Abstract: Secure wireless data prefetching and delivery is provided. A first demand is received from a first requesting device, requesting a first data file from the central agent, the first requesting device storing first cache data including a key and a first portion of the first data file. A second demand is received from a second requesting device, requesting a second data file from the central agent, the second requesting device storing second cache data including the key and a second portion of the second data file. A function is generated configured to allow the first requesting device to generate the first data file from the first portion and to allow the second requesting device to generate the second data file from the second portion. The function is broadcast to the first and second devices, responsive to the first and second demands.

Abstract: Autonomous management of wireless connectivity of priority response vehicles is provided. It is received, from a communications network including a plurality of access points, the access points configured to provide communications services to priority vehicles and non-priority vehicles, locations of the priority vehicles over the communications network. A SON server is utilized, in communication with the plurality of access points, to optimize wireless connectivity for the priority vehicles. It is received, by an enhanced vehicle management system (EVMS) server, in communication with the SON server, network quality information from the SON server. The priority vehicles are routed based on the network quality information.

Abstract: A method for controlling one or more operational characteristics of a plurality of wireless access points of a manufacturing environment includes generating a plurality of state vectors based on network data associated with the plurality of wireless access points and identifying a set of actions from among a plurality of actions and associated with the plurality of state vectors. The method includes determining a reward for each action from among the set of actions, selecting a target action from among the set of actions based on the reward associated with each action from among the set of actions, and selectively adjusting the one or more operational characteristics of the plurality of wireless access points based on the target action.

Abstract: Lane-level matching is provided. For a time index of a time slot of a period of receiving consecutive position information, a lateral distance of the vehicle to each of a plurality of lanes of a roadway is calculated using data from sensors of a vehicle. For each lane of the plurality of lanes, a positional uncertainty of the vehicle in an orthogonal direction to a lane bearing of the lane is calculated, a lane confidence based on an average of confidence values of the lane over the period of receiving consecutive position information is calculated, and a lane probability based on the lane confidence is calculated. For the time index, it is identified which of the lanes has a highest probability as being the lane to which the vehicle is matched.

Abstract: Mesh device communication is provided. A dictionary of indexes corresponding to different messages is stored to a cache memory of an access device. A message is received via a transceiver of the access device. The cache memory is accessed to look up the message to identify an index corresponding to the message. The message is propagated, via the transceiver, to a wireless access device mesh network including a plurality of other access devices by broadcasting the index of the message.

Abstract: Selecting data packages received by a host device is provided. The host device receives a number of N data packages. For each data package of the N data packages: a prioritized data package parameter is calculated. The data packages are sorted according to a predetermined sorting-scheme considering at least prioritized data package parameters. A number of M data packages are down-selected from the N data packages, wherein M < N. The one or more of the down-selected M data packages are processed. Accordingly, hardware and software requirements of the host device may be reduced due to a reduced computational complexity.

Abstract: Systems, methods, and computer-readable media are described for performing real-time vehicular incident risk prediction using real-time vehicle-to-everything (V2X) data. A vehicular incident risk prediction machine learning model is trained using historical V2X data such as historical incident data and historical vehicle operator driving pattern behavior data as well as third-party data such as environmental condition data and infrastructure condition data. The trained machine learning model is then used to predict the risk of an incident for a vehicle on a roadway segment based on real-time V2X data relating to the roadway segment and/or vehicle operators on the roadway segment. A notification of a high risk of incident can then be sent to a V2X communication device of the vehicle to inform an operator of the vehicle.

Abstract: A method includes obtaining a radio frequency (RF) signal magnitude for a plurality of RF signals broadcasted in an environment and generating a digital RF heat map of the environment based on each RF signal magnitude. The method includes determining an RF coverage of the environment based on the digital RF heat map and selecting, for a wireless communication device, a communication channel from among a plurality of communication channels based on the RF coverage and one or more RF probability distribution functions.

Abstract: A computer is programmed to allocate respective connectivity quality data of a geographic area to a first map or a second map. The computer is further programmed to assign one of a plurality of subsets of the first map and one of a plurality of subsets of the second map to a first vehicle, identify respective locations of the first and second vehicles and one of the first or second maps that includes the locations of the first and second vehicles. The computer is further programmed to send, to the first and second vehicles, a map dataset that is a result of applying an XOR function to (1) the subset of the identified map that includes the location of the first vehicle assigned to the first vehicle and (2) the subset of the identified map that includes the location of the second vehicle assigned to the second vehicle.

Abstract: A method includes obtaining a radio frequency (RF) signal magnitude for a plurality of RF signals broadcasted in an environment and generating a digital RF heat map of the environment based on each RF signal magnitude. The method includes determining an RF coverage of the environment based on the digital RF heat map and selecting, for a wireless communication device, a communication channel from among a plurality of communication channels based on the RF coverage and one or more RF probability distribution functions.

Abstract: 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.

Abstract: 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.

Abstract: A computer is programmed to divide respective data of a first high-resolution map of a first geographic area and a second high-resolution map of a second geographic area into a plurality of respective subsets, assign one of the subsets of each of the first high-resolution map and the second high-resolution map to a first vehicle and a second vehicle, identify respective locations of the first vehicle and the second vehicle and the one of the first high-resolution map or the second high-resolution map that includes the locations of the first and second vehicles, and send, to the first and second vehicles, a map dataset that is a result of applying an XOR function to (1) the subset of the identified high-resolution map including the location of the first vehicle and (2) the subset of the identified high-resolution map including the location of the second vehicle.

Abstract: A computer is programmed to allocate respective connectivity quality data of a geographic area to a first map or a second map. The computer is further programmed to assign one of a plurality of subsets of the first map and one of a plurality of subsets of the second map to a first vehicle, identify respective locations of the first and second vehicles and one of the first or second maps that includes the locations of the first and second vehicles. The computer is further programmed to send, to the first and second vehicles, a map dataset that is a result of applying an XOR function to (1) the subset of the identified map that includes the location of the first vehicle assigned to the first vehicle and (2) the subset of the identified map that includes the location of the second vehicle assigned to the second vehicle.

Abstract: A graph of devices is constructed, each device requiring an amount of bandwidth over the network, each vertex of the graph corresponding to a respective one of the devices, each edge of the graph connecting devices according to a weight denoting interference between the connected devices. The vertices of the graph are labeled with labels such that no two vertices sharing the same edge have the same label, each label requiring bandwidth corresponding to the device of that label requiring the most bandwidth. If the sum of the bandwidth required for the labels exceeds the set bandwidth, the edge of the graph having the least interference is deleted, and the perform the construct and label operations are repeated. If the sum of the bandwidth required for the labels is within the set bandwidth, the bandwidth is assigned to the devices.

Abstract: A graph of devices is constructed, each device requiring an amount of bandwidth over the network, each vertex of the graph corresponding to a respective one of the devices, each edge of the graph connecting devices according to a weight denoting interference between the connected devices. The vertices of the graph are labeled with labels such that no two vertices sharing the same edge have the same label, each label requiring bandwidth corresponding to the device of that label requiring the most bandwidth. If the sum of the bandwidth required for the labels exceeds the set bandwidth, the edge of the graph having the least interference is deleted, and the perform the construct and label operations are repeated. If the sum of the bandwidth required for the labels is within the set bandwidth, the bandwidth is assigned to the devices.

Abstract: A computer is programmed to divide respective data of a first high-resolution map of a first geographic area and a second high-resolution map of a second geographic area into a plurality of respective subsets, assign one of the subsets of each of the first high-resolution map and the second high-resolution map to a first vehicle and a second vehicle, identify respective locations of the first vehicle and the second vehicle and the one of the first high-resolution map or the second high-resolution map that includes the locations of the first and second vehicles, and send, to the first and second vehicles, a map dataset that is a result of applying an XOR function to (1) the subset of the identified high-resolution map including the location of the first vehicle and (2) the subset of the identified high-resolution map including the location of the second vehicle.

Abstract: Systems, methods, and computer-readable media are described for performing real-time vehicular incident risk prediction using real-time vehicle-to-everything (V2X) data. A vehicular incident risk prediction machine learning model is trained using historical V2X data such as historical incident data and historical vehicle operator driving pattern behavior data as well as third-party data such as environmental condition data and infrastructure condition data. The trained machine learning model is then used to predict the risk of an incident for a vehicle on a roadway segment based on real-time V2X data relating to the roadway segment and/or vehicle operators on the roadway segment. A notification of a high risk of incident can then be sent to a V2X communication device of the vehicle to inform an operator of the vehicle.

Abstract: A cognitive HF radio is disclosed having a cognitive engine that optimizes HF transmission parameters on the basis of learned experience with previous transmission under varying transmission and environmental conditions. Additionally, electrically small HF antennas optionally using non-Foster matching elements are disclosed. Furthermore, another electrically small HF antenna and associated impedance matching networks are disclosed, including an impedance matching network using non-Foster matching elements.

Abstract: A cognitive HF radio is disclosed having a cognitive engine that optimizes HF transmission parameters on the basis of learned experience with previous transmission under varying transmission and environmental conditions. Additionally, electrically small HF antennas optionally using non-Foster matching elements are disclosed. Furthermore, another electrically small HF antenna and associated impedance matching networks are disclosed, including an impedance matching network using non-Foster matching elements.