Methods to support ai / ML assisted measurement gap configuration adaptation

Abstract

A WTRU may receive a configuration for measurement gap adaptation associated with an AI / ML model. The configuration may be configured to modify one or more characteristics of a measurement gap configuration. The WTRU may receive an indication to evaluate an AI / ML prediction performance associated with the measurement gap configuration. In response to the indication, the WTRU may evaluate the AI / ML prediction performance associated with the measurement gap configuration. The WTRU may adapt the one or more characteristics of the measurement gap configuration.

Description

METHODS TO SUPPORT AI / ML ASSISTED MEASUREMENT GAP CONFIGURATION ADAPTATIONCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority from Provisional U.S. Patent Application No. 63 / 679,438, filed August 5, 2024, the entire disclosure of which is hereby incorporated by reference herein in its entirety.BACKGROUND

[0002] In existing L3 handover mechanisms, handover may be triggered and executed based on reported historical measurement result(s) and / or measurement event(s) (e.g., handover may be a reactive scheme by its nature). Handover may work well among macro cells when a WTRU’s mobility is low for existing services. But handover may be problematic when either WTRU’s mobility is high or among micro cells of high density, or both for existing services or future services, such as XR, where such reactive scheme(s) may result in more unintended events, such as handover failure, radio link failure, Ping-Pong phenomenon, throughput loss or too early / late handover, etc. To improve handover robustness conditional handover may be performed. And to reduce interruption time of frequency handover among small cells LTM HO may be implemented. However, these mechanisms may not sufficient because they may be reactive schemes by design. On the other hand, mechanisms based on AI / ML algorithm(s) may enable proactive schemes.SUMMARY

[0003] A WTRU may receive a configuration for measurement gap adaptation associated with an AI / ML model. The configuration may be configured to modify one or more characteristics of a measurement gap configuration. The one or more characteristics of a measurement gap configuration may comprise a gap length or a periodicity. The WTRU may receive an indication to evaluate an AI / ML prediction performance associated with the measurement gap configuration. In response to the indication, the WTRU may evaluate the AI / ML prediction performance associated with the measurement gap configuration. The WTRU may adapt the one or more characteristics of the measurement gap configuration. The adaptation may include increasing or decreasing a size or number of measurement gaps. The WTRU may receive a network verification prior to performing the adaptation of the one or more characteristics of the measurement gap configuration.

[0004] A wireless transmit / receive unit (WTRU) may include a processor that is configured to receive a first measurement gap configuration, a second measurement gap configuration, and activation criteria associated with the second measurement gap configuration. The second measurement gap configurationmay be associated with an artificial intelligence or machine learning (AI / ML) model. The WTRU may be configured to perform a first plurality of measurements based on the first measurement gap configuration. The WTRU may be configured to determine that the activation criteria has been satisfied based on the first plurality of measurements. The WTRU may be configured to send, based on the determination that the activation criteria has been satisfied, an indication to a network device that the second measurement gap configuration will be applied. The WTRU may be configured to perform a second plurality of measurements based on the second measurement gap configuration.

[0005] In some examples, the activation criteria comprises a threshold value. The WTRU may be configured to determine that the activation criteria has been satisfied based on predicted measurements of the AI / ML model, the first plurality of measurements, and / or the threshold value (e.g., delta different being within a margin). For example, the WTRU may determine that the activation criteria has been satisfied based on a comparison between predicted measurements of the AI / ML model and the first plurality of measurements being below the threshold value.

[0006] In some examples, the WTRU may be configured to receive prediction evaluation criteria (e.g., an evaluation period, performance margin, etc.), and determine that the activation criteria or the deactivation criteria has been satisfied based on the prediction evaluation criteria (e.g., during the evaluation period).

[0007] The indication may include an indication of an overlap between the second measurement gap configuration with one or more schedule uplink transmissions or downlink transmission. In some examples, the WTRU may be configured to receive a confirmation from the network device to apply the second measurement gap configuration.

[0008] In some examples, the WTRU may be configured to receive deactivation criteria associated with the second measurement gap configuration, perform a third plurality of measurements based on the second measurement gap configuration, determine that the deactivation criteria has been satisfied based on the third plurality of measurements, send, based on the determination that the deactivation criteria has been satisfied, a deactivation indication to the network device that the first measurement gap configuration will be applied, and perform a fourth plurality of measurements based on the first measurement gap configuration.

[0009] The second measurement gap configuration may be defined by shorter measurement gaps or less measurement gaps than the first measurement gap configuration. In such examples, the WTRU may be configured to send a scheduling request (SR), activate a configured grant (CG), activate a Semi-persistent scheduling (SPS) configuration, and / or monitor a PDCCH transmission.

[0010] The second measurement gap configuration is defined by longer measurement gaps or more measurement gaps than the first measurement gap configuration. In such examples, the WTRU may be configured to discard uplink data, flush a Hybrid Automatic Repeat Request (HARQ) buffer, deactivate an SPS configuration, and / or deactivate aCG configuration.BRIEF DESCRIPTION OF THE DRAWINGS

[0011] FIG. 1 A is a system diagram illustrating an example communications system in which one or more disclosed embodiments may be implemented.

[0012] FIG. 1 B is a system diagram illustrating an example wireless transmit / receive unit (WTRU) that may be used within the communications system illustrated in FIG. 1A according to an embodiment.

[0013] FIG. 1C is a 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.

[0014] FIG. 1 D is a 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.DETAILED DESCRIPTION

[0015] ABBREVIATIONS AND ACRONYMSACK AcknowledgementBLER Block Error RateBWP Bandwidth PartCAP Channel Access PriorityCAPC Channel access priority classCCA Clear Channel AssessmentCCE Control Channel ElementCE Control ElementCG Configured grant or cell groupCP Cyclic PrefixCP-OFDM Conventional OFDM (relying on cyclic prefix)CQI Channel Quality IndicatorCRC Cyclic Redundancy CheckCSI Channel State InformationCW Contention WindowCWS Contention Window SizeCO Channel OccupancyDAI Downlink Assignment IndexDCI Downlink Control InformationDFI Downlink feedback informationDG Dynamic grantDL DownlinkDM-RS Demodulation Reference Signal DRB Data Radio Bearer eLAA enhanced Licensed Assisted AccessFeLAA Further enhanced Licensed Assisted AccessHARQ Hybrid Automatic Repeat RequestLAA License Assisted AccessLBT Listen-Before-TalkLTE Long Term Evolution e.g. from 3GPP LTE R8 and upNACK Negative ACKMCS Modulation and Coding SchemeMIMO Multiple Input Multiple OutputNR New RadioOFDM Orthogonal Frequency-Division Multiplexing PHY Physical LayerPID Process IDPO Paging OccasionPRACH Physical Random Access Channel PSS Primary Synchronization SignalRA Random Access (or procedure)RACH Random Access ChannelRAR Random Access ResponseRCU Radio access network Central UnitRF Radio Front endRLF Radio Link FailureRLM Radio Link MonitoringRNTI Radio Network IdentifierRO RACH occasionRRC Radio Resource ControlRRM Radio Resource ManagementRS Reference SignalRSRP Reference Signal Received PowerRSSI Received Signal Strength IndicatorSDU Service Data UnitSRS Sounding Reference SignalSS Synchronization SignalSSS Secondary Synchronization SignalSWG Switching Gap (in a self-contained subframe)SPS Semi-persistent schedulingSUL Supplemental UplinkTB Transport BlockTBS T ransport Block SizeTRP Transmission / Reception PointTSC Time-sensitive communicationsTSN Time-sensitive networkingUL UplinkURLLC Ultra-Reliable and Low Latency CommunicationsWBWP Wide Bandwidth PartWLAN Wireless Local Area Networks and related technologies (IEEE 8O2.xx domain)

[0016] 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 systems 100 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.

[0017] As shown in FIG. 1A, 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 WTRU.

[0018] 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 communicationnetworks, 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 be appreciated that the base stations 114a, 114b may include any number of interconnected base stations and / or network elements.

[0019] 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.

[0020] 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).

[0021] 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).

[0022] I n 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).

[0023] I n 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).

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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 tolerance requirements, 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.

[0028] 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.

[0029] 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.

[0030] 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 / receive 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 peripherals138, 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.

[0031] 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.

[0032] 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.

[0033] Although the transmit / receive element 122 is depicted in FIG. 1 B 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.

[0034] 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.

[0035] 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).

[0036] 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.

[0037] 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.

[0038] 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, anaccelerometer, a hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature 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.

[0039] 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 WRTU 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)).

[0040] FIG. 1C 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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 forauthenticating users of the WTRUs 102a, 102b, 102c, bearer activation / deactivation, selecting a particular serving gateway during an initial attach 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.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] Although the WTRU is described in FIGS. 1 A-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.

[0049] In representative embodiments, the other network 112 may be a WLAN.

[0050] 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 an access or an interface to a Distribution System (DS) or another type of wired / wireless network that carries traffic in to and / or out of the 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 thedestination STA. The traffic between ST As 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.

[0051] When using the 802.11 ac 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 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.

[0052] 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.

[0053] Very High Throughput (VHT) STAs may support 20MHz, 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 MHz channels, 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).

[0054] 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, and802.11ac. 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).

[0055] WLAN systems, which may support multiple channels, and channel bandwidths, such as 802.11 n, 802.11 ac, 802.11 af, 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 ST A, 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.

[0056] 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.

[0057] 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 the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 113 may also be in communication with the CN 115.

[0058] 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 MIMOtechnology. For example, gNBs 180a, 108b 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).

[0059] 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).

[0060] 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 to communicate 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.

[0061] 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.

[0062] 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.

[0063] 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 access technologies such as WiFi.

[0064] 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 of traffic 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.

[0065] 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 forwardingpackets, enforcing user plane policies, supporting multi-homed PDU sessions, handling user plane QoS, buffering downlink packets, providing mobility anchoring, and the like.

[0066] The CN 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.

[0067] In view of Figures 1A-1 D, and the corresponding description of Figures 1A-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-ab, 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.

[0068] 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, functions while 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 performing testing using over-the-air wireless communications.

[0069] 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 / orwireless 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.

[0070] Physical layer centric use cases may be implemented that include spatial and temporal beam prediction. Temporal prediction within serving cell may be implemented to predict the best or top-K beam(s) or beam pair(s) in the time domain in order to improve WTRU throughput. Predicting the best ortop-K beam(s) or beam pair(s) among a set of beams by measuring a smaller set of beams may help reduce RS signaling overhead, measurement efforts and WTRU power consumption, etc. By extended L1 beam measurement from serving cell to neighboring cell, a majority of the RAN1 work may be reused (e.g., LTM HO study). AI / ML for air may be leveraged for mobility purpose (e.g., temporal prediction may also be used to predict beam(s) / cell(s) becoming worse so that unintended events like radio link failure or short-stay handover may be avoided), since L3 measurement is based on filtering of L1 measurement.

[0071] Mobility enhancement may be based on information available on the network side, for example handover and stay of time in history among cells to predict WTRU’s trajectory in single hop and hence potential candidates. A WTRU’s trajectory for multiple hops may be predicted for AI / ML mobility over air interface.

[0072] Radio resource management (RRM) measurements and / or events may be predicted and hence candidate target cell(s) may be predicted on the WTRU side. On the network side, assistant information, if necessary, and statistics information based on measurement report(s) from WTRU and / or neighboring nodes may be also used for smart prediction. Handover and / or RRM performance may be improved by proactive measures to either make a better decision(s) or avoid unintended event(s) if some prediction information is known by the network.

[0073] Measurement gaps may be used in NR to temporarily suspend transmission and data reception to allow the WTRU to perform measurements such as for RRM or positioning purposes. The WTRU may use a measurement gap to measure, for example, an RS in a different frequency (e.g., inter frequency measurements) or in a different bandwidth part (BWP) which may require BWP switching.

[0074] Whether a measurement is non-gap-assisted or gap-assisted may depend on the capability of the WTRU, the active BWP of the WTRU, and / or the current operating frequency. The WTRU may report various capabilities regarding measurement gap requirements (e.g., support for UL gaps in FR1 / FR2, supported gap patterns, whether FR1 / FR2 gaps may be independently configured, etc.). The WTRU may further indicate via RRC whether a measurement gap is needed for a particular frequency (e.g., via the IE needforgap).

[0075] Based on the WTRU capability information and network (NW) deployment characteristics (e.g., the SMTC and reference signals for the neighboring carrier), the network may configure one or more measurement gaps via the IE measGapConfig, which may include information like the gap ID, gap length, gap type, applicable frequencies, etc.

[0076] During a measurement gap, the WTRU may perform actions (e.g., retuning) needed to perform the measurements. The WTRU may not report / transmit HARQ, SR, SRS, CSI, UL_SCH, nor monitor PDCCH and / or receive on DL-SCH.

[0077] Measurement gaps may be configured based on WTRU capability and RRC indication, which may be semi-statical ly reported during connection set-up. During measurement gaps, the ability for the WTRU to perform most procedures (e.g., data transmission and / or reception, scheduling, monitoring, etc.) may be limited, which may affect throughput.

[0078] If a WTRU is able to accurately predict measurements via AI / L, then a measurement gap may not be needed to perform the measurement (or characteristics of the gap like the length may be shortened). Alternatively, if the AI / ML prediction is inaccurate, the WTRU may need additional measurement gaps, in which case the existing scheduling may need to be revised. If the WTRU is performing redundant measurements when the AI / ML predictions are satisfactory the system throughput may be negatively affected. If the WTRU has too few gaps which may not be compensated for by AI / ML (e.g., due to lack of model / functionality performance), then the system robustness may be impacted (e.g., the WTRU may perform incorrect mobility actions, or trigger radio link failure (RLF)).

[0079] There may be challenges with updating the measurement gap capabilities, or dynamically indicating the need and / or not need for one. AI / ML RRM predictions may be implemented, for example.

[0080] Described herein are methods that may support AI / ML assisted measurement gap configuration adaptation that may maximize throughput / scheduling efficiency while still satisfying measurement requirements.

[0081] A WTRU may apply a second measurement gap configuration as a function of measurement prediction performance. If the prediction performance exceeds a threshold, WTRU may apply a measurement gap configuration with fewer gaps.

[0082] A WTRU may receive a first and second measurement gap configuration. A measurement gap configuration may include one or more of the following: measGapConfig (e.g., a gap ID, gap length, gap type, applicable frequencies, etc.) (de)activation criteria; prediction evaluation criteria (e.g., criteria to trigger a prediction evaluation, a duration of evaluation, a performance margin, etc.).

[0083] The WTRU may apply a first measurement gap configuration and / or may monitor the activation criteria of the second measurement gap configuration. Activation criteria may include one or more of the following: (de)activation of an AI / ML model; performance of an AI / ML model exceeds / falls below a threshold.

[0084] The WTRU may determine that the activation criteria for a second measurement gap configuration is satisfied. The WTRU may verify the activation of the second measurement gap configuration during an evaluation period (e.g., via prediction evaluation criteria that may be included within the measurement gap configuration). An example of prediction evaluation may include, for example, when the WTRU predicts and performs measurements for an evaluation period. The prediction evaluation criteria may be successful if the delta difference between the predicted and acquired measurement is within a configured margin.

[0085] The WTRU may notify the network that a second measurement gap configuration may be applied if the associated activation criteria (e.g., and prediction evaluation criteria, if configured) is satisfied. A network indication may include a revised measurement configuration which may have been applied. A network indication may include an indication of overlap of a new measurement gap with one or more scheduled UL (re)transmissions or DL receptions.

[0086] The WTRU may receive a confirmation from the network to apply the gap. If the WTRU does not receive response after timeout, the WTRU may apply the gap, etc. The WTRU may apply the second measurement gap configuration. If a measurement gap within the second measurement gap configuration overlaps in time with a scheduled UL (re)transmission or DL reception, the WTRU may perform one or more of the following: send a SR; flush HARQ buffers associated with the transmission; discard or cancel the UL (re)transmission; not receive a DL transmission; and / or not monitor PDCCH.

[0087] Embodiments are described herein for improved throughput by reducing the time a WTRU may suspend UL transmission and / or DL reception to perform unnecessary measurements when measurement prediction may be performing well. Examples described herein may support measurement gap adaptation which may be based on configuration and performance of an AL / ML model and / or functionality. Examples may involve one or more of the following example components (or subcomponents) described herein.

[0088] Throughout the examples described herein, the following terminology may be used. Measurement gap adaptation may refer to any change and / or modification to a current measurement gap configuration and / or the use of measurement gaps within an existing configuration. Examples of such adaptations are described herein. Examples of such adaptations may include skipping, adding, removing, or modifying the characteristics of one or more measurement gap(s). Baseline measurement gap configuration may refer toa measurement gap configuration which may be considered in a non adapted state. For example, the WTRU may not use any configuration and / or values within a configuration that may be associated with an adaptation criteria being met. Adapted measurement gap configuration may refer to a measurement gap configuration or values within a measurement gap configuration which may be different from the baseline measurement gap configuration. Such configurations and / or values may only apply, for example, when an adaptation criteria may have been met, and / or for a configured time period.

[0089] Throughout the examples described herein, the following principles and observations may be applied. Methods for evaluating AL / ML model and / or functionality prediction quality may be equivalent to AL / ML performance monitoring.

[0090] Examples are described herein for configuration and assistance information. The WTRU may be provided with one or more configuration(s) to support measurement gap adaptation. Configurations to support measurement gap adaptation may include configurations for one or more measurement gap(s) and / or configurations for one or more AI / ML models / fu nctionalities.

[0091] Measurement gap and AI / ML model and / or functionality configurations may be independently configured (e.g., there may not be dependency between configurations, and the WTRU may independently apply / remove configurations) or jointly configured (e.g., the two configurations may be linked and both configurations may be jointly applied and / or removed, wherein the application / removal of one configuration may imply the application / removal of the other configuration).

[0092] The examples may support both the initial measurement gap configuration, alternative measurement gap configurations, methods to adapt measurement gap configurations including associated criteria, and / or configurations to evaluate / verify measurement gap adaptation.

[0093] In some examples described herein, the WTRU may adapt a measurement gap configuration. Aspects of measurement gap adaptation such as whether the measurement gap may be adapted, how the measurement gap may be adapted, criteria to adapt measurement gap, and management of multiple measurement gaps may, in themselves, be configured. Appropriate configuration of measurement gap adaptation may ensure that the WTRU behavior may be controlled and the WTRU and network may be aligned on when the WTRU may be performing measurement gaps.

[0094] In some examples described herein, the WTRU may be provided with one or more measurement gap configuration(s). The WTRU may receive one or more measurement gap configuration(s) as part of an RRC connection establishment or resume, or during an RRC connection. The WTRU may receive multiple (e.g., more than one) measurement gap configurations at once, or the WTRU may modify, add, and / orremove one or more measurement gap configuration(s) throughout an RRC connection (e.g., via the gapToReleaseList or gapToAddModList).

[0095] A measurement gap configuration may have an associated configuration (e.g., provided by measGapConfig) that may include one or more information elements. For example, the measurement gap configuration may have an associated configuration that includes a measGapId information element, which may indicate the ID of a measurement gap configuration. The measurement gap configuration may have an associated configuration that includes a gapType information element, which may indicate whether the gap applies to FR1, FR2, or both. The measurement gap configuration may have an associated configuration that includes a gapOffset information element, which may indicate the gap offset of the gap pattern with MGRP that may be indicated in the field mgrp. The measurement gap configuration may have an associated configuration that includes an mgl information element, which may indicate the measurement gap length in ms of the measurement gap. The measurement gap configuration may have an associated configuration that includes an mgrp information element, which may indicate the measurement gap repetition period in ms. The measurement gap configuration may have an associated configuration that includes an mgta information element, which may indicate the measurement gap timing advance in ms. The measurement gap configuration may have an associated configuration that includes a refServCelll ndicator information element, which may indicate the serving cell whose SFN and subframe are used for gap calculation for this gap pattern. The measurement gap configuration may have an associated configuration that includes a preConfigl nd information element, which may indicate whether the measurement gap may be a pre-configured measurement gap. The measurement gap configuration may have an associated configuration that includes a gapSharing information element, which may indicate the measurement gap sharing scheme. The measurement gap configuration may have an associated configuration that includes a gapPriority information element, which may indicate the priority of this measurement gap.

[0096] In some examples described herein, additional configurations to support measurement gap adaptation (e.g., adaptation criteria, measurement gap skipping, temporary modification of a measurement gap) may be provided within a measurement gap configuration, and / or as part of a separate configuration which may be linked to a measurement gap configuration (e.g., by indication of the associated measurement gap ID). If the WTRU receives a measurement gap configuration without such additional adaptation configuration(s), the WTRU may require explicit (de)configuration by the network (e.g., via RRC or MAC CE signaling) to adapt a measurement gap configuration.

[0097] The measurement gap configuration may include a different set of values (e.g., one or more values of the measurement gap configuration), which for example, may be applied if and / or while the measurement gap is in an adapted state (e.g., if adaptation criteria are satisfied, while adaptation criteria are satisfied, and / or during a time period that may be indicated within an adaptation criteria). The values within the measurement gap configuration which the WTRU may apply while the measurement gap may not be adapted may be referred to as the baseline measurement configuration. The values applied while the measurement gap configuration may be in an adapted state may be the adapted measurement gap configuration.

[0098] The network may provide, update, modify, remove, add, or indicate all or part of a measurement gap configuration and / or configurations to support measurement gap adaptation (e.g., criteria, methods, alternative values, time periods, etc.) via RRC signaling (e.g., RRC Setup, RRC Resume) or via one or more of the following signaling methods: MAC CE, DCI, RACH (e.g., MSG2, MSG4, MSGB), PDCCH / PUSCH or NAS.

[0099] Embodiments are described herein for adaptation of the measurement gap configuration. The WTRU may receive a configuration to support adaptation of one or more measurement gap configuration(s). In some examples, an adaptation configuration may include one or more criteria wherein if the configured criteria are satisfied the WTRU may adapt the measurement gap. For example, adaptation criteria for a measurement gap configuration may be linked to performance monitoring. Adaptation criteria for a measurement gap configuration may be linked to cell quality. Adaptation criteria for a measurement gap configuration may be linked to measurement relaxation criteria (e.g., within cell edge, stationary criteria, etc.).

[0100] In some examples described herein, the WTRU may receive a configuration to perform measurement gap skipping. A measurement gap skipping configuration may support, enable, and / or instruct the WTRU not to perform measurements within one or more measurement gaps of a measurement gap configuration. For example, a configuration for measurement gap skipping may include one or more pieces of information. The configuration for measurement gap skipping may include: an indication of whether the skipping applies to one gap; whether the skipping applies to multiple measurement gaps; the number of measurement gaps skipping may apply to; a time to start skipping gaps; a time to end skipping gaps; a duration (e.g., time period) to skip gaps; and / or associated adaptation criteria that may trigger measurement gap skipping (e.g., as described herein).

[0101] In some examples, the WTRU may receive a configuration to temporarily modify one or more measurement gap(s). The WTRU may receive a configuration to determine how long the WTRU may apply the temporary measurement gap configuration adaptation. For example, the temporary measurement gap configuration may include one or more of the start times of the modification, the end time of the modification, and / or a duration of a modification.

[0102] During the duration of the modification period, the WTRU may adapt aspect(s) of the measurement gap configuration. Configurations to support such temporary modification may include, for example, which components of the measurement configuration that may be adapted (e.g., length, offset, periodicity, etc.). Configurations to support such temporary modification may also include temporary values that may be applied for one or more aspects of the measurement gap configuration. Configurations to support such temporary modification may include how to adapt the measurement gap configuration, which may include, increasing the current configuration value (e.g., to the next value or a default value), decreasing the current configuration value (e.g., to a previous value or a default value), and / or applying a different value (e.g., a temporary value provided).

[0103] In some examples herein, the WTRU may be provided with one or more measurement gap configurations which may additionally include configurations to adapt the measurement gap configuration. In another example, the WTRU may be provided with a baseline measurement gap and one or more adapted measurement gap configurations.

[0104] Upon reception of one or more measurement gap configurations, and / or upon reception of a new / updated / modified measurement gap configuration, the WTRU may apply the measurement gap configurations, for example, according to one or more of the following principles described herein. For example, if the criteria for measurement gap adaptation are satisfied, the WTRU may apply the adapted measurement gap configuration. If the criteria for measurement gap adaptation are not satisfied, the WTRU may apply the baseline measurement gap configuration.

[0105] In another example, if multiple measurement gap configurations are provided, the network may indicate a baseline or default measurement gap configuration (e.g., via being explicitly provided by RRC) which may represent a gap configuration (e.g., a conservative gap configuration). The WTRU may apply the baseline measurement gap configuration, for example, upon completion of connection, if no adaptation criteria are satisfied, and / or upon reception of a network indication.

[0106] Examples are described herein for AI / ML model / functionality configurations. In some examples, measurement gap adaptation may rely on the capability, configuration, application, activation, and / orperformance of one or more AI / ML models and / or functionalities. Appropriate configuration and (de)activation of AI / ML model(s) and / or functionality(ies) and associated performance monitoring may therefore be important in measurement gap adaptation.

[0107] AI / ML configuration aspects for measurement gap adaptation are further described herein. In some examples, the WTRU may receive a configuration for Al / M L-supported measurement gap adaptation. The AI / ML configuration may be jointly configured with one or more measurement gap configurations, wherein the (de)activation of an AI / ML model / functionality or adapted measurement gap configuration may cause both the AI / ML model and associated measurement gap configuration to be jointly (de)activated. In another example, the AI / ML model / functionality and measurement gap configuration may be independently configured, and (de)activation of the adapted measurement gap configuration may be conditional (e.g., on the performance of the AI / ML model / functionality). An AI / ML model / functionality may be associated with one or more measurement gap configuration(s) (e.g., via indication of one or more measurement gap ID(s)). In another example, a measurement gap configuration may be associated with one or more AI / ML model / functionality(ies) (e.g., via indication of one or more AI / ML model I D(s) or AI / ML functionality I D(s)).

[0108] A WTRU may be configured with one or more AI / ML configuration aspects (e.g., to support measurement gap adaptation). These AI / ML configurations may include performance monitoring criteria (e.g., threshold(s) to adapt one or more associated measurement gap(s)). The AI / ML configuration may include activation and / or deactivation criteria (e.g., criteria to (de)activate one or more associated adapted measurement gap configurations). The AI / ML configuration may include time to trigger or hysteresis values to support criteria evaluation. The AI / ML configuration may include an association with one or more measurement gap configuration(s) (e.g., via a measurement gap ID).

[0109] The network may provide, update, modify, remove, add, or indicate all or part of an AI / ML configuration(s) that may support measurement gap adaptation (e.g., criteria, associations, etc.) via RRC signaling (e.g., RRC Setup, RRC Resume) or via one or more of the following signaling methods: MAC CE, DCI, RACH (e.g., MSG2, MSG4, MSGB), PDCCH / PUSCH, or NAS.

[0110] Examples are provided herein for prediction evaluation. In some examples, the WTRU may receive a configuration to evaluate, for example, whether the AI / ML model and / or functionality predictions may support an adaptation of a measurement gap configuration. A prediction evaluation configuration (e.g., for measurement gap adaptation) may include an indication (e.g., a flag or enable / disable indication) to perform prediction evaluation. The prediction evaluation configuration (e.g., for measurement gap adaptation) may include whether the performance monitoring may occur before, after, or both before andafter application of a measurement gap. The prediction evaluation configuration (e.g., for measurement gap adaptation) may include an offset to perform the prediction evaluation (e.g., before or after the measurement gap adaptation is applied). The prediction evaluation configuration (e.g., for measurement gap adaptation) may include a duration (e.g., time period) to perform the prediction evaluation. The prediction evaluation configuration (e.g., for measurement gap adaptation) may include a number of measurements. The WTRU may compare performed and predicted measurements. The prediction evaluation configuration (e.g., for measurement gap adaptation) may include criteria to trigger a prediction evaluation. The prediction evaluation configuration (e.g., for measurement gap adaptation) may include a periodicity to trigger a prediction evaluation. The prediction evaluation configuration (e.g., for measurement gap adaptation) may include an evaluation criteria for the prediction, for example: an accuracy value (e.g., the measurements and measurement prediction are 95% accurate), the number of measurements which may satisfy a criteria, and / or the ratio of measurements which may satisfy a criteria. The WTRU may be provided with a threshold or value, and if the comparison between the actual measurements and predicted measurements is below the threshold, the prediction may be satisfied.

[0111] Examples are provided herein for measurement gap adaptation. Throughout the examples herein, the WTRU may adapt the measurement gap configuration. For example, a WTRU may not need as many measurement gaps if AI / ML model and / or functionality may be sufficiently accurate to predict such measurements, allowing additional time for scheduling and improving overall throughput. A WTRU may also, or alternatively, require or use additional measurement gaps (e.g., if the performance of an AI / ML model degrades). Such additional measurement gaps may impact throughput but may support improved connection reliability and robustness.

[0112] Examples herein may support measurement gap adaptation, including methods of adaptation, criteria to apply adaptation, and methods to evaluate and / or verify the adaptation. Such examples may ensure that the WTRU may apply the appropriate measurement gap configuration at the correct time to maximize throughput while ensuring that necessary measurements may be performed to satisfy requirements and maintain a reliable connection.

[0113] Examples are provided herein for adaptation of the measurement gap configuration. In some examples herein, the WTRU may adapt the measurement gap configuration. Methods to adapt the measurement gap configuration may vary from dynamic (e.g., skipping a single measurement gap), to temporary (e.g., skipping or temporarily adjusting a set of measurement gap(s)), to semi-static (e.g., applying a different measurement gap configuration).

[0114] The WTRU may perform one or more methods to adapt a measurement gap, which may depend on one or more factors including configuration satisfaction of measurement criteria to adapt measurement gap configuration and / or network approval of measurement gap adaptation.

[0115] Examples are provided herein for measurement gap skipping and / or addition. In some examples herein, the WTRU may temporarily adapt a measurement gap configuration by skipping one or more measurement gap(s). In one example, the WTRU may perform one or more of the below actions indefinitely (e.g., the WTRU may skip the same measurement gap periodically). In another example, the WTRU may apply the above actions temporarily. The WTRU may determine duration to skip the measurement gap(s) and / or the number of measurement gap(s) affected by the temporary adaptation and / or perform the adaptation based on, for example: one or more of the number of gaps which fit inside a duration, the number of gaps that may be indicated within a configuration, upon satisfaction of an associated criteria, and / or while an associated criteria remains satisfied.

[0116] In some examples herein, the WTRU may temporarily adapt a measurement gap configuration by adding one or more measurement gap(s). In one example, the WTRU may perform one or more of the below actions indefinitely (e.g., the WTRU may add the same measurement gap periodically). In another solution, the WTRU may apply the below actions temporarily. The WTRU may determine duration to add the measurement gap(s) and / or the number of measurement gap(s) affected by the temporary adaptation and / or perform the adaptation based on, for example: one or more of the number of gaps that may be indicated within a configuration, upon satisfaction of an associated criteria, and / or while an associated criteria remains satisfied.

[0117] In another example, the WTRU may perform measurement gap skipping temporarily as a transition prior to applying a semi-static reconfiguration of a measurement gap configuration.

[0118] Embodiments are described herein for modification of measurement gap characteristics. In some examples herein, a WTRU may temporarily adapt one or more characteristics and / or one or more measurement gap(s) within a measurement gap configuration. The WTRU may adapt, for example: one or more measurement gap characteristics such as gap length (e.g., increase or decrease a measurement gap length), applicable frequencies (e.g., apply or remove a measurement gap for FR1 , FR2, or both), the gap periodicity (e.g., the WTRU may increase or decrease the gap periodicity), and / or the gap offset (e.g., the WTRU may extend or reduce the gap offset).

[0119] In one example, the WTRU may perform one or more of the above actions indefinitely. In another example, the WTRU may apply the above actions temporarily. The WTRU may determine duration to adaptthe measurement configuration and / or the number of measurement gap(s) affected by the temporary adaptation and / or perform the adaptation based on, for example: the number of gaps which may fit inside a duration; the number of gaps that may be indicated within a configuration; while an associated criteria remains satisfied.

[0120] Examples are provided herein for application of a revised measurement gap configuration. In one example the WTRU may be provided with more than one measurement gap configuration. The WTRU may apply a first measurement gap configuration, and, upon satisfaction of a criteria, may apply a second measurement gap configuration. Whether the WTRU applies more than one measurement gap configuration simultaneously may depend on, for example: whether the associated activation criteria are satisfied, and / or whether the WTRU may be configured to enable applications of multiple measurement configurations.

[0121] Criteria are described to adapt the measurement gap configuration. In some examples, the WTRU may adapt a measurement gap configuration based on satisfaction of the one or more criteria. Such criteria may be provided as part of the measurement gap configuration and / or may allow network control over adaptation of the measurement gap configuration. The WTRU may adapt measurement gap configurations when the conditions are appropriate to do so (e.g., performance of an AI / ML model and / or functionality is sufficient) by configuration of associated criteria.

[0122] Conditional measurement gap adaptation may be performed, as described herein. In some examples, the WTRU may be provided with one or more criteria to adapt a measurement gap configuration. Upon satisfaction of one or more criteria, the WTRU may apply the measurement gap configuration adaptation. The WTRU may continue to apply the measurement gap adaptation indefinitely once the criteria may be satisfied, until another criteria may be satisfied, and / or the WTRU may perform the measurement gap adaptation as long as the criteria are satisfied. Criteria to adapt a measurement gap configuration may include the performance of an AI / ML model and / or functionality exceeding a threshold. Criteria to adapt a measurement gap configuration may include the performance of an AI / ML model and / or functionality falling below a threshold. Criteria to adapt a measurement gap configuration may include the reference signal received power (RSRP) of a cell being above a threshold. Criteria to adapt a measurement gap configuration may include the RSRP of a cell being below a threshold.

[0123] (De)activation of a joint and / or linked configuration may be performed, as described herein. In some examples, the WTRU may adapt a measurement gap configuration based on an associated AI / ML model / functionality. The WTRU may adapt a measurement gap configuration based on (de)activation of anassociated AI / ML model and / or functionality. The WTRU may adapt a measurement gap configuration based on availability of an associated AI / ML model and / or functionality. The WTRU may adapt a measurement gap configuration based on lack of availability of an associated AI / ML model and / or functionality. The WTRU may adapt a measurement gap configuration based on capability of an associated AI / ML model and / or functionality. The WTRU may adapt a measurement gap configuration based on lack of capability of an associated AI / ML model / functionality.

[0124] Network requested and / or indicated measurement gap adaptation may be performed, as described herein. In some examples, the network may request and / or indicate that the WTRU may perform a measurement gap adaptation. The network request and / or indication may include one or more measurement gap I D(s). The network request and / or indication may include a request to activate one or more measurement gap configurations. The network request and / or indication may include a request to deactivate one or more measurement gap configurations. The network request and / or indication may include a request to modify one or more measurement gap configurations. The network request and / or indication may include a request to modify the configuration of one or more measurement gap configuration(s). The network request and / or indication may include a request to skip one or more measurement gap(s). The network request and / or indication may include a duration (e.g., time period) to perform the associated action(s). The network request and / or indication may include a number of measurement gap(s) to perform the associated action(s).

[0125] Upon receiving a network request for measurement gap adaptation, the WTRU may perform one or more of the indicated actions (e.g., (de)activate a measurement gap, skip one or more measurement gap(s), etc.) to one or more indicated measurement gap(s) (e.g., via the indication of one or more measurement gap IDs). Additional signaling may be introduced to support NW requested measurement gap adaptation. The NW may signal the request for measurement gap adaptation via one or more of the following signaling methods: MAC CE, DCI, RACH (e.g., MSG2, MSG4, MSGB), RRC, PDCCH / PUSCH.

[0126] Evaluation and / or verification of measurement gap adaptation may be performed, as described herein. Verification of an adaptation decision may ensure that measurement gap adaptation is performed based on reliable and verifiable predictions to avoid, for example, connection interruption and signaling overhead (e.g., required to revert an improper configuration).

[0127] In some examples, the WTRU may be configured to perform an additional evaluation / verification of predictions that may be used to adapt measurement gap configurations. Evaluation of the prediction qualitymay occur for a temporary period before and / or after the measurement gap configuration adaptation, based on a WTRU action, indication, or may be ongoing (e.g., periodically) after the gap adaptation.

[0128] Prediction quality may be evaluated, as described herein. In some examples, the WTRU may evaluate the quality of an AI / ML model and / or functionality prediction, for example, to ensure that a measurement gap adaptation may not impact the system performances. The prediction evaluation may be performed for one measurement, or over multiple (i.e. , more than two) measurements. The WTRU may, for example, perform the prediction evaluation over X measurements and / or over all measurements within a time period.

[0129] A WTRU may evaluate the quality of a prediction based on the difference between a performed and predicted measurement that may be above a threshold. A WTRU may evaluate the quality of a prediction based on the difference between a performed and predicted measurement being below a threshold. A WTRU may evaluate the quality of a prediction based on the difference between a performed and predicted measurement being within a range. A WTRU may evaluate the quality of a prediction based on the average difference between X performed and predicted measurements being above a threshold. A WTRU may evaluate the quality of a prediction based on the average difference between X performed and predicted measurements being below a threshold. A WTRU may evaluate the quality of a prediction based on the average difference between X performed and predicted measurements being within a range. A WTRU may evaluate the quality of a prediction based on the difference between the average of X performed measurements and the average of X predicted measurements being above a threshold. A WTRU may evaluate the quality of a prediction based on the difference between the average of X performed measurements and the average of X predicted measurements being below a threshold. A WTRU may evaluate the quality of a prediction based on the difference between the average of X performed measurements and the average of X predicted measurements being within a range. A WTRU may evaluate the quality of a prediction based on the average difference between performed and predicted measurement within a time period being above a threshold. A WTRU may evaluate the quality of a prediction based on the average difference between performed and predicted measurement being within a time period that is below a threshold. A WTRU may evaluate the quality of a prediction based on the average difference between performed and predicted measurement being within a time period within a range. A WTRU may evaluate the quality of a prediction based on the difference between the average of performed measurements within a time period and the average predicted measurement within a time period being above a threshold. A WTRU may evaluate the quality of a prediction based on the differencebetween the average of performed measurements within a time period and the average of predicted measurements within a time period being below a threshold. A WTRU may evaluate the quality of a prediction based on the difference between the average of performed measurements within a time period and the average of predicted measurements within a time period being within a range.

[0130] The evaluation or prediction quality may indicate that, for example, the quality of predictions is insufficient and the WTRU may require an adapted measurement gap configuration which may increase the number of measurements (e.g., via increasing the length of measurement gaps or via additional measurement gaps). In other examples, the evaluation may indicate that the quality of predictions is sufficient such that the WTRU may adapt the measurement gap configuration such that fewer measurements may be performed (e.g., via reducing the length of measurement gap(s) or removing measurement gap(s)).

[0131] The frequency of prediction quality may be evaluated, as described herein. A WTRU may trigger an evaluation of the prediction quality to ensure that adaptation to a measurement adaptation will not negatively impact the system performance. The WTRU may evaluate the prediction quality (e.g., once, based on an event, indication, or criteria, or on an ongoing basis). In some examples, the WTRU may trigger evaluation of the prediction quality based on a WTRU action. The WTRU may trigger evaluation of the prediction quality based on the activation of an AI / ML model and / or functionality. The WTRU may trigger evaluation of the prediction quality based on the deactivation of an AI / ML model and / or functionality. The WTRU may trigger evaluation of the prediction quality based on the adaptation of a measurement gap configuration. The WTRU may trigger evaluation of the prediction quality based on the activation of a measurement gap configuration. The WTRU may trigger evaluation of the prediction quality based on the deactivation of a measurement gap configuration. The WTRU may trigger evaluation of the prediction quality upon initiating RACH (e.g., upon transmission of MSG1 ). The WTRU may trigger evaluation of the prediction quality upon connection establishment (e.g., after transmission of an RRC establishment complete or resume complete message).

[0132] In some examples, the WTRU may evaluate the prediction quality based on one or more criteria. The WTRU may be configured with one or more prediction quality evaluation criteria, wherein satisfaction of one or more criteria may mean the WTRU may trigger an evaluation of the prediction quality. The WTRU may be configured with one or more prediction quality evaluation criteria, satisfaction of which may mean the WTRU may not trigger an evaluation of the prediction quality. The WTRU may or may not evaluate the prediction quality while the one or more criteria are satisfied. The criteria for prediction quality evaluationmay include if the performance of a model goes above a threshold, below a threshold, the RSRP of a cell goes above a threshold, and / or the RSRP of a cell goes below a threshold.

[0133] In another example, the WTRU may evaluate the prediction quality periodically. In one example, the WTRU may receive a configuration which may include, for example, a start or reference time / slot, an on duration, and / or an offset. The WTRU may perform performance monitoring during the on duration time period, and may not perform performance monitoring between subsequent on durations.

[0134] In another example, the WTRU may evaluate the prediction quality upon NW request. A NW request may include, for example, a dedicated evaluation configuration (e.g., performance requirements, evaluation times, etc.}. Upon completion of the prediction quality evaluation, the WTRU may, for example, report back to the network whether the performance is sufficient, insufficient, and / or other associated performance metrics.

[0135] Coordination between a WTRU and a network may be performed, as described herein.Coordination between a WTRU and Network regarding when the WTRU is applying a measurement gap may be important to ensure, for example, that the WTRU may not be currently in a measurement gap so it may transmit and / or receive according to scheduling. The network and WTRU may also be coordinated on when the WTRU may not be in a measurement gap, so that the WTRU may be appropriately scheduled to maximize throughput. Examples described herein support WTRU-network coordination regarding adaptations to the measurement gap configuration performed by the WTRU. This may ensure that the WTRU may be appropriately scheduled, and that a WTRU may receive and / or transmit on pre-existing scheduling.

[0136] Measurement gap adaptation may be coordinated between a WTRU and a network, as described herein. In some examples, the WTRU and network may exchange signaling regarding the measurement gap adaptation (e.g., a request / confirmation of measurement gap adaptation). Coordination between the WTRU and network may occur either before or after measurement gap adaptation and may be performed to ensure alignment between the WTRU and network regarding when the WTRU may be scheduled.

[0137] The NW may verify adaptation of measurement gap configuration, as described herein. In some examples, the WTRU may request and / or respond to confirmation by the network prior to adapting a measurement gap configuration. The measurement gap adaptation request may include, for example, an indication (e.g., a flag or bit) which may indicate the WTRU either wants to activate or deactivate a configuration and an associated measurement gap configuration ID.

[0138] A WTRU may trigger a confirmation request upon one or more measurement gap (de)activation criteria being satisfied. Upon reception of the WTRU request, the network may respond by acknowledging the WTRU’s request. Upon acknowledgment, the WTRU may apply the adapted measurement gap configuration and perform associated WTRU actions. Alternatively, or additionally, the network may reject the WTRU’s request for measurement gap adaptation. If the WTRU request is rejected the WTRU may continue with the current measurement gap configuration. The WTRU may send another adaptation request, for example, if a different criteria is satisfied. Alternatively, the WTRU may be prohibited from sending another measurement gap adaptation request (e.g., for a time period) if the network has rejected the measurement gap adaptation. Whether a WTRU request is sent prior to adaptation of a measurement gap configuration, or the WTRU performs one or more actions autonomously (e.g., as described below) may be based on network configuration.

[0139] Autonomous WTRU adaptation of measurement gap configuration may be performed, as described herein. In some examples, the WTRU may autonomously adapt the measurement configuration (e.g., without explicit confirmation from the network prior to measurement adaptation). Whether the WTRU may autonomously adapt measurement gap configuration may be based on configuration by the network. Whether the WTRU may autonomously adapt measurement gap configuration may be based on whether the WTRU may be adding or removing measurement gap occasions. Whether the WTRU may autonomously adapt measurement gap configuration may be based on whether the WTRU is increasing or decreasing the measurement gap length. Whether the WTRU may autonomously adapt measurement gap configuration may be based on one or more measurement gap (de)activation criteria being satisfied. Upon adaptation, the WTRU may still inform the network that adaptation has been performed. This may be performed, for example, to ensure that the WTRU may be scheduled during the proper time to maximize throughput while ensuring appropriate measurements are performed.

[0140] Signaling for coordination between a WTRU and a network may be performed, as described herein. In some examples, the WTRU and network may use existing signaling (e.g., RRC Reconfiguration) to adapt a measurement gap configuration. Alternatively, additional signaling may be defined to support interaction between the WTRU and network regarding coordination of measurement gap adaptation. Such signaling may be useful to ensure that the WTRU and network remain coordinated in an efficient and low- overhead manner.

[0141] The WTRU may request for measurement gap configuration adaptation, as described herein. The WTRU may signal the request for measurement gap adaptation via one or more of the following signalingmethods: RACH (e.g., MSG1 preamble selection, MSG3, MSGA), MAC CE, UCI, RRC signaling and / or PUSCH / PUCCH. In some examples, the WTRU may include additional information within the measurement gap adaptation request. The WTRU may include preferred gap configuration, updated capabilities, and / or updated needforGap. The WTRU may indicate a revised needforGap. The WTRU may indicate criteria which was satisfied. The WTRU may indicate the ID of the requested measurement gap configuration. Which signaling method is selected by the WTRU may depend on the information required to be transmitted. For example, if the WTRU is requesting an alternative configuration, the WTRU may send a request via RRC signaling. In another example, if the WTRU is requesting adaptation of a measurement gap configuration, it may send a MAC CE or UCI (e.g., including the measurement gap configuration ID and an indication of whether it wants to activate or deactivate the measurement gap).

[0142] A network response for measurement gap configuration adaptation may be performed, as described herein. Additional signaling may be introduced to support NW response to WTRU request for measurement gap adaptation. The NW may signal the response for measurement gap adaptation via one or more of the following signaling methods: MAC CE, DCI, RACH (e.g., MSG2, MSG4, MSGB), RRC, PDCCH / PUSCH. In some examples, the network may also include additional information within the measurement gap adaptation confirmation. The network may include an alternative measurement gap configuration to apply (e.g., via indication of a gap ID). The network may prohibit conditions before sending another activation request.

[0143] Measurement gap adaptation may have an impact on WTRU behavior. WTRU behavior may be impacted depending on, for example, whether adaptation of the measurement gap configuration requires additional time performing measurements (e.g., upon addition of measurement gaps or increase in existing measurement gap duration) or less time performing measurements (e.g., upon removal of measurement gaps and / or decrease in measurement gap length / duration). Impacts may include, for example, how the WTRU handles scheduling and / or scheduling requests and / or how the WTRU performs performance monitoring.

[0144] WTRU behavior may be modified to accommodate measurement gap adaptation, ensuring that aspects such as scheduling and performance monitoring may be revised to accommodate the adapted measurement gap(s).

[0145] Measurement gap adaptation may have an impact on WTRU behavior. In some examples, the WTRU may adapt the WTRU behavior depending on how the measurement gap is adapted. How WTRU behavior may change, for example, may depend on the method and duration of measurement gapadaptation, as well as whether the time allocated to measurement gaps is increasing (e.g., in length or via additional gaps) or decreasing (e.g., due to reduced length or fewer gaps).

[0146] Additional measurement gaps may adapt WTRU behavior. In some examples, adaptation of a measurement gap configuration may result in additional measurement gap duration (e.g., the length of one or more measurement gap(s) may be increased, or one or more measurement gap(s) are added). Such increased measurement gap time may interfere with existing scheduling (e.g., transmission(s) and / or reception(s)).

[0147] In one example, the WTRU may delay adapting the measurement gap configuration until scheduled transmissions and / or receptions are transmitted / received. This delay may include, for example, performing associated retransmissions until HARQ feedback has been received. In another solution, the delay may apply for initial transmission / reception.

[0148] In another example, the WTRU may discard UL signaling (e.g., if another gap is needed which interferes with existing scheduling). The WTRU may deactivate SPS / CG configurations which may overlap with other measurement gap(s). The WTRU may adjust timers / configurations (e.g., if DRX active time overlaps with other gap configurations). The WTRU may flush HARQ buffers that may be associated with scheduling.

[0149] In the case the other measurement gap adaptation interferes with a semi-statically configured scheduling (e.g., a configured grant configuration, semi-persistent scheduling, other periodic signals such as measurements or reference signals, or periodic actions such as DRX on durations), the WTRU may perform additional actions. For example, the WTRU may deactivate one or more interfering CG configurations. The WTRU may deactivate one or more interference SPS configurations. The WTRU may indicate to the NW that there may be an issue with other gap configurations (e.g., indicate that one or more semi-persistent schedule overlaps with another gap configuration, etc.).

[0150] In one example, the WTRU may apply one or more of the above actions upon acknowledgment from the network. In another example, the WTRU may perform one or more of the above actions autonomously. In another example, the WTRU assumes acknowledgment of the measurement gap adaptation by implicitly acknowledging one or more of the above actions.

[0151] WTRU behavior may be adjusted based on fewer measurement gaps. In some examples, adaptation of a measurement gap configuration may result in reduced measurement gap duration (e.g., the length of one or more measurement gap(s) may be decreased, one or more measurement gaps may be skipped, and / or one or more measurement gap(s) may be removed). Such decreased measurement gaptime may allow additional scheduling (e.g., transmission(s) and / or reception(s)). Upon adaptation of measurement gap configuration(s) which may reduce the time the WTRU may perform measurements, the WTRU may send an SR. Upon adaptation of measurement gap configuration(s) which may reduce the time the WTRU may perform measurements, the WTRU may send a BSR. Upon adaptation of measurement gap configuration(s) which may reduce the time the WTRU may perform measurements, the WTRU may monitor PDCCH. Upon adaptation of measurement gap configuration(s) which may reduce the time the WTRU may perform measurements, the WTRU may activate a CG configuration. Upon adaptation of measurement gap configuration(s) which may reduce the time the WTRU may perform measurements, the WTRU may activate an SPS configuration. Upon adaptation of measurement gap configuration(s) which may reduce the time the WTRU may perform measurements, the WTRU may measure an RS.

[0152] Whether the WTRU performs one or more of the above actions may depend on, for example: the magnitude of reduction in measurement time, whether the WTRU has buffered data, and / or upon approval or reconfiguration from the network.

[0153] Performance may be monitored upon measurement gap adaptation. In some examples, AI / ML performance may be impacted due to measurement gap adaptation. For example, additional samples to train / infer provided by additional measurements may improve or speed up AI / ML model training or improve inference. Alternatively, or additionally, fewer inputs caused by less time performing measurements may negatively impact performance or increase training time due to fewer measurements. The WTRU may therefore monitor or adapt AI / ML model / functionality performance based on the measurement gap configuration.

[0154] Examples are provided herein for performance monitoring with additional measurement gaps. In some examples, the availability of additional measurements caused by measurement gap adaptation (e.g., based on an increased length of one or more measurement gap(s) or the addition of one or more additional measurement gap(s)) may impact the performance monitoring and / or prediction evaluation of an AI / ML model / functionality. For example, upon measurement adaptation which may increase the amount of measurements, the WTRU may reduce and / or indicate that the training time of a model may be reduced. Upon measurement adaptation which increases the amount of measurements, the WTRU may increase and / or indicate that more data may be collected (e.g., for the purposes of data collection). Upon measurement adaptation which increases the amount of measurements, the WTRU may indicate that one or more AI / ML functionality(ies) and / or model(s) may be applicable. Upon measurement adaptation which increases the amount of measurements, the WTRU may indicate that one or more AI / ML functionality(ies)and / or model(s) may be available. Upon measurement adaptation which increases the amount of measurements, the WTRU may indicate that the WTRU may be capable of one or more AI / ML functionality(ies) and / or model(s). Upon measurement adaptation which increases the amount of measurements, the WTRU may modify the performance monitoring and / or prediction evaluation (e.g., modify threshold, number of samples, number of measurements needed to average, duration of evaluation period).

[0155] Examples are provided herein for performance monitoring with fewer measurement gaps. In some examples, the availability of additional measurements caused by measurement gap adaptation (e.g., based on an increased length of one or more measurement gap(s) or the addition of one or more additional measurement gap(s)) may impact the performance monitoring and / or prediction evaluation of an AI / ML model / functional ity . For example, upon measurement adaptation which may increase the amount of measurements, the WTRU may increase and / or indicate that the training time of a model may increase. Upon measurement adaptation which may increase the amount of measurements, the WTRU may decrease and / or indicate that less data may be collected (e.g., for the purposes of data collection). Upon measurement adaptation which may increase the amount of measurements, the WTRU may indicate that one or more AI / ML functionality(ies) and / or models may not be applicable. Upon measurement adaptation which may increase the amount of measurements, the WTRU may indicate that one or more AI / ML functionality(ies) and / or models may not be available. Upon measurement adaptation which may increase the amount of measurements, the WTRU may indicate that the WTRU may not be capable of one or more AI / ML functionality(ies) and / or model(s). Upon measurement adaptation which may increase the amount of measurements, the WTRU may modify the performance monitoring and / or prediction evaluation (e.g., modify thresholds, number of samples, number of measurements needed to average, duration of evaluation period).

[0156] Examples of a second measurement gap configuration are described herein. A WTRU may apply a second measurement gap configuration as a function of measurement prediction performance. If the prediction performance exceeds a threshold, the WTRU may apply a measurement gap configuration with fewer gaps.

[0157] A WTRU may receive a first and second measurement gap configuration. A measurement gap configuration may include measGapConfig (e.g., a gap ID, gap length, gap type, applicable frequencies, etc.). A measurement gap configuration may include (de)activation criteria. A measurement gapconfiguration may include prediction evaluation criteria e.g., criteria to trigger a prediction evaluation, a duration of evaluation, a performance margin, etc.).

[0158] The WTRU may apply a first measurement gap configuration and may monitor the activation criteria of the second measurement gap configurations. Activation criteria may include (de)activation of an AI / ML model. Activation criteria may include performance of an AI / ML model exceeding / falling below a threshold. The WTRU may determine that the activation criteria for a second measurement gap configuration is satisfied. The WTRU may verify the activation of the second measurement gap configuration during an evaluation period (e.g., prediction evaluation criteria may be included within the measurement gap configuration). A prediction evaluation may include the WTRU predicting and performing measurements for an evaluation period. If the delta difference between the predicted and acquired measurement is within a configured margin, the prediction evaluation criteria may be successful.

[0159] The WTRU may notify the network that a second measurement gap configuration may be applied if the associated activation criteria (and prediction evaluation criteria, if configured) is satisfied. A network indication may include a revised measurement configuration to be or that has been applied. A network indication may include indication of overlap of another measurement gap with one or more schedule UL (re)transmissions or DL receptions. The WTRU may receive a confirmation from the network to apply the gap or if the WTRU does not receive response after timeout, applies gap.

[0160] The WTRU may apply the second measurement gap configuration. If a measurement gap within the second measurement gap configuration overlaps in time with a scheduled UL (re)transmission or DL reception, the WTRU may send an SR. If a measurement gap within the second measurement gap configuration overlaps in time with a scheduled UL (re)transmission or DL reception, the WTRU may flush HARQ buffers associated with the transmission. If a measurement gap within the second measurement gap configuration overlaps in time with a scheduled UL (re)transmission or DL reception, the WTRU may discard or cancel the UL (re)transmission. If a measurement gap within the second measurement gap configuration overlaps in time with a scheduled UL (re)transmission or DL reception, the WTRU may not receive a DL transmission. If a measurement gap within the second measurement gap configuration overlaps in time with a scheduled UL (re)transmission or DL reception, the WTRU may not monitor PDCCH.

[0161] Embodiments are described herein for improved throughput by reducing the time a WTRU may suspend UL transmission and / or DL reception to perform measurements when measurement prediction may be performing well.

[0162] Examples of gap skipping based on AI / ML performance are described herein. A WTRU may skip one or more measurement gaps as a function of measurement prediction performance. If the prediction performance exceeds a threshold, the WTRU may skip one or more upcoming measurement gaps.

[0163] A WTRU may receive a measurement gap configuration which may include measGapConfig (e.g., a gap ID, gap length, gap type, applicable frequencies, etc.). A WTRU may receive a measurement gap configuration which may include gap skipping criteria. A WTRU may receive a measurement gap configuration which may include prediction evaluation criteria (e.g., criteria to trigger a prediction evaluation, a duration of evaluation, a performance margin, etc.).

[0164] The WTRU may apply the measurement gap configuration and may monitor the gap skipping criteria. Gap skipping criteria may include the (de)activation of an AI / ML model. Gap skipping criteria may include the performance of an AI / ML model exceeding / falling below a threshold. Gap skipping criteria may include the WTRU determining that the gap skipping criteria for a second measurement gap configuration are satisfied.

[0165] The WTRU may verify that gap skipping during an evaluation period (e.g., via prediction evaluation criteria that may be included within the measurement gap configuration). A prediction evaluation may include the WTRU predicting and performing measurements for an evaluation period. A prediction evaluation may include if the delta difference between the predicted and acquired measurement is within a configured margin, the prediction evaluation criteria may be successful. If the associated gap skipping criteria (and prediction evaluation criteria, if configured) are satisfied, the WTRU may skip one or more measurement gaps.

[0166] The WTRU may notify the network that one or more measurement gaps may be skipped in the future. A network indication may include one or more gap I D(s), gap length(s), applicable frequencies, etc. A network indication may include how many times the gap(s) may be skipped.

[0167] Embodiments are described herein for improved throughput by reducing the time a WTRU may suspend UL transmission and / or DL reception to perform unnecessary measurements when measurement prediction may be performing well.

Claims

CLAIMS:1 . A wireless transmit / receive unit (WTRU) comprising: a processor configured to: receive a first measurement gap configuration, a second measurement gap configuration, and activation criteria associated with the second measurement gap configuration, wherein the second measurement gap configuration is associated with an artificial intelligence or machine learning (AI / ML) model; perform a first plurality of measurements based on the first measurement gap configuration; determine that the activation criteria has been satisfied based on the first plurality of measurements; send, based on the determination that the activation criteria has been satisfied, an indication to a network device that the second measurement gap configuration will be applied; and perform a second plurality of measurements based on the second measurement gap configuration.

2. The WTRU of claim 1 , wherein the activation criteria comprises a threshold value; and wherein the processor is configured to determine that the activation criteria has been satisfied based on a comparison between predicted measurements of the AI / ML model and the first plurality of measurements being below the threshold value.

3. The WTRU of claim 1 , wherein the processor is configured to: receive prediction evaluation criteria; and determine that the activation criteria or the deactivation criteria has been satisfied based on the prediction evaluation criteria.

4. The WTRU of claim 1 , wherein the indication comprises an indication of an overlap between the second measurement gap configuration with one or more schedule uplink transmissions or downlink transmission.

5. The WTRU of claim 1 , wherein the processor is configured to:receive a confirmation from the network device to apply the second measurement gap configuration.

6. The WTRU of claim 1 , wherein the processor is configured to: receive deactivation criteria associated with the second measurement gap configuration; perform a third plurality of measurements based on the second measurement gap configuration; determine that the deactivation criteria has been satisfied based on the third plurality of measurements; send, based on the determination that the deactivation criteria has been satisfied, a deactivation indication to the network device that the first measurement gap configuration will be applied; and perform a fourth plurality of measurements based on the first measurement gap configuration.

7. The WTRU of claim 1 , wherein the second measurement gap configuration is defined by shorter measurement gaps or less measurement gaps than the first measurement gap configuration.

8. The WTRU of claim 7, wherein the processor is configured to: send a scheduling request (SR), activate a configured grant (CG), activate a Semi-persistent scheduling (SPS) configuration, or monitor a PDCCH transmission.

9. The WTRU of claim 1 , wherein the second measurement gap configuration is defined by longer measurement gaps or more measurement gaps than the first measurement gap configuration.

10. The WTRU of claim 9, wherein the processor is configured to: discard uplink data, flush a Hybrid Automatic Repeat Request (HARQ) buffer, deactivate an SPS configuration, or deactivate a CG configuration.

11. A method performed by a wireless transmit / receive unit (WTRU), the method comprising: receiving a first measurement gap configuration, a second measurement gap configuration, and activation criteria associated with the second measurement gap configuration, wherein the second measurement gap configuration is associated with an artificial intelligence or machine learning (AI / ML) model;performing a first plurality of measurements based on the first measurement gap configuration; determining that the activation criteria has been satisfied based on the first plurality of measurements; sending, based on the determination that the activation criteria has been satisfied, an indication to a network device that the second measurement gap configuration will be applied; and performing a second plurality of measurements based on the second measurement gap configuration.

12. The method of claim 11 , wherein the activation criteria comprises a threshold value; and wherein the method further comprises: determining that the activation criteria has been satisfied based on a comparison between predicted measurements of the AI / ML model and the first plurality of measurements being below the threshold value13. The method of claim 11 , further comprising: receive prediction evaluation criteria; and determine that the activation criteria or the deactivation criteria has been satisfied based on the prediction evaluation criteria.

14. The method of claim 11 , wherein the indication comprises an indication of an overlap between the second measurement gap configuration with one or more schedule uplink transmissions or downlink transmission.

15. The method of claim 11 , further comprising: receiving a confirmation from the network device to apply the second measurement gap configuration.

16. The method of claim 11 , further comprising: receiving deactivation criteria associated with the second measurement gap configuration; performing a third plurality of measurements based on the second measurement gap configuration;determining that the deactivation criteria has been satisfied based on the third plurality of measurements; sending, based on the determination that the deactivation criteria has been satisfied, a deactivation indication to the network device that the first measurement gap configuration will be applied; and performing a fourth plurality of measurements based on the first measurement gap configuration.

17. The method of claim 11 , wherein the second measurement gap configuration is defined by shorter measurement gaps or less measurement gaps than the first measurement gap configuration.

18. The method of claim 17, further comprising: sending a scheduling request (SR), activating a configured grant (CG), activating a Semi-persistent scheduling (SPS) configuration, or monitoring a PDCCH transmission.

19. The WTRU of claim 11 , wherein the second measurement gap configuration is defined by longer measurement gaps or more measurement gaps than the first measurement gap configuration.

20. The WTRU of claim 19, further comprising: discarding uplink data, flushing a Hybrid Automatic Repeat Request (HARQ) buffer, deactivating an SPS configuration, or deactivating a CG configuration.

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