Cooperative Spectrum Sensing Using Eigenvalue Fusion for OFDMA and Other Wideband Signals
AbstractIn this paper, we propose a new approach for the detection of OFDMA and other wideband signals in the context of centralized cooperative spectrum sensing for cognitive radio (CR) applications. The approach is based on the eigenvalues of the received signal covariance matrix whose samples are in the frequency domain. Soft combining of the eigenvalues at the fusion center is the main novelty. This combining strategy is applied to variants of four test statistics for binary hypothesis test, namely: the eigenvalue-based generalized likelihood ratio test (GLRT), the maximum-minimum eigenvalue detection (MMED), the maximum eigenvalue detection (MED) and the energy detection (ED). It is shown that the eigenvalue fusion can outperform schemes based on decision fusion and sample fusion. A tradeoff is also established between complexity and volume of data sent to the fusion center in all combining strategies.
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Guimarães, D.A.; da Silva, C.R.N.; de Souza, R.A.A. Cooperative Spectrum Sensing Using Eigenvalue Fusion for OFDMA and Other Wideband Signals. J. Sens. Actuator Netw. 2013, 2, 1-24.
Guimarães DA, da Silva CRN, de Souza RAA. Cooperative Spectrum Sensing Using Eigenvalue Fusion for OFDMA and Other Wideband Signals. Journal of Sensor and Actuator Networks. 2013; 2(1):1-24.Chicago/Turabian Style
Guimarães, Dayan A.; da Silva, Carlos R.N.; de Souza, Rausley A.A. 2013. "Cooperative Spectrum Sensing Using Eigenvalue Fusion for OFDMA and Other Wideband Signals." J. Sens. Actuator Netw. 2, no. 1: 1-24.