Abstract: A system for network data analytics comprising a network data analytics function, NWDAF, and one or more network functions, NF, wherein the NWDAF is arranged to obtain a dynamic event definition, wherein the dynamic event definition defines a custom data analytics function for processing data, and register the dynamic event definition at the one or more NFs, where an NF is associated with one or more NF entrypoints for the data, wherein at least one of the NFs is arranged to receive the dynamic event definition from the NWDAF, verify the dynamic event definition in accordance with one or more pre-determined verification criteria, and, if the verification criteria are fulfilled: assign an identifier to the received dynamic event definition, transmit the identifier back to the NWDAF, and register the dynamic event definition in an event definition store of the NF, wherein the NWDAF is arranged to receive the identifier associated with the registered dynamic event definition from the at least one NF.

Abstract: A system for network data analytics, the system comprising a network data analytics function, NWDAF, (200) and at least one NWDAF service consumer function, SCF, (220) arranged to connect to the NWDAF (200), wherein the SCF (220) is arranged to obtain (Sa1) a dynamic analytics function definition, wherein the dynamic analytics function definition defines a custom analytics function for processing data at the NWDAF (200), and register (Sa4, 310, 410) the dynamic analytics function definition at the NWDAF (200), wherein the NWDAF (200) is arranged to receive (Sb1) the dynamic analytics function definition from the SCF (220), assign (Sb3) an analytics function identifier to the received dynamic analytics function definition, transmit (Sb4, 320, 420) the analytics function identifier back to the SCF (220), and register (Sb5) the dynamic analytics function definition in an analytics function definition store of the NWDAF (200), wherein the SCF (220) is arranged to receive (Sa5, 320) the analytics identifier associ

Abstract: A method of predicting a location of a user equipment, UE, in a mobile communication network includes generating a list of potential target base stations by generating a transition count for each potential target base station including a count of transitions from the base station to the potential target base station within a predetermined time period, generating a plurality of relative transition frequencies based on the transition counts, and generating a transition probability for each respective potential target base station based on the relative transition frequency of the potential target base station from the base station.

Abstract: A method of predicting a location of a user equipment, UE, in a mobile communication network includes generating a list of potential target base stations by generating a transition count for each potential target base station including a count of transitions from the base station to the potential target base station within a predetermined time period, generating a plurality of relative transition frequencies based on the transition counts, and generating a transition probability for each respective potential target base station based on the relative transition frequency of the potential target base station from the base station.

Abstract: A method for maintaining a tracking area list, TAL, associated with a first wireless device, WD, in a network having network nodes organized into tracking areas, TA, and arranged to page the first WD. The method includes obtaining data associated with a transition pattern of WDs between TAs in the network, the data being indicative of transition probabilities for WDs moving between the TAs, receiving a message indicating that the first WD is leaving a TA and is entering a current TA, and maintaining the TAL by adding the current TA to the TAL and selecting TAs neighboring the current TA for addition to the TAL based on the transition probabilities of a wireless device moving from the current TA and into neighboring TAs, a neighboring TA associated with high transition probability is selected for addition to the TAL before a neighboring TA associated with low transition probability.

Abstract: A method of predicting a location of a user equipment, UE, in a mobile communication network includes generating a list of potential target base stations by generating a transition count for each potential target base station including a count of transitions from the base station to the potential target base station within a predetermined time period, generating a plurality of relative transition frequencies based on the transition counts, and generating a transition probability for each respective potential target base station based on the relative transition frequency of the potential target base station from the base station.