Abstract:
A method for decompressing data includes receiving, by a network element, a first plurality of packets. Also, the method includes receiving, by the network element, a second plurality of packets. Additionally, the method includes decompressing the first plurality of packets by a first decompressor using a first compression scheme and decompressing the second plurality of packets by a second decompressor using a second compression scheme.
Abstract:
A method includes receiving, by a first device from a second device, a plurality of encoded messages on a plurality of transmission time intervals (TTIs), where the plurality of encoded messages are forward error correction (FEC) encoded, and where the FEC spans the plurality of encoded messages and decoding the plurality of encoded messages using FEC. The method also includes determining a plurality of decoding status messages in accordance with decoding the plurality of encoded messages and transmitting, by the first device to the second device, the plurality of decoding status messages less often than once every TTI.
Abstract:
Visual information from camera sensors can be used to assign scheduling and/or transmission parameters in a wireless network. For example, the visual information can be used to visually discover a user equipment (UE) prior to initiating link discovery. This may be accomplished by analyzing the visual information to identify an absolute or relative position of the UE. The positioned may then be used to select antenna configuration parameters for transmitting a discovery signal, e.g., direction of departure (DoD), angle of departure (AoD), precoder. As another example, the visual information is used to predict a link obstruction over a radio interface between a UE and an AP. In yet other examples, the visual information may be used for traffic engineering purposes, such as to predict a traffic density or pair UEs with APs.
Abstract:
A system and method for agile wireless access network is provided. A method embodiment for agile radio access network management includes determining, by a network controller, capabilities and neighborhood relations of radio nodes in the radio access network. The network controller then configures a backhaul network infrastructure for the radio access network in accordance with the capabilities and the neighborhood relations of the radio nodes.
Abstract:
Interference costs on virtual radio interfaces can be modeled as a function of loading in a wireless network to estimate changes in spectral efficiency and/or resource availability that would result from a provisioning decision. In one example, this modeling is achieved through cost functions that are developed from historical and/or simulated resource cost data corresponding to the wireless network. The cost data may include interference data, spectral efficiency data, and/or loading data for various links over a common period of time (e.g., a month, a year, etc.), and may be analyzed and/or consolidated to obtain correlations between interference costs and loading on the various links in the network. As an example, a cost function may specify an interference cost on one virtual link as a function of loading on one or more neighboring virtual links.
Abstract:
A method includes receiving, by a first device from a second device, a plurality of encoded messages on a plurality of transmission time intervals (TTIs), where the plurality of encoded messages are forward error correction (FEC) encoded, and where the FEC spans the plurality of encoded messages and decoding the plurality of encoded messages using FEC. The method also includes determining a plurality of decoding status messages in accordance with decoding the plurality of encoded messages and transmitting, by the first device to the second device, the plurality of decoding status messages less often than once every TTI.
Abstract:
Embodiments are provided for a location-based network discovery and connection establishment, which take advantage of location/positioning technology of user equipment (UE) and resolve issues above of the blind search approaches. The location-based network discovery and connection establishment schemes use UE location information and a network access MAP to speed up network discovery, and remove the need for continuous search and measurement by the UE. The schemes also reduce the search space. A wireless network access map (MAP) is provided to the UE. The UE uses the MAP information with UE current location information to reduce the search space and speed up network discovery and radio connection establishment with the network. Network operators can use this network access MAP to control the network access and manage the network load distribution. The network access MAP can be customized for each UE.
Abstract:
Interference costs on virtual radio interfaces can be modeled as a function of loading in a wireless network to estimate changes in spectral efficiency and/or resource availability that would result from a provisioning decision. In one example, this modeling is achieved through cost functions that are developed from historical and/or simulated resource cost data corresponding to the wireless network. The cost data may include interference data, spectral efficiency data, and/or loading data for various links over a common period of time (e.g., a month, a year, etc.), and may be analyzed and/or consolidated to obtain correlations between interference costs and loading on the various links in the network. As an example, a cost function may specify an interference cost on one virtual link as a function of loading on one or more neighboring virtual links.
Abstract:
Predicting mobile station migration between geographical locations of a wireless network can be achieved using a migration probability database. The database can be generated based on statistical information relating to the wireless network, such as historical migration patterns and associated mobility information (e.g., velocities, bin location, etc.). The migration probability database consolidates the statistical information into mobility prediction functions for estimating migration probabilities/trajectories based on dynamically reported mobility parameters. By example, mobility prediction functions can compute a likelihood that a mobile station will migrate between geographic regions based on a velocity of the mobile station. Accurate mobility prediction may improve resource provisioning efficiency during admission control and path selection, and can also be used to dynamically adjust handover margins.
Abstract:
Embodiments are provided for traffic scheduling based on user equipment (UE) in wireless networks. A location prediction-based network scheduler (NS) interfaces with a traffic engineering (TE) function to enable location-prediction-based routing for UE traffic. The NS obtains location prediction information for a UE for a next time window comprising a plurality of next time slots, and obtains available network resource prediction for the next time slots. The NS then determines, for each of the next time slots, a weight value as a priority parameter for forwarding data to the UE, in accordance with the location prediction information and the available network resource prediction. The result for the first time slot is then forwarded from the NS to the TE function, which optimizes, for the first time slot, the weight value with a route and data for forwarding the data to the UE.