A Cooperative Spectrum Sensing Method Based on Empirical Mode Decomposition and Information Geometry in Complex Electromagnetic Environment

Table 1

Symbols and notations.

Symbols	Notations
	Gaussian noise in the environment
	The signal transmitted by the PU
	The signal received by the SU
	The number of sampling points
	The number of SU
,	PU signal exists, PU signal does not exist
,	False alarm probability, detection probability,
	The signal collected by the -th SU
	a signal matrix
	The -th intrinsic mode function
	The maximum envelope of
	The minimum envelope of
	Average value of and
	Component of
	Residual
	Reconstructed signal
	Critical point
	after EMD processing
	A new matrix consisting of
	The split parameter
	The length of the split signal vector after splitting
,	A matrix after ODAR or IDAR
,	Covariance matrix of or
	is an dimensional sample
	is an dimensional parameter vector
	A random variable
	is the probability distribution space
	Covariance matrix corresponding to
,	Covariance matrix corresponding to under and
	A point on the manifold
	Arbitrary curve between the two points
	The u-th eigenvalues of the matrix
	The number of environmental noise signal matrices
,	The p-th noise signal covariance matrix after ODAR and IDAR
	Iteration step size
	Iteration step
,	Riemann Mean of and
,	Distance between the sensing signal and reference point and on the manifold
	The j-th Geodesic distance feature vector (GDFV)
	Training set
	The set of training feature vectors belonging to class
	Center point of
	The feature extracted under the channel of the unknown PU state