Role of Artificial Intelligence in Cognitive Radio Networks

2019 ◽  
pp. 258-279 ◽  
Author(s):  
Shikha Singhal ◽  
Shashank Gupta ◽  
Adwitiya Sinha
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Evolutionary Process ◽  
Radio Spectrum ◽  
Radio Networks ◽  
Training Dataset ◽  
Wireless Medium ◽  
Computing Machines

The role of artificial intelligence techniques and its impact in context of cognitive radio networks has become immeasurable. Artificial intelligence redefines and empowers the decision making and logical capability of computing machines through the evolutionary process of leaning, adapting, and upgrading its knowledge bank accordingly. Significant functionalities of artificial intelligence include sensing, collaborating, learning, evolving, training, dataset, and performing tasks. Cognitive radio enables learning and evolving through contextual data perceived from its immediate surrounding. Cognitive science aims at acquiring knowledge by observing and recording externalities of environment. It allows self-programming and self-learning with added intelligence and enhanced communicational capabilities over wireless medium. Equipped with cognitive technology, the vision of artificial intelligence gets broadened towards optimizing usage of radio spectrum by accessing spectrum availability, thereby reducing channel interferences while communication among licensed and non-licensed users.

scholarly journals Adaptive dual-radio spectrum-sensing scheme in cognitive radio networks

2011 ◽  
Vol 13 (14) ◽  
pp. 1247-1262 ◽  
Author(s):  
Weiwei Wang ◽  
Jun Cai ◽  
Attahiru S. Alfa ◽  
Anthony C.K. Soong ◽  
Simin Li
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Spectrum ◽  
Radio Networks

Cognitive Radio Networks

2019 ◽  
pp. 491-518 ◽  
Author(s):  
Nitin Gupta ◽  
Sanjay Kumar Dhurandher ◽  
Bhoopendra Kumar
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Spectrum Sharing ◽  
Dynamic Spectrum Access ◽  
Radio Spectrum ◽  
Radio Networks ◽  
New Paradigm ◽  
Medium Access ◽  
Recent Developments ◽  
Limited Spectrum

The radio spectrum is witnessing a major paradigm shift from fixed spectrum assignment policy to the dynamic spectrum access, which will completely change the way radio spectrum is managed. This step is required to greatly reduce the load on limited spectrum resources, which is being enforced by the exponential growth of wireless services. This is only feasible due to the capabilities of the cognitive radio, which will provide a new paradigm in wireless communication by exploiting the existing unused spectrum bands opportunistically. The chapter provides insight into recent developments in the area of cognitive radio networks with the main focus on review of the spectrum management, which consists of four main challenges: sensing of selected spectrum band, decision about sensed spectrum, sharing of spectrum among many users, and spectrum handoff. Further, sharing of target channel after a channel handoff is analyzed using game theory to get a different perspective on the existing medium access techniques.

AI in Cognitive Radio Networks

2020 ◽  
pp. 192-209
Author(s):  
Preetjot Kaur ◽  
Roopali Garg
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Radio ◽  
Literature Review ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Self Awareness ◽  
Self Learning ◽  
State Of Art ◽  
Structure Association

This chapter provides a-state-of-art of artificial intelligence (AI) techniques applied to cognitive radio networks. Cognitive radio (CR) is an empowering innovation for various new opportunities, for example, spectrum sensing, access, markets, and self-organizing networks. Its target is to enable the system to exploit the available resources through self-learning and to adapt itself accordingly to the sensed environment. To understand this plethora of applications, CR researchers often make use of several types of AI techniques. By utilizing AI, the network system can immediately complete self-awareness learning, structure association, and scheduling several tasks. To help researchers obtain a healthier knowledge of AI techniques along with CR, this chapter presents several such implementations that have already been applied. Finally, the literature review of the best accomplishments in applying AI techniques to CRs is presented and classified according to the major techniques of artificial intelligence.

Cross-Layer Design in Cognitive Radio Networks

2012 ◽  
pp. 282-310 ◽  
Author(s):  
Bin Wang ◽  
Zhiqiang Wu ◽  
Zhongmei Yao
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Dynamic Spectrum Access ◽  
Radio Spectrum ◽  
Radio Networks ◽  
Opportunistic Spectrum Access ◽  
Future Research ◽  
Cross Layer ◽  
Spectrum Access ◽  
Frequency Bands

Radio spectrum has become a precious resource. Most frequency bands have been allocated for exclusive use in the US. However, studies have shown that a very large portion of the radio spectrum is unused or underused for long periods of time at a given geographic location. Therefore, allowing users without a license to operate in licensed bands while causing no interference to the license holder becomes a promising way to satisfy the fast growing need for spectrum resources. Dynamic spectrum access and cognitive radio are technologies for enabling opportunistic spectrum access and enhancing the efficiency and utilization of the spectrum. A cognitive radio adapts to the environment in which it operates by sensing the spectrum and then opportunistically exploiting unused and/or underused frequency bands in order to achieve certain performance goals. Due to the close coupling and interaction among protocol layers, the optimal design of opportunistic spectrum access and cognitive radio networks calls for a cross-layer approach that integrates signal processing and networking with regulatory policy making. This chapter introduces basic concepts, design issues involved, and some recent development in this emerging technological field. Future research directions are also briefly examined.

A SURVEY OF IMPLEMENTATION OF OPPORTUNISTIC SPECTRUM ACCESS ATTACK WITH ITS PREVENTIVE SENSING PROTOCOLS IN COGNITIVE RADIO NETWORKS

2015 ◽  
Vol 3 (6) ◽  
pp. 389
Author(s):  
Monisha Ravi ◽  
Nisha Ravi ◽  
N. Ravi
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Primary User ◽  
Radio Spectrum ◽  
Radio Networks ◽  
Spectrum Efficiency ◽  
Network Simulator ◽  
Secondary Users ◽  
Primary User Emulation Attack ◽  
Research Areas

Recently, the expansive growth of wireless services, regulated by governmental agencies assigning spectrum to licensed users, has led to a shortage of radio spectrum. Since the FCC (Federal Communications Commissions) approved unlicensed users to access the unused channels of the reserved spectrum, new research areas seeped in, to develop Cognitive Radio Networks (CRN), in order to improve spectrum efficiency and to exploit this feature by enabling secondary users to gain from the spectrum in an opportunistic manner via optimally distributed traffic demands over the spectrum, so as to reduce the risk for monetary loss, from the unused channels. However, Cognitive Radio Networks become vulnerable to various classes of threats that decrease the bandwidth and spectrum usage efficiency. Hence, this survey deals with defining and demonstrating framework of one such attack called the Primary User Emulation Attack and suggests preventive Sensing Protocols to counteract the same. It presents a scenario of the attack and its prevention using Network Simulator-2 for the attack performances and gives an outlook on the various techniques defined to curb the anomaly.

TRUST-BASED SPECTRUM SHARING FOR COGNITIVE RADIO NETWORKS

2011 ◽  
Vol 12 (03) ◽  
pp. 155-171 ◽  
Author(s):  
SAZIA PARVIN ◽  
FAROOKH KHADEER HUSSAIN ◽  
SONG HAN ◽  
OMAR KHADEER HUSSAIN
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Spectrum Sharing ◽  
Stochastic Approach ◽  
Radio Spectrum ◽  
Spectrum Management ◽  
Radio Networks ◽  
Secondary Users ◽  
Reliable Technique ◽  
Free Spectrum

Cognitive Radio Networks (CRNs) is a promising technology which deals with shared spectrum access and usage in order to improve the utilization of limited radio spectrum resources for future wireless communications and mobile computing. Security becomes a very challenging issue in CRNs as different types of attacks are very common to cognitive radio technology compared to general wireless networks. The proper working of cognitive radio and the functionality of CRNs relies on the compliant behaviour of the secondary user. In order to address this issue, we propose two approaches in this paper. Firstly, we propose a trust aware model to authenticate the secondary users of CRNs which offers a reliable technique to provide a security-conscious decision by using trust evaluation for CRNs. Secondly, we propose an analytical model for analyzing the availability of spectrum in CRNs using a stochastic approach. We have modeled and analyzed the availability of free spectrum for the usage of secondary users by adopting different activities in a spectrum management scheme to improve the spectrum availability in CRNs.

scholarly journals A Spectrum Sensing Method for TDM based Cognitive Radio Networks

2018 ◽  
Vol 7 (4.1) ◽  
pp. 124
Author(s):  
D Satyanarayana ◽  
Abdullah Said Alkalbani
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
New Technology ◽  
Radio Spectrum ◽  
Radio Networks ◽  
Second Phase ◽  
Spectrum Scarcity ◽  
Spectrum Hole ◽  
Two Phases ◽  
Hole Detection

The usage of mobile radio devices has been increased exponentially for the last few years and the radio spectrum is being exhausted every day. Hence, there is huge demand for new methods and technologies for solving the radio spectrum scarcity. On this line, the researchers invented a new technology called Cognitive Radio Networks (CRN). There are two phases associated with the CRN. The first phase handles the spectrum hole detection and the second phase allocates the spectrum hole. In this paper, we propose a new method for spectrum hole detection in time division multiplexing (TDM) based communications systems. The simulation work shows that the proposed method is useful for solving the spectrum scarcity problems in TDM based systems.   

Cross-Layer Design for Cognitive Radio Networks

2012 ◽  
pp. 219-237
Author(s):  
M. Ayyash ◽  
Y. Al-Sbou
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Interference Management ◽  
Radio Spectrum ◽  
Radio Networks ◽  
Cognitive Networks ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Network Resources ◽  
Key Issues

Nowadays, due to the tremendous growth of wireless communications technologies and multimedia applications, the radio spectrum is starting to be crowded and scarce to meet the continuous growth of frequency requirements. Additionally, interference management is one of the key issues in wireless networks. Therefore, network solutions and evolutions have crucial challenges to overcome the inefficiency in configuring and managing network resources. To optimize wireless network operations and spectrum scarcity, a new networking paradigm, known as cognitive radio networks (CRNs), has been introduced. Due to the limited capabilities of the conventional layered protocol, CRNs adjust layer parameters adaptively according to the spectrum environment and Quality of Service (QoS) requirements. Hence, cross-layer design (CLD) solutions were necessary to allow for improving and optimizing CRNs performance. This chapter provides an extensive and exclusive overview of cognitive networks, CLD methodologies and properties, and cross-layer optimization (CLO) schemes among different layers. Moreover, it presents possible research solutions for cognitive networking. Finally, indispensable highlights of future work research directions are provided.

MAC Layer Spectrum Sensing in Cognitive Radio Networks

2013 ◽  
pp. 210-230
Author(s):  
Mohamed Hamid ◽  
Abbas Mohammed
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Performance Metrics ◽  
Computational Cost ◽  
Radio Spectrum ◽  
Radio Networks ◽  
Superior Performance ◽  
Mac Layer ◽  
Spectrum Utilization ◽  
Network Nodes

Efficient use of the available licensed radio spectrum is becoming increasingly difficult as the demand and usage of the radio spectrum increases. This usage of the spectrum is not uniform within the licensed band but concentrated in certain frequencies of the spectrum while other parts of the spectrum are inefficiently utilized. In cognitive radio environments, the primary users are allocated licensed frequency bands while secondary cognitive users can dynamically allocate the empty frequencies within the licensed frequency band, according to their requested quality of service specifications. In this chapter, the authors investigate and assess the performance of MAC layer sensing schemes in cognitive radio networks. Two performance metrics are used to assess the performance of the sensing schemes: the available spectrum utilization and the idle channel search delay for reactive and proactive sensing schemes. In proactive sensing, the adapted and non-adapted sensing period schemes are also assessed. Simulation results show that proactive sensing with adapted periods provides superior performance at the expense of higher computational cost performed by network nodes.

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