Cognitive Radio Relay Networks with Multiple Primary and Secondary Users: Distributed Stable Matching Algorithms for Spectrum Access

Due to the rapid increase in wireless applications and the number of users, spectrum scarcity, energy consumption and latency issues will emerge, notably in the fifth generation (5G) system. Cognitive radio (CR) has emerged as the primary technology to address these challenges, allowing opportunist spectrum access as well as the ability to analyze, observe, and learn how to respond to environmental 5G conditions. The CR has the ability to sense the spectrum and detect empty bands in order to use underutilized frequency bands without causing unwanted interference with legacy networks. In this paper, we presented a spectrum sensing algorithm based on energy detection that allows secondary user SU to transmit asynchronously with primary user PU without causing harmful interference. This algorithm reduced the sensing time required to scan the whole frequency band by dividing it into n sub-bands that are all scanned at the same time. Also, this algorithm allows cognitive radio networks (CRN) nodes to select their operating band without requiring cooperation with licensed users. According to the BER, secondary users have better performance compared with primary users.

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Asynchronous Channel Allocation in Opportunistic Cognitive Radio Networks

Advances in Wireless Technologies and Telecommunication - Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management ◽

10.4018/978-1-4666-6571-2.ch015 ◽

2015 ◽

pp. 388-426

Author(s):

Sylwia Romaszko ◽

Petri Mähönen

Keyword(s):

Cognitive Radio ◽

Cognitive Radio Networks ◽

Channel Allocation ◽

Optimal Solution ◽

Radio Networks ◽

Traffic Patterns ◽

Spectrum Access ◽

Secondary Users ◽

Channel Parameters ◽

Channel Service

In the case of Opportunistic Spectrum Access (OSA), unlicensed secondary users have only limited knowledge of channel parameters or other users' information. Spectral opportunities are asymmetric due to time and space varying channels. Owing to this inherent asymmetry and uncertainty of traffic patterns, secondary users can have trouble detecting properly the real usability of unoccupied channels and as a consequence visiting channels in such a way that they can communicate with each other in a bounded period of time. Therefore, the channel service quality, and the neighborhood discovery (NB) phase are fundamental and challenging due to the dynamics of cognitive radio networks. The authors provide an analysis of these challenges, controversies, and problems, and review the state-of-the-art literature. They show that, although recently there has been a proliferation of NB protocols, there is no optimal solution meeting all required expectations of CR users. In this chapter, the reader also finds possible solutions focusing on an asynchronous channel allocation covering a channel ranking.

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Game Theoretic Cloud-Assisted Opportunistic Spectrum Access in Cognitive Radio Networks

International Journal of Grid and High Performance Computing ◽

10.4018/ijghpc.2016040106 ◽

2016 ◽

Vol 8 (2) ◽

pp. 94-110

Author(s):

Danda B. Rawat ◽

Sachin Shetty

Keyword(s):

Cognitive Radio ◽

Wide Band ◽

Cognitive Networks ◽

Opportunistic Spectrum Access ◽

Packet Error Rate ◽

Theoretic Approach ◽

Spectrum Access ◽

Secondary Users ◽

Computational Capacity ◽

Game Theoretic

Opportunistic Spectrum Access (OSA) in a Cognitive Radio Network (CRN) is regarded as emerging technology for utilizing the scarce Radio Frequency (RF) spectrum by allowing unlicensed secondary users (SUs) to access licensed spectrum without creating harmful interference to primary users (PUs). The SUs are considerably constrained by their limited power, memory and computational capacity when they have to make decision about spectrum sensing for wide band regime and OSA. The SUs in CRN have the potential to mitigate these constraints by leveraging the vast storage and computational capacity of cloud computing approaches. In this paper, the authors investigate a game theoretic approach for opportunistic spectrum access in cognitive networks. The proposed algorithm leverages the geo-locations of both SUs and spectrum opportunities to facilitate OSA to SUs. The active SUs using game theory adapt their transmit powers in a distributed manner based on the estimated average packet-error rate while satisfying the Quality-of-Service (QoS) in terms of signal-to-interference-noise-ratio (SINR). Furthermore, to control greedy SUs in distributed power control game, the authors introduce a manager/leader through a Stackelberg power adaptation game. The performance of the proposed approaches is investigated using numerical results obtained from simulations.

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Performance Evaluation of Geolocation Based Opportunistic Spectrum Access in Cloud-Assisted Cognitive Radio Networks

International Journal of Monitoring and Surveillance Technologies Research ◽

10.4018/ijmstr.2016010103 ◽

2016 ◽

Vol 4 (1) ◽

pp. 24-41

Author(s):

Swetha Reddy ◽

Isaac Cushman ◽

Danda B. Rawat ◽

Min Song

Keyword(s):

Cognitive Radio ◽

False Alarm ◽

Estimation Error ◽

Time Of Arrival ◽

Spectrum Access ◽

Angle Of Arrival ◽

Secondary Users ◽

Probability Of False Alarm ◽

Computing Platform ◽

Overall Performance

The popularity of cloud-assisted database-driven cognitive radio network (CRN) has increased significantly due to three main reasons; reduced sensing uncertainties (caused by the use of spectrum scanning and sensing techniques), FCC mandated use of a database for storing and utilizing idle channels, and leveraging cloud computing platform to process big data generated by wideband sensing and analyzing. In database-driven CRN, secondary users periodically query the database to find idle channels for opportunistic communications where secondary users use their geolocation (with the help of Global Positioning System - GPS) to find idle channels for given location and time. Use of GPS makes the overall CRN vulnerable where malicious users falsify their geolocations through GPS spoofing to find more channels. The other main drawback of GPS is estimation error while finding location of users and idle bands. Due to this there will be probability of misdetection and false alarm which will have its effect on overall performance and efficiency of the system. In this paper, the authors present a three-stage mechanism for detecting GPS spoofing attacks using angle of arrival, received signal strength and time of arrival. They also evaluate the probability of misdetection and probability of false alarm in this system while detecting location of secondary users. The authors evaluate the performance of the proposed approach using numerical results.

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Non-Cooperative Spectrum Access Strategy Based on Impatient Behavior of Secondary Users in Cognitive Radio Networks

Electronics ◽

10.3390/electronics8090995 ◽

2019 ◽

Vol 8 (9) ◽

pp. 995 ◽

Cited By ~ 1

Author(s):

Zeng ◽

Liu ◽

Wang ◽

Lan

Keyword(s):

Cognitive Radio ◽

Nash Equilibrium ◽

Learning Ability ◽

Equilibrium Strategy ◽

Spectrum Access ◽

Secondary Users ◽

Nash Equilibrium Strategy ◽

Pricing Scheme ◽

The Social ◽

Limited Spectrum

In the cognitive radio network (CRN), secondary users (SUs) compete for limited spectrum resources, so the spectrum access process of SUs can be regarded as a non-cooperative game. With enough artificial intelligence (AI), SUs can adopt certain spectrum access strategies through their learning ability, so as to improve their own benefit. Taking into account the impatience of the SUs with the waiting time to access the spectrum and the fact that the primary users (PUs) have preemptive priority to use the licensed spectrum in the CRN, this paper proposed the repairable queueing model with balking and reneging to investigate the spectrum access. Based on the utility function from an economic perspective, the relationship between the Nash equilibrium and the socially optimal spectrum access strategy of SUs was studied through the analysis of the system model. Then a reasonable spectrum pricing scheme was proposed to maximize the social benefits. Simulation results show that the proposed access mechanism can realize the consistency of Nash equilibrium strategy and social optimal strategy to maximize the benefits of the whole cognitive system.

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