A device and method for machine learning in a telecommunications network based on radio cells. A connection handover in the telecommunications network, in which a mobile terminal switches from one radio cell of the telecommunications network to another radio cell of the telecommunications network during a call connection or a data connection without interrupting this connection, is carried out as a function of a parameter. A series of observations of a property of a signal received by the mobile terminal in the telecommunications network is recorded. A series of observations of a signal, transmitted by a network device in the telecommunications network, for connection handover is recorded. A model for determining an estimated value for the parameter is determined as a function of the series of observations, and the estimated value is determined with the model.

The present disclosure relates to a pre-5.sup.th-generation (5G) or 5G communication system to be provided for supporting higher data rates beyond 4.sup.th-generation (4G) communication system such as long term evolution (LTE). A communication method and apparatus using beamforming are provided. The method includes acquiring transmission beam specific, measurement information of a base station (BS) and measuring a reference signal (RS) transmitted through transmission beams of the BS according to the transmission beam specific, measurement information. The measurement information on each transmission beam is determined according to at least one of an elevation angle of the corresponding transmission beam, an azimuth of the corresponding transmission beam, a handover urgency, information on a handover failure, and information on a radio link failure (RLF). A mobile station (MS) may perform a measurement report or a handover process according to a result of the measurement.

In one embodiment, a system includes: an input/output (I/O) module operative to receive operational data for features associated with at least inter-cell performance in a mobile network, processing circuitry, a model generator application to be executed by the processing circuitry and operative to: use at least one prediction model to analyze training sets comprising examples of values for the features for at least overshooting cells, and to generate a scoring model for detection of the overshooting cells from among cells in the mobile network, and a boomer detection application to be executed by the processing circuitry and operative to: use the scoring model with the operational data to detect the overshooting cells from among cells in a mobile network, and reduce interference by the overshooting cells.

A method and a device for determining an MRO critical scenario and an apparatus are provided. The method includes: obtaining, by the UE, parameter information about a connection problem in the case that the connection problem has been detected by the UE in a cell handover process and cell handover has been performed successfully, or in the case that the connection problem has been detected by the UE within a predetermined time period after the cell handover is performed successfully; and transmitting, by the UE, the parameter information to a network device, so that the network device may determine the MRO critical scenario in accordance with the parameter information. According to the embodiments of the present disclosure, it is able to determine the MRO critical scenario in a scenario where cell handover is performed successfully.

An SHR generation method includes receiving, by a UE, SHR trigger information configured by a network-side device, where trigger information is used for enabling an SHR or setting an SHR trigger condition, and the trigger information contains a target time parameter for SHR generation; and configuring, by the UE, a target timer based on the target time parameter and generating a target SHR in a case that the target timer expires; where a timing start point of the target timer is trigger time of a target event corresponding to the target SHR.

Embodiments described in this disclosure address issues arising due to a current cell having incomplete information about the NR ARFCN for reference point A for all other cells which are included within Last Visited NG-RAN Cell Information. A source NG-RAN CU signals UE History Information to a target NG-RAN CU in a handover message by determining whether the UE History Information includes a previous Last Visited NG-RAN Cell Information entry indicating a Network Type, an NR ARFCN for reference point A, and Cell Type that match those of the current cell associated with the source NG-RAN CU; and adding to the UE History Information a new Last Visited NG-RAN Cell Information entry indicating for the current cell the Network Type, the NR ARFCN for reference point A and the Cell Type.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products are disclosed that may be implemented in a wireless transmit/receive unit (WTRU) for enhancing conditional reconfiguration procedures. In one representative embodiment, the WTRU may receive information associated with a conditional reconfiguration, and the information may respectively indicate a measurement resolution and/or a measurement period for at least one measurement report quantity associated with a conditional reconfiguration. After receiving the information, the WTRU may perform, over the measurement period, measurements on the at least one measurement report quantity according the measurement resolution. On condition the conditional reconfiguration is triggered, the WTRU may perform a random access procedure. After the random access procedure, the WTRU may send a measurement report for the random access procedure to a base station. The measurement report may include the measurements on the at least one measurement report.

A method and system for neighbor relation management in wireless broadband networks is disclosed. The method includes dynamically selecting, by a Serving Base Station (SBS), a set of signal measurement reports from a plurality of signal measurement reports received within a predefined time interval. The method further includes sampling, by the SBS, signal level values of a plurality of configured Neighboring Base Stations (NBSs) and at least one new NBS, from the set of signal measurement reports, for a predefined sampling time period. The method includes computing, by the SBS, a retention factor for each of the plurality of configured NBSs and each of the at least one new NBS, in response to sampling the signal level values.

There is provided mechanisms for beamforming. A method is performed by a network node. The network node is capable of communicating with served wireless devices using multiple beams generated by analog beamforming in an antenna array. The method comprises identifying, based on statistics of handovers of the served wireless devices between the beams, a need to combine at least two of the beams into a new beam. The method comprises determining beamforming weights to be applied at the analog antenna array for generating the new beam. The method comprises communicating with the served wireless devices using the new beam with the determined beamforming weights having been applied at the analog antenna array.

This document generally relates to wireless communication that includes a first communication node that adds a time value to a history information of a user device in response to a dwelling time exceeding 4,095 seconds or exceeding a predetermined upper time value that the user device stays in a cell, where the time value accurately indicates the dwelling time. The first communication node may transmit the history information including the time value to a second communication node. Also, at least one communication node may add time values to at least one history information, where the time values indicate dwelling times that a user device is in cells. At least one of the time values is for a dwelling time that exceeds 4,095 seconds or a predetermined upper time value and accurately indicates the dwelling time. The at least one communication node may correlate the at least one history information.