Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT

Idrees, Zeba; Latif, Shahid; Usman, Muhammad; Gelani, Hasan Erteza; Zheng, Lirong

doi:10.1109/access.2021.3133336

Cited by 12 publications

(5 citation statements)

References 51 publications

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“…Compared with [20], it is obvious that the SINR in (5) is far better since it is the summation of several signals thanks to multiple antennae at the transmitter.…”

Section: Remarkmentioning

confidence: 99%

“…The performance of the CRNs studied widely in [4][5][6][7][8][9][10][11][12] while the performance of FCs was investigated in [13][14][15][16][17][18][19]. Particularly, authors in [4] addressed the channel estimation problem in the overlay CRNs based on the state transition probability method.…”

Section: Introductionmentioning

confidence: 99%

“…The results show that the proposed method outperforms the literature upto 40% relying on the setup parameters. A novel spectrum sensing algorithm for CR-based Internet-of-thing (IoT) was given in [5] to facilitate the efficiency and time sensitivity compared with other approaches. The outage performance of both primary and secondary networks in cognitive device-to-device (D2D) network was derived in the closed-form expressions in [6].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Performance on Cognitive Broadcasting Networks Employing Fountain Codes and Maximal Ratio Transmission

Nguyen¹,

Tu²,

Nguyen³

et al. 2023

RADIOENGINEERING

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The comprehensive performance of cognitive broadcasting networks employing Fountain codes (FC) and maximal ratio transmission (MRT) is investigated in the present paper. More precisely, the secondary transmitter (ST) employs Fountain code to effectively broadcast a common message such as a safety warning, security news, etc., to all secondary receivers (SRs) via underlay protocol of cognitive radio networks (CRNs). Different from works in the literature that are interested in studying the outage probability (OP), and the ergodic capacity of the CRNs. The present paper, on the other hand, focuses on the characteristics of the number of needed time slots to successfully deliver such a message. Particularly, we derive in closed-form expressions the cumulative distribution function (CDF), the probability mass function (PMF), and the average number of the required time slot to broadcast the message to all SRs. Additionally, we also provide the throughput of secondary networks (SNs). We point out the impact of some key parameters, i.e., the number of SRs and the number of transmit antennae at the secondary transmitter, on the performance of these considered metrics. Numerical results via the Monte-Carlo method are given to verify the accuracy of the derived framework as well as to highlight the influences of some essential parameters. Furthermore, we also compare the performance of the proposed networks with state-of-the-art and simulation results unveiling that the considered system consistently outperforms works in the literature.

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“…Compared with [20], it is obvious that the SINR in (5) is far better since it is the summation of several signals thanks to multiple antennae at the transmitter.…”

Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance on Cognitive Broadcasting Networks Employing Fountain Codes and Maximal Ratio Transmission

Nguyen¹,

Tu²,

Nguyen³

et al. 2023

RADIOENGINEERING

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show abstract

“…The goal of this routing mechanism was to obtain high throughput, efficient selection of routing paths, and optimization of the network. A Backward Traffic Difference (BTD) approach [37] was used for the estimation of energy efficient methods. This proposed scheme utilizes the sleep-wake schedule assignments that liable to the various traffics received in the network.…”

Section: Literature Surveymentioning

confidence: 99%

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Kumar,

Sharanya

2023

ijmst

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During the last decade, Cognitive Radio Network (CRN) technology has been a significant advance in addressing the ever-increasing spectrum demand. As the number of licensed and unlicensed users in a network rises to complete a certain activity, the information exchange between various types of traffic becomes more complex and difficult. Congestion in CRN is also caused by the conflict among several users for channel access (PUs and SUs). In a very crowded network, many applications perform badly owing to packet collisions and, as a result, packet loss before significant buffer queue building. This circumstance is aggravated by an increase in network users. Congestion control is a vital and essential aspect of the present research issue in communication networks. Several recent reviews in the literature indicate that the congestion issue in the CRN has not been thoroughly studied. Thus, effective and efficient congestion control strategies are sought to optimize network resource usage and management. To prevent congestion, it is crucial for CRN to do research on the creation of an efficient congestion management system. This will improve the network's resource consumption and performance. "Performance improvement via efficient spectrum management through optimum resource management and congestion control in the CRN by mitigating different threats" is the primary target of this project. This research also focused on enhancing performance by addressing security issues in an IoT-based CRN environment. This study provides a comprehensive review of several similar studies and their limitations, which may be used to formulate a new research target.

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“…This method guarantees that subsequent usage of the spectrum by secondary opportunistic users does not result in significant interference with the primary source communications and vice versa. The above is a particular paradigm of a Cognitive Radio (CR)-enabled IoT network [2], which injects high-level intelligence into IoT networks and assists sensor nodes in using the available spectrum without interfering with the primary sources. In addition, it improves the whole system throughput compared to traditional homogeneous network topologies [3] (i.e., classical cellular, ad hoc), and as a promising enabler communication technology for the IoT, it attains the levels of performance and efficiency required by future wireless communications.…”

Section: Introductionmentioning

confidence: 99%

Detection of Transmission State of Multiple Wireless Sources: A Statistical Mechanics Approach

Evangelatos,

Moustakas

2023

Telecom

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Consider a random network of static primary wireless sources and a co-located network of secondary wireless devices. The channel coefficients between the two networks are assumed to be known to the secondary users (SUs), e.g., using radio environment maps (REM). However, the operational state of the sources is unknown due to intermittency. In this paper, we study the performance of primary source detection by SUs using a message-passing algorithm. Additionally, we employ methods from statistical mechanics, in particular, the Replica approach, to obtain analytic results for the performance of such networks in the large system-size limit. We test the results through a large-scale simulation analysis, obtaining good agreement. The proposed method provides a simple way to evaluate the performance of the system and assess how it depends on the macroscopic parameters that characterize it, such as the average density of SUs and sources and the signal-to-noise ratio. The main contribution of this paper is the application of an algorithm that quantitatively predicts the parameter value region for which accurate and reliable detection of the operational state of the primary sources can be achieved in a fast and decentralized manner.

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Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT

Cited by 12 publications

References 51 publications

Performance on Cognitive Broadcasting Networks Employing Fountain Codes and Maximal Ratio Transmission

Performance on Cognitive Broadcasting Networks Employing Fountain Codes and Maximal Ratio Transmission

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Detection of Transmission State of Multiple Wireless Sources: A Statistical Mechanics Approach

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