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  • Open Access


    Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

    R. Saravanan1,*, R. Muthaiah1, A. Rajesh2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2339-2356, 2024, DOI:10.32604/cmes.2023.030898

    Abstract This study develops an Enhanced Threshold Based Energy Detection approach (ETBED) for spectrum sensing in a cognitive radio network. The threshold identification method is implemented in the received signal at the secondary user based on the square law. The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing. Additionally, the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems. In the dynamic threshold, the signal ratio-based threshold is fixed. The threshold is computed by considering the Modified Black Widow Optimization… More > Graphic Abstract

    Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

  • Open Access


    AI-Driven FBMC-OQAM Signal Recognition via Transform Channel Convolution Strategy

    Zeliang An1, Tianqi Zhang1,*, Debang Liu1, Yuqing Xu2, Gert Frølund Pedersen2, Ming Shen2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2817-2834, 2023, DOI:10.32604/cmc.2023.037832

    Abstract With the advent of the Industry 5.0 era, the Internet of Things (IoT) devices face unprecedented proliferation, requiring higher communications rates and lower transmission delays. Considering its high spectrum efficiency, the promising filter bank multicarrier (FBMC) technique using offset quadrature amplitude modulation (OQAM) has been applied to Beyond 5G (B5G) industry IoT networks. However, due to the broadcasting nature of wireless channels, the FBMC-OQAM industry IoT network is inevitably vulnerable to adversary attacks from malicious IoT nodes. The FBMC-OQAM industry cognitive radio network (ICRNet) is proposed to ensure security at the physical layer to tackle… More >

  • Open Access


    Performance Analysis of Three Spectrum Sensing Detection Techniques with Ambient Backscatter Communication in Cognitive Radio Networks

    Shayla Islam1, Anil Kumar Budati1,*, Mohammad Kamrul Hasan2, Saoucene Mahfoudh3, Syed Bilal Hussian Shah3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 813-825, 2023, DOI:10.32604/cmes.2023.027595

    Abstract In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promising approach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio (SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambient Radio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum for the transmission of data without loss or without collision at a specific time. In this paper, the authors proposed a novel Spectrum Sensing (SS) detection technique in the Cognitive… More >

  • Open Access


    Efficient Resource Allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

    Omar Abdulghafoor1, Musbah Shaat2, Ibraheem Shayea3, Ahmad Hamood1, Abdelzahir Abdelmaboud4, Ashraf Osman Ibrahim5, Fadhil Mukhlif6,*, Herish Badal1, Norafida Ithnin6, Ali Khadim Lwas7

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3045-3064, 2023, DOI:10.32604/cmc.2023.033888

    Abstract The computational complexity of resource allocation processes, in cognitive radio networks (CRNs), is a major issue to be managed. Furthermore, the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users, CRs, and primary users, PUs, exist in the identical geographical area. Hence, this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarios while limiting interference to PUs to allowable threshold. Hence, this paper, compared to other frameworks proposed in the literature, proposes a two-step approach… More >

  • Open Access


    A Double Threshold Energy Detection-Based Neural Network for Cognitive Radio Networks

    Nada M. Elfatih1, Elmustafa Sayed Ali1,5, Maha Abdelhaq2, Raed Alsaqour3,*, Rashid A. Saeed4

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 329-342, 2023, DOI:10.32604/csse.2023.028528


    In cognitive radio networks (CoR), the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability. Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection. However, these methods do not take into account the effect of sample size and its effect on improving CoR performance. In general, a large sample size results in more reliable detection, but takes longer sensing time and increases complexity. Thus, the locally sensed sample size is an optimization problem. Therefore, optimizing the local

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  • Open Access


    Enhanced Primary User Emulation Attack Inference in Cognitive Radio Networks Using Machine Learning Algorithm

    N. Sureka*, K. Gunaseelan

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1893-1906, 2022, DOI:10.32604/iasc.2022.026098

    Abstract Cognitive Radio (CR) is a competent technique devised to smart sense its surroundings and address the spectrum scarcity issues in wireless communication networks. The Primary User Emulation Attack (PUEA) is one of the most serious security threats affecting the performance of CR networks. In this paper, machine learning (ML) principles have been applied to detect PUEA with superior decision-making ability. To distinguish the attacking nodes, Reinforced Learning (RL) and Extreme Machine Learning (EML-RL) algorithms are proposed to be based on Reinforced Learning (EML). Various dynamic parameters like estimation error, attack detection efficiency, attack estimation rate, More >

  • Open Access


    Cognitive Radio Networks Using Intelligent Reflecting Surfaces

    Raed Alhamad*

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 751-765, 2022, DOI:10.32604/csse.2022.021932

    Abstract In this article, we optimize harvesting and sensing duration for Cognitive Radio Networks (CRN) using Intelligent Reflecting Surfaces (IRS). The secondary source harvests energy using the received signal from node A. Then, it performs spectrum sensing to detect Primary Source PS activity. When PS activity is not detected, The Secondary Source SS transmits data to Secondary Destination SD where all reflected signals on IRS are in phase at SD. We show that IRS offers 14, 20, 26, 32, 38, 44, 50 dB enhancement in throughput using M = 8, 16, 32, 64, 128, 256, 512 reflectors with respect to CRN without… More >

  • Open Access


    Cross Layer QoS Aware Scheduling based on Loss-Based Proportional Fairness with Multihop CRN

    K. Saravanan1,*, G. M. Tamilselvan2, A. Rajendran3

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1063-1077, 2022, DOI:10.32604/csse.2022.020789

    Abstract As huge users are involved, there is a difficulty in spectrum allocation and scheduling in Cognitive Radio Networks (CRNs). Collision increases when there is no allocation of spectrum and these results in huge drop rate and network performance degradation. To solve these problems and allocate appropriate spectrum, a novel method is introduced termed as Quality of Service (QoS) Improvement Proper Scheduling (QIPS). The major contribution of the work is to design a new cross layer QoS Aware Scheduling based on Loss-based Proportional Fairness with Multihop (QoSAS-LBPFM). In Medium Access Control (MAC) multi-channel network environment mobile More >

  • Open Access


    Securing Privacy Using Optimization and Statistical Models in Cognitive Radio Networks

    R. Neelaveni1,*, B. Sridevi2, J. Sivasankari3

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 523-533, 2022, DOI:10.32604/csse.2022.021433

    Abstract Cognitive Radio Networks (CRN) are the possible and ideal solution for meeting the spectrum needs of next-generation communication systems. CRN is a promising alternative approach that allows spectrum sharing in many applications. The licensed users considered Primary Users (PU) and unlicensed users as Secondary Users (SU). Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service (QoS). Irrespective of using different optimization techniques, the same methodology is to be updated for the task. So that, learning and optimization go hand in hand. It ensures the security… More >

  • Open Access


    An Effective Secure MAC Protocol for Cognitive Radio Networks

    Bayan Al-Amri1, Gofran Sami2, Wajdi Alhakami1,*

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 133-148, 2022, DOI:10.32604/csse.2022.021543

    Abstract The vast revolution in networking is increasing rapidly along with technology advancements, which requires more effort from all cyberspace professionals to cope with the challenges that come with advanced technology privileges and services. Hence, Cognitive Radio Network is one of the promising approaches that permit a dynamic type of smart network for improving the utilization of idle spectrum portions of wireless communications. However, it is vulnerable to security threats and attacks and demands security mechanisms to preserve and protect the cognitive radio networks for ensuring a secure communication environment. This paper presents an effective secure More >

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