A method of building an ad-hoc network of a wireless relay node and an ad-hoc network system are disclosed. The method includes verifying state information representing a relative distance and angle to a neighboring node capable of receiving data when each of relay nodes transmits the data, determining an action representing a change over time of each relay node, determining, based on an amount of change in a network throughput determined according to the state information and an amount of energy consumption according to the action, a reward corresponding to the action, and building a network including a source node, a destination node, and a plurality of relay nodes by generating, based on a reward of each of the relay nodes, a policy that allows a cumulative reward to be maximized.

A method of building an ad-hoc network of a wireless relay node and an ad-hoc network system are disclosed. The method includes verifying state information representing a relative distance and angle to a neighboring node capable of receiving data when each of relay nodes transmits the data, determining an action representing a change over time of each relay node, determining, based on an amount of change in a network throughput determined according to the state information and an amount of energy consumption according to the action, a reward corresponding to the action, and building a network including a source node, a destination node, and a plurality of relay nodes by generating, based on a reward of each of the relay nodes, a policy that allows a cumulative reward to be maximized.

A station deployment support method includes a positional relationship identification step of, based on travel trajectory data of a mobile object that measures an object present in a three-dimensional space within a predetermined measurable distance and acquires point group data on the measured object, the measurable distance, candidate base station position data, and candidate terminal station position data, generating base station positional relationship identification data and terminal station positional relationship identification data; a measurable range identification step of generating measurable range data based on the travel trajectory data and the measurable distance; and a travel trajectory selection step of selecting at least one piece of travel trajectory data so that the proportion of the measurable range in a predetermined evaluation area satisfies a predetermined value.

A station deployment support method includes a positional relationship identification step of, based on travel trajectory data of a mobile object that measures an object present in a three-dimensional space within a predetermined measurable distance and acquires point group data on the measured object, the measurable distance, candidate base station position data, and candidate terminal station position data, generating base station positional relationship identification data and terminal station positional relationship identification data; a measurable range identification step of generating measurable range data based on the travel trajectory data and the measurable distance; and a travel trajectory selection step of selecting at least one piece of travel trajectory data so that the proportion of the measurable range in a predetermined evaluation area satisfies a predetermined value.

A network device obtains EMF strength of each grid in a first grid group. The first grid group includes M grids obtained by dividing a signal coverage area of the network device, and M is an integer greater than 1. The network device determines a second grid group based on EMF strength of the M grids. The second grid group includes at least a first grid and a second grid, a coverage area of the first grid is greater than that of the second grid, and EMF strength of the first grid is lower than EMF strength of the second grid. The network device monitors EMF strength of a coverage area of the second grid group based on the second grid group, to adjust the EMF strength of the coverage area of the second grid group.

In a connected vehicle environment, network connection parameters such as a network congestion window and bit rate are automatically adjusted dependent on a location of a vehicle in order to optimize network performance. A geospatial database stores learned relationships between network performance of a connected vehicle at different physical locations when configured in accordance with different network parameters. The vehicle can then adjust its network parameters dynamically dependent on its location. A vehicle may maintain multiple connections to different networks concurrently for transmitting duplicate data of a data stream, with the vehicle independently adjusting parameters associated with different networks to optimize performance.

In a connected vehicle environment, network connection parameters such as a network congestion window and bit rate are automatically adjusted dependent on a location of a vehicle in order to optimize network performance. A geospatial database stores learned relationships between network performance of a connected vehicle at different physical locations when configured in accordance with different network parameters. The vehicle can then adjust its network parameters dynamically dependent on its location. A vehicle may maintain multiple connections to different networks concurrently for transmitting duplicate data of a data stream, with the vehicle independently adjusting parameters associated with different networks to optimize performance.

Systems, methods, and computer-readable media for identifying a deployment scheme for forming a wireless mesh network based on environmental characteristics and an optimum deployment scheme. In some examples, a geographical area for deployment of a wireless mesh network is identified. Additionally, environmental information of the geographical area can be collected. Network characteristics of an optimum deployment scheme for forming the wireless mesh network can be defined. As follows, a deployment scheme for forming the wireless mesh network can be identified based on the network characteristics of the optimum deployment scheme and the environmental information of the geographical area.

Systems, methods, and computer-readable media for identifying a deployment scheme for forming a wireless mesh network based on environmental characteristics and an optimum deployment scheme. In some examples, a geographical area for deployment of a wireless mesh network is identified. Additionally, environmental information of the geographical area can be collected. Network characteristics of an optimum deployment scheme for forming the wireless mesh network can be defined. As follows, a deployment scheme for forming the wireless mesh network can be identified based on the network characteristics of the optimum deployment scheme and the environmental information of the geographical area.

An interference detection system in a network identifies a first wireless station that has experienced radio frequency (RF) interference from an unknown source on at least one physical resource block (PRB) by determining that a key performance indicator (KPI) for the at least one PRB on the first wireless station has a value indicative of interference. The interference detection system identifies one or more second wireless stations that have experienced similar interference on the at least one PRB. A plurality of estimated interference source locations are determined based at least on geographic locations of the first wireless station and the one or more second wireless stations. Determining the plurality of estimated interference source locations further comprises generating a boundary based on the geographic locations of the first wireless station and the one or more second wireless stations and selecting a plurality of estimated interference source locations within the boundary.