• Title/Summary/Keyword: Cooperative Cognitive Radio Networks (CRNs)

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Resource Allocation in Multiuser Multi-Carrier Cognitive Radio Network via Game and Supermarket Game Theory: Survey, Tutorial, and Open Research Directions

  • Abdul-Ghafoor, Omar B.;Ismail, Mahamod;Nordin, Rosdiadee;Shaat, Musbah M.R.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.11
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    • pp.3674-3710
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    • 2014
  • In this tutorial, we integrate the concept of cognitive radio technology into game theory and supermarket game theory to address the problem of resource allocation in multiuser multicarrier cognitive radio networks. In addition, multiuser multicarrier transmission technique is chosen as a candidate to study the resource allocation problem via game and supermarket game theory. This tutorial also includes various definitions, scenarios and examples related to (i) game theory (including both non-cooperative and cooperative games), (ii) supermarket game theory (including pricing, auction theory and oligopoly markets), and (iii) resource allocation in multicarrier techniques. Thus, interested readers can better understand the main tools that allow them to model the resource allocation problem in multicarrier networks via game and supermarket game theory. In this tutorial article, we first review the most fundamental concepts and architectures of CRNs and subsequently introduce the concepts of game theory, supermarket game theory and common solution to game models such as the Nash equilibrium and the Nash bargaining solution. Finally, a list of related studies is highlighted and compared in this tutorial.

Physical Layer Security in Underlay CCRNs with Fixed Transmit Power

  • Wang, Songqing;Xu, Xiaoming;Yang, Weiwei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.1
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    • pp.260-279
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    • 2015
  • In this paper, we investigate physical layer security for multiple decode-and-forward (DF) relaying underlay cognitive radio networks (CRNs) with fixed transmit power at the secondary network against passive eavesdropping attacks. We propose a simple relay selection scheme to improve wireless transmission security based on the instantaneous channel information of all legitimate users and the statistical information about the eavesdropper channels. The closed-form expressions of the probability of non-zero secrecy capacity and the secrecy outage probability (SOP) are derived over independent and non-identically distributed Rayleigh fading environments. Furthermore, we conduct the asymptotic analysis to evaluate the secrecy diversity order performance and prove that full diversity is achieved by using the proposed relay selection. Finally, numerical results are presented to verify the theoretical analysis and depict that primary interference constrain has a significant impact on the secure performance and a proper transmit power for the second transmitters is preferred to be energy-efficient and improve the secure performance.

Cooperative Relaying with Interference Cancellation for Secondary Spectrum Access

  • Dai, Zeyang;Liu, Jian;Long, Keping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.10
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    • pp.2455-2472
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    • 2012
  • Although underlay spectrum sharing has been shown as a promising technique to promote the spectrum utilization in cognitive radio networks (CRNs), it may suffer bad secondary performance due to the strict power constraints imposed at secondary systems and the interference from primary systems. In this paper, we propose a two-phase based cooperative transmission protocol with the interference cancellation (IC) and best-relay selection to improve the secondary performance in underlay models under stringent power constraints while ensuring the primary quality-of-service (QoS). In the proposed protocol, IC is employed at both the secondary relays and the secondary destination, where the IC-based best-relay selection and cooperative relaying schemes are well developed to reduce the interference from primary systems. The closed-form expression of secondary outage probability is derived for the proposed protocol over Rayleigh fading channels. Simulation results show that, with a guaranteed primary outage probability, the proposed protocol can achieve not only lower secondary outage probability but also higher secondary diversity order than the traditional underlay case.

Artificial Neural Network with Firefly Algorithm-Based Collaborative Spectrum Sensing in Cognitive Radio Networks

  • Velmurugan., S;P. Ezhumalai;E.A. Mary Anita
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.7
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    • pp.1951-1975
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    • 2023
  • Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.