Channel state information prediction

Abstract

Various aspects of this disclosure relate to user equipment (UE), base stations, apparatuses, and methods for predicting channel state information. In one aspect, the UE determines at least one prediction model, wherein each of the at least one prediction model is determined based on a channel state information (CSI) reference signal (RS) associated with at least one parameter. The UE determines to use one or more of the at least one prediction model to predict a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window. By implementing embodiments of this disclosure, schemes can be provided for how to predict CSI using different prediction models trained with different parameters and how to use different CSI-RS in a measurement window, thereby improving the accuracy and efficiency of the prediction results.

Description

Technical Field

[0001] This disclosure relates to wireless communications, and more specifically to user equipment, base stations, apparatus, and methods for predicting channel state information (CSI). Background Technology

[0002] A wireless communication system may include one or more network communication devices (such as base stations), which may also be referred to as eNodeB (eNB), next-generation NodeB (gNB), or other suitable terms. Each network communication device (such as a base station) may support wireless communication with one or more user communication devices, which may also be referred to as user equipment (UE), or other suitable terms. The wireless communication system may support wireless communication with one or more user communication devices by utilizing the resources of the wireless communication system (e.g., time resources (e.g., symbols, time slots, subframes, frames, etc.) or frequency resources (e.g., subcarriers, carriers)). Furthermore, the wireless communication system may support wireless communication across a variety of radio access technologies, including third-generation (3G) radio access technology, fourth-generation (4G) radio access technology, fifth-generation (5G) radio access technology, and other suitable radio access technologies other than 5G (e.g., sixth-generation (6G)).

[0003] The gNB can send a CSI reference signal (RS) to the UE. The UE can measure the channel based on the CSI-RS and report the channel quantity to the gNB in ​​the CSI report. This quantity can be represented by a Channel Quality Indicator (CQI), Rank Indicator (RI), Precoding Matrix Indicator (PMI), etc. The resources used for sending CSI-RS can be periodic, semi-static, or aperiodic. The UE can perform some form of CSI-RS related data collection. The UE or gNB can train a model (such as an Artificial Intelligence (AI) / Machine Learning (ML) model). The UE can use this model to predict future CSI reports. In this way, the gNB does not need to send CSI-RS in the future, which can increase system capacity. Summary of the Invention

[0004] This disclosure relates to user equipment, base stations, apparatus, and methods for predicting channel state information. In a first aspect of this approach, the UE determines at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI-RS) associated with at least one parameter. The UE determines to use one or more of the at least one prediction model to predict a CSI report for a prediction window, based on at least one CSI-RS in a measurement window corresponding to the prediction window. By implementing embodiments of this disclosure, schemes can be provided for predicting CSI using different prediction models trained with different parameters and for using different CSI-RS in a measurement window, thereby improving the accuracy and efficiency of the prediction results.

[0005] In some implementations of the methods and apparatus described herein, at least one parameter may include one of the following: the number of CSI-RS in the measurement window; the interval of the CSI-RS in the measurement window; a symbol for the CSI-RS, which is configured with or not configured with an uplink (UL) subband; or a CSI-RS mode in the measurement window, wherein the CSI-RS mode indicates at least one of the following: the location of the CSI-RS in the measurement window, at least one interval of the CSI-RS, or the number of CSI-RS.

[0006] In some implementations of the methods and apparatus described herein, when one or more CSI-RS are cancelled in the measurement window, at least one CSI-RS for predicting CSI reports may include: at least one remaining CSI-RS in the measurement window; or at least one remaining CSI-RS and at least one supplementary CSI-RS, wherein the supplementary CSI-RS is determined based on the remaining CSI-RS.

[0007] In some implementations of the methods and apparatus described herein, one or more CSI-RSs may be cancelled in one of the following situations: the CSI-RS overlaps with a UL symbol; the CSI-RS is in a symbol or time slot not configured with a UL subband, and a prediction model associated with a symbol or time slot configured with a UL subband is used; or one or more CSI-RSs are in a symbol or time slot configured with a UL subband, and a prediction model associated with a symbol or time slot not configured with a UL subband is used.

[0008] In some implementations of the methods and apparatus described herein, each of at least one prediction model is determined based on one of the following: a combination of CSI-RS associated with a symbol or time slot configured with a UL subband and a CSI-RS associated with a symbol or time slot not configured with a UL subband; a CSI-RS associated with a symbol or time slot configured with a UL subband; or a CSI-RS associated with a symbol or time slot not configured with a UL subband.

[0009] In some implementations of the methods and apparatus described herein, when all CSI-RS in the measurement window are configured with symbols or time slots of the UL subband, a prediction model among at least one prediction model determined based on the CSI-RS associated with the symbols or time slots of the UL subband can be used for prediction; or when all CSI-RS in the measurement window are not configured with symbols or time slots of the UL subband, a prediction model among at least one prediction model determined based on the CSI-RS not configured with the UL subband can be used for prediction.

[0010] In some implementations of the methods and apparatus described herein, the UE can prevent predicted CSI reporting when none of the parameters of the CSI-RS in the measurement window are the same as the parameters associated with one of the prediction models in at least one prediction model; or the UE can prevent predicted CSI reporting when the number of corresponding parameters of CSI-RS with different parameters in the measurement window exceeds a threshold.

[0011] In some implementations of the methods and apparatus described herein, the UE may cancel CSI reports for a prediction window; transmit CSI reports for CSI-RS in a measurement window via a transceiver; or detect scheduling information from a base station via a transceiver for scheduling CSI reports for a prediction window.

[0012] In some implementations of the methods and apparatus described herein, the UE may predict CSI reports based on a selected prediction model in at least one prediction model if: the number of CSI-RS in the measurement window is the same as the number of CSI-RS used to determine the selected prediction model; or the symbol or slot format of the CSI-RS in the measurement window is the same as the slot format associated with the CSI-RS used to determine the selected prediction model.

[0013] In some implementations of the methods and apparatus described herein, the UE can predict a CSI report based on a prediction model in at least one prediction model that includes a symbol or time slot configured with a UL subband: the number of CSI-RS in a measurement window that includes a symbol or time slot configured with a UL subband is greater than the number of CSI-RS in a measurement window that does not include a UL subband; or the first CSI-RS in a symbol or time slot configured with a UL subband in a measurement window.

[0014] In some implementations of the methods and apparatus described herein, when the number of CSI-RS in a symbol or time slot configured with a UL subband in the measurement window is the same as the number of CSI-RS in a symbol or time slot not configured with a UL subband in the measurement window, the UE can predict CSI reports based on a predefined or indicated prediction model.

[0015] In some implementations of the methods and apparatus described herein, at least one prediction model can be determined based on CSI-RS associated with parameters X and Y, where X can be the minimum number of CSI-RS instances and Y can be the maximum interval between CSI-RS instances. When X for the first prediction model is less than or equal to the number of CSI-RS in the measurement window, and / or when Y for the first prediction model is greater than or equal to the interval between CSI-RS in the measurement window, CSI reports are predicted based on the first prediction model, and the UE can predict CSI reports based on the first prediction model.

[0016] In some implementations of the methods and apparatus described herein, the UE may select one of the first prediction models to predict CSI reports, and the selected first prediction model may be associated with: the same CSI-RS pattern as the CSI-RS pattern in the measurement window; the same CSI-RS interval as the CSI-RS interval in the measurement window; or the same number of CSI-RS as the number of CSI-RS in the measurement window.

[0017] In some implementations of the methods and apparatus described herein, the UE can predict CSI reports based on a predefined, preconfigured, or base station-indicated prediction model.

[0018] In some implementations of the methods and apparatus described herein, the UE may predict multiple CSI reports based on multiple prediction models in at least one prediction model, wherein the multiple prediction models are determined based on at least one parameter that is the same as at least one parameter in the measurement window; or the UE may predict multiple CSI reports based on at least one prediction model.

[0019] In some implementations of the methods and apparatus described herein, the UE may transmit multiple CSI reports to the base station via a transceiver; or transmit a CSI report determined based on the average of multiple CSI reports to the base station via a transceiver.

[0020] In some implementations of the methods and apparatus described herein, the UE may predict a first CSI report based on a prediction model associated with a symbol or time slot configured with a UL subband; predict a second CSI report based on a prediction model associated with a symbol or time slot not configured with a UL subband; and transmit the first and second CSI reports to the base station via a transceiver.

[0021] In some implementations of the methods and apparatus described herein, when none of the parameters of the CSI-RS in the measurement window are the same as those associated with one of the prediction models in at least one prediction model, the UE may determine an extended measurement window based on extending the measurement window by one or more time units; and the UE may determine a predicted CSI report based on one or more prediction models until one or more parameters of the CSI-RS in the extended measurement window are the same as one or more parameters associated with one or more prediction models in at least one prediction model.

[0022] In some implementations of the methods and apparatus described herein, the parameters associated with at least one CSI-RS in the measurement window may be the same as the parameters used to determine one or more prediction models in at least one prediction model.

[0023] In a second aspect of the scheme, a BS described herein may include a processor; and a transceiver coupled to the processor, wherein the processor may be configured to determine at least one prediction model, wherein each of the at least one prediction model is determined based on a CSI-RS associated with at least one parameter; and to receive from the UE via the transceiver one or more CSI reports for a prediction window, the one or more CSI reports being based on at least one CSI-RS in a measurement window corresponding to the prediction window.

[0024] In some implementations of the methods and apparatus described herein, at least one parameter may include one of the following: the number of CSI-RS in the measurement window; the interval of the CSI-RS in the measurement window; a symbol for the CSI-RS, which is configured with or not configured with an uplink (UL) subband; or a CSI-RS mode in the measurement window, wherein the CSI-RS mode indicates at least one of the following: the location of the CSI-RS in the measurement window, at least one interval of the CSI-RS, or the number of CSI-RS.

[0025] In some implementations of the methods and apparatus described herein, the parameters associated with at least one CSI-RS in the measurement window may be the same as the parameters used to determine one or more prediction models in at least one prediction model.

[0026] In some implementations of the methods and apparatus described herein, the BS may send an instruction to the UE indicating which prediction models from at least one prediction model should be used to predict the CSI report.

[0027] In some implementations of the methods and apparatus described herein, the BS may prevent receiving CSI reports, receiving CSI reports for CSI-RS in the measurement window, or sending scheduling information for scheduling CSI reports for the prediction window when none of the parameters of the CSI-RS in the measurement window are the same as the parameters associated with one of the prediction models in at least one prediction model, or when the number of corresponding parameters of CSI-RS with different parameters in the measurement window exceeds a threshold.

[0028] In some implementations of the methods and apparatus described herein, the BS may receive multiple CSI reports based on multiple prediction models in at least one prediction model, wherein the multiple prediction models are determined based on at least one parameter that is the same as at least one parameter in the measurement window; or receive multiple CSI reports based on at least one prediction model.

[0029] In a third aspect of the scheme, a processor for wireless communication may include: at least one memory; and a controller coupled to the at least one memory and configured such that the controller: determines at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI-RS) associated with at least one parameter; and determines to use one or more of the at least one prediction model to predict a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.

[0030] In a fourth aspect of the scheme, a processor for wireless communication may include: at least one memory; and a controller coupled to the at least one memory and configured such that the controller: determines at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI-RS) associated with at least one parameter; and receives from the UE via a transceiver one or more CSI reports for a prediction window, the one or more CSI reports being based on at least one CSI-RS in a measurement window corresponding to the prediction window.

[0031] In a fifth aspect of the scheme, a method performed by a UE as described herein may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on Channel State Information (CSI-RS) associated with at least one parameter; and determining to use one or more of the at least one prediction model to predict a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.

[0032] In a sixth aspect of the scheme, a method performed by a BS as described herein may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on Channel State Information (CSI-RS) associated with at least one parameter; and receiving from a UE one or more CSI reports for a prediction window, the one or more CSI reports being based on at least one CSI-RS in a measurement window corresponding to the prediction window.

[0033] It should be understood that the summary section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0034] Figure 1A An example of a wireless communication system supporting a scheme for predicting CSI according to various aspects of this disclosure is illustrated.

[0035] Figure 1B An example of a subband full-duplex (SBFD) scheme is illustrated.

[0036] Figure 1C The illustration shows an example of the frequency domain resources of CSI-RS in an SBFD time slot.

[0037] Figure 1D The diagram illustrates the process of... tdd-UL-DL-ConfigCommon An example of an uplink (UL) / downlink (DL) configuration.

[0038] Figure 1E The illustration shows an example of the CSI prediction process based on UE-side training.

[0039] Figure 1F The illustration shows an example of the process of CSI prediction based on network (NW) training.

[0040] Figure 1G An example of the model and its measurement and prediction windows is illustrated.

[0041] Figure 2 An example signaling process for predicting CSI is illustrated according to various aspects of this disclosure.

[0042] Figures 3-9 The illustrations show examples of how to predict CSI using different prediction models trained with different parameters, according to various aspects of this disclosure, and how to use different CSI-RS within a measurement window.

[0043] Figures 10-11 An example of a device for predicting CSI is illustrated according to various aspects of this disclosure.

[0044] Figures 12-13 An example of a processor for predicting CSI is illustrated according to various aspects of this disclosure.

[0045] Figures 14-15 A flowchart illustrating a method for predicting CSI according to various aspects of this disclosure is shown. Detailed Implementation

[0046] The principles of this disclosure will now be described with reference to some embodiments. It should be understood that these embodiments are described for illustrative purposes only and to assist those skilled in the art in understanding and implementing this disclosure, and do not impose any limitation on the scope of this disclosure. The disclosure described herein can be implemented in various ways other than those described below.

[0047] In the following description and claims, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0048] References to "an embodiment," "an exemplary embodiment," and "an embodiment," etc., in this disclosure indicate that the described embodiments may include a particular feature, structure, or characteristic, but not every embodiment is required to include that particular feature, structure, or characteristic. Furthermore, these phrases do not necessarily refer to the same embodiment(s). Moreover, when a particular feature, structure, or characteristic is described in connection with an embodiment, those skilled in the art will recognize that in conjunction with other embodiments (whether explicitly described or not) affecting such a feature, structure, or characteristic is within the scope of their knowledge.

[0049] It should be understood that although the terms “first” and “second” may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used to distinguish one element from another. For example, a first element may also be referred to as a second element without departing from the scope of the embodiments, and similarly, a second element may also be referred to as a first element. As used herein, the term “and / or” includes any and all combinations of one or more of the listed terms.

[0050] The terminology used herein is for describing particular embodiments and is not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “the” used herein also include the plural forms. Furthermore, it should be understood that the terms “comprises,” “comprising,” “has,” “having,” “includes,” and / or “including”, when used herein, specify the presence of the stated features, elements, and / or components, but do not exclude the presence or addition of one or more other features, elements, components, and / or combinations thereof.

[0051] As used herein, the term "communication network" refers to a network that conforms to any suitable communication standard, such as 5G NR, LTE, LTE-A Advanced, Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), Narrowband Internet of Things (NB-IoT), etc. Furthermore, communication between terminal devices and network devices in a communication network can be performed according to any suitable generation of communication protocol, including but not limited to first-generation (1G), second-generation (2G), 2.5G, 2.75G, third-generation (3G), fourth-generation (4G), 4.5G, fifth-generation (5G) communication protocols and / or any other currently known or to be developed in the future. Embodiments of this disclosure can be applied to various communication systems. Given the rapid development of communications, there will be future types of communication technologies and systems in which this disclosure can be embodied. This should not be construed as limiting the scope of this disclosure to the systems described above.

[0052] As used herein, the term "network device" generally refers to a node in a communication network through which terminal devices can access the communication network and receive services. Network devices can refer to base stations (BS) or access points (APs), such as Node B (NodeB or NB), Radio Access Network (RAN) nodes, Evolved Node B (eNodeB or eNB), NR NB (also known as gNB), Remote Radio Unit (RRU), Radio Header (RH), infrastructure equipment for V2X (Vehicle-to-Everything) communication, Transmitter Receiver Point (TRP), Receiver Point (RP), Remote Radio Header End (RRH), relay, Integrated Access and Backhaul (IAB) nodes, low-power nodes (such as femtoBS, picoBS, etc.), depending on the terminology and technology applied.

[0053] As used herein, the term "terminal device" generally refers to any terminal device capable of wireless communication. By way of example and not limitation, a terminal device may also be referred to as a communication device, user equipment (UE), end-user equipment, subscriber station (SS), unmanned aerial vehicle (UAV), portable subscriber station, mobile station (MS), or access terminal (AT). Terminal devices may include, but are not limited to, mobile phones, cellular phones, smartphones, VoIP phones, wireless local loop phones, tablets, wearable terminal devices, personal digital assistants (PDAs), portable computers, desktop computers, image capture terminal devices (such as digital cameras), gaming terminal devices, music storage and playback devices, in-vehicle wireless terminal devices, wireless endpoints, mobile stations, laptop embedded devices (LEEs), laptop mounted devices (LMEs), USB dongles, smart devices, wireless customer premises equipment (CPEs), Internet of Things (IoT) devices, watches or other wearable devices, head-mounted displays (HMDs), vehicles, drones, medical devices (e.g., remote surgical equipment), industrial equipment (e.g., robots and / or other wireless devices operating in industrial and / or automated processing chain environments), consumer electronics devices, and devices operating on commercial and / or industrial wireless networks. In the following description, the terms "terminal device," "communication device," "terminal," "user equipment," and "UE" are used interchangeably.

[0054] Various aspects of this disclosure are described in the context of wireless communication systems.

[0055] Figure 1A An example of a wireless communication system 100A supporting schemes for predicting CSI according to various aspects of this disclosure is illustrated. The wireless communication system 100 may include one or more network entities 102 (also referred to as network devices (NEs) or base stations (BSs) 102), one or more UEs 104, a core network 106, and a packet data network 108. The wireless communication system 100 may support various radio access technologies. In some implementations, the wireless communication system 100 may be a 4G network, such as an LTE network or an LTE-A advanced network. In some other implementations, the wireless communication system 100 may be a 5G network, such as an NR network. In other implementations, the wireless communication system 100 may be a combination of 4G and 5G networks, or other suitable radio access technologies, including IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), and IEEE 802.20. The wireless communication system 100 may support radio access technologies other than 5G. In addition, the wireless communication system 100 can support technologies such as time division multiple access (TDMA), frequency division multiple access (FDMA), or code division multiple access (CDMA).

[0056] One or more network entities 102 may be distributed throughout a geographic area to form a wireless communication system 100. One or more of the network entities 102 described herein may be, include, or may be referred to as network nodes, base stations, network elements, radio access networks (RANs), base transceiver stations, access points, NodeBs, eNodeBs (eNBs), next-generation NodeBs (gNBs), or other suitable terms. Network entities 102 and UE 104 may communicate via communication link 110, which may be a wireless or wired connection. For example, network entities 102 and UE 104 may perform wireless communication (e.g., receive signaling, send signaling) via a Uu interface.

[0057] Network entity 102 may provide a geographic coverage area 112 for which network entity 102 supports services (e.g., voice, video, packet data, messaging, broadcasting, etc.) for one or more UEs 104 within the geographic coverage area 112. For example, network entity 102 and UE 104 may support wireless communication of signals associated with services (e.g., voice, video, packet data, messaging, broadcasting, etc.) based on one or more wireless access technologies. In some implementations, network entity 102 may be mobile, for example, a satellite associated with a non-terrestrial network. In some implementations, different geographic coverage areas 112 associated with the same or different radio access technologies may overlap, but different geographic coverage areas 112 may be associated with different network entities 102. The information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the description may be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0058] One or more UEs 104 may be distributed throughout the geographic area of ​​the wireless communication system 100. UE 104 may include or be referred to as a mobile device, wireless device, remote device, remote unit, handheld device, subscriber device, or some other suitable term. In some implementations, UE 104 may be referred to as a unit, station, terminal, or client, etc. Additionally or alternatively, UE 104 may be referred to as an Internet of Things (IoT) device, an Internet of Everything (IoE) device, or a Machine Type Communication (MTC) device, etc. In some implementations, UE 104 may be stationary within the wireless communication system 100. In some other implementations, UE 104 may be mobile within the wireless communication system 100.

[0059] One or more UEs 104 can be devices of different forms or with different capabilities. Figure 1AThe diagram illustrates some examples of UE 104. UE 104 is capable of communicating with various types of devices, such as network entity 102, other UEs 104, or network devices (e.g., core network 106, packet data network 108, relay equipment, integrated access and backhaul (IAB) node, or another network device). Figure 1A As shown. Alternatively or additionally, UE 104 may support communication with other network entities 102 or UE 104 that may act as relays in wireless communication system 100.

[0060] UE 104 can also support direct wireless communication with other UE 104s via communication link 114. For example, UE 104 can support direct wireless communication with another UE 104 via a device-to-device (D2D) communication link. In some implementations, such as vehicle-to-vehicle (V2V) deployments, vehicle-to-everything (V2X) deployments, or cellular V2X deployments, communication link 114 may be referred to as a sidechain. For example, UE 104 can support direct wireless communication with another UE 104 via a PC5 interface.

[0061] Network entity 102 may support communication with core network 106 or with another network entity 102, or both. For example, network entity 102 may interface with core network 106 via one or more backhaul links 116 (e.g., via S1, N2, N2, or another network interface). Network entities 102 may communicate with each other via backhaul links 116 (e.g., via X2, Xn, or another network interface). In some implementations, network entities 102 may communicate directly with each other (e.g., between network entities 102). In some other implementations, network entities 102 may communicate with each other or indirectly (e.g., via core network 106). In some implementations, one or more network entities 102 may include sub-components, such as access network entities, which may be examples of access node controllers (ANCs). An ANC may communicate with one or more UEs 104 via one or more other access network transport entities (which may be referred to as radio headends, smart radio headends, or transmit-receive points (TRPs)).

[0062] In some implementations, network entity 102 can be configured with a decomposed architecture that can utilize protocol stacks physically or logically distributed across two or more network entities 102, such as an Integrated Access Backhaul (IAB) network, Open RAN (O-RAN) (e.g., a network configuration sponsored by the O-RAN Alliance), or Virtualized RAN (vRAN) (e.g., Cloud RAN (C-RAN)). For example, network entity 102 may include one or more of a Central Unit (CU), Distributed Unit (DU), Radio Unit (RU), RAN Intelligent Controller (RIC) (e.g., near real-time RIC, non-real-time RIC), Service Management and Orchestration (SMO) system, or any combination thereof.

[0063] An RU can also be referred to as a radio headend, intelligent radio headend, remote radio headend (RRH), remote radio unit (RRU), or transmit-receive point (TRP). In a decomposed RAN architecture, one or more components of network entity 102 can be co-located, or one or more components of network entity 102 can be located in distributed locations (e.g., separate physical locations). In some implementations, one or more network entities 102 in a decomposed RAN architecture can be implemented as virtual units (e.g., virtual CU (VCU), virtual DU (VDU), virtual RU (VRU)).

[0064] The functional decomposition between CU, DU, and RU can be flexible and can support different functions based on the functions performed at the CU, DU, or RU (e.g., network layer functions, protocol layer functions, baseband functions, radio frequency functions, and any combination thereof). For example, a protocol stack functional decomposition can be used between the CU and DU, allowing the CU to support one or more layers of the protocol stack and the DU to support one or more different layers of the protocol stack. In some implementations, the CU can host upper-layer protocol layer (e.g., Layer 3 (L3), Layer 2 (L2)) functions and signaling (e.g., Radio Resource Control (RRC), Serving Data Adaptation Protocol (SDAP), Packet Data Convergence Protocol (PDCP)). The CU can connect to one or more DUs or RUs, and one or more DUs or RUs can host lower-layer protocol layer functions and signaling, such as Layer 1 (L1) (e.g., Physical (PHY) layer) or L2 (e.g., Radio Link Control (RLC) layer, Media Access Control (MAC) layer), and each can be at least partially controlled by the CU 160.

[0065] Alternatively or additionally, a functional split of the protocol stack can be employed between the DU and RU, allowing the DU to support one or more layers of the protocol stack and the RU to support one or more different layers of the protocol stack. The DU can support one or more different cells (e.g., via one or more RUs). In some implementations, the functional split between the CU and DU, or between the DU and RU, can be within a protocol layer (e.g., some functions of the protocol layer can be performed by one of the CU, DU, or RU, while other functions of the protocol layer are performed by different items in the CU, DU, or RU).

[0066] The CU can be further functionally divided into CU control plane (CU-CP) and CU user plane (CU-UP) functions. The CU can be connected to one or more DUs via mid-range communication links (e.g., F1, F1-c, F1-u), and the DUs can be connected to one or more RUs via fronthaul communication links (e.g., open fronthaul (FH) interfaces). In some implementations, the mid-range or fronthaul communication links can be implemented based on interfaces (e.g., channels) between layers of a protocol stack supported by the respective network entity 102 communicating via such communication links.

[0067] Core network 106 can support user authentication, access authorization, tracking, connectivity, and other access, routing, or mobility functions. Core network 106 can be an evolved packet core (EPC) or a 5G core (5GC), which may include control plane entities that manage access and mobility (e.g., a mobility management entity (MME), access and mobility management functions (AMF)) and user plane entities that route packets or interconnects to external networks (e.g., a serving gateway (S-GW), a packet data network (PDN) gateway (P-GW), or a user plane function (UPF)). In some implementations, the control plane entities may manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management (e.g., data bearers, signaling bearers, etc.) of one or more UEs 104 served by one or more network entities 102 associated with core network 106.

[0068] Core network 106 can communicate with packet data network 108 via one or more backhaul links 116 (e.g., via S1, N2, N2, or another network interface). Packet data network 108 may include application server 118. In some implementations, one or more UEs 104 may communicate with application server 118. UE 104 may establish a session (e.g., Protocol Data Unit (PDU) session, etc.) with core network 106 via network entity 102. Core network 106 can use the established session (e.g., an established PDU session) to route services (e.g., control information, data, etc.) between UE 104 and application server 118. A PDU session may be an example of a logical connection between UE 104 and core network 106 (e.g., one or more network functions of core network 106).

[0069] In wireless communication system 100A, network entity 102 and UE 104 can use the resources of wireless communication system 100 (e.g., time resources (e.g., symbols, time slots, subframes, frames, etc.) or frequency resources (e.g., subcarriers, carriers)) to perform various operations (e.g., wireless communication). In some implementations, network entity 102 and UE 104 can support different resource structures. For example, network entity 102 and UE 104 can support different frame structures. In some implementations, such as in 4G, network entity 102 and UE 104 can support a single frame structure. In some other implementations, such as in 5G and other suitable radio access technologies, network entity 102 and UE 104 can support various frame structures (i.e., multiple frame structures). Network entity 102 and UE 104 can support various frame structures based on one or more digital technologies.

[0070] The wireless communication system 100A may support one or more digital technologies, and the digital technologies may include subcarrier spacing and cyclic prefix. The first digital technology (e.g., μ =0) can be associated with the first subcarrier spacing (e.g., 15 kHz) and a normal cyclic prefix. In some implementations, the first digital technique (e.g., ...) associated with the first subcarrier spacing (e.g., 15 kHz) is... μ =0) can utilize one time slot per subframe. Second digital technologies (e.g., μ =1) can be associated with the second subcarrier spacing (e.g., 30 kHz) and a normal cyclic prefix. The third digital technology (e.g., μ =2) can be associated with a third subcarrier spacing (e.g., 60 kHz) and a normal cyclic prefix or an extended cyclic prefix. A fourth digital technology (e.g., μ =3) can be associated with a fourth subcarrier spacing (e.g., 120 kHz) and a normal cyclic prefix. A fifth digital technology (e.g., μ=4) can be associated with the fifth subcarrier spacing (e.g., 240 kHz) and the normal cyclic prefix.

[0071] The time intervals of resources (e.g., communication resources) can be organized according to frames (also called radio frames). Each frame can have a duration, for example, 10 milliseconds (ms). In some implementations, each frame can include multiple subframes. For example, each frame can include 10 subframes, and each subframe can have a duration, for example, 1 ms. In some implementations, each frame can have the same duration. In some implementations, each subframe of a frame can have the same duration.

[0072] Alternatively or concurrently, the time intervals of resources (e.g., communication resources) can be organized according to time slots. For example, a subframe may include a certain number (e.g., quantity) of time slots. The number of time slots in each subframe may also depend on one or more digital technologies supported in the wireless communication system 100. For example, a first digital technology, a second digital technology, a third digital technology, a fourth digital technology, and a fifth digital technology (i.e., ...) associated with corresponding subcarrier intervals of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz. μ =0、 μ =1、 μ =2、 μ =3、 μ =4) One time slot per subframe, two time slots per subframe, four time slots per subframe, eight time slots per subframe, and 16 time slots per subframe can be used, respectively. Each time slot can include a certain number (e.g., quantity) of symbols (e.g., OFDM symbols). In some implementations, the number (e.g., quantity) of time slots in a subframe can depend on the digital technique. For a normal cyclic prefix, a time slot can include 14 symbols. For an extended cyclic prefix (e.g., for a 60kHz subcarrier spacing), a time slot can include 12 symbols. The relationship between the number of symbols per time slot, the number of time slots per subframe, and the number of time slots per frame for both normal and extended cyclic prefixes can depend on the digital technique. It should be understood that the first digital technique (e.g., quantity) associated with the first subcarrier spacing (e.g., 15kHz) can be... μ The reference of (=0) can be used interchangeably between subframes and time slots. In this disclosure, the time unit can be one or more frames, subframes, time slots, or symbols.

[0073] In the wireless communication system 100A, the electromagnetic (EM) spectrum can be divided into various categories, frequency bands, frequency channels, etc., based on frequency or wavelength. For example, the wireless communication system 100 can support one or more operating frequency bands, such as frequency range names FR1 (410MHz-7.125GHz), FR2 (24.25GHz-52.6GHz), FR3 (7.125GHz-24.25GHz), FR4 (52.6GHz-114.25GHz), FR4a or FR4-1 (52.6GHz-71GHz), and FR5 (114.25GHz-300GHz). In some implementations, network entity 102 and UE 104 can perform wireless communication on one or more operating frequency bands. In some implementations, FR1 can be used by network entity 102 and UE 104, along with other devices or apparatuses, for cellular communication services (e.g., control information, data). In some implementations, FR2 can be used by network entity 102 and UE 104, along with other devices or apparatuses, for short-range, high data rate capabilities.

[0074] FR1 can be associated with one or more digital technologies (e.g., at least three digital technologies). For example, FR1 can be associated with the following: a first digital technology (e.g., μ =0), which includes a 15kHz subcarrier spacing; second digital technology (e.g., μ =1), which includes a 30kHz subcarrier spacing; third digital technology (e.g., μ =2), which includes a subcarrier spacing of 60 kHz. FR2 can be associated with one or more digital technologies (e.g., at least two digital technologies). For example, FR2 can be associated with a third digital technology (e.g., μ =2), which includes a 60kHz subcarrier spacing; fourth digital technology (e.g., μ =3), which includes a subcarrier spacing of 120kHz.

[0075] Figure 1B The illustration shows an example of Subband Full-Duplex (SBFD) scheme 100B. To achieve superior data rates and latency, higher frequency bands of 5G spectrum are unavoidable. Overcoming the reduced coverage of such carriers is a challenge. In 3GPP Release 18, a new duplex scheme may be introduced that enables simultaneous use of downlink and uplink within a TDD carrier using non-overlapping frequency resources; this can be called Subband Full-Duplex (SBFD). The aim of this scheme is to extend the duration of uplink transmissions to improve uplink coverage and capacity. Simultaneous use of DL and UL occurs at the gNB, not at the UE side. Figure 1BAs shown, slots #0 and #1 are SBFD slots. Slot #2 is a UL slot. An SBFD symbol / slot can indicate that the symbol / slot can support simultaneous DL and UL transmissions. A symbol / slot that is SBFD can indicate that the symbol can contain at least two subbands with different transmission directions, one subband being the DL transmission direction and the other being the UL transmission direction, or that the BS can perform downlink and uplink transmissions simultaneously in the symbol. It should be noted that another name can be used to refer to such a symbol. In the context of this disclosure, a non-SBFD symbol can refer to a DL, flexible, or UL symbol.

[0076] Based on the aforementioned background new radio (NR) resource allocation, it is observed that gNB can indicate a frequency domain resource within the bandwidth portion (BWP). Considering that the frequency resource allocation of CSI-RS is continuously configured, and therefore, in a certain time slot or symbol configuration of the UL subband, CSI-RS may overlap with the UL subband. In this case, the following options can be considered. Option (1) is two consecutive CSI-RS resources linked together. Option (2) is a single CSI-RS resource. In option (2), there can be two sub-options. Sub-option (2.1) is a discontinuous CSI-RS resource allocation, and option (2.2) is a continuous CSI-RS resource allocation with discontinuous CSI-RS resources obtained by excluding frequency resources outside the (multiple) DL subbands.

[0077] Regardless of the option chosen, the same result can be obtained: the CSI-RS in SBFD symbols or time slots is discontinuous and differs from the CSI-RS in DL symbols or time slots. Furthermore, the CSI-RS in SBFD symbols / time slots and the CSI-RS in DL symbols / time slots may correspond to the same CSI report or different CSI reports. If they are in the same CSI report, individual CSI measurements can be obtained based on the first CSI-RS and the second CSI-RS respectively, or the CSI report can be obtained based on the CSI-RS in SBFD symbols or non-SBFD symbols at different time instances.

[0078] Figure 1C Example 100C is illustrated, showing the frequency domain resources of CSI-RS in SBFD time slots, as shown by the CSI-RS in the upper DL subband and the lower DL subband in time slot #0. It can be seen that the CSI-RS in time slot #0 is discontinuous and different from the CSI-RS in time slot #2 (DL time slot).

[0079] Figure 1D The diagram illustrates the process of... tdd-UL-DL-ConfigCommonExample 100D represents the uplink (UL) / downlink (DL) configuration. The time division duplex (TDD) slot format in 5G NR includes downlink symbols, uplink symbols, and flexible symbols. The slot format can be determined by the cell common UL / DL configuration tdd-UL-DL-ConfigCommon provided to the UE via system information. tdd-UL-DL-ConfigCommon includes the configuration of transmission mode 1, which includes: (1) by dl-ul-transmission-periodicity The time slot configuration period is represented by P milliseconds; (2) by nrofDownlinkSlots The number of downlink time slots represented by d slots (3) By nrofDownlinkSymbols The number of downlink symbols represented by d sym (4) By nrofUplinkSlots The number of uplink time slots u represents slots ; and (5) by nrofUplinkSymbol The number of uplink symbols represented by u sym .

[0080] The P-millisecond time slot configuration period consists of S time slots. Within these S time slots, the first d... slots Each time slot includes only downlink symbols, and the last u slots Each time slot includes only uplink symbols. In d slots d after one time slot sym The last symbol is the downlink symbol. slots u before the time slot sym The first symbol is the uplink symbol. The remaining (Sd) slot -u slot ) N sym -d sym -u sym The symbols are flexible symbols, where N is a flexible symbol. sym This refers to the number of symbols in the time slot. Here, "flexible" means that the UE cannot make any assumptions about the transmission direction. Downlink control signals (i.e., PDCCH) should be monitored in flexible symbols, and if a scheduling message is detected, the UE should send / receive accordingly. In addition, flexible symbols also serve as a protection period for the UE to switch from DL reception to UL transmission.

[0081] like Figure 1D As shown, the example of slot format 100D is for a time slot of 5ms. dl-ul- TransmissionPeiodicity The 10 time slots. nrofDownlinkSlots =6 indicates that the first 6 time slots are DL time slots (120 to 122). nrofUplinkSlots =3 indicates that the last 3 slots are UL slots (126 to 128). nrofDownlinkSymbols=7 and nrofUplinkSymbols =3 indicates that there is a time slot with 7 DL symbols, 3 UL symbols and 4 flexible symbols between the DL time slot and the UL time slot. Here, the 4 flexible symbols (124) are mainly used as the protection period for the DL to UL handover.

[0082] The UE can also be provided with UE-specific configuration RRC signaling. tdd-UL-DL-ConfigDedicated Its instructions are in tdd-UL-DL-ConfigDedicated The symbol is configured as either UL or DL. It should be noted that... tdd-UL-DL- ConfigCommon The transmission direction of inflexible symbols configured in the middle cannot be... tdd-UL-DL-ConfigDedicated cover.

[0083] Furthermore, the transmission direction of flexible symbols can be indicated via dynamic signaling. This signaling carries a Slot Format Indicator (SFI) and will be received by one or more configured devices. The SFI can indicate the flexible symbol as a DL or UL symbol, and it should be noted that... tdd-UL-DL-ConfigCommon and tdd-UL-DL-ConfigDedicated The transmission direction of the inflexible symbols configured in the middle cannot be covered by SFI.

[0084] If the UE is configured to receive CSI-RS in some resources, CSI-RS will be cancelled in the following cases (1) to (11). Case (1): For operation on a single carrier in an unpaired spectrum, if the UE is configured by a higher layer to receive PDCCH, PDSCH, CSI-RS or DL ​​PRS in the symbol set of a time slot, the UE will receive PDCCH, PDSCH, CSI-RS or DL ​​PRS if the UE does not detect a DCI format instructing the UE to transmit PUSCH, PUCCH, PRACH or SRS in at least one symbol of the symbol set of the time slot; otherwise, the UE will not receive PDCCH, PDSCH, CSI-RS or DL ​​PRS in the symbol set of the time slot.

[0085] Case (2): For UE operation with shared spectrum channel access in FR1 or FR2-2, when the UE is provided with ChannelAccessMode2 =' enabled When 'UE is provided csi-RS-ValidationWithDCI Not provided CO-DurationsPerCell It is not provided SlotFormatCombinationsPerCell Furthermore, if the UE is configured by the higher layer to receive CSI-RS in the symbol set of the time slot, and if the UE does not detect a DCI format indicating non-periodic CSI-RS reception or a DCI format scheduling PDSCH reception in the symbol set of the time slot, the UE cancels CSI-RS reception in the symbol set of the time slot.

[0086] Case (3): For those caused by tdd-UL-DL-ConfigurationCommon or tdd-UL-DL- ConfigurationDedicated The symbol set of the timeslot indicated to the UE as the uplink is not received by the UE when the PDCCH, PDSCH, or CSI-RS overlaps with the symbol set of the timeslot, even if it partially overlaps.

[0087] Case (4): For the symbol set of the slot corresponding to the effective PRACH timing and the time slot before the effective PRACH timing N gap If, as described in Clause 8.1, reception would overlap with any symbol in the symbol set, the UE will not receive PDCCH, PDSCH, or CSI-RS in the time slot. The UE does not expect the symbol set of the time slot to be... tdd-UL-DL-ConfigurationCommon or tdd-UL-DL-ConfigurationDedicated This indicates a downlink.

[0088] Case (5): If the reference cell and the configured directionalCollisionHandling-r16 Another cell in the same neighborhood operates in a different frequency band, when tdd-UL-DL-ConfigurationCommon or tdd-UL-DL- ConfigurationDedicated When a symbol is designated as a downlink or uplink on another cell and an uplink or downlink on a reference cell, the UE considers the symbol flexible and does not need to receive higher-layer configured PDCCH, PDSCH, or CSI-RS, nor does it expect to send higher-layer configured SRS, PUCCH, PUSCH, or PRACH. If the UE detects that the DCI format is scheduled for transmission on one or more symbols in the symbol set on another cell, the UE does not need to receive higher-layer configured PDCCH, PDSCH, or CSI-RS on the flexible symbols on the reference cell in the symbol set.

[0089] Case (6): If at least one symbol in the symbol set is... tdd-UL-DL-ConfigurationCommon or tdd-UL-DL-ConfigurationDedicated If the indication is an uplink, or a symbol corresponding to an SRS, PUCCH, PUSCH, or PRACH transmission configured by a higher layer on a reference cell, then the UE will not receive a PDCCH, PDSCH, or CSI-RS configured by a higher layer on the symbol set of another cell.

[0090] Case (7): If the UE is configured by the higher layer to receive PDSCH or CSI-RS in the symbol set of the time slot, the UE will only receive PDSCH or CSI-RS in the symbol set of the time slot if the SFI index field value in DCI format 2_0 indicates the symbol set of the time slot as downlink, and if applicable, the symbol set is within the remaining channel occupancy duration.

[0091] Case (8): If the UE is configured by the higher layer to receive CSI-RS or PDSCH in the symbol set of the time slot, and the UE detects that the time slot format value is not 255 of DCI format 2_0 (which indicates that the time slot format has a subset of symbols from the symbol set as uplink or flexible), or the UE detects that the DCI format indicates that the UE should send PUSCH, PUCCH, SRS or PRACH in at least one symbol in the symbol set, then the UE cancels the reception of CSI-RS in the symbol set of the time slot or cancels the reception of PDSCH in the time slot.

[0092] Case (9): For UE operation with shared spectrum channel access in FR1 or FR2-2, when the UE is provided ChannelAccessMode2 =' enabled When the UE is configured by a higher layer to receive CSI-RS, and the UE is provided with CO- DurationsPerCell Then for those by tdd-UL-DL-ConfigurationCommon or tdd - UL-DL- ConfigurationDedicated Indicates a set of symbols for downlink or flexible time slots, or when tdd-UL-DL- ConfigurationCommon and tdd - UL-DL-ConfigurationDedicated If not provided, the UE cancels CSI-RS reception in the symbol set of time slots that are not within the remaining channel occupancy duration.

[0093] Case (10): If the UE is configured by the higher layer to receive CSI-RS, or if it detects that DCI format 0_1 ​​indicates that the UE receives CSI-RS in one or more RB sets and the symbol set of the time slot, and the UE detects DCI format 2_0, in which the bitmap indicates that any RB set in one or more RB sets is not available for reception, then the UE cancels the reception of CSI-RS in the symbol set of the time slot.

[0094] Case (11): For those caused by tdd-UL-DL-ConfigurationCommon and tdd-UL-DL- ConfigurationDedicated (If provided) Indicates a flexible set of symbols for time slots, or when tdd-UL-DL- ConfigurationCommon and tdd-UL-DL-ConfigurationDedicated If not provided to the UE, and if the UE does not detect DCI format 2_0 of the time slot format, then the UE will not receive CSI-RS in the symbol set of the time slot if the UE is configured by a higher layer to receive CSI-RS in the symbol set of the time slot. This is unless the UE is provided with... CO-DurationsPerCell Furthermore, the symbol set of the time slot is within the remaining channel occupancy duration.

[0095] Figure 1EThe illustration shows an example of the CSI prediction process 100E based on UE-side training. Figure 1F An example of process 100F for CSI prediction based on network (NW) side training is illustrated. In process 100E, UE 130 can perform some CSI-RS related data collection, and then UE 130 or gNB 132 can train a model, and then the UE can predict future CSI reports based on the model. In this way, the gNB will not need to send CSI-RS in the future, which will increase system capacity. Similarly, the corresponding process 100F for CSI prediction can be shown below.

[0096] For model training, the CSI set can be divided into historical CSI set and future CSI set. For example, a series of continuous samples using a sliding method can be described by slot IDs, such as [0,5,10,15,20,25->28], [5,10,15,20,25,30->33], [10,15,20,25,30,35->38], etc., and these samples can be generated from CSI-RS-Resource-1 with slot ID [0,5,10,15,20,25,30,35,...] and slot spacing of 5, and CSI-RS-Resource-2 with slot ID [28,33,38,...], slot spacing of 5, and offset from the first slot by three slots. A series of consecutive samples using a non-sliding method can be described by slot IDs, such as [0,5,10,15,20,25->28], [30,35,40,45,50,55->58], [60,65,70,75,80,85->88], etc. These samples can be generated from CSI-RS-Resource-1 with slot IDs of [0,5,10,15,20,25,30,35, ...] and slot spacing of 5, and CSI-RS-Resource-2 with slot IDs of [28,58,88, ...] and slot spacing of 30. The applicability of AI-based CSI prediction is highly dependent on the data collection process.

[0097] Figure 1G An example of Model 100G and its measurement and prediction windows is illustrated. Model 100G is trained and used for CSI prediction. Model 100G is associated with one or more of the following parameters: the number of CSI-RS instances in measurement window 190, the interval between CSI-RS instances in measurement window 190, the interval between measurement window 190 and prediction window 192, the number of CSI-RS instances in prediction window 192, and the interval between CSI-RS instances in prediction window 192.

[0098] Currently, during data collection, CSI-RS within the measurement window have fixed intervals and a fixed number, and the model is trained based on these samples associated with one or more parameters. However, when the model is used for prediction, situations may arise where some CSI-RS may be cancelled in certain circumstances, or some CSI-RS may be in SBFD symbols while others are in non-SBFD symbols. The pattern of CSI-RS within the measurement window (including CSI-RS location, interval, or number) may differ from the data configuration process. Therefore, predictions may be inaccurate, resources used for reporting CSI may be wasted, and CSI reports for predicted locations may not be obtained in a timely manner.

[0099] In other words, even if at least one model is trained, and each model is trained based on CSI-RS associated with at least one parameter, if the parameters of the CSI-RS in a certain measurement window are different from the relevant parameters of any model, then the use of the CSI-RS in that measurement window for prediction should be discussed. At least one parameter may include one or more of the following: the number of CSI-RS, the interval of the CSI-RS, the symbol used for the CSI-RS, whether or not it is configured with SBFD, the CSI-RS pattern in the measurement window, etc.

[0100] By implementing embodiments of this disclosure, it is possible to provide a scheme for predicting CSI using different prediction models trained with different parameters and for using different CSI-RS within a measurement window, thereby improving the accuracy and efficiency of the prediction results.

[0101] Figure 2 An example signaling process 200 for predicting CSI according to various aspects of this disclosure is illustrated. UE 104 determines (206) at least one prediction model. Each of the at least one prediction model is determined based on a CSI-RS associated with at least one parameter. Similarly, BS 102 determines (208) at least one prediction model, and each of the at least one prediction model is determined based on a CSI-RS associated with at least one parameter. If at least one prediction model is determined by BS 102 (e.g., trained using CSI-RS samples and CSI report samples), then BS 102 may send the at least one prediction model to UE 104. In some example embodiments, each prediction model may be associated with at least one parameter. At least one parameter may be used to determine the prediction model.

[0102] BS 102 may send (210) one or more CSI-RS 212 to UE 104. UE 104 may receive (214) one or more CSI-RS 212 from BS 102. UE 104 determines (216) to use one or more prediction models from at least one prediction model to predict one or more CSI reports 220 for the prediction window based on at least one CSI-RS 212 in the measurement window corresponding to the prediction window. UE 104 sends (218) one or more CSI reports 220 to BS 102. BS 102 receives (222) one or more CSI reports 220 from UE 104. In some example embodiments, BS 102 may predict a CSI report for a specific location within the prediction window.

[0103] In some example embodiments, at least one parameter may include the number of CSI-RSs in the measurement window. At least one parameter may include the interval between the CSI-RSs in the measurement window. At least one parameter may include a symbol for the CSI-RS (which may be referred to as an SBFD symbol or a DL symbol, respectively), wherein the symbol is configured with or not configured with a UL sub-band.

[0104] At least one parameter may include a CSI-RS pattern within the measurement window. The CSI-RS pattern may indicate at least one of the following: the location of a CSI-RS within the measurement window, at least one interval of a CSI-RS, or the number of CSI-RS. Each of the at least one prediction models may be determined based on a CSI-RS associated with at least one parameter. This may mean that each prediction model may be associated with at least one parameter, or that at least one parameter may be used to determine the prediction model.

[0105] In some example embodiments, if one or more CSI-RSs are cancelled in the measurement window, the at least one CSI-RS used to predict the CSI report may include at least one remaining CSI-RS in the measurement window, or at least one remaining CSI-RS and at least one supplementary CSI-RS. Here, the supplementary CSI-RS may be determined based on the remaining CSI-RS.

[0106] For example, if a CSI-RS overlaps with a UL symbol, one or more CSI-RSs can be cancelled. A CSI-RS can be cancelled if it is in a symbol or time slot not configured with a UL subband, and a prediction model associated with the symbol or time slot configured with a UL subband is used. A CSI-RS can also be cancelled if one or more CSI-RSs are in a symbol or time slot configured with a UL subband, and a prediction model associated with the symbol or time slot not configured with a UL subband is used.

[0107] For example, CSI-RS can be cancelled by the aforementioned cases (1)-(11), or if the SBFD symbol / slot model is used, CSI-RS in the DL symbol can be cancelled, or if the DL symbol / slot model is used, CSI-RS in the SBFD symbol or slot can be cancelled. UE 104 can determine how to predict CSI for the prediction window based on the remaining CSI-RS after the cancellation of some CSI-RS in a measurement window corresponding to the prediction window.

[0108] refer to Figure 3 In the accompanying drawings, reference numeral 330 denotes the DL symbol, and reference numeral 332 denotes the SBFD symbol. It should be noted that reference numerals 330 and 332 also apply to the entire [section / process / etc.]. Figures 3 to 9 Assuming that (multiple) trained models are associated with CSI-RS in DL symbols (non-SBFD symbols), then in measurement window 302, CSI-RS overlapping with SBFD symbols (such as CSI-RS 310 and 312) should be removed. Four CSI-RS (such as CSI-RS 306, 308, 314, and 316) are used to perform predictions (such as one or more of CSI-RS 320, 322, 324, and 326).

[0109] Refer again Figure 2 Each of the at least one prediction model can be determined based on: a combination of CSI-RS associated with a symbol or time slot configured with a UL subband and a CSI-RS associated with a symbol or time slot not configured with a UL subband, a CSI-RS associated with a symbol or time slot configured with a UL subband, or a CSI-RS associated with a symbol or time slot not configured with a UL subband.

[0110] refer to Figure 4 For example, UE 104 can determine how to predict CSI for a prediction window based on the remaining CSI-RS and supplementary CSI-RS. Supplementary CSI-RS can be determined based on the remaining CSI by replacing the cancelled CSI-RS with the remaining CSI-RS within the measurement window. For example, supplementary CSI-RS can be determined by replacing the cancelled CSI-RS with the remaining CSI-RS, such as by replacing the cancelled CSI-RS with remaining CSI-RS that are before or after the cancelled CSI-RS and are close to the cancelled CSI-RS. Figure 4 As shown, CSI-RS 406 can be replaced by CSI-RS 402, and CSI-RS 408 can be replaced by CSI-RS 404. Then, six CSI-RSs can be used to perform predictions.

[0111] refer to Figure 2 If all CSI-RS in the measurement window are in symbols or time slots configured with UL subbands, then a prediction model among at least one prediction model determined based on the CSI-RS associated with the symbols or time slots configured with UL subbands can be used for prediction. If all CSI-RS in the measurement window are in symbols or time slots not configured with UL subbands, then a prediction model among at least one prediction model determined based on the CSI-RS associated with the symbols or time slots not configured with UL subbands can be used for prediction.

[0112] For example, UE 104 can use a model trained based on CSI-RS, which is associated with the same parameters as the CSI-RS in a given measurement window. UE 104 does not expect the corresponding parameters of the CSI-RS in the measurement window to be different from any parameters associated with any model.

[0113] refer to Figures 5A to 5D If a model 500A is trained with CSI-RS associated with SBFD symbols / slots (such as symbols 502, 504, 506, 508, 510, and 512), and another model 500B is trained with CSI-RS associated with DL symbols / slots (such as symbols 514, 516, 518, 520, 522, and 524), then for the measurement window, the CSI-RS used for prediction can be entirely in DL symbols / slots (as shown in CSI Report 2 in Figures 500C and 500D) or in SBFD symbols / slots (as shown in CSI Report 1 in Figures 500C and 500D).

[0114] Refer again Figure 2 If none of the parameters of the CSI-RS in the measurement window are the same as the parameters associated with one of the prediction models in at least one prediction model, then UE 104 may not predict a CSI report. If the number of corresponding parameters of CSI-RS with different parameters in the measurement window exceeds a threshold, then UE 104 may not predict a CSI report.

[0115] In some example embodiments, if UE 104 does not predict CSI reports, UE 104 can cancel the prediction window for CSI reports. UE 104 can send CSI-RS CSI reports in the measurement window in a conventional manner. UE 104 can detect scheduling information from the base station for scheduling CSI reports for the prediction window. CSI reports can be determined without using at least one prediction model.

[0116] refer to Figure 6For example, multiple models (or model parameters) can be trained using CSI-RS associated with multiple slot format combinations (such as models 1-4). The prediction model(s) to be used is selected based on the slot format combination of the CSI-RS in a given measurement window. UE 104 expects the slot format combination of the CSI-RS in a given measurement window to be the same as at least one slot format combination used to train the model.

[0117] In some example embodiments, UE 104 may predict CSI reports based on the selected prediction model from at least one prediction model if the number of CSI-RS in the measurement window is the same as the number of CSI-RS used to determine the selected prediction model, or if the symbol or time slot format associated with the CSI-RS in the measurement window is the same as the time slot format associated with the CSI-RS used to determine the selected prediction model. For example, UE 104 may select one or more models from models 1-4.

[0118] Refer again Figure 2 If the corresponding parameter of a CSI-RS in a measurement window is not the same as any parameter associated with any model, the UE may not predict the CSI for the prediction window. In this case, or if the number of CSI-RSs with different parameters exceeds a threshold, the UE may not predict the CSI for the prediction window. The threshold may be predefined or associated with model parameters. In this case, UE 104 may cancel reporting the CSI for the prediction window. UE 104 may report the CSI of the CSI-RS in the measurement window in the conventional manner. UE 104 may wait for BS 102 to schedule the reporting of CSI-RS for the prediction window.

[0119] In some example embodiments, if the number of CSI-RS in a symbol or time slot configured with a UL subband in the measurement window is greater than the number of CSI-RS in a symbol or time slot not configured with a UL subband in the measurement window, or if the first CSI-RS in a symbol or time slot configured with a UL subband in the measurement window is selected, then UE 104 may predict CSI reports based on a prediction model of at least one prediction model for a symbol or time slot configured with a UL subband.

[0120] For example, the model can be determined based on the true parameters of CSI-RS within a certain measurement window, and the number of CSI-RS within a certain measurement window can be the same as the number of CSI-RS used to train the model. The time slot format of the CSI-RS within a certain measurement window can be the same as the time slot format of the CSI-RS used to train the model. If more CSI-RS instances are in the SBFD symbol, or if the first instance is in the SBFD symbol, then the SBFD model can be used.

[0121] In some example embodiments, if the number of CSI-RS in symbols or time slots configured with UL subbands in the measurement window is the same as the number of CSI-RS in symbols or time slots not configured with UL subbands in the measurement window, then UE 104 can predict CSI reports based on a predefined or indicated prediction model. If the number of instances in SBFD symbols and non-SBFD symbols is the same, then either the SBFD model or the non-SBFD model can be used according to a predefined or indicated model.

[0122] refer to Figure 7 In some example embodiments, if the prediction model in at least one prediction model can be determined based on CSI-RS associated with parameters X and Y, where X is the minimum number of CSI-RS instances and Y is the maximum interval between CSI-RS instances, then UE 104 can predict CSI reports based on the first prediction model if X of the first prediction model is less than or equal to the number of CSI-RS in the measurement window, and / or if Y of the first prediction model is greater than or equal to the interval of CSI-RS in the measurement window, and UE 104 can determine the prediction model in at least one prediction model based on parameters X and Y.

[0123] For example, assuming the parameters include X and Y, and assuming the number of CSI-RS in a measurement window is X1, then models with X less than or equal to X1 can be selected. Assuming the maximum interval of CSI-RS instances in a measurement window is Y1, then models with Y greater than or equal to Y1 can be selected. If multiple models meet the requirements, UE 104 can select the model with the same pattern, smaller interval, or largest number of CSI-RS instances.

[0124] Refer again Figure 2 If more than one model is selected, UE 104 can select one prediction model to predict CSI reports. The selected prediction model can be associated with: the same CSI-RS pattern as the CSI-RS pattern in the measurement window; the same CSI-RS interval as the CSI-RS interval in the measurement window; or the same number of CSI-RS as the number of CSI-RS in the measurement window.

[0125] In some example embodiments, UE 10 may predict CSI reports based on a prediction model predefined, preconfigured, or indicated by the base station. The model used may be predefined in the 3GPP specification or preconfigured or indicated by the base station.

[0126] In some example embodiments, UE 104 may predict multiple CSI reports (e.g., for each location) based on multiple prediction models in at least one prediction model, and the multiple prediction models are determined based on at least one parameter that is the same as at least one parameter in the measurement window. UE 104 may predict multiple CSI reports based on at least one prediction model. UE 104 may send multiple CSI reports to BS 102. UE 104 may send a CSI report determined based on the average of the multiple CSI reports to BS 102.

[0127] For example, UE 104 can predict multiple CSIs for a prediction window based on multiple models in at least one model. The multiple models can be all models, or they can be models among the multiple models that have at least one parameter that is the same as a given measurement window. UE 104 can report multiple CSIs corresponding to the predicted CSIs based on the multiple models. In some examples, a single CSI is reported based on the average of the multiple predicted CSIs.

[0128] refer to Figure 8 In some example embodiments, UE 104 may predict a first CSI report based on a prediction model associated with a symbol or time slot configured with a UL subband. UE 104 may predict a second CSI report based on a prediction model associated with a symbol or time slot not configured with a UL subband. UE 104 may send the first and second CSI reports to BS 102.

[0129] For example, UE 104 can predict multiple CSIs for a prediction window based on multiple models in at least one model. The multiple models can be all models, or they can be models among the multiple models that have at least one parameter that is the same as a given measurement window. UE 104 can report multiple CSIs corresponding to the predicted CSIs based on the multiple models. UE 104 can also report a single CSI based on the average of the multiple predicted CSIs. In some example embodiments, UE 104 can report two predictions based on SBFD model 802 and a non-SBFD model 804.

[0130] refer to Figure 9 In some example embodiments, if none of the parameters of the CSI-RS in the measurement window are the same as those associated with one of the prediction models in at least one prediction model, then UE 104 may determine an extended measurement window based on extending the measurement window by one or more time units. UE 104 may determine the predicted CSI report based on one or more prediction models until one or more parameters of the CSI-RS in the extended measurement window are the same as one or more parameters associated with one or more of the prediction models in at least one prediction model.

[0131] For example, UE 104 can zoom in on the measurement window 902 one time unit at a time until UE 104 finds that valid CSI-RS 920 and 922 satisfy a trained model in the zoomed-in measurement window 908. Then, UE 104 can use this model to predict the CSI in the corresponding prediction window 910, which can be moved from the original prediction window 904.

[0132] In some example embodiments, the parameters associated with at least one CSI-RS in the measurement window may be the same as the parameters used to determine one or more prediction models in at least one prediction model.

[0133] In some example embodiments, BS 102 may send an instruction to UE 104 indicating which prediction models from at least one prediction model should be used to predict CSI reports.

[0134] In some example embodiments, BS 104 may not receive CSI reports if none of the parameters of the CSI-RS in the measurement window are the same as those associated with one of the prediction models in at least one prediction model, or if the number of corresponding parameters of CSI-RS with different parameters in the measurement window exceeds a threshold. BS 102 may receive CSI reports of the CSI-RS in the measurement window. BS 102 may send scheduling information for scheduling CSI reports for the prediction window. CSI reports may be determined without using at least one prediction model.

[0135] In some example embodiments, BS 102 may receive multiple CSI reports (e.g., for each location) based on multiple prediction models in at least one prediction model. The multiple prediction models may be determined based on at least one parameter that is the same as at least one parameter in the measurement window. BS 102 may receive multiple CSI reports based on at least one prediction model.

[0136] By implementing embodiments of this disclosure, it is possible to provide a scheme for predicting CSI using different prediction models trained with different parameters and for using different CSI-RS within a measurement window, thereby improving the accuracy and efficiency of the prediction results.

[0137] Figure 10An example of a device 1000 supporting a scheme for predicting CSI according to various aspects of this disclosure is illustrated. Device 1000 may be an example of a network entity 102 as described herein. Device 1000 may support wireless communication with one or more network entities 102, UE 104, or any combination thereof. Device 1000 may include components for bidirectional communication, including components for transmitting and receiving communications (such as processor 1002, memory 1004, transceiver 1006, and optional I / O controller 1008). These components may communicate electronically or be otherwise coupled (e.g., operational ground, communication ground, functional ground, electronic ground, electrical ground) via one or more interfaces (e.g., bus).

[0138] Processor 1002, memory 1004, transceiver 1006, or various combinations thereof, or various components thereof, may be examples of components used to perform the various aspects of this disclosure described herein. For example, processor 1002, memory 1004, transceiver 1006, or various combinations thereof, or components thereof, may support methods for performing one or more of the operations described herein.

[0139] In some implementations, processor 1002, memory 1004, transceiver 1006, or various combinations or components thereof may be implemented in hardware (e.g., in a communication management circuitry system). The hardware may include a processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, configured to or otherwise supporting components for performing the functions described in this disclosure. In some implementations, processor 1002 and memory 1004 coupled to processor 1002 may be configured to perform one or more functions described herein (e.g., by executing instructions stored in memory 1004 by processor 1002).

[0140] For example, based on the examples disclosed herein, processor 1002 may support wireless communication at device 1000. Processor 1002 may be configured to operate to support components used for predicting CSI.

[0141] Processor 1002 may include intelligent hardware devices (e.g., general-purpose processors, DSPs, CPUs, microcontrollers, ASICs, FPGAs, programmable logic devices, discrete gate or transistor logic components, discrete hardware components, or any combination thereof). In some implementations, processor 1002 may be configured to use a memory controller to operate a memory array. In some other implementations, the memory controller may be integrated into processor 1002. Processor 1002 may be configured to execute computer-readable instructions stored in memory (e.g., memory 1004) to cause device 1000 to perform various functions of this disclosure.

[0142] Memory 1004 may include random access memory (RAM) and read-only memory (ROM). Memory 1004 may store computer-readable, computer-executable code, including instructions that, when executed by processor 1002, cause device 1000 to perform the various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. In some implementations, the code may not be directly executed by processor 1002, but may cause a computer (e.g., when compiled and executed) to perform the functions described herein. In some implementations, memory 1004 may include a basic I / O system (BIOS) that controls basic hardware or software operations, such as interaction with peripheral components or devices.

[0143] I / O controller 1008 can manage the input and output signals of device 1000. I / O controller 1008 can also manage peripheral devices not integrated into device M02. In some implementations, I / O controller 1008 can represent a physical connection or port to an external peripheral device. In some implementations, I / O controller 1008 can utilize an operating system such as iOS®, Android®, MS Windows®, OS / 2®, UNIX®, LINUX®, or other known operating systems. In some implementations, I / O controller 1008 can be implemented as part of a processor, such as processor 1002. In some implementations, a user can interact with device 1000 via I / O controller 1008 or via hardware components controlled by I / O controller 1008.

[0144] In some implementations, device 1000 may include a single antenna 1010. However, in other implementations, device 1000 may have more than one antenna 1010 (i.e., multiple antennas), including multiple antenna panels or antenna arrays capable of concurrently transmitting or receiving multiple wireless transmissions. Transceiver 1006 may communicate bidirectionally via one or more antennas 1010, wired or wireless links, as described herein. For example, transceiver 1006 may represent a wireless transceiver and may communicate bidirectionally with another wireless transceiver. Transceiver 1006 may also include a modem for modulating packets, providing modulated packets to one or more antennas 1010 for transmission, and demodulating packets received from one or more antennas 1010. Transceiver 1006 may include one or more transmit chains, one or more receive chains, or combinations thereof.

[0145] The transmission chain can be configured to generate and transmit signals (e.g., control information, data, packets). The transmission chain may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. At least one modulator may be configured to support one or more techniques, such as amplitude modulation (AM), frequency modulation (FM), or digital modulation schemes such as phase shift keying (PSK) or quadrature amplitude modulation (QAM). The transmission chain may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over a wireless medium. The transmission chain may also include one or more antennas 1010 for transmitting the amplified signal into the air or wireless medium.

[0146] The receiver chain can be configured to receive signals (e.g., control information, data, packets) via a wireless medium. For example, the receiver chain may include one or more antennas 1010 for receiving signals over the air or via a wireless medium. The receiver chain may include at least one amplifier (e.g., a low-noise amplifier (LNA)) configured to amplify the received signal. The receiver chain may include at least one demodulator configured to demodulate the received signal and acquire transmitted data by reversing the modulation technique applied during signal transmission. The receiver chain may include at least one decoder for decoding the demodulated signal to receive the transmitted data.

[0147] Figure 11An example of device 1100 supporting a scheme for predicting CSI according to various aspects of this disclosure is illustrated. Device 1100 may be an example of UE 104 as described herein. Device 1100 may support wireless communication with one or more network entities 102, UE 104, or any combination thereof. Device 1100 may include components for bidirectional communication, including components for transmitting and receiving communications (such as processor 1102, memory 1104, transceiver 1106, and optional I / O controller 1108). These components may communicate electronically or be otherwise coupled (e.g., operational ground, communication ground, functional ground, electronic ground, electrical ground) via one or more interfaces (e.g., bus).

[0148] Processor 1102, memory 1104, transceiver 1106, or various combinations thereof, or various components thereof, may be examples of components used to perform various aspects of the present disclosure described herein. For example, processor 1102, memory 1104, transceiver 1106, or various combinations thereof, or components thereof, may support methods for performing one or more of the operations described herein.

[0149] In some implementations, processor 1102, memory 1104, transceiver 1106, or various combinations or components thereof may be implemented in hardware (e.g., in a communication management circuitry system). The hardware may include a processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, configured to or otherwise supporting components for performing the functions described in this disclosure. In some implementations, processor 1102 and memory 1104 coupled to processor 1102 may be configured to perform one or more functions described herein (e.g., by executing instructions stored in memory 1104 by processor 1102).

[0150] For example, based on the examples disclosed herein, processor 1102 may support wireless communication at device 1100. Processor 1102 may be configured to operate to support components used for predicting CSI.

[0151] Processor 1102 may include intelligent hardware devices (e.g., general-purpose processors, DSPs, CPUs, microcontrollers, ASICs, FPGAs, programmable logic devices, discrete gate or transistor logic components, discrete hardware components, or any combination thereof). In some implementations, processor 1102 may be configured to use a memory controller to operate a memory array. In some other implementations, the memory controller may be integrated into processor 1102. Processor 1102 may be configured to execute computer-readable instructions stored in memory (e.g., memory 1104) to cause device 1100 to perform various functions of this disclosure.

[0152] Memory 1104 may include random access memory (RAM) and read-only memory (ROM). Memory 1104 may store computer-readable, computer-executable code, including instructions that, when executed by processor 1102, cause device 1100 to perform the various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. In some implementations, the code may not be directly executed by processor 1102, but may cause a computer (e.g., when compiled and executed) to perform the functions described herein. In some implementations, memory 1104 may include a basic I / O system (BIOS) that controls basic hardware or software operations, such as interaction with peripheral components or devices.

[0153] I / O controller 1108 can manage the input and output signals of device 1100. I / O controller 1108 can also manage peripheral devices not integrated into device M02. In some implementations, I / O controller 1108 can represent a physical connection or port to an external peripheral device. In some implementations, I / O controller 1108 can utilize an operating system such as iOS®, ANDROID®, MS WINDOWS®, OS / 2®, UNIX®, LINUX®, or other known operating systems. In some implementations, I / O controller 1108 can be implemented as part of a processor, such as processor 1102. In some implementations, a user can interact with device 1100 via I / O controller 1108 or via hardware components controlled by I / O controller 1108.

[0154] In some implementations, device 1100 may include a single antenna 1110. However, in other implementations, device 1100 may have more than one antenna 1110 (i.e., multiple antennas), including multiple antenna panels or antenna arrays capable of concurrently transmitting or receiving multiple wireless transmissions. Transceiver 1106 may communicate bidirectionally via one or more antennas 1110, wired or wireless links, as described herein. For example, transceiver 1106 may represent a wireless transceiver and may communicate bidirectionally with another wireless transceiver. Transceiver 1106 may also include a modem for modulating packets, providing modulated packets to one or more antennas 1110 for transmission, and demodulating packets received from one or more antennas 1110. Transceiver 1106 may include one or more transmit chains, one or more receive chains, or combinations thereof.

[0155] The transmission chain can be configured to generate and transmit signals (e.g., control information, data, packets). The transmission chain may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. At least one modulator may be configured to support one or more techniques, such as amplitude modulation (AM), frequency modulation (FM), or digital modulation schemes such as phase shift keying (PSK) or quadrature amplitude modulation (QAM). The transmission chain may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over a wireless medium. The transmission chain may also include one or more antennas 1110 for transmitting the amplified signal into the air or wireless medium.

[0156] The receiver chain can be configured to receive signals (e.g., control information, data, packets) via a wireless medium. For example, the receiver chain may include one or more antennas 1110 for receiving signals over the air or via a wireless medium. The receiver chain may include at least one amplifier (e.g., a low-noise amplifier (LNA)) configured to amplify the received signal. The receiver chain may include at least one demodulator configured to demodulate the received signal and acquire transmitted data by reversing the modulation technique applied during signal transmission. The receiver chain may include at least one decoder for decoding the demodulated signal to receive the transmitted data.

[0157] Figure 12An example of a processor 1200 supporting a scheme for predicting CSI according to various aspects of this disclosure is illustrated. Processor 1200 may be an example of a processor configured to perform various operations according to the examples described herein. Processor 1200 may include a controller 1202 configured to perform various operations according to the examples described herein. Processor 1200 may optionally include at least one memory 1204, such as an L1 / L2 / L3 cache. Additionally or alternatively, processor 1200 may optionally include one or more arithmetic logic units (ALUs) 1206. One or more of these components may be electronically communicated or otherwise coupled (e.g., operative ground, communicative ground, functional ground, electronic ground, electrical ground) via one or more interfaces (e.g., buses).

[0158] Processor 1200 may be a processor chipset and includes a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receive, acquire, retrieve, send, output, forward, store, determine, identify, access, write, read) according to the examples described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to the processor chipset or included in the processor chipset (e.g., processor 1200)) or other memory (e.g., random access memory (RAM), read-only memory (ROM), dynamic RAM (DRAM), synchronous dynamic RAM (SDRAM), static RAM (SRAM), ferroelectric RAM (FeRAM), magnetic RAM (MRAM), resistive RAM (RRAM), flash memory, phase-change memory (PCM), etc.).

[0159] Controller 1202 can be configured to manage and coordinate various operations of processor 1200 (e.g., signaling, receiving, acquiring, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, and reading) to enable processor 1200 to support various operations of a base station according to the examples described herein. For example, controller 1202 can operate as a control unit of processor 1200 to generate control signals for managing the operation of various components of processor 1200. These control signals include enabling or disabling functional units, selecting data paths, initiating memory accesses, and coordinating operation timing.

[0160] Controller 1202 can be configured to fetch (e.g., fetch, retrieve, receive) instructions from memory 1204 and determine subsequent instructions(s) to be executed, enabling processor 1200 to support various operations according to the examples described herein. Controller 1202 can be configured to track the memory addresses of instructions associated with memory 1204. Controller 1202 can be configured to decode instructions to determine the operations to be performed and the operands involved. For example, controller 1202 can be configured to interpret instructions and determine control signals to be output to other components of processor 1200, enabling processor 1200 to support various operations according to the examples described herein. Additionally or alternatively, controller 1202 can be configured to manage data flow within processor 1200. Controller 1202 can be configured to control data transfers between registers, arithmetic logic unit (ALU), and other functional units of processor 1200.

[0161] Memory 1204 may include one or more caches (e.g., memory or other memory, such as RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc., local to or included in processor 1200). In some implementations, memory 1204 may reside within or on the processor chipset (e.g., local to processor 1200). In some other implementations, memory 1204 may reside outside the processor chipset (e.g., remote from processor 1200).

[0162] Memory 1204 may store computer-readable, computer-executable code, including instructions that, when executed by processor 1200, cause processor 1200 to perform the various functions described herein. The code may be stored in a non-transitory computer-readable medium, such as system memory or another type of memory. Controller 1202 and / or processor 1200 may be configured to execute computer-readable instructions stored in memory 1204 to cause processor 1200 to perform various functions. For example, processor 1200 and / or controller 1202 may be coupled to or coupled to memory 1204, and processor 1200, controller 1202, and memory 1204 may be configured to perform the various functions described herein. In some examples, processor 1200 may include multiple processors, and memory 1204 may include multiple memories. One or more of the multiple processors may be coupled to one or more of the multiple memories, which may be configured individually or collectively to perform the various functions described herein.

[0163] One or more ALU 1206s can be configured to support a variety of operations as described in the examples herein. In some implementations, one or more ALU 1206s may reside within or on a processor chipset (e.g., processor 1200). In some other implementations, one or more ALU 1206s may reside outside the processor chipset (e.g., processor 1200). One or more ALU 1206s can perform one or more calculations on data, such as addition, subtraction, multiplication, and division. For example, one or more ALU 1206s can receive input operands and an opcode that determines the operation to be performed. One or more ALU 1206s are configured with various logic and arithmetic circuitry, including adders, subtractors, shifters, and logic gates, to process and manipulate data according to the operations. Additionally or alternatively, one or more ALU 1206s may support logical operations such as AND, OR, XOR, NOR, and NAND, enabling one or more ALU 1206s to handle conditional operations, comparisons, and bitwise operations.

[0164] Based on the examples disclosed herein, processor 1200 may support wireless communication. Processor 1200 may be configured or operable to support components used for predicting CSI.

[0165] Figure 13 An example of a processor 1300 supporting a scheme for predicting CSI according to various aspects of this disclosure is illustrated. Processor 1300 may be an example of a processor configured to perform various operations according to the examples described herein. Processor 1300 may include a controller 1302 configured to perform various operations according to the examples described herein. Processor 1300 may optionally include at least one memory 1304, such as an L1 / L2 / L3 cache. Additionally or alternatively, processor 1300 may optionally include one or more arithmetic logic units (ALUs) 1306. One or more of these components may be electronically communicated or otherwise coupled (e.g., operative ground, communicative ground, functional ground, electronic ground, electrical ground) via one or more interfaces (e.g., buses).

[0166] Processor 1300 may be a processor chipset and includes a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receive, acquire, retrieve, send, output, forward, store, determine, identify, access, write, read) according to the examples described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to the processor chipset or included in the processor chipset (e.g., processor 1300)) or other memory (e.g., random access memory (RAM), read-only memory (ROM), dynamic RAM (DRAM), synchronous dynamic RAM (SDRAM), static RAM (SRAM), ferroelectric RAM (FeRAM), magnetic RAM (MRAM), resistive RAM (RRAM), flash memory, phase-change memory (PCM), etc.).

[0167] Controller 1302 can be configured to manage and coordinate various operations of processor 1300 (e.g., signaling, receiving, acquiring, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, and reading) to enable processor 1300 to support various operations of the UE according to the examples described herein. For example, controller 1302 can operate as a control unit of processor 1300 to generate control signals for managing the operation of various components of processor 1300. These control signals include enabling or disabling functional units, selecting data paths, initiating memory accesses, and coordinating operation timing.

[0168] Controller 1302 can be configured to fetch (e.g., fetch, retrieve, receive) instructions from memory 1304 and determine subsequent instructions(s) to be executed, enabling processor 1300 to support various operations according to the examples described herein. Controller 1302 can be configured to track the memory addresses of instructions associated with memory 1304. Controller 1302 can be configured to decode instructions to determine the operations to be performed and the operands involved. For example, controller 1302 can be configured to interpret instructions and determine control signals to be output to other components of processor 1300, enabling processor 1300 to support various operations according to the examples described herein. Additionally or alternatively, controller 1302 can be configured to manage data flow within processor 1300. Controller 1302 can be configured to control data transfers between registers, arithmetic logic unit (ALU), and other functional units of processor 1300.

[0169] Memory 1304 may include one or more caches (e.g., memory local to or included in processor 1300, such as RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc.). In some implementations, memory 1304 may reside within or on the processor chipset (e.g., locally to processor 1300). In some other implementations, memory 1304 may reside outside the processor chipset (e.g., remotely from processor 1300).

[0170] Memory 1304 may store computer-readable, computer-executable code, including instructions that, when executed by processor 1300, cause processor 1300 to perform the various functions described herein. The code may be stored in a non-transitory computer-readable medium, such as system memory or another type of memory. Controller 1302 and / or processor 1300 may be configured to execute computer-readable instructions stored in memory 1304 to cause processor 1300 to perform various functions. For example, processor 1300 and / or controller 1302 may be coupled to or coupled to memory 1304, and processor 1300, controller 1302, and memory 1304 may be configured to perform the various functions described herein. In some examples, processor 1300 may include multiple processors, and memory 1304 may include multiple memories. One or more of the multiple processors may be coupled to one or more of the multiple memories, which may be configured individually or collectively to perform the various functions described herein.

[0171] One or more ALU 1306s can be configured to support a variety of operations as described in the examples herein. In some implementations, one or more ALU 1306s may reside within or on a processor chipset (e.g., processor 1300). In some other implementations, one or more ALU 1306s may reside outside the processor chipset (e.g., processor 1300). One or more ALU 1306s can perform one or more calculations on data, such as addition, subtraction, multiplication, and division. For example, one or more ALU 1306s can receive input operands and an opcode that determines the operation to be performed. One or more ALU 1306s are configured with various logic and arithmetic circuitry, including adders, subtractors, shifters, and logic gates, to process and manipulate data according to the operations. Additionally or alternatively, one or more ALU 1306s may support logical operations such as AND, OR, XOR, NOR, and NAND, enabling one or more ALU 1306s to handle conditional operations, comparisons, and bitwise operations.

[0172] Based on the examples disclosed herein, processor 1300 may support wireless communication. Processor 1300 may be configured or operable to support components used for predicting CSI.

[0173] Figure 14 A flowchart illustrating a method 1400 supporting a scheme for predicting CSI according to various aspects of this disclosure is provided. Operation of method 1400 may be implemented by the device or components thereof described herein. For example, operation of method 1400 may be performed by the UE 104 described herein. In some implementations, the device may execute a set of instructions to control the functional elements of the device to perform the described functions. Additionally or alternatively, the device may use dedicated hardware to perform aspects of the described functions.

[0174] At 1405, the method may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RS associated with at least one parameter. The operation of 1405 may be performed according to the examples described herein. In some implementations, aspects of the operation of 1405 may be performed by the device described with reference to FIG1.

[0175] At 1410, the method may include determining to use one or more of at least one prediction model to predict a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window. The operation of 1410 may be performed according to the examples described herein. In some implementations, aspects of the operation of 1410 may be performed by the device described with reference to FIG1.

[0176] Figure 15 A flowchart illustrating a method 1500 for predicting CSI according to various aspects of this disclosure is shown. Operation of method 1500 may be implemented by the device or components thereof described herein. For example, operation of method 1500 may be performed by network entity 102 described herein. In some implementations, the device may execute a set of instructions to control functional elements of the device to perform the described functions additionally or alternatively, and the device may use dedicated hardware to perform aspects of the described functions.

[0177] At 1505, the method may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RS associated with at least one parameter. The operation of 1505 may be performed according to the examples described herein. In some implementations, aspects of the operation of 1505 may be performed by the device described with reference to FIG1.

[0178] At 1510, the method may include receiving one or more CSI reports for a prediction window from the UE via a transceiver, the one or more CSI reports being based on at least one CSI-RS in a measurement window corresponding to the prediction window. Operation of 1510 may be performed according to the examples described herein. In some implementations, aspects of the operation of 1510 may be performed by the device described with reference to FIG1.

[0179] It should be noted that the methods described in this paper describe possible implementations, and the operations and steps can be rearranged or otherwise modified, and other implementations are also possible. Furthermore, aspects from two or more methods can be combined.

[0180] The various illustrative boxes and components disclosed herein can be implemented or performed using a general-purpose processor, DSP, ASIC, CPU, FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware component or any combination thereof designed to perform the functions described herein. The general-purpose processor may be a microprocessor, but alternatively, the processor may be any processor, controller, microcontroller or state machine. The processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration).

[0181] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored on or transmitted via a computer-readable medium as one or more instructions or code. Other examples and implementations are within the scope of this disclosure and the appended claims. For example, due to the nature of software, the functions described herein can be implemented using software executed by a processor, hardware, firmware, hardwiring, or any combination thereof. Features implementing the functions can also be physically located in various locations, including being distributed such that portions of the functions are implemented in different physical locations.

[0182] Computer-readable media include both non-transitory computer storage media and communication media, with communication media including any medium that facilitates the transfer of a computer program from one place to another. Non-transitory storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, non-transitory computer-readable media can include RAM, ROM, electrically erasable programmable ROM (EEPROM), flash memory, optical disc (CD) ROM or other optical disc storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor.

[0183] As used herein, including in the claims, the article “a” preceding an element is unrestricted and should be understood to mean “at least one” or “one or more” of those elements. The terms “a,” “at least one,” “one or more,” and “at least one of one or more” are interchangeable. As used herein, including in the claims, the use of “or” in a list of items (e.g., a list of items beginning with phrases such as “at least one of…” or “one or more of…” or “one or two of…”) indicates an inclusive list, such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C). Furthermore, as used herein, the phrase “based on” should not be construed as a reference to a closed set of conditions. For example, an example step described as “based on condition A” without departing from the scope of this disclosure could be based on both condition A and condition B. In other words, as used herein, the phrase “based on” should be interpreted in the same manner as the phrase “at least partially based on.” Furthermore, as used herein, including in the claims, “set” can include one or more elements.

[0184] The description provided herein is intended to enable those skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the scope of this disclosure. Therefore, this disclosure is not limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A user equipment (UE), comprising: processor; as well as The transceiver is coupled to the processor. The processor is configured as follows: At least one prediction model is determined, wherein each of the at least one prediction model is determined based on a channel state information (CSI) reference signal (RS) associated with at least one parameter; as well as Determine whether to use one or more of the at least one prediction model to predict CSI reports for the prediction window based on at least one CSI-RS in the measurement window corresponding to the prediction window.

2. The UE according to claim 1, wherein the at least one parameter includes one of the following: The number of CSI-RS in the measurement window; The interval of CSI-RS in the measurement window; Symbols used for CSI-RS, which may or may not be configured with an uplink (UL) subband; or The CSI-RS pattern in the measurement window, wherein the CSI-RS pattern indicates at least one of the following: the CSI-RS position in the measurement window, at least one interval of the CSI-RS, or the number of CSI-RS.

3. The UE of claim 1, wherein, in the event that one or more CSI-RSs are cancelled in the measurement window, the at least one CSI-RS used to predict the CSI report comprises: At least one remaining CSI-RS in the measurement window; or The at least one remaining CSI-RS and at least one supplementary CSI-RS, wherein the supplementary CSI-RS is determined based on the remaining CSI-RS.

4. The UE of claim 3, wherein the CSI-RS in the one or more CSI-RSs is cancelled in one of the following situations: The CSI-RS overlaps with the UL symbol; The CSI-RS is used in symbols or time slots not configured with UL subbands, and in prediction models associated with symbols or time slots configured with UL subbands; or One or more CSI-RS are used in symbols or time slots configured with UL subbands, and prediction models are used in symbols or time slots not configured with UL subbands.

5. The UE of claim 1, wherein each of the at least one prediction model is determined based on one of the following: A combination of CSI-RS associated with a symbol or time slot configured with a UL subband and CSI-RS associated with a symbol or time slot not configured with a UL subband; CSI-RS associated with a symbol or time slot configured with UL subbands; or CSI-RS associated with symbols or time slots that are not configured with UL subbands.

6. The UE of claim 1, wherein the processor is further configured to: In the measurement window, when all CSI-RS are in the symbol or time slot configured with UL subbands, the prediction model in at least one prediction model determined based on the CSI-RS associated with the symbol or time slot configured with UL subbands is used for prediction; or In the measurement window, when all CSI-RS are in the symbol or time slot not configured with UL subbands, the prediction model in at least one prediction model determined based on the CSI-RS associated with the symbol or time slot not configured with UL subbands is used for prediction.

7. The UE of claim 1, wherein the processor is further configured to: If none of the parameters of the CSI-RS in the measurement window are the same as the parameters associated with one of the at least one prediction models, then the prediction of the CSI report is prevented; or If the number of corresponding parameters of CSI-RS with different parameters in the measurement window exceeds a threshold, the prediction of the CSI report is prevented.

8. The UE according to claim 7, wherein the processor is further configured to: Cancel the CSI report for the forecast window; Transmit the CSI report for the CSI-RS in the measurement window via the transceiver; or The transceiver detects scheduling information from the base station for scheduling the CSI report for the prediction window.

9. The UE of claim 1, wherein the processor is further configured to predict the CSI report based on a selected prediction model from the at least one prediction model: The number of CSI-RS in the measurement window is the same as the number of CSI-RS used to determine the selected prediction model; or The symbol or slot format of the CSI-RS in the measurement window is the same as the slot format associated with the CSI-RS used to determine the selected prediction model.

10. The UE of claim 1, wherein the processor is further configured to predict the CSI report based on a prediction model in the at least one prediction model for a symbol or time slot configured with a UL subband: The number of CSI-RS in symbols or time slots configured with UL subbands in the measurement window is greater than the number of CSI-RS in symbols or time slots not configured with UL subbands in the measurement window; or The measurement window is configured with the symbol of the UL sub-band or the first CSI-RS in the time slot.

11. The UE of claim 1, wherein the processor is further configured to: When the number of CSI-RS in a symbol or time slot configured with a UL subband in the measurement window is the same as the number of CSI-RS in a symbol or time slot not configured with a UL subband in the measurement window, the CSI report is predicted based on a predefined or indicated prediction model.

12. The UE of claim 1, wherein the prediction model in the at least one prediction model is determined based on CSI-RS associated with parameters X and Y, wherein X is the minimum number of CSI-RS instances and Y is the maximum interval of the CSI-RS instances. Furthermore, the processor is configured to: If X for the first prediction model is less than or equal to the number of CSI-RS in the measurement window, and / or When Y for the first prediction model is greater than or equal to the CSI-RS interval within the measurement window, The CSI report is predicted based on the first prediction model.

13. The UE of claim 12, wherein the processor is further configured to select a first prediction model from the first prediction models to predict the CSI report, wherein the selected first prediction model is associated with: a CSI-RS pattern that is the same as the CSI-RS pattern in the measurement window; an interval of CSI-RS that is the same as the interval of CSI-RS in the measurement window; or a number of CSI-RS that is the same as the number of CSI-RS in the measurement window.

14. The UE of claim 1, wherein the processor is further configured to predict the CSI report based on a predefined, preconfigured, or base station-indicated prediction model.

15. The UE of claim 1, wherein the processor is further configured to: Multiple CSI reports are predicted based on multiple prediction models in the at least one prediction model, wherein the multiple prediction models are determined based on at least one parameter that is the same as at least one parameter in the measurement window; or The multiple CSI reports are predicted based on the at least one prediction model.

16. The UE of claim 15, wherein the processor is further configured to: The multiple CSI reports are sent to the base station via the transceiver; or The transceiver transmits a CSI report, determined based on the average of the plurality of CSI reports, to the base station.

17. The UE of claim 1, wherein the processor is further configured to: The first CSI report is predicted based on a predictive model associated with a symbol or time slot configured with a UL subband. Predicting second CSI reports based on prediction models associated with symbols or time slots not configured with UL subbands; and The first CSI report and the second CSI report are sent to the base station via the transceiver.

18. The UE of claim 1, wherein determining to use one or more of the at least one prediction model to predict the CSI report comprises: If none of the parameters of the CSI-RS in the measurement window are the same as those associated with one of the prediction models in the at least one prediction model, the extended measurement window is determined based on extending the measurement window by one or more time units. The CSI-RS report is determined to be predicted based on the one or more prediction models until one or more parameters of the CSI-RS in the expanded measurement window are the same as one or more parameters associated with one or more prediction models in the at least one prediction model.

19. The UE of claim 1, wherein the parameter associated with the at least one CSI-RS in the measurement window is the same as the parameter used to determine one or more of the at least one prediction models.

20. A base station (BS), comprising: processor; as well as The transceiver is coupled to the processor. The processor is configured as follows: At least one prediction model is determined, wherein each of the at least one prediction model is determined based on a channel state information (CSI) reference signal (RS) associated with at least one parameter; as well as The transceiver receives one or more CSI reports for a prediction window from the user equipment (UE), the one or more CSI reports being based on at least one CSI-RS in a measurement window corresponding to the prediction window.

21. The BS of claim 20, wherein the at least one parameter comprises one of the following: The number of CSI-RS in the measurement window; The interval of CSI-RS in the measurement window; Symbols used for CSI-RS, which may or may not be configured with an uplink (UL) subband; or The CSI-RS pattern in the measurement window, wherein the CSI-RS pattern indicates at least one of the following: the CSI-RS position in the measurement window, at least one interval of the CSI-RS, or the number of CSI-RS.

22. The BS of claim 20, wherein the parameter associated with the at least one CSI-RS in the measurement window is the same as the parameter used to determine one or more of the at least one prediction models.

23. The BS of claim 20, wherein the processor is further configured to: The transceiver sends an instruction to the UE indicating which of the at least one prediction models to use to predict the CSI report.

24. The BS of claim 20, wherein the processor is further configured to: If none of the parameters of the CSI-RS in the measurement window are the same as the parameters associated with one of the at least one prediction models, or if the number of corresponding parameters of CSI-RS with different parameters in the measurement window exceeds a threshold, Prevent receiving the CSI report; Receive the CSI report for the CSI-RS in the measurement window via the transceiver; or The transceiver transmits scheduling information for scheduling the CSI reports for the prediction window.

25. The BS of claim 20, wherein the processor is further configured to: Receive, via the transceiver, multiple CSI reports based on multiple prediction models in the at least one prediction model, wherein the multiple prediction models are determined based on at least one parameter that is the same as at least one parameter in the measurement window; or Multiple CSI reports based on the at least one prediction model are received via the transceiver.

26. A processor for wireless communication, comprising: At least one memory; as well as A controller, coupled to the at least one memory, and configured such that the controller: At least one prediction model is determined, wherein each of the at least one prediction model is determined based on a channel state information (CSI) reference signal (RS) associated with at least one parameter; as well as Determine whether to use one or more of the at least one prediction model to predict CSI reports for the prediction window based on at least one CSI-RS in the measurement window corresponding to the prediction window.

27. A processor for wireless communication, comprising: At least one memory; as well as A controller, coupled to the at least one memory, and configured such that the controller: At least one prediction model is determined, wherein each of the at least one prediction model is determined based on a channel state information (CSI) reference signal (RS) associated with at least one parameter; as well as The transceiver receives one or more CSI reports for the prediction window from the user equipment (UE), the one or more CSI reports being based on at least one CSI-RS in the measurement window corresponding to the prediction window.

28. A method performed by a user equipment (UE), comprising: At least one prediction model is determined, wherein each of the at least one prediction model is determined based on a channel state information (CSI) reference signal (RS) associated with at least one parameter; as well as Determine whether to use one or more of the at least one prediction model to predict CSI reports for the prediction window based on at least one CSI-RS in the measurement window corresponding to the prediction window.

29. A method performed by a base station (BS), comprising: At least one prediction model is determined, wherein each of the at least one prediction model is determined based on a channel state information (CSI) reference signal (RS) associated with at least one parameter; as well as Receive one or more CSI reports for a prediction window from a user equipment (UE), the one or more CSI reports being based on at least one CSI-RS in a measurement window corresponding to the prediction window.

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