Machine learning for channel state information reference signal handling

Abstract

The present disclosure provides a computer-implemented method performed by a first device for handling Channel State Information Reference Signals, CSI-RSs, in a communications system. The method comprises obtaining measurements on CSI-RSs transmitted by a first network node, wherein the measurements are performed according to a first indication of a first subset of CSI-RS resources configured at the first device, and a second indication of second subsets of CSI-RS ports of the CSI-RS resources configured at the first device. The disclosure also provides corresponding methods for network nodes and devices that utilize machine learning models for predicting Channel State Information based on the measured CSI-RS resources and ports.

Description

[0001] MACHINE LEARNING FOR CHANNEL STATE INFORMATION REFERENCE SIGNAL HANDLING

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to wireless communication systems and machine learning techniques, and more particularly to machine learning methods for handling Channel State Information Reference Signals (CSI-RS) in wireless communication networks to optimize channel state information prediction and reporting.

[0004] BACKGROUND

[0005] Wireless communication systems have evolved to support multiple-input multiple-output (MIMO) techniques to enhance data transmission rates and reliability. Modern wireless networks, utilize advanced antenna configurations and beamforming technologies to optimize signal transmission between network nodes and user equipment. Machine learning techniques have emerged as promising approaches for addressing various challenges in wireless communication systems..

[0006] Wireless devices within a wireless communications network may be e.g., User Equipments (UEs), stations (STAs), mobile terminals, wireless terminals, terminals, and / or Mobile Stations (MS). Wireless devices are enabled to communicate wirelessly in a cellular communications network or wireless communication network, sometimes also referred to as a cellular radio system, cellular system, or cellular network. The communication may be performed e.g., between two wireless devices, between a wireless device and a regular telephone and / or between a wireless device and a server via a Radio Access Network (RAN) and possibly one or more core networks, comprised within the wireless communications network. Wireless devices may further be referred to as mobile telephones, cellular telephones, laptops, or tablets with wireless capability, just to mention some further examples. The wireless devices in the present context may be, for example, portable, pocket-storable, hand-held, computer-comprised, or vehicle-mounted mobile devices, enabled to communicate voice and / or data, via the RAN, with another entity, such as another terminal or a server.

[0007] The wireless communications network covers a geographical area which may be divided into cell areas, each cell area being served by a network node, which may be an access node such as a radio network node, radio node or a base station (BS), e.g., a Radio Base Station (RBS), which sometimes may be referred to as e.g., gNB, evolved Node B (eNB), “eNodeB”,“NodeB”, “B node”, Transmission Point (TP), or BTS (Base Transceiver Station), depending on the technology and terminology used. The base stations may be of different classes such as e.g., Wide Area Base Stations, Medium Range Base Stations, Local Area Base Stations, Home Base Stations, pico base stations, etc... , based on transmission power and thereby also cell size. A cell is the geographical area where radio coverage is provided by the base station or radio node at a base station site, or radio node site, respectively. One base station, situated on the base station site, may serve one or several cells. Further, each base station may support one or several communication technologies. The base stations may communicate over the air interface operating on radio frequencies with the terminals within range of the base stations. The wireless communications network may also comprise network nodes which may serve receiving nodes, such as wireless devices, with serving beams. In 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE), base stations, which may be referred to as eNodeBs or even eNBs, may be directly connected to one or more core networks. In the context of this disclosure, the expression Downlink (DL) may be used for the transmission path from the base station to the wireless device. The expression Uplink (UL) may be used for the transmission path in the opposite direction i.e., from the wireless device to the base station.

[0008] The standardization organization 3GPP is currently in the process of specifying a New Radio Interface called NR or 5G-UTRA, as well as a Fifth Generation (5G) Packet Core Network (CN), which may be referred to as Next Generation (NG) Core Network, abbreviated as NG-CN, NGC, 5G CN or 5G Core (5GC). NG may be understood to refer to the interface / reference point between the Radio Access Network (RAN) and the CN in 5G / NR. In a 5G System (5GS), a radio base station in NR may be referred to as a gNB or 5G Node B. An NR UE may be referred to as an nUE.

[0009] Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. The performance may be improved if both the transmitter and the receiver are equipped with multiple antennas, which may result in a multiple-input multipleoutput (MIMO) communication channel. Such systems and / or related techniques may be commonly referred to as MIMO systems. Codebook-based precoding is a fundamental technique used in these MIMO systems.

[0010] A core component of NR may be understood to be the support of MIMO related techniques. NR may be understood to support up to 8-layer spatial multiplexing for up to 32 transmit antenna ports at the gNB with channel dependent precoding. Figure 1 is a schematic diagram illustrating a non-limiting example of data transmission with spatial multiplexing where the information carrying symbol vector s = [s1,s2, ...,sr]Tmay be first multiplied (or precoded) by a precoding matrix IV e cNrXrbefore being sent over / VTantenna ports. Each symbol in s may be associated to a data layer and r may be understood to be the number of data layers or rank, which may be understood to be a property of the wireless channel between the transmitter andthe receiver. W may be understood to serve to beamform each data layer towards the UE such that signal to interference plus noise ratio (SI NR) may be maximized and cross layer interference may be minimized at the UE receiver. Spatial multiplexing may be achieved since multiple symbols may be transmitted simultaneously in a same time and frequency resource element (RE).

[0011] Figure 1 is a schematic diagram illustrating a non-limiting example of data transmission with spatial multiplexing.

[0012] The received NR X 1 signal vector x at the UE equipped with R receive antennas ports may be expressed as:

[0013] x = HWs + e

[0014] where H e CNRXNTmay be understood to be the MIMO channel between the transmit and receive antenna ports, e may be understood to be a noise plus interference vector due to receiver noise and interference.

[0015] The precoder matrix W may be chosen to match the characteristics of the NRXNT MIMO channel matrix H resulting in so-called channel dependent precoding. The precoder W may be a wideband precoder, e.g., the same precoder applied over a whole bandwidth, or a subband precoder, e.g., optimized per subband. W may be typically selected from a codebook of precoding matrices by the UE and reported to the gNB in terms of a precoding matrix indicator (PMI).

[0016] One example method for a UE to select a precoder matrix W may be to select the Wkfrom a codebook that may maximize the Frobenius norm of the hypothesized equivalent channel:

[0017]

[0018] Where

[0019] H may be understood to be a channel estimate

[0020] Wkmay be understood to be a hypothesized precoder matrix with index k.

[0021] In addition to W feedback, a UE may typically also feedback a rank indicator (Rl) and channel quality indicator(s) (CQI) as part of channel state information (CSI) feedback. Given the CSI feedback from the UE, the gNB may determine the transmission parameters to use for data transmissions to the UE.

[0022] For channel estimation purposes, a so-called channel state information reference signal (CSI-RS) may be typically transmitted to the UE.

[0023] Two-dimensional (2D) antenna arrays represent an advanced configuration where the antennas with NTantenna ports discussed above may be either a linear antenna array or 2D plenary antenna array. A linear antenna array may be understood to be a special case of a 2D antenna array. A 2D antenna array may be described by Nhcolumns, corresponding to thehorizontal dimension, Nvrows, corresponding to the vertical dimension, and Nppolarizations. The total number of antenna ports may thus be N = NhNvNp. An example of a cross polarized, e.g., Np= 2, antenna array with

[0024]

[0025] = (4,4) is illustrated in Figure 2.

[0026] Figure 2 is a schematic diagram illustrating a non-limiting example of a two-dimensional antenna array of cross-polarized antenna elements (NP= 2), with Nh= 4 horizontal antenna elements and Nv= 4 vertical antenna elements.

[0027] It may be noted that the 2D antenna array may be rotated at any angle. In this case, the row and columns may no longer correspond to vertical and horizontal directions. To reflect this more general case in NR, a 2D antenna array may be simply defined by a number of antenna ports in each of two dimensions, e.g., N and N2, and Npmay be understood to always be 2. Thus, the total number of antenna ports may be understood to be N = 2N1N2.

[0028] The concept of an antenna port may be understood to be non-limiting in the sense that it may refer to any virtualization, e.g., linear mapping, of the physical antenna elements. For example, pairs of physical sub-elements may be fed the same signal, and hence share the same virtualized antenna port.

[0029] Reference signals serve as known transmitted signals that enable channel estimation and measurement in wireless communication systems. Different reference signal configurations may be employed.

[0030] A CSI-RS may be transmitted over each transmit (Tx) antenna port at the network node and for different antenna ports. The CSI-RS may be multiplexed in time, frequency, and code domain such that the channel between each Tx antenna port at the network node and each receive antenna port at a UE may be measured by the UE. The time-frequency resource used for transmitting CSI-RS may be referred to as a CSI-RS resource.

[0031] In NR, the CSI-RS for beam management may be defined as a 1- or 2-port CSI-RS resource in a CSI-RS resource set where the field repetition may be present. The following three types of CSI-RS transmissions may be supported:

[0032] • Periodic CSI-RS: CSI-RS may be transmitted periodically in certain slots. This CSI-RS transmission may be semi-statically configured using Radio Resource Control (RRC) signaling with parameters such as CSI-RS resource, periodicity, and slot offset.

[0033] • Semi-Persistent CSI-RS: Similar to periodic CSI-RS, resources for semi-persistent CSI-RS transmissions may be semi-statically configured using RRC signaling with parameters such as periodicity and slot offset. However, unlike periodic CSI-RS, dynamic signaling may be needed to activate and deactivate the CSI-RS transmission.• Aperiodic CSI-RS: This may be understood to be a one-shot CSI-RS transmission that may happen in any slot. Here, one-shot may be understood to mean that CSI-RS transmission may only happen once per trigger. The CSI-RS resources, e.g., the Resource Element (RE) locations which may consist of subcarrier locations and OFDM symbol locations, for aperiodic CSI-RS may be semi-statically configured. The transmission of aperiodic CSI-RS may be triggered by dynamic signaling through Physical Downlink Control CHannel (PDCCH) using the Channel State Information (CSI) request field in UL Downlink Control Information (DCI), in the same DCI where the UL resources for the measurement report may be scheduled. Multiple aperiodic CSI-RS resources may be included in a CSI-RS resource set and the triggering of aperiodic CSI-RS may be on a resource set basis.

[0034] In NR, an SSB may consist of a pair of synchronization signals (SSs), physical broadcast channel (PBCH), and DeModulation Reference Signal (DMRS) for PBCH. An SSB may be mapped to 4 consecutive OFDM symbols in the time domain and 240 contiguous subcarriers, 20 Resource Blocks (RBs) in the frequency domain.

[0035] To support beamforming and beam-sweeping for SSB transmission, in NR, a cell may transmit multiple SSBs in different narrow-beams in a time multiplexed fashion. The transmission of these SSBs may be confined to a half frame time interval, 5 ms. It may also be possible to configure a cell to transmit multiple SSBs in a single wide-beam with multiple repetitions. The design of beamforming parameters for each of the SSBs within a half frame may be up to network implementation. The SSBs within a half frame may be broadcasted periodically from each cell. The periodicity of the half frames with SS / PBCH blocks may be referred to as SSB periodicity, which may be indicated by System Information Block 1 (SIB1).

[0036] The maximum number of SSBs within a half frame, denoted by L, may be understood to depend on the frequency band, and the time locations for these L candidate SSBs within a half frame may be understood to depend on the Subcarrier Spacing (SCS) of the SSBs. The L candidate SSBs within a half frame may be indexed in an ascending order in time from 0 to L-1. By successfully detecting PBCH and its associated DMRS, a UE may know the SSB index. A cell may not necessarily transmit SS / PBCH blocks in all L candidate locations in a half frame, and the resource of the un-used candidate positions may be used for the transmission of data or control signaling instead. It may be up to network implementation to decide which candidate time locations to select for SSB transmission within a half frame, and which beam to use for each SSB transmission.

[0037] In NR, a UE may be configured with N>1 CSI reporting settings, e.g., alternatively referred to as CSI-ReportConfig, M>1 resource settings, e.g., alternatively referred to as CSI-ResourceConfig, where each CSI reporting setting may be linked to one or more resource setting for channel and / or interference measurement. The CSI framework may be modular, meaning that several CSI reporting settings may be associated with the same Resource Setting.The measurement resource configurations for beam management may be provided to the UE by RRC Information Elements (lEs) CSI-ResourceConfigs. One CSI-ResourceConfig may contain several NZP-CSI-RS-ResourceSets and / or CSI-SSB-ResourceSets.

[0038] A UE may be configured to perform measurement on CSI-RSs. Here the RRC information element (IE) NZP-CSI-RS-ResourceSet may be used. A NZP CSI-RS resource set may contain the configuration of Ks >1 CSI-RS resources, where the configuration of each CSI-RS resource may include at least: mapping to REs, the number of antenna ports, time-domain behavior, etc. Up to 64 CSI-RS resources may be grouped to a NZP-CSI-RS-ResourceSet. A UE may also be configured to perform measurements on SSBs. Here, the RRC IE CSI-SSB-ResourceSet may be used. Resource sets comprising SSB resources may be defined in a similar manner.

[0039] In the case of aperiodic CSI-RS and / or aperiodic CSI reporting, the network node may configure the UE with ScCSI triggering states. Each triggering state may contain the aperiodic CSI report setting to be triggered along with the associated aperiodic CSI-RS resource sets.

[0040] Periodic and semi-persistent Resource Settings may only comprise a single resource set, e.g., S=1 , while S>=1 for aperiodic Resource Settings. This may be understood to be because in the aperiodic case, one out of the S resource sets comprised in the Resource Setting may be indicated by the aperiodic triggering state that may trigger a CSI report.

[0041] The RRC lEs described above may be defined in 3GPP 38.331 v. 18.0.0.

[0042] Three types of CSI reporting may be supported in NR as follows:

[0043] • Periodic CSI Reporting on Physical Uplink Control Channel (PUCCH): CSI may be reported periodically by a UE. Parameters such as periodicity and slot offset may be configured semi-statically by higher layer RRC signaling from the network node to the UE.

[0044] • Semi-Persistent CSI Reporting on Physical Uplink Shared Channel (PUSCH) or PUCCH: similar to periodic CSI reporting, semi-persistent CSI reporting may be understood to have a periodicity and slot offset which may be semi-statically configured. However, a dynamic trigger from network node to UE may be needed to allow the UE to begin semi-persistent CSI reporting. A dynamic trigger from network node to UE may be needed to request the UE to stop the semi-persistent CSI reporting.

[0045] • Aperiodic CSI Reporting on PUSCH: This type of CSI reporting may involve a singleshot, that is, one time, CSI report by a UE which may be dynamically triggered by the network node using DCI. Some of the parameters related to the configuration of the aperiodic CSI report may be semi-statically configured by RRC but the triggering may be done dynamically via DCI.

[0046] Machine learning (ML) may be understood as the study of computer algorithms that may improve automatically through experience. It is seen as a part of Artificial Intelligence (Al). ML algorithms may build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. ML algorithms may be used in a wide variety of applications, such as email filtering and computer vision, where it maybe difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

[0047] There may be basically three types of ML Algorithms: Supervised Learning, Unsupervised Learning, and Reinforcement Learning (RL).

[0048] Supervised Learning algorithms may comprise a target / outcome variable, or dependent variable, which may have to be predicted from a given set of predictors, that is, independent variables. Using this set of variables, a function may be generated that may map inputs to desired outputs. The training process may continue until the model may achieve a desired level of accuracy on the training data. Once an ML model may have been trained, an inference process may begin, whereby new data may be run through the ML model to calculate an output. Examples of Supervised Learning may be Regression, Decision Tree, Random Forest, KNN, Logistic Regression etc.

[0049] In Unsupervised Learning algorithms, there may be no target or outcome variable to predict / estimate. It may be used for clustering a population into different groups, which may be widely used for segmenting customers in different groups for specific intervention. Examples of Unsupervised Learning may be K-means, mean-shift clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Expectation-Maximization (EM) Clustering using Gaussian Mixture Models (GMM), Agglomerative Hierarchical Clustering, etc....

[0050] Cluster analysis or clustering may be understood as an ML technique which may comprise grouping a set of objects in such a way that objects in the same group, which may be called a cluster, may be understood to be more similar, in some sense, to each other than to those in other groups, that is, other clusters. It may be understood as a main task of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and ML.

[0051] Reinforcement learning (RL) may be understood to be a type of ML where an agent may learn to make decisions by taking actions in an environment to achieve some goal. The agent may receive feedback in the form of rewards, which it may use to learn the best strategy, or policy, to accumulate the most reward over time.

[0052] Reinforcement learning may involve the following. An agent may be understood to be a learner or decision maker that may interact with the environment. The environment may be understood to refer to the world that the agent may interact with and learn from. A state (s) may be understood to refer to a representation of the current situation that the agent may be in. It may be understood to be the context within which the agent may make decisions. An action (a) may be understood to refer to a choice made by the agent that may affect the state. A reward (r) : may be understood to refer to feedback from the environment in response to the actions taken by the agent. It may be a scalar signal that may indicate how well the agent is doing at a given moment. A Policy may be understood to be a strategy used by the agent,which may map states to actions. The policy may be deterministic, that is, always the same action for a given state, or stochastic, that is, probabilistic actions for a given state. A value function may be understood to refer to a function that may estimate how good it may be for the agent to be in a given state, or how good it may be to perform a certain action in a given state. The "goodness" may be typically measured as the expected return, e.g., the cumulative reward, that may be achieved. A Q-function, an Action-Value Function, may be understood to refer to a function that may estimate the value of taking a certain action in a given state, and then following the current policy thereafter. A model of the environment may be understood to refer to the fact that some RL approaches may involve learning a model that may predict the next state (s’) and the reward for the current state and action. This may be understood to allow for planning and reasoning about the future without needing to actually take the action.

[0053] RL may involve making decisions in regard to exploration vs. exploitation. In reinforcement learning, the agent may need to balance exploration, that is, trying new things to discover better rewards, with exploitation, that is, using known information to maximize rewards. This may be understood to be a trade-off in RL.

[0054] In the reinforcement learning problem, the state may change every time the agent may apply a new action. The problem may be represented in the following way: The agent may receive the state of the environment at a certain time (s). Then the agent may select on action (a) and apply it in the environment. When this action is applied, the environment may provide a reward (r) and change to a new state (s’), the reward and state may be provided finally by an interpreter. In reinforcement learning, the term "interpreter" may be used to describe a component of a reinforcement learning system that may interpret the state of the environment and the actions of an agent. It may be understood to be the part of the system that may bridge the agent with the environment it may be trying to learn from.

[0055] This cyclic procedure may be understood to bring a sequence of states, actions and rewards: s1, a1,r1;...;sT,aT,rT. The agent may use different learning algorithms to learn the most appropriate action to take on every different state of the NW, e.g., policy-learning based, such as actor-critic approaches, or value-based learning, such as deep-q networks.

[0056] Rel-18 / Rel-19 AI / ML for CSI feedback enhancements

[0057] Artificial Intelligence (Al) and Machine Learning (ML) have been investigated, both in academia and industry, as promising tools to optimize the design of the air-interface in wireless communication networks. Example use cases may include using autoencoders for Channel State Information (CSI) compression to reduce the feedback overhead and improve channel prediction accuracy; using deep neural networks for classifying Line-of-Sight (LOS) and Non-LOS (NLOS) conditions to enhance the positioning accuracy; using reinforcement learning for beam selection at the network side and / or the User Equipment (UE) side to reduce the signaling overhead andbeam alignment latency; and using deep reinforcement learning to learn an optimal precoding policy for complex Multiple Input Multiple Output (MIMO) precoding problems.

[0058] In 3rd Generation Partnership Project (3GPP) New Radio (NR) standardization work, a release 18 study item on AI / ML for the NR air interface started in May 2022 and completed in December 2023. This study item explored the benefits of augmenting the air-interface with features enabling improved support of AI / ML based algorithms for enhanced performance and / or reduced complexity and / or overhead. Through studying a few selected use cases, CSI feedback, beam management, and positioning, this study item may be understood to aim at laying the foundation for future air-interface use cases leveraging AI / ML techniques.

[0059] Terminologies such as AI / ML model, AI / ML model inference, which may be henceforth referred to as inference, AI / ML model training, which may be henceforth referred to as training, data collection, and model monitoring may be as defined in Section 3.1 of 3GPP TR 38.843 v.

[0060] 18.0.0.

[0061] Two Al CSI use cases, that is, CSI prediction and CSI compression, were studied in 3GPP Rel-18. After continuing study in Rel-19, the CSI prediction use case may start its normative work since the beginning of 2025, while the CSI compression use case may be under continue study in for the whole release of 3GPP Rel-19.

[0062] The CSI prediction use-case using one or more one-sided UE-sided models, where the model inference may be performed entirely at the UE. One or more AI / ML models may be trained and deployed at a UE for the Al-based CSI-prediction feature. During model inference, a UE may be configured by the gNB to measure a set of historical CSI-RSs and then report a predicted CSI for one or multiple future time instances using its AI / ML model(s). Figure 3 provides a non-limiting example for the inference procedure for CSI prediction. For generating the input of CSI prediction model, it may need some further pre-processing on the measured channel; for the output of the CSI prediction model, some further post-processing may also be applied.

[0063] Figure 3 is a schematic diagram illustrating a non-limiting example of the CSI prediction using UE-sided Al model(s).

[0064] The CSI compressing use case using one or more two-sided AI / ML models. A two-sided AI / ML model may be understood to refer to a paired AI / ML Model(s) over which joint inference may be performed across the UE and the network (NW), e.g., the first part of the inference may be first performed by UE and then the remaining part may be performed by gNB, or vice versa. As an example, Figure 4 shows a non-limiting example of the autoencoder (AE)-based CSI compression, where an encoder, a UE-part of the two-sided AE model, may be operated at a UE to compress the estimated wireless channel, and the output of the encoder, the compressed wireless channel information estimates, may be reported from the UE to a gNB. The gNB may use a decoder, the NW-part of the two-sided AE model, to reconstruct the estimated wireless channel information. Here, the two-sided AI / ML model may be composed of the encoder at theUE side and the decoder at the base station, e.g., a gNB, side. Note that in the case of a two-sided model, the code may be generated by the encoder and only interpretable by a jointly trained decoder. The situation may be understood to be different from running an AI / ML model in the UE, reporting the output over the air in a fully standardized format, and running a separate AI / ML model at the base station.

[0065] Figure 4 is a schematic diagram illustrating a non-limiting example of an autoencoder (AE)-based CSI compression using two-sided AI / ML model use case.

[0066] CRI based CSI reporting

[0067] When multiple CSI-RS resources are configured for channel measurement in a CSI report configuration in NR up to Release-18 for CSI feedback, one of the CSI-RS resources may be first selected by the UE and CSI associated to the selected CSI-RS resource may be computed and reported. In this case, a CSI-RS resource indicator (CRI) may be also reported to indicate the selected CSI-RS resource.

[0068] One use case of such CSI reporting may be to support hybrid analog and digital beamforming due to hardware restrictions. For example, analog beam may be implemented for elevation beamforming where multiple analog beams, one at a time, may be formed in elevation domain while within each of the analog beams, digital beamforming may be performed in the azimuth direction. Another use case may be to support hybrid time-domain and frequency-domain digital beamforming. For example, different elevation beams may be formed in digital time-domain, one in each time instance. For each such elevation beam, frequency-domain digital beamforming may be performed in the azimuth direction.

[0069] An example is shown in Figure 5, where four analog beams are formed in the elevation dimension. The four beams may be transmitted at different time instances. Each of the analog beams may be associated to a NZP CSI-RS resource comprising eight beamformed CSI-RS antenna ports in NR up to Release-18. In this case, a UE may measure downlink channels based on the four NZP CSI-RS resources and may determine a best beam among the four beams. The CSI feedback may comprise a CRI indicating the selected beam or the associated NZP CSI-RS resource, Rl, PMI and one or two CQIs associated with the NZP CSI-RS resource. The PMI may indicate a precoding matrix for the beamformed antenna ports.

[0070] In NR up to Release 18, two, four or eight NZP CSI-RS resources may be configured for the purpose and up to eight CSI-RS ports per NZP CSI-RS resource may be configured. In addition, the total number of NZP CSI-RS antenna ports across all the configured NZP CSI-RS resources may not exceed 32.

[0071] Figure 5 is a schematic diagram illustrating a non-limiting example of CSI report for hybrid beamforming with multiple Non-Zero Power (NZP) CSI-RS resources, one NZP CSI-RS resource per beam.

[0072] CRI based CSI reporting for more than 32 ports in Release-19In Rel-19, to support CRI based CSI reporting in increasingly large gNB antenna arrays, it was agreed to extend the existing framework CRI(s)-based CSI reporting for hybrid beamforming. Release 19 may support up to a total of 128 CSI-RS ports across all resources in a CSI-RS resource set.

[0073] In the Release 19 CRI-based reporting framework, a UE may be configured to measure Ks> 1 NZP CSI-RS resources with equal number of ports, with up to 32 ports per NZP CSI-RS resource. The supported combinations of Ksvalue and the maximum number of ports per NZP CSI-RS resource may be as follows shown in Table 4.

[0074] Table 4. Supported combinations of Ksand maximum number of ports per NZP CSI-RS resource.

[0075]

[0076] The CRI-based report may contain the information of M “quadruplets” (CRIn, Rin, PMIn, CQIn), where n = 0, ...,M - 1 and where a legacy codebook, e.g., with up to 32 ports, may be configured for all M “quadruplets”. The supported codebooks may be Rel-15 Type-1 single panel codebook, as defined in Clause 5.2.2.2.1 of 3GPP TS 38.214 v.18.4.0, and Rel-16 eType-ll codebook, as defined in Clause 5.2.2.2.5 of 3GPP TS 38.214, v.18.4.0.

[0077] M may be understood to be a network-configured para, meter via higher-layer RRC signaling. For Rel-15 Type-I single panel codebook, M candidate values may be between 1 and min(4, Ks). For Rel-16 eType-ll codebook, only M = {1,2} may be supported. Further, when M > 1, PMI, Rl and CQI may be independently signalled per CRI.

[0078] SUMMARY

[0079] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description.

[0080] According to a first aspect of the present disclosure, a computer-implemented method performed by the first device is provided. The method is for handling Channel State Information Reference Signals, CSI-RSs, the first device operating in a communications system. The method comprises obtaining a first set of measurements on CSI-RSs transmitted by a first network node operating in the communications system. The first set of measurements has been performed according to one or more of a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and a secondindication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device.

[0081] According to embodiments of the first aspect of the present disclosure, the method may include one or more of the following features. The method may further comprise obtaining a second set of measurements on the CSI-RSs transmitted by the first network node, wherein the second set of measurements has been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources. The method may further comprise sending, to the first network node, or to a second network node operating in the communications system, one or more of a third indication of the first set of measurements, and a fourth indication of the second set of measurements. The method may further comprise one or more of training a machine learning model, MLM, with the obtained first set of measurements and the second set of measurements, to predict a fifth indication of a Channel State Information, CSI, of a channel between the first device and the first network node based on one of the first subset of the first set of two or more CSI-RS resources and the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources, and initiating outputting a sixth indication of the trained MLM. The first set of measurements may be a subset of the second set of measurements. The method may further comprise obtaining a first configuration of the first set of two or more CSI-RS resources, obtaining the one or more of the first indication of the first subset of the first set of two or more CSI-RS resources, and the second indication of the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources, wherein the obtaining of the first set of measurements comprises performing the first set of measurements and wherein the obtaining of the second set of measurements comprises performing the second set of measurements. The first device may obtain one second subset of the one or more CSI-RS ports, and wherein the obtained one second subset of the one or more CSI-RS ports is applied to all the configured CSI-RS resources in the first set of the two or more CSI-RS resources. The first device may obtain more than one second subset of the one or more CSI-RS ports, and wherein each of the more than one second subset of the one or more CSI-RS ports is indicated for one of the configured CSI-RS resources in the first set. The second subset of the one or more CSI-RS ports may be indicated per CSI-RS resource within the indicated first subset of the first set of two or more CSI-RS resources. The method may further comprise obtaining first information to be used forthetraining of the MLM, the first information comprising one or more of one or more codebooks the first device is to train the MLM to predict with, a seventh indication of specific CSI Resource Indicators, CRIs, that the first device is to train the MLM to always predict CSI for, an eighth indication of specific CRIs that the first device is to refrain from training the MLM to predict CSI for, second information of a number of reported CRIs, third information indicating how one ormore beams of the CSI-RS resources, transmitted by the first network node, are spatially related to each other, and a second configuration comprising a ninth indication of a condition indicating similar properties are shared by one or more downlink transmission beams, one or more transmit radio unit mappings for the configured CSI-RS resources, CSI-RS ports or both, one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both. The configured CSI-RS resources may be one of periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

[0082] According to a second aspect of the present disclosure, a first device for handling Channel State Information Reference Signals, CSI-RSs, is provided. The first device operates in a communications system and comprises processing circuitry configured to obtain a first set of measurements on CSI-RSs transmitted by a first network node operating in the communications system, wherein the first set of measurements has been performed according to one or more of a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and a second indication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device.

[0083] A third aspect of the present disclosure relates to, a computer-implemented method performed by a second device is provided. The method is for handling Channel State Information Reference Signals, CSI-RSs, the second device operating in a communications system. The method comprises obtaining a third configuration of a second set of two or more first CSI-RS resources, obtaining one or more of a tenth indication of a third subset of the second set of two or more Channel State Information Reference Signal, CSI-RS, resources, and an eleventh indication of one or more fourth subsets of one or more CSI-RS ports of a second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device, performing a third set of measurements on CSI-RSs transmitted by a third network node operating in the communications system, wherein the third set of measurements is performed according to one or more of the tenth indication, and the eleventh indication, predicting, using the performed third set of measurements as input to a trained machine learning model, MLM, a twelfth indication of a Channel State Information, CSI, of a channel between the second device and the third network node based on the third subset and the one or more fourth subsets, and initiating outputting a thirteenth indication of the twelfth indication.

[0084] According to embodiments of the third aspect of the present disclosure, the method may include one or more of the following features. The method may further comprise obtaining the trained MLM. The second device may obtain one fourth subset of the one or more CSI-RS ports of thesecond CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device, and wherein the obtained one fourth subset is applied to all the configured first CSI-RS resources. The second device may obtain more than one fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device, and wherein each of the more than one fourth subset is indicated for one of the configured first CSI-RS resources. A respective fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources may be indicated per first CSI-RS resource within the indicated third subset of the second set of two or more CSI-RS resources. The third subset of the second set of two or more CSI-RS resources may vary for different time instances. The one or more fourth subsets of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources may vary for different time instances. The method may further comprise obtaining fourth information to be used for the predicting, the fourth information comprising one or more of one or more first codebooks the second device is to use for the predicting, sixth information indicating how one or more first beams of the first CSI-RS resources, transmitted by the third network node, are spatially related to each other, a fourteenth indication of specific Channel State Information, CSI, Resource Indicators, CRIs, that the second device is to predict CSI for, a fifteenth indication of specific CRIs that the second device is to refrain from predicting CSI for, seventh information of a number of reported CRIs, a fourth configuration comprising a sixteenth indication of a first condition indicating similar properties are shared by one or more first downlink transmission beams, one or more first transmission radio unit one or more transmission radio unit mappings for the configured first CSI-RS resources, first CSI-RS ports or both, and one or more first transmission radio unit virtualizations for the configured first CSI-RS resources, first CSI-RS ports or both. The configured first CSI-RS resources may be one of periodic first CSI-RS resources, semi-persistent first CSI-RS resources and aperiodic first CSI-RS resources.

[0085] A fourth aspect of the present disclosure relates to, a second device for handling Channel State Information Reference Signals, CSI-RSs, the second device operating in a communications system, the second device comprising processing circuitry configured to: obtain a third configuration of a second set of two or more first CSI-RS resources, obtain one or more of: a tenth indication of a third subset of the second set of two or more Channel State Information Reference Signal, CSI-RS, resources, and an eleventh indication of one or more fourth subsets of one or more CSI-RS ports of a second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device, perform a third set of measurements on CSI-RSs transmitted by a third network node operating in the communications system, wherein the third set of measurements is performed according to one or more of: the tenth indication, and the eleventh indication, predict, using the performed third set of measurements as input to a trainedmachine learning model, MLM, a twelfth indication of a Channel State Information, CSI, of a channel between the second device and the third network node based on the third subset and the one or more fourth subsets, and initiate outputting a thirteenth indication of the twelfth indication.

[0086] According to a fifth aspect of the present disclosure, a computer-implemented method performed by a first network node is provided. The method is for handling Channel State Information Reference Signals, CSI-RSs, the first network node operating in a communications system. The method comprises sending a first configuration of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources to a first device operating in the communication system, and sending, to the first device one or more of a first indication of a first subset of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources, and a second indication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and transmitting the CSI-RSs.

[0087] According to embodiments of the fifth aspects of the present disclosure, the method may include one or more of the following features. The first network node may send one second subset of the one or more CSI-RS ports. The first network node may send more than one second subset of the one or more CSI-RS ports, and wherein each of the more than one second subset of the one or more CSI-RS ports is indicated for one of the configured CSI-RS resources in the first set. The second subset of the one or more CSI-RS ports may be indicated per CSI-RS resource within the indicated first subset of the first set of two or more CSI-RS resources. The method may further comprise sending first information to be used for the training of an MLM, the first information comprising one or more of one or more codebooks the first device is to train the MLM to predict with, a seventh indication of specific CSI Resource Indicators, CRIs, that the first device is to train the MLM to always predict CSI for, an eighth indication of specific CRIs that the first device is to refrain from training the MLM to predict CSI for, second information of a number of reported CRIs, third information indicating how one or more beams of the CSI-RS resources, transmitted by the first network node, are spatially related to each other, and a second configuration comprising a ninth indication of a condition indicating similar properties are shared by one or more downlink transmission beams, one or more transmit radio unit mappings for the configured CSI-RS resources, CSI-RS ports or both, one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both. The configured CSI-RS resources may be one of periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

[0088] A sixth aspect of the present disclosure relates to, a first network node for handling Channel StateInformation Reference Signals, CSI-RSs, the first network node operating in a communications system, the first network node comprising processing circuitry configured to: send a first configuration of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources to a first device operating in the communication system, and send, to the first device one or more of: i. a first indication of a first subset of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources, and ii. a second indication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and transmit the CSI-RSs.

[0089] According to a seventh aspect of the present disclosure, a computer-implemented method performed by a second network node is provided. The method is for handling Channel State Information Reference Signals, CSI-RSs, the second network node operating in a communications system. The method comprises obtaining, at least from a first device, a third indication of a first set of measurements on CSI-RSs transmitted by a first network node operating in the communications system, wherein the first set of measurements has been performed according to one or more of a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and a second indication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and obtaining, at least from the first device, a fourth indication of a second set of measurements on the CSI-RSs transmitted by the first network node, wherein the second set of measurements has been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

[0090] According to embodiments of the seventh aspects of the present disclosure, the method may include one or more of the following features. The method may further comprise one or more of training a machine learning model, MLM, with the obtained first set of measurements and the second set of measurements, to predict a fifth indication of a Channel State Information, CSI, of a channel between the first device and the first network node based on one of the first subset of the first set of two or more CSI-RS resources and the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources, and initiating outputting a sixth indication of the trained MLM. The first set of measurements may be a subset of the second set of measurements. The method may further comprise obtaining first information to be used for the training of the MLM, the first information comprising one or more of one or more codebooks the second network node is to train the MLM to predict with, a seventh indication of specific CSI Resource Indicators, CRIs, that the second network node is to train the MLM to always predictCSI for, an eighth indication of specific CRIs that the second network node is to refrain from training the MLM to predict CSI for, second information of a number of reported CRIs, third information indicating how one or more beams of the CSI-RS resources, transmitted by the first network node, are spatially related to each other, and a second configuration comprising a ninth indication of a condition indicating similar properties are shared by one or more downlink transmission beams, one or more transmit radio unit mappings for the configured CSI-RS resources, CSI-RS ports or both, one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both. The CSI-RS resources may be one of periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

[0091] An eighth aspect of the present disclosure relates to, a second network node for handling Channel State Information Reference Signals, CSI-RSs, the second network node operating in a communications system, the second network node comprising processing circuitry configured to: obtain, at least from a first device, a third indication of a first set of measurements on CSI-RSs transmitted by a first network node operating in the communications system, wherein the first set of measurements has been performed according to one or more of: a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and a second indication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and obtain, at least from the first device, a fourth indication of a second set of measurements on the CSI-RSs transmitted by the first network node, wherein the second set of measurements has been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

[0092] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.

[0093] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.

[0094] BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Non-limiting and non-exhaustive examples of embodiments herein are described in more detail with reference to the accompanying drawings, according to the following description.

[0096] Figure 1 is a schematic diagram illustrating a non-limiting example of a beam management procedure, according to existing methods.Figure 2 is a schematic diagram illustrating a non-limiting example of data transmission with spatial multiplexing, according to existing methods.

[0097] Figure 3 is a schematic diagram illustrating a non-limiting example of a two-dimensional antenna array of cross-polarized antenna elements, according to existing methods.

[0098] Figure 4 is a schematic diagram illustrating a non-limiting example of the CSI prediction using UE-sided Al model(s), according to existing methods.

[0099] Figure 5 is a schematic diagram illustrating a non-limiting example of CSI report for hybrid beamforming with multiple NZP CSI-RS resources, one NZP CSI-RS resource per beam, according to existing methods.

[0100] Figure 6 is a schematic diagram depicting an example of a communications system, according to embodiments herein.

[0101] Figure 7 illustrates a flowchart depicting a method in a first device, according to embodiments herein.

[0102] Figure 8 illustrates a flowchart depicting a method in a second device, according to embodiments herein.

[0103] Figure 9 illustrates a flowchart depicting a method in a first network node, according to embodiments herein.

[0104] Figure 10 illustrates a flowchart depicting a method in a second network node, according to embodiments herein.

[0105] Figure 11 illustrates a flowchart depicting a non-limiting example of methods according to embodiments herein.

[0106] Figure 12 illustrates a flowchart depicting another non-limiting example of methods according to embodiments herein.

[0107] Figure 13 illustrates a schematic diagram depicting non-limiting examples of aspects of embodiments herein.

[0108] Figure 14 is a schematic block diagram illustrating an embodiment of a first device, according to embodiments herein.

[0109] Figure 15 is a schematic block diagram illustrating an embodiment of a second device,

[0110] according to embodiments herein.

[0111] Figure 16 is a schematic block diagram illustrating an embodiment of a first network node,

[0112] according to embodiments herein.

[0113] Figure 17 is a schematic block diagram illustrating an embodiment of a second network node, according to embodiments herein.

[0114] Figure 18 is a schematic block diagram illustrating an example of a communication system 1800 in accordance with some embodiments.

[0115] Figure 19 is a schematic block diagram illustrating another example of a communication system 1900 according to some embodiments.Figure 20 is a schematic block diagram illustrating an example of a wireless device 200, which may be configured to operate in communication system 1800 of Figure 18 or in communication system 1900 of Figure 19.

[0116] Figure 21 is a schematic block diagram illustrating an example of a network node 2100 in accordance with some embodiments.

[0117] Figure 22 is a schematic block diagram illustrating an example of a virtualization environment 2200 in which functions implemented by some embodiments may be virtualized.

[0118] DETAILED DESCRIPTION

[0119] As part of the development of embodiments herein, one or more challenges with the existing technology will first be identified and discussed.

[0120] CSI-RS overhead is becoming a problem due to larger Transmission Reception Points (TRPs) array, especially in the new frequency bands above 6 GHz. For CRI-based CSI reporting, where typically different CSI-RS resources may be transmitted sequentially in time in different analog, or time domain digital, TRP beams, the CSI-RS transmission may require several slots, which may significantly reduce the spectral efficiency of such beamforming architecture. In addition, with even larger arrays, the total number of ports transmitted across the multiple NZP CSI-RS resources may be even higher than the number 128 total ports supported in Rel-19. In such scenarios, how to support CRI-based CSI reporting with reduced CSI-RS overhead is an open problem to be solved.

[0121] Certain aspects of the present disclosure and their embodiments may provide solutions to these or other challenges. Examples of embodiments herein may relate to data collection for UE-sided CSI prediction for hybrid beamforming at TRP.

[0122] Signaling and configuration methods are described herein for enabling data collection for UE-sided spatial domain CSI prediction for CRI-based CSI reporting. Different CSI-RS resource subset indicator patterns and / or CSI-RS port indicator patterns may be introduced to indicate for the UE the CSI and / or port subsets that may be expected as model inputs. In some examples, Network (NW)-side additional conditions may be used to identify the deployment-dependent spatial filters that may be applied to the CSI-RS resources.

[0123] Some of the embodiments contemplated will now be described more fully hereinafter with reference to the accompanying drawings, in which examples are shown. In this section, the embodiments herein will be illustrated in more detail by a number of exemplary embodiments. Other embodiments, however, are contained within the scope of the subject matter disclosed herein. The disclosed subject matter should not be construed as limited to only the embodiments set forth herein; rather, these embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art. It should be noted that the exemplary embodiments herein are not mutually exclusive. Components from one embodimentmay be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments.

[0124] Figure 6 depicts two non-limiting examples, in panel a) and panel b), respectively, of a communications system 100, e.g., a wireless network or wireless communications network, sometimes also referred to as a wireless communications system, cellular radio system, or cellular network, in which embodiments herein may be implemented. The communications system 100 may be a 5G system, 5G network, or Next Gen System. In other examples, the communications system 100 may be a newer system with similar functionality, e.g., a 6G network. In other examples, the communications system 100 may, e.g., alternatively or additionally, support other technologies such as, for example, Long-Term Evolution (LTE), e.g., LTE for Machines (LTE-M), LTE Frequency Division Duplex (FDD), LTE Time Division Duplex (TDD), LTE Half-Duplex Frequency Division Duplex (HD-FDD), LTE operating in an unlicensed band, such as LTE Licensed-Assisted Access (LAA), enhanced eLAA (eLAA), further enhanced LAA (feLAA) and / or MulteFire. Yet in other examples, the communications system 100 may further support other technologies such as, for example Wideband Code Division Multiple Access (WCDMA), Universal Terrestrial Radio Access (UTRA) TDD, Global System for Mobile communications (GSM) network, GSM / Enhanced Data Rates for GSM Evolution (EDGE) Radio Access Network (GERAN) network, Ultra-Mobile Broadband (UMB), EDGE network, network comprising any combination of Radio Access Technologies (RATs) such as e.g. Multi-Standard Radio (MSR) base stations, multi-RAT base stations etc., any 6rd Generation Partnership Project (3GPP) cellular network, WiFi networks, Worldwide Interoperability for Microwave Access (WiMax), or any cellular network or system. The communications system 100 may support Machine Type Communication (MTC), enhanced MTC (eMTC), Internet of Things (loT) and / or NarrowBand loT (NB-loT). Thus, although terminology from 5G / NR and LTE may be used in this disclosure to exemplify embodiments herein, this should not be seen as limiting the scope of the embodiments herein to only the aforementioned system.

[0125] The communications system 100 may comprise a first network node 111 as depicted in the non-limiting examples of Figure 6. In some embodiments, the communications system 100 may comprise a second network node 112. In other embodiments, the communications system 100 may comprise a third network node 113. Any of the first network node 111, the second network node 112 and the third network node 113 may be a radio network node, radio access node or RAN node. That is, a transmission point such as a radio base station, for example a gNB, or any other network node with similar features capable of serving a user equipment, such as a wireless device or a machine type communication device, in the communications system 100. In some examples, any of the first network node 111, the second network node 112 and the third network node 113 may be a distributed node or may manage a virtualized network function, and may partially perform its functions in collaboration with a virtualnode in a cloud 115. Any of the first network node 111, the second network node 112 and the third network node 113 may be directly connected to one or more core networks, e.g., to one or more network nodes in the one or more core networks. Any of the first network node 111 , the second network node 112 and the third network node 113 may be of different classes, such as, e.g., macro base station, home base station or pico base station, based on transmission power and thereby also cell size. In some examples, any of the first network node 111 , the second network node 112 and the third network node 113 may serve receiving nodes with serving beams. Any of the first network node 111 , the second network node 112 and the third network node 113 may support one or several communication technologies, and its name may depend on the technology and terminology used.

[0126] In some examples, the third network node 113 may be a core network node, e.g., a core network access node. In some examples, as depicted in panel b) of Figure 6, the third network node 113 may be a network node in the cloud 115.

[0127] Any of the first network node 111 , the second network node 112 and the third network node 113 may be the same node, or be co-localized. In some examples, as depicted in the non-limiting example of panel a) of Figure 6, the first network node 111 , the second network node 112 and the third network node 113 may be the same network node. In some examples, as depicted in the non-limiting example of panel b) of Figure 6, the first network node 111 and the second network node 112 may be the same network node, and the third network node 113 may be a different network node. In other examples, the first network node 111 , the second network node 112 and the third network node 113 may be different network nodes.

[0128] The communications system 100 may cover a geographical area, which in some embodiments may be divided into cell areas, wherein each cell area may be served by a radio network node, although, one radio network node may serve one or several cells.

[0129] In some examples, the communications system 100 may include an access network, such as a radio access network (RAN), and a core network, which may include one or more core network nodes. The access network may include one or more access network nodes, such as any of the first network node 111, the second network node 112, the third network node 113, e.g., which may be generally referred to as network nodes, or any other similar 3rd Generation Partnership Project (3GPP) access nodes or non-3GPP access points. Moreover, as will be appreciated by those of skill in the art, a network node may not necessarily be limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it may be understood that network nodes may include disaggregated implementations or portions thereof. For example, in some embodiments, the communications system 100 may include one or more Open-RAN (ORAN) network nodes. Any of the first network node 111 , the second network node 112, and the third network node 113 may be ORAN network nodes. An ORAN network node may be understood to be a node in thecommunications system 100 that may support an ORAN specification, e.g., a specification published by the O-RAN Alliance, or any similar organization, and may operate alone or together with other nodes to implement one or more functionalities of any node in the communications system 100, including one or more network nodes and / or core network nodes.

[0130] Examples of an ORAN network node may include an open radio unit (0-Rll), an open distributed unit (0-Dll), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller, near-real time or non-real time, hosting software or software plug-ins, such as a near-real time control application, e.g., xApp, or a non-real time control application, e.g., rApp, or any combination thereof, the adjective “open” designating support of an ORAN specification. Any of the first network node 111 , the second network node 112, and the third network node 113 may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an A1, F1, W1, E1, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment, in which one or more network functions may be virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an O-2 interface defined by the O-RAN Alliance or comparable technologies.

[0131] O-RAN may specify intent Application Programming Interfaces (APIs) toward the Service Management and Orchestration (SMO).

[0132] A plurality of devices may be located in the communication system 100, whereof a first device 131 is depicted in the non-limiting example of Figure 6. In some embodiments, as depicted in the non-limiting examples of Figure 6, the communications system 100 may comprise second device 132. Any of the first device 131 and the second device 132 may be a wireless communication device such as a UE, a 5G UE or nUE, which may also be known as e.g., mobile terminal, wireless terminal and / or mobile station, a mobile telephone, cellular telephone, or laptop with wireless capability, just to mention some further examples. Any of the first device 131 and the second device 132 may be, for example, portable, pocket-storable, hand-held, computer-comprised, or a vehicle-mounted mobile device, enabled to communicate voice and / or data, via the RAN, with another entity, such as a server, a laptop, a Personal Digital Assistant (PDA), or a tablet, Machine-to-Machine (M2M) device, a sensor, loT device, NB-loT device, device equipped with a wireless interface, such as a printer or a file storage device, modem, or any other radio network unit capable of communicating over a radio link in a communications system. Any of the first device 131 and the second device 132 comprised in the communications system 100 may be enabled to communicate wirelessly in the communications system 100. The communication may be performed e.g., via a RAN, andpossibly the one or more core networks, which may be comprised within the communications system 100.

[0133] The first device 131 may be configured to communicate within the wireless communications network 100 with the first network node 111 over a first link, e.g., a radio link, via any of the one or more beams 121, 122, 123, or one or more cells. The first device 131 may be configured to communicate within the wireless communications network 100 with the second network node 112 over a second link 142, e.g., a radio link or a wired link. The second device 132 may be configured to communicate within the wireless communications network 100 with the second network node 112 over a third link 143, e.g., a radio link or a wired link. The second device 132 may be configured to communicate within the wireless communications network 100 with the third network node 113 over a respective link, e.g., a radio link, such as via any of the one or more beams 121 , 122, 123, or one or more cells, or other one or more beams served by the third network node 113. The first network node 111 may be configured to communicate within the communications system 100 with the second network node 112 over a fourth link 144, e.g., a radio link or a wired link.

[0134] Generally, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is clearly given and / or is implied from the context in which it is used. All references to a / an / the element, apparatus, component, means, step, etc. are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and / or where it is implicit that a step must follow or precede another step. Any feature of any of the embodiments disclosed herein may be applied to any other embodiment, wherever appropriate. Likewise, any advantage of any of the embodiments may apply to any other embodiments, and vice versa. Other objectives, features and advantages of the enclosed embodiments will be apparent from the following description.

[0135] In general, the usage of “first”, “second”, “third”, ... , and / or “fifteenth” herein may be understood to be an arbitrary way to denote different elements or entities, and may be understood to not confer a cumulative or chronological character to the nouns they modify, unless otherwise noted, based on context.

[0136] Several embodiments are comprised herein. It should be noted that the examples herein are not mutually exclusive. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments.

[0137] More specifically, the following are embodiments related to a device, such as the first device 131, e.g., a first UE, a second device, such as the second device 132, e.g, a second UE,a first network node, such as the first network node 111, e.g., a first gNB, and a second network node, such as the second network node 112, e.g., a second gNB.

[0138] In the following description CSI-RS is taken an illustrative example. CSI-RS may be replaced in the following description by a / the “first reference signal” or a / the “first RS”.

[0139] The first device 131 embodiments relate to Figure 7, any of Figures 11-14, and Figures 18-20.

[0140] A computer-implemented method, performed by a device, such as the first device 131 is described herein. The method may be understood to be for handling Channel State Information Reference Signals (CSI-RSs) The first device 131 may operate in a communications system, such as the communications system 100.

[0141] In some embodiments, the communications system 100 may support New Radio (NR). The method may comprise one or more of the following actions. In some embodiments, all the actions may be performed. In some examples, Action 704 may be performed. One or more embodiments may be combined, where applicable. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. All possible combinations are not described to simplify the description. A non-limiting example of the method performed by the first device 131 is depicted in Figure 7. In Figure 7, optional actions in some embodiments may be represented with dashed lines. In some embodiments, the actions may be performed in a different order than that depicted Figure 7.

[0142] o Obtaining 704 a first set of measurements. The first device 131 may be configured to perform the obtaining in this Action 704.

[0143] The first set of measurements may be on CSI-RSs. The CSI-RSs may be transmitted by a first network node 111 operating in the communications system 100.

[0144] The first set of measurements may have been performed according to one or more of : i. a first indication; the first indication may be, e.g., of a first subset of a first set of two or more Channel State Information Reference Signal (CSI-RS) resources configured at the first device 131, and

[0145] ii. a second indication; the second indication may be, e.g., of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), e.g., a first CSI-RS resource of the first set of two or more CSI-RS resources configured at the first device 131.

[0146] The first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern.The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0147] Any of the one or more CSI-RS ports may be a reference signal that may be transmitted from a Transmitter, such as the first network node 111, e.g., from a gNB / TRP.

[0148] Obtaining in this Action 704 may comprise receiving, retrieving, fetching or performing the first set of measurements.

[0149] In some embodiments, the obtaining 704 of the first set of measurements may comprise performing the first set of measurements.

[0150] The configured CSI-RS resources may be one of: periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

[0151] In some embodiments, the method may further comprise one or more of the following actions:

[0152] o Obtaining 705 a second set of measurements. The first device 131 may be configured to perform the obtaining in this Action 705.

[0153] The second set of measurements may be on the CSI-RSs. The CSI-RSs may be transmitted by the first network node 111. The second set of measurements may have been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

[0154] In some embodiments, the obtaining 705 of the second set of measurements may comprise performing the second set of measurements.

[0155] o Sending 706 one or more of: a third indication and a fourth indication. The first device 131 may be configured to perform the sending in this Action 706.

[0156] The sending in this Action 706 may be to the first network node 111, or to the second network node 112 operating in the communications system 100.

[0157] The third indication may be of the first set of measurements.

[0158] The fourth indication may be of the second set of measurements.

[0159] The first set of measurements may be a subset of the second set of measurements. In some embodiments, the method may further comprise one or more of the following two actions: In some embodiments,

[0160] o Training 707 a machine learning model, MLM. The first device 131 may be configured to perform the training in this Action 707.

[0161] The MLM may be any of, e.g., a Neural Network, a Convolutional Neural Network, a Federated Learning MLM, an Autoencoder, Decision Tree, etc.

[0162] The training of the MLM may be with the obtained first set of measurements and the second set of measurements.

[0163] The training of the MLM may be to predict a fifth indication. The fifth indication may be of a Channel State Information (CSI). The CSI may be of a channel between the first device 131and the first network node 111. The training of the MLM to predict the fifth indication may be based on one of the first subset of the first set of two or more CSI-RS resources and the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources.

[0164] o Initiating 708 outputting a sixth indication. The first device 131 may be configured to perform the initiating in this Action 708.

[0165] Initiating may comprise starting or triggering.

[0166] The sixth indication may be of the trained MLM.

[0167] In some embodiments, the method may further comprise one or more of the following two actions:

[0168] o Obtaining 701 a first configuration. The first device 131 may be configured to perform the obtaining in this Action 701.

[0169] The first configuration may be of the first set of two or more CSI-RS resources.

[0170] o Obtaining 702 one or more of the first indication and the second indication. The first device 131 may be configured to perform the obtaining in this Action 702.

[0171] The first indication may be of the first subset of the first set of two or more CSI-RS resources.

[0172] The second indication may be of the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources.

[0173] In some embodiments, the first device 131 may obtain one second subset of the one or more CSI-RS ports. The obtained one second subset of the one or more CSI-RS ports may be applied to all the configured CSI-RS resources in the first set of the two or more CSI-RS resources.

[0174] In some embodiments, the first device 131 may obtain more than one second subset of the one or more CSI-RS ports. Each of the more than one second subset of the one or more CSI-RS ports may be indicated for one of the configured CSI-RS resources in the first set.

[0175] In some embodiments, the second subset of the one or more CSI-RS ports may be indicated per CSI-RS resource within the indicated first subset of the first set of two or more CSI-RS resources. In some examples, the second subset of the one or more CSI-RS ports may be-different for different CSI-RS resources.

[0176] o Obtaining 703 first information. The first device 131 may be configured to perform the obtaining in this Action 703.

[0177] The first information may be to be used for the training of the MLM. The first information may comprise one or more of:

[0178] i. one or more codebooks the first device 131 may have to train the MLM to predict with,ii. a seventh indication of specific CSI Resource Indicators (CRIs) that the first device 131 may have to train the MLM to always predict CSI for, iii. an eighth indication of specific CRIs that the first device 131 may have to refrain from training the MLM to predict CSI for,

[0179] iv. second information of a number of reported CRIs,

[0180] v. third information indicating how one or more beams of the CSI-RS resources, transmitted by the first network node 111, may be spatially related to each other, and

[0181] vi. a second configuration comprising a ninth indication of a condition indicating similar properties may be shared by:

[0182] a) one or more downlink transmission beams,

[0183] b) one or more transmit radio unit mappings for the configured CSI- RS resources, CSI-RS ports or both,

[0184] c) one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both.

[0185] The first device 131 may be a device that may collect data to use as input to the MLM during a training phase of the MLM. In some examples, the first device 131 may train the MLM itself.

[0186] Figure 14, optional units are indicated with dashed boxes.

[0187] The first device 131 may comprise an arrangement as shown in Figure 14 or in Figure 20.

[0188] The second device 132 embodiments relate to Figure 8, any of Figures 11-13, Figure 15 and Figures18-20.

[0189] A computer-implemented method, performed by a device, such as the second device 132 is described herein. The method may be understood to be for handling CSI-RSs. The second device 132 may operate in a communications system, such as the communications system 100.

[0190] In some embodiments, the communications system 100 may support New Radio (NR). The method may comprise one or more of the following actions. In some embodiments, all the actions may be performed. In some examples, Action 802, Action 803, Action 805, Action 806 and Action 807 may be performed. One or more embodiments may be combined, where applicable. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. All possible combinations are not described to simplify the description. A non-limiting example of the method performed by the second device 132 is depicted in Figure 8. In Figure 8, optional actions in some embodiments may berepresented with dashed lines. In some embodiments, the actions may be performed in a different order than that depicted Figure 8.

[0191] The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the first device 131 and will thus not be repeated here to simplify the description. For example, the first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0192] The second device 132 may be a device that may perform inference with the MLM, once trained. The second device 132 may use similar input data to the MLM as the first measurements, using new or fresh data or measurements.

[0193] o Obtaining 802 a third configuration. The second device 132 may be configured to perform the obtaining in this Action 802.

[0194] The third configuration may be of a second set of two or more first CSI-RS resources. In some examples, the second set may be a new set of the two or more CSI-RS resources. In other examples, the third configuration may be the first configuration.

[0195] o Obtaining 803 one or more of a tenth indication and an eleventh indication. The second device 132 may be configured to perform the obtaining in this Action 803.

[0196] i. The tenth indication may be of a third subset of the second set of two or more Channel State Information Reference Signal, CSI-RS, resources, and

[0197] ii. The eleventh indication may be of one or more fourth subsets of one or more CSI-RS ports of a second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device 132.

[0198] Any of the third subset and the one or more fourth subsets may be new subsets obtained during an inference of the MLM.

[0199] o Performing 805 a third set of measurements. The second device 132 may be configured to perform the performing in this Action 805.

[0200] The third set of measurements may be on CSI-RSs transmitted by the third network node 113 operating in the communications system 100. The third set of measurements may be performed according to one or more of:

[0201] i. the tenth indication, and

[0202] ii. the eleventh indication.The tenth indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The eleventh indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0203] o Predicting 806 a twelfth indication. The second device 132 may be configured to perform the predicting in this Action 806.

[0204] The twelfth indication may be of a CSI of a channel between the second device 132 and the third network node 113. The predicting 806 may be based on the third subset and the one or more fourth subsets.

[0205] The predicting 806 may be using the performed third set of measurements as input to the trained MLM.

[0206] o Initiating 807 outputting a thirteenth indication. The second device 132 may be configured to perform the initiating in this Action 807.

[0207] Initiating may comprise starting or triggering, e.g., sending, the thirteenth indication.

[0208] The thirteenth indication may be of the twelfth indication. The thirteenth indication may be a result of the inference using the MLM.

[0209] In some embodiments, the method may further comprise one or more of the following actions:

[0210] o Obtaining 801 the trained MLM. The second device 132 may be configured to perform the obtaining in this Action 801.

[0211] The obtaining in this Action 801 may be, e.g., from the first device 131 or the second network node 112 operating in the communications network 100.

[0212] In some embodiments, the second device 132 may obtain one fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device 132, The obtained one fourth subset may be applied to all the configured first CSI-RS resources.

[0213] In some embodiments, the second device 132 may obtain more than one fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device 132. Each of the more than one fourth subset may be indicated for one of the configured first CSI-RS resources.

[0214] In some embodiments, a respective fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources may be indicated per first CSI-RS resource within the indicated third subset of the second set of two or more CSI-RS resources. In some examples, the respective fourth subset may be different for different CSI-RS resources.

[0215] In some embodiments, the third subset of the second set of two or more CSI-RS resources may vary for different time instances.In some embodiments, the one or more fourth subsets of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources may vary for different time instances.

[0216] o Obtaining 804 fourth information. The second device 132 may be configured to perform the obtaining in this Action 804.

[0217] The fourth information may be to be used for the predicting 806.

[0218] The fourth information may comprise one or more of:

[0219] i. one or more first codebooks the second device 132 may have to use for the predicting 806,

[0220] ii. sixth information indicating how one or more first beams of the first CSI-RS resources, transmitted by the third network node 113, may be spatially related to each other,

[0221] iii. a fourteenth indication of specific CRIs that the second device 132 may have to predict CSI for,

[0222] iv. a fifteenth indication of specific CRIs that the second device 132 may have to refrain from predicting CSI for,

[0223] v. seventh information of a number of reported CRIs, vi. a fourth configuration comprising a sixteenth indication of a first condition indicating similar properties may be shared by:

[0224] d) one or more first downlink transmission beams,

[0225] e) one or more first transmission radio unit one or more transmission radio unit mappings for the configured first CSI- RS resources, first CSI-RS ports or both, and

[0226] f) one or more first transmission radio unit virtualizations for the configured first CSI-RS resources, first CSI-RS ports or both.

[0227] In some embodiments, the configured first CSI-RS resources may be one of: periodic first CSI-RS resources, semi-persistent first CSI-RS resources and aperiodic first CSI-RS resources.

[0228] In Figure 15, optional units are indicated with dashed boxes.

[0229] The second device 132 may comprise an arrangement as shown in Figure 15 or in Figure 20.

[0230] The first network node 111 embodiments relate to Figure 9, any of Figures 11-13, Figure 16 and Figures 18-19, and Figures 21-22.A computer-implemented method, performed by a network node, such as the first network node 111 is described herein. The method may be understood to be for handling CSI-RSs. The first network node 111 may operate in a communications system, such as the communications system 100.

[0231] In some embodiments, the communications system 100 may support New Radio (NR). The method may comprise one or more of the following actions. In some embodiments, all the actions may be performed. In some examples, Action 901 and Action 902 may be performed. In some examples, Action 901, Action 902 and Action 903 may be performed. One or more embodiments may be combined, where applicable. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. All possible combinations are not described to simplify the description. A non-limiting example of the method performed by the first network node 111 is depicted in Figure 9. In Figure 9, optional actions in some embodiments may be represented with dashed lines. In some embodiments, the actions may be performed in a different order than that depicted Figure 9.

[0232] The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the first device 131 and will thus not be repeated here to simplify the description. For example, the first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0233] The first network node 111 may be a network node that may configure the first device 131 to collect data to use as input to the MLM during a training phase of the MLM. In some examples, the first network node 111 may train the MLM itself.

[0234] o Sending 901 the first configuration. The first network node 111 may be configured to perform the sending in this Action 901.

[0235] The first configuration may be of the first set of two or more CSI-RS resources.

[0236] The sending in this Action 901 may be to the first device 131 operating in the communication system 100.

[0237] o Sending 902 one or more of the first indication and the second indication. The first network node 111 may be configured to perform the sending in this Action 902.

[0238] The sending in this Action 902 may be to the first device 131.

[0239] i. the first indication may be, e.g., of the first subset of the first set of two or more CSI-RS resources;

[0240] ii. the second indication may be, e.g., of the one or more second subsets of the one or more CSI-RS ports of the first set of two or more Channel State InformationReference Signal, CSI-RS, resources configured at the first device (131), e.g., the first CSI-RS resource of the first set of two or more CSI-RS resources.

[0241] In some embodiments, the first network node 111 may send one second subset of the one or more CSI-RS ports.

[0242] In some embodiments, the first network node 111 may send more than one second subset of the one or more CSI-RS ports. Each of the more than one second subset of the one or more CSI-RS ports may be indicated for one of the configured CSI-RS resources in the first set.

[0243] In some embodiments, the second subset of the one or more CSI-RS ports may be indicated per CSI-RS resource within the indicated first subset of the first set of two or more CSI-RS resources; the second subset may be different for different CSI-RS resources.

[0244] In some embodiments, the method may further comprise the following action:

[0245] o Transmitting 903 the CSI-RSs. The first network node 111 may be configured to perform the transmitting in this Action 903.

[0246] The transmitting in this Action 903 may be, e.g., according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

[0247] The configured CSI-RS resources may be one of: periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

[0248] In some embodiments, the method may further comprise the following action:

[0249] o Sending 904 the first information. The first network node 111 may be configured to perform the sending in this Action 904.

[0250] The first information may be to be used for the training of the MLM. The first information may comprise one or more of:

[0251] i. the one or more codebooks the first device 131 may have to train the MLM to predict with,

[0252] ii. the seventh indication of the specific CRIs that the first device 131 may have to train the MLM to always predict CSI for,

[0253] iii. the eighth indication of the specific CRIs that the first device 131 may have to refrain from training the MLM to predict CSI for,

[0254] iv. the second information of the number of reported CRIs, v. the third information indicating how the one or more beams of the CSI-RS resources, transmitted by the first network node 111, may be spatially related to each other, and

[0255] vi. the second configuration comprising the ninth indication of the condition indicating similar properties may be shared by:

[0256] a) the one or more downlink transmission beams,b) the one or more transmit radio unit mappings for the configured CSI-RS resources, CSI-RS ports or both,

[0257] c) the one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both.

[0258] In Figure 16, optional units are indicated with dashed boxes.

[0259] The first network node 111 may comprise an arrangement as shown in Figure 16 or in any of Figures 21-22.

[0260] The second network node 112 embodiments relate to Figure 10, any of Figures 11-13, Figure 17 and Figures 18-19, and Figures 21-22.

[0261] A computer-implemented method, performed by a network node, such as the second network node 112 is described herein. The method may be understood to be for handling CSI-RSs. The second network node 112 may operate in a communications system, such as the communications system 100.

[0262] In some embodiments, the communications system 100 may support New Radio (NR). The method may comprise one or more of the following actions. In some embodiments, all the actions may be performed. In some examples, Action 1001 and Action 1002 may be performed. One or more embodiments may be combined, where applicable. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. All possible combinations are not described to simplify the description. A non-limiting example of the method performed by the second network node 112 is depicted in Figure 10. In Figure 10, optional actions in some embodiments may be represented with dashed lines. In some embodiments, the actions may be performed in a different order than that depicted Figure 10.

[0263] The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the first device 131 and will thus not be repeated here to simplify the description. For example, the first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0264] The second network node 112 may be a network node 112 that may collect data to use as input to the MLM during a training phase of the MLM and train the MLM.

[0265] o Obtaining 1001 the third indication. The second network node 112 may be configured to perform the obtaining in this Action 1001.

[0266] The obtaining in this Action 1001 may be at least from the first device 131. That is, the second network node 112 may receive a respective third indication from every first device.The third indication may be of the first set of measurements.

[0267] The first set of measurements may be on CSI-RSs. The CSI-RSs may be transmitted by the first network node 111 operating in the communications system 100.

[0268] The first set of measurements may have been performed according to one or more of : i. the first indication; the first indication may be, e.g., of the first subset of the first set of two or more CSI-RS resources configured at the first device 131, and

[0269] ii. the second indication; the second indication may be, e.g., of the one or more second subsets of the one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), e.g., the first CSI-RS resource of the first set of two or more CSI-RS resources configured at the first device 131.

[0270] The configured CSI-RS resources may be one of: periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

[0271] o Obtaining 1002 the fourth indication. The second network node 112 may be configured to perform the obtaining in this Action 1002.

[0272] The obtaining in this Action 1002 may be at least from the first device 131. That is, the second network node 112 may receive a respective fourth indication from every first device.

[0273] The fourth indication may be of the second set of measurements.

[0274] The second set of measurements may be on the CSI-RSs. The CSI-RSs may be transmitted by the first network node 111. The second set of measurements may have been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

[0275] The first set of measurements may be a subset of the second set of measurements.

[0276] In some embodiments, the method may further comprise one or more of the following two actions:

[0277] o Training 1004 the MLM. The second network node 112 may be configured to perform the training in this Action 1004.

[0278] The training of the MLM may be with the obtained first set of measurements and the second set of measurements.

[0279] The training of the MLM may be to predict the fifth indication. The fifth indication may be of the CS). The CSI may be of the channel between the first device 131 and the first network node 111. The training of the MLM to predict the fifth indication may be based on one of the first subset of the first set of two or more CSI-RS resources and the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources.

[0280] o Initiating 1005 outputting the sixth indication. The second network node 112 may be configured to perform the initiating in this Action 1005.

[0281] Initiating may comprise starting or triggering.The sixth indication may be of the trained MLM.

[0282] In some embodiments, the method may further comprise the following action:

[0283] o Obtaining 1003 the first information. The second network node 112 may be configured to perform the obtaining in this Action 1003.

[0284] The first information may be to be used for the training of the MLM. The first information may comprise one or more of:

[0285] i. the one or more codebooks the second network node 112 may have to train the MLM to predict with,

[0286] ii. the seventh indication of the specific CRIs that the second network node 112 may have to train the MLM to always predict CSI for,

[0287] iii. the eighth indication of the specific CRIs that the second network node 112 may have to refrain from training the MLM to predict CSI for, iv. the second information of the number of reported CRIs, v. the third information indicating how the one or more beams of the CSI-RS resources, transmitted by the first network node 111, may be spatially related to each other, and

[0288] vi. the second configuration comprising the ninth indication of the condition indicating similar properties may be shared by:

[0289] d) the one or more downlink transmission beams,

[0290] e) the one or more transmit radio unit mappings for the configured CSI-RS resources, CSI-RS ports or both,

[0291] f) the one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both.

[0292] In Figure 17, optional units are indicated with dashed boxes.

[0293] The second network node 112 may comprise an arrangement as shown in Figure 17 or in any of Figures 21-22.

[0294] Some embodiments herein will now be further described with some non-limiting examples, which may be combined with the embodiments just described.

[0295] In the following description, any reference to a / the UE, may be understood to equally refer to any of the first device 131 and the second device 132; any reference to a / the gNB and / or a / the Radio access node and / or a / the core network access node and / or a / the BS and / or a / the RAN node and / or a / the base station and / or a / the NW node may be understood to equally refer to any of the first network node 111 , the second network node 112 and the third network node 113; any reference to a / the node in RAN or in the core network may be understood to equally refer to the second network node 112.

[0296] Figure 11 illustrates a non-limiting example of a high-level flowchart of the training method, associated with embodiments herein.Figure 12 illustrates a non-limiting example of a high-level flowchart of the inference method associated with embodiments herein.

[0297] In the following examples, it may be assumed that the UE may have been configured for training of an AI / ML model used for CSI prediction for CRI-based CSI reporting, and wherein the UE may have been configured with M CSI-RS resources, wherein M may be 2 or larger, and where each CSI-RS resource may have N CSI-RS ports, wherein N may be 2 or larger.

[0298] In some examples, the UE may be configured with a CSI-RS resource subset indicator pattern, indicating which of the M CSI-RSs corresponding to the M CSI-RS resources that the UE may have to assume are to be muted, or conversely, which ones the UE may have to assume are to be transmitted, during inference. It may be understood to be relevant that the UE may know which CSI-RSs / CSI-RS ports that may be muted during inference such that the UE may train the AI / ML model accordingly.

[0299] In one detailed example, a bitstring may be used as CSI-RS resource subset indicator, and wherein the first bit may be used to indicate if a first CSI-RS corresponding to the first CSI-RS resource is muted, or, conversely, transmitted, during inference, the second bit may be used to indicate if a second CSI-RS corresponding to a second CSI-RS resource may be muted, or, conversely, transmitted, during inference, and so on. In one related example, the CSI-RS resources may be configured in a CSI-RS resource set, and the first CSI-RS resource may be the CSI-RS resource with lowest CSI-RS resource ID in that CSI-RS resource set, the second CSI-RS resource may be the CSI-RS resource with second lowest CSI-RS resource ID in that CSI-RS resource set, and so on.

[0300] In some examples, the UE may be configured with a CSI-RS port subset indicator pattern, indicating which of the N CSI-RS ports of one or more of the CSI-RSs corresponding to the M CSI-RS resources that the UE may have to assume are to be muted, or, conversely, that the UE may have to assume are to be transmitted, during inference. In one related example, one CSI-RS port subset indicator pattern is configured per CSI-RS resource. This may be understood to mean that, when the CSI-RS corresponding to the CSI-RS resource for which the CSI-RS port subset indicator pattern is configured, the UE may be required to know which of the N CSI-RS ports in the CSI-RS may be muted, or, conversely, transmitted, from the CSI-RS port subset indicator pattern. One benefit with this approach may be understood to be that inference may benefit from sounding different CSI-RS ports for different CSI-RS resources, e.g., different analog beams. In another related example, one CSI-RS port subset indicator pattern may be configured and applied to all M CSI-RS resources. One benefit with this approach may be understood to be that less RRC signaling may be required.

[0301] In an alternative example, which CSI-RSs corresponding to the M CSI-RS resources may be muted, or, conversely, transmitted, and which of the N CSI-RS ports of one or more of the CSI-RSs corresponding to the M CSI-RS resources may be jointly indicated via a bitstringwith N*M bits. In one detailed example, the Ith(j = 0, 1, ... , N * M - 1) bit in the jointly indicated bitstring may indicate whether or not the nth(n = 0, 1, .... , N - 1) CSI-RS port in the CSI-RS corresponding to the mth(m = 0,1, ...,M - 1) CSI-RS resource. In one detailed example, n and m may be given as follows:

[0302] n = mod(i,N),

[0303]

[0304] In an alternative example, n and m may be given as follows:

[0305] m = mod i,M

[0306]

[0307] In another example, a UE may receive a CSI-RS resource subset indicator pattern, e.g., a bitstring, indicating which of the M CSI-RSs corresponding to the M CSI-RS resources that the UE may have to assume are to be muted during inference. In an example, it may be assumed that the CSI-RS resource subset indicator pattern indicates M' of the M CSI-RSs corresponding to the M CSI-RS resources are muted. Then, M - M' CSI-RSs may be understood to be unmuted, and the UE may be configured with configured with M - M' CSI-RS port subset indicator patterns for these M - M' unmuted CSI-RSs. In a detailed example, the M - M' CSI-RS port subset indicator patterns may be associated with the M - M' CSI-RS resources corresponding to the M - M' unmuted CSI-RSs. This example may be understood to be beneficial as it may have reduced signaling overhead compared to the case when CSI-RS port subset indicator patterns may be signaled for all M CSI-RS resources.

[0308] In some alternative examples, the UE may be configured with a time domain configuration, consisting of P time configuration instances, and wherein different time configuration instances may be associated with different subset indicator pattern. In one related example, the UE may be configured with a CSI-RS resource subset indicator pattern for each of the P time configuration instances. This may be used for example to transmit, during inference, CSI-RS resources in a first half of the analog TRP beams in a first time instance, and the second half of the analog beams in a second time instance, which may facilitate CSI prediction at the UE compared to transmitting in the same analog TRP beams every time instance. In one related example, the UE may be configured with a CSI-RS port subset indicator pattern for each of the P time configuration instances. This may be used for example to transmit, during inference, CSI-RS ports in a first half of the TRP antenna elements in a first time instance, and the second half of the TRP antenna elements in asecond time instance, which may facilitate CSI prediction at the UE compared to transmit in the same analog TRP beams every time instance.

[0309] In one example, the UE may be indicated with CRIs that the UE may have to always predict CSI for, and / or indication of specific CRIs that the UE may not need to predict CSI for, and / or information of number of reported CRIs. This may be indicated during training of the AI / ML model to facilitate the training since the UE may get information about what CRI reporting settings may be used during inference.

[0310] In one example, the UE may also be configured with one or more non-AI / ML codebook schemes to be applied across an CSI-RS resource, and which the UE may have to assume when training the AI / ML model, for example a legacy NR Type I codebook, or legacy NR Type II codebook, or similar new codebooks in 6G.

[0311] In one example, the UE may be indicated with assistance information about how the TRP beams of the CSI-RS resources may be spatially related to each other, which may be indicated by RRC signaling and / or a rule in the specification. In one related example, based on the indicated assistance information, the UE may assume that CSI-RS resources configured in a CSI-RS resource set may be ordered according to the CSI-RS resource ID, and that these CSI-RS resources may be transmitted in TRP beams ordered according to spatial correlation, e.g., how close the pointing direction of the TRP beams may be. Figure 13 is a schematic diagram that illustrates one example of this, where the UE may assume that when CSI-RS resourcel is transmitted in a first TRP beam (Beaml), CSI-RS resource2 is transmitted in a second TRP beam (Beam2) with a pointing direction closest to the first TRP beam, CSI-RS resources is transmitted in a third TRP beam (Beam3) with a pointing direction closest to the second TRP beam, and CSI-RS resource4 is transmitted in a fourth TRP beam (Beam4) with a pointing direction closest to the third TRP beam.

[0312] In one example, two CSI-RS resources may be transmitted simultaneously, and where the two CSI-RS resources correspond to different TRP beams, and wherein the first CSI-RS resource is associated with antenna elements of a first polarization of the TRP antenna array, and the second CSI-RS resource is associated with antenna elements of a second polarization of the TRP antenna array. This may be used to speed up the sounding of all analog TRP beams in case the analog TRP beams may be steered individually per polarization.

[0313] In one example, an associated ID, may be used to identify the NW-sided additional conditions that may not be explicitly indicated to the UE. Examples of NW-sided additional conditions for this use case may include deployment-dependent spatial filter / spatial relation / spatial properties / polarization properties / TXRU virtualizations applied to the CSI-RS resources / CSI-RS ports. In one example, when a set of CSI-RS resources / CSI-RS ports may be configured / linked with an associated ID, the UE may assume that a fixed (over time) spatialfilter / spatial relation / spatial property / polarization property / TXRU virtualizations may be used for the CSI-RS resources and CSI-RS ports, both when used during training and inference.

[0314] In an example, the UE may assume that similar NW-side additional conditions, such as the properties of one or more DL Tx beams and / or the properties of one or more antenna port mappings / TXRU virtualizations for the configured CSI-RS resources / CSI-RS ports, may be associated with the same associated ID.

[0315] In an example, for a configuration of training data collection, the set of M CSI-RS resources and the set of N CSI-RS ports may be configured to be linked to an associated ID based on the NW-side additional conditions during the training data collection phase.

[0316] The model training may be done in different ways. As one example, the measurements collected for different associated IDs may be used for creating different training data sets to train different AI / ML models. As another example, the measurements collected for a group of multiple associated IDs may be used together to create a dataset to train an AI / ML model that may work for any of these associated IDs. As yet another example, the measurements collected for all associated IDs may be used together to create a global dataset to train a generic / global AI / ML model that may works for all association IDs.

[0317] In an example, for a configuration for model inference, the measurement resources for CSI reporting, e.g., the set of M CSI-RS resources, the set of N CSI-RS ports, the subset of CSI-RS resources and / or the subset of CSI-RS ports, may be configured to be linked to an associated ID based on the current NW additional conditions.

[0318] During model inference, when receiving the configuration with an associated ID, the UE may select an AI / ML model that may be training for such association ID to perform CSI prediction. If there is no model that matches to the received second associated ID, the UE may inform the network node, and request for fallback to other non-AI based schemes.

[0319] It may be noted that even though “bitstrings” are used herein, in some examples in this disclosure, the exact signaling may use some other structure and the examples disclosed may be non-limiting.

[0320] Examples herein may include:

[0321] Training

[0322] 1. A Method in a UE for data collection for training of a UE-sided AI / ML based spatial domain CSI prediction for CRI-based CSI reporting, the method comprising:

[0323] a. Receiving a configuration of two or more CSI-RS resources

[0324] b. Receiving at least one of:

[0325] i. a CSI-RS resource subset indicator patternii. one or more CSI-RS port subset indicator pattern(s) c. Perform a first set of measurements on the CSI-RSs according to the at least one of the CSI-RS resource subset indicator patterns and one or more CSI-RS port subset indicator pattern(s)

[0326] d. Perform a second set of measurements on the CSI-RSs according to all the configured CSI-RS resources

[0327] e. Perform training of the UE-sided AI / ML based spatial domain CSI prediction for CRI-based CSI reporting using the first set of measurements and the second set of measurements

[0328] 2. 1 and wherein the UE may receive one CSI-RS port subset indicator pattern, the received one CSI-RS port subset indicator pattern may be applied to all the configured CSI-RS resources

[0329] 3. 1 and wherein the UE may receive more than one CSI-RS port subset indicator pattern, each of the more than one CSI-RS port subset indicator patterns may be indicated for one of the configured CSI-RS resources

[0330] 4. 1 and 3, wherein the CSI-RS port subset indicator pattern may be indicated per CSI- RS resource within the indicated CSI-RS resource subset, and may be different for different CSI-RS resources.

[0331] 5. 1-4, and wherein the UE may receive assistance configuration associated with the training of the UE-sided AI / ML based spatial domain CSI prediction for CRI-based CSI reporting, where the assistance configuration may contain one or more of

[0332] a. One or more codebooks the UE may have to train AI / ML model for

[0333] b. Indication of specific CRIs that the UE may have to always predict CSI for, and / or indication of specific CRIs that the UE may not need to predict CSI for, and / or information of number of reported CRIs, note that the reporting of CSI may only be done during inference and this indication may be only used to facilitate the training of the AI / ML model with additional information of what may have to be reported during inference.

[0334] c. Information about how the TRP beams of the CSI-RS resources may be spatially related to each other

[0335] d. Configuration including a NW-sided additional condition ID, where the UE may assume that similar properties of one or more DL Tx beams and / or similar properties of one or more TXRU mappings / virtualizations for the configured CSI- RS resources / CSI-RS ports may be associated with the same NW-sided additional condition ID, which may be used both during training and inference.

[0336] 6. 1-5, and wherein the configured CSI-RS resources may be periodic CSI-RS resources or semi-persistent CSI-RS resources or aperiodic CSI-RS resources.Inference

[0337] 1. A Method in a UE for data collection for inference of a UE-sided AI / ML based spatial domain CSI prediction for CRI-based CSI reporting, the method comprising

[0338] a. Receiving a configuration of a set of two or more CSI-RS resources b. Receiving at least one of:

[0339] i. a CSI-RS resource subset indicator pattern

[0340] ii. one or more CSI-RS port subset indicator pattern(s) c. Perform a set of measurements on the CSI-RSs according to the at least one of the CSI-RS resource subset indicator patterns and one or more CSI-RS port subset indicator pattern(s)

[0341] d. Perform prediction of the CSI associated with the two or more configured CSI- RS resources based on the set of measurements

[0342] e. Report the predicted CSI

[0343] 2. 1 and wherein the UE may receive one CSI-RS port subset indicator pattern, the received one CSI-RS port subset indicator pattern may be applied to all the configured CSI-RS resources.

[0344] 3. 1 and wherein the UE may receive more than one CSI-RS port subset indicator pattern, each of the more than one CSI-RS port subset indicator patterns may be indicated for one of the configured CSI-RS resources.

[0345] 4. 1 and 3, wherein the CSI-RS port subset indicator pattern may be indicated per CSI- RS resource within the indicated CSI-RS resource subset, and may be different for different CSI-RS resources.

[0346] 5. All above and wherein the CSI-RS resource subset indicator pattern may vary for different time instances.

[0347] 6. All above and wherein the CSI-RS port subset indicator pattern(s) may vary for different time instances.

[0348] 7. 1 and wherein the UE may receive assistance configuration associated with the inference of the UE-sided AI / ML based spatial domain CSI prediction for CRI-based CSI reporting, wherein the assistance configuration may contain one or more of a. One or more codebooks the UE may have to train AI / ML model for

[0349] b. Information about how the TRP beams of the CSI-RS resources may be spatial related to each other

[0350] c. Indication of specific CRIs that the UE may have to always predict CSI for, and / or indication of specific CRIs that the UE may not need to predict CSI for, and / or information of number of reported CRIsd. Configuration including a NW-sided additional condition ID, where the UE may assume that similar properties of one or more DL Tx beams and / or similar properties of one or more TXRLI mappings / virtualizations for the configured CSI- RS resources / CSI-RS ports may be associated with the same NW-sided additional condition ID, which may be used both during training and inference.

[0351] Certain embodiments disclosed herein may provide one or more of the following technical advantage(s), which may be summarized as follows.

[0352] An advantage of embodiments herein may be understood to be that CSI-RS overhead may be reduced for hybrid beamforming architecture at TRPs, which may increase spectral efficiency in the system, since saved time / frequency resource may be used for data.

[0353] Figure 14 depicts an example of the arrangement that the first device 131 may comprise to perform the method actions described above in relation to Figure 7 and / or any of Figures 11-13.

[0354] Several embodiments are comprised herein. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the first device 131 and will thus not be repeated here. For example, the first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0355] The embodiments herein in the first device 131 may be implemented through one or more processors, such as a processing circuitry 1401 in the first device 131 depicted in Figure 14a, together with computer program code for performing the functions and actions of the embodiments herein. A processor, as used herein, may be understood to be a hardware component. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the first device 131. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the first device 131.

[0356] The first device 131 may further comprise a memory 1402 comprising one or more memory units. The memory 1402 is arranged to be used to store obtained information, storedata, configurations, schedulings, and applications etc. to perform the methods herein when being executed in the first device 131.

[0357] In some embodiments, the first device 131 may receive information from, e.g., the first network node 111 , the second network node 112, the third network node 113, the second device 132, or another structure in the communications system 100, through a receiving port 1403. In some embodiments, the receiving port 1403 may be, for example, connected to one or more antennas in first device 131. In other embodiments, the first device 131 may receive information from another structure in the communications system 100 through the receiving port 1403. Since the receiving port 1403 may be in communication with the processing circuitry 1401, the receiving port 1403 may then send the received information to the processing circuitry 1401. The receiving port 1403 may also be configured to receive other information.

[0358] The processing circuitry 1401 in the first device 131 may be further configured to transmit or send information to e.g., the first network node 111 , the second network node 112, the third network node 113, the second device 132, or another structure in the communications system 100, through a sending port 1404, which may be in communication with the processing circuitry 1401, and the memory 1402.

[0359] Those skilled in the art will also appreciate that the processing circuitry 1401 described above may comprise a combination of analog and digital modules, and / or one or more processors configured with software and / or firmware, e.g., stored in memory, that, when executed by the one or more processors such as the processing circuitry 1401, perform as described above. One or more of these processors, as well as the other digital hardware, may be included in a single Application-Specific Integrated Circuit (ASIC), or several processors and various digital hardware may be distributed among several separate components, whether individually packaged or assembled into a System-on-a-Chip (SoC).

[0360] The processing circuitry 1401 may be configured to, or operable to, perform the method actions according to Figure 7 and / or any of Figures 11-13.

[0361] Also, in some embodiments, the first device 131 may be configured to perform the actions of Figure 7 and / or any of Figures 11-13 with respective units that may be implemented as one or more applications running on one or more processors such as the processing circuitry 1401.

[0362] Thus, the methods according to the embodiments described herein for the first device 131 may be respectively implemented by means of a computer program 1405 product, comprising instructions, i.e. , software code portions, which, when executed on at least one processing circuitry 1401, cause the at least one processing circuitry 1401 to carry out the actions described herein, as performed by the first device 131. The computer program 1405 product may be stored on a computer-readable storage medium 1406. The computer-readable storage medium 1406, having stored thereon the computer program 1405, may comprise instructions which, when executed on at least one processing circuitry 1401, cause the at leastone processing circuitry 1401 to carry out the actions described herein, as performed by the first device 131. In some embodiments, the computer-readable storage medium 1406 may be a non-transitory computer-readable storage medium, such as a CD ROM disc, or a memory stick. In other embodiments, the computer program 1405 product may be stored on a carrier containing the computer program 1405 just described, wherein the carrier is one of an electronic signal, optical signal, radio signal, or the computer-readable storage medium 1406, as described above.

[0363] The first device 131 may comprise a communication interface configured to facilitate communications between the first device 131 and other nodes or devices, e.g., the first network node 111, the second network node 112, the third network node 113, the second device 132, or another structure in the communications system 100. The interface may, for example, include a transceiver configured to transmit and receive radio signals over an air interface in accordance with a suitable standard.

[0364] In other embodiments, the first device 131 may also comprise a radio circuitry 1407, which may comprise e.g., the receiving port 1403 and the sending port 1404. The radio circuitry 1407 may be configured to set up and maintain at least a wireless connection with the first network node 111 , the second network node 112, the third network node 113, the second device 132, or another structure in the communications system 100. Circuitry may be understood herein as a hardware component.

[0365] Hence, embodiments herein also relate to the first device 131 comprising the processing circuitry 1401 and the memory 1402, said memory 1402 containing instructions executable by said processing circuitry 1401, whereby the first device 131 is operative to perform the actions described herein in relation to the first device 131, e.g., in Figure 7 and / or any of Figures 11-13.

[0366] Figure 15 depicts an example of the arrangement that the second device 132 may comprise to perform the method actions described above in relation to Figure 8 and / or any of Figures 11-13.

[0367] Several embodiments are comprised herein. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the second device 132 and will thus not be repeated here. For example, the first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0368] The embodiments herein in the second device 132 may be implemented through one or more processors, such as a processing circuitry 1501 in the second device 132 depicted inFigure 15a, together with computer program code for performing the functions and actions of the embodiments herein. A processor, as used herein, may be understood to be a hardware component. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the second device 132. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the second device 132.

[0369] The second device 132 may further comprise a memory 1502 comprising one or more memory units. The memory 1502 is arranged to be used to store obtained information, store data, configurations, schedulings, and applications etc. to perform the methods herein when being executed in the second device 132.

[0370] In some embodiments, the second device 132 may receive information from, e.g., the first network node 111 , the second network node 112, the third network node 113, the first device 131, or another structure in the communications system 100, through a receiving port 1503. In some embodiments, the receiving port 1503 may be, for example, connected to one or more antennas in second device 132. In other embodiments, the second device 132 may receive information from another structure in the communications system 100 through the receiving port 1503. Since the receiving port 1503 may be in communication with the processing circuitry 1501, the receiving port 1503 may then send the received information to the processing circuitry 1501. The receiving port 1503 may also be configured to receive other information.

[0371] The processing circuitry 1501 in the second device 132 may be further configured to transmit or send information to e.g., the network node 111 , the second network node 112, the third network node 113, the first device 131 , or another structure in the communications system 100, through a sending port 1504, which may be in communication with the processing circuitry 1501, and the memory 1502.

[0372] Those skilled in the art will also appreciate that the processing circuitry 1501 described above may comprise a combination of analog and digital modules, and / or one or more processors configured with software and / or firmware, e.g., stored in memory, that, when executed by the one or more processors such as the processing circuitry 1501, perform as described above. One or more of these processors, as well as the other digital hardware, may be included in a single Application-Specific Integrated Circuit (ASIC), or several processors and various digital hardware may be distributed among several separate components, whether individually packaged or assembled into a System-on-a-Chip (SoC).

[0373] The processing circuitry 1501 may be configured to, or operable to, perform the method actions according to Figure 8 and / or any of Figures 11-13.Also, in some embodiments, the second device 132 may be configured to perform the actions of Figure 8 and / or any of Figures 11-13 with respective units that may be implemented as one or more applications running on one or more processors such as the processing circuitry 1501.

[0374] Thus, the methods according to the embodiments described herein for the second device 132 may be respectively implemented by means of a computer program 1505 product, comprising instructions, i.e. , software code portions, which, when executed on at least one processing circuitry 1501, cause the at least one processing circuitry 1501 to carry out the actions described herein, as performed by the second device 132. The computer program 1505 product may be stored on a computer-readable storage medium 1506. The computer-readable storage medium 1506, having stored thereon the computer program 1505, may comprise instructions which, when executed on at least one processing circuitry 1501, cause the at least one processing circuitry 1501 to carry out the actions described herein, as performed by the second device 132. In some embodiments, the computer-readable storage medium 1506 may be a non-transitory computer-readable storage medium, such as a CD ROM disc, or a memory stick. In other embodiments, the computer program 1505 product may be stored on a carrier containing the computer program 1505 just described, wherein the carrier is one of an electronic signal, optical signal, radio signal, or the computer-readable storage medium 1506, as described above.

[0375] The second device 132 may comprise a communication interface configured to facilitate communications between the second device 132 and other nodes or devices, e.g., the network node 111, the second network node 112, the third network node 113, the first device 131, or another structure in the communications system 100. The interface may, for example, include a transceiver configured to transmit and receive radio signals over an air interface in accordance with a suitable standard.

[0376] In other embodiments, the second device 132 may also comprise a radio circuitry 1507, which may comprise e.g., the receiving port 1503 and the sending port 1504. The radio circuitry 1507 may be configured to set up and maintain at least a wireless connection with the network node 111, the second network node 112, the third network node 113, the first device 131, or another structure in the communications system 100. Circuitry may be understood herein as a hardware component.

[0377] Hence, embodiments herein also relate to the second device 132 comprising the processing circuitry 1501 and the memory 1502, said memory 1502 containing instructions executable by said processing circuitry 1501, whereby the second device 132 is operative to perform the actions described herein in relation to the second device 132, e.g., in Figure 8 and / or any of Figures 11-13.Figure 16 depicts an example of the arrangement that the first network node 111 may comprise to perform the method actions described above in relation to Figure 9 and / or any of Figures 11-13.

[0378] Several embodiments are comprised herein. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the first network node 111 and will thus not be repeated here. For example, the first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0379] The embodiments herein in the first network node 111 may be implemented through one or more processors, such as a processing circuitry 1601 in the first network node 111 depicted in Figure 16a, together with computer program code for performing the functions and actions of the embodiments herein. A processor, as used herein, may be understood to be a hardware component. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the first network node 111. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the first network node 111.

[0380] The first network node 111 may further comprise a memory 1602 comprising one or more memory units. The memory 1602 is arranged to be used to store obtained information, store data, configurations, schedulings, and applications etc. to perform the methods herein when being executed in the first network node 111.

[0381] In some embodiments, the first network node 111 may receive information from, e.g., the second network node 112, the third network node 113, the first device 131, the second device 132, or another structure in the communications system 100, through a receiving port 1603. In some embodiments, the receiving port 1603 may be, for example, connected to one or more antennas in first network node 111. In other embodiments, the first network node 111 may receive information from another structure in the communications system 100 through the receiving port 1603. Since the receiving port 1603 may be in communication with the processing circuitry 1601, the receiving port 1603 may then send the received information to the processing circuitry 1601. The receiving port 1603 may also be configured to receive other information.

[0382] The processing circuitry 1601 in the first network node 111 may be further configured to transmit or send information to e.g., the second network node 112, the third network node 113, the first device 131, the second device 132, or another structure in the communications system100, through a sending port 1604, which may be in communication with the processing circuitry 1601, and the memory 1602.

[0383] Those skilled in the art will also appreciate that the processing circuitry 1601 described above may comprise a combination of analog and digital modules, and / or one or more processors configured with software and / or firmware, e.g., stored in memory, that, when executed by the one or more processors such as the processing circuitry 1601, perform as described above. One or more of these processors, as well as the other digital hardware, may be included in a single Application-Specific Integrated Circuit (ASIC), or several processors and various digital hardware may be distributed among several separate components, whether individually packaged or assembled into a System-on-a-Chip (SoC).

[0384] The processing circuitry 1601 may be configured to, or operable to, perform the method actions according to Figure 9 and / or any of Figures 11-13.

[0385] Also, in some embodiments, the first network node 111 may be configured to perform the actions of Figure 9 and / or any of Figures 11-13 with respective units that may be implemented as one or more applications running on one or more processors such as the processing circuitry 1601.

[0386] Thus, the methods according to the embodiments described herein for the first network node 111 may be respectively implemented by means of a computer program 1605 product, comprising instructions, i.e. , software code portions, which, when executed on at least one processing circuitry 1601, cause the at least one processing circuitry 1601 to carry out the actions described herein, as performed by the first network node 111. The computer program 1605 product may be stored on a computer-readable storage medium 1606. The computer-readable storage medium 1606, having stored thereon the computer program 1605, may comprise instructions which, when executed on at least one processing circuitry 1601, cause the at least one processing circuitry 1601 to carry out the actions described herein, as performed by the first network node 111. In some embodiments, the computer-readable storage medium 1606 may be a non-transitory computer-readable storage medium, such as a CD ROM disc, or a memory stick. In other embodiments, the computer program 1605 product may be stored on a carrier containing the computer program 1605 just described, wherein the carrier is one of an electronic signal, optical signal, radio signal, or the computer-readable storage medium 1606, as described above.

[0387] The first network node 111 may comprise a communication interface configured to facilitate communications between the first network node 111 and other nodes or devices, e.g., the second network node 112, the third network node 113, the first device 131, the second device 132, or another structure in the communications system 100. The interface may, for example, include a transceiver configured to transmit and receive radio signals over an air interface in accordance with a suitable standard.In other embodiments, the first network node 111 may also comprise a radio circuitry 1607, which may comprise e.g., the receiving port 1603 and the sending port 1604. The radio circuitry 1607 may be configured to set up and maintain at least a wireless connection with the second network node 112, the third network node 113, the first device 131, the second device 132, or another structure in the communications system 100. Circuitry may be understood herein as a hardware component.

[0388] Hence, embodiments herein also relate to the first network node 111 comprising the processing circuitry 1601 and the memory 1602, said memory 1602 containing instructions executable by said processing circuitry 1601, whereby the first network node 111 is operative to perform the actions described herein in relation to the first network node 111, e.g., in Figure 9 and / or any of Figures 11-13.

[0389] Figure 17 depicts an example of the arrangement that the second network node 112 may comprise to perform the method actions described above in relation to Figure 10 and / or any of Figures 11-13.

[0390] Several embodiments are comprised herein. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the second network node 112 and will thus not be repeated here. For example, the first indication may be also referred to herein as a Channel State Information Reference Signal (CSI-RS) resource subset indicator pattern. The second indication may be also referred to herein as one or more CSI-RS port subset indicator patterns.

[0391] The embodiments herein in the second network node 112 may be implemented through one or more processors, such as a processing circuitry 1701 in the second network node 112 depicted in Figure 17a, together with computer program code for performing the functions and actions of the embodiments herein. A processor, as used herein, may be understood to be a hardware component. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the second network node 112. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the second network node 112.

[0392] The second network node 112 may further comprise a memory 1702 comprising one or more memory units. The memory 1702 is arranged to be used to store obtained information, store data, configurations, schedulings, and applications etc. to perform the methods herein when being executed in the second network node 112.In some embodiments, the second network node 112 may receive information from, e.g., the first network node 111 , the third network node 113, the first device 131 , the second device 132, or another structure in the communications system 100, through a receiving port 1703. In some embodiments, the receiving port 1703 may be, for example, connected to one or more antennas in second network node 112. In other embodiments, the second network node 112 may receive information from another structure in the communications system 100 through the receiving port 1703. Since the receiving port 1703 may be in communication with the processing circuitry 1701, the receiving port 1703 may then send the received information to the processing circuitry 1701. The receiving port 1703 may also be configured to receive other information.

[0393] The processing circuitry 1701 in the second network node 112 may be further configured to transmit or send information to e.g., the first network node 111, the third network node 113, the first device 131, the second device 132, or another structure in the communications system 100, through a sending port 1704, which may be in communication with the processing circuitry 1701, and the memory 1702.

[0394] Those skilled in the art will also appreciate that the processing circuitry 1701 described above may comprise a combination of analog and digital modules, and / or one or more processors configured with software and / or firmware, e.g., stored in memory, that, when executed by the one or more processors such as the processing circuitry 1701, perform as described above. One or more of these processors, as well as the other digital hardware, may be included in a single Application-Specific Integrated Circuit (ASIC), or several processors and various digital hardware may be distributed among several separate components, whether individually packaged or assembled into a System-on-a-Chip (SoC).

[0395] The processing circuitry 1701 may be configured to, or operable to, perform the method actions according to Figure 10 and / or any of Figures 11-13.

[0396] Also, in some embodiments, the second network node 112 may be configured to perform the actions of Figure 10 and / or any of Figures 11-13 with respective units that may be implemented as one or more applications running on one or more processors such as the processing circuitry 1701.

[0397] Thus, the methods according to the embodiments described herein for the second network node 112 may be respectively implemented by means of a computer program 1705 product, comprising instructions, i.e. , software code portions, which, when executed on at least one processing circuitry 1701, cause the at least one processing circuitry 1701 to carry out the actions described herein, as performed by the second network node 112. The computer program 1705 product may be stored on a computer-readable storage medium 1706. The computer-readable storage medium 1706, having stored thereon the computer program 1705, may comprise instructions which, when executed on at least one processing circuitry 1701, cause the at least one processing circuitry 1701 to carry out the actions described herein, asperformed by the second network node 112. In some embodiments, the computer-readable storage medium 1706 may be a non-transitory computer-readable storage medium, such as a CD ROM disc, or a memory stick. In other embodiments, the computer program 1705 product may be stored on a carrier containing the computer program 1705 just described, wherein the carrier is one of an electronic signal, optical signal, radio signal, or the computer-readable storage medium 1706, as described above.

[0398] The second network node 112 may comprise a communication interface configured to facilitate communications between the second network node 112 and other nodes or devices, e.g., the first network node 111, the third network node 113, the first device 131, the second device 132, or another structure in the communications system 100. The interface may, for example, include a transceiver configured to transmit and receive radio signals over an air interface in accordance with a suitable standard.

[0399] In other embodiments, the second network node 112 may also comprise a radio circuitry 1707, which may comprise e.g., the receiving port 1703 and the sending port 1704. The radio circuitry 1707 may be configured to set up and maintain at least a wireless connection with the first network node 111, the third network node 113, the first device 131, the second device 132, or another structure in the communications system 100. Circuitry may be understood herein as a hardware component.

[0400] Hence, embodiments herein also relate to the second network node 112 comprising the processing circuitry 1701 and the memory 1702, said memory 1702 containing instructions executable by said processing circuitry 1701, whereby the second network node 112 is operative to perform the actions described herein in relation to the second network node 112, e.g., in Figure 10 and / or any of Figures 11-13.

[0401] Generally, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is clearly given and / or is implied from the context in which it is used. All references to a / an / the element, apparatus, component, means, step, etc. are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and / or where it is implicit that a step must follow or precede another step. Any feature of any of the embodiments disclosed herein may be applied to any other embodiment, wherever appropriate. Likewise, any advantage of any of the embodiments may apply to any other embodiments, and vice versa. Other objectives, features and advantages of the enclosed embodiments will be apparent from the following description.As used herein, the expression “at least one of:” followed by a list of alternatives separated by commas, and wherein the last alternative is preceded by the “and” term, may be understood to mean that only one of the list of alternatives may apply, more than one of the list of alternatives may apply or all of the list of alternatives may apply. This expression may be understood to be equivalent to the expression “at least one of:” followed by a list of alternatives separated by commas, and wherein the last alternative is preceded by the “or” term.

[0402] Further Extensions And Variations

[0403] Figure 18 shows an example of a communication system 1800 in accordance with some embodiments.

[0404] In the example, the communication system 1800, such as the communications system 100, includes a telecommunications network 1802 that includes an access network 1804, such as a radio access network (RAN), and a core network 1806, which includes one or more core network nodes 1808, such as the second network node 112, in some examples. The access network 1804 includes one or more access network nodes or base stations of various types, such as any of the first network node 111, the second network node 112 and the third network node 113 in some examples. For example, access network nodes 1810A and 1810B are depicted (which may be collectively referred to as network nodes 1810), or any other similar 3rdGeneration Partnership Project (3GPP) access nodes or non-3GPP access points (APs). Some embodiments of the access network 1804 may include more than one access network technology. The network nodes 1810 of access network 1804 facilitate direct or indirect connection of wireless devices, also referred to as user equipments (UEs), e.g., any of the first device 131 and the second device 132, such as by connecting UEs 1812A, 1812B, 1812C, and 1812D (one or more of which may be generally referred to as UEs 1812) to the core network 1806 over one or more wireless connections. Any of the UEs 1812A, 1812B, 1812C, and 1812D are examples of any of the first device 131 and the second device 132.

[0405] Moreover, a network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunications network 1802 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a network node in the telecommunications network 1802 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other network nodes to implement one or more functionalities of any network node in thetelecommunications network 1802, including one or more access network nodes 1810 and / or core network nodes 1808.

[0406] Examples of an ORAN network node include an open radio unit (0-Rll), an open distributed unit (O-DU), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-Cll user plane (O-CU-UP), a RAN intelligent controller (near-real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). An ORAN network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an A1, F1, W1, E1, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN network node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the O-RAN Alliance or comparable technologies.

[0407] The network nodes 1810, e.g., any of the first network node 111, the second network node 112 and the third network node 113, facilitate direct or indirect connection of one or more UEs 1812, e.g., any of the first device 131 and the second device 132, to the core network 1806 over one or more wireless connections. Example wireless communications over a wireless connection include transmitting and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system 1800 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that may facilitate or participate in the communication of data and / or signals whether via wired or wireless connections. The communication system 1800 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0408] The UEs 1812, e.g., any of the first device 131 and the second device 132, may be any of a wide variety of communication devices, including wireless devices arranged, configured, and / or operable to communicate wirelessly with the network nodes 1810 and other communication devices. Similarly, the network nodes 1808, 1810, e.g., any of the first network node 111, the second network node 112 and the third network node 113, are arranged, capable, configured, and / or operable to communicate directly or indirectly (e.g., via other devices of telecommunications network 1802) with the UEs 1812 and / or with other network nodes or equipment in the telecommunications network 1802 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in thetelecommunications network 1802. More specifically, UEs 1812 may send messages, data, and / or other signals to network nodes 1808, 1810 or other elements of the telecommunications network 1802 by transmitting such signals to the relevant device directly without the signals passing through any intervening devices or by transmitting such signals to the relevant device indirectly through an intervening device (or multiple intervening devices) that then transmit the signal to the relevant device. Similarly, network nodes 1808, 1810 may send messages, data, and other signals to UEs 18122, other network nodes 1808, 1810, and other devices in telecommunications network 1802 directly or indirectly. As one specific example, a core network node 108 may transmit a particular message to a UE 1812 by transmitting the message to an access network node 1810 that will then transmit the message to the intended UE 1812. Similarly, a core network node 108 may receive a particular message from a UE 1812 by receiving the message from an access network node 1810 that itself received the message from the UE 1812.

[0409] In the depicted example, the core network 1806 connects elements of the access network 1804 (e.g., one or more of the network nodes 1810) to one or more host computing systems, such as host 1816. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network 1806 includes one or more core network nodes (e.g., core network node 1808) of various types, one or more of which may be generally referred to as network nodes 1808. Network nodes 1808 are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, access network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node 1808. Example core network nodes provide functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier Deconcealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0410] The host 1816 may be under the ownership or control of a service provider other than an operator or provider of the access network 1804 and / or the telecommunications network 1802. The host 1816 may be operated by the service provider or on behalf of the service provider. The host 1816 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded audio / video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.As a whole, the communication system 1800 of Figure 18 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system 1800 may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (Wi-Fi); and / or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (Wi-Max), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, Li-Fi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox. Moreover, the communication system 1800 may be configured to support multiple different standards, protocols, or other rule sets, with individual components supporting all of the relevant rule sets or with different components or sub-systems within the communication system 1800 supporting different standards, protocols, or rule sets.

[0411] As one example, in certain embodiments, access network 1804 may contain some access network nodes 1810 that support 3GPP radio access technologies (RAT), such as LTE or NR, while other access network nodes 1810 support (or the same access network nodes 1810 additionally support) non-3GPP RATs, such as Wi-Fi or a proprietary RAT. As another example, telecommunications network 1802 may support multiple generations of related communication standards (e.g., 4G and 5G 3GPP communication standards) and, as a result, may include an access network 104 and / or a core network 106 that supports multiple different standard generations or may include multiple access networks 104 and / or multiple core networks 106 with individual networks 104, 106 supporting different standard generations.

[0412] Telecommunications network 1802 may support network slicing to provide different logical networks to different devices that are connected to the telecommunications network 1802. For example, the telecommunications network 1802 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing Enhanced Mobile Broadband (eMBB) services to other UEs, and / or Massive Machine Type Communication (mMTC) / Massive loT services to yet further UEs.

[0413] In some examples, one or more of the UEs 1812 are configured to transmit and / or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network 1804 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 1804. Additionally, a UE may be configured for operating in single- or multi-RAT or multi-standard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LTE, i.e. being configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network) New Radio - Dual Connectivity (EN-DC).In the example, the hub 1814 communicates with the access network 1804 to facilitate indirect communication between one or more UEs (e.g., UE 1812C and / or 1812D) and network nodes (e.g., network node 1810B). In some examples, the hub 1814 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 1814 may be a broadband router enabling access to the core network 1806 for the UEs. As another example, the hub 1814 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes 1810, or by executable code, script, process, or other instructions in the hub 1814.

[0414] As another example, the hub 1814 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub 1814 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub 1814 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 1814 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 1814 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0415] The hub 1814 may have a constant / persistent or intermittent connection to the network node 181 OB. The hub 1814 may also allow for a different communication scheme and / or schedule between the hub 1814 and UEs (e.g., UE 1812C and / or 1812D), and between the hub 1814 and the core network 1806. In other examples, the hub 1814 is connected to the core network 1806 and / or one or more UEs via a wired connection. Moreover, the hub 1814 may be configured to connect to an M2M service provider over the access network 1804 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 1810 while still connected via the hub 1814 via a wired or wireless connection. In some embodiments, the hub 1814 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node 1810B. In other embodiments, the hub 1814 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node 1810B, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0416] Figure 19 is another example of a communication system 1900, such as the wireless communications network 100, according to some embodiments. As used herein, the communication system 1900 includes multiple access points (APs) 1910 (with four exemplary APs 1910A, 1910B, 1910C, and 1910D being depicted), such as any of the first network node 111, the second network node 112 and the third network node 113, and multiple wireless devices, referred to in the context of communication system 1900 as stations (STAs) 1912 (referred toindividually as STA 1912A, STA 1912B, STA 1912C, STA 1912D, and STA 1912E), such as e.g., any of the first device 131 and the second device 132. STA 1912A is served by AP 1910A in a first basic service set (BSS) 1920A. STA 191 OB and STA 1910C are served by AP 191 OB in a second BSS, BSS 1920B. STA 1912D is served by AP 1910C in a third BSS, BSS 1920C. STA 1912E is served by AP 1910D in a fourth BSS, BSS 1920D. Stations 1912 may be non-AP STAs and correspond to various kinds of wireless devices, for example, user terminals, such as mobile or stationary computing devices like smartphones, laptop computers, desktop computers, tablet computers, gaming devices, head-mounted displays (HMDs) for Augmented Reality (AR) or Virtual Reality (VR), or the like. Further, stations 1912 could, for example, correspond to other kinds of equipment like smart home devices, printers, multimedia devices, data storage devices, or the like.

[0417] Each of STAs 1912 may connect through a radio link to one of APs 1910. For example, depending on location or channel conditions experienced by a given STA 1912, the STA may select an appropriate AP and BSS for establishing the radio link. The radio link may be based on one or more orthogonal frequency-division multiplexing (OFDM) carriers from a frequency spectrum that is shared on the basis of a contention-based mechanism, e.g., an unlicensed or license exempt band like 2.4 GHz Industrial, Scientific, and Medical (ISM) band, the 5 GHz band, the 6 GHz band, or the 60 GHz band.

[0418] Each AP 1910 may provide data connectivity to STAs 1912 connected to a particular AP 1910. As illustrated, APs 1910 may be connected to a data network 1930. In this way, APs 1910 may also provide data connectivity between STAs 1912 and other entities, e.g., to one or more servers, service providers, data sources, data sinks, user terminals, or the like. Accordingly, the radio link established between a given STA 1912 and its serving AP 1910 may be used for providing various kinds of services to STA 1912, e.g., a voice service, a multimedia service, or other data service. Such services may be based on applications that are executed on STA 1912 and / or on a device linked to STA 1912. By way of example, Figure 19 illustrates an application service platform 1932 provided in data network 1930. The application(s) executed on STA 1912 and / or on one or more other devices linked to STA 1912 may use the radio link for data communication with one or more other STA 1912 and / or the application service platform 1932, thereby enabling utilization of the corresponding service(s) at STA 1912.

[0419] Figure 20 shows a wireless device 2000, such as any of the first device 131 and the second device 132, which may be configured to operate in communication system 1800 of Figure 18 or in communication system 1900 of Figure 190. The wireless device 2000 may be alternatively referred to as a UE 2000, like a UE 1812 within the context of communication system 1800, or as a station (STA) 2000 or as a non-access-point station (non-AP STA) 2000, like a STA 1912 within the context of the communication system 1900, in accordance with respective embodiments. As used herein, a wireless device refers to a device capable, configured, arranged and / or operableto communicate wirelessly with network nodes and / or other wireless devices. Examples of a wireless device include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage device, playback appliance, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), smart device, wireless customer-premise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, and wireless terminal. Other examples include any type of UE identified by the 3rd Generation Partnership Project (3GPP), including a narrow band internet of things (NB-loT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0420] A wireless device 2000 may support device-to-device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to-everything (V2X). In other examples, wireless device 2000 may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, wireless device 2000 may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, wireless device 2000 may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0421] In particular embodiments, wireless device 2000 includes processing circuitry 2002 that is operatively coupled via a bus 2004 to an input / output interface 2006, a power source 2008, a memory 2010, a communication interface 2012, and / or any other component, or any combination thereof. Certain embodiments of wireless device 2000 may include all or a subset of the components shown in Figure 20. The level of integration between the components may vary from one embodiment of wireless device 2000 to another. In general, in a particular embodiment of wireless device 2000, processing circuitry 2002, input / output interface 2006, power source 2008, memory 2010, and communication interface 2012 may, in whole or in part, represent or include physical components common to or shared by one or more of the other elements of wireless device 2000. Further, certain embodiments of wireless devices 2000 may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0422] The processing circuitry 2002 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory 2010. The processing circuitry 2002 may be implemented as one or more hardware-implemented state machines (e.g., in discrete logic, field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.);programmable logic together with appropriate firmware; one or more stored computer programs, general-purpose processors, such as a microprocessor or digital signal processor (DSP), together with appropriate software; or any combination of the above. For example, the processing circuitry 2002 may include multiple central processing units (CPUs).

[0423] In the example, the input / output interface 2006 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into wireless device 2000. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g., a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presencesensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0424] In some embodiments, the power source 2008 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricity outlet), photovoltaic device, or power cell, may be used to supply power to circuitry or to charge an associated battery. The power source 2008 may further include power circuitry for delivering power from the power source 2008 itself, and / or an external power source, to the various parts of wireless device 2000 via input circuitry or an interface such as an electrical power cable. Power source 2008 may perform any formatting, converting, or other modification to make accessible power suitable for the respective components of the wireless device 2000 to which power is supplied.

[0425] The memory 2010 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 2010 includes one or more programs 2014, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 2016. The memory 2010 may store, for use by wireless device 2000, any of a variety of various operating systems or combinations of operating systems.

[0426] The memory 2010 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD-DVD) optical discdrive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (IIICC) including one or more subscriber identity modules (SIMs), such as a IISIM and / or ISIM, other memory, or any combination thereof. The IIICC may for example be an embedded IIICC (elllCC), integrated IIICC (illlCC) or a removable IIICC commonly known as ‘SIM card.’ The memory 2010 may allow wireless device 2000 to access instructions, programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory 2010, which may be or comprise a device-readable storage medium.

[0427] The processing circuitry 2002 may be configured to communicate with an access network or other network via or using the communication interface 2012. The communication interface 2012 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 2022. The communication interface 2012 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another wireless device ora network node in an access network). Each transceiver may include a transmitter 2018 and / or a receiver 2020 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 2018 and receiver 2020 may be coupled to one or more antennas (e.g., antenna 2022) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0428] In the illustrated embodiment, communication functions of the communication interface 2012 may include cellular communication, Wi-Fi communication (e.g., according to an IEEE 802.11 family standard), LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / internet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0429] In particular embodiments, wireless device 2000 may provide an output of data captured via a sensor, through its communication interface 2012, via a wireless connection to a network node, and / or in any appropriate manner. Data captured by sensors of a wireless device 2000 canbe communicated through a wireless connection to a network node via another wireless device 2000. In particular embodiments, such output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0430] As another example, wireless device 2000 comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, wireless device 2000 may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0431] Wireless device 2000, when in the form of an Internet of Things (loT) device, may be a device for use in one or more application domains, these domains comprising, but not limited to, wearable technology, extended industrial application and healthcare. Non-limiting examples of such an loT device are a device which is or which is embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smartwatch, a fitness tracker, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. In particular embodiments, wireless device 2000 represents an loT device that comprises circuitry and / or software in dependence of the intended application of the loT device in addition to other components as described in relation to the example embodiment of wireless device 2000 shown in Figure 20.

[0432] As yet another specific example, in an loT scenario, wireless device 2000 may represent a machine or other device that performs monitoring and / or measurements, and transmits the results of such monitoring and / or measurements to another wireless device and / or a network node. Wireless device 2000 may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, wireless device 2000 may implement the 3GPP NB-loT standard. In other scenarios, wireless device 2000 may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.In practice, any number of wireless devices 2000 may be used together with respect to a single use case. For example, a first wireless device 2000 might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second wireless device 2000 that is a remote controller operating the drone. When a user makes changes from the remote controller, the first wireless device 2000 may adjust the throttle on the drone (e.g. by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second wireless device 2000 can also include more than one of the functionalities described above. For example, wireless device 2000 might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.

[0433] Figure 21 shows a network node 2100, such as any of the first network node 111, the second network node 112 and the third network node 113, in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunications network. In accordance with respective embodiments, network node 2100 may be configured to operate in communication system 1800 of Figure 18, like network nodes 1808 or 1810, or in communication system 1900 of Figure 19, like an AP 1910 or a station 1912. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e.g., O-RU, O-DU, O-CU).

[0434] Network nodes 2100 may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. Network node 2100 may be a relay node or a relay donor node controlling a relay. Network nodes 2100 may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node) and / or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0435] Other examples of network nodes 2100 include multiple transmission point (multi-TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).In particular embodiments, network node 2100 includes a processing circuitry 2102, a memory 2104, a communication interface 2106, and a power source 2108. In general, in a particular embodiment of network node 2100, processing circuitry 2102, memory 2104, communication interface 2106, and power source 2108 may, in whole or in part, represent or include physical components common to or shared by one or more of the other elements of network node 2100.

[0436] The network node 2100 may be composed of multiple distinct network entities (e.g., a NodeB entity and a RNC entity, or a BTS entity and a BSC entity, etc.), which may each have or utilize their own respective physical components. In certain scenarios in which the network node 2100 comprises multiple such entities (e.g., BTS and BSC), one or more of the separate entities may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, the network node 2100 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memories 2104 or portions of memory 2104 for different RATs) and some components may be reused (e.g., a same antenna 2110 may be shared by different RATs). The network node 2100 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 2100, for example GSM, WCDMA, LTE, NR, Wi-Fi (e.g., according to an IEEE 802.11 family standard), Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node 2100.

[0437] The processing circuitry 2102 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other components, such as the memory 2104, to provide network node 2100 functionality.

[0438] In some embodiments, the processing circuitry 2102 includes a system on a chip (SOC). In some embodiments, the processing circuitry 2102 includes one or more of radio frequency (RF) transceiver circuitry 2112 and baseband processing circuitry 2114. In some embodiments, the RF transceiver circuitry 2112 and the baseband processing circuitry 2114 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry 2112 and baseband processing circuitry 2114 may be on the same chip or set of chips, boards, or units.

[0439] The memory 2104 may comprise any form of volatile or non-volatile computer-readable memory including, without limitation, persistent storage, solid-state memory, remotely mountedmemory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry 2102. The memory 2104 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and / or other instructions capable of being executed by the processing circuitry 2102 and utilized by the network node 2100. The memory 2104 may be used to store any calculations made by the processing circuitry 2102 and / or any data received via the communication interface 2106. In some embodiments, the processing circuitry 2102 and memory 2104 is integrated.

[0440] The communication interface 2106 is used in wired or wireless communication of signaling and / or data with UEs, other network nodes, and / or any other network equipment. In the illustrated embodiment, communication interface 2106 comprises port(s) / terminal(s) 2116 to send and receive data, for example to and from a network over a wired connection. In particular embodiments, network node 2000 may be capable of wireless communication and communication interface 2106 may also include radio front-end circuitry 2118 that may be coupled to, or in certain embodiments a part of, an antenna 2110. Particular embodiments of radio frontend circuitry 2118 include filter(s) 2120 and amplifier(s) 2122. The radio front-end circuitry 2118 may be connected to an antenna 2110 and processing circuitry 2102. The radio front-end circuitry may be configured to condition signals communicated between antenna 2110 and processing circuitry 2102. The radio front-end circuitry 2118 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry 2118 may convert the digital data into a radio signal(s) having the appropriate channel and bandwidth parameters using a combination of filters 2120 and / or amplifiers 2122. The radio signal(s) may then be transmitted via the antenna 2110. Similarly, when receiving data, the antenna 2110 may collect radio signals which are then converted into digital data by the radio front-end circuitry 2118. The digital data may be passed to the processing circuitry 2102. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0441] In certain alternative embodiments, network node 2100 may be capable of wireless communication but does not include separate radio front-end circuitry 2118, instead, the processing circuitry 2102 includes radio front-end circuitry and is connected to the antenna 2110. Similarly, in some embodiments, all or some of the RF transceiver circuitry 2112 is part of the communication interface 2106. In still other embodiments, the communication interface 2106 includes one or more ports or terminals 2116, the radio front-end circuitry 2118, and the RF transceiver circuitry 2112, as part of a radio unit (not shown), and the communication interface2106 communicates with the baseband processing circuitry 2114, which is part of a digital unit (not shown).

[0442] The antenna 2110 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 2110 may be coupled to the radio front-end circuitry 2118 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 2110 is separate from the network node 2100 and connectable to the network node 2100 through one or more interfaces or ports.

[0443] The antenna 2110, communication interface 2106, and / or the processing circuitry 2102 may be configured to perform some or all of the receiving operations and / or obtaining operations described herein as being performed by the network node 2100. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna 2110, the communication interface 2106, and / or the processing circuitry 2102 may be configured to perform some or all of the transmitting or sending operations described herein as being performed by the network node 2100. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0444] The power source 2108 provides power to the various components of network node 2100 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 2108 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 2100 with power for performing the functionality described herein. For example, the network node 2100 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 2108. As a further example, the power source 2108 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.

[0445] Embodiments of the network node 2100 may include additional components beyond those shown in Figure 21 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node 2100 may include user interface equipment to allow input of information into the network node 2100 and to allow output of information from the network node 2100. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 2100.

[0446] Figure 22 is a block diagram illustrating a virtualization environment 2200 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can beapplied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments 2200 hosted by one or more of hardware nodes, such as a hardware computing device that operates as an access network node, UE, core network node, or host. Further, in embodiments in which a virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment 2200 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an O-2 interface.

[0447] Applications 2202 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0448] Hardware 2204 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers 2206 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VM 2208A and VM 2208B (which may be collectively referred to as VMs 2208), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 2206 may present a virtual operating platform that appears like networking hardware to one or more of the VMs 2208.

[0449] The VMs 2208 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by virtualization layer 2206. Different embodiments of the instance of a virtual appliance 2202 may be implemented on one or more of VMs 2208, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.

[0450] In the context of NFV, each of the VMs 2208 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 2208, and that part of hardware 2204 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more of the VMs 2208 on top of the hardware 2204 and corresponds to an application 2202.Hardware 2204 may be implemented in a standalone network node with generic or specific components. Hardware 2204 may implement some functions via virtualization. Alternatively, hardware 2204 may be part of a larger cluster of hardware (e.g. such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration 2210, which, among others, oversees lifecycle management of applications 2202. In some embodiments, hardware 2204 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system 2212 which may alternatively be used for communication between hardware nodes and radio units.

[0451] Although the computing devices described herein (e.g., UEs, network nodes, hosts) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions and methods disclosed herein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.

[0452] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particularembodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by.

Claims

Claims:

1. A computer-implemented method performed by a first device (131), the method being for handling Channel State Information Reference Signals, CSI-RSs, the first device (131) operating in a communications system (100), the method comprising:- obtaining (704) a first set of measurements on CSI-RSs transmitted by a first network node (111) operating in the communications system (100), wherein the first set of measurements has been performed according to one or more of:i. a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), andii. a second indication of one or more second subsets of one or more CSI- RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), e.g., a first CSI-RS resource of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131).

2. The method according to claim 1, further comprising:- obtaining (705) a second set of measurements on the CSI-RSs transmitted by the first network node (111), wherein the second set of measurements has been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

3. The method according to claim 2, further comprising:- sending (706), to the first network node (111), or to a second network node (112) operating in the communications system (100), one or more of:i. a third indication of the first set of measurements, andii. a fourth indication of the second set of measurements.

4. The method according to claim 2, further comprising one or more of:training (707) a machine learning model, MLM, with the obtained first set of measurements and the second set of measurements, to predict a fifth indicationof a Channel State Information, CSI, of a channel between the first device (131) and the first network node (111) based on one of the first subset of the first set of two or more CSI-RS resources and the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources, and- initiating (708) outputting a sixth indication of the trained MLM.

5. The method according to any of claims 2-4, wherein the first set of measurements is a subset of the second set of measurements.

6. The method according to any of claims 1-5, wherein the method further comprises:- obtaining (701) a first configuration of the first set of two or more CSI-RS resources,- obtaining (702) the one or more of:i. the first indication of the first subset of the first set of two or more CSI-RS resources, andii. the second indication of the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources,wherein the obtaining (704) of the first set of measurements comprises performing the first set of measurements and wherein the obtaining (705) of the second set of measurements comprises performing the second set of measurements.

7. The method according to claim 6, wherein the first device (131) obtains one second subset of the one or more CSI-RS ports, and wherein the obtained one second subset of the one or more CSI-RS ports is applied to all the configured CSI-RS resources in the first set of the two or more CSI-RS resources.

8. The method according to claim 6, wherein the first device (131) obtains more than one second subset of the one or more CSI-RS ports, and wherein each of the more than one second subset of the one or more CSI-RS ports is indicated for one of the configured CSI-RS resources in the first set.

9. The method according to claims 1 and 8, wherein the second subset of the one or more CSI-RS ports is indicated per CSI-RS resource within the indicated first subset of the firt set of two or more CSI-RS resources.

10. The method according to any of claims 4-5, further comprising:- obtaining (703) first information to be used for the training of the MLM, the first information comprising one or more of:i. one or more codebooks the first device (131) is to train the MLM to predict with,ii. a seventh indication of specific CSI Resource Indicators, CRIs, that the first device (131) is to train the MLM to always predict CSI for,iii. a eighth indication of specific CRIs that the first device (131) is to refrain from training the MLM to predict CSI for,iv. second information of a number of reported CRIs,v. third information indicating how one or more beams of the CSI-RS resources, transmitted by the first network node (111), are spatially related to each other, andvi. a second configuration comprising an ninth indication of a condition indicating similar properties are shared by:a) one or more downlink transmission beams,b) one or more transmit radio unit mappings for the configured CSI- RS resources, CSI-RS ports or both,c) one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both.

11. The method according to any of claims 1-10, wherein the configured CSI-RS resources are one of: periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

12. A first device for handling Channel State Information Reference Signals, CSI-RSs, the first device operating in a communications system, the first device comprising a processing circuitry configured to:obtain a first set of measurements on CSI-RSs transmitted by a first network node operating in the communications system, wherein the first set of measurements has been performed according to one or more of:i. a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, anda second indication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device.

13. The first device according to claim 12, wherein the processing circuitry is further configured to perform any of the method steps of claims 2-11.

14. A computer-implemented method performed by a second device (132), the method being for handling Channel State Information Reference Signals, CSI-RSs, the second device (132) operating in a communications system (100), the method comprising:- obtaining (802) a third configuration of a second set of two or more first CSI-RS resources,- obtaining (803) one or more of:i. a tenth indication of a third subset of the second set of two or more Channel State Information Reference Signal, CSI-RS, resources, andii. an eleventh indication of one or more fourth subsets of one or more CSI- RS ports of a second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device (132),performing (805) a third set of measurements on CSI-RSs transmitted by a third network node (113) operating in the communications system (100), wherein the third set of measurements is performed according to one or more of:i. the tenth indication, andii. the eleventh indication,- predicting (806), using the performed third set of measurements as input to a trained machine learning model, MLM, a twelfth indication of a Channel State Information, CSI, of a channel between the second device (132) and the third network node (113) based on the third subset and the one or more fourth subsets, and- initiating (807) outputting a thirteenth indication of the twelfth indication.

15. The method according to claim 14, wherein the method further comprises:- obtaining (801) the trained MLM, e.g., from a first device (131) or a second network node (112) operating in the communications network (100).

16. The method according to any of claims 14-15, wherein the second device (132) obtains one fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device (132), and wherein the obtained one fourth subset is applied to all the configured first CSI-RS resources.

17. The method according to any of claims 14-16, wherein the second device (132) obtains more than one fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device (132), and wherein each of the more than one fourth subset is indicated for one of the configured first CSI-RS resources.

18. The method according to claims 14 and 17, wherein a respective fourth subset of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources is indicated per first CSI-RS resource within the indicated third subset of the second set of two or more CSI-RS resources.

19. The method according to any of claims 14-18, wherein the third subset of the second set of two or more CSI-RS resources varies for different time instances.

20. The method according to any of claims 14-19, wherein the one or more fourth subsets of the one or more CSI-RS ports of the second CSI-RS resource of the second set of two or more CSI-RS resources vary for different time instances.

21. The method according to any of claims 14-20, further comprising:- obtaining (804) fourth information to be used for the predicting (806), the fourth information comprising one or more of:i. one or more first codebooks the second device (132) is to use for the predicting (806),ii. sixth information indicating how one or more first beams of the first CSI- RS resources, transmitted by the third network node (113), are spatially related to each other,iii. a fourteenth indication of specific Channel State Information, CSI, Resource Indicators, CRIs, that the second device (132) is to predict CSI for,iv. a fifteenth indication of specific CRIs that the second device (132) is to refrain from predicting CSI for,v. seventh information of a number of reported CRIs,vi. a fourth configuration comprising a sixteenth indication of a first condition indicating similar properties are shared by:a) one or more first downlink transmission beams,b) one or more first transmission radio unit one or more transmission radio unit mappings for the configured first CSI-RS resources, first CSI-RS ports or both, andc) one or more first transmission radio unit virtualizations for the configured first CSI-RS resources, first CSI-RS ports or both.

22. The method according to any of claims 14-21, wherein the configured first CSI-RS resources are one of: periodic first CSI-RS resources, semi-persistent first CSI-RS resources and aperiodic first CSI-RS resources.

23. A second device for handling Channel State Information Reference Signals, CSI-RSs, the second device operating in a communications system, the second device comprising processing circuitry configured to:obtain a third configuration of a second set of two or more first CSI-RS resources,obtain one or more of:i. a tenth indication of a third subset of the second set of two or more Channel State Information Reference Signal, CSI-RS, resources, andii. an eleventh indication of one or more fourth subsets of one or more CSI- RS ports of a second CSI-RS resource of the second set of two or more CSI-RS resources configured at the second device,perform a third set of measurements on CSI-RSs transmitted by a third network node operating in the communications system, wherein the third set of measurements is performed according to one or more of:i. the tenth indication andii. the eleventh indication,predict, using the performed third set of measurements as input to a trained machine learning model, MLM, a twelfth indication of a Channel State Information, CSI, of a channel between the second device and the third network node based on the third subset and the one or more fourth subsets, andinitiate outputting a thirteenth indication of the twelfth indication.

24. The second device according to claim 23, wherein the processing circuitry is further configured to perform any of the method steps of claims 15-22.

25. A computer-implemented method performed by a first network node (111), the method being for handling Channel State Information Reference Signals, CSI-RSs, the first network node (111) operating in a communications system (100), the method comprising:sending (901) a first configuration of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources to a first device (131) operating in the communication system (100), and- sending (902), to the first device (131) one or more of:i. a first indication of a first subset of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources, andii. a second indication of one or more second subsets of one or more CSI-RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), e.g., a first CSI-RS resource of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources, and, e.g., optionally,- transmitting (903) the CSI-RSs, e.g., according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

26. The method according to claim 25, wherein the first network node (111) sends one second subset of the one or more CSI-RS ports.

27. The method according to claim 25, wherein the first network node (111) sends more than one second subset of the one or more CSI-RS ports, and wherein each of the more than one second subset of the one or more CSI-RS ports is indicated for one of the configured CSI-RS resources in the first set.

28. The method according to claims 25 and 27, wherein the second subset of the one or more CSI-RS ports is indicated per CSI-RS resource within the indicated first subset of the first set of two or more CSI-RS resources (and can be different for different CSI-RS resources).

29. The method according to any of claims 25-28, further comprising:- sending (904) first information to be used for the training of an MLM, the first information comprising one or more of:i. one or more codebooks the first device (131) is to train the MLM to predict with,ii. a seventh indication of specific CSI Resource Indicators, CRIs, that the first device (131) is to train the MLM to always predict CSI for,iii. an eighth indication of specific CRIs that the first device (131) is to refrain from training the MLM to predict CSI for,iv. second information of a number of reported CRIs,v. third information indicating how one or more beams of the CSI-RS resources, transmitted by the first network node (111), are spatially related to each other, andvi. a second configuration comprising a ninth indication of a condition indicating similar properties are shared by:a) one or more downlink transmission beams,b) one or more transmit radio unit mappings for the configured CSI- RS resources, CSI-RS ports or both,c) one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both.

30. The method according to any of claims 25-29, wherein the configured CSI-RS resources are one of: periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

31. A first network node for handling Channel State Information Reference Signals, CSI- RSs, the first network node operating in a communications system, the first network node comprising processing circuitry configured to:send a first configuration of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources to a first device operating in the communication system, andsend, to the first device one or more of:i. a first indication of a first subset of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources, andii. a second indication of one or more second subsets of one or more CSI- RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, andtransmit the CSI-RSs.

32. The first network node according to claim 31 , wherein the processing circuitry is further configured to perform any of the method steps of claims 26 -30.

33. A computer-implemented method performed by a second network node (112), the method being for handling Channel State Information Reference Signals, CSI-RSs, the second network node (112) operating in a communications system (100), the method comprising:- obtaining (1001), at least from a first device (131), a third indication of a first set of measurements on CSI-RSs transmitted by a first network node (111) operating in the communications system (100), wherein the first set of measurements has been performed according to one or more of:i. a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), andii. a second indication of one or more second subsets of one or more CSI- RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), e.g., a first CSI-RS resource of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device (131), and- obtaining (1002), at least from the first device (131), a fourth indication of a second set of measurements on the CSI-RSs transmitted by the first network node (111), wherein the second set of measurements has been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

34. The method according to claim 33, further comprising one or more of:training (1004) a machine learning model, MLM, with the obtained first set of measurements and the second set of measurements, to predict a fifth indicationof a Channel State Information, CSI, of a channel between the first device (131) and the first network node (111) based on one of the first subset of the first set of two or more CSI-RS resources and the one or more second subsets of the one or more CSI-RS ports of the first set of two or more CSI-RS resources, and- initiating (1005) outputting a sixth indication of the trained MLM.

35. The method according to any of claims 33-34, wherein the first set of measurements is a subset of the second set of measurements.

36. The method according to any of claims 33-35, further comprising:- obtaining (1003) first information to be used for the training of the MLM, the first information comprising one or more of:i. one or more codebooks the second network node (112) is to train the MLM to predict with,ii. a seventh indication of specific CSI Resource Indicators, CRIs, that the second network node (112) is to train the MLM to always predict CSI for,iii. a eighth indication of specific CRIs that the second network node (112) is to refrain from training the MLM to predict CSI for,iv. second information of a number of reported CRIs,v. third information indicating how one or more beams of the CSI-RS resources, transmitted by the first network node (111), are spatially related to each other, andvi. a second configuration comprising a ninth indication of a condition indicating similar properties are shared by:a) one or more downlink transmission beams,b) one or more transmit radio unit mappings for the configured CSI- RS resources, CSI-RS ports or both,c) one or more transmit radio unit virtualizations for the configured CSI-RS resources, CSI-RS ports or both.

37. The method according to any of claims 33-36, wherein the CSI-RS resources are one of: periodic CSI-RS resources, semi-persistent CSI-RS resources and aperiodic CSI-RS resources.

38. A second network node for handling Channel State Information Reference Signals, CSI- RSs, the second network node operating in a communications system, the second network node comprising processing circuitry configured to:obtain, at least from a first device, a third indication of a first set of measurements on CSI-RSs transmitted by a first network node operating in the communications system, wherein the first set of measurements has been performed according to one or more of:i. a first indication of a first subset of a first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, andii. a second indication of one or more second subsets of one or more CSI- RS ports of the first set of two or more Channel State Information Reference Signal, CSI-RS, resources configured at the first device, and- obtain, at least from the first device, a fourth indication of a second set of measurements on the CSI-RSs transmitted by the first network node, wherein the second set of measurements has been performed according to all configured CSI-RS resources of the first set of the two or more CSI-RS resources.

39. The second network node according to claim 38, wherein the processing circuitry is further configured to perform any of the method steps of claims 34 -37.

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