Optimized Statistical Beamforming for Cooperative Spectrum Sensing in Cognitive Radio Networks Article Swipe
Ubaid M. Al‐Saggaf
,
Jawwad Ahmad
,
Mohammed A. Alrefaei
,
Muhammad Moinuddin
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/math11163533
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/math11163533
In cognitive radio (CR), cooperative spectrum sensing (CSS) employs a fusion of multiple decisions from various secondary user (SU) nodes at a central fusion center (FC) to detect spectral holes not utilized by the primary user (PU). The energy detector (ED) is a well-established technique of spectrum sensing (SS). However, a major challenge in designing an energy detector-based SS is the requirement of correct knowledge for the distribution of decision statistics. Usually, the Gaussian assumption is employed for the received statistics, which is not true in real practice, particularly with a limited number of samples. Another big challenge in the CSS task is choosing an optimal fusion strategy. To tackle these issues, we have proposed a beamforming-assisted ED with a heuristic-optimized CSS technique that utilizes a more accurate distribution of decision statistics by employing the characterization of the indefinite quadratic form (IQF). Two heuristic algorithms, genetic algorithm with multi-parent crossover (GA-MPC) and constriction factor particle swarm-based optimization (CF-PSO), are developed to design optimum beamforming and optimum fusion weights that can maximize the global probability of detection pd while constraining the global probability of false alarm pf to below a required level. The simulation results are presented to validate the theoretical findings and to asses the performance of the proposed algorithm.
Related Topics
Concepts
Cognitive radio
Fusion center
False alarm
Computer science
Detector
Beamforming
Crossover
Algorithm
Heuristic
Statistical power
Gaussian
Mathematical optimization
Energy (signal processing)
Fusion rules
Artificial intelligence
Mathematics
Statistics
Telecommunications
Wireless
Image (mathematics)
Image fusion
Quantum mechanics
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/math11163533
- https://www.mdpi.com/2227-7390/11/16/3533/pdf?version=1692162163
- OA Status
- gold
- Cited By
- 3
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385872603
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4385872603Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/math11163533Digital Object Identifier
- Title
-
Optimized Statistical Beamforming for Cooperative Spectrum Sensing in Cognitive Radio NetworksWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-16Full publication date if available
- Authors
-
Ubaid M. Al‐Saggaf, Jawwad Ahmad, Mohammed A. Alrefaei, Muhammad MoinuddinList of authors in order
- Landing page
-
https://doi.org/10.3390/math11163533Publisher landing page
- PDF URL
-
https://www.mdpi.com/2227-7390/11/16/3533/pdf?version=1692162163Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/2227-7390/11/16/3533/pdf?version=1692162163Direct OA link when available
- Concepts
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Cognitive radio, Fusion center, False alarm, Computer science, Detector, Beamforming, Crossover, Algorithm, Heuristic, Statistical power, Gaussian, Mathematical optimization, Energy (signal processing), Fusion rules, Artificial intelligence, Mathematics, Statistics, Telecommunications, Wireless, Image (mathematics), Image fusion, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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