Abstract:
A method for operating a first device-to-device (D2D) device in a cellular communications system includes receiving geo-location information from a first entity in the cellular communications system, the geo-location information including location information for cellular users of the cellular communications system and resources of the cellular communications system available to the cellular users, selecting one of the resources to avoid causing interference to a cellular transmission, the resource being selected in accordance with the geo-location information, and transmitting to a second D2D device over the selected resource.
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:
An embodiment method includes receiving service parameters for a service and locating logical network nodes for a service-specific data plane logical topology at respective physical network nodes among a plurality of physical network nodes according to the service parameters, a service-level topology, and a physical infrastructure of the plurality of physical network nodes. The method also includes defining connections among the logical network nodes according to the service parameters, the service-level topology, and the physical infrastructure, and defining respective connections for a plurality of UEs to at least one of the logical network nodes according to the service parameters, the service-level topology, and the physical infrastructure. The method further includes defining respective functionalities for the logical network nodes.
Abstract:
Systems, devices and methods for link level communication between a user equipment and plurality of network devices are described. A user equipment can include at least one processor configured to: after broadcasting a first data message to the plurality of base stations, receive one or more acknowledgements, corresponding to the first data message, from at least one of the plurality of base stations; and upon receipt of at least one acknowledgement, broadcast an indicator to the plurality of base stations, the indicator providing an indication of at least one of the at least one received acknowledgement.
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 user equipment (UE) may compute uplink power control levels as a function of a downlink signal to noise ratio (SNIR). For example, the UE may determine an uplink transmit power level by summing a full power control (FPC) transmit power level, a product of a first adjustment factor (β) and the downlink SNIR, and a negative of a second adjustment factor (Δ2) when the product of the first adjustment factor (β) and the downlink SNIR is greater than or equal to the second adjustment factor (Δ2). A UE may also compute an uplink power control level as a function of target and/or current interference levels associated with neighboring base stations. A UE may also iteratively reduce a transmit power level until an interference level experienced by a neighboring base station has fallen below a threshold.
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:
Inter-cell interference can be reduced by re-assigning uplink scheduling responsibilities for a user equipment (UE) from a controller associated with a serving access point (AP) to a controller associated with a neighboring AP, as the controller associated with the neighboring AP may have better access to channel information corresponding to interference experienced by the neighboring AP as a result of uplink transmissions from the UE. After the re-assignment, the controller associated with the neighboring AP may independently schedule an uplink transmission parameter (e.g., a transmit power level, a modulation coding scheme level and/or a precoder) of the UE in a manner that mitigates inter-cell-interference in the neighboring cell.