System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and/or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.
1 . A system for spectrum channelization in an electromagnetic environment comprising:
at least one data analysis engine configured to analyze measured data based on the electromagnetic environment to create analyzed data;
a learning engine operable to learn the electromagnetic environment and/or make predictions about the electromagnetic environment; and
a survey occupancy application;
wherein the learning engine is operable to learn information from a channelization engine operable to prepare and/or divide at least one spectrum into a plurality of spectrum bands; and
wherein the survey occupancy application is operable to determine occupancy in the plurality of spectrum bands and to preprocess at least two signals that exist together in one spectrum band of the plurality of spectrum bands based on interference between the at least two signals.
2 . The system of claim 1 , wherein the channelization engine includes a frequency domain programmable channelizer configured to classify the analyzed data.
3 . The system of claim 1 , wherein the learning engine utilizes statistical learning techniques and/or control theory.
4 . The system of claim 1 , wherein the channelization engine is operable to provide a comparison of at least one receiver channel, and wherein the comparison provides anomalous detection using a mask with frequency and power, and wherein the mask is comprised of an average of maximum power values based on a first derivative and a second derivative to identify and confirm the maximum power values.
5 . The system of claim 1 , wherein the channelization engine includes channelization selector logic for a table lookup of filter coefficient and channelization vectors.
6 . The system of claim 5 , wherein data from the table lookup of filter coefficient and channelization vectors undergoes preprocessing with a mix circular rotator to produce a plurality of blocks of a plurality of points.
7 . The system of claim 1 , further comprising a tip and cue server operable to use the analyzed data from the at least one data analysis engine to create actionable data.
8 . The system of claim 7 , wherein the tip and cue server and the at least one data analysis engine are operable to run autonomously.
9 . The system of claim 1 , further comprising a noise floor estimator operable to estimate a bin-wise noise model, estimate a bin-wise noise plus signal model, determine a bin-level probability of false alarm, a bin-level threshold, a channel-level probability of false alarm, a channel-level level threshold, calculate a detection vector, count a number of elements above the bin-level threshold, determine a probability of false alarm, determine a probability of missed detection, and/or determine an overall detection probability.
10 . The system of claim 1 , further comprising a detection engine operable to estimate a number of channels, corresponding bandwidths for the number of channels, and/or center frequencies using an averaged power spectral density (PSD) of at least one signal of interest.
11 . The system of claim 1 , further including a classification engine, wherein the classification engine is operable to generate a query to a static database to classify at least one signal of interest based on information from a frequency domain programmable channelizer.
12 . The system of claim 1 , further including a blind detection engine and/or a blind classification engine.
13 . The system of claim 1 , wherein the at least one data analysis engine includes a semantic engine and/or an optimization engine.
14 . The system of claim 1 , wherein the channelization engine includes a time domain programmable channelizer configured to classify the analyzed data.
15 . A system for spectrum channelization in an electromagnetic environment comprising:
at least one data analysis engine configured to analyze measured data from the electromagnetic environment to create analyzed data;
a channelization engine operable to prepare and/or divide at least one spectrum into a plurality of spectrum bands based on the analyzed data;
a learning engine operable to learn the electromagnetic environment and/or make predictions about the electromagnetic environment based on the analyzed data; and
a survey occupancy application operable to determine occupancy in the plurality of spectrum bands and to preprocess at least two signals that exist that exist together in one spectrum band of the plurality of spectrum bands based on interference between the at least two signals.
16 . The system of claim 15 , wherein the channelization engine includes at least one fast Fourier transform (FFT) configuration operable to resolve ambiguities between at least two channels by employing a sufficient resolution bandwidth.
17 . The system of claim 15 , wherein the learning engine utilizes statistical learning techniques and/or control theory.
18 . A method for spectrum channelization in an electromagnetic environment comprising:
analyzing measured data from the electromagnetic environment using at least one data analysis engine to create analyzed data;
preparing and/or dividing at least one spectrum into a plurality of spectrum bands using a channelization engine based on the analyzed data;
learning the electromagnetic environment and/or predicting the electromagnetic environment using a learning engine based on the analyzed data; and
determining, via a survey occupancy application, occupancy in the plurality of spectrum bands and preprocessing at least two signals that exist together in one spectrum band of the plurality of spectrum bands based on interference between the at least two signals;
wherein the at least one data analysis engine is in communication with the channelization engine; and
wherein the learning engine is operable to learn information from the channelization engine.
19 . The method of claim 18 , further comprising the learning engine utilizing statistical learning techniques and/or control theory.
20 . The method of claim 18 , further comprising the channelization engine determining channel occupancy and/or channel noise for the plurality of spectrum bands.