FACILITATING IMPLEMENTATION OF COMMUNICATION NETWORK DEPLOYMENT THROUGH NETWORK PLANNING IN ADVANCED NETWORKS

    公开(公告)号:US20220369118A1

    公开(公告)日:2022-11-17

    申请号:US17314936

    申请日:2021-05-07

    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.

    Radio access network control with deep reinforcement learning

    公开(公告)号:US11494649B2

    公开(公告)日:2022-11-08

    申请号:US16778031

    申请日:2020-01-31

    Abstract: A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.

    CONTROLLING QUALITY OF SERVICE CLASS IDENTIFIER WEIGHTS FOR IMPROVED PERFORMANCE IN 5G OR OTHER NEXT GENERATION NETWORKS

    公开(公告)号:US20220141706A1

    公开(公告)日:2022-05-05

    申请号:US17574957

    申请日:2022-01-13

    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.

    APPARATUSES AND METHODS FOR NETWORK RESOURCE DIMENSIONING IN ACCORDANCE WITH DIFFERENTIATED QUALITY OF SERVICE

    公开(公告)号:US20220086664A1

    公开(公告)日:2022-03-17

    申请号:US17538037

    申请日:2021-11-30

    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.

    APPARATUSES AND METHODS FOR NETWORK RESOURCE DIMENSIONING IN ACCORDANCE WITH DIFFERENTIATED QUALITY OF SERVICE

    公开(公告)号:US20210352493A1

    公开(公告)日:2021-11-11

    申请号:US16868718

    申请日:2020-05-07

    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.

    TIME DISTANCE OF ARRIVAL BASED MOBILE DEVICE LOCATION DETECTION WITH DISTURBANCE SCRUTINY

    公开(公告)号:US20180227876A1

    公开(公告)日:2018-08-09

    申请号:US15946163

    申请日:2018-04-05

    CPC classification number: H04W64/00 G01S5/10

    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.

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