With multiple connections (20) communicatively coupling a User Equipment (UE) (12) to a wireless communication network (10), methods and apparatuses disclosed for performing flow control at the Radio Link Control (RLC) level advantageously control the shares of overall data conveyed on the respective connections (20) in a manner that accounts for changing conditions on the involved radio links (22) while accommodating signaling delays and other complexities that arise from distributed or virtualized implementations of the underlying processing apparatuses (18). The disclosed methods and apparatuses have applicability both to uplink multi-connectivity and downlink multi-connectivity, and apply to various multi-connectivity scenarios, including scenarios involving mixed Radio Access Technologies (RATs) and Carrier Aggregation (CA) configurations that aggregate two or more Component Carriers (CCs) for carrying user traffic between a UE (12) and the network (10).

Aspects of the subject disclosure may include, for example, identifying geographic clusters that are similar based on metrics and geo-spatial association. Embodiments of the disclosure are directed to operations that include obtaining data corresponding to a communication network, applying a first algorithm to the data to generate a plurality of bins, generating a respective score for each bin of the plurality of bins, applying a second algorithm, based on the respective scores, to generate a plurality of clusters, and generating a graph for each cluster of the plurality of clusters, wherein vertices of each graph are represented by the bins of the cluster, and wherein edges of each graph connect the bins of the cluster to adjacent bins of the cluster. Other embodiments are disclosed.

A method for distributing connections to mobility management node instances includes publishing IP addresses for receiving connection requests and ingress messages from RAN nodes. The method further includes maintaining connection loading measurements of the mobility management node instances, receiving a connection request message generated by a RAN node for initiating a connection with one of the mobility management node instances, applying a connection distribution algorithm to select a mobility management node instance to handle the connection request message, and creating an association between an IP address of the selected mobility management node instance and an IP address and port of the RAN node extracted from a source IP address and source port field of the connection request. The method further includes forwarding the connection request message to the selected mobility management node instance.

A satellite communication method and a network device are disclosed. A first network device learns of traffics of a plurality of satellite communications link or air interface resources allocated to a plurality of satellite base stations. The first network device sends identification information to a second network device, where the identification information indicates that a traffic of a satellite communications link reaches a specified threshold, or that an air interface resource allocated by a ground station to a satellite base station reaches a specified threshold. The second network device receives an identifier message, determines a to-be-linked satellite base station that has an idle resource, and sends, to the to-be-linked satellite base station, a second message including information about a generated beam of the to-be-linked satellite base station.

A method and apparatus for enhancing load balancing within wireless networks and, in particular, within wireless networks operating within Enterprise Networks is disclosed. The method and apparatus efficiently balance the load that is shouldered by each BS/AP within the wireless network. This is particularly advantageous within wireless networks operating within an Enterprise Network. Improved BS/AP deployments in Enterprise Networks that maintain high system throughput in the EN while optimizing the performance of UEs (with regard to battery utilization and service) are disclosed. Improved EN deployments for UE mobility that reduces measurement scans required of and performed by the UEs are disclosed.

A programmable device includes a plurality of first partial reconfiguration slots, a plurality of transceivers and a second partial reconfiguration slot. The plurality of first partial reconfiguration slots are configured to execute one or more applications or network functions. The second partial reconfiguration slot is configured to route data traffic flows between the plurality of first partial reconfiguration slots and the plurality of transceivers.

A load balancing method and device, a storage medium and an electronic device are provided. The method includes the following operations. A first node receives cell available resource information of a target cell of a second node from the second node, wherein the cell available resource information includes at least one of: an overlapping situation of the cell with other cells in a frequency domain, an available resource of the cell obtained by performing predetermined processing on an original available resource of the cell according to the overlapping situation of the cell with other cells in the frequency domain, an available resource of one or more beams in the cell, and one or more beam identifiers of the one or more beams in the cell. The first node performs load balancing according to the cell available resource information of the target cell of the second node.

Embodiments are directed towards systems and methods for user plane function (UPF) and network slice load balancing within a 5G network. Example embodiments include systems and methods for load balancing based on current UPF load and thresholds that depend on UPF capacity; UPF load balancing using predicted throughput of new UE on the network based on network data analytics; UPF load balancing based on special considerations for low latency traffic; UPF load balancing supporting multiple slices, maintaining several load-thresholds for each UPF and each slice depending on the UPF and network slice capacity; and UPF load balancing using predicted central processing unit (CPU) utilization and/or predicted memory utilization of new UE on the network based on network data analytics.

The present disclosure provides for methods, apparatuses, and non-transitory computer-readable storage media for load balancing traffic scenarios by a network device. In an embodiment, a method includes training a plurality of learning agents to load balance a respective plurality of traffic scenarios to obtain a plurality of control policies. The method further includes performing at least one clustering iteration. Each clustering iteration includes selecting a pair of control policies and merging the pair of control policies into a clustered control policy that replaces the pair of control policies. The method further includes determining to stop the performing of the at least one clustering iteration when a quantity of control policies remaining in the plurality of control policies meets a predetermined value. The method further includes deploying to each base station of a plurality of base stations a corresponding control policy from the plurality of control policies.

Embodiments are directed towards embodiments are directed toward systems and methods for user plane function (UPF) and network slice load balancing within a 5G network. Example embodiments include systems and methods for load balancing based on current UPF load and thresholds that depend on UPF capacity; UPF load balancing using predicted throughput of new UE on the network based on network data analytics; UPF load balancing based on special considerations for low latency traffic; UPF load balancing supporting multiple slices, maintaining several load-thresholds for each UPF and each slice depending on the UPF and network slice capacity; and UPF load balancing using predicted central processing unit (CPU) utilization and/or predicted memory utilization of new UE on the network based on network data analytics.