Abstract: A method related to selecting a channel bandwidth may include partitioning the plurality of networks into a plurality (P) of local radio environments and identifying, for the P local radio environments, an available channel bandwidth set comprising a plurality of channel bandwidth values. The method may also relate to determining whether the plurality of channel bandwidth values provide a frequency reuse distance that is greater than a threshold frequency reuse distance, wherein the frequency reuse distance is estimated based at least on the pathloss measurement and, based on a determination that at least one of the plurality of channel bandwidth values provides the frequency reuse distance that is greater than the threshold frequency reuse distance, configuring a channel plan for the plurality of networks with a channel bandwidth value from the at least one of the plurality of channel bandwidth values.

Abstract: A method related to selecting a channel bandwidth may include partitioning the plurality of networks into a plurality (P) of local radio environments and identifying, for the P local radio environments, an available channel bandwidth set comprising a plurality of channel bandwidth values. The method may also relate to determining whether the plurality of channel bandwidth values provide a frequency reuse distance that is greater than a threshold frequency reuse distance, wherein the frequency reuse distance is estimated based at least on the pathloss measurement and, based on a determination that at least one of the plurality of channel bandwidth values provides the frequency reuse distance that is greater than the threshold frequency reuse distance, configuring a channel plan for the plurality of networks with a channel bandwidth value from the at least one of the plurality of channel bandwidth values.

Abstract: The present disclosure discloses a system and method for classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.

Abstract: Adapting scanning of frequency channels of different or varying widths to collect wideband spectrum data is disclosed. Scanning methods and/or configurations are modified based upon the type and signal strength of the interferers present or expected in the spectrum. The system includes: selecting a portion for scanning, wherein the portion includes contiguous and non-contiguous segments, partitioning the selected portion into a first plurality of channels, where at least two of the plurality of channels have different widths, each of the first plurality of channels including contiguous or non-contiguous segments; during a first scan of the selected portion, scanning the selected portion of the radio frequency spectrum at least by scanning a first channel with a first width and scanning a second channel with a second width that is different than the first width; and based on the first scan, collecting data representing the selected portion of the radio frequency spectrum.

Abstract: The present disclosure discloses a system and method for. classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.

Abstract: The present disclosure discloses a system and method for classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.

Abstract: The present disclosure discloses a system and method for classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.

Abstract: The present disclosure discloses a system and method for classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.

Abstract: Adapting scanning of frequency channels of different or varying widths to collect wideband spectrum data is disclosed. Scanning methods and/or configurations are modified based upon the type and signal strength of the interferers present or expected in the spectrum. The system includes: selecting a portion for scanning, wherein the portion includes contiguous and non-contiguous segments, partitioning the selected portion into a first plurality of channels, where at least two of the plurality of channels have different widths, each of the first plurality of channels including contiguous or non-contiguous segments; during a first scan of the selected portion, scanning the selected portion of the radio frequency spectrum at least by scanning a first channel with a first width and scanning a second channel with a second width that is different than the first width; and based on the first scan, collecting data representing the selected portion of the radio frequency spectrum.

Abstract: The present disclosure discloses a system and method for. classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.