Methods for user equipment trajectory prediction and reporting

Abstract

A wireless transmit / receive unit (WTRU) may facilitate trajectory prediction and associated measurements. The WTRU may indicate prediction capability to the network. The WTRU may receive configuration information from the network. The configuration information may comprise a triggering condition for sending a trajectory prediction report. The WTRU may perform measurements. The WTRU may determine if the triggering condition for sending the trajectory report is fulfilled. Upon determining that the triggering condition has been fulfilled, the WTRU may send a trajectory report.

Description

METHODS FOR USER EQUIPMENT TRAJECTORY PREDICTION AND REPORTINGCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application Number 63 / 572,459, filed April 1 , 2024, which is hereby incorporated herein by reference in its entirety.BACKGROUND

[0002] User equipment (UE) may be configured as an uncrewed aerial vehicle (UAV). Wireless networks may support UE AUVs. Current wireless network mobility procedures may be reactive and may rely on current measurements available at the UE. For example, a UE may continuously perform measurements of neighbor cells and evaluate measurement reporting or conditional handover (CHO) conditions. In the case of CHO, resources on several candidate neighbor cells may be reserved in anticipation of the UE handing over to one of these cells. This may result in large overhead on both the UE and network side.SUMMARY

[0003] Any description herein that is described with reference to a UE may be equally applicable to a wireless transmit / receive unit (WTRU) (or vice versa). Described herein are mechanisms for configuring and utilizing a WTRU to facilitate trajectory prediction and associated measurements. For example, a WTRU may be configured to perform any of the processes or procedures described herein as being performed by a UE (or vice versa).

[0004] A WTRU may send predicted trajectory information to a network when predicted trajectory information becomes available at the WTRU (e.g. , when trajectory predicted with more than a certain level of confidence) or when an update is needed regarding previously reported trajectory information (e.g., when the trajectory is expected to change, when the prediction confidence changes, when new information that was not available / reported before becomes available, or the like, etc.).

[0005] An example method may be performed by a WTRU. The method may comprise indicating the WTRU’s prediction capability to a network. The method may comprise receiving configuration of triggeringconditions / events for sending trajectory prediction reporting. The method may comprise performing a measurement and / or trajectory prediction. The method may comprise monitoring / determining if the triggering conditions for sending trajectory reports are fulfilled. The method may comprise determining the triggering conditions are fulfilled. The method may comprise, upon determining that the triggering conditions are fulfilled, at least one of sending a trajectory report / update to the network, or indicating availability of the trajectory report.

[0006] An example WTRU may comprise a transceiver and a processor. The processor may be configured to indicate, via the transceiver, trajectory prediction capability to a network. The processor may be configured to receive, via the transceiver, configuration of triggering conditions / events for sending trajectory prediction reporting. The processor may be configured to perform a trajectory prediction. The processor may be configured to monitor / determine if the triggering conditions for sending trajectory reports are fulfilled. The processor may be configured to determine if the triggering conditions are fulfilled. The processor may be configured to, upon a determination that the triggering conditions are fulfilled, at least one of send, via the transceiver, a trajectory report / update to the network, or indicate availability of the trajectory report.

[0007] An example non-transitory computer-readable storage medium may comprise executable instructions for configuring at least one processor to indicate trajectory prediction capability to a network. The executable instructions may configure the at least one processor to receive configuration of triggering conditions / events for sending trajectory prediction reporting. The executable instructions may configure the at least one processor to perform a trajectory prediction. The executable instructions may configure the at least one processor to monitor / determine if the triggering conditions for sending trajectory reports are fulfilled. The executable instructions may configure the at least one processor to determine if the triggering conditions are fulfilled. The executable instructions may configure the at least one processor to, upon a determination that the triggering conditions are fulfilled, at least one of send a trajectory report / update to the network, or indicate availability of the trajectory report.

[0008] A example method may be performed by a WTRU. The method may comprise providing trajectory prediction capability information. The method may comprise receiving a trajectory prediction configuration, wherein the trajectory prediction configuration comprises at least one trigger condition. The method may comprise performing trajectory prediction based on the received trajectory prediction configuration. The method may comprise determining if at least one trigger condition of the at least onetrigger conditions has been fulfilled. The method may comprise, based on determining that the at least one trigger condition has been fulfilled, providing a trajectory report. The trajectory prediction capability information may be provided to a network. The trajectory prediction configuration may be received from the network. The trajectory report may be provided to the network. The trajectory report may comprise a trajectory update. The trajectory prediction capability information may comprise information associated with a prediction time horizon. The trajectory prediction capability information may comprise information associated with a confidence level. The trajectory prediction capability information may comprise information associated with a time when a trajectory prediction is possible. The trajectory prediction capability information may comprise information associated with a location where trajectory prediction is possible. The trajectory prediction configuration may comprise information associated with a radio signal level threshold. The trajectory prediction configuration may comprise information associated with a change from a previous trajectory report. The trajectory prediction configuration may comprise information associated with a location of interest. The trajectory prediction configuration may comprise information associated with a time of interest.

[0009] An example WTRU may comprise a transceiver and a processor. The processor may be configured to provide, via the transceiver, trajectory prediction capability information. The processor may be configured to receive, via the transceiver, a trajectory prediction configuration, wherein the trajectory prediction configuration comprises at least one trigger condition. The processor may be configured to perform trajectory prediction based on the received trajectory prediction configuration. The processor may be configured to determine if at least one trigger condition of the at least one trigger conditions has been fulfilled. The processor may be configured to, based on a determination that the at least one trigger condition has been fulfilled, provide, via the transceiver, a trajectory report. The trajectory prediction capability information may be provided to a network. The trajectory prediction configuration may be received from the network. The trajectory report may be provided to the network. The trajectory report may comprise a trajectory update. The trajectory prediction capability information may comprise information associated with a prediction time horizon. The trajectory prediction capability information may comprise information associated with a confidence level. The trajectory prediction capability information may comprise information associated with a time when a trajectory prediction is possible. The trajectory prediction capability information may comprise information associated with a location where trajectory prediction is possible. The trajectory prediction configuration may comprise information associated with a radio signal level threshold. The trajectory prediction configuration may comprise information associatedwith a change from a previous trajectory report. The trajectory prediction configuration may comprise information associated with a location of interest. The trajectory prediction configuration may comprise information associated with a time of interest.

[0010] An example non-transitory computer-readable storage medium may comprise executable instructions for configuring at least one processor to provide trajectory prediction capability information. The executable instructions may configure the at least one processor to receive a trajectory prediction configuration, wherein the trajectory prediction configuration comprises at least one trigger condition. The executable instructions may configure the at least one processor to perform trajectory prediction based on the received trajectory prediction configuration. The executable instructions may configure the at least one processor to determine if at least one trigger condition of the at least one trigger conditions has been fulfilled. The executable instructions may configure the at least one processor to, based on a determination that the at least one trigger condition has been fulfilled, provide a trajectory report. The trajectory prediction capability information may be provided to a network. The trajectory prediction configuration may be received from the network. The trajectory report may be provided to the network. The trajectory report may comprise a trajectory update. The trajectory prediction capability information may comprise information associated with a prediction time horizon. The trajectory prediction capability information may comprise information associated with a confidence level. The trajectory prediction capability information may comprise information associated with a time when a trajectory prediction is possible. The trajectory prediction capability information may comprise information associated with a location where trajectory prediction is possible. The trajectory prediction configuration may comprise information associated with a radio signal level threshold. The trajectory prediction configuration may comprise information associated with a change from a previous trajectory report. The trajectory prediction configuration may comprise information associated with a location of interest. The trajectory prediction configuration may comprise information associated with a time of interest.

[0011] A example method may be performed by a WTRU. The method may comprise providing measurement prediction capability information. The method may comprise receiving a trajectory prediction configuration, wherein the trajectory prediction configuration comprises at least one trigger condition and information associated with how to determine trajectory from measurements. The method may comprise performing measurements and measurement predictions. The method may comprise transforming the performed measurements and measurement predictions to predicted trajectory according to the received trajectory prediction configuration. The method may comprise determining if at least one trigger conditionof the at least one trigger conditions has been fulfilled. The method may comprise, based on determining that the at least one trigger condition has been fulfilled, providing a trajectory report. The measurement prediction capability information may be provided to a network. The measurement prediction configuration may be received from the network. The trajectory report may be provided to the network. The trajectory report may comprise a trajectory update. The trajectory measurement capability information may comprise information associated with a prediction time horizon. The measurement prediction capability information may comprise information associated with a confidence level. The measurement prediction capability information may comprise information associated with a time when a trajectory prediction is possible. The measurement prediction capability information may comprise information associated with a location where trajectory prediction is possible. The trajectory prediction configuration may comprise information associated with a radio signal level threshold. The trajectory prediction configuration may comprise information associated with a change from a previous trajectory report. The trajectory prediction configuration may comprise information associated with a location of interest. The trajectory prediction configuration may comprise information associated with a time of interest.

[0012] An example WTRU may comprise a transceiver and a processor. The processor may be configured to provide, via the transceiver, measurement prediction capability information. The processor may be configured to receive, via the transceiver, a trajectory prediction configuration, wherein the trajectory prediction configuration comprises at least one trigger condition and information associated with how to determine trajectory from measurements. The processor may be configured to perform measurements measurement predictions. The processor may be configured to transform the performed measurements and measurement predictions to predicted trajectory according to the received trajectory prediction configuration. The processor may be configured to determine if at least one trigger condition of the at least one trigger conditions has been fulfilled. The processor may be configured to, based on determining that the at least one trigger condition has been fulfilled, provide, via the transceiver, a trajectory report. The measurement prediction capability information may be provided to a network. The measurement prediction configuration may be received from the network. The trajectory report may be provided to the network. The trajectory report may comprise a trajectory update. The measurement prediction capability information may comprise information associated with a prediction time horizon. The measurement prediction capability information may comprise information associated with a confidence level. The measurement prediction capability information may comprise information associated with a time when a trajectory prediction is possible. The measurement prediction capability information may compriseinformation associated with a location where trajectory prediction is possible. The trajectory prediction configuration may comprise information associated with a radio signal level threshold. The trajectory prediction configuration may comprise information associated with a change from a previous trajectory report. The trajectory prediction configuration may comprise information associated with a location of interest. The trajectory prediction configuration may comprise information associated with a time of interest.

[0013] An example non-transitory computer-readable storage medium may comprise executable instructions for configuring at least one processor to provide measurement prediction capability information. The executable instructions may configure the at least one processor to receive a trajectory prediction configuration, wherein the trajectory prediction configuration comprises at least one trigger condition and information associated with how to determine trajectory from measurements. The executable instructions may configure the at least one processor to perform measurements and measurement predictions. The executable instructions may configure the at least one processor to transform the performed measurements and measurement predictions to predicted trajectory according to the received trajectory prediction configuration. The executable instructions may configure the at least one processor to determine if at least one trigger condition of the at least one trigger conditions has been fulfilled. The executable instructions may configure the at least one processor to, based on determining that the at least one trigger condition has been fulfilled, provide a trajectory report. The measurement prediction capability information may be provided to a network. The trajectory prediction configuration may be received from the network. The trajectory report may be provided to the network. The trajectory report may comprise a trajectory update. The measurement prediction capability information may comprise information associated with a prediction time horizon. The measurement prediction capability information may comprise information associated with a confidence level. The measurement prediction capability information may comprise information associated with a time when a trajectory prediction is possible. The measurement prediction capability information may comprise information associated with a location where trajectory prediction is possible. The trajectory prediction configuration may comprise information associated with a radio signal level threshold. The trajectory prediction configuration may comprise information associated with a change from a previous trajectory report. The trajectory prediction configuration may comprise information associated with a location of interest. The trajectory prediction configuration may comprise information associated with a time of interest.

[0014] An example WTRU may comprise a transceiver and a processor. The processor may be configured to receive a trajectory prediction configuration, wherein the trajectory prediction configuration is related to performing trajectory prediction and reporting predicted trajectory information, and wherein the trajectory prediction configuration comprises at least one triggering condition for reporting predicted trajectory information. The processor may be configured to perform a trajectory prediction in accordance with the received trajectory prediction configuration. The processor may be configured to determine predicted trajectory information based on the performance of the trajectory prediction. The processor may be configured to determine that a triggering condition of the at least one triggering condition is fulfilled. The processor may be configured to, based on the at least one triggering condition being fulfilled, transmit the determined predicted trajectory information. The processor may be configured to transmit to a network a capability of the WTRU associated with trajectory prediction. The trajectory prediction configuration may comprise an indication of at least one prediction model.

[0015] The predicted trajectory information may comprise location information. The location information may comprise at least one of a sequence of locations, a range of locations, cell information, Global Navigation Satellite System (GNSS) co-ordinates, predicted arrival time at a location, predicted departure time from a location, or predicted time of stay at a location.

[0016] The transmitted prediction trajectory information may comprise a full trajectory report. The full trajectory report may comprise an indication that the full trajectory report replaces a previous trajectory report. The transmitted trajectory information may comprise an update trajectory report. The transmitted trajectory update report may comprise an indication of a modification of a previous trajectory report. The modification of the previous trajectory report may comprise at least one of removal of a location that was indicated in the previous trajectory report, removal of a cell of a previous trajectory report, an addition of a location that was indicated in the previous trajectory report, an addition of a cell of a previous trajectory report, or a modification of time information associated with a location indicated in the previous trajectory report.

[0017] The at least one triggering condition may be based on a confidence level of a prediction being greater than or equal to a threshold confidence level. The at least one triggering condition may be based on a trajectory prediction being applicable for a duration of time after transmission of trajectory projection information. The at least one triggering condition may be based on the WTRU being in a predetermined location during a predetermined duration of time. The at least one triggering condition may be based on alocation of the WTRU at a predetermined time differing by greater than a threshold distance compared to a previously reported trajectory for the predetermined time. The at least one triggering condition may be based on at least one parameter of a projected trajectory differing by greater than a respective threshold amount compared to the at least one parameter of a previously reported trajectory.

[0018] The trajectory prediction configuration may be related to determining a trajectory based on measurements. The trajectory prediction configuration may be related to performing trajectory prediction based on at least one of measurement time duration, filter coefficients for consolidating past and current measurements, measurement sampling intervals, or beam consolidation thresholds for cell level measurement calculations. The trajectory prediction configuration may be related to performing trajectory prediction based on artificial intelligence or machine learning model training. The trajectory prediction configuration may be related to reporting predicted trajectory information based on timing associated with transmission of a predicted trajectory report. The trajectory prediction configuration may be related to reporting predicted trajectory information based on prohibiting a predicted trajectory report.

[0019] An example method may be performed by a WTRU. The method may comprise receiving a trajectory prediction configuration, wherein the trajectory prediction configuration is related to performing trajectory prediction and reporting predicted trajectory information, and wherein the trajectory prediction configuration comprises at least one triggering condition for reporting predicted trajectory information. The method may comprise performing a trajectory prediction in accordance with the received trajectory prediction configuration. The method may comprise determining predicted trajectory information based on the performance of the trajectory prediction. The method may comprise determining that a triggering condition of the at least one triggering condition is fulfilled. The method may comprise, based on the at least one triggering condition being fulfilled, transmitting the determined predicted trajectory information. The method may comprise transmitting to a network a capability of the WTRU associated with trajectory prediction. The trajectory prediction configuration may comprise an indication of at least one prediction model.

[0020] The predicted trajectory information may comprise location information. The location information may comprise at least one of a sequence of locations, a range of locations, cell information, Global Navigation Satellite System (GNSS) co-ordinates, predicted arrival time at a location, predicted departure time from a location, or predicted time of stay at a location.

[0021] The transmitted predicted trajectory information may comprise a full trajectory report. The full trajectory report may comprise an indication that the full trajectory report replaces a previous trajectory report. The transmitted trajectory information may comprise an update trajectory report. The transmitted trajectory update report may comprise an indication of a modification of a previous trajectory report. The modification of the previous trajectory report may comprise at least one of removal of a location that was indicated in the previous trajectory report, removal of a cell of a previous trajectory report, an addition of a location that was indicated in the previous trajectory report, an addition of a cell of a previous trajectory report, or a modification of time information associated with a location indicated in the previous trajectory report.

[0022] Regarding the method, the at least one triggering condition may be based on a confidence level of a prediction being greater than or equal to a threshold confidence level. The at least one triggering condition may be based on a trajectory prediction being applicable for a duration of time after transmission of trajectory projection information. The at least one triggering condition may be based on the WTRU being in a predetermined location during a predetermined duration of time. The at least one triggering condition may be based on a location of the WTRU at a predetermined time differing by greater than a threshold distance compared to a previously reported trajectory for the predetermined time. The at least one triggering condition may be based on at least one parameter of a projected trajectory differing by greater than a respective threshold amount compared to the at least one parameter of a previously reported trajectory.

[0023] Regarding the method, the trajectory prediction configuration may be related to determining a trajectory based on measurements. The trajectory prediction configuration may be related to performing trajectory prediction based on at least one of measurement time duration, filter coefficients for consolidating past and current measurements, measurement sampling intervals, or beam consolidation thresholds for cell level measurement calculations. The trajectory prediction configuration may be related to performing trajectory prediction based on artificial intelligence or machine learning model training. The trajectory prediction configuration may be related to reporting predicted trajectory information based on timing associated with transmission of a predicted trajectory report. The trajectory prediction configuration may be related to reporting predicted trajectory information based on prohibiting a predicted trajectory report.BRIEF DESCRIPTION OF THE DRAWINGS

[0024] A more detailed understanding may be had from the detailed description below, given by way of example in conjunction with drawings appended hereto. Figures in such drawings, like the detailed description, are examples. As such, the Figures and the detailed description are not to be considered limiting, and other equally effective examples are possible and likely. Like reference numerals (“ref.” or “refs.”) in the Figures indicate like elements.

[0025] FIG. 1 A is an example system diagram illustrating an example communications system in which one or more disclosed embodiments may be implemented.

[0026] FIG. 1 B is an example system diagram illustrating an example wireless transmit / receive unit (WTRU) that may be used within the communications system illustrated in FIG. 1 A according to an embodiment.

[0027] FIG. 1 C is an example system diagram illustrating an example radio access network (RAN) and an example core network (CN) that may be used within the communications system illustrated in FIG. 1 A according to an embodiment.

[0028] FIG. 1 D is an example system diagram illustrating a further example RAN and a further example CN that may be used within the communications system illustrated in FIG. 1 A according to an embodiment.

[0029] FIG. 2 depicts an example function framework for artificial intelligence / machine learning (AI / ML) for a new radio (NR) air interface.

[0030] FIG. 3 depicts an example diagram illustrating a WTRU capable of directly predicting trajectory.

[0031] FIG. 4 depicts an example diagram illustrating a WTRU capable of directly predicting measurements.EXAMPLE NETWORKS FOR IMPLEMENTATION OF THE INVENTION

[0032] FIG. 1A is a diagram illustrating an example communications system 100 in which one or more disclosed embodiments may be implemented. The communications system 100 may be a multiple access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users. The communications system 100 may enable multiple wireless users to access such content through the sharing of system resources, including wireless bandwidth. For example, the communications systems100 may employ one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), zero-tail unique-word DFT-Spread OFDM (ZT UW DTS-s OFDM), unique word OFDM (UW-OFDM), resource block-filtered OFDM, filter bank multicarrier (FBMC), and the like.

[0033] As shown in FIG. 1 A, the communications system 100 may include wireless transmit / receive units (WTRUs) 102a, 102b, 102c, 102d, a RAN 104 / 113, a CN 106 / 115, a public switched telephone network (PSTN) 108, the Internet 110, and other networks 112, though it will be appreciated that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and / or network elements. Each of the WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and / or communicate in a wireless environment. By way of example, the WTRUs 102a, 102b, 102c, 102d, any of which may be referred to as a “station” and / or a “STA”, may be configured to transmit and / or receive wireless signals and may include a user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a subscription-based unit, a pager, a cellular telephone, a personal digital assistant (PDA), a smartphone, a laptop, a netbook, a personal computer, a wireless sensor, a hotspot or Mi-Fi device, an Internet of Things (loT) device, a watch or other wearable, a head-mounted display (HMD), a vehicle, a drone, a medical device and applications (e.g., remote surgery), an industrial device and applications (e.g., a robot and / or other wireless devices operating in an industrial and / or an automated processing chain contexts), a consumer electronics device, a device operating on commercial and / or industrial wireless networks, and the like. Any of the WTRUs 102a, 102b, 102c and 102d may be interchangeably referred to as a UE. Further, any description herein that is described with reference to a WTRU may be equally applicable to a WTRU (or vice versa). For example, a WTRU may be configured to perform any of the processes or procedures described herein as being performed by a WTRU (or vice versa).

[0034] The communications systems 100 may also include a base station 114a and / or a base station 114b. Each of the base stations 114a, 114b may be any type of device configured to wirelessly interface with at least one of the WTRUs 102a, 102b, 102c, 102d to facilitate access to one or more communication networks, such as the CN 106 / 115, the I nternet 110, and / or the other networks 112. By way of example, the base stations 114a, 114b may be a base transceiver station (BTS), a Node-B, an eNode B, a Home Node B, a Home eNode B, a gNB, a NR NodeB, a site controller, an access point (AP), a wireless router, and the like. While the base stations 114a, 114b are each depicted as a single element, it will beappreciated that the base stations 114a, 114b may include any number of interconnected base stations and / or network elements.

[0035] The base station 114a may be part of the RAN 104 / 113, which may also include other base stations and / or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), relay nodes, etc. The base station 114a and / or the base station 114b may be configured to transmit and / or receive wireless signals on one or more carrier frequencies, which may be referred to as a cell (not shown). These frequencies may be in licensed spectrum, unlicensed spectrum, or a combination of licensed and unlicensed spectrum. A cell may provide coverage for a wireless service to a specific geographical area that may be relatively fixed or that may change over time. The cell may further be divided into cell sectors. For example, the cell associated with the base station 114a may be divided into three sectors. Thus, in one embodiment, the base station 114a may include three transceivers, i.e., one for each sector of the cell. In an embodiment, the base station 114a may employ multiple-input multiple output (MIMO) technology and may utilize multiple transceivers for each sector of the cell. For example, beamforming may be used to transmit and / or receive signals in desired spatial directions.

[0036] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over an air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 116 may be established using any suitable radio access technology (RAT).

[0037] More specifically, as noted above, the communications system 100 may be a multiple access system and may employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, and the like. For example, the base station 114a in the RAN 104 / 113 and the WTRUs 102a, 102b, 102c may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may establish the air interface 115 / 116 / 117 using wideband CDMA (WCDMA). WCDMA may include communication protocols such as High-Speed Packet Access (HSPA) and / or Evolved HSPA (HSPA+). HSPA may include High-Speed Downlink (DL) Packet Access (HSDPA) and / or High-Speed UL Packet Access (HSUPA).

[0038] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E-UTRA), which may establish the air interface 116 using Long Term Evolution (LTE) and / or LTE-Advanced (LTE-A) and / or LTE-Advanced Pro (LTE-A Pro).

[0039] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as NR Radio Access , which may establish the air interface 116 using New Radio (NR).

[0040] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement multiple radio access technologies. For example, the base station 114a and the WTRUs 102a, 102b, 102c may implement LTE radio access and NR radio access together, for instance using dual connectivity (DC) principles. Thus, the air interface utilized by WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and / or transmissions sent to / from multiple types of base stations (e.g., a eNB and a gNB).

[0041] In other embodiments, the base station 114a and the WTRUs 102a, 102b, 102c may implement radio technologies such as IEEE 802.11 (i.e., Wireless Fidelity (WiFi), IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1X, CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), GSM EDGE (GERAN), and the like.

[0042] The base station 114b in FIG. 1 A may be a wireless router, Home Node B, Home eNode B, or access point, for example, and may utilize any suitable RAT for facilitating wireless connectivity in a localized area, such as a place of business, a home, a vehicle, a campus, an industrial facility, an air corridor (e.g., for use by drones), a roadway, and the like. In one embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.11 to establish a wireless local area network (WLAN). In an embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN). In yet another embodiment, the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR etc.) to establish a picocell or femtocell. As shown in FIG. 1A, the base station 114b may have a direct connection to the Internet 110. Thus, the base station 114b may not be required to access the Internet 110 via the CN 106 / 115.

[0043] The RAN 104 / 113 may be in communication with the CN 106 / 115, which may be any type of network configured to provide voice, data, applications, and / or voice over internet protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d. The data may have varying quality of service (QoS) requirements, such as differing throughput requirements, latency requirements, error tolerancerequirements, reliability requirements, data throughput requirements, mobility requirements, and the like. The CN 106 / 115 may provide call control, billing services, mobile location-based services, pre-paid calling, Internet connectivity, video distribution, etc., and / or perform high-level security functions, such as user authentication. Although not shown in FIG. 1A, it will be appreciated that the RAN 104 / 113 and / or the CN 106 / 115 may be in direct or indirect communication with other RANs that employ the same RAT as the RAN 104 / 113 or a different RAT. For example, in addition to being connected to the RAN 104 / 113, which may be utilizing a NR radio technology, the CN 106 / 115 may also be in communication with another RAN (not shown) employing a GSM, UMTS, CDMA 2000, WiMAX, E-UTRA, or WiFi radio technology.

[0044] The CN 106 / 115 may also serve as a gateway for the WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and / or the other networks 112. The PSTN 108 may include circuit- switched telephone networks that provide plain old telephone service (POTS). The Internet 110 may include a global system of interconnected computer networks and devices that use common communication protocols, such as the transmission control protocol (TCP), user datagram protocol (UDP) and / or the internet protocol (IP) in the TCP / IP internet protocol suite. The networks 112 may include wired and / or wireless communications networks owned and / or operated by other service providers. For example, the networks 112 may include another CN connected to one or more RANs, which may employ the same RAT as the RAN 104 / 113 or a different RAT.

[0045] Some or all of the WTRUs 102a, 102b, 102c, 102d in the communications system 100 may include multi-mode capabilities (e.g., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links). For example, the WTRU 102c shown in FIG. 1A may be configured to communicate with the base station 114a, which may employ a cellular-based radio technology, and with the base station 114b, which may employ an IEEE 802 radio technology.

[0046] FIG. 1 B is a system diagram illustrating an example WTRU 102. As shown in FIG. 1 B, the WTRU 102 may include a processor 118, a transceiver 120, a transmit / recei ve element 122, a speaker / microphone 124, a keypad 126, a display / touchpad 128, non-removable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and / or other peripherals 138, among others. It will be appreciated that the WTRU 102 may include any sub-combination of the foregoing elements while remaining consistent with an embodiment.

[0047] The processor 118 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), a state machine, and the like. The processor 118 may perform signal coding, data processing, power control, input / output processing, and / or any other functionality that enables the WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit / receive element 122. While FIG. 1B depicts the processor 118 and the transceiver 120 as separate components, it will be appreciated that the processor 118 and the transceiver 120 may be integrated together in an electronic package or chip.

[0048] The transmit / receive element 122 may be configured to transmit signals to, or receive signals from, a base station (e.g., the base station 114a) over the air interface 116. For example, in one embodiment, the transmit / receive element 122 may be an antenna configured to transmit and / or receive RF signals. In an embodiment, the transmit / receive element 122 may be an emitter / detector configured to transmit and / or receive IR, UV, or visible light signals, for example. In yet another embodiment, the transmit / receive element 122 may be configured to transmit and / or receive both RF and light signals. It will be appreciated that the transmit / receive element 122 may be configured to transmit and / or receive any combination of wireless signals.

[0049] Although the transmit / receive element 122 is depicted in FIG. 1B as a single element, the WTRU 102 may include any number of transmit / receive elements 122. More specifically, the WTRU 102 may employ MIMO technology. Thus, in one embodiment, the WTRU 102 may include two or more transmit / receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.

[0050] The transceiver 120 may be configured to modulate the signals that are to be transmitted by the transmit / receive element 122 and to demodulate the signals that are received by the transmit / receive element 122. As noted above, the WTRU 102 may have multi-mode capabilities. Thus, the transceiver 120 may include multiple transceivers for enabling the WTRU 102 to communicate via multiple RATs, such as NR and IEEE 802.11 , for example.

[0051] The processor 118 of the WTRU 102 may be coupled to, and may receive user input data from, the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128 (e.g., a liquid crystal display(LCD) display unit or organic light-emitting diode (OLED) display unit). The processor 118 may also output user data to the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128. In addition, the processor 118 may access information from, and store data in, any type of suitable memory, such as the non-removable memory 130 and / or the removable memory 132. The non-removable memory 130 may include random-access memory (RAM), read-only memory (ROM), a hard disk, or any other type of memory storage device. The removable memory 132 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like. In other embodiments, the processor 118 may access information from, and store data in, memory that is not physically located on the WTRU 102, such as on a server or a home computer (not shown).

[0052] The processor 118 may receive power from the power source 134, and may be configured to distribute and / or control the power to the other components in the WTRU 102. The power source 134 may be any suitable device for powering the WTRU 102. For example, the power source 134 may include one or more dry cell batteries (e.g., nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar cells, fuel cells, and the like.

[0053] The processor 118 may also be coupled to the GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102. In addition to, or in lieu of, the information from the GPS chipset 136, the WTRU 102 may receive location information over the air interface 116 from a base station (e.g., base stations 114a, 114b) and / or determine its location based on the timing of the signals being received from two or more nearby base stations. It will be appreciated that the WTRU 102 may acquire location information by way of any suitable locationdetermination method while remaining consistent with an embodiment.

[0054] The processor 118 may further be coupled to other peripherals 138, which may include one or more software and / or hardware modules that provide additional features, functionality and / or wired or wireless connectivity. For example, the peripherals 138 may include an accelerometer, an e-compass, a satellite transceiver, a digital camera (for photographs and / or video), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands free headset, a Bluetooth® module, a frequency modulated (FM) radio unit, a digital music player, a media player, a video game player module, an Internet browser, a Virtual Reality and / or Augmented Reality (VR / AR) device, an activity tracker, and the like. The peripherals 138 may include one or more sensors, the sensors may be one or more of a gyroscope, an accelerometer, a hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, atemperature sensor, a time sensor; a geolocation sensor; an altimeter, a light sensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and / or a humidity sensor.

[0055] The WTRU 102 may include a full duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for both the UL (e.g., for transmission) and downlink (e.g., for reception) may be concurrent and / or simultaneous. The full duplex radio may include an interference management unit 139 to reduce and or substantially eliminate self-interference via either hardware (e.g., a choke) or signal processing via a processor (e.g., a separate processor (not shown) or via processor 118). In an embodiment, the WTRU 102 may include a half-duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for either the UL (e.g., for transmission) or the downlink (e.g., for reception)).

[0056] FIG. 1 C is a system diagram illustrating the RAN 104 and the CN 106 according to an embodiment. As noted above, the RAN 104 may employ an E-UTRA radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 104 may also be in communication with the CN 106.

[0057] The RAN 104 may include eNode-Bs 160a, 160b, 160c, though it will be appreciated that the RAN 104 may include any number of eNode-Bs while remaining consistent with an embodiment. The eNode-Bs 160a, 160b, 160c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the eNode-Bs 160a, 160b, 160c may implement MIMO technology. Thus, the eNode-B 160a, for example, may use multiple antennas to transmit wireless signals to, and / or receive wireless signals from, the WTRU 102a.

[0058] Each of the eNode-Bs 160a, 160b, 160c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and / or DL, and the like. As shown in FIG. 1 C, the eNode-Bs 160a, 160b, 160c may communicate with one another over an X2 interface.

[0059] The CN 106 shown in FIG. 1 C may include a mobility management entity (MME) 162, a serving gateway (SGW) 164, and a packet data network (PDN) gateway (or PGW) 166. While each of the foregoing elements are depicted as part of the CN 106, it will be appreciated that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0060] The MME 162 may be connected to each of the eNode-Bs 162a, 162b, 162c in the RAN 104 via an S1 interface and may serve as a control node. For example, the MME 162 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, bearer activation / deactivation, selecting a particular serving gateway during an initial attachment of the WTRUs 102a, 102b, 102c, and the like. The MME 162 may provide a control plane function for switching between the RAN 104 and other RANs (not shown) that employ other radio technologies, such as GSM and / or WCDMA.

[0061] The SGW 164 may be connected to each of the eNode Bs 160a, 160b, 160c in the RAN 104 via the S1 interface. The SGW 164 may generally route and forward user data packets to / from the WTRUs 102a, 102b, 102c. The SGW 164 may perform other functions, such as anchoring user planes during inter- eNode B handovers, triggering paging when DL data is available for the WTRUs 102a, 102b, 102c, managing and storing contexts of the WTRUs 102a, 102b, 102c, and the like.

[0062] The SGW 164 may be connected to the PGW 166, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0063] The CN 106 may facilitate communications with other networks. For example, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional land-line communications devices. For example, the CN 106 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 106 and the PSTN 108. In addition, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and / or wireless networks that are owned and / or operated by other service providers.

[0064] Although the WTRU is described in FIGS. 1A-1 D as a wireless terminal, it is contemplated that in certain representative embodiments that such a terminal may use (e.g., temporarily or permanently) wired communication interfaces with the communication network.

[0065] In representative embodiments, the other network 112 may be a WLAN.

[0066] A WLAN in Infrastructure Basic Service Set (BSS) mode may have an Access Point (AP) for the BSS and one or more stations (STAs) associated with the AP. The AP may have access or an interface to a Distribution System (DS) or another type of wired / wireless network that carries traffic in to and / or out ofthe BSS. Traffic to STAs that originates from outside the BSS may arrive through the AP and may be delivered to the STAs. Traffic originating from STAs to destinations outside the BSS may be sent to the AP to be delivered to respective destinations. Traffic between STAs within the BSS may be sent through the AP, for example, where the source STA may send traffic to the AP and the AP may deliver the traffic to the destination STA. The traffic between STAs within a BSS may be considered and / or referred to as peer-to- peer traffic. The peer-to-peer traffic may be sent between (e.g., directly between) the source and destination STAs with a direct link setup (DLS). In certain representative embodiments, the DLS may use an 802.11 e DLS or an 802.11 z tunneled DLS (TDLS). A WLAN using an Independent BSS (I BSS) mode may not have an AP, and the STAs (e.g., all of the STAs) within or using the IBSS may communicate directly with each other. The IBSS mode of communication may sometimes be referred to herein as an “ad- hoc” mode of communication.

[0067] When using the 802.11ac infrastructure mode of operation or a similar mode of operations, the AP may transmit a beacon on a fixed channel, such as a primary channel. The primary channel may be a fixed width (e.g., 20 MHz wide bandwidth) or a dynamically set width via signaling. The primary channel may be the operating channel of the BSS and may be used by the STAs to establish a connection with the AP. In certain representative embodiments, Carrier Sense Multiple Access with Collision Avoidance (CSMA / CA) may be implemented, for example, in 802.11 systems. For CSMA / CA, the STAs (e.g., every STA), including the AP, may sense the primary channel. If the primary channel is sensed / detected and / or determined to be busy by a particular STA, the particular STA may back off. One STA (e.g., only one station) may transmit at any given time in a given BSS.

[0068] High Throughput (HT) STAs may use a 40 MHz wide channel for communication, for example, via a combination of the primary 20 MHz channel with an adjacent or nonadjacent 20 MHz channel to form a 40 MHz wide channel.

[0069] Very High Throughput (VHT) STAs may support 20 MHz, 40 MHz, 80 MHz, and / or 160 MHz wide channels. The 40 MHz, and / or 80 MHz, channels may be formed by combining contiguous 20 MHz channels. A 160 MHz channel may be formed by combining 8 contiguous 20 MHz channels, or by combining two non-contiguous 80 MHz channels, which may be referred to as an 80+80 configuration. For the 80+80 configuration, the data, after channel encoding, may be passed through a segment parser that may divide the data into two streams. Inverse Fast Fourier Transform (IFFT) processing, and time domain processing, may be done on each stream separately. The streams may be mapped on to the two 80 MHzchannels, and the data may be transmitted by a transmitting STA. At the receiver of the receiving STA, the above described operation for the 80+80 configuration may be reversed, and the combined data may be sent to the Medium Access Control (MAC).

[0070] Sub 1 GHz modes of operation are supported by 802.11 af and 802.11 ah. The channel operating bandwidths, and carriers, are reduced in 802.11 af and 802.11 ah relative to those used in 802.11 n, and 802.11ac. 802.11 af supports 5 MHz, 10 MHz and 20 MHz bandwidths in the TV White Space (TVWS) spectrum, and 802.11 ah supports 1 MHz, 2 MHz, 4 MHz, 8 MHz, and 16 MHz bandwidths using non-TVWS spectrum. According to a representative embodiment, 802.11 ah may support Meter Type Control / Machine- Type Communications, such as MTC devices in a macro coverage area. MTC devices may have certain capabilities, for example, limited capabilities including support for (e.g., only support for) certain and / or limited bandwidths. The MTC devices may include a battery with a battery life above a threshold (e.g., to maintain a very long battery life).

[0071] WLAN systems, which may support multiple channels, and channel bandwidths, such as 802.11n, 802.11 ac, 802.11af, and 802.11 ah, include a channel which may be designated as the primary channel. The primary channel may have a bandwidth equal to the largest common operating bandwidth supported by all STAs in the BSS. The bandwidth of the primary channel may be set and / or limited by a STA, from among all STAs in operating in a BSS, which supports the smallest bandwidth operating mode. In the example of 802.11 ah, the primary channel may be 1 MHz wide for STAs (e.g., MTC type devices) that support (e.g., only support) a 1 MHz mode, even if the AP, and other STAs in the BSS support 2 MHz, 4 MHz, 8 MHz, 16 MHz, and / or other channel bandwidth operating modes. Carrier sensing and / or Network Allocation Vector (NAV) settings may depend on the status of the primary channel. If the primary channel is busy, for example, due to a STA (which supports only a 1 MHz operating mode), transmitting to the AP, the entire available frequency bands may be considered busy even though a majority of the frequency bands remains idle and may be available.

[0072] In the United States, the available frequency bands, which may be used by 802.11 ah, are from 902 MHz to 928 MHz. In Korea, the available frequency bands are from 917.5 MHz to 923.5 MHz. In Japan, the available frequency bands are from 916.5 MHz to 927.5 MHz. The total bandwidth available for 802.11 ah is 6 MHz to 26 MHz depending on the country code.

[0073] FIG. 1 D is a system diagram illustrating the RAN 113 and the CN 115 according to an embodiment. As noted above, the RAN 113 may employ an NR radio technology to communicate with theWTRUs 102a, 102b, 102c over the air interface 116. The RAN 113 may also be in communication with the CN 115.

[0074] The RAN 113 may include gNBs 180a, 180b, 180c, though it will be appreciated that the RAN 113 may include any number of gNBs while remaining consistent with an embodiment. The gNBs 180a, 180b, 180c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the gNBs 180a, 180b, 180c may implement MIMO technology. For example, gNBs 180a, 180b may utilize beamforming to transmit signals to and / or receive signals from the gNBs 180a, 180b, 180c. Thus, the gNB 180a, for example, may use multiple antennas to transmit wireless signals to, and / or receive wireless signals from, the WTRU 102a. In an embodiment, the gNBs 180a, 180b, 180c may implement carrier aggregation technology. For example, the gNB 180a may transmit multiple component carriers to the WTRU 102a (not shown). A subset of these component carriers may be on unlicensed spectrum while the remaining component carriers may be on licensed spectrum. In an embodiment, the gNBs 180a, 180b, 180c may implement Coordinated Multi-Point (CoMP) technology. For example, WTRU 102a may receive coordinated transmissions from gNB 180a and gNB 180b (and / or gNB 180c).

[0075] The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using transmissions associated with a scalable numerology. For example, the OFDM symbol spacing and / or OFDM subcarrier spacing may vary for different transmissions, different cells, and / or different portions of the wireless transmission spectrum. The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using subframe or transmission time intervals (TTIs) of various or scalable lengths (e.g . , containing varying number of OFDM symbols and / or lasting varying lengths of absolute time).

[0076] The gNBs 180a, 180b, 180c may be configured to communicate with the WTRUs 102a, 102b, 102c in a standalone configuration and / or a non-standalone configuration. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c without also accessing other RANs (e.g., such as eNode-Bs 160a, 160b, 160c). In the standalone configuration, WTRUs 102a, 102b, 102c may utilize one or more of gNBs 180a, 180b, 180c as a mobility anchor point. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using signals in an unlicensed band. In a non-standalone configuration WTRUs 102a, 102b, 102c may communicate with / connect to gNBs 180a, 180b, 180c while also communicating with / connecting to another RAN such as eNode-Bs 160a, 160b, 160c. For example, WTRUs 102a, 102b, 102c may implement DC principles tocommunicate with one or more gNBs 180a, 180b, 180c and one or more eNode-Bs 160a, 160b, 160c substantially simultaneously. In the non-standalone configuration, eNode-Bs 160a, 160b, 160c may serve as a mobility anchor for WTRUs 102a, 102b, 102c and gNBs 180a, 180b, 180c may provide additional coverage and / or throughput for servicing WTRUs 102a, 102b, 102c.

[0077] Each of the gNBs 180a, 180b, 180c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and / or DL, support of network slicing, dual connectivity, interworking between NR and E-UTRA, routing of user plane data towards User Plane Function (UPF) 184a, 184b, routing of control plane information towards Access and Mobility Management Function (AMF) 182a, 182b and the like. As shown in FIG. 1D, the gNBs 180a, 180b, 180c may communicate with one another over an Xn interface.

[0078] The CN 115 shown in FIG. 1 D may include at least one AMF 182a, 182b, at least one UPF 184a, 184b, at least one Session Management Function (SMF) 183a, 183b, and possibly a Data Network (DN) 185a, 185b. While each of the foregoing elements are depicted as part of the CN 115, it will be appreciated that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0079] The AMF 182a, 182b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N2 interface and may serve as a control node. For example, the AMF 182a, 182b may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, support for network slicing (e.g., handling of different PDU sessions with different requirements), selecting a particular SMF 183a, 183b, management of the registration area, termination of NAS signaling, mobility management, and the like. Network slicing may be used by the AMF 182a, 182b in order to customize CN support for WTRUs 102a, 102b, 102c based on the types of services being utilized WTRUs 102a, 102b, 102c. For example, different network slices may be established for different use cases such as services relying on ultra-reliable low latency (URLLC) access, services relying on enhanced massive mobile broadband (eMBB) access, services for machine type communication (MTC) access, and / or the like. The AMF 162 may provide a control plane function for switching between the RAN 113 and other RANs (not shown) that employ other radio technologies, such as LTE, LTE-A, LTE-A Pro, and / or non-3GPP (third generation partnership project) access technologies such as WiFi.

[0080] The SMF 183a, 183b may be connected to an AMF 182a, 182b in the CN 115 via an N11 interface. The SMF 183a, 183b may also be connected to a UPF 184a, 184b in the CN 115 via an N4 interface. The SMF 183a, 183b may select and control the UPF 184a, 184b and configure the routing oftraffic through the UPF 184a, 184b. The SMF 183a, 183b may perform other functions, such as managing and allocating WTRU IP address, managing PDU sessions, controlling policy enforcement and QoS, providing downlink data notifications, and the like. A PDU session type may be IP-based, non-IP based, Ethernet-based, and the like.

[0081] The UPF 184a, 184b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N3 interface, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices. The UPF 184, 184b may perform other functions, such as routing and forwarding packets, enforcing user plane policies, supporting multi-homed PDU sessions, handling user plane QoS, buffering downlink packets, providing mobility anchoring, and the like.

[0082] The ON 115 may facilitate communications with other networks. For example, the CN 115 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 115 and the PSTN 108. In addition, the CN 115 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and / or wireless networks that are owned and / or operated by other service providers. In one embodiment, the WTRUs 102a, 102b, 102c may be connected to a local Data Network (DN) 185a, 185b through the UPF 184a, 184b via the N3 interface to the UPF 184a, 184b and an N6 interface between the UPF 184a, 184b and the DN 185a, 185b.

[0083] In view of Figs. 1 A-1 D, and the corresponding description of Figs. 1 A-1 D, one or more, or all, of the functions described herein with regard to one or more of: WTRU 102a-d, Base Station 114a-b, eNode-B 160a-c, MME 162, SGW 164, PGW 166, gNB 180a-c, AMF 182a-b, UPF 184a-b, SMF 183a-b, DN 185a-b, and / or any other device(s) described herein, may be performed by one or more emulation devices (not shown). The emulation devices may be one or more devices configured to emulate one or more, or all, of the functions described herein. For example, the emulation devices may be used to test other devices and / or to simulate network and / or WTRU functions.

[0084] The emulation devices may be designed to implement one or more tests of other devices in a lab environment and / or in an operator network environment. For example, the one or more emulation devices may perform the one or more, or all, functions while being fully or partially implemented and / or deployed as part of a wired and / or wireless communication network in order to test other devices within the communication network. The one or more emulation devices may perform the one or more, or all, functionswhile being temporarily implemented / deployed as part of a wired and / or wireless communication network. The emulation device may be directly coupled to another device for purposes of testing and / or may perform testing using over-the-air wireless communications.

[0085] The one or more emulation devices may perform the one or more, including all, functions while not being implemented / deployed as part of a wired and / or wireless communication network. For example, the emulation devices may be utilized in a testing scenario in a testing laboratory and / or a non-deployed (e.g., testing) wired and / or wireless communication network in order to implement testing of one or more components. The one or more emulation devices may be test equipment. Direct RF coupling and / or wireless communications via RF circuitry (e.g., which may include one or more antennas) may be used by the emulation devices to transmit and / or receive data.

[0086] Described herein are example mechanisms to facilitate uncrewed aerial vehicle (DAV) trajectory prediction and associated measurements. The herein described trajectory prediction mechanisms also are applicable to any WTRU in motion and are not restricted to UAV trajectory prediction. For example, the herein described mechanisms may facilitate trajectory prediction when a WTRU is in a moving vehicle such as an automotive vehicle, an air vehicle (e.g., airplane, jet, helicopter, UAV, drone), a water vehicle, etc.

[0087] New radio (NR) may support flight path reporting for WTRUs configured as UAVs. A WTRU may be configured to include flight path availability indication. A WTRU may include flight path availability in various message types, such as, for example, RRCReestablishmentComplete, RRCReconfigurationComplete, RRCResumeComplete, RRCSetupComplete, UEAssistancelnformation message, or any appropriate combination thereof. A UAV WTRU may be configured to send an indication that updates are available regarding previously reported flight path information, depending on various factors and scenarios. For example, a UAV WTRU may send an indication that updates are available regarding previously reported flight information when a new waypoint that was not reported in previous flight path report is now available, when a waypoint that was reported previously has to be removed, when the difference between a previously reported waypoint and the new waypoint is more than a certain configured distance threshold, when a timestamp is available for a waypoint that was previously indicated with no timestamp, when the difference between the timestamp that was indicated for a certain waypoint and the new timestamp is more than a certain configured time threshold, or any appropriate combination thereof.

[0088] When one of the above conditions is fulfilled, the WTRU may send an indication in one of the above messages (e.g., trigger a UEAssistancelnformation, or send indication in the RRC complete messages), and the network may send a UElnformationRequest indicating that a flight path is requested and the WTRU may respond with a UElnformationResponse message that may contain the current flight path information. In the case of flight path update, this may be the whole flight path information and not only the updates from previously indicated flight path information.

[0089] Regarding mobility, a WTRU may perform measurements of serving and neighbor cells based on a configuration received by a gNB. The WTRU may be configured to report the measurements periodically or when certain events are fulfilled (e.g., A3 event, where a neighbor cell’s signal quality becomes better than the serving cell by more than a certain threshold). The WTRU may be configured with a conditional handover (CHO) configuration regarding a certain neighbor cell, which may contain a handover (HO) command and associated measurement event. When the measurement event conditions are fulfilled, the WTRU may execute the HO command associated with the event, instead of sending a measurement report.

[0090] Artificial Intelligence and / or Machine Learning (AI / ML) may be applicable to NR. AI / ML may be utilized, for example, to enhance mobility associated with network triggered L3-based handover (e.g., handover triggered by the network based on information received by the WTRU, such as measurement reports). WTRU UAV trajectory information may be used by the network to facilitate the HO of the WTRU (e.g., reserve resources at target cells / nodes on time, send the HO or CHO command to the WTRU on time, etc.).

[0091] Current mobility procedures may be reactive and may rely on current measurements available at the WTRU (e.g., measurement reported and gNB sending the HO command, or WTRU executing a CHO when the CHO conditions are fulfilled). This may come with a big overhead on both the WTRU and network side. For example, WTRUs may continuously perform measurements of neighbor cells and evaluate measurement reporting or CHO conditions. In the case of CHO, resources on several candidate neighbor cells must be reserved in anticipation of the WTRU handing over to one of these cells. Flight path information for UAVs may be deterministic and the reported flight path information may be expected to change only in unexpected scenarios (e.g., collision avoidance). Aspects of trajectory prediction made by the gNB and may be limited to only 1 traversing 1 gNB, which is impractical for any urban situation. If aWTRU has a capability to predict trajectory (e.g., based on an AI / ML model), a more proactive approach may be taken to performing WTRU mobility.

[0092] With the advancement of AI / ML mechanisms, it is anticipated that models may be trained that can predict the trajectory of the WTRU (e.g., at least within a short / limited time horizon, for a given location or time of day, etc.). For example, many users commute to and from work during specific time durations and drive along the same route (or use public transportation). The AI / ML model for capturing these trajectory patterns and predicting future trajectories may reside at the WTRU, the network, or external to the network (e.g., an OTT server that belongs to a WTRU vendor), or any appropriate combination thereof. For example, a WTRU configuration may be related to predicted trajectory information based on an AI / ML model and / or AI / ML model training. The training may also be done by / at the WTRU, network or external to the network, or any appropriated combination thereof. Having such information may transform the currently reactive approach of making mobility decisions into a proactive approach that allows the network to better prepare target cell candidates, anticipate radio resource usage / requirements, know how much time a WTRU will need to be served in a given cell, etc. Described herein are mechanism, methods, and apparatus for enabling WTRU trajectory prediction signaling and enhancing the signaling of trajectory updates.

[0093] An example method may comprise sending predicted trajectory information to the network when predicted trajectory information becomes available at the WTRU (e.g., when trajectory predicted with more than a certain level of confidence) or when an update is applicable regarding a previously reported trajectory information (e.g., when the trajectory is expected to change, when the prediction confidence changes, new information that was not available / reported before becomes available, etc.).

[0094] A WTRU may indicate to the network the WTRU’s capability to predict trajectory (e.g., based on AI / ML model). Capability information may include time / duration of day for prediction, prediction time horizon, number of cells that can be predicted, confidence of prediction, etc. Capability information may include several sets of information, one for each AI / ML model, for example. The WTRU may receive a configuration from the network on conditions to trigger predicted trajectory report / update or availability indication, where the triggering conditions may be the fulfillment of one or more of the following: upon handover; measurement event fulfillment (e.g., Ax event); confidence level of prediction becomes above a certain threshold; when prediction for a certain time duration or / and number of cells becomes available; when the WTRU expects to be in certain configured location within a given duration (e.g., cell, one of groupof cells, within a global navigation satellite system (GNSS) location / range, etc.); WTRU speed range, or WTRU speed change rate, has changed by more than a certain configure threshold; when previously reported trajectory expires or becomes outdated; when current location has diverged by more than a certain configured distance threshold compared to the reported trajectory for the current time; when current prediction has diverged by more than a certain configured distance / time threshold compared to the previously reported trajectory; WTRU monitors the triggering conditions and sends a predicted trajectory report / update (or send indication of the availability of trajectory report / update) when the conditions are fulfilled; or any appropriate combination thereof.

[0095] If the WTRU is able to make reliable trajectory predictions, the information can be used by the network to perform proactive mobility decisions. With knowledge of the WTRU’s upcoming trajectory, that possibly contains information about several cells / locations, each with time (e.g., actual time, time window information, etc.), the network could be able to allocate its UL / DL resources accordingly (e.g., prepare CHO candidates on time; opt to schedule the WTRU more aggressively or conservatively considering the expected time of stay in the current cell, the load conditions in the current cell and the expected target cell, the QoS profile of the active bearers of the WTRU, etc.).

[0096] Within this description, the terms AIML and AI / ML are used interchangeably. The terms “prediction”, “projection”, “expectation”, and “estimation” are used interchangeably. The terms “predicted”, “projected”, “expected”, and “estimated” are used interchangeably. The terms “report” and “indication” are used interchangeably. The term Ax is used to refer to any of the events A1, A2, A3, A4, A5, A6. Event A1 is associated with a serving becoming better than threshold. Event A2 is associated with a serving becoming worse than threshold. Event A3 is associated with a neighbor becoming offset better than SpCell, where SpCell is the Primary Cell, PCell or the Primary Secondary Cell, PSCell, in the case of dual connectivity. Event A4 is associated with a neighbor becoming better than threshold. Event A5 is associated with a SpCell becoming worse than thresholdl and neighbor becoming better than threshold2. And Event A6 is associated with a neighbor becoming offset better than SCell, where an SCell is a Secondary Cell in the case of carrier aggregation. The term Bx is used to refer to any of the events B1, B2. Event B1 is associated with inter radio access technology (RAT) neighbor becoming better than threshold. Event B2 is associated with a PCell becoming worse than thresholdl and inter RAT neighbor becoming better than threshold2. The term Condx refers to any conditional events. The term HO is used to describe either a legacy HO (e.g., RRC triggered handover) or a L1 / L2 triggered HO L1 / L2-triggered mobility (LTM). The term CHO is used to describe either a legacy CHO (e.g., an RRC HO command that is pre-configuredat the WTRU and executed when the CHO conditions are fulfilled) or an LTM CHO (e.g., an LTM configuration that is executed when certain LTM trigger conditions are fulfilled). The terms ‘trajectory’ and ‘path’ are used interchangeably. The terms “location” and “position” are used interchangeably. The terms “information” and “report” are used interchangeably. The terms “UE located in cell x” and “DE under the coverage of cell x” are used interchangeably.

[0097] AI / ML models may be applicable to trajectory prediction. The examples described herein are agnostic to the kind of AI / ML model / technique used by the WTRU (e.g., the algorithm used, the mechanism such as neural network or what kind of neural network, e.g., depth and parameters / weights of the network, etc.), the origins of the model (e.g., WTRU vendor, operator, network vendor, etc.), or how / where the training of the model is done (e.g., the input data used for the training, where the training is performed, if the training is performed offline or online, etc.). The model may be trained based on historical observation of the UE’s mobility (e.g., during certain time durations of the day, during which days of the week, at which locations, etc.).

[0098] There may be some WTRU capability communication between the WTRU and the network about AI / ML capability (e.g., where the WTRU can indicate to the network the supported AI / ML models / functions, confidence level of predictions, time horizon of predictions (how far along in the future are the prediction being made), etc.). The WTRU may support several AI / ML models for a certain functionality (e.g., with different prediction time horizons, prediction confidence levels, processing requirements, trained under / for operation in different frequencies / cells / location / times of day, etc.). A given AI / ML model may operate in different modes (e.g., with different levels of prediction confidence levels at different prediction time horizons, etc.). The WTRU may choose the AI / ML model to use for a certain functionality (e.g., network decides for which functionalities the WTRU can use AI / ML based operation, and the WTRU may choose the AI / ML model to use) or the network may explicitly control this (e.g., WTRU provides details of AI / ML models and their capabilities, network determines which model to activate for a particular functionality). A WTRU configuration may be related to performing trajectory prediction based on an AI / ML learning model training. The AI / ML models may be available at the WTRU already trained, or the WTRU may be provided with an untrained AI / ML model and performs the training by itself. The AI / ML model may be available at the WTRU already trained, and the WTRU may be enabled / configured to perform further training (e.g., for different conditions such as freq uencies / cells / location / ti mes of day, for the same conditions as the initial training but for increasing the level of confidence or / and the prediction time horizon, for different WTRU speeds, etc.).

[0099] Life cycle management (LCM) of AI / ML refers all the aspects of deploying and properly utilizing an AI / ML model in a given system. The following are example aspects / components of LCM: data collection; model training; functionality / model identification; model delivery / transfer; model inference operation; functionality / model selection, activation, deactivation, switching and fallback operation; functionality / model monitoring; model update; and WTRU capability reporting / identification. Data collection may be performed for different purposes in LCM, e.g. , model training, model inference, model monitoring, model selection, model update, etc. Model training may be performed online or offline. In online training, a model that is currently being used for inference may be trained in real time (continuously) with the arrival of new training samples / data sets. In offline training, data may be collected, and the model nay be trained using the collected data, and the trained model may be used later for inference. Functionality / model identification is a process / method of identifying an AI / ML functionality / model for the common understanding between the network and the WTRU. Identification of the model or functionality may be done offline without over-the-air signaling (e.g., implicitly via implementation where a model’s global ID indicates the functionality the model is to be used for, the training conditions, applicability conditions, etc.), or model identified explicitly via 3GPP based signaling (either initiated by the WTRU or the by the network). Once a model is identified, it may be assigned a local model ID that is used for further signaling in subsequent LCM operations. Model delivery / transfer refers to the delivery of an AI / ML model from one entity to another (e.g., from a network node / function such as a gNB, CN entity, etc. to the WTRU, etc.). The model that is being transferred could be already trained or untrained. A model also may be transferred transparently to the 3GPP network (e.g., a WTRU vendor can train the models on an OTT server and deliver them to the WTRUs transparently to the 3GPP network, e.g., like any other User plane traffic). Model inference operation refers to a process of using a trained AI / ML model to produce a set of outputs based on a set of inputs. Regarding functionality / model selection, activation, deactivation, switching, and fallback operation, selection refers to choosing a given AI / ML model among multiple models for the same AI / ML function. Activation / Deactivation refers to the enabling or disabling of a certain AI / ML model for a specific AI / ML operation. Switching refers to deactivating a currently active AI / ML model and activating another model. Fallback refers to disabling a certain AI / ML function and using, e.g., legacy operation that doesn’t employ AI / ML. Functionality / model monitoring refers to monitoring / observing the inference performance of a given AI / ML model or an AI / ML functionality. Model update refers to updating the AI / ML model parameters (e.g., after model (re)-training). WTRU capability reporting / identification refers to identifying what AI / ML relatedcapabilities the WTRU has (e.g., supported functionalities, models for each supported functionality, training conditions of the models, applicability conditions of the models, etc.).

[0100] FIG. 2 depicts an example function framework for AI / ML for a NR air interface. FIG. 2 summarizes the general LCM framework for AI / ML for NR air interface. The Management function (202) depicted in FIG, 2 may be a function that oversees the operation (e.g., selection / (de)activation / switching / fallback) and monitoring (e.g., performance) of AI / ML models or AI / ML functionalities. This function (202) also may be responsible for making decisions to ensure the proper inference operation based on data received from the Data Collection function (201) and the Inference function (206). Management Instruction (204) may be the information provided as input to manage the Inference function (206). This may include selection / (de)activation / switching of AI / ML models or AI / ML- based functionalities, fallback to non-AI / ML operation. Performance Feedback / Retraining Request (208) may be the information provided as input for the Model Training function (210), e.g., for model (re)training or updating purposes.

[0101] Various examples of location information and determination are described herein. A trajectory information / report may include information related to WTRU locations. The WTRU location may be a geographical location co-ordinates (e.g., (x,y,z) GNSS co-ordinates). The WTRU location may be cell level location information. A WTRU configuration may be related to performing trajectory prediction based on measurements. For example, a WTRU configuration may be related to performing trajectory prediction based on time duration, filter coefficients for consolidating past and current measurements, measurement sampling intervals, or beam consolidation thresholds for cell level measurement calculations. The WTRU may be configured with signal level thresholds (e.g., reference signal received power -RSRP threshold) and if the WTRU determines that a certain cell has a signal level above this threshold, the WTRU may consider itself under the coverage of that cell. Thus, if there are several cells that fulfill that condition, the WTRU may consider itself to be under the coverage of all such cells. In an example, the WTRU may be configured with more than one threshold, one for determining the entrance into the coverage area of a cell and another one for leaving the coverage area of a cell. The cell coverage area determination threshold(s) described herein may be common for all cells. The thresholds may be cell specific. The thresholds may be frequency specific (e.g., different frequencies associated with different thresholds). The thresholds may be RAT specific (e.g., different thresholds for LTE cells as compared to NR cells, etc.). The thresholds may be WTRU speed specific (e.g., different thresholds for low speed values or value ranges as compared to high speed values or value ranges). The WTRU may be configured to consider a maximum number of cells thatit can consider that it is under coverage of. For example, the WTRU may be configured to consider itself to be under the strongest cell that it can detect / measure. The WTRU may be configured with a time duration (similar to Time To Trigger for radio resource management (RRM) measurements, for example) that the signal level threshold conditions have to be fulfilled to consider the WTRU is under the coverage of that cell. The WTRU may be configured with coverage determination thresholds that are dependent on the number of cells the WTRU has detected. For example, if the WTRU has detected very few cells, the thresholds may be lower as compared to the case where the WTRU has detected many cells. The WTRU may be configured with several thresholds for different number of detected cells, or / and configured with baseline thresholds and scaling factors that can be used to scale the thresholds up or down depending on the number of detected cells.

[0102] The WTRU may use measurement configurations for RRM on detecting and measuring cells. That is, the WTRU may follow the RRM measurement principles such as not measuring cells that are in the blocked / black list, measuring only cells that are in the allowed / white list, measuring only the cells within the public land mobile network(s)-PLMN(s) the WTRU has a registration, measuring only frequencies the WTRU is configured to measure or configured to prioritize, etc.

[0103] The WTRU may be configured with a completely different measurement configuration for location determination / prediction as compared with RRM measurement configuration. In one solution, the WTRU may be configured to consider some parts of the RRM measurement configuration also for the location determination / prediction and provided with different / separate parts specific to location determination / prediction.

[0104] The WTRU may perform the cell measurements for trajectory prediction purposes (inference, training ,etc.) without restricting itself on the limitations of RRM measurements. For example, the WTRU may measure all cells at a certain frequency even if the RRM measurement configuration is to measure only a certain specific cells (e.g., WTRU was configured with an allowed / white list of cells to measure) of or not to measure (e.g., WTRU was configured with a blocked / black list of cells not to measure). The WTRU may follow the RRM measurement restrictions if it is not able to detect / measure a certain number of cells at a given location (or / and for a certain duration of time). For example, the WTRU may be configured to stick to the RRM measurement restrictions as long as it can detect / measure at least 2 cells. If the WTRU finds out that it is only under the coverage of one cell, it may start measuring cells that are outside the whitelist or within the blacklist, etc.

[0105] The WTRU may be provided with different measurement filtering configuration, e.g., different from RRM measurement filtering configuration, to use for determining if it is under the coverage of a certain cell. For example, the WTRU may be configured with different filtering time duration length, different filter coefficients for consolidating past and current measurements, different sampling intervals, etc. The WTRU may be provided with different beam consolidation thresholds for cell level measurement calculations when performing measurements for location determination / prediction. The WTRU may be configured with different numbers of beams to consolidate for cell level measurement calculations when performing measurements for location determination / prediction.

[0106] Although some examples of location determination / prediction may be either geographic coordinates level or cell(s) level, in other examples, location information may be known / predicted / determined at beam level (e.g., at cell x and beam A, at cell x and beams a or b, etc.).

[0107] Regarding the input / output of an AI / ML model, the AI / ML model used by the WTRU to predict WTRU trajectory may use current WTRU location and past / historical WTRU location information as an input. The current WTRU location may be determined using any of the above-described examples. The current WTRU location may be GNSS coordinates, if the WTRU has such capability. The AI / ML model may use current and past / historical cell level and / or beam level measurements of serving and neighboring cells. The AI / ML model may use the WTRU’s past / historical cell coverage or the statistical cell coverage of all WTRUs in that particular geographic area (for example leaving a train station most people go up the street but some go down the street.

[0108] The AI / ML model may use predicted cell / beam measurements of serving and neighboring cells and, based on the measurement predictions, the model may infer WTRU locations in the future. For example, the WTRU may infer a multitude of future signal levels of serving and neighbor cells, and use these inferred signal levels to determine the future location, using any of the solutions above for determining the WTRU location based on the cell / beam signal levels and configured thresholds for determining when in coverage of a cell / beam.

[0109] The WTRU may not have an AI / ML model for trajectory predictions, but may have an AI / ML model for measurement predictions. But based on any of the above-described examples for determining location based on cell / beam level measurements, the WTRU may be transform the measurement predictions into trajectory predictions.

[0110] Regarding the WTRU informing the network about its trajectory prediction capability, in one example, the WTRU may indicate that it is capable of trajectory prediction. The WTRU may indicate this capability as part of WTRU capability reporting. The WTRU may indicate this capability as a response to an explicit request from the network. For example, trajectory prediction capability may not be indicated as part of the normal / legacy WTRU capability reporting, but may be indicated upon explicit network request from the network (e.g., explicit request about trajectory prediction capability, general AI / ML capability request, etc.).

[0111] The WTRU may indicate that it is capable of AI / ML based trajectory prediction, and the WTRU may provide details of this capability if the network sends a subsequent request for detailed information. The trajectory prediction capability information may include any appropriate combination of the following. Trajectory prediction capability information may include time duration of day for prediction (e.g., between 7:30 am and 8:30 am). Trajectory prediction capability information may include prediction time horizon (e.g., up to 20 min in advance). Trajectory prediction capability information may include prediction location horizon (e.g., in terms of distance, in terms of number of cells to be traversed, etc.). Trajectory prediction capability information may include confidence of prediction (e.g., confidence percentage, error margin, etc.). Trajectory prediction capability information may include predicted location type(s) (e.g., GNSS coordinates, cell level predictions, beam level predictions ,etc.).

[0112] If time related trajectory information is available, the WTRU may be capable of predicting that it is going to traverse a certain list of cells within a given time, the order in which it is going to pass the cells, and the time of stay in each cell. If time related trajectory information is available, the WTRU may not be capable of predicting the time of stay in each cell, and as such indicates only the list of cells in a particular order that it is predicting to pass through, with a total expected time duration for the trajectory. If time related trajectory information is available, the WTRU may be able to predict only the order in which it is going to pass through the indicated cells without any time of stay information or total trajectory time information. If time related trajectory information is available, the WTRU may be able to predict the cells that it expects to pass through, without any indication of the sequence in which it is passing through them or any time related information.

[0113] The WTRU may indicate several capabilities that combine many of the above trajectory capability parameters. For example, capability 1 may refer to time duration 1 , prediction time horizon 1, predictionlocation horizon 1, confidence of prediction 1. Capability 2 may refer to time duration 2, prediction time horizon 2, prediction location horizon 2, confidence of prediction 2, etc.

[0114] The WTRU’s trajectory prediction capability may be WTRU speed dependent. Thus, one or more prediction related capabilities (as in the example above) may be associated with different WTRU speeds.

[0115] The WTRU may indicate the applicability conditions for the trajectory prediction. The applicability conditions may be the training conditions under which the prediction model was trained at, which could contain aspects such as, for example, time durations (e.g., time durations in which prediction is possible), geographical area (e.g., location co-ordinates, list of cells, RAN areas, etc.), WTRU speed, data set ID (e.g., an ID that is related to the training data / conditions, where the details of the training / data conditions are known by the network as well or available at another location / database that the network has access to), or any appropriate combination thereof.

[0116] There may be different combinations of applicability conditions. For example, the WTRU may indicate it is capable of predicting its trajectory during time duration A at areas X or Y, during time duration B at area Z, etc. The WTRU may indicate applicability conditions that are related to internal WTRU conditions such as memory, battery, and other hardware / software related aspects. For example, the WTRU may indicate it is capable of trajectory predictions at a high confidence level or for a longer timer horizon, but that will require a higher processing / memory / UE battery, etc., while it can do a lower confidence trajectory prediction with lower processing / memory / UE battery consumption, etc.

[0117] The WTRU may indicate one or more AI / ML models that are used for trajectory prediction. For example, the models may be associated with different model IDs (e.g., global model ID, a local model ID assigned by the WTRU or the gNB that is applicable at the cell level, gNB level, CN level, etc.). The WTRU may indicate different trajectory prediction capabilities for each AI / ML model. For example, each model may be associated with different capabilities discussed above and / or different applicability conditions. The WTRU may receive a request from the network about trajectory prediction that requests specific capability information instead of the WTRU sending the full trajectory related capability, and it may respond if it supports the requested capability or not (and optionally additional information related to the concerned capability or capabilities the network requested about). Some examples are given below.

[0118] The WTRU may receive a request from the network if it has trajectory prediction capability at a given time duration (e.g., between 7:30 am and 8 am), and if the WTRU has such capability, it may respond with an acknowledgement of that (and may include additional information such as the days of the weekwhere such prediction can be made, the areas / cells / location the WTRU normally expects to be in those areas, or maybe even an average trajectory during that time duration).

[0119] The WTRU may receive a request from the network if it has trajectory prediction capability at a given area (e.g., in some cells / geographical location, etc.), and the WTRU may respond with an acknowledgement (if it has such capability), and may further include additional information such as the days or / time durations during which trajectory prediction in the indicated area(s) can be made, and may even include an average trajectory around that area (e.g., if the indicated area was a group of cells, the WTRU may indicate to the network the order in which it usually expects to traverse within these cells, etc.).

[0120] The WTRU may be capable of doing measurement prediction only (e.g., cell / beam level measurement prediction of serving and neighbor cells), and not predicting trajectories directly. The WTRU, after sending such a capability information to the network, may be provided with a configuration on how to transform the measurement predictions to trajectory predictions as discussed in any of the examples above (e.g., signal level thresholds to indicate whether the WTRU is in the coverage of a certain cell or not, etc.). After this, the WTRU may perform the measurement predictions, and based on that and the received configuration transform the measurement predictions into trajectory predictions, and send that information to the network.

[0121] The WTRU may inform the network about assistance information needed for trajectory prediction inference, training, or performance monitoring. The WTRU may indicate that the trajectory prediction (in general or at a particular model level) may require assistance information from the network. In the assistance information request, the WTRU may indicate the reason for the assistance information (e.g., inference, training, performance monitoring, etc.). The WTRU may indicate that it needs positioning reference symbols (PRSs) configured (e.g., always when trajectory prediction is to be performed, for a certain duration, at certain cells, for certain AI / ML models, etc.) to perform the trajectory prediction. For example, the WTRU may need to determine / collect current / actual location / position for a certain duration to use as input for the AI / ML model to do the trajectory prediction.

[0122] The WTRU may indicate that it needs information about its position (e.g., always when trajectory prediction is to be performed, for a certain duration, at certain cells, for certain AI / ML models, etc.) to perform the trajectory prediction. For example, to do so, the WTRU may be configured with positioning sounding reference signals (pSRS) so that it can send the signals and network determines the position information. In another example, the WTRU may be configured with PRSs and configured to send the PRSmeasurements, using which the network does the positioning determination. The WTRU may receive the determined position from the network. The WTRU may not need to send the measured PRSs one by one, and may compile / log a certain amount of measurements before sending them to the network (e.g. certain measurement instances / values, measurements over a certain period of time, measurements over a certain number of cells / HOs, etc.). In such cases, the WTRU may add additional information such as timestamps, measurement instance number, measurement configuration ID, etc., that can be used by the network to process these logged information properly. This may be expanded so that the WTRU may support any known method of measurement that helps the network and the WTRU to determine its position using any of the know methods.

[0123] The WTRU may request position information from the network as a one-shot position information, periodically (e.g., every x msec, etc.), when the location has changed by more than a certain distance (e.g., x meters from current position, x meters from a reference position that is known to both the WTRU and network, etc.), or a combination (e.g., periodically every time the WTRU position changes from previously indication position by the network by more than a certain distance threshold, rate of change of position, etc.).

[0124] The assistance information to be used by the WTRU may be different from position related information. For example, the WTRU may request information about additional non positioning related measurements, such as downlink RRM related reference signals (e.g., SSBs, CSI-RSs, etc., that are related to serving cells or neighbor cells). For example, the measurements of these additional reference signals / beams / cells may not be needed to be performed for radio link monitoring or radio resource management purposes, but can enable the WTRU to make a more accurate trajectory prediction, collect more data for training or performance monitoring purposes, etc.

[0125] The WTRU may indicate that it is to be configured with measurement gaps for making interfrequency measurements that are needed for more accurate trajectory prediction, collect more data for training or performance monitoring, etc. In one example, the WTRU may indicate the need for gaps and the network may determine the gap configuration (e.g., periodicity, gap duration and pattern, etc.). In another example, the WTRU may indicate the preferred gap configuration (or configurations) to the network.

[0126] Regarding the contents of the trajectory report, the predicted trajectory information may contain a set of location and time pairs (e.g., time of arrival at that location, duration of stay at that location, time ofdeparture at that location, etc.), and the trajectory information may be associated with a confidence level. An example is shown below.{ location"!, timel , Iocation2, time2, locations, time3, }, confidence: 85%

[0127] The locations may be location coordinates (e.g.. location 1 refers to x,y,z GNSS co-ordinates) or one or more cell identities (e.g., location 1 refers to cells A, B, C, location 2 refers to cells B, C, D, etc.) indicating the cells the WTRU is under the coverage of. In case of location co-ordinates, the location information could be delta / relative information (e.g., from the first location in the report, which is indicated in absolute terms). The cell identities can be global cell identities (e.g., CGI) or local / regional cell identities (e.g., PCI).

[0128] The time information may be absolute time information (e.g., 10:14:35) or relative / delta time information (e.g., first location associated with absolute time, other locations associated with delta time, or the first value being a delta from a reference time known to both the WTRU and the network and the other values delta from the first value, all values delta from a reference time, etc.).

[0129] The time information may be a time duration information (e.g., earliest time expected to arrive at that location, latest time to arrive at that location, etc.), and it can be either delta or absolute time. Some examples are shown below.

[0130] Time information may comprise start time and end times, e.g., {10:14:35, 10:15:45} , indicating that WTRU predicts to be in the associated location during these absolute times

[0131] Time information may comprise start or end time and duration information, e.g., {10:14:35, 70 sec}, indicating first anticipated time of arrival at the location and expected duration of stay in that location, which can be interpreted the same as at a time information provided as {10:14:35, 10:15:45}.

[0132] Time information may comprise average estimated time and duration, e.g., {10:14:35, 70 sec}, which can be interpreted as {10:13:25, 10:15:45}, i.e., 70 sec before or after 10:14:35.

[0133] Time information may comprise, similar to the above, but also for delta time values (e.g., the first location associated with an absolute time and delta information for the start and end durations, while the other locations may include just a delta information to that, e.g., location 1 : {10:13:25, 1-:15:45}, location 2 {5 min, 10 min}...m, which is interpreted as location 2 is expected to be reached at least 5 min after location 1 , but not later than 10 min after location 1 , etc.}. The time might not be set to the clock but is just a duration that the WTRU is expected to stay in that cell.

[0134] The WTRU may provide separate confidence levels for the location and time information. The WTRU may provide confidence level for each location / time information pair instead of or in addition to the whole trajectory information. The WTRU may provide separate confidence levels for each location and each time information, even for a given location / time pair (e.g., Iocation_1 (confidence level A), time_1 (confidence level B), which can be interpreted as the WTRU having a confidence level of A of being at that location at some point, and assuming that happens, its confidence that it will be at that location at time_1 is of confidence level B.

[0135] The WTRU may provide multiple trajectory information, each with different confidence levels (or sub confidence levels) according to any of the solutions above. For example, the WTRU may provide the following predicted trajectory information: trajectory 1 : { locationA, timel, locationB, time2, locationC, time3, }, confidence:75% trajectory 2: { locationA, timel, locationD, time2, locationC, time3 }, likelihood:65% trajectory 3: { location , timel, locationY, time4, locationZ, time5, }, likelihood:50%

[0136] The trajectory information may contain a tree like structure that indicates several paths a WTRU might take. An example is shown below.{ locationl, timel, confidence: 95%}{location 2.a, time 2.a, confidence 85%}{location 3. a, time 3. a, confidence 75%}{location 3. b, time 3. b, confidence 25%}{location 2. b, time 2.b, confidence 15%}{location 3.c, time 3.c, confidence 85%}{location 3.d, time 3.d, confidence 15%}, etc.

[0137] An example interpretation of the above may be that the WTRU predicts that it will be in location 1 at time 1, with a 95% confidence. After that, the WTRU expects its trajectory to be at location 2.a or at location 2.b at times 2.a or times 2. b, with confidence levels of 85% and 15%, respectively. If location 2. a materializes, the WTRU expects to be at locations 3.a or location 3. b, at times 3.a and time 3. b, with confidence levels of 75% and 25%, respectively, and so on.

[0138] The trajectory information may contain only location information without detailed time duration or arrival information at each location, but only a time duration for the validity of the trajectory. For example,the WTRLI may indicate that it expects to follow a certain trajectory during a certain time duration (e.g., locations 1, 2, 3, ...n) without any indication about the time of arrival / departure at each location. The trajectory information may implicitly or explicitly indicate the sequence in which the WTRU arrives at these locations. In another example, the trajectory information may not indicate the sequence in which the WTRU arrives at these locations (e.g., what the WTRU is predicting is the WTRU will be at the indicated locations at some point during the indicated trajectories time duration). The WTRU may indicate in the trajectory report some indication of the sequence of the locations, each for example, with some confi dence / likeli hood level. For example, if the WTRU predicts that it will pass through 3 locations with the trajectory time duration, the indicated trajectory report may be similar to the example shown below.First location:50% probability: location A, 40% probability: location B, 10% probability location C Second location:If first location is location A:40% probability: location B, 60% probability: location CIf first location is location B:45% probability: location A, 55% probability: location CIf first location is location C:30% probability: location A, 70% probability: location BThird location: (this will be deterministic based on what location 1 and location 2 were).

[0139] The trajectory information may be a current location, direction of mobility, and speed information (e.g., current location x, traveling at 45 degrees in the NW direction at an average speed of x km / h, for the next x time duration). The trajectory information may contain multiple sets of such information, e.g. {current location, [time duration 1 : direction, speed], [time duration 2: direction, speed], .. .}. Similar to the examples above, confidence level of the trajectory information may be set at the whole trajectory level, at a particular time duration / direction / speed level, or at the granularity of each individual entity in the report. Some examples are shown below.- trajectory info: confidence level: x%, current location, [time duration 1 : direction, speed], [time duration 2: direction, speed], ...}.- trajectory info: current location, [confidence level 1 , time duration 1 : direction, speed], [confidence level 1 , time duration 2: direction, speed], ...}.trajectory info: current location, [time duration 1 (^confidence level): direction(-«-confidence level), speed(-confidence level)], time duration 2 (-confidence level): direction(+confidence level), speed(-confidence level)]

[0140] The WTRU may send trajectory information that uses a combination of more than one or more of the examples described above. For example, the WTRU may be able to predict more precise geographic coordinates for time duration t1 , and prediction at cell level for time duration t1 to t2, and direction / speed level after t2, etc., and as such may include a trajectory information that contains all these in one report.

[0141] The WTRU may indicate that trajectory information is temporary. For example, the WTRU may indicate that the trajectory information is only valid for the associated time duration information of the trajectory (e.g., trajectory information is indicating trajectory for the next 30 minutes, and after that it is not valid anymore).

[0142] The WTRU may indicate that the trajectory information is valid semi-statically for other time durations or days of the week. For example, in the trajectory information the WTRU may indicate that, unless otherwise updated by the WTRU later, the WTRU expects to follow the same trajectory on certain specific days every week / month / year (e.g., every working day between 8 and 8:30, every weekend between 12 and 12:30, every first day of the week, every last Thursday of the month, on public holidays, etc.). The network may incorporate this information as part of the WTRU context (e.g., in the RAN) and may use it without the need for the WTRU to communicate this same information every day. In another example, the network may store this information in the core network (CN) (e.g., associated with the permanent WTRU identifier, such as the international mobile subscriber identity - IMSI), so that the information may be available at the network even if the WTRU goes back and forth between RRC CONNECTED and RRC IDLE / I NACTIVE states.

[0143] Regarding the contents of a trajectory report update, the WTRU may send a report to amend a trajectory report that it has sent before. This, for example, may be due to some anticipated sudden change of direction of the WTRU (e.g., User usually takes the same public transport, e.g., subway / bus / tram, but due to unexpected conditions such as traffic jam, bus / train drivers’ strike, accidents, etc., takes a car / cycle, that takes a route very different from the subway / bus / train). The update report may be a full trajectory prediction report, indicating to the network that any previously sent trajectory report is not valid anymore. The update report may be a delta trajectory report that adds / removes some elements from the report (e.g., a WTRU may indicate the removal of a location / cell that it has included in previous trajectory report). The update report may be a delta trajectory report that modifies the confidence level of one or more entries in aprevious trajectory report. The update report may be a delta trajectory report that modifies the time information associated with one or more previously associated locations. The update report may be a simple indication (e.g., a Boolean flag), indicating whether the previously sent trajectory information is still valid or not. This could, for example, be sent to the network upon an explicit request from the network for such information.

[0144] The WTRU may send some lightweight update information about trajectory. For example, it may be that the time information may not be 100% accurate even if the predicted location information is. Thus, the WTRU can send a simple uplink (UL) indication to the network stating that it expects to arrive at the next indicated location in the previously sent trajectory report (e.g., within a certain duration from now). The time duration information in this UL indication may be implicit in the message (e.g., WTRU is already configured with a time duration value and sends the indication when it expects to be at the next location, e.g., with more than a certain confidence level), or it can be explicitly included in the UL indication. Such an UL indication may be a UCI, MAC CE, RRC message, etc. Similarly, a WTRU may be configured to trigger and send lightweight update information indicating failure / error instead of confirmation of previously indicated trajectory (e.g., if the next location is going to be skipped, if the arrival time at the next location is expected to be much later or sooner than what was indicated before, etc.).

[0145] Regarding how the trajectory information may be sent, the trajectory information may be sent via an RRC message. For example, this could be a new RRC message or a modification of an existing RRC message such as the WTRU assistance information. The trajectory information may be sent via a NAS message or a NAS like message that is above the RRC protocol (e.g., trajectory information sent to a CN entity such as the LMF instead of the RAN, e.g.).

[0146] Whenever the WTRU has a trajectory report or trajectory update report to provide to the network, according to any of the solutions above, the WTRU may send an indication to the network a trajectory report or a trajectory report update is available, and may send the information on explicit request from the network. Such an indication may be provided in several ways. For example, the indication may be sent in an RRC complete messages (e.g., opportunistically as part of any RRC complete message). The information may be sent in a separate RRC message (e.g., new RRC message, in WTRU assistance information message, etc.). The information may be sent in a MAC CE. The information may be sent in a universal communications identifier (UCI).

[0147] When the WTRU has a trajectory report or trajectory update report to provide to the network, according to any of the examples above, the WTRU may send the report immediately to the network (i.e., the report is generated and forwarded to the lower layers for transmission, and sent when / if UL transmission resources are available). The trajectory report and report updates may be sent via an already specified signaling radio bearer (SRB) (e.g., SRB1 , SRB2, SRB3, SRB4, etc.). The trajectory report and report updated may be sent via a new SRB (e.g., SRBx) that has different behavior than currently defined SRBs (e.g., different priority, different message segmentation support, etc.).

[0148] The WTRU may be configured to use a certain SRB depending on the trajectory report or report update that needs to be sent. Some examples are given below.

[0149] If the latest trajectory prediction is different from the previously reported trajectory prediction by more than a certain configured error margin, the WTRU may send the new report / update using SRB1 , while if the difference is below a certain configured margin, the WTRU may send the new report / update using SRB2, etc.

[0150] If the size of the trajectory prediction report / update is bigger than a certain configured size, the WTRU may use SRB4 to send the report, while if the this size, is less, the WTRU may send the report via SRB2

[0151] If the WTRU has a trajectory report / update to send and it has no UL resources available, it may send an SR to the network to indicate the need for UL grants. In one example solution, the SR may be a newly defined SR for this purpose.

[0152] The SR may be sent depending on the urgency of the report / update (e.g., the SR is sent only if the report was indicating that the latest trajectory prediction at the WTRU is different from the one it has sent previously by more than a certain error margin, otherwise, the WTRU can wait until it gets an UL grant for other reasons, e.g., due to UL UP data, next CG occasion, etc., to send the report).

[0153] Conditions / events for triggering trajectory prediction related information are described below. Triggering conditions for sending a (predicted) trajectory information are described. This information / report may be a full trajectory report or trajectory report update (e.g., a delta trajectory report, an indication whether the previously sent report or some entries of the report are valid or not, etc.), according to any of the solutions above. The full trajectory report may comprise an indication that the full trajectory report supersedes and / or replaces a previous trajectory report. Optionally, the full trajectory report may comprisean indication that a previous trajectory report is not valid. Optionally, the full trajectory report may comprise an indication that the full trajectory report replaces a previous trajectory report. The trajectory update report may be a delta trajectory report that adds and / or removes some elements from a previous trajectory report. For example, the trajectory update report may comprise an indication regarding the removal and / or addition of a location that was included in a previous trajectory report, the trajectory update report may comprise an indication regarding the removal and / or addition of a cell that was included in a previous trajectory report, or any appropriate combination thereof. The trajectory update report may comprise an indication of a modification of a previous trajectory report. The modification of the previous trajectory report may comprise at least one of removal of a location that was indicated in the previous trajectory report, removal of a cell of a previous trajectory report, an addition of a location that was indicated in the previous trajectory report, an addition of a cell of a previous trajectory report, or a modification of time information associated with a location indicated in the previous trajectory report. Based on triggering, the WTRU may send the report / update immediately when the triggering conditions are fulfilled or the WTRU may just send an indication that a report / update is available (e.g., WTRU will send the report / update only if the network further request it).

[0154] The WTRU may be explicitly requested by the network to send a one-shot (aperiodic) trajectory report. In this request, the network may include information about the time duration of the trajectory report or it can be up to the WTRU to determine the trajectory time duration. For example, if no time duration is included in the request, the WTRU may include the trajectory prediction for a time duration that is limited by its prediction model. In another example, if the request contains a time duration, the WTRU will send a trajectory prediction, the duration of which will be the minimum of the time duration that the WTRU’s model is able to predict and the time duration indicated in the request.

[0155] The time duration included in the request by the network may be a delta / relative time from the current time (e.g., for the next x seconds / minutes). The relative time duration may not explicitly included in the request but previously communicated to the WTRU. For example, the WTRU may be previously configured by the network to consider the time duration to be 10 minutes, and every time a request is sent by the network, it may send trajectory information for the next 10 minutes. Or the time may be explicitly fixed by the standard or is globally configured in SIBs or O&M based on the network implementation. The time duration included in the request by the network may be an absolute time (e.g., between 10:30 and 11 :00).

[0156] The request from the network may include information related to the confidence level of the prediction. For example, the WTRU may be requested to send trajectory report if the confidence level of that prediction is above a certain confidence level threshold (this could be at the whole trajectory report level, or at individual location / time entries within the trajectory report, as discussed in any of the solutions above). The confidence level threshold for reporting may be explicitly included in the request. The confidence level threshold for reporting may not be explicitly included in the request but previously communicated to the WTRU. For example, the WTRU may be previously configured by the network to consider the confidence level for reporting to be at least 80%, and every time a request is sent by the network, it may send trajectory information if the confidence level of the trajectory is above 80% (or include particular location / time record / element within the trajectory report if the confidence level of the element is above 80%).

[0157] The request for trajectory information sent from the network to the WTRU may include one or more location information. For example, the request may indicate identity of cells x and y, and in response to that the WTRU may send a report indicating trajectory information regarding those cells (e.g., no report if the WTRU doesn’t expect to be in those cells, e.g., within a configured duration, a short report explicitly indicating that the WTRU is not expected to be there, a report indicating the expected time of arrivals at the indicated cells and corresponding confidence levels, etc.). Time or time duration information may also be included along with the location information in the request (indicating to the WTRU to send a report if the WTRU expects to be in the indicated location within / at the indicated arri val / departure times or time durations, etc.).

[0158] The WTRU may be configured to send predicted trajectory information periodically (e.g., where periodicity is defined in terms of time, e.g., every x seconds / minutes). The WTRU may be configured to send predicted trajectory information in terms of the difference between the current WTRU location from the last time such a report was generated (e.g., WTRU sends the report every time its location has changed by more than a certain meters / kms from the previous reporting. The WTRU may be configured to send predicted trajectory information when / if it detects a change from the previously reported trajectory (e.g., if the WTRU has reported a prediction that it will pass through cell A, then B, and then C, but it realizes that it has gone through cell A, then B and then D, it may trigger a report / update upon determining that it has gone from cell B to D, instead of cell C).

[0159] The WTRU may be configured to send predicted trajectory information when / after it has arrived at the last location indicated in the previous trajectory report. The WTRU may be configured to send the trajectory report at a location before the last location (e.g. , at the penultimate location, at the nth location before the last one, etc.). The WTRU may be configured to send predicted trajectory information when / after the time duration for the previous trajectory report has elapsed / expired (e.g., if WTRU has sent a trajectory prediction report between 10 am and 11 am, it may trigger a new trajectory report at 11 am). The WTRU may be configured to send trajectory information a certain time duration before the expiry of the previous trajectory report (e.g., if this time duration is specified to be 10 minutes, and WTRU has sent a previous trajectory report that has a time duration of 10 am to 11 am associated with it, WTRU will trigger the next trajectory report at 10:50 am, etc.).

[0160] A combined approach that considers both periodicity and distance / location differences may also be utilized. For example, the WTRU may be configured to send the trajectory information every x seconds, but only if the distance / location difference threshold conditions are also fulfilled during that time.

[0161] The WTRU may be configured to send trajectory information after performing a handover (e.g., include the report / update in the HO complete command, include an indication that a report / update is available in the HO complete command, etc.).

[0162] The WTRU may be configured to send trajectory information when detecting the confidence level of the trajectory prediction (e.g., the confidence level of the whole trajectory, the confidence level of a particular location / time entry within the trajectory, etc.) has become above a certain threshold. The WTRU may be configured to send trajectory information when detecting the confidence level of the trajectory prediction currently at the WTRU is greater than or less than the confidence level indicated in a previously sent trajectory information by more than a certain configured threshold. For example, if the WTRU has sent a trajectory prediction information stating that it expects to be in cell x within 5 minutes at a confidence level of 50% and if the confidence level of the prediction has increased to 90% within 1 minute of sending that prediction, it may a trajectory report / update to the network indicating that it expects to be in cell x within 4 min at 90% confidence level.

[0163] The WTRU may be configured to send trajectory information when a certain measurement event (e.g., Ax, Bx, etc.) gets fulfilled (or if the WTRU is capable of measurement prediction, when a certain measurement event Is expected to be fulfilled, e.g., within a given duration, etc.).

[0164] The WTRU may be configured to send trajectory information when it predicts to be within a given location (e.g., configured cell or group of cells, gNSS area range, etc.) within a given duration or / and confidence level (e.g., WTRU preconfigured with the concerned cell identity or identities, time duration, confidence level). One or more time duration and / or confidence levels may be associated with the configured cell or group of cells. For example, the WTRU may be configured to send trajectory information when / if it predicts that it will be in one of the configured cells within time duration 1 at a confidence level of 80% or within time duration 2 at a confidence level of 70%, etc.

[0165] The WTRU may be configured to send trajectory information when it has predicted trajectory information that covers a certain area (e.g., difference between the first location and last location is more thana certain distance threshold, when it is predicted the trajectory for a given sequence of cells or group of cells, etc.). A confidence level threshold may also be configured associated with this to control the reporting (e.g., WTRU reports the trajectory if the area / distance conditions are fulfilled and the confidence is above the configured confidence threshold.).

[0166] A WTRU configuration may be related to reporting predicted trajectory information. A WTRU configuration may be related to reporting predicted trajectory information based on timing associated with transmission of a predicted trajectory report. The WTRU may be configured to send trajectory information when it has predicted a trajectory information that covers a certain configured time duration (e.g., relative time duration from now, absolute time duration, e.g., between 9 am and 9:15 am, etc.) A confidence level threshold may also be configured associated with this to control the reporting (e.g., WTRU reports the trajectory if the absolute / relative time duration conditions are fulfilled and the confidence is above the configured confidence threshold.).

[0167] The WTRU may be configured to send trajectory information when it has detected that it has diverged or it is predicting to diverge from a previously sent trajectory information by more than a certain threshold. This may be contain one or more of the following. The WTRU has arrived (or now expects to arrive) at a certain previously indicated location earlier or later than a certain time threshold, as compared to the previously reported time for that location. The WTRU has not arrived at a previously indicated location within a configured time window as compared to the time information indicated for that location (e.g., WTRU has indicated it expects to be in cell x between 8 and 8:10 am, assuming in a previous report, and assuming the configured time window was 5 minutes, the WTRU will trigger the trajectory report if it has not arrived at that cell at 8:15). The WTRU has detected that the direction of movement has changedby more than a certain degrees. The WTRU has detected that the speed has changed by more than a certain speed threshold. A metric that is based on the differences of the previously indicated times and the current predicted times for the different indicated locations is more than a certain threshold (e.g. , the metric is a mean squared error of the time differences). A metric that is based on the differences of the previously indicated locations and the current predicted locations for the different indicated time durations is more than a certain threshold (e.g., the metric is a mean squared error of the location differences). A metric that is based on location and time differences. When more than a certain new locations (e.g., new cells that were not indicated in the previous report) are predicted in the trajectory, etc.

[0168] A WTRU configuration may be related to reporting predicted trajectory information based on prohibiting a predicted trajectory report. The WTRU may be configured with prohibit timers for predicted trajectory reporting. There may be one prohibit timer value configured for all kinds of trajectory reporting (e.g., WTRU forbidden not to send two sequential trajectory reports within a time duration less than the configured prohibit timer duration, regardless of the conditions that triggered the trajectory report), or several independent timers can be configured, each corresponding to different triggering conditions (e.g., first timer value configured to be used with reports triggered due to new location addition to the predicted trajectory, second timer value configured to be used with reports triggered due to location removal from the predicted trajectory, third timer value configured to be used with reports triggered due to confidence level changes in the predictions, etc.).

[0169] Aspects related to trajectory prediction at the network are described. WTRU trajectory prediction may be used in conjunction with network WTRU trajectory prediction, as an input into the model (WTRU prediction as an input into network prediction and / or visa-versa). The WTRU trajectory prediction may be sent to the network via any appropriate message new or existing like RRC reconfiguration, handover signaling or even MAC signaling. For feedback to the model on both the network and the WTRU sides the reporting may be sent to multiple gNBs, for example, if the network model in gNB A predicts that the WTRU will go to cells A1 and A2 in gNB A and cells B1 and B2 in gNB B and cell C1 in gNB C, the model in gNB A could make use of how the WTRU model is predicting trajectory when it is served in gNB B or gNB C along the predicted trajectory, or in general how a particular UE’s predicted trajectory aligns with the networks predicted trajectory. Feedback may comprise the WTRU history report generated by the WTRU either normally as in the status quo or explicitly triggered by the end of the predicted cells or when the WTRU has deviated from the predicted cells or for example going to idle after moving to another gNB since going toidle mode implies WTRU driven mobility vs. network driven mobility or other events, like the WTRU stopping movement for a longer period of time.

[0170] The WTRU may be configured to report additional information related to the lifecycle management (LCM) of the one or more AI / ML models doing trajectory prediction to the network. The additional information may include any one or more of the following: Model ID of the one or more models at the WTRU doing trajectory prediction; Model ID of the currently activated model at the WTRU doing trajectory prediction; Conditions under which the one or more models are applicable to use for inference (e.g., radio conditions, cell frequency range, area, topology, geography, topography, e.g., urban vs rural, etc.) - For example, one model may be applicable in a particular topography, for example, in a rural setting and may not be suitable to do trajectory prediction in an urban setting which is more dynamic with many more obstacles; Conditions under which the one or more models were trained (e.g., radio conditions, cell frequency range, area, topology, geography, topography, e.g., urban vs rural, etc.) - For example, one model may be trained under certain radio conditions, e.g., RSRP in a certain range and may not be applicable to be used for inference in a different frequency range.

[0171] The WTRU may be configured to simply report the functionality for which AI / ML capability is enabled, e.g., trajectory prediction without reporting information on the models doing the prediction. The WTRU may still report other indications such as a model switch indication (without including the model ID of the target model) or an indication for model training / retraining / fine-tuning or a fallback to legacy procedures.

[0172] The WTRU may be configured to do performance monitoring. For example, as the WTRU keeps moving, it may compare its actual trajectory with its predicted trajectory. The WTRU may have been preconfigured with some distance thresholds d by the network, such that if the deviation between the actual trajectory and the predicted trajectory exceeds the preconfigured threshold, the WTRU may be configured to take any one or more of the following actions and inform the network of the correctional action taken. The WTRU may redo trajectory prediction. The WTRU may update trajectory prediction. The WTRU may report updated trajectory prediction to the network (NW). The WTRU may train / retrain / fine-tune trajectory prediction model. The WTRU may switch to another trajectory prediction model among the models at the WTRU. The WTRU may activate another trajectory prediction model among the models at the WTRU. The WTRU may switch to another legacy / GPS system for trajectory monitoring. The WTRU may download new / updated / fine-tuned model from the NW and / or third party.

[0173] The NW may do performance monitoring, even if the trajectory prediction model may be at the WTRU. The WTRU may not do any performance monitoring and may simply report the output of the AI / ML model to the NW. The WTRU may be reporting additional information to the NW allowing the NW to compare the reported trajectory predictions against the additional information which may include the coordinates of the WTRU, positioning information, GPS, beam related information that may allow the NW to determine the location of the WTRU (e.g., beam ID), etc. Following the performance monitoring at the NW, the WTRU may receive an indication from the NW to do any one or more of the following actions: train / retrain / fine-tune trajectory prediction model; switch to another trajectory prediction model among the models at the UE; activate another trajectory prediction model among the models at the UE; switch to another legacy / GPS system for trajectory monitoring; download new / updated / fine-tuned model from the NW and / or third party; redo trajectory prediction; update trajectory prediction; report updated trajectory prediction to the NW.

[0174] The WTRU may receive configuration from the network for model training if the model is at the NW or at an over the top (OTT) server. For example, the MDT framework may be enhanced for trajectory computation and / or prediction. For example, the NW may send a special RRC message, ‘loggedMeasurementConfig uration’ message to the WTRU to trigger the measurement and logging at the WTRU. In another example a new framework may be devised attuned to trajectory computation and / or prediction. The WTRU may receive such configuration and / or update thereof as part of RRC (re)configuration. The data collection framework may include any one or more of the following parameters being measured and reported. Parameters may include WTRU location, WTRU speed / velocity, WTRU direction of motion, or the like. Additional information that may include throughput, handover performance, cell reselection performance etc.

[0175] The data collection framework may also include information on how / when to make the measurements and reporting, which may include any one or more of the following. The information may include frequency to make measurements. The information may include frequency for reporting measurements. The information may include maximum and / or minimum time interval between consecutive measurements. The information may include maximum and / or minimum time interval between consecutive reporting. The information may include when to report (e.g., reporting times, reporting intervals, events for reporting). The information may include maximum number of measurements that can be made. The information may include maximum number of that can be reported. The information may include minimum number of measurements that must be reported at once.

[0176] The WTRU may be configured to send measurements for training of the model at the NW when the WTRU is moving / flying along a certain predetermined trajectory to allow the NW to assess the quality of the measurements reported by the WTRU. The WTRU may be configured to send measurements in various / random areas, e.g., not necessarily moving along a certain predetermined trajectory. The WTRU may be configured to send measurements for training of the model at the NW when the WTRU is moving / flying along a certain predetermined trajectory for a certain time period during which the NW may determi ne / assess the accuracy of the measurements reported by the WTRU. If found to be accurate (e.g., accuracy > 95%), the WTRU may receive new configuration from the network to also report measurements outside of the predetermined trajectory.

[0177] Examples may include sending predicted trajectory information to the network when predicted trajectory information becomes available at the WTRU (e.g., when trajectory predicted with more than a certain level of confidence) or when an update is needed regarding a previously reported trajectory information (e.g., when the trajectory is expected to change, when the prediction confidence changes, new information that was not available / reported before becomes available, etc.). For example, a WTRU may be configured to indicate to the network the WTRU’s capability to predict trajectory (e.g., based on AI / ML model). The capability information may include time / duration of day for prediction, prediction time horizon, number of cells that can be predicted, confidence of prediction, etc. The capability information may include several sets of information, one for each AI / ML model. The WTRU may be configured to receive a configuration from the network on conditions to trigger predicted trajectory report / update or availability indication. Triggering conditions may include, upon handover, measurement event fulfillment (e.g., Ax event), confidence level of prediction becomes above a certain threshold, when prediction for a certain time duration or / and number of cells becomes available, when the WTRU expects to be in certain configured location within a given duration (e.g., cell, one of group of cells, within a GNSS location / range, etc.), WTRU speed range or WTRU speed change rate has changed by more than a certain configure threshold, when previously reported trajectory expires or becomes outdated, when current location has diverged by more than a certain configured distance threshold compared to the reported trajectory for the current time, when current prediction has diverged by more than a certain configured distance / time threshold compared to the previously reported trajectory, monitors the triggering conditions and sends a predicted trajectory report / update (or send indication of the availability of trajectory report / update) when the conditions are fulfilled, or the like, or any appropriate combination thereof.

[0178] If the WTRU is able to make reliable trajectory predictions, the information may be used by the network to perform proactive mobility decisions. With knowledge of the WTRU’s upcoming trajectory, that possibly contains information about several cells / locations, each with time (e.g., actual time, time window information, etc.), the network may be able to allocate its UL / DL resources accordingly (e.g., prepare CHO candidates on time; opt to schedule the WTRU more aggressively or conservatively considering the expected time of stay in the current cell, the load conditions in the current cell and the expected target cell, the QoS profile of the active bearers of the WTRU, etc.).

[0179] FIG. 3 depicts an example diagram illustrating a WTRU capable of directly predicting trajectory. FIG. 3 illustrates an example realization of some of the herein examples (e.g., WTRU capable of directly predicting trajectory). As depicted in FIG. 3, at step 302, a WTRU may send capability information to the network, indicating that it is capable of trajectory prediction (including detailed information about prediction time horizon, confidence levels, location / areas / time duration where / when trajectory prediction is possible, etc.). At step 304, the WTRU may receive a trajectory prediction configuration from the network regarding the triggering conditions / thresholds / events for trajectory reporting (e.g., radio signal level related thresholds, detection of changes from previously reported trajectory, locations / times of interest, etc.). The trajectory prediction configuration may be related to performing trajectory prediction and reporting predicted trajectory information, wherein the trajectory prediction configuration may comprise at least one triggering condition for reporting trajectory prediction information.

[0180] The WTRU may perform trajectory prediction at step 306. Predicted trajectory information may comprise location information. The location information may comprise at least one of a sequence of locations, a range of locations, cell information, Global Navigation Satellite System (GNSS) co-ordinates, predicted arrival time at a location, predicted departure time from a location, or predicted time of stay at a location. The WTRU may monitor if the conditions (e.g., triggering conditions) are fulfilled at step 308. A triggering condition may comprises any appropriate triggering condition. Triggering conditions may comprises at least one, or any appropriate combination, of the following as described herein. A triggering condition may be based on a confidence level of a prediction being greater than or equal to a threshold confidence level. A triggering condition may be based on a trajectory prediction being applicable for a duration of time after transmission of trajectory projection information. A triggering condition may be based on the WTRU being in a predetermined location during a predetermined duration of time. A triggering condition may be based on a location of the WTRU at a predetermined time differing by greater than a threshold distance compared to a previously reported trajectory for the predetermined time. A triggeringcondition may be based on at least one parameter of a projected trajectory differing by greater than a respective threshold amount compared to the at least one parameter of a previously reported trajectory.

[0181] At step 310, upon determining that the triggering conditions are fulfilled, the WTRU may send / transmit a trajectory report or report update. The transmitted trajectory report may comprise trajectory prediction information. Transmitted predicted trajectory information may comprise a full trajectory report. Optionally, the full trajectory report may comprise an indication that the full trajectory report replaces a previous trajectory report. The transmitted trajectory update report may comprise an indication of a modification of a previous trajectory report. The modification of the previous trajectory report may comprise at least one of removal of a location that was indicated in the previous trajectory report, removal of a cell of a previous trajectory report, an addition of a location that was indicated in the previous trajectory report, an addition of a cell of a previous trajectory report, or a modification of time information associated with a location indicated in the previous trajectory report. The transmitted trajectory report may comprise trajectory prediction information comprising a trajectory update report comprising an indication of a modification of a previous trajectory report.

[0182] In one example, the WTRU may receive configuration information at step 304 without sending the WTRU’s prediction trajectory capabilities at step 302. In another example the WTRU may send the WTRU’s prediction trajectory capabilities at step 302 and receive configuration information at step 304.

[0183] FIG. 4 depicts an example diagram illustrating a WTRU capable of directly predicting measurements. FIG. 4 illustrates an example realization of some of the herein examples (e.g. WTRU capable of predicting measurements). At step 402, the WTRU may send capability information to the network, indicating that it is capable of measurement prediction (including detailed information about prediction time horizon, confidence levels, etc.). At step 404, the WTRU may receive a trajectory prediction configuration from the network regarding on how to determine location from measurement (e.g., thresholds to consider to be under a certain cell) and the triggering conditions / thresholds / events for trajectory reporting. The trajectory prediction configuration may be related to performing trajectory prediction and reporting predicted trajectory information, wherein the trajectory prediction configuration may comprise at least one triggering condition for reporting trajectory prediction information.

[0184] The WTRU may perform measurement and measurement prediction at step 406. The WTRU may transform the (predicted) measurements to a predicted trajectory at step 408. Predicted trajectory information may comprise location information. The location information may comprise at least one of asequence of locations, a range of locations, cell information, Global Navigation Satellite System (GNSS) co-ordinates, predicted arrival time at a location, predicted departure time from a location, or predicted time of stay at a location

[0185] The WTRU may monitor if the triggering conditions are fulfilled at step 410. A triggering condition may comprises any appropriate triggering condition. Triggering conditions may comprises at least one, or any appropriate combination, of the following as described herein. A triggering condition may be based on a confidence level of a prediction being greater than or equal to a threshold confidence level. A triggering condition may be based on a trajectory prediction being applicable for a duration of time after transmission of trajectory projection information. A triggering condition may be based on the WTRU being in a predetermined location during a predetermined duration of time. A triggering condition may be based on a location of the WTRU at a predetermined time differing by greater than a threshold distance compared to a previously reported trajectory for the predetermined time. A triggering condition may be based on at least one parameter of a projected trajectory differing by greater than a respective threshold amount compared to the at least one parameter of a previously reported trajectory.

[0186] At step 412, upon determining that the triggering conditions are fulfilled, WTRU may send / transmit a trajectory report or report update. The transmitted trajectory report may comprise trajectory prediction information. Transmitted predicted trajectory information may comprise a full trajectory report. Optionally, the full trajectory report may comprise an indication that the full trajectory report replaces a previous trajectory report. The transmitted trajectory update report may comprise an indication of a modification of a previous trajectory report. The modification of the previous trajectory report may comprise at least one of removal of a location that was indicated in the previous trajectory report, removal of a cell of a previous trajectory report, an addition of a location that was indicated in the previous trajectory report, an addition of a cell of a previous trajectory report, or a modification of time information associated with a location indicated in the previous trajectory report. The transmitted trajectory report may comprise trajectory prediction information comprising a trajectory update report comprising an indication of a modification of a previous trajectory report.

[0187] In one example, the WTRU may receive configuration information at step 404 without sending the WTRU’s prediction trajectory capabilities at step 402. In another example the WTRU may send the WTRU’s prediction trajectory capabilities at step 402 and receive configuration information at step 404.

[0188] Although features and elements are provided above in particular combinations, one of ordinary skill in the art will appreciate that each feature or element can be used alone or in any combination with the other features and elements. The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations may be made without departing from its spirit and scope, as will be apparent to those skilled in the art. No element, act, or instruction used in the description of the present application should be construed as critical or essential to the invention unless explicitly provided as such. Functionally equivalent methods, apparatuses, and articles of manufacture, within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims.

[0189] In addition, methods provided herein may be implemented in a computer program, software, or firmware incorporated in a computer-readable medium for execution by a computer or processor. Examples of computer-readable media include electronic signals (transmitted over wired or wireless connections) and computer-readable storage media (which do not include transitory signals). Examples of computer-readable storage media, which are differentiated from signals, may include, but are not limited to, a read only memory (ROM), a random access memory (RAM), a register, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks, and digital versatile disks (DVDs). A processor in association with software may be used to implement a radio frequency transceiver for use in a WTRU, UE, terminal, base station, RNC, or any host computer.

[0190] In an illustrative embodiment, any of the operations, processes, etc. described herein may be implemented as computer-readable instructions stored on a computer-readable storage medium. The computer-readable instructions may be executed by a processor of a mobile unit, a network element, and / or any other computing device.

Claims

CLAIMSWhat is claimed is:1 . A wireless transmit / receive unit (WTRU) comprising: a transceiver; and a processor configured to: receive a trajectory prediction configuration, wherein the trajectory prediction configuration is related to performing trajectory prediction and reporting predicted trajectory information, and wherein the trajectory prediction configuration comprises at least one triggering condition for reporting predicted trajectory information; perform a trajectory prediction in accordance with the received trajectory prediction configuration; determine predicted trajectory information based on the performance of the trajectory prediction; determine that a triggering condition of the at least one triggering condition is fulfilled; and based on the at least one triggering condition being fulfilled, transmit the determined predicted trajectory information.

2. The WTRU of claim 1 , wherein the trajectory prediction configuration comprises an indication of at least one prediction model.

3. The WTRU of claim 1 , wherein the processor is configured to transmit to a network a capability of the WTRU associated with trajectory prediction.

4. The WTRU of claim 1 , wherein the predicted trajectory information comprises location information.

5. The WTRU of claim 4, wherein the location information comprises at least one of: a sequence of locations; a range of locations; cell information;Global Navigation Satellite System (GNSS) co-ordinates; predicted arrival time at a location; predicted departure time from a location; or predicted time of stay at a location.

6. The WTRU of claim 1 , wherein the transmitted predicted trajectory information comprises one of a full trajectory report or an update trajectory report.

7. The WTRU of claim 1 , wherein: the transmitted predicted trajectory information comprises a trajectory update report; and the trajectory update report comprises an indication of a modification of a previous trajectory report.

8. The WTRU of claim 7, wherein the modification of the previous trajectory report comprises at least one of: removal of a location that was indicated in the previous trajectory report; addition of a location that was indicated in the previous trajectory report; or a modification of time information associated with a location indicated in the previous trajectory report.

9. The WTRU of claim 1 , wherein the at least one triggering condition is based on a confidence level of a prediction being greater than or equal to a threshold confidence level.

10. The WTRU of claim 1 , wherein the at least one triggering condition is based on a trajectory prediction being applicable for a duration of time after transmission of trajectory projection information.11 . The WTRU of claim 1 , wherein the at least one triggering condition is based on the WTRU being in a predetermined location during a predetermined duration of time.

12. The WTRU of claim 1, wherein the at least one triggering condition is based on a location of the WTRU at a predetermined time differing by greater than a threshold distance compared to a previously reported trajectory for the predetermined time.

13. The WTRU of claim 1 , wherein the at least one triggering condition is based on at least one parameter of a projected trajectory differing by greater than a respective threshold amount compared to the at least one parameter of a previously reported trajectory.

14. The WTRU of claim 1 , wherein the trajectory prediction configuration is related to determining a trajectory based on measurements.

15. The WTRU of claim 1 , wherein the trajectory prediction configuration is related to performing trajectory prediction based on at least one of measurement time duration, filter coefficients for consolidating past and current measurements, measurement sampling intervals, or beam consolidation thresholds for cell level measurement calculations.

16. The WTRU of claim 1 , wherein the trajectory prediction configuration is related to performing trajectory prediction based on artificial intelligence or machine learning model training.

17. The WTRU of claim 1 , wherein the trajectory prediction configuration is related to reporting predicted trajectory information based on timing associated with transmission of a predicted trajectory report.

18. The WTRU of claim 1 , wherein the trajectory prediction configuration is related to reporting predicted trajectory information based on prohibiting a predicted trajectory report.

19. A method performed by a wireless transmit / receive unit (WTRU) comprising: receiving a trajectory prediction configuration, wherein the trajectory prediction configuration is related to performing trajectory prediction and reporting predicted trajectory information, and wherein the trajectory prediction configuration comprises at least one triggering condition for reporting predicted trajectory information; performing a trajectory prediction in accordance with the received trajectory prediction configuration; determining predicted trajectory information based on the performance of the trajectory prediction; determining that a triggering condition of the at least one triggering condition is fulfilled; and based on the at least one triggering condition being fulfilled, transmitting the determined predicted trajectory information.

20. The method of claim 19, wherein the trajectory prediction configuration comprises an indication of at least one prediction model.

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