Abstract: To address technical problems facing managing multiple sources of information from multiple vehicles, vehicular computing power may be exploited to process such information before sharing with others, which may help reduce network traffic overhead. A technical solution to improve this information processing over vehicular networks by using a hybrid Named Function Network (NFN) and Information Centric Network (ICN), such as in a hybrid NFN/ICN. An NFN may be used to orchestrate computations in a highly dynamic environment after decomposing the computations into a number of small functions. A function may include a digitally signed binary supplied by a car vendor or other trusted authority and executed within a controlled environment, such as a virtual machine, container, Java runtime-environment, or other controlled environment.

Abstract: Techniques are provided for optimizing the operations of an ICN, particularly for an ICN with clustered nodes. A cluster head node may function as an orchestrator and a coordinator for efficient caching, routing, and computing and for co-existence of ICN and IP nodes in the network. A content store of an ICN router may include an indication of the time after which data expires and the new data is to be swapped in place of the expired data after that point in time. Digital rights management (DRM) enforcement is provided by managing access to a DRM engine in at least one of the ICN nodes in a cluster. Congestion control is provided by minimizing the number of ICN scoped interest requests and thereby minimizing the potentially high volume of data responses. These techniques optimize interest packet forwarding and processing through collaboration with neighboring ICN nodes.

Abstract: A circuit arrangement includes a preprocessing circuit configured to obtain context information related to a user location, a learning circuit configured to determine a predicted user movement based on context information related to a user location to obtain a predicted route and to determine predicted radio conditions along the predicted route, and a decision circuit configured to, based on the predicted radio conditions, identify one or more first areas expected to have a first type of radio conditions and one or more second areas expected to have a second type of radio conditions different from the first type of radio conditions and to control radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas.

Abstract: Aspects of mmWave beam tracking and beam sweeping are described, for example, an apparatus can include an antenna array including sub-arrays and processing circuitry configured to perform beamforming, beam tracking, and management thereof at the antenna sub-arrays. The processing circuitry can further be configured to determine the angle of arrival of a received signal received in response to performing the beamforming function and adjust phase shifters of the apparatus according to the angle of arrival. Other apparatuses, systems and methods are described.

Abstract: Systems and methods of determining a device position are described. GPS and cellular signals, in addition to VIO displacement are used to determine the device position via a loose or tight coupling algorithm. Both algorithms iteratively linearize base station position equations around an intermediate position that changes each iteration based on VIO displacement and solves the linearized solutions until convergence. The loose coupling algorithm uses the GPS fix as an initiation position, linearizing and solving using the base station equations only. The tight coupling algorithm linearizes both the base station and GPS position equations, using an arbitrary initial position. To account for multipath effects, the linearization and solution are performed for multiple random sets of measurements and the position with the smallest error metric is selected.

Abstract: Methods and apparatus for predicting favored wireless service areas for drones are disclosed. A controller for a drone includes a service area identifier to identify favored wireless service areas during a flight of the drone. The favored wireless service areas are predicted by a model developed remotely from the drone. The controller also includes a service area selector to select one of the favored wireless service areas during the flight. The controller also includes a route manager to adjust a flight path of the drone during the flight based on the selected one of the favored wireless service areas.

Abstract: Various methods and devices for positioning autonomous agents including verifying a reported agent location using physical attributes of the received signal; improving agent formation for iterative localization; selecting agents for distributed task sharing; intelligent beacon-placement for group localization; relative heading and orientation determination utilizing time of flight; and secure Instrument Landing System (ILS) implementation for unmanned agents.

Abstract: A range between a first wireless device and a second wireless device is estimated using a first mechanism based on messages transmitted over a first communication channel. The first communication channel is associated with a first radio access technology capability of the wireless devices. One or more metrics indicative of an accuracy of the range estimates provided by the first mechanism are obtained. A second mechanism to estimate a range between the first wireless device and the second wireless device may be implemented in favor of the first mechanism when the metric fails to satisfy a criterion. The second mechanism is based on unicast messages transmitted over a second communication channel. The second communication channel is associated with a second radio access technology capability of the wireless devices and may be the same as, or different from, the first communication channel.

Abstract: A method of determining a position of a mobile platform includes obtaining a plurality of pseudorange measurements from multiple time epochs of a satellite navigation system (SPS) and obtaining a plurality of visual-inertial odometry (VIO) velocity measurements from a VIO system. Each time epoch of the SPS includes at least one pseudorange measurement corresponding to a first satellite and at least one pseudorange measurement corresponding to a second satellite. The method also includes combining the plurality of pseudorange measurements with the plurality of VIO velocity measurements to identify one or more outlier pseudorange measurements in the plurality of pseudorange measurements. The one or more outlier pseudorange measurements are then discarded from the plurality of pseudorange measurements to generate a remaining plurality of pseudorange measurements.

Abstract: A method of determining a trajectory of a mobile platform includes obtaining a satellite positioning system (SPS) measurement from one or more SPS signals acquired by an SPS receiver of the mobile platform. The method also includes obtaining a visual-inertial odometry (VIO) measurement of the mobile platform from a VIO system of the mobile platform. A first position estimate of the mobile platform is determined based, at least in part, on the SPS measurement and the VIO measurement. The method then includes adjusting the first position estimate to generate a smoothed position estimate based, in part, on a smoothing parameter that controls a smoothness of the trajectory. The trajectory of the mobile platform is then determined, at least in part, using the smoothed position estimate.

Abstract: Systems, methods, computer program products, and apparatuses to determine, by a neural network based on training data related to wireless signals exchanged by a device and a plurality of wireless access points in an environment, a respective distance between the device and each wireless access point, receive location data related to a respective location of each wireless access point of the plurality of wireless access points, determine a geometric cost of the neural network based on a geometric cost function, the respective distances, and the received location data, and train a plurality of values of the neural network based on a backpropagation and the determined geometric cost.

Abstract: A circuit arrangement includes a preprocessing circuit configured to obtain context information related to a user location, a learning circuit configured to determine a predicted user movement based on context information related to a user location to obtain a predicted route and to determine predicted radio conditions along the predicted route, and a decision circuit configured to, based on the predicted radio conditions, identify one or more first areas expected to have a first type of radio conditions and one or more second areas expected to have a second type of radio conditions different from the first type of radio conditions and to control radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas.

Abstract: Systems and techniques for information centric network (ICN) emergency data collection are described herein. For example, an event coverage area may be measured. An interest packet may be transmitted to map nodes within the coverage area. In an example, the interest packet specifies a group prefix. A group of nodes that respond to the interest packet may be selected as event detecting nodes. Then, an event subscription interest packet may be transmitted to the event-detecting nodes.

Abstract: Systems and techniques for efficient remote function execution in an information centric network (ICN) are described herein. For example, a requestor node may transmit an admission probe interest packet. Here, the admission probe interest packet includes a name that includes a function. The admission probe interest packet also includes a metric of a parameter of the function. In response, the requestor node may receive a manifest data packet. The manifest includes a metric of function execution at a node that created the manifest data packet. The manifest also includes a name of an implementation of the function. The requestor node may then determine that the metric of function execution meets a threshold and transmit an interest packet that includes the name of the implementation of the function.

Abstract: Systems and techniques for machine generation of content names in an information centric network (ICN) are described herein. For example, a node may obtain content. An inference engine may be invoked to produce a name for the content. Once the content is named, the node may respond to an interest packet that includes the name of the content. The response is a data packet that includes the content.

Abstract: Systems and techniques for information centric network (ICN) interworking are described herein. For example, a request may be received at a convergence layer of a node. Here, the request originates from an application on the node. A network protocol, from several available to the node, may be determined to transmit the request. The node then transmits the request via the selected network protocol.

Abstract: Systems and techniques for mission critical (MC) push notification mechanism in a high-reliability (HR) information centric network (ICN) are described herein. For example, a node may test network links to other nodes to classify the other nodes into proximate nodes and non-proximate nodes based on a reception metric. The node may then elect a set of leader nodes from the proximate nodes. Here, the set of leader nodes are selected based on link quality between respective leader nodes and non-proximate nodes. The node may detect an MC event and create an ICN data packet that contains data from the MC event. The node may then transmit the ICN data packet to the set of leader nodes that then relay the ICN data packet to the non-proximate nodes.

Abstract: A wireless communication device according to some aspects includes an output determiner configured to determine first weighted signals for a plurality of antennas with first beamforming weights, a selector configured to select, from the plurality of antennas, a reference antenna based on signal powers of the first weighted signals, a weight controller configured to determine second beamforming weights for a predetermined number of antennas of the plurality of antennas based on a difference between the first weighted signal of the reference antenna and the first weighted signals of the predetermined number of antennas, the output determiner further configured to determine second weighted signals for the plurality of antennas with the second beamforming weights.

Abstract: A communication circuit arrangement includes a first kernel dimension filter circuit configured to apply a first kernel dimension filter to a first input signal to estimate a first kernel dimension interference signal from a first amplifier, a second kernel dimension filter circuit configured to apply a second kernel dimension filter to a second input signal to estimate a second kernel dimension interference signal from a second amplifier, a joint delay tap dimension filter configured to apply a joint delay tap dimension filter to a combination of the first kernel dimension interference signal and the second kernel dimension interference signal to obtain an estimated joint interference signal, and a cancelation circuit configured to remove the estimated joint interference signal from a received signal to obtain a clean signal.

Abstract: An apparatus and a method for identifying a desired signal and suppressing co-channel interference in real-time from a signal received over a wireless channel are disclosed. For example, the method, by a circuit, determines values of a first set of terms of a cost function that are based on received data, the cost function being a measure of a level of the received data being non-Gaussian, determines, by the circuit, optimal values of a set of weight vectors for maximizing the cost function, identifies, by the circuit, a desired signal based on the optimal values of the set of weight vectors and the values of the first set of terms, and decodes, by a channel decoder coupled to the circuit, a channel of the desired signal that is identified.