Point cloud data between a base station device and a terminal station device is acquired as a point cloud data group. A radius of a first Fresnel zone defined by the base station device and the terminal station device at each position where the point cloud data group is acquired is calculated. A region specified by the radius at each position where the point cloud data group is acquired is scanned to detect the point cloud data, and a non-line-of-sight region is extracted. A ratio of a total area of all the extracted non-line-of-sight regions to an area of a region constructed by the first Fresnel zone is calculated. A received power is estimated based on the calculated ratio between the areas. Whether or not there is a line of sight between the base station device and the terminal station device is determined based on the received power.

Embodiments of this disclosure provide a method and apparatus for wireless network deployment and a terminal device, wherein, the method includes: estimating whether a deployment position of a current node satisfies a requirement according to planned network information and deployed network information of the current node; and optimizing the deployment position of the current node when an estimation result of the estimating unit is no. With the embodiments of this disclosure, deployment quality of an actual deployment position of a wireless network node may be estimated, such that actual deployment satisfies a requirement on network planning.

This system and method provides for a plurality of satellite ground stations, distributed across some geographic region, and for these regions in turn to be scalable to cover large regions or even the globe using a combination of low-orbit satellites, terrestrial participant devices, and cloud-based communications. The invention in its simplest form is intended to solve the short temporal window problem inherent to the scenario where a single base or ground station is trying to track and communicate with a low-end LEOSAT or even a cube-satellite.

Disclosed are various embodiments for provisioning radio-based networks with locality rules. In one embodiment, at least one locality rule associated with an organization is accessed. The locality rule(s) require that at least a subset of network traffic for a radio-based network remain within a particular geographic area. The radio-based network includes a radio access network and an associated core network. A topology for the radio-based network is determined based at least in part on the locality rule(s). The radio-based network is provisioned or reconfigured for the organization to have the topology complying with the at least one locality rule.

Disclosed are various embodiments for provisioning radio-based networks with locality rules. In one embodiment, at least one locality rule associated with an organization is accessed. The locality rule(s) require that at least a subset of network traffic for a radio-based network remain within a particular geographic area. The radio-based network includes a radio access network and an associated core network. A topology for the radio-based network is determined based at least in part on the locality rule(s). The radio-based network is provisioned or reconfigured for the organization to have the topology complying with the at least one locality rule.

An electronic device that provides installation instructions is described. During operation, the electronic device may automatically generate a radio-frequency project plan for a network in an environment using a radio-frequency model and a model corresponding to at least a portion of the environment. Then, based at least in part on the radio-frequency project plan, the electronic device may interactively provide the installation instructions to an installer while a given access point in the access points is being installed in the environment. Moreover, after the given access point is installed, the electronic device may validate the given access point. Next, the electronic device may perform automatic testing of the given access point. Furthermore, the electronic device may provide a comparison of estimated communication performance of the given access point in the radio-frequency project plan and measured communication performance of the given access point.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels. In some implementations, information is obtained. An encoder network is used to process the information and generate a first RF signal. The first RF signal is transmitted through a first channel. A second RF signal is determined that represents the first RF signal having been altered by transmission through the first channel. Transmission of the first RF signal is simulated over a second channel implementing a machine-learning network, the second channel representing a model of the first channel. A simulated RF signal that represents the first RF signal having been altered by simulated transmission through the second channel is determined. A measure of distance between the second RF signal and the simulated RF signal is calculated. The machine-learning network is updated using the measure of distance.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels. In some implementations, information is obtained. An encoder network is used to process the information and generate a first RF signal. The first RF signal is transmitted through a first channel. A second RF signal is determined that represents the first RF signal having been altered by transmission through the first channel. Transmission of the first RF signal is simulated over a second channel implementing a machine-learning network, the second channel representing a model of the first channel. A simulated RF signal that represents the first RF signal having been altered by simulated transmission through the second channel is determined. A measure of distance between the second RF signal and the simulated RF signal is calculated. The machine-learning network is updated using the measure of distance.

A method and associated systems for improving robustness of a cellular network. A topology of the cellular network is represented as an undirected graph that represents base stations as nodes and represents communication paths between base stations as edges. Each node is associated with a “synergistic” version of a Shapley value proportional to an amount of network disturbance that would occur if that value's corresponding base station should fail. The synergistic nature of the synergistic Shapley values allows them to account for scenarios in which multiple base stations fail at the same time. A synergistic Shapley value of a particular node is derived as a function of how many of the shortest paths between nodes of the graph lengthen when the node's corresponding base station fails. Base stations and nodes associated with higher synergistic Shapley values are deemed to be “censorious” and in need of reconfiguration.

A graph of devices is constructed, each network device serving an amount of bandwidth over the network, each vertex of the graph corresponding to a respective one of the network devices, each edge of the graph connecting network devices by interference weight, such that edges between connected network devices using different channels have an interference weight of zero, and edges between connected network devices using the same channel have an interference weight denoting an amount of interference between the connected network devices. A cell utilization of each of the network devices is determined according to an amount of traffic served by the respective network device compared to a total of the amounts of bandwidth for all network devices. A vehicle requesting bandwidth is assigned to the one of the network devices having a smallest product of cell utilization and maximum interference weight edge.