Energy efficiency in cognitive radio network using cooperative spectrum sensing based on hybrid spectrum handoff

Arshid, Kaleem; Zhang, Jianbiao; Hussain, Iftikhar; Pathan, Muhammad Salman; Yaqub, Muhammad; Jawad, Abdul; Munir, Rizwan; Ahmad, Fahad

doi:10.1016/j.eij.2022.06.008

Cited by 18 publications

(4 citation statements)

References 46 publications

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“…Classical local techniques can also be part of a cooperative framework for spectrum sensing, which is usually employed to increase the detection reliability in either a centralized (e.g., Fusion Center), decentralized, or relay-assisted manner [27][28][29]. In [30,31], cooperative spectrum sensing methods are suggested based on an energy detector.…”

Section: Recent Methods and Motivationmentioning

confidence: 99%

An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks

Trigka

Δρίτσας

2022

Sensors

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The rapid growth in wireless communications, coupled with insufficient utilization of the spectrum, led to the development of new wireless services and the promising technology of cognitive radio (CR) networks, which facilitate periodic access to the unoccupied spectrum bands and thus increases spectral efficiency. A fundamental task in CR networks is spectrum sensing, through which unauthorized secondary users (SUs) detect unoccupied bands in the spectrum. To achieve this, an accurate estimate of the power spectrum is necessary. From this perspective, and given that many other factors can affect individual detection, such as pathloss and receiver uncertainty, we aim to improve its estimate by exploiting the spatial diversity in the SUs’ observations. Spectrum sensing is treated as a parameters estimation problem, assuming that the parameters’ vector of each SU consists of some global and partially common parameters. To exploit this modeling, distributed and cooperative spectrum sensing is the subject of interest in this study. Diffusion techniques, and especially the Adapt-Then-Combine (ATC) method will be exploited, where each SU cooperates with a group of nodes in its neighborhood that share the same parameters of interest. We consider a network of three static PUs with overlapping power spectrums, and thus, frequency bands. The performance of the employed method will be evaluated under two scenarios: (i) when the PUs spectrum varies, since some frequency bands are not yet utilized, and (ii) when the frequency bands of the PUs are fixed, but there is a mobile SU in the network, changing regions and parameters of interest. Experimental results and performance analysis reveal the ATC algorithm robustness and efficiency.

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Section: Recent Methods and Motivationmentioning

confidence: 99%

An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks

Trigka

Δρίτσας

2022

Sensors

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“…A cognitive radio's constant spectrum sensing method outcomes in low data transmission and high energy consumption, especially in areas with large population densities. Spectrum sensing takes care of the CR's energy usage in the promising technology known as energy harvesting in CRNs [5]. Energy harvesters have the strong ability to capture and store energy from different energy sources as well as ambient energy.…”

Section: Y R (N)mentioning

confidence: 99%

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

Saravanan,

Muthaiah,

Rajesh

2024

CMES

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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 Algorithm (MBWO). So, the proposed methodology is a combination of dynamic threshold detection and MBWO. The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal. These limitations undermine the sensing accuracy of the energy identification technique. Hence, the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks. The projected approach is executed and analyzed with performance and comparison analysis. The proposed method is contrasted with the conventional techniques of the Whale Optimization Algorithm (WOA) and Grey Wolf Optimization (GWO). It indicated superior results, achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8, outperforming conventional techniques. KEYWORDSCognitive radio network; spectrum sensing; noise uncertainty; modified black widow optimization algorithm; energy detection technique Abbreviation Λ slc Complete test statistics of complete signals identified based on receiver chains of the secondary user Λ R Test statistics for signals identified at the receiver chain of the secondary chain n Complete number of secondary users of receiver chains r Count of secondary users in receiver chains

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“…In 2022, Arshid et al [ 32 ] deployed a user transmission system that senses available channels through cooperative spectrum sensing. Energy economy was achieved by optimizing the energy consumption of the sensing process.…”

Section: Literature Reviewmentioning

confidence: 99%

Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks

Vaduganathan,

Neware,

Falkowski-Gilski

et al. 2023

Entropy

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The rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs. A precise approximation of the power spectrum is essential to accomplish this. On the assumption that each SU’s parameter vector contains some globally and partially shared parameters, spectrum sensing is viewed as a parameter estimation issue. Distributed and cooperative spectrum sensing (CSS) is a key component of this concept. This work introduces a new component-specific cooperative spectrum sensing model (CSCSSM) in CRNs considering the amplitude and phase components of the input signal including Component Specific Adaptive Estimation (CSAE) for mean squared deviation (MSD) formulation. The proposed concept ensures minimum information loss compared to the traditional methods that consider error calculation among the direct signal vectors. The experimental results and performance analysis prove the robustness and efficiency of the proposed work over the traditional methods.

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Energy efficiency in cognitive radio network using cooperative spectrum sensing based on hybrid spectrum handoff

Cited by 18 publications

References 46 publications

An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks

An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks

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

Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks

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