Abstract: Systems and methods of frequency planning for a cellular gateway in a Wi-Fi network include connecting to cellular infrastructure at a cellular frequency; providing a Wi-Fi connection at a Wi-Fi frequency selected to coexist with the cellular frequency; and responsive to interference between the cellular frequency and the Wi-Fi frequency, performing one or more actions to reduce the interference.

Abstract: Systems and methods of selecting and controlling base stations for connectivity to a cellular gateway for a Wi-Fi network include obtaining information related to a cellular infrastructure of a cellular network; determining a list of preferred cellular identifiers, each identifying a cell for connectivity with the cellular gateway, based on a plurality of factors; and providing the list of preferred cellular identifiers to the cellular gateway where the cellular gateway utilizes the list for wireless access to the cellular infrastructure.

Abstract: Systems and methods of geographically limiting a cellular gateway for a Wi-Fi network include obtaining a location of the cellular gateway; determining whether the cellular gateway is authorized to operate at the location on a given cellular network; and performing an action including any of blocking, allowing, or partially allowing operation of the cellular gateway on the cellular network. The method can be implemented by a cloud service, and wherein the location is determined by one of the cellular gateway and a user device connected to the cellular gateway.

Abstract: Systems and methods for Wi-Fi network failover to cellular connection with throttling of traffic include detecting an outage on wired connections for any of the plurality of Wi-Fi networks; determining the any of the plurality of Wi-Fi networks have switched to a cellular connection as a failover based on the outage; and determining whether to throttle traffic on any cellular connection based on the failover and instructing corresponding gateways accordingly.

Abstract: Systems and methods of installing a cellular gateway in a Wi-Fi network include obtaining a cellular gateway that is configured to provide cellular connectivity to the Internet for an associated Wi-Fi network; measuring a plurality of locations in a building for the Wi-Fi network; and receiving an indication based on the measuring, on a mobile device, for locating the cellular gateway in the building. The mobile device can execute at least one of a mobile application and a browser session and communicates with the cellular gateway via any of Bluetooth and Wi-Fi.

Abstract: System and methods for managing a Wi-Fi network of a plurality of Wi-Fi networks from a cloud-based Network Operations Control (NOC) dashboard are provided. A method, according to one implementations, includes the step of obtaining Wi-Fi metrics and cellular metrics from a network. The method also includes the step of displaying a dashboard on a user interface for use by a support agent at a Network Operations Center (NOC). Also, the method includes the step of displaying both the Wi-Fi metrics and the cellular metrics on the dashboard.

Abstract: Small cell identification using machine learning is provided. A method can include extracting, by a device comprising a processor, signal strength information for a cell in a cellular communication network from user equipment log data; estimating, by the device, path loss information associated with the cell at respective distances based on the signal strength information for the cell, resulting in estimated path loss information; and, based on the estimated path loss information, optionally along with other information such as antenna transmission power, antenna transmission frequency band, percentage of user equipments having a distance to a base station within a threshold, maximum user equipment distance to a base station, etc., classifying, by the device, the cell as a type from a group of types of cells, the group comprising a macro cell and a small cell.

Abstract: Small cell identification using machine learning is provided. A method can include extracting, by a device comprising a processor, signal strength information for a cell in a cellular communication network from user equipment log data; estimating, by the device, path loss information associated with the cell at respective distances based on the signal strength information for the cell, resulting in estimated path loss information; and, based on the estimated path loss information, optionally along with other information such as antenna transmission power, antenna transmission frequency band, percentage of user equipments having a distance to a base station within a threshold, maximum user equipment distance to a base station, etc., classifying, by the device, the cell as a type from a group of types of cells, the group comprising a macro cell and a small cell.

Abstract: Small cell identification using machine learning is provided. A method can include extracting, by a device comprising a processor, signal strength information for a cell in a cellular communication network from user equipment log data; estimating, by the device, path loss information associated with the cell at respective distances based on the signal strength information for the cell, resulting in estimated path loss information; and, based on the estimated path loss information, optionally along with other information such as antenna transmission power, antenna transmission frequency band, percentage of user equipments having a distance to a base station within a threshold, maximum user equipment distance to a base station, etc., classifying, by the device, the cell as a type from a group of types of cells, the group comprising a macro cell and a small cell.

Abstract: Small cell identification using machine learning is provided. A method can include extracting, by a device comprising a processor, signal strength information for a cell in a cellular communication network from user equipment log data; estimating, by the device, path loss information associated with the cell at respective distances based on the signal strength information for the cell, resulting in estimated path loss information; and, based on the estimated path loss information, optionally along with other information such as antenna transmission power, antenna transmission frequency band, percentage of user equipments having a distance to a base station within a threshold, maximum user equipment distance to a base station, etc., classifying, by the device, the cell as a type from a group of types of cells, the group comprising a macro cell and a small cell.