An orchestration tool determines optimal user plane function (UPF) positioning by using edge nodes as proxy for UPF performance prediction. A disclosed solution includes: using a plurality of edge nodes as proxies to predict performance of a UPF, which has not yet been built, for routing data packets to a proxy-call session control function (P-CSCF) from locations of each of the plurality of edge nodes; selecting, by an orchestrator, a first edge node location; and generating, by the orchestrator, an alert indicating selection of the first edge node location. A first UPF will be built at the first edge node location although, in some examples, upon further monitoring, the orchestrator may determine that the second edge node location will outperform the first edge node location, resulting in the UPF moving to the second edge node location. In some examples, performance criteria depend on traffic type (e.g., real-time gaming).

One embodiment is directed to an open radio access network (O-RAN) distributed antenna system (DAS) that comprises a central access node (CAN) configured to communicatively couple at least one O-RAN distributed unit (O-DU) to the O-RAN DAS, where the O-DU is configured to communicate with a single O-RAN remote unit (O-RU) entity. The O-RAN DAS also includes a plurality of O-RAN remote units (O-RUs) communicatively coupled to the CAN over a fronthaul network, where the O-DU, CAN, and O-RUs are configured to natively use an O-RAN fronthaul interface to communicate fronthaul data over the fronthaul network. The CAN is configured to appear to the O-DU as the single O-RU entity for a cell served by the O-DU even though the CAN is configured to serve the cell using multiple O-RUs that form a simulcast group for that cell. One or more CANs can be used. Other embodiments are disclosed.

One embodiment is directed to an open radio access network (O-RAN) distributed antenna system (DAS) that comprises a central access node (CAN) configured to communicatively couple at least one O-RAN distributed unit (O-DU) to the O-RAN DAS, where the O-DU is configured to communicate with a single O-RAN remote unit (O-RU) entity. The O-RAN DAS also includes a plurality of O-RAN remote units (O-RUs) communicatively coupled to the CAN over a fronthaul network, where the O-DU, CAN, and O-RUs are configured to natively use an O-RAN fronthaul interface to communicate fronthaul data over the fronthaul network. The CAN is configured to appear to the O-DU as the single O-RU entity for a cell served by the O-DU even though the CAN is configured to serve the cell using multiple O-RUs that form a simulcast group for that cell. One or more CANs can be used. Other embodiments are disclosed.

Various network slice assignment arrangements are presented. A network slice management system can create a multi-dimensional attribute matrix that defines network slices that operate on a physical cellular network. Using a machine learning algorithm, network slices that operate on the physical cellular network can be clustered based on attributes to create slice classes. A classification process to determine a slice class that most closely matches a cellular network service request may be performed. A network slice can then be selected from the slice class and be used for providing cellular network service.

Systems and methods model earth stations and other captive terrestrial sites as simulated cell sites in a radio access network (RAN) to identify potential cellular network interferers with the earth stations. A computing device selects an earth station within a geographic area of a RAN segment and model the earth station as a cell within the RAN segment, wherein the modeling creates a simulated earth station cell. The computing device obtains sector carrier data for cells in the RAN segment and scores, based on the sector carrier data, neighboring cells to the simulated earth station cell. The scoring indicates a level of potential interference of the neighboring cells with the earth station based on geo-spatial relevance. The computing device identifies projected mobility interference in neighboring cells to the earth station and provides prioritization recommendations for interference mitigation for the earth station based on the scoring and the identifying.

Techniques are described for dynamic bid-driven reconfiguration in a wireless communication network. An analytics front-end system (AFES) can be implemented in a provider network. The AFES can obtain network service experience (NSE) predictions derived by a network data analytics function (NWDAF) based on network status data received from back-end network functions of the provider network. The AFES can generate bid options based on the NSE predictions, each having a respective NSE definition and bid value. The bid options can be output to a user bidding interface, via which a user can review and select the bid options. In response to the user selecting one of the bid options, the AFES can direct a network policy server to update one or more subscriber policy definitions for one or more subscribers based on the respective NSE definition of the selected bid option, thereby dynamically updating at least one subscriber's NSE.

Techniques are described for dynamic bid-driven reconfiguration in a wireless communication network. An analytics front-end system (AFES) can be implemented in a provider network. The AFES can obtain network service experience (NSE) predictions derived by a network data analytics function (NWDAF) based on network status data received from back-end network functions of the provider network. The AFES can generate bid options based on the NSE predictions, each having a respective NSE definition and bid value. The bid options can be output to a user bidding interface, via which a user can review and select the bid options. In response to the user selecting one of the bid options, the AFES can direct a network policy server to update one or more subscriber policy definitions for one or more subscribers based on the respective NSE definition of the selected bid option, thereby dynamically updating at least one subscriber's NSE.

Disclosed are systems and methods for a robust Self-Organizing Network (SON) framework that quantifies SON applications' control and management of a network into key performance indicators (KPI) that are leveraged to determine the impact of a SON's application effectiveness in regulating network parameters, which then dictates how the SON application operates. The disclosed framework is configured to receive multiple data streams from existing data sources, determine the performance of a node on a network, and then automatically perform SON operations based therefrom. The disclosed framework can utilize this information to predict additional and/or future opportunities for SON automation on the network.

Methods and apparatus for determining a desired or optimal location for one or more access points within a premises. In one embodiment, software is provided to wireless-enabled client devices in a user premises; the software enables each of the devices to communicate with one another and collect a plurality of data relating to the connectivity of each at various locations within the premises. The data is used to determine a desired or optimal location for placement of an access point. Once the optimal location is determined, the access point is placed, and the client devices communicate therewith. In one variant, ongoing data may be collected as the system operates to ensure continued optimization. In the instance changes in the topology or environment of the user premises cause significant alterations to the communication signals or connectivity, a new optimal location for the access point may be determined.

Methods and apparatus for determining a desired or optimal location for one or more access points within a premises. In one embodiment, software is provided to wireless-enabled client devices in a user premises; the software enables each of the devices to communicate with one another and collect a plurality of data relating to the connectivity of each at various locations within the premises. The data is used to determine a desired or optimal location for placement of an access point. Once the optimal location is determined, the access point is placed, and the client devices communicate therewith. In one variant, ongoing data may be collected as the system operates to ensure continued optimization. In the instance changes in the topology or environment of the user premises cause significant alterations to the communication signals or connectivity, a new optimal location for the access point may be determined.