Adaptive energy detector for spectrum sensing in cognitive radio networks

Martínez, Daniela M.; Andrade, Ángel G.

doi:10.1016/j.compeleceng.2015.08.013

Cited by 15 publications

(13 citation statements)

References 24 publications

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“…The performance of the proposed method is compared with traditional-ED [3], Fuzzy-ED [39] and DIsCOVER [40]. The comparisons are performed for different SNRs by setting p f ≤ 0.1 .…”

Section: Resultsmentioning

confidence: 99%

Dynamic dual threshold cooperative spectrum sensing for cognitive radio under noise power uncertainty

Wan

Ding

Xiong

et al. 2019

Hum. Cent. Comput. Inf. Sci.

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The rapid development of wireless communications has brought endless new types of services or applications for human beings. The emergence of many kinds of communication equipments makes the public frequency band more and more crowded [1]. At present, most of the wireless communication systems employ fixed spectrum allocation mechanism. Only authorized users can be allowed to access the corresponding authorized spectrum resources, which will lead to inefficient usage of the licensed spectrum. From the report issued by International Telecommunication Union (ITU), there are still plenty of free spectrum resources within certain authorized bands at specific temporal and spatial scenarios. In cognitive radio (CR) system, by dynamically adjusting transmission power, carrier frequency, modulation and other parameters, SUs can utilize the spectrum holes as well as avoid interference with primary users (PUs). By applying cognitive radio technology, the SUs can fully access free authorized bands and apply suitable

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“…The performance of the proposed method is compared with traditional-ED [3], Fuzzy-ED [39] and DIsCOVER [40]. The comparisons are performed for different SNRs by setting p f ≤ 0.1 .…”

Section: Resultsmentioning

confidence: 99%

Dynamic dual threshold cooperative spectrum sensing for cognitive radio under noise power uncertainty

Wan

Ding

Xiong

et al. 2019

Hum. Cent. Comput. Inf. Sci.

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“…These methods require a careful choice of the fixed threshold values to guarantee improved performance particularly when sensing conditions abruptly change. The GTT method of Martinez et al, [42] depends on a correlation function to improve the accuracy of noise estimation, while the method of Liu et al, [43] does not require the noise power nor a threshold to be known apriori. Some other methods belonging to the GTT class were found in [26], which was based on the expectation maximization algorithm, and in [44], based on compressive sensing.…”

Section: Global Thresholding Techniquesmentioning

confidence: 99%

A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio

Onumanyi

Abu‐Mahfouz

Hancke

2018

Physical Communication

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“…is considered. On the other hand, can be easily affected by the received power from the PU, which in turn depends on the fading channel response [10,11]. It is also clear that increasing the number of samples obtained by the energy detector can reduce .…”

Section: Sensing and Historymentioning

confidence: 99%

“…Several ideas were proposed to improve ED performance, including adaptive ED, in which the detection threshold is calculated from (11) based on an estimated noise power 2 w . The sensor updates this estimate every calibration period [10] and keeps updating the threshold as the noise power changes in the environment. Another proposed method to enhance ED performance is the use of two detection thresholds [32], wherein if the test statistic Θ( ) is below a lower threshold 1 , hypothesis H 0 is declared.…”

Section: Sensing and Historymentioning

confidence: 99%

“…A large body of work has been dedicated to researching the various aspects of CRN operations, such as spectrum sensing to identify empty bands [4][5][6][7][8][9][10][11], channel allocation among SUs [1,12,13], establishment and maintenance of a common control channel (CCC) to allow persistent communications between different SUs [3,14], and spectrum handoff and mobility. A summary of relevant research is presented in the next section.…”

Section: Introductionmentioning

confidence: 99%

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Sensing Device Management for History‐Based Spectrum Sharing in Cognitive Radio Networks

Hawa

Jubair

Al‐Zubi

et al. 2018

Wireless Communications and Mobile Computing

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A novel approach to managing a fully distributed cognitive radio network (CRN) is presented. This approach builds on the concept of history-based spectrum access, in which cognitive base stations (BSs) independently estimate the system load using history records and adaptively swap their occupied spectrum bands to ensure allocation fairness and high overall throughput. In addition, cognitive BSs monitor primary user (PU) behavior in order to avoid interfering with active PUs. In this work, we address two issues that afflict history-based access: the first is the high cost of the sensing devices needed at each cognitive BS to be able to independently draw conclusions about the status of the CRN and the second is the unreliability inherent in practical sensing hardware (such as energy detectors). Simulation results show that the proposed technique manages to solve the two abovementioned issues without any noticeable drop in performance and without sacrificing the distributed nature of the protocol.

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Adaptive energy detector for spectrum sensing in cognitive radio networks

Cited by 15 publications

References 24 publications

Dynamic dual threshold cooperative spectrum sensing for cognitive radio under noise power uncertainty

Dynamic dual threshold cooperative spectrum sensing for cognitive radio under noise power uncertainty

A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio

Sensing Device Management for History‐Based Spectrum Sharing in Cognitive Radio Networks

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