Abstract:
Intelligent, automated, fixed wireless internet planning (e.g., using a computerized tool) is enabled. For instance, a system can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: determining, for a user equipment determined to be within a defined coverage area, a signal to interference and noise ratio, based on the signal to interference and noise ratio, determining a spectral efficiency value corresponding to the user equipment, based on the spectral efficiency value and a total available bandwidth of a network via which the defined coverage area is enabled, determining an available throughput corresponding to the user equipment, and in response to a determination that the available throughput exceeds a threshold throughput, designating the user equipment, in a data store, as being covered within the defined coverage area by the total available bandwidth of the network.
Abstract:
Aspects of the subject disclosure may include, for example, a non-transitory machine-readable storage medium comprising executable instructions that, when executed by a processing system including a processor, perform operations comprising: identifying a first plurality of cells as a controlled group of cells; determining, for each cell of the controlled group of cells, an average number of allocated physical resource blocks; determining, for each cell of the controlled group of cells, a total number of physical resource blocks available to carry payload traffic; determining, for each cell of the controlled group of cells, a metric equal to: (a) the average number of allocated physical resource blocks of the cell divided by (b) the total number of physical resource blocks of the cell available to carry payload traffic; and performing a load balancing of the controlled group of cells based upon the metric. Other embodiments are disclosed.
Abstract:
Techniques for locating a mobile device using a time distance of arrival (TDOA) method with disturbance scrutiny are provided. In an aspect, for respective combinations of three base station devices of a number of base station devices greater than or equal to three, intersections in hyperbolic curves, generated using a closed form function with input values based on differences of distances from the device to pairs of base station devices of the respective combinations of three base station devices, are determined. The intersection points are then tested for robustness against measurement errors associated with the input values and a subset of the intersection points that are associated with a degree of resistance to the measurement errors are selected to estimate a location of the device.
Abstract:
User quality of experience assessment in radio access networks is provided herein. A method can include measuring an average packet size of incoming data packets received via a radio access network, the incoming data packets respectively comprising data directed to respective network equipment served via the radio access network; determining service metrics for outgoing data packets transmitted via the radio access network to the respective network equipment in response to the incoming data packets being received via the radio access network, wherein the service metrics comprise an average transmission delay for the outgoing data packets and a packet loss rate for the outgoing data packets; and determining a quality of experience value associated with a performance of the radio access network based on a function of the average packet size of the incoming data packets and the service metrics for the outgoing data packets.
Abstract:
Aspects of the subject disclosure may include, for example, calculating a respective first quality metric for each cell of a plurality of cells included in a network, calculating a respective second quality metric for each cell of the plurality of cells, calculating a capacity of each cell of the plurality of cells in accordance with the first quality metric for the cell and the second quality metric for the cell, and allocating traffic of the network amongst the plurality of cells in accordance with the respective capacity of each cell of the plurality of cells. Other embodiments are disclosed.
Abstract:
The disclosed technology is directed towards load balancing in an adaptive and automated way for wireless mobility networks to improve the overall harmonic-average UE throughput within each controlled group of cells (e.g., different frequency carriers serving a sector of a base station). A load balancer (e.g., analytics component) obtains various device traffic data including throughput data for cells of a group. Pairs of cells in a group (sharing a site and face) can be selected based on satisfying various criteria, with estimated throughput gain achieved by changing the handoff rates between the cell pairs. The technology iteratively repeats the overall process, driving a system to an optimal equilibrium.
Abstract:
Aspects include determining whether a utilization of wireless spectrum associated with a guaranteed class of traffic in a network is greater than a first threshold, responsive to the determining indicating that the utilization of the wireless spectrum associated with the guaranteed class of traffic is greater than the first threshold, causing an upgrade of a capacity in the network, and responsive to the determining indicating that the utilization of the wireless spectrum associated with the guaranteed class of traffic is not greater than the first threshold: determining a throughput for a non-guaranteed class of traffic for each cell of a plurality of cells of the network, and responsive to determining that the throughput for the non-guaranteed class of traffic for at least one cell of the plurality of cells is less than a second threshold, causing the upgrade of the capacity in the network. Other embodiments are disclosed.
Abstract:
The disclosed technology describes on-demand adjusting of the quality of service (QoS) class identifier (QCI) relative weight settings for different QCI classes associated with user devices. A QoS controller, which can be implemented in a standalone or a cloud configuration, updates the QCI weight settings as requested or needed to deal with changing network environments, such as growing traffic, different RF conditions, new devices, ratio of different service classes of user devices, to improve the overall performance of one or more cell sites. In one implementation, the QoS controller collects actual network statistics, and runs simulations based on those statistics with different groups of candidate QCI weight settings to generate multiple result sets. The QoS controller evaluates the result sets to determine which group of QCI weight settings meets desired performance objectives, and then applies those QCI weight settings to one or more NodeBs for use with actual data traffic.
Abstract:
Aspects of the subject disclosure may include, for example, calculating a throughput of each cell of a plurality of cells of a communication network, calculating a total throughput of the plurality of cells, and distributing, in accordance with a first distribution, carrier aggregated traffic amongst the plurality of cells, wherein each cell obtains a respective portion of the carrier aggregated traffic as part of the first distribution in accordance with the throughput of the cell and the total throughput. Other embodiments are disclosed.
Abstract:
Distribution of traffic to cells in a communication network can be controlled. A distribution management component (DMC) can determine overall device traffic throughput for cells of a sector that satisfy a defined traffic throughput criterion relating to a harmonic mean of the device traffic throughput for the cells to desirably enhance or maximize the harmonic mean of the overall device traffic throughput. Based on the overall device traffic throughput for the cells, the DMC can determine whether to adjust a characteristic associated with a cell of the cells to facilitate adjusting distribution of device traffic among the cells of the sector to achieve desirable load balancing of traffic by the sector and in the network. Load balancing can be achieved by controlling respective parameters with regard to communication devices that are in idle mode or connected mode to facilitate directing communication devices and associated traffic to desired cells.