R. Saravanan^1,*, R. Muthaiah¹, A. Rajesh²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2339-2356, 2024, DOI:10.32604/cmes.2023.030898 - 15 December 2023

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

Zeliang An¹, Tianqi Zhang^1,*, 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 - 08 October 2023

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 >

Shayla Islam¹, Anil Kumar Budati^1,*, 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 - 23 April 2023

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 >

Omar Abdulghafoor¹, Musbah Shaat², Ibraheem Shayea³, Ahmad Hamood¹, Abdelzahir Abdelmaboud⁴, Ashraf Osman Ibrahim⁵, Fadhil Mukhlif^6,*, 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 - 31 March 2023

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 >

Saifur Rahman Sabuj¹, Mohammad Saadman Alam², Majumder Haider², Md Akbar Hossain³, Al-Sakib Khan Pathan^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2023.024078 - 06 February 2023

Abstract This paper discusses the significance and prospects of low altitude small satellite aerial vehicles to ensure smooth aerial-ground communications for next-generation broadband networks. To achieve the generic goals of fifthgeneration and beyond wireless networks, the existing aerial network architecture needs to be revisited. The detailed architecture of low altitude aerial networks and the challenges in resource management have been illustrated in this paper. Moreover, we have studied the coordination between promising communication technologies and low altitude aerial networks to provide robust network coverage. We talk about the techniques that can ensure userfriendly control and monitoring More > Graphic Abstract

R. Nandakumar¹, Vijayakumar Ponnusamy^2,*, Aman Kumar Mishra²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2805-2819, 2023, DOI:10.32604/iasc.2023.028645 - 17 August 2022

Abstract In the Internet of Things (IoT) scenario, many devices will communicate in the presence of the cellular network; the chances of availability of spectrum will be very scary given the presence of large numbers of mobile users and large amounts of applications. Spectrum prediction is very encouraging for high traffic next-generation wireless networks, where devices/machines which are part of the Cognitive Radio Network (CRN) can predict the spectrum state prior to transmission to save their limited energy by avoiding unnecessarily sensing radio spectrum. Long short-term memory (LSTM) is employed to simultaneously predict the Radio Spectrum More >

Nada M. Elfatih¹, Elmustafa Sayed Ali^1,5, Maha Abdelhaq², Raed Alsaqour^3,*, Rashid A. Saeed⁴

Computer Systems Science and Engineering, Vol.45, No.1, pp. 329-342, 2023, DOI:10.32604/csse.2023.028528 - 16 August 2022

Abstract

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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C. Ambhika^1,*, C. Murukesh²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 827-838, 2023, DOI:10.32604/iasc.2023.026832 - 06 June 2022

Abstract With the demand for wireless technology, Cognitive Radio (CR) technology is identified as a promising solution for effective spectrum utilization. Connectivity and robustness are the two main difficulties in cognitive radio networks due to their dynamic nature. These problems are solved by using clustering techniques which group the cognitive users into logical groups. The performance of clustering in cognitive network purely depends on cluster head selection and parameters considered for clustering. In this work, an adaptive neuro-fuzzy inference system (ANFIS) based clustering is proposed for the cognitive network. The performance of ANFIS improved using hybrid More >

N. Sureka^*, K. Gunaseelan

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1893-1906, 2022, DOI:10.32604/iasc.2022.026098 - 25 May 2022

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 >

Raed Alhamad^*

Computer Systems Science and Engineering, Vol.43, No.2, pp. 751-765, 2022, DOI:10.32604/csse.2022.021932 - 20 April 2022

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 P_S activity. When P_S activity is not detected, The Secondary Source S_S transmits data to Secondary Destination S_D where all reflected signals on IRS are in phase at S_D. 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 >