US 11,659,421 B2
Tensor decomposition-based big data processing system and processing method for spectrum monitoring
Hongguang Ma, Xi'an (CN); Jinku Guo, Xi'an (CN); Qinbo Jiang, Xi'an (CN); and Zhiqiang Liu, Xi'an (CN)
Filed on Dec. 10, 2020, as Appl. No. 17/117,601.
Claims priority of application No. CN202010547293.0 (CN), filed on Jun. 16, 2020.
Prior Publication US 2021/0392523 A1, Dec. 16, 2021
Int. Cl. H04W 24/08 (2009.01)
CPC H04W 24/08 (2013.01) 7 Claims
OG exemplary drawing
1. A method of processing big data for regional spectrum monitoring based on tensor decomposition, comprising the step of:
S1: processing calibration of parameters of a spectrum monitoring station, and determining spectrum monitoring sampling point M and bandwidth B, wherein the parameters comprise a geolocation V, a synchronized clock t, a synchronized time tn(0 . . . N);
S2: processing discretization of spectrum monitoring data at a sampling time completely and a structured processing of spectrum monitoring data for a monitoring period to obtain a one-dimensional spectrum monitoring sequence Itn at the given sampling time and a two-dimensional spectrum monitoring matrix W at the given monitoring period; and
S3: constructing a cuboid matrix Q based on the two-dimensional spectrum monitoring matrix W and processing tensor decomposition for the cuboid matrix Q,
wherein step S3 comprises the steps of:
S3.1: calculating a geographical center point V0 on a geographical distribution according to latitude and longitude positions Vn of K number of spectrum monitoring stations, where n equals to 1, 2, 3, . . . , K, where

OG Complex Work Unit Math
S3.2: calculating the distance Dn between Vn of each spectrum monitoring station and the geographic center point V0, where ∥⋅∥2 is the second-order norm:
S3.3: along an ascending order of the distance Dn between the spectrum monitoring station and the geographic center point V0, arranging the corresponding spectrum matrix of the station to construct the spectrum monitoring network cuboid matrix Q, where Q=[W1, W2, . . . WK]T;
S3.4: performing tensor decomposition on the three-dimensional cuboid matrix Q, setting an analysis bandwidth F and dividing the cuboid matrix Q according to the analysis bandwidth F into segments, processing tensor decomposition for each segment, determining a validity of the tensor decomposition by setting MF>80% as a criterion of the validity; if MF<80%, the analysis bandwidth F is reduced to half, and the segments that does not meet the validity requirement is divided into segments according to the reduced analysis bandwidth F to re-process with tensor decomposition until the validity requirement are met or the minimum analysis bandwidth is reached;
S3.5: based on the results of tensor decomposition, calculating a center frequency, frequency occupancy, time occupancy, space occupancy of the emitter, or evaluating the environmental complexity;
S3.6: performing K-L divergence and mutual information calculations on the co-frequency emitters to identify whether it is an independent emitter or not.