Systems, methods, and computer-readable media for radio resource management in a Citizens Broadband Radio Service (CBRS) network include one or more CBRS devices (CBSDs) which can obtain a group type associated with the CBSDs and their associated Radio Environment Map (REM) reports of one or more frequency channels of the CBRS network. The group type and the REM reports may be provided to a Self-Organizing Network (SON) manager of the CBRS network, where the SON manager may determine and provide to the CBSDs, one or more of a channel utilization information, transmission power, or mobility load management information for the CBSD, based on the group type and the REM reports.

A method and a system for forming a network of network devices, the method including providing a plurality of network devices in a physical environment, each of the plurality of network devices being controllable by a mobile network module connectable to the network devices. A network configuration device with a memory unit for storing device configuration data connects a mobile network module to the network configuration device. The mobile network module reads out the device configuration data stored in the memory unit of the network configuration device. The mobile network module connects to a network device and configuring the network device, based on the device configuration data.

A method and a system for forming a network of network devices, the method including providing a plurality of network devices in a physical environment, each of the plurality of network devices being controllable by a mobile network module connectable to the network devices. A network configuration device with a memory unit for storing device configuration data connects a mobile network module to the network configuration device. The mobile network module reads out the device configuration data stored in the memory unit of the network configuration device. The mobile network module connects to a network device and configuring the network device, based on the device configuration data.

Aspects include determining whether a utilization of wireless spectrum associated with a guaranteed class of traffic in a network is greater than a first threshold, responsive to the determining indicating that the utilization of the wireless spectrum associated with the guaranteed class of traffic is greater than the first threshold, causing an upgrade of a capacity in the network, and responsive to the determining indicating that the utilization of the wireless spectrum associated with the guaranteed class of traffic is not greater than the first threshold: determining a throughput for a non-guaranteed class of traffic for each cell of a plurality of cells of the network, and responsive to determining that the throughput for the non-guaranteed class of traffic for at least one cell of the plurality of cells is less than a second threshold, causing the upgrade of the capacity in the network. Other embodiments are disclosed.

A system and method are described which enable planned evolution and obsolescence of multiuser wireless spectrum. One embodiment of such a system includes one or multiple centralized processors and one or multiple distributed nodes that communicate via wireline or wireless connections. The distributed nodes may share their identification number and other reconfigurable system parameters with the centralized processor. The information about all distributed nodes may be stored in a database that is shared by all centralized processors. The reconfigurable system parameters may comprise power emission, frequency band, modulation/coding scheme. The distributed nodes may be software defined radios such as FPGA, DSP, GPU and/or GPCPU that run algorithms for baseband signal processing and may be reconfigured remotely by the centralized processor. A cloud wireless system may be used wherein the distributed nodes are reconfigured periodically or instantly to adjust to the evolving wireless architecture.

A system and method are disclosed for estimating the location of a satellite terminal. The terminal is selected from among a plurality of terminals, and one or more position estimates are generated for a satellite which provides service to the terminal. The position estimated can be generated, for example, by performing a first one or more iterative grid searches over a plurality of potential position estimates for the satellite. A location estimate is subsequently generated for the terminal by performing a second one or more iterative grid searches over a plurality of potential location estimates for the terminal.

A system and method are disclosed for estimating the location of a satellite terminal. The terminal is selected from among a plurality of terminals, and one or more position estimates are generated for a satellite which provides service to the terminal. The position estimated can be generated, for example, by performing a first one or more iterative grid searches over a plurality of potential position estimates for the satellite. A location estimate is subsequently generated for the terminal by performing a second one or more iterative grid searches over a plurality of potential location estimates for the terminal.

A method and system for determining deployment parameters of a set of customer premises equipment (CPE) in a housing environment. A housing database (2) and a simulation database (3) connected to a processor (4) are present, the housing database (2) storing housing information, and the simulation database (3) storing simulation data with Wi-Fi performance parameters for a subset of housing types. The processor (4) clusters the stored housing information based on the Wi-Fi performance parameters, associates each of the clustered housing parameter sets with one of the subset of housing types, and for a specific one of the housing types determines deployment parameters based on data obtained from the simulation database (3). The matching of a specific housing environment with one of the subset of housing types allows to quickly and efficiently optimize deployment parameters, such as number, type and placement of CPE.

A method and system for determining deployment parameters of a set of customer premises equipment (CPE) in a housing environment. A housing database (2) and a simulation database (3) connected to a processor (4) are present, the housing database (2) storing housing information, and the simulation database (3) storing simulation data with Wi-Fi performance parameters for a subset of housing types. The processor (4) clusters the stored housing information based on the Wi-Fi performance parameters, associates each of the clustered housing parameter sets with one of the subset of housing types, and for a specific one of the housing types determines deployment parameters based on data obtained from the simulation database (3). The matching of a specific housing environment with one of the subset of housing types allows to quickly and efficiently optimize deployment parameters, such as number, type and placement of CPE.

Aspects of the subject disclosure may include, for example, embodiments receiving a notification of actions, determining a potential bias metric for the actions in response to analyzing the actions using a machine learning application, determining the potential bias metric for the actions is above a potential bias threshold for the actions, and adjusting the actions to mitigate potential bias in the actions according to the potential bias metric being above the potential bias threshold using the machine learning application. Further embodiments can include determining a potential bias metric for the adjusted actions in response to analyzing the adjusted actions using the machine learning application, determining the potential bias metric for the adjusted actions is below the potential bias threshold for the actions, and providing a notification that indicates to implement the adjusted actions. Other embodiments are disclosed.