The present disclosure relates to a communication method and system for converging a 5th-generation (5G) communication system for supporting higher data rates beyond a 4th-generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. Embodiments herein disclose a network management apparatus, method, and computer-readable storage medium for or management of shared NSI in a communication system.

The present disclosure relates to a communication method and system for converging a 5th-generation (5G) communication system for supporting higher data rates beyond a 4th-generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. Embodiments herein disclose a network management apparatus, method, and computer-readable storage medium for or management of shared NSI in a communication system.

Embodiments include methods performed by a second network node in a wireless communications network that includes a first network node, the second network node, and a third network node. Such methods include receiving, from the first network node, a configuration comprising a pattern indicative of whether or not each of a plurality of Synchronization Signal Block (SSB) transmissions, that are configured based on a nominal timing, are actually transmitted by the third network node according to the nominal timing. Such methods include, based on the received configuration, managing transmission and/or reception configurations for one or more of the following: one or more cells served by the second network node; and one or more UEs served by the second network node via the one or more cells. Other embodiments include second network nodes configured to perform such methods.

Embodiments include methods performed by a second network node in a wireless communications network that includes a first network node, the second network node, and a third network node. Such methods include receiving, from the first network node, a configuration comprising a pattern indicative of whether or not each of a plurality of Synchronization Signal Block (SSB) transmissions, that are configured based on a nominal timing, are actually transmitted by the third network node according to the nominal timing. Such methods include, based on the received configuration, managing transmission and/or reception configurations for one or more of the following: one or more cells served by the second network node; and one or more UEs served by the second network node via the one or more cells. Other embodiments include second network nodes configured to perform such methods.

A slice manager associated with a network access point of a telecommunication network can manage combinations of network slices and bandwidth parts for user equipment (UE). The bandwidth parts can have independently set numerologies, such as subcarrier spacing values. The UE can be configured to use one or more active bandwidth parts at a time, such that the slice manager can instruct the UE to use multiple active bandwidth parts simultaneously with respect to the same network slice or multiple network slices.

In order to maintain performance during wireless communication, a transmitting electronic device may selectively perform a remedial action based on a monitored throughput. In particular, the transmitting electronic device may monitor communication with one or more receiving electronic devices, and may calculate a throughput metric based on the monitored communication. For example, the transmitting electronic device may monitor data rates, may receive feedback about the communication from at least one of the receiving electronic devices, and may determine an observed distribution of the data rates. Then, the transmitting electronic device may compare the throughput metric to a threshold value. If the throughput metric is less than the threshold value, the transmitting electronic device may perform the remedial action. This remedial action may include: denying subsequent association requests, discontinuing an existing association; and/or notifying a cellular-telephone network that the remedial action was needed.

In order to maintain performance during wireless communication, a transmitting electronic device may selectively perform a remedial action based on a monitored throughput. In particular, the transmitting electronic device may monitor communication with one or more receiving electronic devices, and may calculate a throughput metric based on the monitored communication. For example, the transmitting electronic device may monitor data rates, may receive feedback about the communication from at least one of the receiving electronic devices, and may determine an observed distribution of the data rates. Then, the transmitting electronic device may compare the throughput metric to a threshold value. If the throughput metric is less than the threshold value, the transmitting electronic device may perform the remedial action. This remedial action may include: denying subsequent association requests, discontinuing an existing association; and/or notifying a cellular-telephone network that the remedial action was needed.

A method for operating a base station is provided. The method includes in response to a triggering event, fetching information on a base station (BS) configuration parameters comprising a location, a height, an antenna pattern, and topographical details surrounding the BS; determining the BS configuration parameters that are error prone and require re-estimation; obtain measurement reports created by at least one user equipment (UE); determining an audit method to perform an audit correction, the audit correction based on the one or more of the BS configuration parameters to re-estimate, available BS information and the measurement reports; performing the audit correction, to obtain a result based on a computed score for each candidate value of the BS configuration parameters; generating, based on the result, one or more corrective actions; and adjusting at least one of the BS configuration parameters based on the one or more corrective actions.

A dynamic BSS color feature for co-hosted virtual access points is described. An example of a storage medium includes instructions to operations including enabling, by an access point, a dynamic basic service set (BSS) color feature for operation with multiple virtual access points (VAPs) hosted by the access point; switching a parameter of the access point to indicate that no co-hosted BSS is present; assigning a different BSS color to each of the VAPs; performing access point operations, including utilizing the assigned BSS colors for transmissions relating to any of the VAPs; and disabling the dynamic BSS color feature upon occurrence of one or more conditions.

Provided is a method and system for optimizing utilization and performance of a Wi-Fi network for one or more subscriber client devices through a Wi-Fi console application by monitoring an RF environment of the Wi-Fi network to detect interference to a subscriber client device from one or more neighboring client devices that include non-subscriber client devices and other subscriber client devices and allocating a spectrum/channel for the subscriber client device to access the Wi-Fi network using an AI model based on the interference detected, throughput requirements of applications running on the subscriber client device and importance/priority of an activity on the subscriber client device. The AI model constructs a relational aggregated graph and decompose the relational aggregated graph into dynamic clusters. A heuristic deep-learning method is applied to analyze the dynamic clusters to reduce a computation time for recommendation of a suitable spectrum/channel for accessing the Wi-Fi network.