Abstract:
In accordance with an embodiment, a method of operating a base station in a wireless system, includes partitioning a frequency band into at least one band of a first type and at least one band of a second type, and coordinating the partitioning with at least one further base station. The at least one band of the first type includes a band on which the base station transmits power proportional to a distance of a user device from the base station, and the at least one band of the second type comprises a band on which base station transmits a data rate inversely proportional to a distance of a user device from the base station.
Abstract:
Embodiments are provided for assessing radio resource requirements using virtual bin virtualization. An embodiment method includes receiving a service request from a user equipment (UE) in a geographical bin. Resource requirements are then obtained, from a lookup table (LUT), for a serving radio node and neighbor radio nodes associated with the geographic bin of the UE. The LUT comprises a plurality of entries that map combinations of path losses of wireless links for the serving radio node and neighbor radio nodes to corresponding combinations of resource requirements. The entries of the path losses further include one or more service specific and network node parameters for the serving radio nodes and neighbor radio nodes, which are also mapped to the resource requirements. The obtained resource requirements are then assessed, including deciding whether to serve the UE according to the resource requirements and to resource availability.
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.
Abstract:
The computational complexity of MCS adaptation for linear and non-linear MU-MIMO can be reduced by avoiding QR decomposition during subsequent stages of MCS adaptation. For instance, QR decomposition can be avoided in later stages of MCS adaptation by computing an instant upper right triangular matrix (R1) directly from an earlier upper right triangular matrix (R) and an earlier unitary matrix (U), which were obtained during a previous stage of MCS adaptation. As such, the instant upper right triangular matrix (R1) is obtained without performing QR decomposition on an instant Hermitian matrix (H1H), thereby allowing MCS adaptation to be performed for the new user group with less complexity. Additionally, computational complexity of MCS adaptation for linear MU-MIMO can be further reduced by avoiding matrix inversion during subsequent stages of MCS adaptation.
Abstract:
Methods and devices for reducing traffic over a wireless link through the compression or suppression of high layer packets carrying predictable background data prior to transportation over a wireless link. The methods include intercepting application layer protocol packets carrying the predictable background data. In embodiments where the background data is periodic in nature, the high layer packets may be compressed into low-layer signaling indicators for communication over a low-layer control channel (e.g., an on off keying (OOK) channel). Alternatively, the high layer packets may be suppressed entirely (not transported over the wireless link) when a receiver side daemon is configured to autonomously replicate the periodic background nature according to a projected interval. In other embodiments, compression techniques may be used to reduce overhead attributable to non-periodic background data that is predictable in context.
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:
The computational complexity of MCS adaptation for linear and non-linear MU-MIMO can be reduced by avoiding QR decomposition during subsequent stages of MCS adaptation. For instance, QR decomposition can be avoided in later stages of MCS adaptation by computing an instant upper right triangular matrix (R1) directly from an earlier upper right triangular matrix (R) and an earlier unitary matrix (U), which were obtained during a previous stage of MCS adaptation. As such, the instant upper right triangular matrix (R1) is obtained without performing QR decomposition on an instant Hermitian matrix (H1H), thereby allowing MCS adaptation to be performed for the new user group with less complexity. Additionally, computational complexity of MCS adaptation for linear MU-MIMO can be further reduced by avoiding matrix inversion during subsequent stages of MCS adaptation.
Abstract:
An embodiment user equipment has a list of predictive data that a user may request, and programming to receive prefetched data based on the list of predictive data at a reduced cost, wherein the reduced cost is lower than a network cost of downloading the data, and to store the prefetched data within the UE for future consumption. An embodiment base station has a list of predictive data a UE may request, a high priority queue for data requested by the UE, and a low priority queue with predictive data corresponding to the list of predictive data. The base station further includes programing to send the requested data and to send the predictive data.