Control mechanisms for multi-transmit / receive communications.

Abstract

An apparatus for use by a communication element or function capable of performing multi-transmission point TRP operations, comprising at least one processing circuit and at least one memory for storing instructions, which, when executed by the at least one processor, cause the apparatus to at least obtain channel state information reporting configuration information for enabling group-based beam reporting based on prediction (S510), receive a plurality of beams including at least one set of beams for measurement and at least one set of beams for prediction (S520), determine associations of the received plurality of beams with respective TRPs of a communication network (S530), measure resources from the at least one set of beams for measurement to identify beam groups for simultaneous reception (S540), and determine further beam groups usable for simultaneous reception by using a prediction model, the further beam groups including beams from the at least one set of beams for measurement and the at least one set of beams for prediction.

Description

[Technical Field]

[0001] Examples of the present disclosure relate to apparatuses, methods, systems, computer programs, computer program products, and (non-transitory) computer-readable media that can be used to control multiple transmission points using beam management. In particular, examples of the present disclosure relate to apparatuses, methods, systems, computer programs, computer program products, and (non-transitory) computer-readable media that can be used to enable improved beam management that enables a communication element or communication function, such as a user equipment, to communicate with multiple transmission and reception points of a communication network. [Background technology]

[0002] The following description of the background art may include insights, discoveries, understandings or disclosures, or associations that were unknown about the relevant prior art to at least some example embodiments of the present disclosure, together with the disclosures provided by the present disclosure. Some of such contributions of the present disclosure may be specifically pointed out below, while others of such contributions of the present disclosure will be apparent from the relevant context.

[0003] The following meanings apply to the abbreviations used herein: 3GPP 3rd Generation Partnership Project (3 rd Generation Partnership Project) 4G (fourth generation) 5G fifth generation AI artificial intelligence CPU central processing unit CIR configuration information request CRI CSI-RS resource indicator CSI Channel State Information DL downlink DCI Downlink Control Information eNB E-UTRAN Node B (E-UTRAN Node B) FNN: Fully connected neural network FR frequency range gNB Next generation node B ID identification L1 Level 1 LTE Long Term Evolution LTE-A LTE Advanced ML machine learning MU MIMO Multi-user multiple input multiple output NN neural network NW network, network side PDCCH Physical downlink control channel PDSCH Physical downlink shared channel RS reference signal RSRP reference signal receiving power RRC (radio resource control) Rx receiver SINR signal to interference plus noise ratio SGD Stochastic Gradient Descent SSB synchronization signal block TRP transmission reception point Tx transmitter UE User Equipment UL uplink Summary of the Invention [Means for solving the problem]

[0004] According to an example embodiment, for example, an apparatus is provided for use by a communication element or communication function capable of performing multi-transmission point TRP operations, the apparatus comprising at least one processing circuit and at least one memory for storing instructions that, when executed by the at least one processor, cause the apparatus to at least obtain channel state information reporting configuration information to enable group-based beam reporting based on prediction, receive a plurality of beams including at least one set of beams for measurement and at least one set of beams for prediction, determine associations of the received plurality of beams with respective TRPs of the communication network, measure resources from the at least one set of beams for measurement to identify beam groups for simultaneous reception, and determine further beam groups usable for simultaneous reception by using a prediction model, the further beam groups including beams from the at least one set of beams for measurement and the at least one set of beams for prediction.

[0005] Further, according to an example embodiment, there is provided a method for use in, for example, a communication element or communication function capable of performing multi-transmission point TRP operations, the method including: obtaining channel state information reporting configuration information to enable group-based beam reporting based on prediction; receiving a plurality of beams including at least one set of beams for measurement and at least one set of beams for prediction; determining associations of the received plurality of beams with respective TRPs of the communication network; measuring resources from the at least one set of beams for measurement to identify beam groups for simultaneous reception; and determining further beam groups usable for simultaneous reception by using a prediction model, wherein the further beam groups include beams from the at least one set of beams for measurement and the at least one set of beams for prediction.

[0006] According to further refinements, these examples may include one or more of the following features: - if the prediction based on the prediction model results in the output of at least one further beam group, at least some of the resulting further beam groups may be reported to a TRP of the communication network in a predefined order, the predefined order reflecting a suitability level of the reported further beam groups for simultaneous reception; - when reporting at least some of the resulting further beam groups, additional parameters may be included that indicate communication characteristics of the beams of the at least one further beam group, the communication characteristics may include at least one of a reference signal received power indication, a signal-to-interference-plus-noise ratio, a reliability metric associated with the prediction model used, and an indication of a capability value set; - A capability for supporting prediction-based group-based beam reporting may be reported to a TRP of the communication network, and channel state information reporting configuration information may be received in response to the capability report; - a predefined or received configuration indicating the association of the received reference signal with at least two transmission points of the communication network may be used to determine the association of the received plurality of beams with each TRP of the communication network; - A beam may be represented by downlink reference signal resources including at least one of channel state information reference signal and synchronization signal block resources, and the downlink reference signal resources may be grouped into groups each corresponding to a respective TRP; - at least one set of beams for measurement may include downlink reference signals transmitted by a corresponding TRP, and at least one set of beams for prediction may include downlink reference signals not transmitted by a corresponding TRP; - the identified beam group or the beam group forming the further beam group may include one of a) beams corresponding to two TRPs or spatial filters, where at least one beam corresponds to one TRP or spatial filter and another beam corresponds to another TRP or spatial filter, or b) beams corresponding to only one TRP or spatial filter, where one subset of the beams of the beam group are from the set of beams for measurement and another subset of the beams of the beam group are determined from the set of beams for prediction; - To identify a beam group for simultaneous reception, at least one of a reference signal received power or a channel state information amount may be measured based on a signal transmission from the communication network as a resource from at least one set of beams for measurement; - the prediction model used to determine the further beam groups available for simultaneous reception may be a machine learning prediction model using a neuronal network configuration having a plurality of neuronal network blocks including at least one of a fully connected neuronal network block, an activation function layer, and a batch normalization layer; - the prediction model used to determine the further beam groups available for simultaneous reception may be a non-machine learning prediction model; - Identified beam groups for beam measurements and simultaneous reception can be used as input data for the prediction model; - the prediction model to be applied may be determined based on information provided by the obtained channel state information reporting configuration information; - at least a portion of the determined further beam groups usable for simultaneous reception may be reported as uplink control information to the communication network; - spatial filters may be applied that are adjusted to receive beams identified or determined as usable for simultaneous reception; and A communication element or communication function may be included in a user equipment having multiple receiving panels for simultaneously receiving beams from multiple TRPs of the communication network.

[0007] According to an example embodiment, an apparatus is provided for use by, for example, a communications network control element or communications network control function acting as a transmission / reception point TRP for communicating with a communications element or communications function, the apparatus comprising at least one processing circuit and at least one memory for storing instructions that, when executed by the at least one processor, cause the apparatus to at least receive an indication of the communications element's or communications function's capability to support prediction-based group-based beam reporting, and cause the communications element or communications function to transmit channel state information reporting configuration information to enable prediction-based group-based beam reporting.

[0008] Further, according to an example embodiment, a method is provided for use in, for example, a communication network control element or communication network control function acting as a transmission / reception point TRP for communicating with a communication element or communication function, the method including receiving an indication of the communication element's or communication function's capability to support prediction-based group-based beam reporting, and transmitting channel state information reporting configuration information to the communication element or communication function to enable prediction-based group-based beam reporting.

[0009] According to further refinements, these examples may include: - Predictive group-based beam reporting may be triggered by triggering aperiodic channel state information reporting for communication elements or communication functions corresponding to the channel state information reporting configuration information.

[0010] Further, according to embodiments, there is provided, for example, a computer program product for a computer, comprising software code portions for performing the steps of the above-defined method when said product is executed on a computer. The computer program product may comprise a computer-readable medium on which said software code portions are stored. Furthermore, the computer program product can be directly readable into the internal memory of a computer and / or can be transmitted over a network by at least one of an upload, download and push procedure.

[0011] Some examples of the disclosure relating to embodiments are now described, by way of example only, with reference to the accompanying drawings, in which: [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 illustrates an example communication network environment in which examples of the present disclosure may be implemented. [Figure 2] FIG. 10 is a signaling diagram illustrating an example of a beam reporting procedure according to an example of the present disclosure. [Figure 3]FIG. 1 is a diagram of a beam measurement procedure according to an example of the present disclosure. [Figure 4] FIG. 1 is a diagram of a NN design for beam prediction according to an example of the present disclosure. [Figure 5] 1 is a flowchart of processing performed in a communications element or function, according to some examples of the present disclosure. [Figure 6] 1 is a flowchart of processing performed in a communications network control element or function, according to some examples of the present disclosure. [Figure 7] FIG. 2 is a diagram of communication elements or functions according to some examples of the present disclosure. [Figure 8] FIG. 1 is a diagram of a communication network control element or function according to some examples of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0013] For example, wire-based communication networks such as Integrated Services Digital Network (ISDN) and Digital Subscriber Line (DSL) or cellular third generation (3G) systems such as cdma2000 (code division multiple access) systems and Universal Mobile Telecommunications System (UMTS) systems. rdgeneration), fourth generation (4G) communication networks, or enhanced communication networks based for example on Long Term Evolution (LTE) or Long Term Evolution Advanced (LTE-A), fifth generation (5G) communication networks, Global System for Mobile communications (GSM), General Packet Radio System (GPRS), cellular second generation (2G) networks such as Enhanced Data Rates for Global Evolution (EDGE), ndFurther expansion of communication networks, such as wireless communication networks, such as (internal) generation communication networks, or other wireless communication systems, such as wireless local area networks (WLANs), Bluetooth, or Worldwide Interoperability for Microwave Access (WiMAX), has occurred throughout the world in recent years. Various organizations, such as the European Telecommunications Standards Institute (ETSI), the 3rd Generation Partnership Project (3GPP), Telecoms & Internet converged Services & Protocols for Advanced Networks (TISPAN), the International Telecommunication Union (ITU), the 3rd Generation Partnership Project 2 (3GPP2), the Internet Engineering Task Force (IETF), the Institute of Electrical and Electronics Engineers (IEEE), and the WiMAX Forum, are working on standards or specifications for telecommunication networks and access environments.

[0014] Several developments have been made to improve communication network performance, such as throughput, robustness, accuracy, or reliability. For example, in 5G networks, beamforming (or beam management) and MU-MIMO are used in combination to improve performance, e.g., in terms of throughput and connection density. Massive MIMO uses multiple antenna arrays and spatial multiplexing to transmit independent, individually coded data signals known as "streams." This allows simultaneous communication with multiple user equipment (UE) over the same time period and frequency resources. On the other hand, beamforming is used in conjunction with MIMO to more tightly focus communication beams toward individual UEs, enabling higher connection density and minimizing interference between individual beams.

[0015] To further improve performance, as one example, research into artificial intelligence (AI) / machine learning (ML) for the NR air interface is being conducted, for example, in Release 18 of the 3GPP specifications. The goal is to explore the benefits of augmenting the air interface with features that enable improved support for AI / ML-based algorithms for enhanced performance and / or reduced complexity / overhead. As a goal, sufficient use cases should be considered to enable the identification of a general AI / ML framework, including functional requirements for an AI / ML architecture that can be used in various projects. It also seeks to identify areas where AI / ML can improve the performance of air interface functions.

[0016] One initial use case involves beam management, where strategies related to beam prediction in the spatial domain (BM-Case 1) and beam prediction in the time domain (BM-Case 2) are explored to reduce overhead and latency.

[0017] With regard to the use cases BM-Case 1 and BM-Case 2 shown above, e.g., with regard to AI / ML-based beam management, it is agreed that BM-Case 1 is considered in relation to spatial-domain DL beam prediction for set A of beams based on measurement results of set B of beams, while BM-Case 2 is considered in relation to temporal DL beam prediction for set A of beams based on historical measurement results of set B of beams. Note that the beams in set A and set B can be in the same frequency range (FR). For use case BM-Case 1, it is possible, for example, that set B is a subset of set A or that the beams in set A and set B are different. In general, set B is for DL ​​beam measurements and set A is for DL ​​prediction.

[0018] With respect to the AI / ML input, it is considered that only L1-RSRP measurements are made based on Set B, or alternatively, L1-RSRP measurements are made based on Set B and aiding information. For example, the available aiding information may include one or more of: Tx and / or Rx beam shape information (e.g., Tx and / or Rx beam pattern, Tx and / or Rx beam boresight direction (azimuth and elevation), 3 dB beam width, etc.), expected Tx and / or Rx beam for prediction (e.g., expected Tx and / or Rx angle for prediction, Tx and / or Rx beam ID), UE location information, UE direction information, Tx beam usage information, UE orientation information, etc.

[0019] In communication networks such as 5G new radio (NR) systems, beamforming is used both at the network-side transmit / receive point (TRP), such as a gNB, and at the user equipment (UE) side. Beam management is used to acquire and maintain the TRP and UE beam for communication. For example, a beam management procedure is used to determine an appropriate Tx beam to be used by the TRP and an appropriate Rx beam to be utilized by the UE. The selected TRP Tx beam and UE Rx beam are then used for communication. The reference signal for beam management is, for example, a channel state information reference signal (CSI-RS) or a synchronization signal block (SSB).

[0020] For example, the TRP sends a specific reference signal to the UE, and the UE uses the reference signal to measure the radio link quality. After the measurement, the UE may report to the TRP which Tx beam is better for communication, and the reported content may include the Tx beam index or beam pair link index and the reference signal received power (RSRP). Considering a large number of beams, the overhead for reporting the beam status may be high. To reduce this overhead, group-based beam reporting has been proposed. The UE may report several Tx beams that can be received simultaneously, such as two.

[0021] More specifically, in 3GPP, the following group-based beam reporting mechanism is provided:

[0022] In Release 15, groupBasedBeamReporting allows a UE to report two beams that can be received by the UE simultaneously. The UE does not know whether the two beams are from the same TRP or different TRPs. For example, Release 15 reporting is valid for L1-RSRP or L1-SINR reporting (CSI-ReportConfig with reportQuantity set to 'cri-RSRP', 'ssb-Index-RSRP', 'cri-RSRP-CapabilitySetIndex', 'ssb-Index-RSRP-CapabilitySetIndex', 'cri-SINR', 'ssb-Index-SINR', 'cri-SINR-CapabilitySetIndex', or 'ssb-Index-SINR-CapabilitySetIndex').

[0023] On the other hand, in Release 17, group-based beam reporting allows a UE to report two groups of CSI-RS or SSBRIs by selecting one CSI-RS or SSB from each of two CSI resource sets for reporting configuration so that the CSI-RS and / or SSB resources of each group can be received simultaneously by the UE. Here, the UE knows the association of the beam to the TRP and that the reported beams within a beam group are from different TRPs. Release 17 group-based beam reporting (groupBasedBeamReporting-r17) is supported by configuring the UE for two CSI resource sets. Otherwise, the number of configured CSI-RS resource sets is limited to one. Release 17 reporting is valid for L1-RSRP reporting (CSI-ReportConfig with reportQuantity set to 'cri-RSRP', 'ssb-Index-RSRP', 'cri-RSRP-CapabilitySetIndex', or 'ssb-Index-RSRP-CapabilitySetIndex').

[0024] Various exemplary examples of the present disclosure will be described below to illustrate a process for improving a UE's simultaneous communication with multiple TRPs using group-based reporting with AI / ML. For this purpose, a communication network architecture based on 3GPP standards for communication networks, such as 5G, will be used as an example of a communication network to which the examples of the present disclosure may be applied, but the present disclosure is not limited to such an architecture. It will be apparent to those skilled in the art that the examples of the present disclosure may also be applied to other types of networks, such as systems using Wi-Fi, worldwide interoperability for microwave access (WiMAX), Bluetooth®, personal communications services (PCS), ZigBee®, wideband code division multiple access (WCDMA), ultra-wideband (UWB) technology, mobile ad-hoc networks (MANETs), and wired access. Furthermore, although the description of some examples of the present disclosure relates to mobile communication networks without loss of generality, the principles of the present disclosure may be similarly extended and applied to any other type of communication network, such as a wired communication network.

[0025] The following examples and embodiments should be understood as illustrative examples only. Although the specification may refer to "one" or "several" examples or embodiments in several places, this does not necessarily mean that each such reference relates to the same example or embodiment, or that a feature applies only to a single example or embodiment. Also, single features of different embodiments may be combined to provide other embodiments. Furthermore, terms such as "comprises" and "includes" should be understood as not limiting the described embodiments to consisting only of those stated features; such examples and embodiments may also include features, structures, units, modules, etc. that are not expressly stated.

[0026] A basic system architecture of a (tele)communication network, including a mobile communication system, to which some examples of the present disclosure are applicable, may include one or more communication network architectures, including a wireless access network subsystem and a core network. Such architectures may include one or more communication network control elements or functions, access network elements, radio access network elements, access service network gateways, or base transceiver stations, such as a base station (BS), access point (AP), Node B (NB), eNB, or gNB, distributed or centralized units, that control respective coverage areas or cells, whereby one or more communication stations, e.g., communication elements, user devices, such as UEs, or terminal devices, such as another device with similar functionality, such as a modem chipset, chip, module, etc., can communicate over one or more channels by one or more communication beams to transmit several types of data in multiple access domains, which may be part of a station, element, function, or application capable of communicating, such as a UE, an element or function usable in a machine-to-machine communication architecture, or may be attached as a separate element to such an element, function, or application capable of communicating. Additionally, core network elements or network functions may be included, such as gateway network elements / functions, mobility management entities, mobile switching centers, servers, databases, etc.

[0027] The general functions and interconnections of the described elements and functions, which also depend on the type of actual network, are known to those skilled in the art and are described in the corresponding specifications, so a detailed description thereof will be omitted here. However, it should be noted that, other than those described in detail herein below, several additional network elements and signaling links may be utilized for communication to or from the elements, functions or applications, such as communication endpoints, servers, gateways, communication network control elements such as radio network controllers, and other elements of the same or other communication networks.

[0028] A communications network architecture as considered in the examples of this disclosure may also be capable of communicating with other networks, such as the public switched telephone network or the Internet, and with individual devices or groups of devices that are not considered part of the network, such as monitoring devices, such as cameras, sensors, arrays of sensors, etc. The communications network may also support the use of cloud services for virtual network elements or their functions, although it should be noted that virtual network portions of a telecommunications network may also be provided by non-cloud resources, such as, for example, an internal network. It should be recognized that network elements, such as access systems, core networks, etc., and / or their respective functionality, may be implemented by using any nodes, hosts, servers, access nodes, or entities, etc., appropriate for such use. In general, network functions may be implemented either as network elements on dedicated hardware, as software instances running on dedicated hardware, or as virtualized functions instantiated in a suitable platform, such as, for example, a cloud infrastructure.

[0029] Furthermore, a network element or network function such as a TRP of a UE, a gNB, etc., or other network element or network function as described herein, and any other element, function, or application, may be implemented by software, such as by a computer program product for a computer, and / or by hardware. To perform their respective processing, the correspondingly used device, node, function, or network element may include several means, modules, units, components, etc. (not shown) required for control, processing, and / or communication / signaling functionality. Such means, modules, units and components may include, for example, one or more processors or processing units including one or more processing units for executing instructions and / or programs and / or processing data, storage or memory units or means (e.g., ROM, RAM, EEPROM, etc.) for storing instructions, programs and / or data to serve as a working area for the processor or processing unit, etc., input or interface means (e.g., floppy disk, CD-ROM, EEPROM, etc.) for inputting data and instructions by software, user interfaces (e.g., screens, keyboards, etc.) for providing monitoring and operability to users, other interfaces or means for establishing links and / or connections under the control of a processor unit or part (e.g., wired and wireless interface means, e.g., wireless interface means including antenna units, etc. and means for forming wireless communication units, etc.), and the like, and each means for forming an interface such as a wireless communication unit may also be located at a remote location (e.g., a radio head or radio station, etc.). It should be noted that in this specification, a processing unit should not be considered as representing only a physical part of one or more processors, but may also be considered as a logical part of the processing tasks referred to performed by one or more processors.

[0030] It should be appreciated that, according to some examples, the concept of a so-called "liquid" or flexible network may be utilized, in which the operation and functionality of a network element, network function, or other entity of the network may be flexibly performed in different entities or functions, such as nodes, hosts, or servers. In other words, the "division of labor" between the involved network elements, functions, or entities may vary from case to case.

[0031] As used in this application, the term "circuitry" may refer to one or more or all of the following: (a) hardware-only circuit implementations (e.g., implementations in analog and / or digital circuitry only); and (b) (where applicable) any combination of hardware circuitry and software, such as: (i) combinations of analog and / or digital hardware circuitry with software / firmware; and (ii) any portion of a hardware processor with software (including digital signal processors, software, and memory that work together to cause a device, such as a mobile phone or server, to perform various functions) and hardware circuitry, and / or a processor, such as a microprocessor or portion of a microprocessor, that requires software (e.g., firmware) to operate but may not be present if not required for operation. This definition of circuit applies to all uses of the term in this application, including any claims. As a further example, the term circuit, as used in this application, encompasses a hardware circuit or processor (or processors) alone, or a portion of a hardware circuit or processor and its (or their) accompanying software and / or firmware implementation. The term circuit also encompasses, for example, a baseband integrated circuit or processor integrated circuit for a mobile device, or a similar integrated circuit in a server, cellular network device, or other computing or network device, where applicable to certain claim elements.

[0032] Figure 1 shows a diagram illustrating an example communication network environment in which examples of the present disclosure can be implemented. In particular, in Figure 1, a UE 10 is shown located within a communication network, as an example of a communication element or function, and the communication network is represented by two TRPs, namely TRP#1 20 and TRP#2 25, which are communication network control elements or functions, such as gNBs.

[0033] The UE 10 can communicate with multiple TRPs simultaneously. For example, the UE 10 includes multiple antenna panels 10-1, 10-2, and 10-3. The UE 10 uses the panels 10-1, 10-2, and 10-3 to support multi-TRP operation, and the multiple panels are used to communicate with one or more TRPs via beams that facilitate simultaneous reception.

[0034] The TRPs, i.e., TRP#1 20 and TRP#2 25 as shown in FIG. 1, each provide multiple beams, i.e., beams P1 to P4 in the case of TRP#2 and beams Q1 to Q4 in the case of TRP#1 20.

[0035] Note that the configuration illustrated in Figure 1 is merely an example for illustrative purposes. In an environment where multi-TRP communication is performed by a UE, more UEs, more TRPs, and more or fewer beams per TRP may be provided. Also, the number of panels per UE may vary.

[0036] There are situations in which not all beams are suitable for joint transmission to a UE, even though they may be individually received by the UE (by a single TRP transmission). For example, in the configuration illustrated in Figure 1, it may be assumed that UE 10 cannot simultaneously receive beams Q1 and P3 (or P4) because they are received at the same panel 10-2.

[0037] In other words, it is difficult for a UE operating in, say, FR2 to simultaneously receive from two TRPs unless the UEs have different panels. Therefore, the benefit to the network of scheduling transmissions in two (or more) beams is questionable unless it is known in advance that the UE will be able to receive them.

[0038] In this regard, as described above, group-based beam reporting may be utilized, where beams are divided into two sets and reporting is performed for the beam groups. However, in this regard, it should be considered that the beams used by each TRP may be individually subjected to beam refinement, and a pair of beams (beam groups) may be reported after such a beam refinement phase for each TRP. Generally, each TRP needs to transmit a large number of reference signals, such as SSB and CSI-RS, which raises overhead concerns because each beam is associated with a different SSB or CSI-RS resource. In addition, the overall beam reporting for group-based beam reporting may have a large latency because time is required for the TRP and UE to complete beam sweeping / refinement, and the selection of a beam group to support simultaneous transmission is usually based on multiple measurements.

[0039] According to an example of the present disclosure, a procedure is provided that enables improved beam management so that communication network performance can be enhanced when a communication element or communication function, such as a UE, communicates with multiple TRPs of a communication network. That is, according to an example of the present disclosure, for example, considering the above-mentioned BM-Case 1 (spatial domain beam prediction), a UE that supports multi-TRP operation (single DCI or multi-DCI), such as the UE 10 in FIG. 1, reports beam pairs that the UE 10 can simultaneously receive. The approach proposed in the example of the present disclosure allows the UE 10 to predict beam pairs for simultaneous reception. This can achieve reduced RS overhead and reduced latency in beam measurement and reporting.

[0040] In detail, according to the example of the present disclosure, the following procedure is proposed: The principles underlying the example of the present disclosure will be explained as an example of utilizing the approach according to the example of the present disclosure with reference to FIG.

[0041] The UE 10 obtains configuration information from the communication network, for example, that can be used for predictive group-based beam reporting. For example, when the UE 10 reports its ability to support such predictive group-based beam reporting to the communication network, the corresponding configuration information is obtained. Predictive group-based beam reporting involves an indication to the network that one or more beam pairs (or one or more beam groups) supporting simultaneous communication (i.e., reception at the UE side) can be reported based on beam prediction, for example, based on an algorithm, specific method, or implementation used at the UE side. Alternatively, there are other examples in which the UE 10 obtains the configuration information, for example, when responding to a corresponding inquiry from the network, or based on a preset configuration that assumes, for example, that a UE attaching to the network can support predictive group-based beam reporting.

[0042] For example, the UE 10 receives a CSI reporting configuration in response to a corresponding report, enabling group-based beam reporting based on prediction. Furthermore, the UE 10 receives multiple sets of beams, e.g., at least two sets of beams for measurement (referred to as Set B1 and Set B2) and at least two sets of beams for prediction (referred to as Set A1 and Set A2). Sets A1 and B1 are received from one TRP, e.g., TRP#1 20, and sets A2 and B2 are received from another TRP, e.g., TRP#2 25.

[0043] For example, according to some examples of the present disclosure, the entire measured set of beams (set B) may be a superset that includes the union of beams in set B1 and set B2. Furthermore, the entire predicted set of beams (set A) may be a superset that includes the union of beams in set A1 and set A2. According to some further examples of the present disclosure, set B1 may be a subset of set A1, and set B2 may be a subset of set A2. In another variation, set B1 and set A1 may be different from each other, and set B2 and set A2 may be different from each other.

[0044] According to some examples of the present disclosure, the UE 10 is configured to use a predefined or received configuration that indicates an association between a set of measurement / prediction beams (sets A1 / A2 and B1 / B2) and a TRP, such as a TRP ID, a physical cell ID, or a CORESETPoolIndex (CORESET represents a set of physical resources (i.e., a specific area on the NR downlink resource grid) and a set of parameters used to carry PDCCH / DCI). Alternatively, a reference index applied for PDCCH / PDSCH reception may also be used.

[0045] It should be noted that, according to some examples of the present disclosure, sets of beams may be associated with each other, for example, Set A1 and Set B1 (or Set A2 and Set B2) may be associated with each other based on a defined association between the set of beams and the TRP / PCI / CORESETPoolindex (or have a reference index applied for PDCCH / PDSCH reception).

[0046] Further, according to some examples of the present disclosure, UE10 measures resources from measurement sets, i.e., Set B1 and Set B2, and uses beam measurements (e.g., L1-RSRP and beam index) to identify suitable beam pairs for simultaneous reception from Set B1 and Set B2.

[0047] The UE 10 then determines additional beam groups or beam pairs that are suitable or usable for simultaneous reception. This determination is made by using a prediction model. The prediction model uses at least the beam measurements (L1-RSRP and beam index), set B1, and the identified beam groups / pairs from set B1 as inputs for the prediction model. The additional beam groups / pairs may include, for example: - a beam pair including a beam from a prediction set (e.g., set A1) corresponding to one TRP / PCI / CORESETPoolindex and a beam from another prediction set (e.g., set A2) corresponding to another TRP / PCI / CORESETPoolindex; - beam pairs comprising a beam from a measurement set (set B1 or set B2) corresponding to one TRP / PCI / CORESETPoolindex and a beam from a prediction set (set A2 or set A1) corresponding to another TRP / PCI / CORESETPoolindex, and - A beam pair including a beam from a measurement set (e.g., set B1) corresponding to one TRP / PCI / CORESETPoolindex and a beam from another measurement set (e.g., set B2) corresponding to another TRP / PCI / CORESETPoolindex.

[0048] After the determination, the UE 10 reports a predefined portion of the determined beam pairs to the network, for example, to the TRP#1 20. The predefined portion may include, for example, the best or most suitable beam pairs among the determined beam pairs in a preset order, for example, from best to worst or from worst to best. Furthermore, the information sent to the network may also include other information, such as additional parameters. These parameters may include, for example, one or more of: corresponding L1-RSRP / L1-SINR values, a reliability metric associated with the prediction, and a capability value set indication. It should also be noted that corresponding parameters may be omitted.

[0049] According to a further example of the present disclosure, UE10 may also report beam pairs / groups corresponding to both the identified beam groups / pairs (from sets B1 and B2) and the determined beam groups / pairs (from sets A1 / B1 and A2 / B2).

[0050] Furthermore, according to a further example of the present disclosure, the UE 10 may be configured to report a limited number of beam groups / pairs, each group / pair having at least two beams.

[0051] Once the determined beam pairs / groups are reported, the UE 10 may apply different spatial filters to receive the reported beam groups / pairs. Further, according to examples of the present disclosure, based on the reported beam groups / pairs, the UE 10 may be scheduled to simultaneously receive simultaneous data transmissions from multiple TRPs, where the corresponding reported beam pairs are assumed to receive the data.

[0052] Figure 2 shows a signaling diagram illustrating an example of a beam reporting procedure according to an example of the present disclosure. In particular, Figure 2 provides one possible way of implementing the above procedure. In the example shown in Figure 2, it is assumed that a periodic CSI-RS transmission and CSI reporting configuration is associated with aperiodic CSI triggering. This enables dynamic beam prediction reporting that takes measurements and predictions into account.

[0053] As shown in Figure 2, signaling between a UE (e.g., UE 10 in Figure 1) and two TRPs (e.g., TRP#1 20 and TRP#2 25 in Figure 1) is shown. On the UE side as a signaling instance, UL and DL communication elements, a measurement module for measuring signals received by beams, and a prediction model entity are provided.

[0054] At S200, the UE 10 sends a capability indication to the network (eg, TRP#1 20) indicating that it supports prediction-based group-based beam reporting.

[0055] At S210, the UE receives, e.g., via RRC, configuration information enabling group-based beam reporting, e.g., in the form of a CSI-ReportConfig. In this regard, information is provided that enables the UE 10 to further define beam sets for measurement and beam sets for prediction, e.g., up to four RS (Reference Signal) sets, where the CSI-ReportConfig may indicate the RS sets as CMR1 through CMR4 (i.e., sets A1 / A2 / B1 / B2 as above).

[0056] At S230, the UE 10 determines, based on the received CSI-ReportConfig information, which prediction model may be applied for group-based beam reporting and the associated RS set for measurement and prediction.

[0057] At S235, the UE 10 further determines that the RS set is associated with at least two TRPs (e.g., two CORESETPoolIndexes for the mDCI scenario). This association determination may be performed, for example, via a predefined configuration or a configuration received from the communication network. For example, at S235, it is determined that set A1 / B1 is associated with CORESETPoolIndex 0 (TRP#1 20) and set A2 / B2 is associated with CORESETPoolIndex 1 (TRP#2 25).

[0058] At S240, the network (i.e., TRP#1 20) triggers prediction-based group-based beam reporting by triggering aperiodic CSI reporting in DCI corresponding to the CSI-ReportConfig. Further, at S250 and S255, TRP#1 20 and TRP#2 25 send corresponding RS sets. The RSs may be sent, for example, periodically, semi-persistently, or aperiodically. For example, the UE 10 receives CSI-RS (or SSB) transmissions associated with set B1 from TRP#1 20 and set B2 from TRP#2 25.

[0059] At S260, the measurement module of the UE 10 measures, for example, the L1-RSRP or other appropriate CSI quantity based on the received CSI-RS (or SSB). The UE 10 further determines beam pairs (or beam groups) for simultaneous reception (i.e., for multi-TRP reception).

[0060] In S270, the beam measurements (e.g., beam index and further parameters such as measured L1-RSRP) and the identified beam pairs are used as inputs for a predictive model.

[0061] At S280, UE10 performs group-based beam prediction by using the prediction model (e.g., AI / ML model) determined at S230. As input for the prediction model, data provided based on the beam measurements at S260 corresponding to sets B1 and B2 are used. As a result of the prediction, for example, the best beam pair (group) for simultaneous reception taking into account sets A1 / B1 and A2 / B2 is determined. It is noted that an example of such an AI / ML prediction model is described below, for example, with reference to FIG. 4.

[0062] At S290, the output of the prediction model, including the determined best beam pair and the corresponding L1-RSRP, is provided, for example, in a preset ranking order, which is used by the UE to construct CSI feedback (as UL control information) to report, at S295, according to the reporting quantity configured in CSI-ReportConfig, which is used to report the CSI quantity to the communication network (e.g., TRP#1 20).

[0063] Further details regarding a beam measurement procedure according to an example of the present disclosure are shown in Figure 3. In particular, Figure 3 shows a procedure in which multi-TRP operation with a limited number of beam measurements from each TRP is supported.

[0064] 3, beams from TRP#1 20 and TRP#2 25 are shown, with beam set A1 including six beams (indicated by CRI_x1, RSRP_x1 to CRI_x6, RSRP_x6) from TRP#1 20 and beam set A2 including six beams (indicated by CRI_y1, RSRP_y1 to CRI_y6, RSRP_y6) from TRP#2 25. In the example of FIG. 3, it is assumed that sets B1 and B2 are subsets of sets A1 and A2, respectively.

[0065] Beam measurements without RSRP are referred to as set B1 (e.g., CRI_x4, CRI_x3) and set B2 (e.g., CRI_y3, CRI_y5), which correspond to TRP#1 20 and TRP#2 25, respectively. Note that the numbers shown in parentheses refer to the expected relative strength of L1-RSRP for each measured beam (i.e., (0) to (3), where (0) represents no RSRP and (3) represents high RSRP).

[0066] 3, two beam pairs are identified by the UE 10 based on the beam measurements (e.g., CRI_x5, CRI_y4 and CRI_x6, CRI_y1). These beam pairs represent identified beam pairs.

[0067] Reference numeral 30 in Figure 3 represents a prediction model. The input of the prediction model is provided by beam measurements (i.e., identified beam pairs, beam indices, and L1-RSRP values). Based on the input, the prediction model 30 predicts more beam pairs and corresponding L1-RSRPs for sets A1 and A2, which are indicated as determined beam pairs available for simultaneous reception based on the prediction (i.e., for example, beam pairs CRI_x1, CRI_y3 and CRI_x4, CRI_y1 in addition to the identified beam pairs CRI_x5, CRI_y4 and CRI_x6, CRI_y1).

[0068] Next, FIG. 4 shows a diagram of a NN design for spatial beam prediction according to an example of the present disclosure, as an example of a prediction model usable in connection with an example of the present disclosure. Note that FIG. 4 illustrates only one example of a usable prediction model. In general, the usable prediction model may be selected by the UE based on, for example, implementation decisions, and various approaches may be used by the UE for the prediction model, such as machine learning (ML) or non-machine learning (non-ML) based models, and the accuracy of the prediction may be variably set.

[0069] 4, beam measurements 400 of set B1 and beam measurements 410 of set B2 are used as inputs for the predictive model. Additionally, identified beam pairs for the beam measurements (from set B1 and set B2) are used.

[0070] The prediction model is composed of multiple NN blocks (NN Block 1 to NN Block L in Figure 4). NN Block 1 takes as input beam measurements considering CRI and RSRP measurements for each set of beams (Set B1 and Set B2) for CSI-RS resources xi (i = 1,...,N) and yi (i = 1,...,N), and the identified best beam pair (xi,yj) (i,j is selected from (i = 1,...,N)). Then, each inner NN block (2,...,L-1) calculates n h (i.e., the number of neurons), and finally, the NN block L has M output neurons corresponding to the CRI pairs (resource / beam pairs corresponding to the pairings of Set A1 and Set A2 resources, i.e., xi, yj (i, j = 1, ..., N)).

[0071] Note that each NN block may include a fully connected layer (FNN), an activation function layer, and a batch normalization layer, as shown in Figure 4. In this case, information travels only forward from the input to the output block.

[0072] In the lth NN block, the output vector m l is calculated using a nonlinear activation function σ,

number

number

number

number

number

number

number

number

[0073] The output of the network m L is then passed to the SoftMax function, and thus P y = softmax(m L ) and the probability distribution P m Therefore, we consider ranking these probabilities, for example in descending order, and selecting the best K beam pairs as follows:

number

[0074] According to an example of the present disclosure, an ML model (an example of which is illustrated in FIG. 4 ) may be trained using a stochastic gradient descent (SGD) algorithm, which calculates the weights W of the ML model. l Calculate the minimum value of the loss function in the direction of the gradient with respect to the input data.

number

number

number

[0075] Figure 5 illustrates a flowchart of processing performed in a communication element or function capable of multi-TRP operation, such as a UE, according to some examples of the present disclosure. That is, Figure 5 illustrates a flowchart related to processing performed by a communication element or function, such as a UE 10, as also described in conjunction with Figures 1 through 4. According to some examples of the present disclosure, the UE has multiple receive panels for simultaneously receiving beams from multiple TRPs of a communication network.

[0076] At S510, the UE obtains CSI reporting configuration information for enabling prediction-based group-based beam reporting. According to some examples of the present disclosure, to obtain the CSI reporting configuration information, the UE pre-reports a capability for supporting prediction-based group-based beam reporting to a TRP of a communication network, and the CSI reporting configuration information is received in response to the capability report.

[0077] At S520, the UE receives a plurality of beams, including at least one set of beams for measurement (referred to above as Set B) and at least one set of beams for prediction (referred to above as Set A).

[0078] At S530, the UE determines associations of the received beams to respective TRPs of the communication network.

[0079] According to some examples of the present disclosure, to determine the association of the received multiple beams with each TRP of the communication network, the UE uses a predefined or received configuration indicating the association of the received reference signal with at least two transmission points of the communication network.

[0080] At S540, the UE measures resources from at least one set of beams for measurement to identify a beam group for simultaneous reception.

[0081] It should be noted that, according to some examples of the present disclosure, the beams are represented by DL reference signal resources, including at least one of CSI RS and SSB resources, and the DL signal resources are grouped into groups each corresponding to a respective TRP (e.g., TRP#1 20 or TRP#2 25 as described above).

[0082] Further, according to some examples of the present disclosure, at least one set of beams for measurement includes downlink reference signals transmitted by the corresponding TRP, and at least one set of beams for prediction includes downlink reference signals not transmitted by the corresponding TRP.

[0083] According to some examples of the present disclosure, the beam groups forming the identified or further beam groups include beams corresponding to two TRPs or spatial filters, where at least one beam corresponds to one TRP or spatial filter and another beam corresponds to another TRP or spatial filter, or the beam groups forming the identified or further beam groups include beams corresponding to only one TRP or spatial filter, where one subset of the beams in each beam group are from the set of beams for measurement and another subset of the beams in each beam group are determined from the set of beams for prediction.

[0084] According to some examples of the present disclosure, to identify a beam group for simultaneous reception, at least one of RSRP or CSI quantities is measured based on signal transmissions from the communication network, for example, from RS transmissions from respective TRPs, as resources from at least one set of beams for measurement.

[0085] At S550, the UE determines a further beam group available for simultaneous reception by using the prediction model, the further beam group including beams from at least one set of beams for measurement and at least one set of beams for prediction.

[0086] According to some examples of the present disclosure, when a prediction based on the prediction model results in the output of at least one additional beam group, the UE reports at least some of the resulting additional beam groups to the TRP of the communication network in a predefined order, where the predefined order reflects the suitability levels of the reported additional beam groups for simultaneous reception (e.g., in ascending or descending order of suitability).

[0087] According to some examples of the present disclosure, when reporting at least some of the resulting additional beam groups, the UE may include additional parameters indicative of communication characteristics of the beams of the at least one additional beam group, such as an RSRP indication, a SINR, a reliability metric associated with the used prediction model, and an indication of a capability value set.

[0088] According to some examples of the present disclosure, the prediction model used to determine the additional beam groups available for simultaneous reception is a machine learning prediction model using a neural network configuration having a plurality of NN blocks including at least one of a fully connected neural network block, an activation function layer, and a batch normalization layer. Alternatively, the prediction model used to determine the additional beam groups available for simultaneous reception is a non-machine learning prediction model.

[0089] According to some examples of the present disclosure, the UE uses the beam measurements and the identified beam groups for simultaneous reception as input data for the prediction model.

[0090] Furthermore, according to some examples of the present disclosure, the UE is configured to determine the prediction model to be applied based on information provided by the obtained channel state information reporting configuration information, for example, the prediction model to be used is determined based on signaling characteristics of the RS from the network.

[0091] Further, according to some examples of the present disclosure, the UE reports at least a portion of the determined additional beam groups available for simultaneous reception as uplink control information to the communication network.

[0092] According to some examples of the present disclosure, the UE applies a spatial filter adjusted to receive beams identified or determined as usable for simultaneous reception.

[0093] Figure 6 illustrates a flowchart of processing performed in a communications network control element or function, such as a gNB used as a TRP (e.g., TRP#1 20), according to some examples of the present disclosure. That is, Figure 6 illustrates a flowchart related to processing performed by a communications network control element or function, such as TRP#1 20, as also described in connection with Figures 1 to 4.

[0094] At S610, the TRP receives from the UE an indication of the capability of a communication element or communication function to support predictive-based group-based beam reporting.

[0095] At S620, the TRP transmits CSI reporting configuration information to the UE to enable prediction-based group-based beam reporting.

[0096] Furthermore, according to some examples of the present disclosure, the TRP is configured to trigger a prediction-based group-based beam reporting by triggering aperiodic CSI reporting to UEs corresponding to the CSI reporting configuration information.

[0097] 7 illustrates a diagram of a communication element or function, such as a UE 10, performing processing according to some examples of the present disclosure, such as those described in connection with FIGS. 1 through 4. It should be noted that a network element or function, such as a UE 10, may include additional elements or functions beyond those described herein below. Furthermore, even if reference is made to a network element or function, the element or function may be another device or function having a similar task, such as a chipset, chip, module, application, or the like, that may be part of the network element or that may be attached as a separate element to the network element or the like. It should be understood that each block, and any combination thereof, may be implemented by various means, such as hardware, software, firmware, one or more processors and / or circuits, or a combination thereof.

[0098] The UE 10 shown in FIG. 7 may include a processing circuit, processing function, control unit, or processor 101, such as a CPU, suitable for executing instructions provided by a program or the like related to a control procedure. The processor 101 may include one or more processing units or functions dedicated to a specific process, as described below, or the process may be performed in a single processor or processing function. Also, the parts for performing such a specific process may be provided, for example, as separate elements, or in one or more further processors, processing functions, or processing units, such as in one physical processor, such as a CPU, or in one or more physical or virtual entities. Reference numeral 102 denotes an input / output (I / O) unit or function (interface) connected to the processor or processing function 101. The I / O unit 102 may be used to communicate with a communication network, such as the TRPs 20 and 25. The I / O unit 102 may be a combined unit including communication equipment for several entities, or may include a distributed structure including multiple different interfaces for different entities. Reference numeral 104 denotes memory that can be used, for example, to store data and programs executed by the processor or processing function 101 and / or as working storage for the processor or processing function 101. It should be noted that the memory 104 can be implemented by using one or more memory portions of the same or different types of memory.

[0099] The processor or processing function 101 is configured to perform processing related to the above control procedures. In particular, the processor or processing circuit or function 101 includes one or more of the following subportions: Subportion 1011 is a processing unit usable as a portion for obtaining a CSI reporting configuration. Portion 1011 may be configured to perform processing according to S510 of FIG. 5 . Furthermore, the processor or processing circuit or function 101 may include subportion 1012 usable as a portion for receiving a beam. Portion 1012 may be configured to perform processing according to S520 of FIG. 5 . Furthermore, the processor or processing circuit or function 101 may include subportion 1013 usable as a portion for determining associations. Portion 1013 may be configured to perform processing according to S530 of FIG. 5 . Furthermore, the processor or processing circuit or function 101 may include subportion 1014 usable as a portion for measurement. Portion 1014 may be configured to perform processing according to S540 of FIG. 5 . Furthermore, the processor or processing circuit or function 101 may include a sub-portion 1015 that can be used as a portion for determining the beam group. The portion 1015 may be configured to perform processing according to S550 of FIG.

[0100] FIG. 8 illustrates a diagram of a communications network control element or function, such as a gNB, that is a TRP (e.g., TRP#1 20) that controls communications according to some examples of the present disclosure, as described in connection with FIGS. 1 through 4. It should be noted that a network element or function, such as the TRP 20, may include additional elements or functions beyond those described herein below. Furthermore, even if reference is made to a network element or function, the element or function may also be another device or function having a similar task, such as a chipset, chip, module, application, or the like, that may be part of the network element or that may be attached as a separate element to the network element or the like. It should be understood that each block, and any combination thereof, may be implemented by various means, such as hardware, software, firmware, one or more processors and / or circuits, or the like.

[0101] The TRP 20 shown in FIG. 8 may include a processing circuit, processing function, control unit, or processor 201, such as a CPU, suitable for executing instructions provided by a program or the like related to a control procedure. The processor 201 may include one or more processing units or functions dedicated to specific processes as described below, or the processes may be performed in a single processor or processing function. Also, the parts for performing such specific processes may be provided, for example, as separate elements, or in one or more further processors, processing functions, or processing units, such as in one physical processor such as a CPU, or in one or more physical or virtual entities. Reference numerals 202 and 203 denote input / output (I / O) units or functions (interfaces) connected to the processor or processing function 201. The I / O unit 202 may be used to communicate with communication elements or communication functions, such as a UE as shown in FIG. 1. The I / O unit 203 may be used to communicate with other network functions. I / O units 202 and 203 may be a combined unit including communication equipment for several entities, or may include a distributed structure including multiple different interfaces for different entities. Reference numeral 204 denotes a memory usable for example for storing data and programs executed by processor or processing function 201 and / or as working storage for processor or processing function 201. It should be noted that memory 204 may be implemented by using one or more memory portions of the same or different types of memory.

[0102] The processor or processing function 201 is configured to perform processing related to the above control procedures. In particular, the processor or processing circuit or function 201 includes one or more of the following sub-portions: Sub-portion 2011 is a processing unit usable as a part for receiving capability indications. Part 2011 may be configured to perform processing according to S610 of FIG. 6 . Furthermore, the processor or processing circuit or function 201 may include a sub-portion 2012 usable as a part for sending CSI reporting configurations. Part 2012 may be configured to perform processing according to S620 of FIG. 6 .

[0103] It should be noted that the example embodiments of the present disclosure are applicable to a variety of different network configurations. In other words, the examples shown in the above figures, used based on the examples discussed above, are merely illustrative and do not limit the present disclosure in any way. That is, additional existing and proposed new functionality available in the corresponding operating environment may be used in connection with the example embodiments of the present disclosure based on the defined principles.

[0104] Furthermore, although the above example embodiments mainly describe UEs as communication elements or communication functions to which the proposed control procedures apply, the example embodiments may also concern other communication elements or communication functions to which the corresponding processing is applicable.

[0105] According to a further example embodiment, there is provided an apparatus for use by, for example, a communication element or communication function capable of performing multi-transmission point TRP operations, the apparatus comprising: means configured to obtain channel state information report configuration information to enable group-based beam reporting based on prediction; means configured to receive a plurality of beams including at least one set of beams for measurement and at least one set of beams for prediction; means configured to determine associations of the received plurality of beams with respective TRPs of the communication network; means configured to measure resources from the at least one set of beams for measurement to identify a beam group for simultaneous reception; and means configured to determine further beam groups usable for simultaneous reception by using a prediction model, the further beam group including beams from the at least one set of beams for measurement and the at least one set of beams for prediction.

[0106] Furthermore, according to some other examples of embodiment, the apparatus defined above may further comprise means for performing at least one of the processes defined in the above methods, such as the method according to that described in relation to FIG. 5.

[0107] According to a further example embodiment, an apparatus is provided for use by, for example, a communication network control element or communication network control function acting as a transmission / reception point TRP for communicating with a communication element or communication function, the apparatus including means configured to receive an indication of the communication element's or communication function's capability to support prediction-based group-based beam reporting, and means configured to send channel state information reporting configuration information to the communication element or communication function to enable prediction-based group-based beam reporting.

[0108] Furthermore, according to some other examples of embodiment, the apparatus defined above may further comprise means for performing at least one of the processes defined in the above methods, such as the method according to that described in relation to FIG. 5.

[0109] According to a further example embodiment, a non-transitory computer-readable medium is provided that includes program instructions, for example, for use in a communication element or communication function capable of multi-transmission point (TRP) operation, to cause the device to perform processes including: obtaining channel state information reporting configuration information to enable group-based beam reporting based on prediction; receiving a plurality of beams including at least one set of beams for measurement and at least one set of beams for prediction; determining associations of the received plurality of beams with respective TRPs of the communication network; measuring resources from the at least one set of beams for measurement to identify beam groups for simultaneous reception; and determining further beam groups usable for simultaneous reception by using a prediction model, wherein the further beam groups include beams from the at least one set of beams for measurement and the at least one set of beams for prediction.

[0110] According to a further example embodiment, a non-transitory computer-readable medium is provided that includes program instructions, for example, when used in a communication network control element or communication network control function acting as a transmission / reception point TRP for communicating with a communication element or communication function, to cause the device to perform processing including receiving an indication of the communication element's or communication function's ability to support prediction-based group-based beam reporting, and sending channel state information reporting configuration information to the communication element or communication function to enable prediction-based group-based beam reporting.

[0111] The above configuration can reduce RS overhead and latency in beam measurement and reporting.

[0112] The following should be recognized: The access technology by which traffic is transferred to and from entities in the communication network may be any suitable current or future technology, such as WLAN (Wireless Local Area Network), WiMAX (Worldwide Interoperability for Microwave Access), LTE, LTE-A, 5G, Bluetooth, infrared, etc.; furthermore, embodiments may also be applied to wired technologies, such as IP-based access technologies, e.g. cable networks or fixed lines. - Embodiments that are suitable to be implemented as software code or portions thereof and executed using a processor or processing functionality do not rely on software code and may be written using any known or future-developed programming language, such as a high-level programming language such as Objective-C, C, C++, C#, Java, Python, Javascript, other scripting languages, or a lower-level programming language such as machine language or assembler. Implementation of the embodiments is hardware independent and may be implemented using any known or future developed hardware technology, such as a microprocessor or CPU (Central Processing Unit), MOS (Metal Oxide Semiconductor), CMOS (Complementary MOS), BiMOS (Bipolar MOS), BiCMOS (Bipolar CMOS), ECL (Emitter Coupled Logic), and / or TTL (Transistor-Transistor Logic), or any hybrid thereof. - The embodiments may be implemented as separate devices, apparatus, units, means or functions or in a distributed manner, e.g. one or more processors or processing functions may be used or shared in a process, or one or more processing sections or processing units may be used or shared in a process, one physical processor or two or more physical processors may be used to implement one or more processing units dedicated to a particular process as described. The device may be implemented by a semiconductor chip, a chipset, or a (hardware) module containing such a chip or chipset. - embodiments may also be implemented as any combination of hardware and software, such as ASIC (Application Specific IC) components, FPGA (Field-programmable Gate Arrays) or CPLD (Complex Programmable Logic Device) components, or DSP (Digital Signal Processor) components; The embodiments may also be implemented as a computer program product including a computer usable medium having computer readable program code embedded therein, the computer readable program code being adapted to perform processes as described in the embodiments, and the computer usable medium may be a non-transitory medium.

[0113] Although the present disclosure has been described hereinabove with reference to specific embodiments, the present disclosure is not limited thereto and may be variously modified.

Claims

1. 1. Apparatus for use by a communication element or function capable of multi-transmission point TRP operation, comprising: at least one processing circuit; and at least one memory for storing instructions that, when executed by the at least one processor, cause the apparatus to perform at least: obtaining channel state information report configuration information for enabling predictive group-based beam reporting; receiving a plurality of beams, including at least one set of measurement beams and at least one set of prediction beams; determining associations of the received beams with respective TRPs of the communication network; measuring resources from at least one set of beams for measurement to identify a beam group for simultaneous reception; determining a further beam group usable for simultaneous reception by using the prediction model, the further beam group including beams from at least one set of beams for measurement and at least one set of beams for prediction; Device.

2. The instructions further include: The device of claim 1, wherein when a prediction based on a prediction model results in the output of at least one additional beam group, at least some of the resulting additional beam groups are reported to a TRP of the communication network in a predefined order, the predefined order reflecting the suitability level of the reported additional beam groups for simultaneous reception.

3. The instructions further include: The device of claim 2, wherein when reporting at least a portion of the resulting further beam groups, additional parameters are included indicating communication characteristics of the beams of at least one of the further beam groups, the communication characteristics including at least one of a reference signal received power indication, a signal-to-interference-plus-noise ratio, a reliability metric associated with the prediction model used, and an indication of a capability value set.

4. The instructions further include: An apparatus as described in any one of claims 1 to 3, wherein a TRP of a communication network is caused to report a capability for supporting prediction-based group-based beam reporting, and channel state information reporting configuration information is received in response to the capability report.

5. The instructions further include: An apparatus as described in any one of claims 1 to 4, which uses a predefined or received configuration indicating the association of a received reference signal with at least two transmission points of a communication network to determine the association of the received multiple beams with each TRP of the communication network.

6. 6. The apparatus of claim 1, wherein the beam is represented by downlink reference signal resources, including at least one of channel state information reference signal and synchronization signal block resources, and the downlink reference signal resources are grouped into groups each corresponding to a respective TRP.

7. At least one set of beams for measurement includes a downlink reference signal transmitted by a corresponding TRP; The apparatus of claim 1 , wherein at least one set of beams for prediction includes a downlink reference signal that is not transmitted by a corresponding TRP.

8. The beam groups forming the identified beam group or further beam groups are a) beams corresponding to two TRPs or spatial filters, where at least one beam corresponds to one TRP or spatial filter and another beam corresponds to another TRP or spatial filter, or b) beams corresponding to only one TRP or spatial filter, where one subset of the beams of the beam group are from the set of beams for measurement and another subset of the beams of the beam group are determined from the set of beams for prediction; 8. The apparatus of claim 1, further comprising one of:

9. The instructions further include: An apparatus as described in any one of claims 1 to 8, wherein at least one of a reference signal received power or a channel state information amount is measured based on a signal transmission from a communication network as a resource from at least one set of beams for measurement to identify a beam group for simultaneous reception.

10. 10. The apparatus of claim 1, wherein the predictive model used to determine further beam groups available for simultaneous reception is a machine learning predictive model using a neuronal network configuration having a plurality of neuronal network blocks including at least one of a fully connected neuronal network block, an activation function layer, and a batch normalization layer.

11. 10. The apparatus of claim 1, wherein the predictive model used to determine further beam groups that can be used for simultaneous reception is a non-machine learning predictive model.

12. The instructions further include:

12. The apparatus of claim 1, adapted to use identified beam groups for beam measurement and simultaneous reception as input data for a prediction model.

13. The instructions further include:

13. The apparatus of claim 1, wherein the prediction model to be applied is determined based on information provided by the obtained channel state information reporting configuration information.

14. The instructions further include:

14. The apparatus of claim 1, wherein at least a portion of the determined further beam groups available for simultaneous reception are reported as uplink control information to a communications network.

15. The instructions further include:

15. Apparatus according to any one of claims 1 to 14, adapted to apply spatial filters adjusted to receive beams identified or determined as usable for simultaneous reception.

16. 16. The device according to any one of claims 1 to 15, wherein the communication element or function is included in a user equipment having multiple receiving panels for simultaneously receiving beams from multiple TRPs of the communication network.

17. 1. A method for use in a communication element or function capable of multi-transmission point TRP operation, comprising: obtaining channel state information report configuration information to enable predictive group-based beam reporting; receiving a plurality of beams, including at least one set of measurement beams and at least one set of prediction beams; determining an association of the received beams with respective TRPs of the communication network; measuring resources from at least one set of beams for measurement to identify a beam group for simultaneous reception; determining a further group of beams available for simultaneous reception by using the prediction model, the further group of beams including beams from at least one set of beams for measurement and at least one set of beams for prediction; A method comprising:

18. The method of claim 17, further comprising: when a prediction based on the prediction model results in the output of at least one additional beam group, reporting at least some of the resulting additional beam groups to a TRP of the communication network in a predefined order, the predefined order reflecting a suitability level of the reported additional beam groups for simultaneous reception.

19. The method of claim 18, further comprising, when reporting at least some of the resulting further beam groups, including additional parameters indicating communication characteristics of the beams of at least one further beam group, the communication characteristics including at least one of a reference signal received power indication, a signal-to-interference-plus-noise ratio, a reliability metric associated with the prediction model used, and an indication of a capability value set.

20. 20. A method according to any one of claims 17 to 19, further comprising reporting to a TRP of a communication network a capability for supporting prediction-based group-based beam reporting, wherein channel state information reporting configuration information is received in response to the capability report.

21. 21. A method according to any one of claims 17 to 20, further comprising using a predefined or received configuration indicating association of the received reference signal with at least two transmission points of the communication network to determine association of the received beams with each TRP of the communication network.

22. 22. The method of claim 17, wherein the beam is represented by downlink reference signal resources, including at least one of channel state information reference signal and synchronization signal block resources, and the downlink reference signal resources are grouped into groups each corresponding to a respective TRP.

23. At least one set of beams for measurement includes a downlink reference signal transmitted by a corresponding TRP; 23. The method of any one of claims 17 to 22, wherein at least one set of beams for prediction includes downlink reference signals that are not transmitted by the corresponding TRP.

24. The beam groups forming the identified beam group or further beam groups are a) beams corresponding to two TRPs or spatial filters, where at least one beam corresponds to one TRP or spatial filter and another beam corresponds to another TRP or spatial filter, or b) beams corresponding to only one TRP or spatial filter, where one subset of the beams of the beam group are from the set of beams for measurement and another subset of the beams of the beam group are determined from the set of beams for prediction; 24. The method of any one of claims 17 to 23, comprising one of:

25. 25. A method according to any one of claims 17 to 24, further comprising measuring at least one of a reference signal received power or a channel state information amount as a resource from at least one set of beams for measurement based on signal transmission from a communication network to identify a beam group for simultaneous reception.

26. 26. The method of any one of claims 17 to 25, wherein the prediction model used to determine further beam groups available for simultaneous reception is a machine learning prediction model using a neuronal network configuration having a plurality of neuronal network blocks including at least one of a fully connected neuronal network block, an activation function layer, and a batch normalization layer.

27. 26. A method according to any one of claims 17 to 25, wherein the predictive model used to determine further beam groups available for simultaneous reception is a non-machine learning predictive model.

28. 28. The method of any one of claims 17 to 27, further comprising using the identified beam groups for beam measurements and simultaneous reception as input data for a predictive model.

29. 29. The method of any one of claims 17 to 28, further comprising determining the prediction model to be applied based on information provided by the obtained channel state information reporting configuration information.

30. 30. The method of any one of claims 17 to 29, further comprising reporting at least a portion of the determined further beam groups available for simultaneous reception as uplink control information to the communications network.

31. The instructions further include:

31. A method according to any one of claims 17 to 30, comprising applying a spatial filter adjusted to receive beams identified or determined as usable for simultaneous reception.

32. 32. The apparatus of any one of claims 17 to 31, wherein the communication element or function is included in a user equipment having multiple receiving panels for simultaneously receiving beams from multiple TRPs of the communication network.

33. 1. Apparatus for use by a communications network control element or function acting as a transmission / reception point TRP for communicating with a communications element or function, comprising: at least one processing circuit; and at least one memory for storing instructions that, when executed by the at least one processor, cause the apparatus to perform at least: receiving an indication of a capability of a communication element or communication function to support predictive group-based beam reporting; causing a communication element or communication function to transmit channel state information reporting configuration information to enable predictive group-based beam reporting; Device.

34. The instructions further include: The apparatus of claim 33, wherein the prediction-based group-based beam reporting is triggered by triggering aperiodic channel state information reporting for communication elements or communication functions corresponding to the channel state information reporting configuration information.

35. 1. A method for use in a communications network control element or function acting as a transmission / reception point TRP for communicating with a communications element or function, comprising: receiving an indication of a capability of a communication element or communication function to support predictive group-based beam reporting; transmitting channel state information reporting configuration information to a communication element or communication function to enable predictive group-based beam reporting; A method comprising:

36. 36. The method of claim 35, further comprising triggering a predictive group-based beam reporting by triggering aperiodic channel state information reporting to communication elements or communication functions corresponding to the channel state information reporting configuration information.

37. 37. A computer program product for a computer, comprising software code portions for performing the steps of any one of claims 17 to 32 or claims 35 or 36, when said product is run on a computer.

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