Reduced complexity blind beamforming for multiple antenna spectrum sensing

Eigenvalue based detection is one of the most promising blind spectrum sensing techniques in cognitive radio. However, it suffers from computational complexity resulting from sample covariance matrix computation and eigenvalue decom-position. In this paper, we propose a reduced-complexity blind dete...

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Hauptverfasser: Elleuch, Ines, Abdelkefi, Fatma, Siala, Mohamed
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description Eigenvalue based detection is one of the most promising blind spectrum sensing techniques in cognitive radio. However, it suffers from computational complexity resulting from sample covariance matrix computation and eigenvalue decom-position. In this paper, we propose a reduced-complexity blind detection algorithm to detect the presence of a main direction in terms of energy. Instead of eigenvalue decomposition, our method is based on a series of beamforming using simple beam patterns to reduce computational complexity. Simulation results show that our method provides acceptable performances compared to the well-known Maximum to Minimum Eigenvalue (MME) method with a considerable gain in computational complexity.
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subjects Array signal processing
Cognitive Radio
Complexity theory
Computationnal Complexity
Covariance matrices
Eigenvalue detection
Eigenvalues and eigenfunctions
Random Beamforming
Sensors
Spectrum Sensing
Symmetric matrices
Vectors
title Reduced complexity blind beamforming for multiple antenna spectrum sensing
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