A Novel Sensing Strategy Based on Energy Detector for Spectrum Sensing

Huang, Hai; Zhu, Jia; Mu, Junsheng

doi:10.3390/app9214634

Cited by 2 publications

(3 citation statements)

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“…It has been found that, increasing L does not significantly affect the execution time. The authors in [46] derive an optimal threshold ξ opt for the detection task. A version of the traditional ED with an SNR-adaptive thresholding for multiple-input multiple-output (MIMO) systems is derived in [47].…”

Section: ) Generalized Energy Detection For Computational Optimizationmentioning

confidence: 99%

“…Implementation in real-world prototypes requires fast processing which can in the ED's case be provided by decreasing the number of samples used for the TS computation. Reliable detection can be achieved for SNR as low as −15 dB [46] with N being over 60 times smaller than the necessary for CLT approximation [33]. Substantial relaxation of N is possible even for some complex fading channels (such as Rayleigh/ Nakagami-2/α-κ-µ/α-η-µ) in γ < 0 dB [39], [65].…”

Section: ) Lessons Learnedmentioning

confidence: 99%

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Probabilistic Spectrum Sensing Based on Feature Detection for 6G Cognitive Radio: A Survey

et al. 2021

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With the advent of Sixth Generation (6G) telecommunication systems already envisioned, increased effort is made to further develop current communication technologies, so they can be incorporated together with the novel ones, to deliver uninterrupted and satisfactory service for any application in every location on the ground, underwater, in the air, or in space. One such technology is Cognitive Radio (CR) which has received much attention due to its potential for increase of utilization, especially in the bands below 6 GHz. The main enabler for CR is spectrum sensing because it provides the opportunity for dynamic assessment of the radio environment to identify unused channels. This functionality has been the object of many research works for that very reason. In spite of this, the provision of accurate and fast spectrum characterization in time, frequency and space has proven to be a non-trivial task. This paper presents a detailed review of probabilistic spectrum sensing methods classified by the feature they extract from the received signal samples, to provide accurate detection of the primary user (PU) signal. The main design characteristics (such as probability of detection, robustness to noise and fading, signal/noise model assumptions, and computational complexity), strengths and weaknesses for each type are also summarized. Based on current concepts for 6G networks and applications, a framework for human-centric cognition-based wireless access is presented, which specifies the role of spectrum sensing-based CR in future networks.INDEX TERMS 6G, cognitive radio, feature detection, human-centric wireless access, Internet of Things, probabilistic spectrum sensing, wireless communications.

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Section: ) Generalized Energy Detection For Computational Optimizationmentioning

confidence: 99%

Section: ) Lessons Learnedmentioning

confidence: 99%

Probabilistic Spectrum Sensing Based on Feature Detection for 6G Cognitive Radio: A Survey

et al. 2021

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“…Among the methods used for spectrum sensing, energy detection (ED) [4][5][6][7][8] is the most commonly used one, due to its simplicity as well as its almost universal applicability. Alternative spectrum sensing approaches use eigenvalue-based algorithms [9], covariance-based detection methods [10,11], cyclostationary feature detection [12,13], or compressive sensing [14,15].…”

Section: Introductionmentioning

confidence: 99%

Three-Event Energy Detection with Adaptive Threshold for Spectrum Sensing in Cognitive Radio Systems

Marțian

Sammarraie

Vlădeanu

et al. 2020

Sensors

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Implementation of dynamic spectrum access (DSA) in cognitive radio (CR) systems requires the unlicensed secondary users (SU) to implement spectrum sensing to monitor the activity of the licensed primary users (PU). Energy detection (ED) is one of the most widely used methods for spectrum sensing in CR systems, and in this paper we present a novel ED algorithm with an adaptive sensing threshold. The three-event ED (3EED) algorithm for spectrum sensing is considered for which an accurate approximation of the optimal decision threshold that minimizes the decision error probability (DEP) is found using Newton’s method with forced convergence in one iteration. The proposed algorithm is analyzed and illustrated with numerical results obtained from simulations that closely match the theoretical results and show that it outperforms the conventional ED (CED) algorithm for spectrum sensing.

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A Novel Sensing Strategy Based on Energy Detector for Spectrum Sensing

Cited by 2 publications

References 32 publications

Probabilistic Spectrum Sensing Based on Feature Detection for 6G Cognitive Radio: A Survey

Probabilistic Spectrum Sensing Based on Feature Detection for 6G Cognitive Radio: A Survey

Three-Event Energy Detection with Adaptive Threshold for Spectrum Sensing in Cognitive Radio Systems

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