Abstract: A method (200) is disclosed for orchestrating acquisition of a quantity of communication network data for training a target Machine Learning (ML) model for use by a communication network node. The method comprises obtaining a representation of a data acquisition state for the communication network data (210) and using an orchestration ML model to map the representation of the data acquisition state to a first amount of the communication network data to be collected from sources of the communication network data, and a remaining amount of the communication network data to be generated using a generative model (220). The method further comprises, when sufficient data has been collected (240), causing a generative model for the communication network data to be trained using the collected communication network data (250), and causing the remaining amount of the communication network data to be generated using the trained generative model (260).

Abstract: Embodiments include methods for managed machine learning (ML) in a communication network, such as by one or more first network functions (NFs) of the communication network. Such methods include determining whether processing of an ML model in the communication network should be distributed to one or more user equipment (UEs) operating in the communication network, based on characteristics of the respective UEs. Such methods also include, based on determining that the processing of the ML model should be distributed to the one or more UEs, establishing trusted execution environments (TEEs) in the respective UEs and distributing the ML model for processing in the respective TEEs. Other embodiments include complementary methods for UEs, as well as UEs and NFs (or communication networks) configured to perform such methods.

Abstract: Embodiments include methods for managed machine learning (ML) in a communication network, such as by one or more first network functions (NFs) of the communication network. Such methods include determining whether processing of an ML model in the communication network should be distributed to one or more user equipment (UEs) operating in the communication network, based on characteristics of the respective UEs. Such methods also include, based on determining that the processing of the ML model should be distributed to the one or more UEs, establishing trusted execution environments (TEEs) in the respective UEs and distributing the ML model for processing in the respective TEEs. Other embodiments include complementary methods for UEs, as well as UEs and NFs (or communication networks) configured to perform such methods.

Abstract: A method and apparatus for facilitating communications with a roaming mobile subscriber unit which roams beyond a microcellular communication network, such as a Digital Electronic Cordless Telephone (DECT) system. A mobility server of the microcellular communication networks is coupled to a macrocellular communication network, such as a Global System for Mobile communications (GSM) network. Wide-area mobility management functions of the macrocellular communication network are provided to the microcellular communication network and are used to facilitate call routing to and from the roaming, mobile subscriber unit.

Abstract: A method and apparatus for facilitating communications with a roaming mobile subscriber unit which roams beyond a microcellular communication network, such as a Digital Electronic Cordless Telephone (DECT) system. A mobility server of the microcellular communication networks is coupled to a macrocellular communication network, such as a Global System for Mobile communications (GSM) network. Wide-area mobility management functions of the macrocellular communication network are provided to the microcellular communication network and are used to facilitate call routing to and from the roaming, mobile subscriber unit.

Abstract: A routing system, and an associated method, for routing a call to a multi-mode transceiver. Selection of a service subscription pursuant to which calls are to be routed to the transceiver is made at the transceiver, and information related to the selected service subscription is transmitted to a service node and stored at the service node. When an originating party desires to place a call to the transceiver, the originating party accesses the information stored at the service node. Responsive to the information stored at the service node, the call is routed to the transceiver pursuant to the selected service subscription.