Аlgorithm for Spectrum Sensing and Signal Selection by External Parameters
Keywords:
radio frequency spectrum, signal selection, external parameters, radio monitoring, associative arrayAbstract
For modern radio monitoring, a panoramic view of a wide frequency band and signal selection is its most important part. The constant growth of the number of radio electronic devices and the expansion of the instantaneous bandwidth of analysis in modern radio receiving devices leads to the fact that a significant number of analog and digital signals can be observed at the same time. Automatic adaptation of radio monitoring system to further signal processing is possible due to preliminary signal selection. The goal of this research is to develop an algorithm for signals selection in panoramic radio monitoring systems by their external parameters. The essence of proposed algorithm is to detect occupied bands of radio frequency spectrum, estimate center frequency and bandwidth of each channel, noise level and signal-to-noise ratio. Creation of frequency channels allows for signal filtering and estimation of pulse durations, as well as occupancy of each channel. Estimates of parameter for each signal fragment and frequency channel are recorded in associative arrays, which simplifies further signal selection. Due to variability of noise and propagation channel, estimates of signal parameters for each signal fragment are random variables. To obtain reliable estimates of signal center frequency and bandwidth, they are further grouping. Array of data can be accessed both by frequency channel number (table rows) and by signal parameters (keys), which are table column headers. Associative relationships between data provide flexible signals filtering by any combination of parameters. To test developed algorithm, we analyzed frequency band of 933-953 MHz and used the DataFrame Multi Index data container of Pandas package of Python programming language. This structure provides multi-level indexing, flexible access to data, and a wide range of tools for their processing and modifying. Developed algorithm can be used in existing and future radio monitoring systems for radio electronic devices identification and databases creation.
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