Abstract:
Distribution of traffic to cells in a communication network can be controlled. User equipment (UE) can perform measurements regarding signal quality with cells and communicate measurement information and a connection request to a source cell. The source cell can establish an initial connection with the UE. Meanwhile, the UE can perform additional measurements and communicate additional measurement information to the source cell. A distribution management component (DMC) can analyze the measurement information and cell-related information and determine whether to redirect the UE from the source cell to a target cell based on the analysis results. If the DMC determines that the UE is to be redirected to the target cell, the DMC can release the connection to the source cell and communicate a redirect message that includes target cell information to the UE, and the UE can send a connection request to the target cell.
Abstract:
A device can receive, from a network node device, call trace event data relating to characteristics of a wireless communication session between the network node device and a user equipment. The device can sequence and combine the call trace event data for a period of the wireless communication session. The device can analyze the call trace event data to determine a category of network communication traffic transmitted via a communication channel between the network node device and the user equipment. In response to a determination that the network communication traffic comprises streaming video packets, the device can facilitate directing of network resources to be allocated to support the wireless communication session.
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:
A method, computer readable medium and apparatus for calculating a capacity for high speed packet access data in a link in a communications network are disclosed. For example, the method initializes parameters associated with streaming data, long elastic data and short elastic data, determines, via a processor, a capacity value such that a quality of service metric is met for the streaming data, the long elastic data and the short elastic data and provisions the link with the capacity value if the quality of service metric is met.
Abstract:
A method and apparatus for selecting a bandwidth option for a cell in a network are disclosed. For example, the method obtains, for the cell, network traffic data for a geographical area for mobility traffic and fixed wireless traffic, a physical characteristic of an antenna in the geographical area, and a type of connectivity at a customer premise, determines a busy time data traffic from the network traffic data for both the fixed wireless traffic and the mobility traffic, determines, for the cell, a cell range from the physical characteristic of the antenna and the type of connectivity at the customer premise, selects a bandwidth option from a plurality of bandwidth options, and determines an average throughput in accordance with the bandwidth option that is selected and the cell range, wherein the average throughput comprises a throughput for serving both the mobility traffic and the fixed wireless traffic.
Abstract:
Facilitating implementation of communication network deployment through network planning in advanced networks (e.g., 5G, 6G, and beyond) is provided herein. Operations of a system can include, configuring a first deployment scenario for first network equipment and a second deployment scenario for second network equipment. The first deployment scenario is selected from a group of first deployment scenarios and can include a first parameter. The second deployment scenario is selected from a group of second deployment scenarios and can include a second parameter. The configuring can include determining that a sum of the first parameter and the second parameter satisfies a function of a defined parameter level. The operations also can include facilitating a first enactment of the first deployment scenario for the first network equipment and a second enactment of the second deployment scenario for the second network equipment.
Abstract:
Aspects of the subject disclosure may include, for example, obtaining first information indicative of data plane utilization, wherein the data plane is associated with a wireless communications network; obtaining second information indicative of control plane utilization, wherein the control plane is associated with the wireless communications network; applying the first information and the second information to one or more machine learning algorithms; and generating via the one or more machine learning algorithms one or more outputs, wherein the one or more outputs indicates whether one or more network resources should be added to improve the data plane utilization. Other embodiments are disclosed.
Abstract:
Intelligent, adaptive scheduling weight adjustment is enabled, e.g., to improve network performance. For instance, A non-transitory machine-readable medium can comprise executable instructions that, when executed by a processor, facilitate performance of operations, comprising based on key performance indicators corresponding to data traffic flows via a network, determining quality of service data representative of respective qualities of service for the data traffic flows, using a scheduling weight data traffic model generated using machine learning and trained using past quality of service data representative of past qualities of service of past data traffic flows via the network, from prior to the data traffic flows, and past scheduling weight settings applied to the past data traffic flows, determining a scheduling weight setting to be applied to a data traffic flow of the data traffic flows, and applying the scheduling weight setting to the data traffic flow.
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.
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.