arrival rates of secondary user packets for different impatience parameters, different batch sizes of secondary user packets, and different arrival rates of primary user packets. Finally, a pricing policy for secondary users is presented and the dynamic spectrum allocation scheme is socially optimized.
Journal Article
An IoT and machine learning‐based routing protocol for reconfigurable engineering application
With new telecommunications engineering applications, the cognitive radio (CR) network‐based internet of things (IoT) resolves the bandwidth problem and spectrum problem. However, the CR‐IoT routing method sometimes presents issues in terms of road finding, spectrum resource diversity and mobility. This study presents an upgradable cross‐layer routing protocol based on CR‐IoT to improve routing efficiency and optimize data transmission in a reconfigurable network. In this context, the system is developing a distributed controller which is designed with multiple activities, including load balancing, neighbourhood sensing and machine‐learning path construction. The proposed approach is based on network traffic and load and various other network metrics including energy efficiency, network capacity and interference, on an average of 2 bps/Hz/W. The trials are carried out with conventional models, demonstrating the residual energy and resource scalability and robustness of the reconfigurable CR‐IoT.
Journal Article
Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks
The rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs. A precise approximation of the power spectrum is essential to accomplish this. On the assumption that each SU’s parameter vector contains some globally and partially shared parameters, spectrum sensing is viewed as a parameter estimation issue. Distributed and cooperative spectrum sensing (CSS) is a key component of this concept. This work introduces a new component-specific cooperative spectrum sensing model (CSCSSM) in CRNs considering the amplitude and phase components of the input signal including Component Specific Adaptive Estimation (CSAE) for mean squared deviation (MSD) formulation. The proposed concept ensures minimum information loss compared to the traditional methods that consider error calculation among the direct signal vectors. The experimental results and performance analysis prove the robustness and efficiency of the proposed work over the traditional methods.
Journal Article
Issues, Challenges, and Research Trends in Spectrum Management: A Comprehensive Overview and New Vision for Designing 6G Networks
With an extensive growth in user demand for high throughput, large capacity, and low latency, the ongoing deployment of Fifth-Generation (5G) systems is continuously exposing the inherent limitations of the system, as compared with its original premises. Such limitations are encouraging researchers worldwide to focus on next-generation 6G wireless systems, which are expected to address the constraints. To meet the above demands, future radio network architecture should be effectively designed to utilize its maximum radio spectrum capacity. It must simultaneously utilize various new techniques and technologies, such as Carrier Aggregation (CA), Cognitive Radio (CR), and small cell-based Heterogeneous Networks (HetNet), high-spectrum access (mmWave), and Massive Multiple-Input-Multiple-Output (M-MIMO), to achieve the desired results. However, the concurrent operations of these techniques in current 5G cellular networks create several spectrum management issues; thus, a comprehensive overview of these emerging technologies is presented in detail in this study. Then, the problems involved in the concurrent operations of various technologies for the spectrum management of the current 5G network are highlighted. The study aims to provide a detailed review of cooperative communication among all the techniques and potential problems associated with the spectrum management that has been addressed with the possible solutions proposed by the latest researches. Future research challenges are also discussed to highlight the necessary steps that can help achieve the desired objectives for designing 6G wireless networks.
Journal Article
Gini Index Test Metric Based Collaborative Sensing of Spectrum for Cognitive Networks
The key confront for a cognitive radio network is to identify the presence of primary users consistently so as to curtail the intrusion to license approved communications. Consequently, sensing of spectrum is a main significant requisite of a cognitive network. Nevertheless, because of the ambiguity in the channel, local interpretations don’t provide a trustworthy solution and therefore collaboration is needed between the users. Collaborative spectrum sensing is a competent scheme to enhance the spectrum utility in wireless networks, which utilizes cooperation between multiple nodes to prevail over the inadequacy of single-node to improve the performance of detection. In this paper, a detailed investigation, simulation and comparative analysis of collaborative scheme for sensing the spectrum of cognitive networks based on Gini Index test metrics is done and the results are compared with various other detecting schemes. The simulation is accomplished by means of Matlab R2014 software.
Journal Article