Energy Detection Technique for Adaptive Spectrum Sensing

Sobrón, Iker; Diniz, Paulo S. R.; Martins, Wallace A.; Vélez, Manuel

doi:10.1109/tcomm.2015.2394436

Cited by 120 publications

(69 citation statements)

References 24 publications

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“…Due to the simplicity and relevance, energy detection technique has been a preferred approach for many spectrum sensing studies and this approach is adopted in this research work. An energy detector, simply measures the energy received on a primary band during an observation period and declares the band as occupied if the measured energy is greater than a properly set threshold, or unoccupied otherwise [11], [21], [22], [23], [24]. Thus, the test statistic for the conventional energy detector is given by:…”

Section: Energy Detectionmentioning

confidence: 99%

Optimal Allocation Techniques for Reducing the Sensing Error Probability with Improved Energy Detection in Cognitive Radio

Кумар

Pal²

2017

IJARCSSE

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Abstract-In cognitive radio, spectrum sensing is one of the important tasks and is used to detect primary users. Energy detection is used for the spectrum sensing when the prior information about the primary users is not available. In this paper an improved version of energy detection is reported by increasing the detection performance. In this work sensing error probability is reduced by using an algorithm to improve the energy detection, here a decision statistic is computed by an arbitrary positive index p in place of squaring operation. An optimal value of threshold is derived which is satisfying a minimum error probability and derived the minimum number of samples required to achieve a target error probability. Keywords-cognitive radio, spectrum sensing, energy detection, improved energy detection, sensing error probability. [7] has emerged as a promising solution that can effectively deal with the existing conflicts between spectrum demand growth and spectrum underutilization. CR aims at improving spectrum usage efficiency by allowing some unlicensed (secondary) users to access in an opportunistic and non-interfering manner to some licensed bands temporarily unoccupied by the licensed (primary) users. I. INTRODUCTIONOne of the most important challenges for a CR network is not to cause harmful interference to primary users. To guarantee interference-free spectrum access, secondary users should reliably identify the presence of primary users, which basically aims to determine whether a primary signal is present within a certain frequency range. The spectrum utilization can be improved by allowing an unlicensed or secondary user (SU) to access a licensed frequency band at the time when the licensed or primary user (PU) is absent. In cognitive radio, SU senses an idle frequency band of a PU, and if a band is found to be idle, SU may transmit over that band. But as soon as PU returns, SU must vacate the band immediately. This complete process requires accurate spectrum sensing to avoid harmful interference to PU. There are number of different spectrum sensing techniques that have been proposed so far such as likelihood ratio test [8] [18]. ED does not require a prior knowledge about primary signals, it is less complex and easy to implement than the other spectrum sensing techniques. In this method the energy of the received signal is compared with a pre-evaluated threshold and it is a non coherent technique. In the most generic case, a CR user is not expected to be provided with any prior information about the primary signals that may be present within a certain frequency band. When the secondary receiver cannot gather sufficient information, the energy detection principle [16] can be used due to its ability to work irrespective of the signal structure to be detected. Therefore energy detection technique is preferred when sufficient information is not available about PUs. While other techniques depend on the detection accuracy, sensing time, information availability about primary signals and a complicated compu...

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Section: Energy Detectionmentioning

confidence: 99%

Optimal Allocation Techniques for Reducing the Sensing Error Probability with Improved Energy Detection in Cognitive Radio

Кумар

Pal²

2017

IJARCSSE

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“…Therefore, ED requires an accurate estimation of the noise variance; otherwise, we can face a SNR-wall problem, where the ED becomes incapable to made a robust decision about the PU status, even with a very large observation time [5,6]. However, many studies have been proposed to enhance the energy detector (ED) performance and to overcome its limitations [5,[7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Spectrum sensing based on cumulative power spectral density

Nasser

Mansour

Yao

et al. 2017

EURASIP J. Adv. Signal Process.

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This paper presents new spectrum sensing algorithms based on the cumulative power spectral density (CPSD). The proposed detectors examine the CPSD of the received signal to make a decision on the absence/presence of the primary user (PU) signal. Those detectors require the whiteness of the noise in the band of interest. The false alarm and detection probabilities are derived analytically and simulated under Gaussian and Rayleigh fading channels. Our proposed detectors present better performance than the energy (ED) or the cyclostationary detectors (CSD). Moreover, in the presence of noise uncertainty (NU), they are shown to provide more robustness than ED, with less performance loss. In order to neglect the NU, we modified our algorithms to be independent from the noise variance.

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“…Spectrum sensing functions have been frequently considered as important components in existing CR approaches, such as [7][8][9][10] . However, due to the presence of noise and fading of wireless channels, hidden terminals, obstacles and so on, spectrum sensing of individual nodes cannot achieve high detection accuracies.…”

Section: Introductionmentioning

confidence: 99%