Cooperative spectrum sensing method based on free probability theory
A technology of collaborative spectrum sensing and probability theory, applied in transmission monitoring, electrical components, transmission systems, etc., can solve the problem of low spectrum sensing performance
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Embodiment 1
[0037] Such as figure 1 As shown, K secondary base stations BS distributed in different geographical locations 1 ,BS 2 ,...,BS K Cooperative sensing channel to determine whether the main base station is sending a signal. The primary base station and each secondary base station are equipped with N t And N r Two antennas, between them is the MIMO Rayleigh fading channel. When the main base station sends a signal, the sampling rate is 1 / T s , Then the sampling signal output by the k-th receiver at time n Can be expressed as
[0038] y k ( n ) = P k N t H k s ( n ) + v k ( n ) , k = 1 . . . k - - - ( 1 )
[0039] among them, Is the transmitted symbol vector at time n, its elements satisfy zero mean independent and identical distribution, and the variance is 1; Is the MIMO channel matrix between the transmitter and the k-th receiver. Its elements are complex Gaussian variables with a mea...
Embodiment 2
[0131] Such as figure 2 As shown, the present invention provides a cooperative spectrum sensing method based on free probability theory, which is suitable for MIMO communication environment, and specifically includes the following steps:
[0132] Step 1: Sample the received signals of multiple antennas of each secondary base station, and the sampled signals will be processed in a centralized manner;
[0133] Step 2: According to the noise variance of all received sampling signals and channels, with the help of the asymptotic free characteristic and Wishart distribution characteristic of the random matrix, the algorithm based on free deconvolution is used to solve the average received signal power of all receiving antennas That is, the detection statistics;
[0134] Step 3: According to the target false alarm probability p f ,Use Monte Carlo simulation to calculate the detection threshold τ in the presence of noise;
[0135] Step 4: Put Compare with τ to determine whether the main ba...
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