Spectrum sensing for low SNR environment using maximum-minimum eigenvalue (MME) detection

Detecting the presence or absence of primary user is the key task of cognitive radio networks. However, relying on single detector reduces the probability of detection and increases the probability of missed detection. Combining two conventional spectrum sensing techniques by integrating their individual features improves the probability of detection especially under noise uncertainty. This paper introduces a modified two-stage detection technique that depends on the energy detection as a first stage due to its ease and speed of detection, and the proposed Modified Combinational Maximum-Minimum Eigenvalue based detection as a second stage under noise uncertainty and comperes it with the case of using Maximum-Minimum Eigenvalue and Combinational Maximum-Minimum Eigenvalue as a second stage.

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Spectrum sensing through spectrum discriminator and maximum minimum eigenvalue detector: A comparative study

2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings ◽

10.1109/i2mtc.2012.6229452 ◽

2012 ◽

Cited By ~ 12

Author(s):

Mohamed Hamid ◽

Kurt Barbe ◽

Niclas Bjorsell ◽

Wendy Van Moer

Keyword(s):

Comparative Study ◽

Spectrum Sensing ◽

Minimum Eigenvalue ◽

Maximum Minimum

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A maximum-minimum eigenvalue detection simpler method based on secondary users locations for cooperative spectrum sensing

2014 International Congress on Technology, Communication and Knowledge (ICTCK) ◽

10.1109/ictck.2014.7033503 ◽

2014 ◽

Cited By ~ 2

Author(s):

Vahid Abed ◽

Ali Shahzadi

Keyword(s):

Spectrum Sensing ◽

Cooperative Spectrum Sensing ◽

Minimum Eigenvalue ◽

Secondary Users ◽

Maximum Minimum ◽

Simpler Method

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Spectrum sensing in low SNR regime via stochastic resonance

2010 44th Annual Conference on Information Sciences and Systems (CISS) ◽

10.1109/ciss.2010.5464907 ◽

2010 ◽

Cited By ~ 7

Author(s):

Kun Zheng ◽

Husheng Li ◽

Seddik M. Djouadi ◽

Jun Wang

Keyword(s):

Stochastic Resonance ◽

Spectrum Sensing ◽

Low Snr

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Complexity Issues within Eigenvalue-Based Multi-Antenna Spectrum Sensing

Advances in Wireless Technologies and Telecommunication - Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management ◽

10.4018/978-1-4666-6571-2.ch023 ◽

2015 ◽

pp. 603-617 ◽

Cited By ~ 1

Author(s):

Ines Elleuch ◽

Fatma Abdelkefi ◽

Mohamed Siala

Keyword(s):

Computational Complexity ◽

False Alarm ◽

Spectrum Sensing ◽

Complexity Analysis ◽

Floating Point ◽

Beam Forming ◽

Multiple Antenna ◽

Deep Insight ◽

Minimum Eigenvalue ◽

Insight Into

This chapter provides a deep insight into multiple antenna eigenvalue-based spectrum sensing algorithms from a complexity perspective. A review of eigenvalue-based spectrum-sensing algorithms is provided. The chapter presents a finite computational complexity analysis in terms of Floating Point Operations (flop) and a comparison of the Maximum-to-Minimum Eigenvalue (MME) detector and a simplified variant of the Multiple Beam forming detector as well as the Approximated MME method. Constant False Alarm Performances (CFAR) are presented to emphasize the complexity-reliability tradeoff within the spectrum-sensing problem, given the strong requirements on the sensing duration and the detection performance.

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