Method for KPI selection, determination and indication of beam measurement set based on AIML system

Abstract

Techniques may be used for artificial intelligence (AI) / machine learning (ML) beam management, such as in 5G new radio (NR) systems. A wireless transmit / receive unit (WTRU) may receive configuration information for a reference signal (RS) resource set A, configuration information for an RS resource set B, and configuration information for a plurality of candidate QCL hypothesis sets of the RS resource set B from a gNodeB (gNB). The WTRU may perform measurements on RSs received on each resource of the RS resource set B based on at least one of the plurality of candidate QCL hypothesis sets. The WTRU may perform a measurement on an RS received on a resource in an RS resource set A and select one of a plurality of candidate QCL hypothesis sets based on the performed measurement and the determined KPI value.

Description

[0001] Related applications This application claims the benefit and priority of U.S. Provisional Patent Application No. 63 / 494,141, filed April 4, 2023, entitled “Method for KPI Selection, Determination and Indication of Beam Measurement Sets Based on AIML System”, the entire contents of which are incorporated herein by reference. Background Technology

[0002] The 3rd Generation Partnership Project (3GPP) has approved a radio access network (RAN) research project on artificial intelligence (AI) / machine learning (ML) for the 5G New Radio (NR) air interface. Beam management for optimally aligning highly directional transmit and receive beams has been selected as one of the target use cases for AI / ML in the air interface. Utilizing 5G millimeter wave (mmWave) to achieve directional communication with a larger number of antenna elements and provide additional beamforming gain requires effective beam management so that WTRUs and gNBs can efficiently identify and utilize the optimal beam over time. Summary of the Invention

[0003] The technology can be used for artificial intelligence (AI) / machine learning (ML) beam management, such as in 5G New Radio (NR) systems. A Wireless Transmit / Receive Unit (WTRU) can receive configuration information from a gNodeB (gNB) for a Reference Signal (RS) resource set A, where RS resource set A includes resources for all beams associated with the gNB. The WTRU can receive configuration information for an RS resource set B, which is smaller than the size of RS resource set A. The WTRU can receive configuration information for multiple candidate QCL hypothesis sets for RS resource set B, where each QCL hypothesis set is associated with at least one RS resource in RS resource set A. The WTRU can receive information indicating one or more Key Performance Indicators (KPIs). The WTRU can perform measurements on the RS received on each resource in RS resource set B based on at least one of the multiple candidate QCL hypothesis sets. The WTRU can perform measurements on the RS received on resources in RS resource set A and select one of the multiple candidate QCL hypothesis sets based on the performed measurements and determined values ​​of the indicated one or more KPIs. WTRU can send a message to gNB reporting the selected set of QCL hypothesis set B. Attached Figure Description

[0004] The invention can be understood in more detail from the following description given by way of example in conjunction with the accompanying drawings, wherein like reference numerals denote like elements, and wherein: Figure 1AThis is a system diagram illustrating an example communication system that can implement one or more of the disclosed embodiments; Figure 1B This illustrates that, according to an embodiment, it is possible to Figure 1A The system diagram shown is of an example wireless transmit / receive unit (WTRU) used in the communication system. Figure 1C This illustrates that, according to an embodiment, it is possible to Figure 1A The diagram shows an example radio access network (RAN) and an example core network (CN) used within a communication system. Figure 1D This illustrates that, according to an embodiment, it is possible to Figure 1A The system diagram shows another example RAN and another example CN used within the communication system shown; Figure 2 This is a system diagram illustrating an example communication system, which includes a base station employing directional communication with a large number of directional beams to communicate with one or more WTRUs via an air interface; and Figure 3 This is a flowchart illustrating a process as part of the beam management procedure for WTRU to select and indicate the configured RS resource set (set B) and associated quasi-cooperative positioning (QCL) assumptions. Detailed Implementation

[0005] Figure 1A This diagram illustrates an example communication system 100 that can implement one or more of the disclosed embodiments. The communication system 100 can be a multiple access system that provides content such as voice, data, video, messaging, and broadcasting to multiple wireless users. The communication system 100 enables multiple wireless users to access such content by sharing system resources, including wireless bandwidth. For example, the communication system 100 can 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-tailed Unique Word Discrete Fourier Transform Spread Spectrum Orthogonal Frequency Division Multiplexing (ZT-UW-DFT-S-OFDM), Unique Word OFDM (UW-OFDM), Resource Block Filtered OFDM, Filter Bank Multicarrier (FBMC), etc.

[0006] like Figure 1AAs shown, the communication system 100 may include wireless transmit / receive units (WTRUs) 102a, 102b, 102c, 102d, a radio access network (RAN) 104, a core network (CN) 106 / 115, a public switched telephone network (PSTN) 108, the Internet 110, and other networks 112. However, it will be understood that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and / or network elements. Each of the WTRUs 102a, 102b, 102c, and 102d can be any type of device configured to operate and / or communicate in a wireless environment. For example, WTRUs 102a, 102b, 102c, and 102d (any of which may be referred to as a station (STA)) may be configured to transmit and / or receive wireless signals and may include user equipment (UE), mobile stations, fixed or mobile subscriber units, subscription-based units, pagers, cellular phones, personal digital assistants (PDAs), smartphones, laptops, netbooks, personal computers, wireless sensors, hotspots or Mi-Fi devices, Internet of Things (IoT) devices, watches or other wearable devices, head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in the context of industrial and / or automated processing chains), consumer electronics devices, devices operating on commercial and / or industrial wireless networks, etc. Any of WTRUs 102a, 102b, 102c, and 102d may be interchangeably referred to as a UE.

[0007] The communication system 100 may also include base station 114a and / or base station 114b. Each of base stations 114a and 114b may be any type of device configured to wirelessly interface with at least one of WTRUs 102a, 102b, 102c, and 102d to facilitate access to one or more communication networks such as CN 106, Internet 110, and / or other networks 112. As an example, base stations 114a and 114b may be base transceiver stations (BTS), node Bs, eNode-Bs (eNBs), home node Bs, home eNode-Bs, next-generation node Bs (such as gNode-Bs (gNBs), new radio (NR) node Bs), site controllers, access points (APs), wireless routers, etc. Although base stations 114a and 114b are each depicted as a single element, it will be understood that base stations 114a and 114b may include any number of interconnected base stations and / or network elements.

[0008] Base station 114a may be part of RAN 104, which may also include other base stations and / or network elements (not shown), such as base station controllers (BSCs), radio network controllers (RNCs), relay nodes, etc. Base station 114a and / or base station 114b may be configured to transmit and / or receive radio signals on one or more carrier frequencies, which may be referred to as cells (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 specific geographic area that may be relatively fixed or may change over time. A cell may also be divided into cell sectors. For example, the cell associated with base station 114a may be divided into three sectors. Therefore, in one embodiment, base station 114a may include three transceivers, i.e., one for each sector of the cell. In embodiments, 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 a desired spatial direction.

[0009] Base stations 114a and 114b can communicate with one or more of WTRUs 102a, 102b, 102c, and 102d via air interface 116, which can be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.). Any suitable radio access technology (RAT) can be used to establish air interface 116.

[0010] More specifically, as described above, the communication system 100 can be a multiple access system and can employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, etc. For example, base station 114a in RAN 104 and WTRUs 102a, 102b, and 102c can implement radio technologies, such as using Wideband CDMA (WCDMA) to establish Universal Mobile Telecommunications System (UMTS) Land Air Interface Access (UTRA) for air interface 116. WCDMA can include communication protocols such as High-Speed ​​Packet Access (HSPA) and / or Evolved HSPA (HSPA+). HSPA can include High-Speed ​​Downlink (DL) Packet Access (HSDPA) and / or High-Speed ​​Uplink (UL) Packet Access (HSUPA) communications.

[0011] In one embodiment, base station 114a and WTRUs 102a, 102b, 102c may implement radio technologies such as using Long Term Evolution (LTE) and / or LTE-Advanced (LTE-A) and / or LTE-Advanced Pro (LTE-A Pro) to establish Evolved UMTS Terrestrial Radio Access (E-UTRA) for air interface 116.

[0012] In one embodiment, base station 114a and WTRUs 102a, 102b, 102c can implement radio technologies, such as using NR to establish NR radio access for air interface 116.

[0013] In one embodiment, base station 114a and WTRUs 102a, 102b, and 102c can implement multiple radio access technologies. For example, base station 114a and WTRUs 102a, 102b, and 102c can, for instance, use a dual connectivity (DC) principle to jointly implement LTE radio access and NR radio access. Therefore, the air interface used by WTRUs 102a, 102b, and 102c can be characterized by multiple types of radio access technologies and / or transmissions sent to / from multiple types of base stations (e.g., eNBs and gNBs).

[0014] In other embodiments, base station 114a and WTRUs 102a, 102b, 102c can implement radio technologies such as IEEE 802.11 (i.e., WiFi), IEEE 802.16 (i.e., WiMAX), CDMA2000, CDMA2000 1X, CDMA2000 EV-DO, Provisional Standard 2000 (IS-2000), Provisional Standard 95 (IS-95), Provisional Standard 856 (IS-856), Global System for Mobile Communications (GSM), Enhanced Data Rate GSM Evolution (EDGE), GSMEDGE (GERAN), etc.

[0015] Figure 1ABase station 114b can be, for example, a wireless router, master node B, master eNode B, or access point, and can utilize any suitable RAT to facilitate wireless connectivity in local areas such as commercial locations, homes, vehicles, campuses, industrial facilities, air corridors (e.g., for use by drones), roads, etc. In one embodiment, base station 114b and WTRUs 102c, 102d can implement radio technologies such as IEEE 802.11 to establish a wireless local area network (WLAN). In one embodiment, base station 114b and WTRUs 102c, 102d can implement radio technologies such as IEEE 802.15 to establish a wireless personal area network (WPAN). In yet another embodiment, base station 114b and WTRUs 102c, 102d can utilize cellular-based RATs (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-a, LTE-a Pro, NR, etc.) to establish picocells or femtocells. Figure 1A As shown, base station 114b can be directly connected to Internet 110. Therefore, base station 114b does not need to access Internet 110 via CN 106.

[0016] RAN 104 can communicate with CN 106, which can be any type of network configured to provide voice, data, application, and / or Voice over Internet Protocol (VoIP) services to one or more of WTRUs 102a, 102b, 102c, and 102d. Data can have different Quality of Service (QoS) requirements, such as different throughput requirements, latency requirements, fault tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, etc. CN 106 can provide call control, billing services, location-based services, prepaid calling, internet connectivity, video distribution, etc., and / or perform advanced security functions such as user authentication. Although... Figure 1A As not shown, but will be understood, RAN 104 and / or CN 106 can communicate directly or indirectly with other RANs that use the same RAT as or a different RAT than RAN 104. For example, in addition to connecting to RAN 104, which may be utilizing NR radio technology, CN 106 can also communicate with another RAN (not shown) using GSM, UMTS, CDMA 2000, WiMAX, E-UTRA, or WiFi radio technology.

[0017] CN 106 can also serve as a gateway for WTRUs 102a, 102b, 102c, and 102d to access PSTN 108, the Internet 110, and / or other networks 112. PSTN 108 may include a circuit-switched telephone network providing Common Old-Style Telephone Service (POTS). The Internet 110 may include a global system of interconnected computer networks and devices using common communication protocols such as Transmission Control Protocol (TCP), User Datagram Protocol (UDP), and / or Internet Protocol (IP) from the TCP / IP Internet Protocol suite. Network 112 may include wired and / or wireless communication networks owned and / or operated by other service providers. For example, network 112 may include another CN connected to one or more RANs, which may use the same RAT as RAN 104 or a different RAT.

[0018] Some or all of the WTRUs 102a, 102b, 102c, and 102d in communication system 100 may include multi-mode capabilities (e.g., WTRUs 102a, 102b, 102c, and 102d may include multiple transceivers for communicating with different wireless networks via different wireless links). For example, Figure 1A The WTRU 102c shown can be configured to communicate with a base station 114a that can use cellular-based radio technology and with a base station 114b that can use IEEE 802 radio technology.

[0019] Figure 1B This is a system diagram illustrating an exemplary WTRU 102. (See diagram below.) Figure 1B As shown, WTRU 102 may include a processor 118, a transceiver 120, a transmitting / receiving element 122, a speaker / microphone 124, a keypad 126, a display / touchpad 128, non-removable memory 130, removable memory 132, a power supply 134, a Global Positioning System (GPS) chipset 136, and / or other components / peripherals 138, etc. It will be understood that, while remaining consistent with the embodiments, WTRU 102 may include any sub-combination of the foregoing components.

[0020] Processor 118 can be a general-purpose processor, a special-purpose processor, a conventional processor, a digital signal processor (DSP), multiple microprocessors, one or more microprocessors associated with a DSP core, a controller, a microcontroller, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), any other type of integrated circuit (IC), a state machine, etc. Processor 118 can perform signal encoding, data processing, power control, input / output processing, and / or any other functions that enable WTRU 102 to operate in a wireless environment. Processor 118 can be coupled to transceiver 120, which can be coupled to transmitting / receiving element 122. Although Figure 1B While the processor 118 and transceiver 120 are depicted as separate components, it will be understood that the processor 118 and transceiver 120 can be integrated together in an electronic package or chip.

[0021] Transmitting / receiving element 122 can be configured to transmit signals to or receive signals from a base station (e.g., base station 114a) via air interface 116. For example, in one embodiment, transmitting / receiving element 122 can be an antenna configured to transmit and / or receive RF signals. In one embodiment, transmitting / receiving element 122 can be a transmitter / detector configured to transmit and / or receive, for example, IR, UV, or visible light signals. In yet another embodiment, transmitting / receiving element 122 can be configured to transmit and / or receive both RF signals and optical signals. It will be understood that transmitting / receiving element 122 can be configured to transmit and / or receive any combination of wireless signals.

[0022] Although the transmitting / receiving element 122 is in Figure 1B While depicted as a single element, WTRU 102 may include any number of transmit / receive elements 122. More specifically, WTRU 102 may employ MIMO technology. Thus, in one embodiment, WTRU 102 may include two or more transmit / receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals via air interface 116.

[0023] Transceiver 120 can be configured to modulate signals transmitted by transmitting / receiving element 122 and demodulate signals received by transmitting / receiving element 122. As described above, WTRU 102 can have multi-mode capability. Therefore, transceiver 120 can include multiple transceivers for enabling WTRU 102 to communicate via various RATs (e.g., such as NR and IEEE 802.11).

[0024] The processor 118 of WTRU 102 can be coupled to and receive user input data from: a speaker / microphone 124, a keypad 126, and / or a display / touchpad 128 (e.g., a liquid crystal display (LCD) unit or an organic light-emitting diode (OLED) display unit). The processor 118 can also output user data to the speaker / microphone 124, keypad 126, and / or display / touchpad 128. Additionally, the processor 118 can access information and store data from any suitable type of memory, such as non-removable memory 130 and / or removable memory 132. 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. Removable memory 132 may include a subscriber identity module (SIM) card, memory stick, secure digital storage (SD) card, etc. In other embodiments, the processor 118 can access information and store data from memory not actually located on WTRU 102, such as on a server or home computer (not shown).

[0025] The processor 118 may receive power from the power supply 134 and may be configured to distribute power to other components in the WTRU 102 and / or control power to those other components. The power supply 134 may be any suitable device for powering the WTRU 102. For example, the power supply 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, etc.

[0026] The processor 118 may also be coupled to a GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) about the current location of the WTRU 102. In addition to or instead of information from the GPS chipset 136, the WTRU 102 may receive location information from base stations (e.g., base stations 114a, 114b) via air interface 116 and / or determine its location based on the timing of signals received from two or more nearby base stations. It will be understood that, while remaining consistent with the embodiments, the WTRU 102 may acquire location information using any suitable location determination method.

[0027] The processor 118 can also be connected to other peripheral devices 138, which may include one or more software and / or hardware modules that provide additional features, functions, and / or wired or wireless connectivity. For example, peripheral device 138 may include an accelerometer, electronic compass, satellite transceiver, digital camera (for photos and / or video), Universal Serial Bus (USB) port, vibration device, television transceiver, hands-free headset, Bluetooth® module, FM radio unit, digital music player, media player, video game player module, internet browser, virtual reality and / or augmented reality (VR / AR) device, activity tracker, etc. Peripheral device 138 may include one or more sensors. Sensors may be one or more of the following: gyroscope, accelerometer, Hall effect sensor, magnetometer, orientation sensor, proximity sensor, temperature sensor, time sensor; geolocation sensor, altimeter, light sensor, touch sensor, magnetometer, barometer, gesture sensor, biometric sensor, humidity sensor, etc.

[0028] WTRU 102 may include a full-duplex radio, wherein some or all of the transmission and reception of signals (e.g., associated with a specific subframe of both UL (e.g., for transmission) and DL (e.g., for reception)) may be concurrent and / or simultaneous. The full-duplex radio may include an interference management unit to reduce and / or substantially eliminate self-interference via hardware (e.g., a choke) or signal processing via a processor (e.g., a separate processor (not shown) or via processor 118). In embodiments, WTRU 102 may include a half-duplex radio, wherein some or all of the transmission and reception of signals (e.g., associated with a specific subframe of both UL (e.g., for transmission) or DL ​​(e.g., for reception)) may be concurrent and / or simultaneous.

[0029] Figure 1C This is a system diagram illustrating RAN 104 and CN 106 according to an embodiment. As described above, RAN 104 can employ E-UTRA radio technology to communicate with WTRUs 102a, 102b, and 102c via air interface 116. RAN 104 can also communicate with CN 106.

[0030] RAN 104 may include eNode-Bs 160a, 160b, and 160c, but it will be understood that RAN 104 may include any number of eNode-Bs while remaining consistent with the embodiments. eNode-Bs 160a, 160b, and 160c may each include one or more transceivers for communicating with WTRUs 102a, 102b, and 102c via air interface 116. In one embodiment, eNode-Bs 160a, 160b, and 160c may implement MIMO technology. Therefore, for example, eNode-B 160a may use multiple antennas to transmit radio signals to and / or receive radio signals from WTRU 102a.

[0031] Each of the eNode-B 160a, 160b, and 160c can be associated with a specific cell (not shown) and can be configured to handle radio resource management decisions, handover decisions, user scheduling in UL and / or DL, etc. Figure 1C As shown, eNode-B 160a, 160b, and 160c can communicate with each other via the X2 interface.

[0032] Figure 1C The CN 106 shown may include a Mobility Management Entity (MME) 162, a Serving Gateway (SGW) 164, and a Packet Data Network (PDN) Gateway (PGW) 166. While the foregoing elements are described as part of CN 106, it will be understood that any of these elements may be owned and / or operated by an entity other than a CN operator.

[0033] The MME 162 can connect to each of the eNode-Bs 162a, 162b, and 162c in RAN 104 via the S1 interface and can act as a control node. For example, the MME 162 can be responsible for authenticating users of WTRUs 102a, 102b, and 102c, activating / deactivating bearers, selecting a specific serving gateway during the initial attachment of WTRUs 102a, 102b, and 102c, etc. The MME 162 can provide control plane functions for handover between RAN 104 and other RANs (not shown) employing other radio technologies such as GSM and / or WCDMA.

[0034] The SGW 164 can connect to each of the eNode Bs 160a, 160b, and 160c in RAN 104 via the S1 interface. The SGW 164 can typically route and forward user data packets to or from WTRUs 102a, 102b, and 102c. The SGW 164 can perform other functions such as anchoring the user plane during eNode-B handover, triggering paging when DL data is available to WTRUs 102a, 102b, and 102c, and managing and storing the context of WTRUs 102a, 102b, and 102c.

[0035] SGW 164 can be connected to PGW 166, which can provide WTRU 102a, 102b, 102c with access to packet-switched networks (such as Internet 110) to facilitate communication between WTRU 102a, 102b, 102c and IP-enabled devices.

[0036] CN 106 can facilitate communication with other networks. For example, CN 106 can provide WTRUs 102a, 102b, and 102c with access to circuit-switched networks (such as PSTN 108) to facilitate communication between WTRUs 102a, 102b, and 102c and conventional terrestrial line communication devices. For example, CN 106 may include an IP gateway (e.g., an IP Multimedia Subsystem (IMS) server) or be able to communicate with it, serving as an interface between CN 106 and PSTN 108. Additionally, CN 106 can provide WTRUs 102a, 102b, and 102c with access to other networks 112, which may include other wired and / or wireless networks owned and / or operated by other service providers.

[0037] Despite WTRU in Figures 1A to 1D While described as a wireless terminal, it is envisioned that, in some representative embodiments, such a terminal may (e.g., temporarily or permanently) use a wired communication interface with a communication network.

[0038] In a representative embodiment, the other network 112 may be a WLAN.

[0039] A WLAN in Infrastructure Basic Services Set (BSS) mode may have an access point (AP) for the BSS and one or more stations (STAs) associated with the AP. The AP may have access or an interface to a distribution system (DS) or another type of wired / wireless network that loads traffic into and / or out of the BSS. Traffic originating outside the BSS destined for a STA can be delivered to the AP. Traffic from a STA to a destination outside the BSS can be sent to the AP for delivery to the appropriate destination. Traffic between STAs within the BSS can be sent via the AP, for example, where a source STA can send traffic to the AP, and the AP can deliver the traffic to the destination STA. Traffic between STAs within the BSS can be considered and / or referred to as point-to-point traffic. Point-to-point traffic can be sent between a source STA and a destination STA using a direct link setup (DLS) (e.g., directly between them). In some representative embodiments, the DLS may use 802.11e DLS or 802.11z Tunneled DLS (TDLS). A WLAN using the Standalone BSS (IBSS) mode may not have an access point (AP), and STAs within the IBSS or using the IBSS (e.g., all STAs) can communicate directly with each other. The IBSS communication mode may sometimes be referred to as an "ad-hoc" communication mode in this document.

[0040] When operating in 802.11ac infrastructure mode or a similar mode, the AP can transmit beacons on a fixed channel, such as the primary channel. The primary channel can be of fixed width (e.g., a bandwidth of 20 MHz) or dynamically configured. The primary channel can be the operating channel of the BSS and can be used by the STA to establish a connection with the AP. In some representative embodiments, Carrier Sense Multiple Access - Collision Avoidance (CSMA / CA) can be implemented, for example, in an 802.11 system. For CSMA / CA, each STA, including the AP, can sense the primary channel. If a particular STA senses / detects the primary signal and / or determines that the primary signal is busy, that STA can back off. A single STA (e.g., only one station) can transmit in a given BSS at any given time.

[0041] High-throughput (HT) STAs can communicate using a 40 MHz wide channel, for example, by combining a primary 20 MHz channel with adjacent or non-adjacent 20 MHz channels.

[0042] Very High Throughput (VHT) STAs can support channels with widths of 20 MHz, 40 MHz, 80 MHz, and / or 160 MHz. 40 MHz and / or 80 MHz channels can be formed by combining consecutive 20 MHz channels. A 160 MHz channel can be formed by combining eight consecutive 20 MHz channels, or by combining two non-consecutive 80 MHz channels, which can be referred to as an 80+80 configuration. In the 80+80 configuration, data, after channel coding, can be passed through a fragment parser that splits the data into two streams. Inverse Fast Fourier Transform (IFFT) processing and time-domain processing can be performed on each stream separately. The streams can be mapped onto the two 80 MHz channels, and the data can be transmitted by the transmitting STA. At the receiver of the receiving STA, the above operations of the 80+80 configuration can be reversed, and the combined data can be sent to the Media Access Control (MAC) layer, entities, etc.

[0043] 802.11af and 802.11ah support operating modes below 1 GHz. The channel operating bandwidth and carrier are reduced in 802.11af and 802.11ah compared to those used in 802.11n and 802.11ac. 802.11af supports 5 MHz, 10 MHz, and 20 MHz bandwidths in the TV Blank (TVWS) spectrum, and 802.11ah supports 1 MHz, 2 MHz, 4 MHz, 8 MHz, and 16 MHz bandwidths using non-TVWS spectrum. According to a representative embodiment, 802.11ah can support instrument-type control / machine-type communication (MTC), such as MTC devices in macro coverage areas. MTC devices may have certain capabilities, such as limited capabilities, including supporting (e.g., only supporting) certain and / or limited bandwidths. MTC devices may include batteries with a battery life exceeding a threshold (e.g., to maintain a very long battery life).

[0044] WLAN systems that can support multiple channels and channel bandwidths (such as 802.11n, 802.11ac, 802.11af, and 802.11ah) include a channel that can be designated as the primary channel. The primary channel can have a bandwidth equal to the maximum common operating bandwidth supported by all STAs in the BSS. The bandwidth of the primary channel can be set and / or limited by the STAs operating in the BSS that support the minimum bandwidth operating mode. In the 802.11ah example, for STAs that support (e.g., only support) the 1 MHz mode (e.g., MTC type devices), the primary channel can be 1 MHz wide, 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 Sense and / or Network Allocation Vector (NAV) settings can depend on the status of the primary channel. If the primary channel is busy, for example, due to STAs (which only support the 1 MHz operating mode) transmitting to the AP, then all available frequency bands can be considered busy even if most of the available bands remain idle.

[0045] In the United States, the available frequency band for 802.11ah is 902 MHz to 928 MHz. In South Korea, the available frequency band is 917.5 MHz to 923.5 MHz. In Japan, the available frequency band is 916.5 MHz to 927.5 MHz. The total available bandwidth for 802.11ah is 6 MHz to 26 MHz, depending on the country code.

[0046] Figure 1D This is a system diagram illustrating RAN 104 and CN106 according to an embodiment. As described above, RAN 104 can employ NR radio technology to communicate with WTRUs 102a, 102b, and 102c via air interface 116. RAN 104 can also communicate with CN106.

[0047] RAN104 may include gNBs 180a, 180b, and 180c, but it will be understood that RAN104 may include any number of gNBs while remaining consistent with the embodiments. gNBs 180a, 180b, and 180c may each include one or more transceivers for communicating with WTRUs 102a, 102b, and 102c via air interface 116. In one embodiment, gNBs 180a, 180b, and 180c may implement MIMO technology. For example, gNBs 180a and 180b may utilize beamforming to transmit signals to and / or receive signals from gNBs 180a, 180b, and 180c. Thus, for example, gNB 180a may use multiple antennas to transmit radio signals to and / or receive radio signals from WTRU 102a. In one embodiment, gNBs 180a, 180b, and 180c may implement carrier aggregation technology. For example, gNB 180a can transmit multiple component carriers to WTRU 102a (not shown). A subset of these component carriers may be located on unlicensed spectrum, while the remaining component carriers may be located on licensed spectrum. In one embodiment, gNBs 180a, 180b, and 180c can implement Coordinated Multipoint (CoMP) technology. For example, WTRU 102a can receive coordinated transmissions from gNBs 180a and 180b (and / or gNB 180c).

[0048] WTRUs 102a, 102b, and 102c can communicate with gNBs 180a, 180b, and 180c using transmissions associated with an scalable set of parameters. For example, the OFDM symbol spacing and / or OFDM subcarrier spacing can be varied for different transmissions, different cells, and / or different portions of the radio transmission spectrum. WTRUs 102a, 102b, and 102c can communicate with gNBs 180a, 180b, and 180c using subframes of various or scalable lengths or transmission time intervals (TTIs) (e.g., containing different numbers of OFDM symbols and / or absolute times of varying durations).

[0049] gNBs 180a, 180b, and 180c can be configured to communicate with WTRUs 102a, 102b, and 102c in standalone and / or non-standalone configurations. In standalone configuration, WTRUs 102a, 102b, and 102c can communicate with gNBs 180a, 180b, and 180c without accessing other RANs (e.g., eNode Bs 160a, 160b, and 160c). In standalone configuration, WTRUs 102a, 102b, and 102c can use one or more of gNBs 180a, 180b, and 180c as mobility anchors. In standalone configuration, WTRUs 102a, 102b, and 102c can communicate with gNBs 180a, 180b, and 180c using signals in unlicensed frequency bands. In a non-standalone configuration, WTRUs 102a, 102b, and 102c can communicate / connect with gNBs 180a, 180b, and 180c while also communicating / connecting with another RAN (such as eNode-B160a, 160b, and 160c). For example, WTRUs 102a, 102b, and 102c can implement DC principles to communicate substantially simultaneously with one or more gNBs 180a, 180b, and 180c and one or more eNode-Bs 160a, 160b, and 160c. In a non-standalone configuration, eNode-Bs 160a, 160b, and 160c can act as mobility anchors for WTRUs 102a, 102b, and 102c, and gNBs 180a, 180b, and 180c can provide additional coverage and / or throughput to serve WTRUs 102a, 102b, and 102c.

[0050] Each of gNBs 180a, 180b, and 180c can be associated with a specific cell (not shown) and can be configured to handle air interface resource management decisions, handover decisions, user scheduling in UL and / or DL, support for network slicing, interaction between DC, NR, and E-UTRA, routing of user plane data to User Plane Functions (UPF) 184a and 184b, and routing of control plane information to Access and Mobility Management Functions (AMF) 182a and 182b, etc. Figure 1D As shown, gNB 180a, 180b, and 180c can communicate with each other via the Xn interface.

[0051] Figure 1DThe CN106 shown 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. Although the foregoing elements are described as part of CN106, it will be understood that any of these elements may be owned and / or operated by an entity other than a CN operator.

[0052] AMF 182a and 182b can connect to one or more of the gNBs 180a, 180b, and 180c in RAN104 via the N2 interface and can act as control nodes. For example, AMF 182a and 182b can be responsible for authenticating users of WTRU 102a, 102b, and 102c, supporting network slicing (e.g., handling different Protocol Data Unit (PDU) sessions with different requirements), selecting specific SMF 183a and 183b, managing registration areas, terminating Non-Access Stratum (NAS) signaling, mobility management, etc. AMF 182a and 182b can use network slicing to customize CN support for WTRU 102a, 102b, and 102c based on the service types being used by WTRU 102a, 102b, and 102c. For example, different network slices can be established for different use cases, such as services that rely on Ultra Reliable Low Latency (URLLC) access, services that rely on Enhanced Massive Mobile Broadband (eMBB) access, and services for MTC access. AMF182a and 182b can provide control plane functions for handover between RAN 104 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).

[0053] SMFs 183a and 183b can connect to AMFs 182a and 182b in CN106 via the N11 interface. SMFs 183a and 183b can also connect to UPFs 184a and 184b in CN106 via the N4 interface. SMFs 183a and 183b can select and control UPFs 184a and 184b, and configure traffic routing through UPFs 184a and 184b. SMFs 183a and 183b can perform other functions, such as managing and allocating UE IP addresses, managing PDU sessions, controlling policy enforcement and QoS, and providing DL data notifications. PDU session types can be IP-based, non-IP-based, or Ethernet-based.

[0054] UPF 184a and 184b can be connected via the N3 interface to one or more of the gNBs 180a, 180b, and 180c in RAN 104. These gNBs can provide WTRU 102a, 102b, and 102c with access to packet-switched networks (such as the Internet 110) to facilitate communication between WTRU 102a, 102b, and 102c and IP-enabled devices. UPF 184 and 184b can perform other functions such as routing and forwarding packets, enforcing user plane policies, supporting multihomed PDU sessions, handling user plane QoS, buffering DL packets, and providing mobility anchoring.

[0055] CN106 can facilitate communication with other networks. For example, CN106 may include or be able to communicate with an IP gateway (e.g., an IP Multimedia Subsystem (IMS) server) that serves as an interface between CN106 and PSTN 108. Additionally, CN106 can provide WTRUs 102a, 102b, and 102c with access to other networks 112, which may include other wired and / or wireless networks owned and / or operated by other service providers. In one embodiment, WTRUs 102a, 102b, and 102c can be connected to DNs 185a and 185b via UPFs 184a and 184b through their N3 interfaces and the N6 interface between UPFs 184a and 184b and local DNs 185a and 185b.

[0056] Given Figures 1A to 1D and Figures 1A to 1D The corresponding description may be performed by one or more emulation elements / devices (not shown) that perform one or more of the functions described herein with respect to any of the following: WTRU 102a to 102d, base stations 114a to 114b, eNode-B 160a to 160c, MME 162, SGW 164, PGW 166, gNB 180a to 180c, AMF 182a to 182b, UPF 184a to 184b, SMF 183a to 183b, DN 185a to 185b, and / or any other device described herein. An emulation device may be one or more devices configured to emulate one or more or all of the functions described herein. For example, an emulation device may be used to test other devices and / or simulate network and / or WTRU functions.

[0057] Simulation devices can be designed to perform one or more tests on other devices in laboratory and / or carrier network environments. For example, one or more simulation devices may perform one or more functions when fully or partially implemented and / or deployed as part of a wired and / or wireless communication network to test other devices within the communication network. One or more simulation devices may perform one or more functions when temporarily implemented / deployed as part of a wired and / or wireless communication network. Simulation devices may be directly coupled to another device for testing and / or performing tests using over-the-air wireless communication.

[0058] One or more simulation devices can perform one or more functions without being implemented / deployed as part of a wired and / or wireless communication network. For example, a simulation device can be used to test scenarios in a laboratory and / or undeployed (e.g., under test) wired and / or wireless communication networks to enable testing of one or more components. One or more simulation devices can be test equipment. The simulation device can transmit and / or receive data using direct RF coupling and / or wireless communication via an RF circuit system (e.g., which may include one or more antennas).

[0059] Beam management processes can include selecting the optimal (highest quality) analog beam for transmission. For example, the WTRU can measure one or more reference signals (RS) associated with one or more beams and received from the gNB. The WTRU can indicate the quality of the measured RS to the gNB. The gNB can select a beam based on the report of the measured RS quality received from the WTRU, and the gNB can accordingly transmit downlink signals (e.g., on the PDSCH / PDCCH). AI / ML techniques can be used to improve the performance and complexity of conventional beam management processes. According to the example embodiments described herein, AI / ML can be used for beam prediction in the time and / or spatial domains to reduce overhead and latency and improve beam selection accuracy.

[0060] In one example, AI / ML can be used for beam management to predict the best (highest quality) beam (or beam pair) from a set of beams (or beam pairs) with more accuracy and less overhead than a conventional beam management process. In a conventional beam management process without AI / ML, the WTRU measures the reference signal (RS) associated with the beam to determine beam quality, and the WTRU reports one or more of the best beams among the measured beams to the gNB. The gNB can then make a decision about which beams are used for downlink transmission (e.g., for PDSCH / PDCCH). In conventional beam management, the WTRU measures all configured RSs to determine one or more highest quality beams(s). In one example, the AI / ML model applied by the WTRU (or gNB) to the beam management process can be used to predict one or more beams (or beam pairs) from all possible beams (or beam pairs), including those not measured by the WTRU (or gNB) (i.e., those for which the WTRU did not perform RS measurements). By using AI / ML, WTRU can measure fewer beams (RS) compared to traditional beam management processes while successfully identifying the highest quality beam among all beams (i.e., measured and unmeasured beams). In one example, the input to the AI / ML model can be beam measurements and / or a set of beam parameters (e.g., denoted by set B), which can also be referred to as a set of measurements for beams (or beam pairs). Set B is a subset of the predicted beam set (e.g., denoted by set A), which includes all possible beams (or beam pairs). In other words, the AI / ML model executed by WTRU (or gNB) can predict one or more beams (or beam pairs) in set A based on the input of beam measurements and / or beam parameters of beams (or beam pairs) in set B.

[0061] Figure 2This is a system diagram illustrating an example communication system 200, which includes a base station 214 employing directional communication with a large number of directional beams to communicate with one or more WTRUs 202 via an air interface. For example, base station 214 may be equipped with a large number of antenna elements that provide directional beams and achieve higher beamforming gain and, consequently, higher data rates. Base station 214 may be configured to transmit and / or receive radio signals on one or more carrier frequencies, and may be referred to as cell 208. In one example, the prediction beam set, also known as set A, includes all beams transmitted from base station 214, including beam 204 shown in solid lines and beam 206 shown in dashed lines. The measurement beam set (referred to as set B) is a subset of set A and includes only beam 206 shown in dashed lines. In one example, set A has 64 beams, and set B has one of 4, 8, 16, or 32 beams for spatial prediction. Quasi-cooperative positioning (QCL) assumptions refer to assumptions about the QCL reference for RS (e.g., QCL assumption 1: the QCL reference for set B {RS#1, RS#2, ...} is SSB #1 SSB #3 ...; QCL assumption 2: the QCL reference for set B {RS#1, RS#2, ...} is SSB #2 SSB #4 ...; where all SSBs {SSB #1, SSB #2, SSB #3 ...} are associated with different beams).

[0062] AI / ML models for beam measurement processes can be trained using sets B of different types and sizes (in terms of beam count). For example, an AI / ML model trained with a larger set B size may improve prediction accuracy, but at the cost of overhead. Similarly, an AI / ML model trained with a smaller set B size may have lower prediction accuracy and lower overhead. In one example, an AI / ML model trained with a single fixed set B may perform better (higher prediction accuracy) at the cost of flexibility in inputting to the AI / ML model. Conversely, an AI / ML model trained with multiple or random sets B has greater flexibility in terms of inputting to the AI / ML model at possible performance costs. In one example, the first set B (or the corresponding AI / ML model) may be the optimal set for maximizing a subset of key performance indicators (KPIs) from a larger group or all possible KPIs, while the second set B (or the corresponding AI / ML model) may be adapted to satisfy different KPI thresholds. Another example set B may be robust enough to satisfy several different KPI thresholds, but not optimal for any particular KPI. Therefore, an AI / ML-based beam selection process is needed to determine and report the optimal set B selection based on one or more KPIs.

[0063] This paper discloses a beam measurement process that uses AI / ML for WTRU to determine and indicate the optimal set B to be used to perform beam measurements and achieve one or more KPI objectives. Here, set B can be a measurement beam resource set that includes the beams / resources to be measured, and the predicted set B can be (e.g., using AI / ML) the set of beams / resources that it predicts to measure.

[0064] In one example, a procedure is used to select and indicate a (configured) measurement beam resource set (e.g., set B) based on one or more KPIs (the measurement beam resource set is "configured" meaning the WTRU is configured to know which RSs belong to the measurement beam resource set). According to the example procedure, the WTRU may receive configuration information for any one or more of the following: a cell-specific RS resource set, a WTRU-specific RS resource set, candidate quasi-cooperative localization (QCL) hypotheses, and / or corresponding thresholds for the KPIs. The WTRU may (dynamically) determine the need for new candidate QCL hypotheses and may select one or more new candidate QCL hypotheses based on the KPIs.

[0065] In the following text, “a” and “an” and similar phrases will be interpreted as “one or more” and “at least one”. Similarly, any term ending with a suffix will be interpreted as “one or more” and “at least one”. The term “may” will be interpreted as “may, for example”. Artificial intelligence (AI) can be broadly defined as the behavior exhibited by machines. Such behavior can, for example, mimic cognitive functions to perceive, reason, adapt, and act. Machine learning (ML) can refer to a type of algorithm based on learning through experience (“data”) rather than explicit programming (“configuration of a set of rules”) to solve problems. Machine learning can be considered a subset of AI. Different machine learning paradigms can be envisioned based on the nature of the data or feedback available to the learning algorithm. For example, supervised learning methods can involve learning a function that maps inputs to outputs based on labeled training examples, where each training example can be a pair consisting of an input and a corresponding output. For example, unsupervised learning methods can involve detecting patterns in data for which no pre-existing labels are present. For example, reinforcement learning methods can involve performing a sequence of actions in an environment to maximize cumulative rewards. In the examples, machine learning algorithms are applied using combinations or interpolation of the methods described above. For example, semi-supervised learning methods can use a combination of a small amount of labeled data and a large amount of unlabeled data during training. In this respect, semi-supervised learning falls between unsupervised learning (without labeled training data) and supervised learning (with only labeled training data).

[0066] Deep learning (DL) refers to a class of machine learning algorithms that employ artificial neural networks (specifically deep neural networks (DNNs)) loosely inspired by biological systems. DNNs are a special category of machine learning models inspired by the human brain, where the input is linearly transformed and passed multiple times through a non-linear activation function. DNNs typically consist of multiple layers, each composed of a linear transformation and a given non-linear activation function. DNNs can be trained using training data via a backpropagation algorithm. Recently, DNNs have demonstrated state-of-the-art performance in various fields (e.g., speech, vision, natural language, etc.) and for various machine learning settings (e.g., supervised, unsupervised, and semi-supervised). Artificial Intelligence Markup Language (AIML)-based methods / processes refer to achieving behaviors and / or conforming to requirements through data-based learning without explicitly configuring the sequence of action steps. Such methods enable the learning of complex behaviors that might be difficult to specify and / or achieve using traditional methods.

[0067] A WTRU can transmit or receive signals (carrying data or control information) or reference signals on a physical channel based on at least one spatial domain filter. The term "beam" can be used to refer to a spatial domain filter. A beam pair can refer to a set of two beams, a transmit (Tx) beam and a receive (Rx) beam. A WTRU can transmit a physical channel or signal using the same spatial domain filter used to receive RS (e.g., Channel State Information Reference Signal (CSI-RS)) or synchronization signal (SS) blocks. The WTRU transmission can be referred to as the "target," and the received RS or SS block can be referred to as the "reference" or "source." In this context, the WTRU can be said to be transmitting a target physical channel or signal based on a spatial relationship relating to a reference to the RS or SS block.

[0068] The WTRU can transmit the first physical channel or signal using the same spatial domain filter as the spatial domain filter used to transmit the second physical channel or signal. The first and second transmissions can be referred to as the "target" and the "reference" (or "source"), respectively. In this case, the WTRU can be said to transmit the first (target) physical channel or signal based on the spatial relationship with the reference of the second (reference) physical channel or signal.

[0069] For example, spatial relationships can be implicit or configured by messages from the gNB, such as, but not limited to, Radio Resource Control (RRC) messages, Media Access Control (MAC) Control Elements (CEs), or L1 / L2 control information, such as Downlink Control Information (DCI). For instance, the WTRU can implicitly transmit information on the Physical Uplink Shared Channel (PUSCH) and can transmit a Demodulation Reference Signal (DM-RS) on the PUSCH based on the same spatial domain filter as the Sounding Reference Signal (SRS) indicated by the SRS Resource Indicator (SRI), where the SRS Resource Indicator (SRI) can be indicated, for example, in the DCI or configured by an RRC message. In another example, spatial relationships can be configured by an RRC message for the SRS Resource Indicator (SRI) or signaled by a MAC CE (e.g., via the PUCCH) for the PUCCH (e.g., for a PUCCH received X times, symbols, milliseconds, or microseconds after spatial relationship signaling). Such spatial relationships can also be referred to as “beam indication.” The WTRU can receive information on the first (target) downlink channel or signal based on the same spatial domain filters or spatial reception parameters as the second (reference) downlink channel or signal. For example, such spatial association can exist between a physical channel such as the PDCCH or Physical Downlink Shared Channel (PDSCH) and its corresponding DM-RS. In one example, if the first and second signals are reference signals, this spatial association may exist when the WTRU is configured to have a Quasi-Companion (QCL) assumption type D between the respective antenna ports. Spatial association can be configured as a Transmission Configuration Indicator (TCI) state. The WTRU can receive an indication of the association between the CSI-RS or SS block and the DM-RS via an index to a TCI state set, which can be configured by the RRC and / or signaled by the MAC CE. The indication of the association between the CSI-RS or SS block and the DM-RS can be referred to as a "beam indication".

[0070] In the following text, Transmit and Receive Points (TRPs) may be used interchangeably with any of the following: Transmit Point (TP), Receive Point (RP), Radio Remote Header (RRH), Distributed Antenna (DA), Base Station (BS), (BS) Sector, and Cell (e.g., the geographic cell area served by the BS). In the following text, Multiple TRPs may be used interchangeably with any of the following: MTRP, M-TRP, and Multiple TRPs.

[0071] The WTRU may report a subset of Channel State Information (CSI) components. For example, CSI components may include, but are not limited to, any one or more of the following: CSI-RS Resource Indicator (CRI); Synchronization Signal Block (SSB) Resource Indicator (SSBRI) indicating the panel received at the WTRU (e.g., panel identifier or group identifier); measurements, such as Layer 1 Reference Signal Received Power (L1-RSRP) and / or Layer 1 Signal-to-Interference-plus-Noise Ratio (L1-SINR) taken from the SSB or CSI-RS (e.g., CRI-RSRP, CRI-SINR, SSB Index-RSRP, SSB Index-SINR); and / or other Channel State Information (CSI), including but not limited to Rank Indicator (RI), Channel Quality Indicator (CQI), Precoding Matrix Indicator (PMI), and / or Layer Index (LI).

[0072] The example procedure can be used for channel measurements and / or interference measurements. For example, the WTRU can receive a Synchronization Signal / Physical Broadcast Channel (SS / PBCH) block. An SS / PBCH block, also known as an SSB, can include a Primary Synchronization Signal (PSS), a Secondary Synchronization Signal (SSS), and / or a Physical Broadcast Channel (PBCH). The WTRU can monitor, receive, and / or attempt to decode the SSB during the example procedure, which includes, but is not limited to, initial access, initial synchronization, radio link monitoring (RLM), cell search, and / or cell handover.

[0073] In one example, the WTRU can measure and report Channel State Information (CSI), where the CSI for each connectivity mode can include one or more of the following information or be configured with one or more of the following information: CSI reporting configuration, CSI-RS resource set, and / or Non-Zero Power (NZP) CSI-RS resources. The CSI reporting configuration may include, but is not limited to, any of the following information: number of CSI reports (e.g., Channel Quality Indicator (CQI), Rank Indicator (RI), Precoding Matrix Indicator (PMI), CSI-RS Resource Indicator (CRI), Layer Indicator (LI)), CSI report type (e.g., aperiodic, semi-persistent, periodic), CSI report codebook configuration (e.g., Type I, Type II port selection, etc.), and / or CSI report frequency. The CSI-RS resource set may include, but is not limited to, any of the following CSI resource settings: NZP-CSI-RS resources for channel measurements; NZP-CSI-RS resources for interference measurements; and / or CSI-IM resources for interference measurements. NZP CSI-RS resources may include, but are not limited to, any of the following information: NZP CSI-RS resource ID; periodicity and offset; QCL information and TCI-status; and / or resource mapping (e.g., number of ports, density, CDM type, etc.).

[0074] In one example, the WTRU may indicate, identify, and / or configure one or more RSs. The WTRU may monitor, receive, and / or measure one or more parameters based on the corresponding RS. Instance parameters that may be included in RS measurements include (but are not limited to) any of the following: Synchronization Signal (SS) Reference Signal Received Power (SS-RSRP); CSI-RSRP; SS-SINR; CSI-SINR; Received Signal Strength Indicator (RSSI); Cross-Layer Interference RSSI (CLI-RSSI); and / or SRS-RSRP. These instance parameters are described below.

[0075] In one example, the SS-RSRP can be measured by the WTRU based on the received synchronization signal (e.g., the demodulated reference signal (DMRS) on the PBCH or SSS). The SS-RSRP can be defined as a linear average of the power contribution of the resource element (RE) carrying the corresponding synchronization signal. Power scaling of the reference signal can be used when measuring RSRP. In an example where SS-RSRP is used for L1-RSRP, the measurement can be based on a CSI reference signal other than the synchronization signal. In this example, the CSI-RSRP can be measured based on a linear average of the power contribution of the RE carrying the corresponding CSI-RS. The CSI-RSRP measurement can be configured within the measurement resources used for the configured CSI-RS timing.

[0076] In one example, SS-SINR can be measured by the WTRU based on the received synchronization signal (e.g., DMRS on the PBCH or SSS). SS-SINR can be defined as the linear average of the power contribution of the RE carrying the corresponding synchronization signal divided by the linear average of the noise and interference power contributions. In the example where SS-SINR is used for L1-SINR, noise and interference power measurements can be performed based on resources configured by a higher layer. In the example, CSI-SINR can be measured based on the linear average of the power contribution of the RE carrying the corresponding CSI-RS divided by the linear average of the noise and interference power contributions. In the example where CSI-SINR is used for L1-SINR, noise and interference power measurements can be performed based on resources configured by a higher layer. Otherwise, noise and interference power can be measured based on resources carrying the corresponding CSI-RS.

[0077] In one example, RSSI can be measured by the WTRU based on the average of the total power contribution and bandwidth in the configured (DL) OFDM symbols. Power contributions can be received from different resources (e.g., co-channel serving cells and / or non-serving cells, adjacent channel interference, thermal noise, etc.). In the example, CLI-RSSI can be measured based on the average of the total power contribution in the configured OFDM symbols with configured (DL) time and frequency resources. Power contributions can be received from different resources (e.g., cross-layer interference, co-channel serving cells and / or non-serving cells, adjacent channel interference, thermal noise, etc.). SRS-RSRP can be measured based on the linear average of the power contribution of the RE carrying the corresponding SRS.

[0078] The example procedure can be used for beam configuration and / or CSI report configuration. CSI report configuration (e.g., CSI report configuration can be used with a single bandwidth portion (BWP)). (E.g., indicated by BWP-Id) Associated with and may provide information to configure parameters, including but not limited to any one or more of the following: CSI-RS resources and / or CSI-RS resource sets for channel and interference measurements; CSI-RS report configuration type, including periodic, semi-persistent, and / or aperiodic; CSI-RS transmission period for periodic and / or semi-persistent CSI reports; CSI-RS transmission slot offset for periodic, semi-persistent, and / or aperiodic CSI reports; CSI-RS transmission slot offset list for semi-persistent and / or aperiodic CSI reports; time constraints for channel and / or interference measurements; reporting band configuration (e.g., wideband / subband CQI, PMI, etc.); thresholds and / or calculation modes for reporting quantities (e.g., CQI, RSRP, SINR, LI, RI, etc.); codebook configuration; group-based beam reporting; CQI table; subband size; non-PMI port indication; and / or port index.

[0079] The example procedure can be used for CSI-RS resource configuration. A CSI-RS resource set (e.g., NZP-CSI-RS-ResourceSet) may include one or more CSI-RS resources (e.g., NZP-CSI-RS resource and CSI-ResourceConfig), where WTRUs may be configured in the CSI-RS resources with one or more of the following: CSI-RS period and slot offset for periodic and semi-persistent CSI-RS resources; CSI-RS resource mapping to define the number, density, CDM type, OFDM symbol, and subcarrier occupancy of CSI-RS ports; the bandwidth portion to which the configured CSI-RS is allocated; and / or references to including (one or more) QCL source RSs and (one or more) TCI-States of corresponding QCL types.

[0080] The example procedure can be used for RS resource set configuration. A WTRU can be configured with one or more RS resource sets. For example, RS resource set configuration can include, but is not limited to, any one or more of the following: RS resource set ID; one or more RS resources for the RS resource set; repetition (i.e., on or off); non-periodic trigger offset (e.g., one of 0-6 time slots); and / or Tracking Reference Signal (TRS) information (e.g., true or false).

[0081] The example procedure can be used for RS resource configuration. A WTRU can be configured with one or more RS resources. For example, RS resource configuration can include, but is not limited to, one or more of the following: RS resource identifier (ID); resource mapping (e.g., RE in a Physical Resource Block (PRB); power control offset (e.g., a value of -8, ..., 15); power control offset with SS (e.g., -3 dB, 0 dB, 3 dB, 6 Db); ID scrambling; periodicity and offset; and / or QCL information (e.g., based on TCI status). An RS resource set can be a collection of one or more RS resources.

[0082] This document describes example attributes of authorization or assignment. The nature of authorization or assignment may include (but is not limited to) any one or more of the following: frequency allocation; aspects of time allocation (e.g., duration); priority; modulation and coding scheme (MCS); transport block size (TBS); number of spatial layers; number of transport blocks; TCI status; CRI; SRI; number of repetitions; type of repetition scheme (e.g., type A or type B); type of authorization (e.g., authorization type 1, authorization type 2, or dynamic authorization); type of assignment (e.g., dynamic assignment, semi-persistent scheduling (configured) assignment); configured authorization index or semi-persistent assignment index; periodicity of configured authorization or assignment; channel access priority class (CAPC); and / or any parameters provided in the DCI, by the MAC element, or by the RRC message used for scheduling authorization or assignment.

[0083] In one example, the indication of DCI may include, but is not limited to, any one or more of the following: explicit indication via the DCI field or via RNTI for masking PDCCH cyclic redundancy check (CRC); and / or implicit indication by attributes such as DCI format, DCI size, CORESET or search space, aggregation level, the first RE of the received DCI (e.g., the index of the first control channel element), wherein the mapping between attributes and values ​​can be signaled, for example, via RRC messages or MAC elements. Here, RS may be used interchangeably with one or more of RS resources, RS resource sets, RS ports, and / or RS port groups. Here, RS may be used interchangeably with any of SSB, CSI-RS, SRS, DMRS, Tracking Reference Signal (TRS), Positioning Reference Signal (PRS), and / or Phase Tracking Reference Signal (PTRS). Here, the reference signal (RS) can be any one or more of the following example signals, but not limited to: sounding reference signal (SRS); channel state information-reference signal (CSI-RS); demodulation reference signal (DM-RS); phase tracking reference signal (PT-RS); and / or synchronization signal block (SSB).

[0084] Here, a channel may refer to, but is not limited to, any one or more of the following example channels: PDCCH; PDSCH; Physical Uplink Control Channel (PUCCH); Physical Uplink Shared Channel (PUSCH); and / or Physical Random Access Channel (PRACH).

[0085] Here, key performance indicators (KPIs) may refer to, for example, but not limited to, one or more of the following indicators or indications: signal quality (e.g., L1-RSRP, SINR, CQI, RSSI, reference signal reception quality (RSRQ)); prediction performance (e.g., the percentage of Genie-assisted beams (i.e., the truly highest quality beams) that are part of the top K predicted beams; in other words, the percentage of times the truly best beam is included in the set of the top K predicted beams); link quality (e.g., throughput, block error rate (BLER)); data distribution (e.g., the mean and / or variance of measured and / or predicted beam measurements); RSRP (e.g., L1-RSRP) difference (i.e., the difference between the measured RSRP and the predicted RSRP of a beam).

[0086] Here, signals, (on the channel) information, transmissions, and messages (e.g., information and messages such as in DL or UL signals, DL or UL channels) can be used interchangeably. Here, RS resource sets can be used interchangeably with RS resources and / or beam groups (because a resource or resource set can correspond to a beam or beam group, and vice versa). Here, beam reporting can be used interchangeably with CSI measurements, CSI reports, and / or beam measurements. Here, the example process for beam resource prediction can be applied in a similar manner to beam resources belonging to a single cell or multiple cells and a single TRP or multiple TRPs. Here, CSI reports can be used interchangeably with CSI measurements, beam reports, and / or beam measurements. Here, set B can be used to refer to, but is not limited to, any one or more of the following: a set of RS resource sets; a set of beams; a set of beam pairs; a beam RS resource set; an RS resource set; and / or a beammap. Here, set A can be used to refer to, but is not limited to, any one or more of the following: a set of RS resource sets; a set of beams; a set of beam pairs; a beam RS resource set; an RS resource set; and / or a beam pattern.

[0087] This document discloses an example procedure for calculating KPIs that can be used in beam measurement processes. In one example, the WTRU can calculate KPIs based on AI / ML model outputs and / or RS measurements. The WTRU can calculate one or more KPIs for one or more sets B. For example, the WTRU can calculate the L1-RSRP difference by comparing the predicted L1-RSRP with the measured L1-RSRP. For example, the WTRU can use the best (i.e., highest quality) predicted beam to calculate BLER and / or calculate Top-K beam prediction accuracy.

[0088] As part of an example process for calculating KPIs, the WTRU may receive configuration information. For example, the WTRU may receive, but is not limited to, any one or more of the following configuration information: configuration information for an RS resource set having one or more RS resources associated with (e.g., all beams) of set A; and / or configuration information for an RS resource set having one or more RS resources associated with set B (e.g., a subset of beams of set A). The WTRU may measure the signals received on one or more RS resources to determine measured beam characteristics. Measured beam characteristics may include, but are not limited to, any of the following measurements: RSRP, L1-RSRP, SINR, CQI, RSSI, RSRQ, throughput, BLER, and / or data distribution parameters (e.g., the mean and / or variance of the measured L1-RSRP values).

[0089] The WTRU can calculate one or more KPIs based on one or more of the predicted and / or measured beam characteristics. In one example, the WTRU can calculate a link quality difference KPI (e.g., throughput and / or BLER difference) by calculating the difference between the highest link quality achieved via the measured beam (beams associated with set B) and the predicted beam (beams associated with set A). In one example, the WTRU can calculate a beam and / or signal quality difference KPI (e.g., RSRP, L1-RSRP, SINR, CQI, SINR, RSSI, and / or RSRQ difference) by calculating the difference between the highest measured signal quality and the predicted signal quality. In another example, the WTRU can calculate the data distribution difference between the measured beam quality and the predicted beam quality (e.g., RSRP, L1-RSRP, SINR, CQI, SINR, RSSI, and / or RSRQ). In yet another example, the WTRU can calculate the difference between the mean and / or variance of the measured and predicted beam quality. In another example, WTRU can calculate a prediction accuracy KPI, which can be, for example, the percentage of the best measured beam (e.g., according to L1-RSRP, SINR, BLER, or throughput, etc.) being one of the top K (e.g., K is an integer greater than or equal to 1) prediction beams.

[0090] The example procedure can be used to select and indicate the configured measurement beam resource set (i.e., referred to as set B, and equivalently as the (configured) RS resource set) based on KPIs. For example, the WTRU can receive configuration information for a cell-specific RS resource set (set A), configuration information for a WTRU-specific RS resource set (set B), and / or configuration information for candidate QCL hypotheses and corresponding thresholds. The WTRU can (dynamically) determine the need for new candidate QCL hypotheses and can select one or more new candidate QCL hypotheses based on KPIs.

[0091] According to an exemplary beam measurement procedure employing AI / ML, the WTRU can be configured (e.g., receiving configuration information from the gNB) to have a first set of beam measurement resources (equivalent to a first set of RS resources) "Set A" (e.g., having longer periods of RS transmission and / or being used for cell-specific RS transmissions). The WTRU can be configured (e.g., receiving configuration information from the gNB) to have a second set of beam measurement resources (equivalent to a second set of RS resources) "Set B" (e.g., having shorter periods of RS transmissions compared to those in Set A and / or being used for WTRU-specific RS transmissions). In one instance, Set A may include eight RS resources associated with eight beams b1, ..., b8. Set B may include four resources from eight possible resources, and there are no fixed beams (e.g., the association of beams with RS resources may not be fixed and may depend on, for example, QCL assumptions).

[0092] The WTRU can be configured with multiple candidate QCL hypotheses for set B. For example, QCL hypothesis candidate set #1 can be associated with beams b2, b4, b6, b8; QCL hypothesis candidate set #2 can be associated with beams b1, b3, b5, b7; QCL hypothesis candidate set #3 can be associated with beams b3, b4, b5, b6; and QCL hypothesis candidate set #4 can be associated with beams b1, b2, b7, b8. Set B can be initialized at the WTRU using a first QCL hypothesis (e.g., the default QCL hypothesis), which can be, for example, QCL hypothesis candidate set #1 associated with beams b2, b4, b6, b8.

[0093] The WTRU can be configured (e.g., receiving configuration information from a gNB) with a set of one or more KPIs. Examples of KPIs include, but are not limited to, the following performance metrics: throughput, Layer 1 Reference Signal Received Power (L1-RSRP) difference, number of beams satisfying the L1-RSRP, number of beams satisfying the Signal-to-Interference-Noise Ratio (SINR) threshold, input distribution, and / or output data distribution. The WTRU can be configured with a set of KPI thresholds such that each KPI is associated with one or more KPI thresholds.

[0094] In the following example, RSRP is used as a predicted beam quality for illustrative purposes, but it can be similarly replaced by other example signal quality metrics (e.g., L1-RSRP, SINR, CQI, RSSI, RSRQ, etc.). The WTRU can perform measurements on set B based on initial QCL assumptions and can determine the predicted RSRP value (or more generally, the signal quality value) for set A. The WTRU can perform measurements on set A based on received RS to determine the measured RSRP value for set A. The WTRU can determine the RSRP difference by calculating the difference between the predicted RSRP value for set A and the measured RSRP value for set A for each beam in set A. Based on the determined RSRP difference (or absolute RSRP) value (e.g., compared to a (KPI) RSRP threshold), the WTRU can determine whether new QCL assumptions for set B are needed. For example, when the RSRP difference is greater than or equal to the RSRP threshold, the WTRU can determine that new QCL assumptions for set B are needed, while when the RSRP difference is less than the RSRP threshold, the WTRU can determine that new QCL assumptions for set B are not needed.

[0095] In one example, if a new QCL hypothesis for set B is needed, WTRU can sort candidate QCL hypotheses according to the number of KPIs that satisfy the association threshold. Example KPIs may include, but are not limited to, any of the following example KPIs. An example KPI is the number of beams that satisfy the L1-RSRP threshold. WTRU can assess the number of beams that satisfy the L1-RSRP threshold if the mean and / or variance of the determined L1-RSRP difference (between the predicted RSRP values ​​and the measured RSRP values ​​for set A) satisfies one or more thresholds. Another example KPI is the number of beams that satisfy the L1-SINR threshold. WTRU can assess the number of beams that satisfy the L1-SINR threshold if the mean and / or variance of the L1-SINR difference (between the predicted SINR values ​​and the measured SINR values ​​for set A) satisfies one or more thresholds. Another example of a KPI is the input / output data distribution. WTRU can compare the distributions of inputs (e.g., measurements / predictions from a second RS resource set associated with set B) and outputs (e.g., measurements / predictions from a first RS resource set associated with set A).

[0096] The WTRU can determine a preferred set of B QCL hypotheses based on a ranking of candidate QCL hypotheses, the ranking being based on evaluated KPIs. The WTRU can report the preferred set of B QCL hypotheses to the gNB, and the WTRU can receive corresponding acknowledgments or confirmations from the gNB (e.g., via the Physical Downlink Control Channel (PDCCH), via the Dedicated Control Resource Set (CORESET), and / or from the search space of the gNB). When performing beam measurements, the WTRU can apply the reported set of B QCL hypotheses, for example, based on the report and / or confirmations.

[0097] According to one example, WTRU can be configured with one or more of the following configurations: a first set of one or more RS resources; a second set of one or more RS resources; a set of candidate QCL hypotheses; a set of KPIs; a set of thresholds; and / or a CORESET and / or a search space. These configurations are described below.

[0098] In one example, the WTRU may be configured with one or more first RS resources (e.g., corresponding to all beams, referred to as set A, with a longer period; e.g., for cell-specific RS transmissions). The first one or more RS resources may be configured in a first RS resource set (e.g., set A equals eight resources with beams b1, ..., b8). In one example, the WTRU may be configured with one or more second RS resources (e.g., corresponding to a subset of all beams, referred to as set B, with a shorter period; e.g., for WTRU-specific RS transmissions). The second one or more RS resources may be configured in a second RS resource set. The second RS resource set may be associated with the first RS resource set based on one or more explicit configurations and / or implicit configurations (e.g., configuring one or more RSs in the first and second RS resource sets). In one example, set B may include four resources without a defined beam.

[0099] In one example, the WTRU can be configured with one or more sets of candidate QCL hypotheses (e.g., for a second or more RS resources, or equivalently, a second set of RS resources). For example, the WTRU can be configured with one or more sets of candidate QCL hypotheses, and each set of QCL hypotheses may include one or more reference RS resources (e.g., reference RS resources for QCL type -D). Some of the one or more reference RS resources may be the same as some of the reference RS resources in the second or more RS resources. In one example, the WTRU can determine a set of candidate QCL hypotheses as the default / initial candidate QCL hypotheses. For example, the WTRU can determine a set of one or more candidate QCL hypotheses based on the order of the configured candidate QCL hypotheses (e.g., based on gNB configuration) (e.g., configuration of the default candidate QCL hypothesis set ID) and / or based on predetermined rules (e.g., lowest / highest candidate QCL hypothesis set ID, first / last configured candidate QCL hypothesis set, etc.). As an example, candidate QCL hypothesis set #1 can be associated with beams b2, b4, b6, and b8; candidate QCL hypothesis set #2 can be associated with beams b1, b3, b5, and b7; candidate QCL hypothesis set #3 can be associated with beams b3, b4, b5, and b6; and candidate QCL prediction set #4 can be associated with beams b1, b2, b7, and b8.

[0100] In the example, the WTRU can be configured with a set of KPIs such that the set of KPIs can be used, for example, to evaluate a first or more RS resources and / or a second or more RS resources. The KPIs in the KPI set can include, but are not limited to, any or more of the following performance indicators: throughput; ACK / NACK ratio; quality difference; number of RSs meeting a corresponding threshold; and / or input / output data allocation. Examples of KPIs are described below. For example, for the KPI throughput, the WTRU can evaluate throughput, for example, based on DL transmissions (e.g., if the WTRU has ongoing PDCCH and / or PDSCH transmissions within a time window). In another example, the WTRU can evaluate hypothetical throughput based on measured quality (e.g., RSRP). For example, for the ACK / NACK ratio, the WTRU can evaluate the ACK / NACK ratio (e.g., based on the ongoing PDCCH and / or PDSCH transmissions within a time window). In yet another example, the WTRU can evaluate hypothetical BLER based on measured quality (e.g., RSRP).

[0101] For example, for poor KPI quality, the WTRU can assess the quality difference based on predicted quality values ​​(e.g., measurements based on a second or more RS resources) and measured RSRP values ​​(e.g., measurements based on a first or more RS resources). For example, for the number of RSs meeting a corresponding threshold, the WTRU can determine the number of beams meeting the corresponding threshold (e.g., based on measurements performed on RSs received on the first or more RS resources and / or the second or more RS resources). For example, for KPI input / output data distribution, the WTRU can compare the distribution of a first set of measured and / or predicted quality (e.g., measured and / or predicted values ​​from the first or more RS resources and / or the second or more RS resources) and a second set of measured and / or predicted quality (e.g., measured and / or predicted values ​​from one or more inference inputs, the first or more RS resources, and the second or more RS resources). The measured and / or predicted values ​​from the inference inputs can be predefined or configured by an A gNB. For example, the quality and / or statistical values ​​(e.g., the mean and / or variance of the quality) of one or more measurements can be predefined and / or configured by the gNB. The quality value can be determined as any one or more of the following: RSRP, RSRQ, SINR, assumed PDCCH / PDSCH BLER, etc.

[0102] In one example, the WTRU can be configured with a set of thresholds. For instance, the WTRU can be configured with a set of thresholds for a set of KPIs. Each threshold can be associated with one or more KPIs in that set. The number of configured thresholds can be equal to the number of configured KPIs. In one example, the WTRU can be configured to have a CORESET / search space. In another example, the WTRU can be configured to have one or more CORESET / search spaces for receiving acknowledgment indications from the gNB.

[0103] In one example, the WTRU can perform measurements (e.g., by measuring the signal quality of RSs received on the resource) on a second or more RS resources (e.g., a second set of RS resources, set B). The measurements can be based on previously determined and / or indicated candidate QCL hypotheses. For example, the WTRU can receive indications of candidate QCL hypotheses to be applied to the second or more RS resources (e.g., via one or more of RRC, MAC CE, and DCI). In another example, if there are no previously determined / indicated candidate QCL hypotheses, the WTRU can perform measurements on the second or more RS resources based on default candidate QCL hypotheses. Based on this measurement, the WTRU can determine a value for the quality of the first or more RS resources. For example, if the RS received on the first or more RS resources is the same RS received on the second or more RS resources, the WTRU can use a measurement of signal quality (e.g., RSRP, SINR, CQI, L1-RSRP, RSSI, etc.). If the RS received on the first or more RS resources is not the same RS received on the second or more RS resources, the WTRU can determine a predicted value for the quality of the RS.

[0104] In one example, the WTRU can perform measurements (e.g., by measuring the signal quality of the RSs received on the resource) on a second or more RS resources (e.g., a first set of RS resources, set A). The measurements can be based on QCL assumptions (e.g., QCL type-D) previously determined / indicated for each RS received on the second or more RS resources. For example, the WTRU can receive indications of the QCL assumptions to be applied to each RS received on the first or more RS resources (e.g., via one or more of RRC, MACCE, and DCI).

[0105] In one example, the WTRU may determine or select a first set of KPIs (e.g., from this set of KPIs) (e.g., based on configuration / instructions from the gNB and / or predefined KPIs), and the WTRU may determine the corresponding value for each of the determined or selected KPIs. Based on the first set of KPIs and the corresponding value for each KPI, the WTRU may determine whether a new candidate QCL hypothesis determination process needs to be triggered. The first set of KPIs may include any one or more of the following: throughput; ACK / NACK ratio; and / or quality difference. For example, the WTRU may evaluate throughput (e.g., based on PDCCH and / or PDSCH transmissions received by the WTRU within a time window). In another example, the WTRU may evaluate the hypothetical throughput based on measured quality (e.g., RSRP). For example, the WTRU may evaluate the ACK / NACK ratio (e.g., based on PDCCH and / or PDSCH transmissions received by the WTRU within a time window). In yet another example, the WTRU may evaluate the hypothetical BLER based on measured quality (e.g., RSRP). For example, WTRU can assess the quality difference based on predicted signal quality values ​​(e.g., measurements of RSs received on a second or more RS resources) and measured signal quality values ​​(e.g., measurements of RSs received on a first or more RS resources having a first / second QCL assumption, respectively).

[0106] Based on the determined first set of KPIs and the corresponding values ​​for each KPI, the WTRU can determine whether a new candidate QCL hypothesis determination process needs to be triggered. For example, the determined first set of KPIs may include any one or more of the following: throughput; ACK / NACK ratio; and / or signal / RS / beam quality difference. For example, for the throughput KPI, the WTRU can determine whether a new candidate QCL hypothesis determination process needs to be triggered based on throughput. For example, if the throughput is below (or equal to) a corresponding threshold (e.g., insufficient performance), the WTRU may trigger a new candidate QCL hypothesis determination process. If the throughput is above the corresponding threshold (e.g., sufficient performance), the WTRU may not trigger a new candidate QCL hypothesis determination process.

[0107] For example, for the ACK / NACK ratio KPI, WTRU can determine whether a new candidate QCL hypothesis determination process needs to be triggered based on the ACK / NACK ratio. For instance, if the ACK / NACK ratio is below (or equal to) a corresponding threshold (e.g., insufficient performance), WTRU can trigger a new candidate QCL hypothesis determination process. If the ACK / NACK ratio is above the corresponding threshold (e.g., sufficient performance), WTRU may not trigger a new candidate QCL hypothesis determination process.

[0108] For example, for a poor quality KPI, the WTRU can determine whether a new candidate QCL hypothesis determination process needs to be triggered based on the quality difference. For instance, if the quality difference is below (or equal to) a corresponding threshold (e.g., good prediction accuracy), the WTRU can trigger a new candidate QCL hypothesis determination process (e.g., enabling mode prediction). If the quality difference is above the corresponding threshold (e.g., poor prediction accuracy), the WTRU may not trigger a new candidate QCL hypothesis determination process. In another example, if the quality difference is above a corresponding threshold (e.g., poor prediction accuracy), the WTRU can trigger a new candidate QCL hypothesis determination process (e.g., selecting a new beam pattern for good prediction accuracy). If the quality difference is below (or equal to) the corresponding threshold (e.g., good prediction accuracy), the WTRU may not trigger a new candidate QCL hypothesis determination process.

[0109] In one example, the WTRU can determine a second set of KPIs (e.g., based on this set of KPIs) (e.g., based on configuration / instructions from gNB and / or predefined KPIs) and the corresponding values ​​for each KPI. Based on the second set of KPIs and the corresponding values ​​for each KPI, the WTRU can determine one or more new candidate QCL hypothesis sets from the configured candidate QCL hypothesis set. The second set of KPIs may include, but is not limited to, any one or more of the following performance metrics: throughput; ACK / NACK ratio; quality difference; quality (e.g., RSRP, RSRQ, SINR, BLER (e.g., PDCCH / PDSCH) etc.); and / or input / output data allocation.

[0110] For example, for a throughput KPI, WTRU can assess that the average throughput and / or the variance of the throughput of a set of candidate QCL hypotheses (e.g., within a time window) are above a corresponding threshold. For example, WTRU can determine the number of RSs that meet the corresponding threshold (e.g., by assessing whether the measured and / or predicted throughput of each RS is greater than the corresponding threshold). For an ACK / NACK ratio KPI, WTRU can assess the variance of the average throughput and / or ACK / NACK ratio of a set of candidate QCL hypotheses relative to a corresponding threshold (e.g., within a time window). For example, WTRU can determine the number of RSs that meet the corresponding threshold (e.g., for each RS, determining whether the measured and / or predicted ACK / NACK ratio is greater than the corresponding threshold). For example, for a quality difference KPI, WTRU can assess that the average quality difference and / or the variance of the quality difference of a set of candidate QCL hypotheses (e.g., within a time window) are above a corresponding threshold. For example, WTRU can determine the number of RSs that meet the corresponding threshold (e.g., by determining whether the measured and / or predicted quality difference is less than the corresponding threshold for each RS). This quality can be determined by the UE performing signal quality measurements on the received RSs (e.g., RSRP, RSRQ, SINR, BLER, etc. of PDCCH and / or PDSCH). For example, the WTRU can evaluate the average quality and / or quality variance (e.g., within a time window) of a set of candidate QCL hypotheses and determine whether the evaluated average quality and / or quality variance is higher than a corresponding threshold. For example, the WTRU can determine the number of RSs that meet the corresponding threshold (e.g., RSs whose measured and / or predicted quality is greater than the corresponding threshold).

[0111] For example, for input / output data distribution KPIs, WTRU can compare the distribution of a first set of measurement and / or prediction quality (e.g., measurement and / or prediction quality values ​​based on RSs received on a first or more RS resources and / or a second or more RS resources) and a second set of measurement and / or prediction quality (e.g., measurement and / or prediction quality values ​​based on RSs received on a first or more RS resources and a second or more RS resources, based on one or more inferred inputs from an AI / ML model). WTRU can evaluate one or more first statistics (e.g., mean and / or variance) of the first set of measurement and / or prediction quality and one or more second statistics of the second set of measurement and / or prediction quality. For example, WTRU can determine the difference between the first and second statistics and compare that difference to a corresponding threshold (e.g., assess whether the difference between one or more statistics is greater than a corresponding threshold).

[0112] In one example, the WTRU can determine one or more new candidate QCL hypotheses, which can be based on, for example, a second set of KPIs (e.g., different from the first set of KPIs). For instance, the WTRU can rank the configured candidate QCL hypotheses based on values ​​determined for the second set of KPIs (e.g., based on the ranking order of the number of KPIs that satisfy a corresponding threshold for each configured candidate QCL hypothesis). Based on the determined rankings, the WTRU can determine or select one or more new candidate QCL hypotheses from the configured candidate QCL hypotheses. The number of the one or more new candidate QCL hypotheses determined can be based on a predetermined number and / or a value configured / indicated by the gNB.

[0113] In one example, the WTRU may indicate to the gNB the determination of one or more new candidate QCL hypotheses (e.g., by sending the indication via MAC CE and / or CSI report). For example, the WTRU may include any one or more of the following information when indicating to the gNB the determination of one or more new candidate QCL hypotheses: an indication of whether one or more new candidate QCL hypotheses were determined; and / or an indication of the determined new candidate QCL hypotheses. In one example, the WTRU may indicate to the gNB whether one or more new candidate QCL hypotheses were determined. For example, an indicator bit or flag set "0" may indicate no new candidate QCL hypotheses, and "1" may indicate new candidate QCL hypotheses. The indication of whether one or more new candidate QCL hypotheses were determined can be implicit. For example, the WTRU indicating one or more identical candidate QCL hypothesis IDs (the same IDs as the current QCL hypothesis) may imply to the gNB that no new candidate QCL hypotheses exist. A WTRU indicating one or more different new candidate QCL hypothesis IDs (i.e., IDs different from the current QCL hypothesis) may imply to the gNB that new candidate QCL hypotheses exist. In one example, the WTRU may indicate one or more new candidate QCL hypotheses. For example, the WTRU can indicate one or more set IDs of newly identified candidate QCL hypotheses. These new candidate QCL hypothesis set IDs can be based on one or more of the following: For example, the ID can be determined based on the set ID of the semi-statistical configuration of each candidate QCL hypothesis set. In another example, the new candidate QCL hypothesis set ID can be determined based on the activated QCL hypotheses (e.g., the WTRU can receive indications of activation / deactivation of one or more QCL hypothesis sets based on the configured QCL hypothesis sets (e.g., MAC CE and / or DCI).

[0114] In one example, in response to an indication / report from the WTRU regarding a determined new candidate QCL hypothesis sent to the gNB, the WTRU may receive one or more acknowledgment indications. For example, the WTRU may receive signals on the PDCCH in a configured CORESET and / or search space. In one example, signal reception on the PDCCH may be based on a configured CORESET and / or search space, such that the configured CORESET / search space can be used regardless of the type of QCL hypothesis determined by the WTRU. In another example, signal reception on the PDCCH may be configured based on two or more CORESETs and / or search spaces, such that two or more CORESETs / search spaces can be used for implicit indication. For example, if the WTRU receives a signal on the PDCCH in a first CORESET / search space, the WTRU may receive a first indication. If the WTRU receives a signal on the PDCCH in a second CORESET / search space, the WTRU may receive a second indication. The first and second indications can be one or more of the following: ACK / NACK (e.g., the first indication can indicate ACK, and the second indication can indicate NACK for WTRU indication / reporting); and / or new candidate QCL hypothesis selection (e.g., the first indication can indicate the candidate QCL hypothesis set for the first report, and the second indication can indicate the candidate QCL hypothesis set for the second report).

[0115] In one example, the WTRU may apply one or more sets of reported / indicated candidate QCL hypotheses to, for example, a second or more RS resources (e.g., within a second RS resource set). The WTRU's application of the one or more sets of reported / indicated candidate QCL hypotheses may be based on WTRU reports / instructions. For example, the WTRU may apply the one or more sets of reported / indicated candidate QCL hypotheses after an application time or period as indicated in the report / instruction. In another example, the WTRU may apply the one or more sets of reported / indicated candidate QCL hypotheses based on gNB confirmation. For example, the WTRU may apply the one or more sets of reported / indicated candidate QCL hypotheses after an application time or period indicated in the gNB confirmation.

[0116] Figure 3This is a flowchart illustrating process 300 as part of a beam management process for the WTRU to select and indicate a configured RS resource set (set B) and associated quasi-cooperative positioning (QCL) hypotheses. At 302, the WTRU can receive configuration information for RS resource set A from the gNB. RS resource set A may include resources for all beams associated with the gNB. At 304, the WTRU can receive configuration information for RS resource set B from the gNB, where RS resource set B is smaller than RS resource set A. RS resource set B may include resources for a subset of all beams associated with the gNB. At 306, the WTRU can receive configuration information for multiple candidate QCL hypothesis sets for RS resource set B (e.g., each QCL hypothesis corresponds to a resource in RS resource set B), where each QCL hypothesis set in the multiple candidate set B QCL hypothesis sets is associated with at least one RS resource in RS resource set A. At 308, the WTRU can receive information from the gNB indicating one or more key performance indicators (KPIs). Examples of KPIs may include, but are not limited to: throughput, L1-RSRP difference, number of RS resources that meet the L1-RSRP / SINR threshold, and input / output data distribution. WTRU can determine the value of at least one of the received KPIs.

[0117] At 310, the WTRU can perform measurements on the RS received on each resource in RS resource set B based on at least one of multiple candidate QCL hypothesis sets in RS resource set B. At 312, the WTRU can perform measurements on the reference signal (RS) received on resources in RS resource set A. At 314, the WTRU can select one of multiple candidate QCL hypothesis sets in set B based on the performed measurements and the determined values ​​of the received KPIs. At 316, the WTRU can send a message to the gNB reporting the selected set of QCL hypotheses in set B. Example methods can be used to determine and indicate the measurement beam resource set (set B) based on a single KPI. In one example, the WTRU can determine one or more WTRU-specific sets B and can report the determined set B that satisfies the KPI threshold of the highest-ranked KPI priority. The WTRU can receive configuration information for any one or more of the following parameters: one or more RS resource sets with RS resources; a set of KPI types and corresponding KPI thresholds; a set B indicating gNB configuration or an indication of WTRU-specific set B determination; set B determination parameters (e.g., set B size, set B type, set B determination rules); KPI priority ordering; and / or fallback set B determination parameters. The WTRU can measure received RSs associated with one or more RS resource sets. The WTRU can determine one or more sets B in response to receiving an indication to enable WTRU-specific set B determination, at least one set B determination parameter, and / or one or more measured RS resources.

[0118] The WTRU can calculate one or more KPI values ​​for one or more defined sets B based on one or more RS measurements. The WTRU can sort the defined sets B based on KPI priority ranking and the calculated KPI values, as well as KPI thresholds. The WTRU can report the selected set B, associated set B parameters, associated RS resources, one or more KPI values ​​and / or one or more KPI types determined based on the sorting of the defined sets B. For example, if at least one associated KPI value satisfies at least one associated KPI threshold, the WTRU can report only set B from one or more defined sets B. In one example, the WTRU can report the number of set Bs that satisfy at least one KPI threshold and the associated KPI types. If no defined set B satisfies one or more configured KPI thresholds, the WTRU can determine at least one fallback set B based on fallback set B determination parameters and RS resources of one or more measurements. The WTRU can report any one or more of the following: indication of fallback set B; indication of the determined fallback set B and / or associated RS resources; and / or any KPI thresholds satisfied by the determined fallback set B.

[0119] In one example, the WTRU may receive configuration information for any one or more of the following: For example, the configuration information may include information indicating one or more sets of RS resources with RS resources. For example, the configuration information may include information indicating the KPIs to be used (e.g., in bitmap form) and information indicating the corresponding KPI thresholds (e.g., performance metrics related to beam prediction accuracy, link quality, input / output data distribution based on AI / ML models, and / or the L1-RSRP difference between predicted and measured L1-RSRPs). For example, the configuration information may include information indicating one or more sets of RS resources associated with set A (e.g., having a larger periodic window than set B for beam scanning). For example, the configuration information may include an indication (e.g., WTRU_SetB_SelectType) for indicating set B configured by the gNB or determined by the WTRU. For example, configuration information may indicate the size of set B (e.g., fixed N beams, max_SetB_size, or no preference), the type of set B (e.g., fixed, random, or no preference, etc.), and / or the rules for determining set B (e.g., uniform, where, for example, each Nth beam associated with set A is part of set B). For example, configuration information may include a KPI level indicator bitmap. In another example, configuration information may include default / fallback rules for determining set B (e.g., a random set B of size N beams, a uniform set).

[0120] The WTRU can measure RSs associated with one or more RS resource sets. Based on WTRU_SetB_SelectType, the WTRU can input RS measurements into an AI / ML model based on the received B configuration set. For example, set B can be determined by rules (e.g., set B type, set B size, or pre-configured set B as part of the WTRU's capabilities). For example, set B can consist of a random set of RS measurements from different cell-specific set Bs. The WTRU can compute KPIs based on the AI / ML model output and / or RS measurements. The WTRU can indicate the set B with the highest value KPI (e.g., via CRI RS indication, set B size and / or type of the random set B) that satisfies a KPI threshold with the highest possible KPI_rank. The WTRU can send indications based on set B determined by a single KPI indication, multiple KPI indications, or fallback rules. Based on a single KPI indication, the WTRU can send indications of the KPIs associated with the indicated set B (e.g., using a bitmap). Based on a single KPI indicator, WTRU can indicate the number of sets B with the highest KPI values ​​that satisfy KPI thresholds other than the highest KPI _rank. WTRU can also indicate other KPI thresholds that are satisfied (e.g., using a bitmap). If no set B satisfies the configured KPI thresholds (i.e., it can be used as a fallback rule indicator), WTRU can indicate set B based on the fallback rule and any KPI thresholds satisfied by the fallback set B (i.e., in addition to the configured criteria).

[0121] The WTRU can be configured with one or more KPIs (e.g., by receiving instructions or configuration information) and associated thresholds for determining and / or selecting set B. The WTRU can determine and / or select set B that satisfies one or more KPIs and report the determined and / or selected set B to the gNB, for example, using any of the following example processes that can be used by the WTRU.

[0122] In the example process, the WTRU can receive configuration information for the selection and / or determination of set B. The WTRU can receive one or more of the following configuration information and / or parameters (e.g., via RRC signaling, and / or MAC-CE indication, and / or DCI indication) from the gNB to perform KPI-based set B determination / selection and to indicate to the gNB the determined / selected set B and associated parameters. In one example, the WTRU can receive information indicating one or more RS resource sets (e.g., one or more CSI-RS resource sets and / or one or more SSB resource sets). The WTRU can measure the RSs associated with one or more configured RS resource sets. The WTRU can use measured RS beam quality values ​​and predicted RS beam quality values ​​(e.g., RSRP, class of each beam) to calculate KPIs for one or more candidate sets B. In one example, the WTRU can receive information indicating one or more KPIs to be used for beam set B determination and corresponding KPI thresholds. For example, the WTRU can be configured with a first KPI set. The WTRU can receive further configuration information or indications from the gNB (e.g., via MAC-CE indication and / or DCI indication), which serve as a second set of KPIs to be used for a subset of the first KI set determined by set B (e.g., a bitmap where each bit corresponds to a KPI and a bit value of 1 indicates that the corresponding KPI belongs to the second KPI set). The indicated KPIs may be related to, for example, beam prediction accuracy; link quality; performance metrics of input and output data distribution based on AI / ML models; and / or the difference between predicted beam quality and measured beam quality (e.g., L1-RSRP). In one example, the WTRU may receive information indicating one or more RS resource sets associated with set A. (e.g., having a beam scan ratio compared to set B (T...) B The associated period is a larger period (T) A ), where, for example, T A >T B ).

[0123] In one example, the WTRU may receive information indicating parameters or rules for determining candidate set B. Examples of parameters or rules for determining candidate set B may include, but are not limited to, any of the following: the size (cardinality) of set B; the maximum number of beams in set B (max_setB_size); an indication that the size of set B is not specified; the type of set B (e.g., fixed, random, or unbiased); and / or the combination of B determination rules (e.g., uniform). In another example, the WTRU may receive information indicating one or more candidate sets B. In one example, the WTRU may use a set B selection process of a certain type (WTRU_SetB_SelectType). For example, if WTRU_SetB_SelectType = 1, the WTRU may determine one or more candidate sets B based on set B determination parameters and / or rules, and may select set B based on KPIs of set B. If WTRU_SetB_SelectType = 0, the WTRU may select one or more sets B from candidate sets B based on one or more KPIs. In the example, the WTRU may receive an order of KPIs or a sorting order of a set of KPIs. For example, the WTRU can receive the rank of each KPI or the rank of a set of KPIs (e.g., the rank order of a second set of KPIs). In one example, the WTRU may be pre-configured with a set of sorting orders associated with the KPI set (e.g., via RRC signaling). The WTRU can also dynamically receive indications of the set of sorting orders associated with the KPI set (e.g., bit sequences with values ​​such as 00, 10, 11, ..., where each bit sequence value corresponds to a position in a pre-configured sorting order by the WTRU), wherein such indications may be received, for example, via MAC-CE indications and / or DCI indications. In one example, the WTRU may receive default or backoff rules for determining set B (e.g., a random set B of size N beams, or a uniform set B). In one example, the WTRU may receive default or backoff rules for selecting set B (e.g., set B with the highest indicated, configured, or selected KPIs).

[0124] The example procedure can be used to indicate to the gNB the selection of one or more sets B. The WTRU can select one or more sets B based on the determination of a single KPI and can indicate the selected set B to the gNB (e.g., by signaling on the PUCCH or PUSCH). In one example, to indicate the selected set B when candidate set B is configured by the gNB (e.g., when WTRU_SetB_SelectType = 0), the WTRU can indicate the identifier (e.g., index) of each set B and / or parameters associated with the selected set B (set B size and / or type). In another example, the WTRU can indicate the selected set B to the gNB as a bitmap (e.g., by signaling on the PUCCH or PUSCH) (e.g., each bit in the bitmap represents a candidate set B, a bit value "1" indicates that the corresponding set B has been selected, and a bit value "0" indicates that the corresponding set B has not been selected). To indicate the selected set B, when the candidate set B is determined by WTRU based on parameters and / or rules for the candidate set B (e.g., WTRU_SetB_SelectType = 1), WTRU can indicate the RS (e.g., CRI) associated with set B.

[0125] In one example, the WTRU can indicate to the gNB the KPIs selected for each set B and / or the KPI values ​​for the selected set B (e.g., by signaling on the PUCCH or PUSCH). If the determined and / or selected set B is based on the fallback rules configured on the gNB, the WTRU can indicate to the gNB associated with the fallback procedure used (e.g., using a bit indication transmitted in a message or signal using the PUCCH or PUSCH). If the WTRU is configured with multiple fallback rules, the WTRU can indicate the fallback rule used (e.g., by transmitting a bitmap using the PUCCH or PUSCH). The WTRU can indicate one or more KPIs satisfied by each set B determined using the fallback rules.

[0126] The example procedures can be used to select a single KPI for set B. In one example, if the WTRU is configured with a single KPI and / or receives an indication of a single KPI, the WTRU can use that KPI and an associated KPI threshold to perform set B selection. If the WTRU is configured with multiple KPIs and / or receives indications of multiple KPIs, the WTRU can select a single KPI based on the level of each of one or more KPIs (e.g., selecting the KPI with the highest level). Based on the selected or determined KPI and the associated threshold, the WTRU can select one or more sets B using one or more of the procedures described herein, based on configurations and / or indications received from the gNB (e.g., via RRC signaling, MAC-CE indications, and / or DCI indications).

[0127] The example procedure can be used to select one or more sets B based on a single selected KPI. The WTRU can use one or more of the following procedures to select one or more sets B based on a single selected KPI. In the example procedure, if the selected KPI exceeds a threshold (selected, configured, or indicated), the WTRU can select candidate and indicate set B (e.g., set B with the highest KPI). The WTRU can send an indication of the selected set B to the gNB (e.g., via PUCCH or PUSCH). The WTRU can also indicate the number of additional candidate sets B that satisfy the threshold of the selected KPI. In one example, the WTRU can select all candidate sets B that have KPIs exceeding the threshold associated with the (selected, indicated, or configured) KPI. In one example, if no candidate set B satisfies the threshold of the selected KPI, the WTRU can select the set B with the highest selected KPI. The WTRU can send an indication to the gNB that the selected set B does not meet the KPI threshold (e.g., by indicating, for example, via a single bit with a value of "0", that the selected set B or candidate set B does not meet the threshold KPI, or otherwise report the KPI of the selected set B).

[0128] When the WTRU is configured and / or indicated to have a set of KPIs, the sample procedure can be used to select one or more sets B based on a single KPI. For each indicated and / or configured KPI, the WTRU can select one or more candidate sets B. In one example, for each KPI, the WTRU can select a candidate set B (e.g., the candidate set B with the highest KPI value). In another example, for each KPI, if the KPI value exceeds a threshold associated with that KPI, the WTRU can select a candidate set B (e.g., the candidate set B with the highest KPI value). In addition to indicating the selected set B, the WTRU can also indicate the associated KPIs for each set B selected to the gNB (e.g., via a bitmap, where each bit corresponds to a KPI). The WTRU can indicate the number of candidate sets B that satisfy each KPI.

[0129] The example procedure can be used to select and indicate cell-specific measurement beam resource sets (e.g., set B) based on multiple KPIs. In one example, the WTRU can report the identifier of set B (and RS resources), where the WTRU determines that multiple KPI values ​​meet a threshold. The WTRU receives configuration information for configuring any one or more of the following: one or more RS resource sets associated with one or more sets B; sets of KPI types; a max_SetB indicator indicating the maximum number of sets B to report; KPI type weights; and / or multiple KPI score thresholds. The WTRU can measure the RS resources of one or more RS resource sets. RS resource sets can be associated with one or more configured sets B. The WTRU can calculate one or more KPI values ​​for one or more sets B based on the measured RS resources of one or more RS resource sets associated with one or more sets B. The WTRU can calculate one or more multiple KPI scores for one or more sets B based on the KPI type weights and the calculated KPI values. The WTRU can sort all sets B according to their multiple KPI scores, based on the order in which their multiple KPI scores meet the configured multiple KPI score thresholds. WTRU can report the indices of the top k sets B that satisfy the configured multi-KPI score thresholds, where k is less than or equal to the configured number of sets B, and k is less than or equal to the maximum number of sets B used for reporting (e.g., max_SetB). WTRU can also report the CRIs of the RS resources associated with the k sets B.

[0130] In one example, the WTRU can receive configuration information for any of the following parameters: Configuration information can be used for one or more RS resource sets, where the RS resources of the RS resource sets correspond to beams of a specific set B. Configuration information can be used for KPIs (e.g., bitmaps) to be used (e.g., beam prediction accuracy related, link quality related, performance metrics of input / output data distribution based on AI / ML models, and / or L1-RSRP difference between prediction measurements). Configuration information can be targeted at one or more RS resource sets associated with set A (e.g., having a larger periodic window than set B beam scans). The configuration information can be targeted at the max_SetB indicator indicating the maximum number of set B to be reported. Configuration information can be used to indicate WTRU_SetB_toggle, which indicates either cell-specific (e.g., value '1') or WTRU-specific (e.g., value '0') set B. Configuration information can be used for KPI weights and multi-KPI score thresholds. For example, KPI weights might have values ​​of 20%, 30%, and 50% for beam prediction accuracy, BLER, and L1-RSRP difference, respectively.

[0131] The WTRU can measure RSs associated with one or more RS resource sets. An RS resource set can be associated with one or more configured sets B. Based on the WTRU_SetB_ toggle, the WTRU can input the measurement results into an AI / ML model of a beam belonging to one or more (gNB configured) sets B, and the WTRU can calculate the KPIs of one or more sets B. The WTRU can calculate multi-KPI scores for one or more sets B based on KPI weights and the calculated KPIs. The WTRU can sort all sets B that meet the multi-KPI score threshold according to their multi-KPI scores. The WTRU can send a one-bit indication, for example, indicating the set B identifier based on multi-KPI (e.g., value '0') or single KPI (e.g., value '1'). The WTRU can send an indication of the CRI of the RS resource set associated with the set B ranked up to max_SetB. The WTRU can send an indication of the highest-ranked set B (e.g., a 1-bit indication value "1" if ranked highest, otherwise an indication value "0"). If at least one set B satisfies the multiple KPI score threshold, the WTRU can send an indication value of "1"; otherwise, an indication value of "0".

[0132] The example procedure can be used for configuration of selecting sets B(s) based on multiple KPIs. WTRU can be configured with one or more of the following parameters to determine, select, and indicate sets B based on multiple KPIs: one or more RS resource sets; one or more KPI types; weights associated with KPI types; multiple KPI score thresholds; and / or the maximum number of sets B to be reported (e.g., the max_SetB indicator).

[0133] In an example KPI with one or more RS resource sets, the WTRU can be configured with one or more first RS resource sets. For example, the first resource set could correspond to set B beams / measurement beams / transmit beams. In one example, the WTRU can be configured with a second RS resource set. For example, the second RS resource set could correspond to set A beams, which includes both measured / transmitted beams and predicted beams (skipped beams). In one example, the WTRU can be configured to have a set A period greater than the set B period. In one example, the WTRU can be configured to have QCL relationships for one or more resources in set B. The WTRU can be configured to have default QCL relationships and / or assumptions. The WTRU can be configured to have one or more candidate QCL relationships and / or assumptions.

[0134] In one or more example KPI types, the WTRU can be configured to have one or more KPI types suitable for selection of set B. For example, a KPI type can be associated with link quality. Link quality can be measured based on, for example, L1-RSRP, RSRQ, CQI, SINR, PDCCH BLER, and / or ACK / NACK ratio. In one example, a KPI type can be associated with beam prediction accuracy. In one example, beam prediction accuracy can be represented as the difference between link quality based on the difference between predicted and actual measurements. For example, a KPI type can be associated with a performance metric of the input / output data distribution based on an AI / ML model. For example, the WTRU can be configured to determine the difference between the statistics of the predicted beam and the actual measured beam. For example, a KPI type can be associated with the L1-RSRP difference between the predicted and measured beams. For example, a KPI type can be associated with the size of set B. For example, a smaller set B size can be prioritized over a larger set B size. In one example, WTRU can be configured with supported KPIs, and a subset of the supported KPIs can be selected for configuration of set B (i.e., applicable KPIs). In one example, the applicable KPIs can be configured to reference a bitmap of supported KPIs.

[0135] In the example KPI with weights associated with KPI type, WTRU can be configured with one or more weights associated with the KPI type. For example, weights can be used to configure each KPI type to indicate the relative importance of different KPI types. For example, WTRU can be configured with weight values ​​of 20%, 30%, and 50% for beam prediction accuracy, BLER, and L1-RSRP difference, respectively. In the example KPI with multiple KPI score thresholds, WTRU can be configured with multiple KPI score thresholds. For example, a threshold can indicate the minimum score required to meet the reporting requirements of set B. To determine, select, and / or indicate set B based on multiple KPIs, WTRU can be configured to have a maximum number of sets B to report (e.g., a max_SetB indicator).

[0136] In one example, the WTRU can be configured to have an indication of whether set B is WTRU-specific or cell-specific. In one example, this indication can be configured as a single-bit indication, where a value of "0" or the absence of this indication can be interpreted as a cell-specific configuration of set B, while a value of "1" can indicate a WTRU-specific configuration of set B (and vice versa).

[0137] The example procedure can be used by a WTRU to select a candidate set B based on multiple KPIs. In one example, the WTRU can be configured with RS resources of one or more RS resource sets. The RS resource sets can be associated with one or more configured sets B. The WTRU can be configured with pre-configured criteria to select cell-specific measurement beams (set B). For example, the pre-configured criteria can be based on multiple KPIs. In one example, the WTRU can derive multiple KPIs for each RS resource set. In the example, the WTRU can jointly consider the values ​​of multiple KPIs to select candidate set B. In one example, the WTRU can be configured with a bitmap of applicable KPIs. Based on the received configuration, the WTRU can determine a subset of supported KPI types (i.e., applicable KPI types). In the example, for each applicable KPI type, the WTRU can determine one or more KPI values ​​for one or more sets B based on the measured RS resources from the pre-configured RS resource sets. For example, the WTRU can derive KPI values ​​and / or statistics associated with the KPI values. For example, the WTRU can derive KPI values ​​within a pre-configured time interval. For example, the pre-configured time interval can be a function of the periodicity of the RS resources from the resource sets.

[0138] In one example, WTRU can be configured with weights associated with each KPI type. WTRU can derive a KPI score for each KPI value based on pre-configured weights associated with the KPI type. For example, the weights could be an implicit mechanism for prioritizing the most relevant KPIs. WTRU can compare KPI scores to a multi-KPI score threshold. For example, a KPI score could be a weighted sum of KPI values ​​associated with one or more RS resource sets. If the KPI scores of set B are greater than the multi-KPI score threshold, WTRU can consider set B as a candidate for selection. WTRU can be configured to select set B with the highest multi-KPI scores. WTRU can be configured to indicate the top n sets B with the highest multi-KPI scores within the candidate set B, such that the value of n can be pre-configured.

[0139] In one example, the WTRU can be configured to determine the multi-KPI scores of the default QCL hypothesis. For example, the WTRU can be configured to compare the multi-KPI scores of candidate QCL hypotheses. For example, if the multi-KPI score of at least one candidate QCL hypothesis is greater than the multi-KPI score of the default QCL hypothesis by a pre-configured threshold, the WTRU can be configured to select a candidate QCL hypothesis. If the multi-KPI score of a candidate QCL hypothesis is less than the multi-KPI score of the default QCL hypothesis, the WTRU can be configured to select the default QCL hypothesis. In one example, if none of the candidate QCL hypotheses are higher than the pre-configured multi-KPI score threshold, the WTRU can be configured to select the default QCL hypothesis.

[0140] The example procedure can be used to indicate the WTRU of a selected candidate set B. WTRU can be configured to indicate the selected candidate set B(s). In the example, WTRU can be configured to indicate the best candidate set B based on the highest multi-KPI score. In one example, WTRU can be configured to indicate the top n sets of candidates B, such that the value of n can be pre-configured as max_SetB of WTRU. In one example, WTRU can implicitly indicate the set B that ranks highest in terms of multi-KPI score, for example, by including it as the first set B in the feedback message. In another example, WTRU can explicitly indicate the highest-ranking set B among the indicated candidate sets B. In one example, WTRU can indicate whether at least one set B in the indicated candidate sets B is above a multi-KPI score threshold. For example, if at least one set B meets the multi-KPI score threshold, WTRU can indicate the value '1', otherwise it indicates the value '0'.

[0141] In one example, WTRU can be configured to report the indices of the top k sets B that have multi-KPI scores greater than a configured multi-KPI score threshold, where k is less than or equal to the configured number of sets B, and k is less than or equal to the maximum number of sets B to report (e.g., max_SetB). In one example, WTRU can indicate whether the selection of set B is based on multi-KPI or single-KPI. In another example, WTRU can be configured to implicitly or explicitly indicate the multi-KPI scores associated with candidate sets B. For example, WTRU can indicate that candidate sets B(s) are ordered in descending order of multi-KPI scores. Alternatively, WTRU can explicitly indicate the multi-KPI score associated with each of the selected candidate sets B.

[0142] In one example, the WTRU can report the CRI of the RS resource associated with the indicated candidate set B. In another example, the WTRU can indicate the selected candidate set B in a MAC CE or other message. In yet another example, the WTRU can indicate the selected candidate set B in an Uplink Control Information (UCI). In one example, the WTRU can be configured to indicate candidate set B periodically. In yet another example, the WTRU can be configured to indicate candidate set B(s) based on pre-configured events. An example pre-configured event is when candidate set B becomes better than the default QCL assumption in terms of multiple KPI scores. Another example of a pre-configured event is when the default QCL assumption becomes better than the currently configured QCL assumption. Yet another example of a pre-configured event is when a candidate QCL assumption becomes better than the currently configured QCL assumption.

[0143] In one example, the WTRU can be configured to indicate the multi-KPI scores of the default QCL hypothesis and candidate QCL hypotheses. In another example, the WTRU can indicate either the default or candidate QCL hypothesis based on conditions. For example, if the multi-KPI scores of at least one candidate QCL hypothesis are greater than the multi-KPI scores of the default QCL hypothesis by a pre-configured threshold, the WTRU can be configured to indicate a candidate QCL hypothesis. If the multi-KPI scores of a candidate QCL hypothesis are less than the multi-KPI scores of the default QCL hypothesis, the WTRU can be configured to indicate the default QCL hypothesis. In another example, if none of the candidate QCL hypotheses are above a pre-configured multi-KPI score threshold, the WTRU can be configured to select the default QCL hypothesis.

[0144] The example procedure can be used to determine and indicate WTRU-specific measurement beam resource sets (sets B) based on multiple KPIs. The WTRU determines one or more WTRU-specific sets B and reports the determined sets B that meet the multiple KPI thresholds. In one example, the WTRU may receive configuration information for the following parameters: one or more RS resource sets with RS resources; sets of KPI types; an indication to enable WTRU-specific set B determination; set B determination parameters (e.g., set B size and / or set B type and / or set B determination rules); KPI type weights and multiple KPI score thresholds; and / or fallback set B determination parameters.

[0145] The WTRU can measure RSs associated with one or more RS resource sets. The WTRU can determine one or more sets of RSs based on a reception indication that enables WTRU-specific set B determination, at least one set B determination parameter, and one or more measured RS resources. The WTRU can calculate one or more KPI values ​​for one or more determined sets of RSs based on one or more RS measurement results. The WTRU can calculate multi-KPI scores for one or more determined sets of RSs based on KPI type weights and one or more calculated KPI values. The WTRU can report the determined set of RSs with the highest multi-KPI score (including the associated RS resource and at least one set B determination parameter). For example, the WTRU can (only) report determined sets of RSs that meet a multi-KPI score threshold. In one example, the WTRU can report the number of other determined sets of RSs that meet the multi-KPI score threshold. If no determined set of RSs meets the configured multi-KPI score threshold, the WTRU determines at least one fallback set of RSs based on fallback set B determination parameters and one or more measured RS resources. The WTRU can indicate a set of RSs based on fallback rules and any KPI thresholds met by the fallback set of RSs. WTRU can report at least one of the following: indication of rollback set B, the determined rollback set B and / or associated RS resources.

[0146] In one example, the WTRU may receive configuration information for any one or more of the following parameters: one or more RS resource sets with RS resources; KPIs to be used (e.g., as a bitmap) (e.g., performance metrics related to beam prediction accuracy, link quality, input / output data distribution based on AI / ML models, L1-RSRP difference between predicted and measured beam quality); an indication WTRU_SetB_toggle that indicates set B as cell-specific ('0') or WTRU-specific ('1'); one or more RS resource sets associated with set A (e.g., having a larger periodic window than set B's beam scan); and the size of set B (e.g., fixed N beams, max_SetB_...). Size or no preference); set B type (e.g., fixed, random, or no preference); set B determination rules (e.g., uniform); KPI weights and multi-KPI score thresholds (e.g., weights of 20%, 30%, and 50% for beam prediction accuracy, BLER, and L1-RSRP difference, respectively); and / or default / fallback rules for set B determination (e.g., a random set B of size N beams, or a uniform set B).

[0147] WTRU can measure RSs associated with one or more RS resource sets. Based on the WTRU_SetB_toggle, WTRU can input RS measurements into an AI / ML model based on the received SetB configuration (e.g., a SetB determined by rules such as SetB type, SetB size, or pre-configured SetB as part of WTRU capabilities). In one example, SetB could consist of a random set of RS measurements from different cell-specific SetBs.

[0148] WTRU can compute KPIs based on AI / ML model output and / or RS measurements. WTRU can compute multi-KPI scores for one or more sets B based on KPI weights. WTRU can indicate that set B (e.g., using an RS indicator via CRI, or set B size and type of a random set B) has the highest multi-KPI score that satisfies the multi-KPI score threshold and the computed KPI. WTRU can send an indication of set B determined based on a single KPI, multi-KPI, or fallback rule. Based on the multi-KPI indication, WTRU can send an indication of the number of other set Bs that satisfy the multi-KPI score threshold. In one example, the number of random set Bs or the number of fixed set Bs can be indicated by WTRU to gNB. If no set B satisfies the configured KPI threshold (which can be used as a fallback rule indication), WTRU can indicate set B based on the fallback rule and any KPI thresholds satisfied by the fallback set B (i.e., in addition to the configured criteria).

[0149] To identify one or more sets B and report the identified sets B that meet single or multiple KPI requirements, the WTRU and / or gNB may send and / or receive example indications, signaling (e.g., control and data signaling), messages, configurations, and rules. This signaling may include, but is not limited to: broadcast signaling; RRC signaling; MAC CE; initial access messages; and / or transmission on the (L1) channel. For example, for broadcast signaling, the WTRU may access / retrieve information on set B via any of the System Information Block (SIB), Positioning SIB (posSIB), and / or SSB (e.g., where there are no security / privacy issues when sharing set B). For example, for RRC signaling, the WTRU may send / receive any of the request messages, response messages, and / or configuration messages associated with the identification of set B via RRC messages. For example, for MAC CE, the WTRU may send / receive any of the request messages, response messages, configuration messages, and activation / deactivation indications associated with the selection and / or activation of one or more sets B in one or more MAC CEs. For example, the initial access message may include, but is not limited to, Msg1, Msg2, Msg3, Msg4, Msg5, Msg A, and / or Msg B. For example, the L1 channel may include PUCCH, PUSCH, PDCCH, and / or PDSCH.

[0150] In one example, the WTRU can receive a general configuration from the network (e.g., via a gNB). For instance, the WTRU can be configured with a measurement set (set B) of one or more beam / beam pairs, which is fed into an AI / ML model to predict the optimal beam / beam pair in set A. The WTRU can receive a configuration including one or more RS resource sets, where the RS resources correspond to one or more sets B. The WTRU can also receive one or more RS resource sets, where the RS resources correspond to one or more sets A, for example, having a larger period than the beam scan of set B.

[0151] Example procedures can be used to provide information about KPIs and / or KPI rules / configurations. In one example, the WTRU can receive one or more KPIs for one or more sets B. For example, the WTRU can receive KPIs in bitmap or mapping table form. The WTRU can receive associations used between KPIs and set B. As an example of association, KPI x is used for a random set B, and KPI y is used for a fixed set B. Examples of KPIs that the WTRU can configure include, but are not limited to, KPIs related to beam prediction accuracy, link quality, performance metrics of input / output data distribution based on AI / ML models, L1-RSRP / L1-RSRQ measurement results and / or the difference between the predicted beam / RS quality and the measured beam / RS quality. KPIs can be grouped into categories, and the WTRU can receive information about the groups from the network. For example, for a fixed set B of a certain size, the WTRU can use KPIs related to beam prediction accuracy (e.g., L1-RSRP, the difference between consecutive L1-RSRP measurements) based on the received information. For a random set B, the WTRU can use KPIs related to channel measurement results (CQI, PMI, etc.). The WTRU can be configured with one or more thresholds corresponding to each KPI and / or multiple KPI thresholds corresponding to several selected KPIs. For example, the WTRU can be configured to assign weights of 20%, 30%, and 50% respectively to beam prediction accuracy, BLER, and L1-RSRP difference. The WTRU can be configured with a set of rules regarding the weighting of multiple KPIs. As an example, if BLER and L1-RSRP are used as multiple KPIs, a weight of (50%, 50%) is used, while if beam prediction accuracy and BLER are used as multiple KPIs, a weight of (60%, 40%) is used.

[0152] The example procedure can be used to provide information about set B and the rules / parameters used to determine set B. Such information may include, but is not limited to, the following: measurement beam set and / or beam pair set B can be WTRU-specific, cell-specific, WTRU-specific group, cell-specific group, tracking area-specific, and / or cell-specific type (e.g., macro cell deployment specific vs. small cell deployment specific). The WTRU can receive information about the suitability of set B from the network (e.g., from the gNB). In one example, this information can be in the form of a one-bit toggle type indication (e.g., WTRU_SetB_toggle, indicating cell-specific ('0') or WTRU-specific ('1') set B). For example, in cases where set B can be specific to a type of cell or a group of cells, more bits can be used to transmit higher-granularity information. For example, some additional bits can be used to indicate cell IDs and / or cell ID groups.

[0153] The WTRU can receive information about the size and / or type of set B to be used. Size information may include, for example, the number of fixed N beams in set B, and a `max_setB_size` indicated by the number of bits, bytes, or Mbits. The WTRU can receive information about the type of set B (e.g., fixed or random). A fixed 1-bit field may exist to configure the type of set B, for example, "1" for a fixed set B and "0" for a random set B. Multi-bit indicators can be used to indicate the type and size of set B. In one example, no preference may be indicated.

[0154] The WTRU can be configured with rules / parameters for determining set B. For example, in some cases, the WTRU may be able to use a mixed and / or random set B to adapt to different environments with greater flexibility (e.g., a mixed set B for small and large cells). In one example, the WTRU can be configured to prioritize performance over flexibility. Set B selection can be performance-dependent. For example, the WTRU may be allowed to use the flexibility of a mixed / random set B as long as performance remains above a certain threshold (e.g., as long as beam prediction accuracy is greater than a corresponding threshold). The WTRU can also be configured with set B switching rules. In one example, the WTRU can be configured to measure the performance of the selected / determined set B within a pre-configured time window after selection as the measurement beam set. If the performance falls below a threshold, the WTRU can switch to another set B (e.g., one with a larger size or a fixed type specific to the current scenario to improve accuracy).

[0155] The WTRU can be configured with fallback rules. For example, if no set B meets a configured single KPI threshold or multiple KPI thresholds, the WTRU can fall back to the default set B. In one example, the default set B could be a random set B with the flexibility to adapt to various scenarios / configurations. The WTRU can be configured to determine at least one fallback set B based on fallback set B determination parameters and one or more measured RS resources. The WTRU can indicate set B based on fallback rules and any KPI thresholds that the fallback set B meets. For example, the WTRU can report at least one of the following: the fallback set B, the determined fallback set B, and / or an indication of the associated RS resources to said fallback set B.

[0156] This document describes examples of WTRU behavior. Examples of WTRU behavior (e.g., following configuration received from the network) used to identify one or more WTRU-specific sets B and report selected sets B that meet multiple KPI thresholds may involve any one or more of the following WTRU actions. In one example, the WTRU may measure RSs associated with one or more RS resource sets, where RS resources correspond to one or more sets B. The WTRU may calculate KPIs based on AI / ML model outputs and / or RS measurement results, with exemplary KPIs including throughput, L1-RSRP, L1-RSRQ, L1-RSRP difference, SINR, the number of beams / beam indices that meet L1-RSRP, L1-RSRQ, and / or SINR thresholds. The WTRU may calculate a single KPI or multiple KPI scores for one or more sets B based on KPI weights. The WTRU may indicate that a set B has the highest multiple KPI score that meets multiple KPI score thresholds and the calculated KPI (e.g., by sending RS indications via CRI, set B size, set B type, random set B, and / or fixed set B). If no set B meets the configured KPI threshold (rollback rule indication), the WTRU can indicate set B to the network based on the rollback rules and any KPI thresholds met by the rollback set B (i.e., other than the configured criteria). After receiving any configuration / message / indication from the network, the WTRU can send an acknowledgment message to the network. Similarly, the WTRU can receive an acknowledgment message after any WTRU action (e.g., after a network indication when rolling back to the default set B, or after an indication sent to the network when switching from one type or set B to another).

[0157] Although the features and elements have been described above in specific combinations, those skilled in the art will understand that each feature or element can be used alone or in any combination with other features and elements. Furthermore, the methods described herein can be implemented in a computer program, software, or firmware incorporated into a computer-readable medium for execution by a computer or processor. Examples of computer-readable media include electronic signals (transmitted via wired or wireless connections) and computer-readable storage media. Examples of computer-readable storage media include, but are not limited to, read-only memory (ROM), random access memory (RAM), registers, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROMs and DVDs. The processor associated with the software can be used to implement a radio frequency transceiver used in a WTRU, UE, terminal, base station, RNC, or any host computer.

Claims

1. A wireless transmit / receive unit (WTRU), the WTRU comprising: transceiver; as well as Processor, wherein the transceiver and the processor are configured to: Receive configuration information for a reference signal (RS) resource set A from a gNodeB (gNB), wherein the RS resource set A includes resources for all beams associated with the gNB; Receive configuration information for RS resource set B from the gNB, wherein the size of RS resource set B is smaller than the size of RS resource set A, and wherein RS resource set B is capable of including resources for a subset of all beams associated with the gNB; The gNB receives configuration information for a plurality of candidate QCL hypothesis sets for the RS resource set B, wherein each QCL hypothesis set in the plurality of candidate QCL hypothesis sets is associated with at least one RS resource of the RS resource set A. Receive information from the gNB indicating one or more key performance indicators (KPIs); Based on at least one candidate QCL hypothesis set from the plurality of candidate QCL hypothesis sets, measurements are performed on the RS received on each resource of the RS resource set B. Perform measurements on the RSs received on the resources in the RS resource set A; A candidate QCL hypothesis set is selected from the plurality of candidate QCL hypothesis sets based on the measured values ​​performed and the determined values ​​of one or more indicated KPIs; as well as Send a message to the gNB reporting the selected set of QCL hypotheses B.

2. The WTRU according to claim 1, wherein, The one or more KPIs include any one or more of the following: signal quality; throughput; Layer 1 reference signal received power (L1-RSRP); signal-to-interference-plus-noise ratio (SINR); channel quality indicator (CQI); received signal strength indicator (RSSI); reference signal received quality (RSRQ); L1-RSRP difference; number of RS resources that meet the L1-RSRP threshold; SINR difference; number of RS resources that meet the SINR threshold; input data distribution; or output data distribution.

3. The WTRU according to claim 1, wherein, The RS resource set A is a cell-specific RS resource set, and the RS resource set B is a WTRU-specific RS resource set.

4. The WTRU according to claim 1, wherein, The transceiver and the processor are further configured to: Receive one or more KPI thresholds corresponding to one or more indicated KPIs, wherein the values ​​of the one or more KPIs determined are based on the one or more KPI thresholds.

5. The WTRU according to claim 1, wherein, The transceiver and the processor are further configured to determine the value of one or more indicated KPIs, wherein determining the value of one or more indicated KPIs includes: The reference signal received power (RSRP) difference is determined by comparing the predicted RSRP value with the measured RSRP value for each beam in the RS resource set A; and The determination of whether a new set B QCL hypothesis is needed is based on the RSRP difference relative to the RSRP threshold.

6. The WTRU according to claim 1, wherein, Measurements performed on the received RS include measuring one or more of the following: Received Reference Signal Power (SS-RSRP); Channel State Information RSRP (CSI-RSRP); Synchronization Signal to Interference-plus-Noise Ratio (SS-SINR); CSI-SINR; Received Signal Strength Indicator (RSSI); Cross-Layer Interference RSSI (CLI-RSSI); or Sounding Reference Signal RSRP (SRS-RSRP).

7. The WTRU according to claim 1, wherein, The RS includes one or more of the following: synchronization signal (SS); sounding reference signal (SRS); demodulation reference signal (DMRS); primary synchronization signal (PSS); secondary synchronization signal (SSS); synchronization signal block (SSB); channel state information reference signal (CSI-RS); tracking reference signal (TRS); positioning reference signal (PRS); or phase tracking reference signal (PTRS).

8. The WTRU according to claim 1, wherein, The configuration information for RS resource set A and the configuration information for RS resource set A may each include one or more of the following: one or more RS resource set identifiers (IDs); indications for one or more RS resources of the corresponding RS resource set A or RS resource set B; indications of repetition information; indications of non-periodic trigger offsets; tracking reference signal (TRS) information; One or more RS resource IDs; resource mapping information indicating resource elements in a physical resource block (PRB); power control offset information; power control offset with synchronization signal (SS) information; scrambling ID; periodicity information; offset information; or QCL information.

9. The WTRU according to claim 1, wherein, The RS resource set A and the RS resource set A each include one of the following: multiple beams; multiple beam pairs; multiple beam patterns; or multiple RS resource sets.

10. The WTRU according to claim 1, wherein, The transceiver and the processor are further configured to: Based on the determined values ​​of one or more received KPIs, determine whether it is necessary to select a new set of candidate QCL hypotheses for RS resource set B.

11. A method performed by a wireless transmit / receive unit (WTRU), the method comprising: Receive configuration information for a reference signal (RS) resource set A from a gNodeB (gNB), wherein the RS resource set A includes resources for all beams associated with the gNB; The gNB receives configuration information for RS resource set B, wherein the size of RS resource set B is smaller than the size of RS resource set A, and RS resource set B is capable of including resources for a subset of all beams associated with the gNB. The gNB receives configuration information for a plurality of candidate QCL hypothesis sets for the RS resource set B, wherein each QCL hypothesis set in the plurality of candidate QCL hypothesis sets is associated with at least one RS resource of the RS resource set A. Receive information from the gNB indicating one or more key performance indicators (KPIs); Based on at least one candidate QCL hypothesis set from the plurality of candidate QCL hypothesis sets, measurements are performed on the RS received on each resource of the RS resource set B. Perform measurements on the RSs received on the resources in the RS resource set A; A candidate QCL hypothesis set is selected from the plurality of candidate QCL hypothesis sets based on the measured values ​​performed and the determined values ​​of one or more indicated KPIs; as well as Send a message to the gNB reporting the selected set of QCL hypotheses B.

12. The method according to claim 11, wherein, The one or more KPIs include any one or more of the following: signal quality; throughput; Layer 1 reference signal received power (L1-RSRP); signal-to-interference-plus-noise ratio (SINR); channel quality indicator (CQI); received signal strength indicator (RSSI); reference signal received quality (RSRQ); L1-RSRP difference; number of RS resources that meet the L1-RSRP threshold; SINR difference; number of RS resources that meet the SINR threshold; input data distribution; or output data distribution.

13. The method according to claim 11, wherein, The RS resource set A is a cell-specific RS resource set, and the RS resource set B is a WTRU-specific RS resource set.

14. The method according to claim 11, further comprising: Receive one or more KPI thresholds corresponding to one or more indicated KPIs, wherein the values ​​of the one or more KPIs determined are based on the one or more KPI thresholds.

15. The method of claim 11, further comprising determining a value for one or more indicated KPIs, wherein determining a value for one or more indicated KPIs comprises: The reference signal received power (RSRP) difference is determined by comparing the predicted RSRP value with the measured RSRP value for each beam in the RS resource set A; and The determination of whether a new set B QCL hypothesis is needed is based on the RSRP difference relative to the RSRP threshold.

16. The method according to claim 11, wherein, Measurements performed on the received RS include measuring one or more of the following: Received Reference Signal Power (SS-RSRP); Channel State Information RSRP (CSI-RSRP); Synchronization Signal to Interference-plus-Noise Ratio (SS-SINR); CSI-SINR; Received Signal Strength Indicator (RSSI); Cross-Layer Interference RSSI (CLI-RSSI); or Sounding Reference Signal RSRP (SRS-RSRP).

17. The method according to claim 11, wherein, The RS includes one or more of the following: synchronization signal (SS); sounding reference signal (SRS); demodulation reference signal (DMRS); primary synchronization signal (PSS); secondary synchronization signal (SSS); synchronization signal block (SSB); channel state information reference signal (CSI-RS); tracking reference signal (TRS); positioning reference signal (PRS); or phase tracking reference signal (PTRS).

18. The method according to claim 11, wherein, The configuration information of RS resource set A and the configuration information of RS resource set A may each include one or more of the following: one or more RS resource set identifiers (IDs); indications for one or more RS resources of the corresponding RS resource set A or RS resource set B; indications of repetition information; indications of non-periodic trigger offsets; tracking reference signal (TRS) information; One or more RS resource IDs; resource mapping information indicating resource elements in a physical resource block (PRB); power control offset information; power control offset with synchronization signal (SS) information; scrambling ID; periodicity information; offset information; or QCL information.

19. The method according to claim 11, wherein, The RS resource set A and the RS resource set A each include one of the following: multiple beams; multiple beam pairs; multiple beam patterns; or multiple RS resource sets.

20. The method according to claim 11, further comprising: Based on the determined values ​​of one or more received KPIs, it is determined whether a new candidate QCL hypothesis set needs to be selected for RS resource set B.

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