Beam prediction report structure

Abstract

A method, network node and wireless device for beam prediction report structure are disclosed. According to one aspect, a method in a wireless device (WD) includes configuring at least a first part of a two part beam prediction report, the first part of the two part beam prediction report beam being fixed in size and configured to include transmit beam information for a first beam. The first part of the two part beam prediction report includes an indication of a number of beams for which beam information may be reported by the WD in the second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size. The method includes transmitting at least the first part of the two part beam prediction report.

Description

[0001] BEAM PREDICTION REPORT STRUCTURE

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to wireless communications, and in particular, to beam prediction report.

[0004] BACKGROUND The Third Generation Partnership Project (3 GPP) has developed and is developing standards for Fourth Generation (4G) (also referred to as Long Term Evolution (LTE)) and Fifth Generation (5G) (also referred to as New Radio (NR)) wireless communication systems. Such systems provide, among other features, broadband communication between network nodes, such as base stations, and mobile wireless devices (WD), as well as communication between network nodes and between WDs. The 3GPP is also developing standards for Sixth Generation (6G) wireless communication networks.

[0005] In high frequency range FR2, multiple radio frequency (RF) beams may be used to transmit and receive signals at a network node (e.g., gNB) and a wireless device (WD). For each downlink (DL) beam from a network node, there is typically an associated best WD receive (Rx) beam for receiving signals from the DL beam. The DL beam and the associated WD Rx beam forms a beam pair. The beam pair may be identified through a so-called beam management process in NR.

[0006] A DL beam is (typically) identified by an associated DL reference signal (RS) transmitted in the beam, either periodically, semi-persistently, or aperiodically. The DL RS for this purpose may be a Synchronization Signal (SS) and Physical Broadcast Channel (PBCH) block (SSB) or a Channel State Information RS (CSLRS). By measuring all the DL RSs, the WD may determine and report to the network node the best DL beam to use for DL transmissions. The network node may then transmit a burst of DL-RS in the reported best DL beam to let the WD evaluate candidate WD RX beams.

[0007] Although not explicitly stated in the NR specification, beam management has been divided into three procedures, schematically illustrated in FIG. 1 :

[0008] P-1 : Purpose is to find a coarse direction for the WD using wide network node transmit (TX) beam covering the whole angular sector;

[0009] P-2: Purpose is to refine the network node TX beam by doing a new beam search around the coarse direction found in Pl; and

[0010] P-3: Used for WD that has analog beamforming to let them find a suitable WD RX beam.

[0011] P-1 is expected to utilize beams with rather large beamwidths and where the beam reference signals are transmitted periodically and are shared between all WDs of the cell. Typically reference signal to use for P-1 are periodic CSI-RS or Synchronization Signal Block (SSB). The WD then reports the N best beams to the network node and their corresponding reference signal received power (RSRP) values.

[0012] P-2 is expected to use aperiodic / or semi -persistent CSI-RS transmitted in narrow beams around the coarse direction found in P-1.

[0013] P-3 is expected to use aperiodic or semi -persistent CSI-RSs repeatedly transmitted in one narrow network node beam. One alternative way is to let the WD determine a suitable WD RX beam based on the periodic SSB transmission. Since each SSB consists of four orthogonal frequency division multiplexed (OFDM) symbols, a maximum of four WD RX beams may be evaluated during each SSB burst transmission. One benefit with using SSB instead of CSI-RS is that no extra overhead of CSI-RS transmission is needed.

[0014] A CSI-RS is transmitted over each Tx antenna port at the network node and for different antenna ports. The CSI-RS are multiplexed in time, frequency, and a code domain such that the channel between each Tx antenna port at the network node and each receive antenna port at a WD may be measured by the WD. The time-frequency resource used for transmitting CSI-RS is referred to as a CSI-RS resource.

[0015] In NR, the CSI-RS for beam management is defined as a 1- or 2-port CSI-RS resource in a CSI-RS resource set where the filed repetition is present. The following three types of CSI-RS transmissions are supported:

[0016] • Periodic CSI-RS: CSI-RS is transmitted periodically in certain slots. This CSI-RS transmission is semi-statically configured using Radio Resource Control (RRC) signaling with parameters such as CSI-RS resource, periodicity, and slot offset;

[0017] • Semi -Persistent CSI-RS: Similar to periodic CSI-RS, resources for semi -persistent CSI-RS transmissions are semi-statically configured using RRC signaling with parameters such as periodicity and slot offset. However, unlike periodic CSI-RS, dynamic signaling is needed to activate and deactivate the CSI- RS transmission; and

[0018] • Aperiodic CSI-RS: This is a one-shot CSI-RS transmission that may happen in any slot. Here, one-shot means that CSI-RS transmission only happens once per trigger. The CSI-RS resources (i.e., the resource elements (RE) locations which consist of subcarrier locations and OFDM symbol locations) for aperiodic CSI-RS are semi-statically configured. The transmission of aperiodic CSI-RS is triggered by dynamic signaling through a physical downlink control channel (PDCCH) using the CSI request field in uplink (UL) downlink control information (DCI), in the same DCI where the UL resources for the measurement report are scheduled. Multiple aperiodic CSI-RS resources may be included in a CSI-RS resource set and the triggering of aperiodic CSI-RS is on a resource set basis.

[0019] In NR, an SSB consists of a pair of synchronization signals (SSs), physical broadcast channel (PBCH), and demodulation reference signal (DMRS) for PBCH. A SSB is mapped to 4 consecutive OFDM symbols in the time domain and 240 contiguous subcarriers (20 RBs) in the frequency domain.

[0020] 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 is confined to a half frame time interval (5 ms). It is also 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 is up to network implementation. The SSBs within a half frame are broadcasted periodically from each cell. The periodicity of the half frames with SS / PBCH blocks is referred to as SSB periodicity, which is indicated by SIB1.

[0021] The maximum number of SSBs within a half frame, denoted by L, depends on the frequency band, and the time locations for these L candidate SSBs within a half frame depends on the SCS of the SSBs. The L candidate SSBs within a half frame are indexed in an ascending order in time from 0 to L-l. By successfully detecting PBCH and its associated DMRS, a WD knows the SSB index. A cell does not necessarily transmit SS / PBCH blocks in all L candidate locations in a half frame, and the resource of the unused candidate positions may be used for the transmission of data or control signaling instead. It is 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.

[0022] In NR, a WD may be configured with N>1 CSI reporting settings (i.e., CSL

[0023] ReportConfig), M>1 resource settings (i.e., CSI-ResourceConfig), where each CSI reporting setting is linked to one or more resource setting for channel and / or interference measurement. The CSI framework is modular, meaning that several CSI reporting settings may be associated with the same Resource Setting.

[0024] The measurement resource configurations for beam management are provided to the WD by RRC IES CSI-ResourceConfigs. One CSI-ResourceConfig contains several non-zero power (NZP)-CSI-RS-ResourceSets and / or CSI-SSB-ResourceSets.

[0025] A WD may be configured to perform measurement on CSI-RSs. Here the RRC information element (IE) NZP-CSI-RS-ResourceSet is used. A NZP CSI-RS resource set contains the configuration of Ks >1 CSI-RS resources, where the configuration of each CSI-RS resource includes at least: mapping to REs, the number of antenna ports, timedomain behavior, etc. Up to 64 CSI-RS resources may be grouped to an NZP-CSI-RS- ResourceSet. A WD may also be configured to perform measurements on SSBs. Here, the RRC IE CSI-SSB-ResourceSet is used. Resource sets comprising SSB resources are defined in a similar manner.

[0026] In cases of aperiodic CSI-RS and / or aperiodic CSI reporting, the network node configures the WD with ScCSI triggering states. Each triggering state contains the aperiodic CSI report setting to be triggered along with the associated aperiodic CSI-RS resource sets.

[0027] Periodic and semi-persistent Resource Settings may only comprise a single resource set (i.e., S=l) while S>=1 for aperiodic Resource Settings. This is because in the aperiodic case, one out of the S resource sets comprised in the Resource Setting is indicated by the aperiodic triggering state that triggers a CSI report.

[0028] Three types of CSI measurement reporting are supported in NR as follows:

[0029] • Periodic CSI Reporting on PUCCH: CSI is reported periodically by a WD. Parameters such as periodicity and slot offset are configured semi-statically by higher layer RRC signaling from the network node to the WD;

[0030] • Semi -Persistent CSI Reporting on PUSCH or PUCCH: similar to periodic CSI reporting, semi-persistent CSI reporting has a periodicity and slot offset which may be semi-statically configured. However, a dynamic trigger from network node to WD may be needed to allow the WD to begin semi -persistent CSI reporting. A dynamic trigger from network node to WD is needed to request the WD to stop the semi-persistent CSI reporting; and • Aperiodic CSI Reporting on PUSCH: This type of CSI reporting involves a single-shot (i.e., one time) CSI report by a WD which is dynamically triggered by the network node using DCI. Some of the parameters related to the configuration of the aperiodic CSI report is semi-statically configured by RRC but the triggering is dynamic.

[0031] In each CSI reporting setting, the content and time-domain behavior of the report is defined, along with the linkage to the associated Resource Settings. The CSI-ReportConfig IE comprise the following configurations:

[0032] • reportConfigType o Defines the time-domain behavior, i.e., periodic CSI reporting, semi-persistent CSI reporting, or aperiodic CSI reporting, along with the periodicity and slot offset of the report for periodic CSI reporting.

[0033] • reportQuantity o Defines the reported CSI parameter(s) (i.e., the CSI content), such as precoder matrix indicator (PMI), channel quality indicator (CQI), rank indicator (RI), LI (layer indicator), CRI (C SIRS resource index) and Ll-RSRP. Only a certain number of combinations are possible (e.g., ‘cri-RI-PMI-CQI’ is one possible value and ‘cri-RSRP’ is another) and each value of reportQuantity may be said to correspond to a certain CSI mode.

[0034] • codebookConfig o Defines the codebook used for PMI reporting, along with possible codebook subset restriction (CBSR). Two “Types” of PMI codebook are defined in NR, Type I CSI and Type II CSI, each codebook type further has two variants each.

[0035] • reportFrequencyConfiguration o Define the frequency granularity of PMI and CQI (wideband or subband), if reported, along with the CSI reporting band, which is a subset of subbands of the bandwidth part (BWP) which the CSI corresponds to; and

[0036] • Measurement restriction in time domain (ON / OFF) for channel and interference respectively. For beam management, a WD may be configured to report Ll-RSRP for up to four different CSI-RS / SSB resource indicators. The reported RSRP value corresponding to the first (best) CRI / SSBRI requires 7 bits, using absolute values, while the others require 4 bits using encoding relative to the first. In NR release 16, the report of Ll- SINR for beam management has already been supported.

[0037] During the 3GPP meeting RANl#109-e it was agreed to study artificial intelligence / machine learning (AI / ML) based spatial beam prediction (BM-Case 1) for a set A of beams based on measurement results of Set B of beams. The Set B of beams may either be a subset of the Set A of beams, or the set A of beams may consist of different beams compared to the Set B of beams (for example Set A consists of narrow beams and Set B consists of wide beams). The spatial beam prediction may either be made at the NW side or at the WD side.

[0038] During the 3GPP meeting RANl#109-e it was also agreed to study AI / ML based temporal (BM-Case 2) beam prediction for a Set A of beams based on measurement results of Set B of beams, where the Set A of beams and Set B of beams may be the same set of beams or different set of beams. For AI / ML based temporal beam prediction, it was also agreed that the measurement results of K (K>=1) latest measurement instances during a time window T1 of the Set B beams are used for AI / ML model input. Furthermore, it was agreed that one or more beams from the Set A beams will be used as AI / ML model output, where the AI / ML model output should be F predictions for F future time instances, where all F future time instances are located within a time window T2.

[0039] During the 3 GPP meeting RANI #115, it was also considered to capture the figure depicted in FIG. 2 and description of the two sub-use cases for providing a description of the BM use case as part of the 3GPP Technical Report 38.843Version 18.0.0.

[0040] FIG. 2 provides an example for the inference procedure for beam management for BM-Casel and BM-Case2. Measurements based on Set B of beams are used as model input. In addition, beam ID information may be also provided as input to the AI / ML model. Based on model output (e.g., probability of each beam in Set A to be the Top-1 beam, predicted Ll-RSRPs), Top-l / N beam(s) among Set A of beams may be predicted and / or potentially with predicted Ll-RSRPs (depending on the labeling). In the evaluation, for BM-Case 1, the measurements of Set B (otherwise stated) are used as model input to predict Top-l / N beams from Set A, and for BM-Case2, the measurements from historic time instance(s) are used as model input for temporal DL beam prediction of beams from Set A. In the evaluation, the cases that Set A and Set B are different (Set B is NOT a subset of Set A), and Set B is a subset of Set A for both BM-Case 1 and BM-Case2, and case that Set A and Set B are the same for BM- Case2 are considered. And the performance of DL Tx beam prediction and DL Tx-Rx beam pair prediction is evaluated.

[0041] For both BM-Casel and BM-Case2, WD may report the prediction result to NW based on the output of a WD-sided model, or NW may predict the Top-l / N beam(s) based on the reported measurements of Set B for a NW-sided model.

[0042] It is noted that as beam is something that is formed on the NW side the WD may only measure the result of this. This may for example be that the narrow beams are measured by CSI-RS resources and the wide beams are measured by SSBs at the WD side. This would be how the WD may see the beams.

[0043] FIG. 3 illustrates a schematic example of the Set A of beams and the Set B of beams. The top illustration shows all the narrow network node beams, which constitutes the Set A of beams, and the lower illustrations shows all the wide network node beams, which constitutes the Set B of beams. Set B is different from Set A. FIG. 4 illustrates another example of the Set A of beams and the Set B of beams, wherein Set A contains narrow network node beams and set B is subset of Set A containing some narrows beams from the network node.

[0044] During 3 GPP meeting RAN1#110, a set of possible outputs of AI / ML beam prediction from a WD-sided model were listed as follows:

[0045] Regarding the sub use case BM-Casel and BM-Case2, study the following alternatives for AI / ML output:

[0046] • Alt.1 : Tx and / or Rx Beam ID(s) and / or the predicted Ll-RSRP of the N predicted DL Tx and / or Rx beams

[0047] • E.g., N predicted beams may be the top-N predicted beams

[0048] • Alt.2: Tx and / or Rx Beam ID(s) of the N predicted DL Tx and / or Rx beams and other information • For further study (FFS): other information (e.g., probability for the beam to be the best beam, the associated confidence, beam application time / dwelling time, Predicted Beam failure)

[0049] • E.g., N predicted beams may be the top-N predicted beams

[0050] • Alt.3 : Tx and / or Rx Beam angle(s) and / or the predicted Ll-RSRP of the N predicted DL Tx and / or Rx beams

[0051] • E.g., N predicted beams may be the top-N predicted beams

[0052] • FFS: details of Beam angle(s)

[0053] • FFS: how to select the N DL Tx and / or Rx beams (e.g., Ll-RSRP higher than a threshold, a sum probability of being the best beams higher than a threshold, RSRP corresponding to the expected Tx and / or Rx beam direction(s))

[0054] • Notel : It is up to companies to provide other alternative(s)

[0055] • Note2: Beam ID is only used for discussion purpose

[0056] • Note3: All the outputs are “nominal” and only for discussion purpose

[0057] • Noted: Values of N is up to each company.

[0058] • Note5: All of the outputs in the above alternatives may vary based on whether the AI / ML model inference is at WD side or network node side

[0059] • Note 6: The Top-N beam IDs may have been derived via postprocessing of the ML-model output

[0060] CSI reports in NR with two parts are currently supported for CSI feedback on PUSCH. Parti consist of the most important parts and has high priority, while part2 consist of less important parts and hence has lower priority (and even if the WD only reports parti, the NW still have enough information to do some useful actions).

[0061] Below is some text from 3GPP Technical Report (TR) 38.214 Version 18.4.0 for CSI reporting with two parts:

[0062] For Type I, Type II, Enhanced Type II and Further Enhanced Type II Port Selection CSI feedback on PUSCH, a CSI report comprises of two parts. Part 1 has a fixed payload size and is used to identify the number of information bits in Part 2. Part 1 shall be transmitted in its entirely before Part 2.

[0063] - For Type I CSI feedback, Part 1 contains RI (if reported), CRI (if reported), CQI for the first codeword (if reported). Part 2 contains PMI (if reported), LI (if reported) and contains the CQI for the second codeword (if reported) when RI is larger than 4. For a CSI-ReportConfig configured with codebookType set to 'typelSinglePanef and the corresponding CSI-RS Resource Set for channel measurement configured with two Resource Groups and Resource Pairs, Part 1 contains RI(s), CRI(s), CQI(s) for the first codeword and is zero padded to a fixed payload size (if needed). Part 2 contains the CQI(s) for the second codeword (if reported) when RI is larger than 4, Lis (if reported) and PMI(s).

[0064] - For Type II CSI feedback, Part 1 contains RI (if reported), CQI, and an indication of the number of non-zero wideband amplitude coefficients per layer for the Type II CSI (see Clause 5.2.2.2.3). The fields of Part 1 - RI (if reported), CQI, and the indication of the number of non-zero wideband amplitude coefficients for each layer are separately encoded. Part 2 contains the PMI and LI (if reported) of the Type II CSI. The elements of ili4ii, i2,i,i (if reported) and i2,2,i (if reported) are reported in the increasing order of their indices, i = 0,1, ... , 2L - 1, where the element of the lowest index is mapped to the most significant bits and the element of the highest index is mapped to the least significant bits. Part 1 and 2 are separately encoded.

[0065] - For Enhanced Type II CSI feedback (see Clause 5.2.2.2.5) and Further Enhanced Type II Port Selection CSI feedback (see Clause 5.2.2.2.7), Part 1 contains RI (if reported), CQI, and an indication of the overall number of non-zero amplitude coefficients across layers. The fields of Part 1 - RI (if reported), CQI, and the indication of the overall number of non-zero amplitude coefficients across layers - are separately encoded. Part 2 contains the PMI of the Enhanced Type II or Further Enhanced Type II Port Selection CSI. Part 1 and 2 are separately encoded.

[0066] SUMMARY

[0067] Some embodiments advantageously provide methods, network nodes and wireless devices (WDs) for beam prediction report structure. During inference of WD-sided beam prediction (spatial and / or time domain beam prediction), the WD may be configured to report predicted beam ID(s) and associated performance metric(s) per reported beam to the network. One example of such performance metric is the probability that a reported beam is the strongest beam (best beam). It is also possible that the number of beams the WD should include in a beam prediction report depends on how probable it is that the different beams are the best beam. For example, if the best beam has a 99% chance to be the best beam, it may be better that the WD reduce the beam prediction report overhead signaling by not reporting any other beams. This, in turn, means that the beam prediction report will vary in size for different report occasions, and how to structure such report in order to reduce overhead signaling (i.e., to allow an adaptation of reporting size based on that actual report payload) is an open issue.

[0068] Some embodiments include methods for structuring the reporting of beam prediction related information for a WD-sided model. The methods introduce a two-part beam prediction report where the first part is a fixed size report, which includes an indication of a flexible (second part) of the beam prediction report. A method for adapting the flexible part is based on WD-sided ML model output information, in combination with network node-configuration(s) or pre-configured values. The embodiments outline different alternatives for such reporting methods. Some embodiments disclose how to select and report the N DL Tx and / or Rx beams (e.g., Ll-RSRP higher than a threshold, a sum probability of being the best beams higher than a threshold, RSRP corresponding to the expected Tx and / or Rx beam direction(s)).

[0069] According to some embodiments, a wireless device (WD) configured to communicate with a network node is provided. The method comprising configuring a first part of a two part beam prediction report. The first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to reported by the WD in the a second part of the two part beam prediction report. The second part of the two part beam prediction report being variable in size. The method further comprises transmitting the first part of the two part beam prediction report.

[0070] According to some embodiments, a method implemented in a wireless device (WD) is provided. The method comprising configuring a first part of a two part beam prediction report. The first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to reported by the WD in the a second part of the two part beam prediction report. The second part of the two part beam prediction report being variable in size. The method further comprises transmitting the first part of the two part beam prediction report. According to some embodiments, a network node configured to communicate with a wireless device, (WD), is provided. The network node configured to receive at least a first part of a two part beam prediction report. The first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to be reported by the WD in the second part of the two part beam prediction report. The method further comprises the second part of the two part beam prediction report being variable in size. The network node further selects for subsequent transmission to the WD at least one beam of the first beam configured in the first part of the two part beam prediction report and a beam for which the beam information is reported by the WD in the second part of the two part beam prediction report.

[0071] According to some embodiments, a method implemented in a network node 16 is provided. The method comprising receiving a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to be reported by the WD in the second part of the two part beam prediction report. The method further comprises the second part of the two part beam prediction report being variable in size. The method further selecting for subsequent transmission to the WD at least one beam as the first beam configured in the first part of the two part beam prediction report and a beam for which the beam information is reported by the WD in the second part of the two part beam prediction report.

[0072] Advantages of some embodiments may include that the beam prediction reporting overhead during inference of WD-sided beam prediction (spatial and / or time domain beam prediction) may be reduced.

[0073] BRIEF DESCRIPTION OF THE DRAWINGS

[0074] A more complete understanding of the present embodiments, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:

[0075] FIG. 1 illustrates three procedures of beam management;

[0076] FIG. 2 illustrates inputs and outputs of an AI / ML model;

[0077] FIG. 3 illustrates a schematic example of two sets of beams; FIG. 4 illustrates another schematic example of two sets of beams;

[0078] FIG. 5 is a schematic diagram of an example network architecture illustrating a communication system connected via an intermediate network to a host computer according to the principles in the present disclosure;

[0079] FIG. 6 is a block diagram of a host computer communicating via a network node with a wireless device over an at least partially wireless connection according to some embodiments of the present disclosure;

[0080] FIG. 7 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for executing a client application at a wireless device according to some embodiments of the present disclosure;

[0081] FIG. 8 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data at a wireless device according to some embodiments of the present disclosure;

[0082] FIG. 9 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data from the wireless device at a host computer according to some embodiments of the present disclosure;

[0083] FIG. 10 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data at a host computer according to some embodiments of the present disclosure;

[0084] FIG. 11 is a flowchart of an example process in a network node for beam prediction report structure.

[0085] FIG. 12 is a flowchart of an example process in a wireless device for beam prediction report structure.

[0086] FIG. 13 is a high level illustration of an example of two parts of information configured according to principles disclosed herein;

[0087] FIG. 14 is second example illustration of two parts of information configured according to principles disclosed herein;

[0088] FIG. 15 is a third example illustration of two parts of information configured according to principles disclosed herein;

[0089] FIG. 16 is a fourth example illustration of two parts of information configured according to principles disclosed herein; and

[0090] FIG. 17 is a fifth example illustration of two parts of information configured according to principles disclosed herein.

[0091] DETAILED DESCRIPTION

[0092] Before describing in detail example embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to beam prediction report structure. Accordingly, components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. Like numbers refer to like elements throughout the description.

[0093] As used herein, relational terms, such as “first” and “second,” “top” and “bottom,” and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and / or “including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0094] In embodiments described herein, the joining term, “in communication with” and the like, may be used to indicate electrical or data communication, which may be accomplished by physical contact, induction, electromagnetic radiation, radio signaling, infrared signaling or optical signaling, for example. One having ordinary skill in the art will appreciate that multiple components may interoperate and modifications and variations are possible of achieving the electrical and data communication.

[0095] In some embodiments described herein, the term “coupled,” “connected,” and the like, may be used herein to indicate a connection, although not necessarily directly, and may include wired and / or wireless connections. The term “network node” used herein may be any kind of network node comprised in a radio network which may further comprise any of base station (BS), radio base station, base transceiver station (BTS), base station controller (BSC), radio network controller (RNC), g Node B (gNB), evolved Node B (eNB or eNodeB), Node B, multistandard radio (MSR) radio node such as MSR BS, multi -cell / multicast coordination entity (MCE), integrated access and backhaul (IAB) node, relay node, donor node controlling relay, radio access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU) Remote Radio Head (RRH), a core network node (e.g., mobile management entity (MME), self-organizing network (SON) node, a coordinating node, positioning node, MDT node, etc.), an external node (e.g., 3rd party node, a node external to the current network), nodes in distributed antenna system (DAS), a spectrum access system (SAS) node, an element management system (EMS), etc. The network node may also comprise test equipment. The term “radio node” used herein may be used to also denote a wireless device (WD) such as a wireless device (WD) or a radio network node.

[0096] In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) are used interchangeably. The WD herein may be any type of wireless device capable of communicating with a network node or another WD over radio signals, such as wireless device (WD). The WD may also be a radio communication device, target device, device to device (D2D) WD, machine type WD or WD capable of machine to machine communication (M2M), low-cost and / or low-complexity WD, a sensor equipped with WD, Tablet, mobile terminals, smart phone, laptop embedded equipped (LEE), laptop mounted equipment (LME), USB dongles, Customer Premises Equipment (CPE), an Internet of Things (loT) device, or a Narrowband loT (NB-IOT) device, etc.

[0097] Also, in some embodiments the generic term “radio network node” is used. It may be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-cell / multicast Coordination Entity (MCE), IAB node, relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

[0098] Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE and / or New Radio (NR), may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the aforementioned system. Other wireless systems, including without limitation Wide Band Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB) and Global System for Mobile Communications (GSM), may also benefit from exploiting the ideas covered within this disclosure.

[0099] Note further, that functions described herein as being performed by a wireless device or a network node may be distributed over a plurality of wireless devices and / or network nodes. In other words, it is contemplated that the functions of the network node and wireless device described herein are not limited to performance by a single physical device and, in fact, may be distributed among several physical devices.

[0100] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0101] Some embodiments provide beam prediction report structures.

[0102] Returning now to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 5 a schematic diagram of a communication system 10, according to an embodiment, such as a 3 GPP -type cellular network that may support standards such as LTE and / or NR (5G), which comprises an access network 12, such as a radio access network, and a core network 14. The access network 12 comprises a plurality of network nodes 16a, 16b, 16c (referred to collectively as network nodes 16), such as NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area 18a, 18b, 18c (referred to collectively as coverage areas 18). Each network node 16a, 16b, 16c is connectable to the core network 14 over a wired or wireless connection 20. A first wireless device (WD) 22a located in coverage area 18a is configured to wirelessly connect to, or be paged by, the corresponding network node 16a. A second WD 22b in coverage area 18b is wirelessly connectable to the corresponding network node 16b. While a plurality of WDs 22a, 22b (collectively referred to as wireless devices 22) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole WD is in the coverage area or where a sole WD is connecting to the corresponding network node 16. Note that although only two WDs 22 and three network nodes 16 are shown for convenience, the communication system may include many more WDs 22 and network nodes 16.

[0103] Also, it is contemplated that a WD 22 may be in simultaneous communication and / or configured to separately communicate with more than one network node 16 and more than one type of network node 16. For example, a WD 22 may have dual connectivity with a network node 16 that supports LTE and the same or a different network node 16 that supports NR. As an example, WD 22 may be in communication with an eNB for LTE / E-UTRAN and a gNB for NR / NG-RAN.

[0104] The communication system 10 may itself be connected to a host computer 24, which may be embodied in the hardware and / or software of a standalone server, a cloud- implemented server, a distributed server or as processing resources in a server farm. The host computer 24 may be under the ownership or control of a service provider, or may be operated by the service provider or on behalf of the service provider. The connections 26, 28 between the communication system 10 and the host computer 24 may extend directly from the core network 14 to the host computer 24 or may extend via an optional intermediate network 30. The intermediate network 30 may be one of, or a combination of more than one of, a public, private or hosted network. The intermediate network 30, if any, may be a backbone network or the Internet. In some embodiments, the intermediate network 30 may comprise two or more sub-networks (not shown).

[0105] A network node 16 is configured to include a beam selection unit 32 which may be configured to select for subsequent transmission to the WD at least one beam of a first beam configured in a first part of a two part beam prediction report and a beam for which the beam information is reported by the WD in a second part of the two part beam prediction report. A wireless device 22 is configured to include a beam report configuration unit 34 which may be configured to configure a two part beam prediction report as described herein.

[0106] Example implementations, in accordance with an embodiment, of the WD 22, network node 16 and host computer 24 discussed in the preceding paragraphs will now be described with reference to FIG. 6. In a communication system 10, a host computer 24 comprises hardware (HW) 38 including a communication interface 40 configured to set up and maintain a wired or wireless connection with an interface of a different communication device of the communication system 10. The host computer 24 further comprises processing circuitry 42, which may have storage and / or processing capabilities. The processing circuitry 42 may include a processor 44 and memory 46. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 42 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 44 may be configured to access (e.g., write to and / or read from) memory 46, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0107] Processing circuitry 42 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by host computer 24. Processor 44 corresponds to one or more processors 44 for performing host computer 24 functions described herein. The host computer 24 includes memory 46 that is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 48 and / or the host application 50 may include instructions that, when executed by the processor 44 and / or processing circuitry 42, causes the processor 44 and / or processing circuitry 42 to perform the processes described herein with respect to host computer 24. The instructions may be software associated with the host computer 24.

[0108] The software 48 may be executable by the processing circuitry 42. The software 48 includes a host application 50. The host application 50 may be operable to provide a service to a remote user, such as a WD 22 connecting via an OTT connection 52 terminating at the WD 22 and the host computer 24. In providing the service to the remote user, the host application 50 may provide user data which is transmitted using the OTT connection 52. The “user data” may be data and information described herein as implementing the described functionality. In one embodiment, the host computer 24 may be configured for providing control and functionality to a service provider and may be operated by the service provider or on behalf of the service provider. The processing circuitry 42 of the host computer 24 may enable the host computer 24 to observe, monitor, control, transmit to and / or receive from the network node 16 and or the wireless device 22.

[0109] The communication system 10 further includes a network node 16 provided in a communication system 10 and including hardware 58 enabling it to communicate with the host computer 24 and with the WD 22. The hardware 58 may include a communication interface 60 for setting up and maintaining a wired or wireless connection with an interface of a different communication device of the communication system 10, as well as a radio interface 62 for setting up and maintaining at least a wireless connection 64 with a WD 22 located in a coverage area 18 served by the network node 16. The radio interface 62 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers. The communication interface 60 may be configured to facilitate a connection 66 to the host computer 24. The connection 66 may be direct or it may pass through a core network 14 of the communication system 10 and / or through one or more intermediate networks 30 outside the communication system 10.

[0110] In the embodiment shown, the hardware 58 of the network node 16 further includes processing circuitry 68. The processing circuitry 68 may include a processor 70 and a memory 72. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 68 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 70 may be configured to access (e.g., write to and / or read from) the memory 72, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0111] Thus, the network node 16 further has software 74 stored internally in, for example, memory 72, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node 16 via an external connection. The software 74 may be executable by the processing circuitry 68. The processing circuitry 68 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by network node 16. Processor 70 corresponds to one or more processors 70 for performing network node 16 functions described herein. The memory 72 is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 74 may include instructions that, when executed by the processor 70 and / or processing circuitry 68, causes the processor 70 and / or processing circuitry 68 to perform the processes described herein with respect to network node 16. For example, processing circuitry 68 of the network node 16 may include a beam selection unit 32 which may be configured to select for subsequent transmission to the WD at least one beam of a first beam configured in a first part of a two part beam prediction report and a beam for which the beam information is reported by the WD in a second part of the two part beam prediction report.

[0112] The communication system 10 further includes the WD 22 already referred to. The WD 22 may have hardware 80 that may include a radio interface 82 configured to set up and maintain a wireless connection 64 with a network node 16 serving a coverage area 18 in which the WD 22 is currently located. The radio interface 82 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers.

[0113] The hardware 80 of the WD 22 further includes processing circuitry 84. The processing circuitry 84 may include a processor 86 and memory 88. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 84 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 86 may be configured to access (e.g., write to and / or read from) memory 88, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0114] Thus, the WD 22 may further comprise software 90, which is stored in, for example, memory 88 at the WD 22, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the WD 22. The software 90 may be executable by the processing circuitry 84. The software 90 may include a client application 92. The client application 92 may be operable to provide a service to a human or non-human user via the WD 22, with the support of the host computer 24. In the host computer 24, an executing host application 50 may communicate with the executing client application 92 via the OTT connection 52 terminating at the WD 22 and the host computer 24. In providing the service to the user, the client application 92 may receive request data from the host application 50 and provide user data in response to the request data. The OTT connection 52 may transfer both the request data and the user data. The client application 92 may interact with the user to generate the user data that it provides.

[0115] The processing circuitry 84 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by WD 22. The processor 86 corresponds to one or more processors 86 for performing WD 22 functions described herein. The WD 22 includes memory 88 that is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 90 and / or the client application 92 may include instructions that, when executed by the processor 86 and / or processing circuitry 84, causes the processor 86 and / or processing circuitry 84 to perform the processes described herein with respect to WD 22. For example, the processing circuitry 84 of the wireless device 22 may include a beam report configuration unit 34 which may be configured to configure a two part beam prediction report as described herein.

[0116] In some embodiments, the inner workings of the network node 16, WD 22, and host computer 24 may be as shown in FIG. 6 and independently, the surrounding network topology may be that of FIG. 5.

[0117] FIG. 7 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIGS. 5 and 6, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIG. 6. In a first step of the method, the host computer 24 provides user data (Block SI 00). In an optional substep of the first step, the host computer 24 provides the user data by executing a host application, such as, for example, the host application 50 (Block SI 02). In a second step, the host computer 24 initiates a transmission carrying the user data to the WD 22 (Block SI 04). In an optional third step, the network node 16 transmits to the WD 22 the user data which was carried in the transmission that the host computer 24 initiated, in accordance with the teachings of the embodiments described throughout this disclosure (Block SI 06). In an optional fourth step, the WD 22 executes a client application, such as, for example, the client application 92, associated with the host application 50 executed by the host computer 24 (Block SI 08).

[0118] FIG. 8 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIG. 5, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 5 and 6. In a first step of the method, the host computer 24 provides user data (Block SI 10). In an optional substep (not shown) the host computer 24 provides the user data by executing a host application, such as, for example, the host application 50. In a second step, the host computer 24 initiates a transmission carrying the user data to the WD 22 (Block SI 12). The transmission may pass via the network node 16, in accordance with the teachings of the embodiments described throughout this disclosure. In an optional third step, the WD 22 receives the user data carried in the transmission (Block SI 14).

[0119] FIG. 9 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIG. 5, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 5 and 6. In an optional first step of the method, the WD 22 receives input data provided by the host computer 24 (Block SI 16). In an optional substep of the first step, the WD 22 executes the client application 92, which provides the user data in reaction to the received input data provided by the host computer 24 (Block SI 18). Additionally or alternatively, in an optional second step, the WD 22 provides user data (Block S120). In an optional substep of the second step, the WD provides the user data by executing a client application, such as, for example, client application 92 (Block S122). In providing the user data, the executed client application 92 may further consider user input received from the user. Regardless of the specific manner in which the user data was provided, the WD 22 may initiate, in an optional third substep, transmission of the user data to the host computer 24 (Block S124). In a fourth step of the method, the host computer 24 receives the user data transmitted from the WD 22, in accordance with the teachings of the embodiments described throughout this disclosure (Block S126).

[0120] FIG. 10 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIG. 5, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 5 and 6. In an optional first step of the method, in accordance with the teachings of the embodiments described throughout this disclosure, the network node 16 receives user data from the WD 22 (Block S128). In an optional second step, the network node 16 initiates transmission of the received user data to the host computer 24 (Block SI 30). In a third step, the host computer 24 receives the user data carried in the transmission initiated by the network node 16 (Block SI 32).

[0121] FIG. 11 is a flowchart of an example process in a network node 16 for beam prediction report structure. One or more blocks described herein may be performed by one or more elements of network node 16 such as by one or more of processing circuitry 68 (including the beam selection unit 32), processor 70, radio interface 62 and / or communication interface 60. Network node 16 such as via processing circuitry 68 and / or processor 70 and / or radio interface 62 and / or communication interface 60 is configured to receive at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information may be reported by the WD 22 in the second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size (Block SI 34). The process includes selecting for subsequent transmission to the WD 22 at least one beam of the first beam and a beam for which the beam information is reported by the WD 22 (Block SI 36).

[0122] In some embodiments, the first part of the two part beam prediction report includes identifies a best beam based on reference signal received power (RSRP) values and a probability associated with the best beam. The best beam may be the beam that has highest probability of being the best beam or the best beam is the beam with highest predicted RSRP. In some embodiments,

[0123] In some embodiments, the first part of the two part beam prediction report indicates a predicted RSRP associated with the first beam.

[0124] In some embodiments, the second part of the two part beam prediction report includes a number M of best beams and a number N of weakest beams.

[0125] In some embodiments, the number of beams for which beam information is to be reported by the WD 22 is based at least in part on an accumulated probability of a best beam.

[0126] In some embodiments, the number of beams for which beam information is to be reported by the WD 22 is based at least in part on an accumulated probability of a weakest beam.

[0127] In some embodiments the second part of the two part beam report includes one or more of the following information for each of the number of beams for which beam information is to be reported by the WD the reported beams in the second part of the two part beam report

[0128] Beam index

[0129] Probability of athe beam being the best beam Predicted RSRP for a beam.

[0130] In some embodiments, the first part of the two part beam prediction report indicates a number of additional beams for each of multiple future time instances included in the second part of the two part beam prediction report.

[0131] In some embodiments, the first part of the two part beam prediction report indicates a number of future time instances included in the second part of the two part beam prediction report. Furthermore, in some embodiments the first part of the two part beam prediction report indicates which future time instances that are included in the second part of the two part beam prediction report.

[0132] In some embodiments, the second part of the two part beam prediction report, includes one or more of the following information for each of the reported beams for one or more of the future time instances

[0133] • Beam index

[0134] • Probability of a beam being the best beam

[0135] • Predicted RSRP for a beam.

[0136] FIG. 12 is a flowchart of an example process in a wireless device 22 according to some embodiments of the present disclosure. One or more blocks described herein may be performed by one or more elements of wireless device 22 such as by one or more of processing circuitry 84 (including the beam report configuration unit 34), processor 86, radio interface 82 and / or communication interface 60. Wireless device 22 such as via processing circuitry 84 and / or processor 86 and / or radio interface 82 is configured to configure at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information may be reported by the WD 22 in the second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size (Block S138). The process includes transmitting at least the first part of the two part beam prediction report (Block S140).

[0137] In some embodiments, the first part of the two part beam prediction report includes identifies a best beam based on reference signal received power (RSRP) values and a probability associated with the best beam. The best beam may be the beam that has highest probability of being the best beam or the best beam is the beam with highest predicted RSRP. In some embodiments,

[0138] In some embodiments the first part of the two part beam prediction report indicates a predicted RSRP associated with the first beam.

[0139] In some embodiments, the second part of the two part beam prediction report includes a number M of best beams and a number N of weakest beams. In some embodiments, the number of beams for which beam information is to be reported by the WD 22 is based at least in part on an accumulated probability of a best beam. In some embodiments, the number of beams for which beam information is to be reported by the WD 22 is based at least in part on an accumulated probability of a weakest beam. In some embodiments the second part of the two part beam report includes one or more of the following information for each of the number of beams for which beam information is to be reported by the WD the reported beams in the second part of the two part beam report

[0140] Beam index

[0141] Probability of a beam being the best beam

[0142] Predicted RSRP for a beam.

[0143] In some embodiments, the first part of the two part beam prediction report indicates a number of additional beams for each of multiple future time instances included in the second part of the two part beam prediction report.

[0144] In some embodiments, the first part of the two part beam prediction report indicates a number of future time instances included in the second part of the two part beam prediction report.

[0145] Furthermore, in some embodiments the first part of the two part beam prediction report indicates which future time instances that are included in the second part of the two part beam prediction report.

[0146] In some embodiments, the second part of the two part beam prediction report, includes one or more of the following information for each of the reported beams for one or more of the future time instances

[0147] • Beam index

[0148] • Probability of a beam being the best beam

[0149] • Predicted RSRP for a beam.

[0150] Having described the general process flow of arrangements of the disclosure and having provided examples of hardware and software arrangements for implementing the processes and functions of the disclosure, the sections below provide details and examples of arrangements for beam prediction report structures.

[0151] The information for the two parts is shown in the high-level illustration of FIG. 13.

[0152] For part 1 of the beam prediction report, it contains information so that the network node 16 may perform proper beam management in case the WD 22 cannot transmit part 2. The information in part 1 may include one or more of the following information:

[0153] Downlink reference signal index (DL-RS index);

[0154] Best beam index;

[0155] Best beam TX angle;

[0156] Best beam TX angle / index probability; Best beam TX angle / index predicted Ll-RSRP (for linkadaptation);

[0157] Probability of new beam better than previous beam;

[0158] Time-index of prediction; and / or Validity of time-based prediction.

[0159] Moreover, in some embodiments, the content of part 2 is indicated in part 1, such that the network node 16 may determine the size of part 2 after decoding part 1. For example, the part 1 may comprise information about number of predicted beams in part 2, number of predicted future time instances in part 2 (for temporal beam prediction) etc.

[0160] Content of each field in the CSI report (both valid for part 1 and part 2): beam index - An integer value. In one embodiment, the size of this field is log2(#beams in setA); beam angle - Two values between 0-180, representing the azimuth / horizontal direction of a beam main lobe from a transmission point of view. Can be represented in any granularity;

[0161] Beam probability - a value between e.g., 0-100%, quantized in any range or method as described in subsequent sections;

[0162] Time index - an absolute time stamp in UTC, or value referring to a relative time instance or a NR / LTE timeframe unit;

[0163] Validity of time-based prediction - for example an absolute time in ms or LTE / NR time units indicating for how long the predicted value is valid (defining the time-window); and / or

[0164] Signaling of second part -see above.

[0165] The configuration of part 2 of the beam prediction report is flexible, where the size may e.g., depend on one or more of: network node 16 configuration of value, for example the network node 16 configures the WD 22 to report information on a maximum of M beams, and T time instances;

[0166] Pre-configuration of value, for example the standard defines a report information on a maximum of M beams; and / or

[0167] WD-model inference output, for example the inference output estimate that there are at most M beams being candidate for being the strongest. In general, the number of beams included in the beam prediction report are the best M beams as determined by the AI / ML model in the WD 22. There are several methods to determine the best M beams to include in the report. The method utilizes the AI / ML model output as metrics to select the best M beams to report.

[0168] In some embodiments the number of beams included in the beam prediction report depends on the accumulated probability that the best beam is among the reported beams. For example, the WD 22 may be configured to report up to maximum N beams, where the number of actually reported beams is the M (M<=N) beams with highest probability to be the best beam, and M is the number of beams included in the beam prediction report such that the accumulated probability that the best beam is among the reported M beams is over a certain probability threshold Y. So, for example, if the probability threshold Y=95%, and the best beam has a probability of 70% to be the best, and the second beam has a probability of 27% to be the best beam, and the third beam has a probability of 3% to be the best beam, then the WD 22 only includes the first and second beam in the beam prediction report since the accumulated probability that one of them are the best beam are above the probability threshold Y = 95% (i.e., 70%+27% = 97% > 95%).

[0169] In some embodiments, the WD 22 is configured to not report beams for which the probability of the beam being the best beam is below a threshold Z. As non-limiting example, the network node 16 may not be interested in low accuracy predictions, e.g., a probability of a beam being the best beam less than 10 or 20 %. By configuring such a rule, the overhead on the beam prediction report may be reduced. In one embodiment, the value of M, and / or Y, and / or Z is specified in a procedural text in the standard instead of being configurable. In a related embodiment, the WD 22 indicates the supported values, e.g., in its WD 22 capability signaling, after which the network node 16 may configure the WD 22 to report according to one or more of the supported values.

[0170] In some embodiments, the best M beams to report are determined based on the predicted Ll-RSRPs of the beams, typically the M beams with the highest predicted Ll- RSRPs. To reduce the beam prediction report size, the M (MAN) beams may be determined in several ways. In one example, the predicted Ll-RSRP of the best (i.e., Top- 1) beam is determined as Ll-RSRP(O), and (M-l) beams with highest predicted Ll-RSRP which are within ALI-RSRP (dB) of Ll-RSRP(O) are obtained, i.e., the best M beams with predicted Ll-RSRP in the range of [Ll-RSRP(O)- ALI-RSRP (dB), Ll-RSRP(O)]. The threshold ALI-RSRP may be a fixed value (e.g., 5 dB) or a relative value (e.g., 20%* Ll- RSRP(0)).

[0171] In some embodiments, the best M beams to report are determined based on multiple metrics. In one example, the best M beams are those that satisfy multiple metrics simultaneously, for instance, (1) the probability of the beam being the best beam is higher than a threshold Z (e.g., Z=20%), AND (2) the predicted Ll-RSRPs of the beams is among the highest. In another example, the best M beams are those that are the top beam(s) according to at least one metric, for instance, (1) the probability of the beam being the best beam is the highest Ml (e.g., Ml=2) beams, OR (2) the predicted Ll-RSRPs of the beams is among the highest M2 (e.g., M2=3) beams.

[0172] In some embodiments, the reported beams from WD 22 may include one or more best beams and one or more weakest beams. For example, the WD 22 may be configured to report up to K beams, where K beams contains at least M beams with highest probability to be the best beam and N beams with the lowest probability to be the best beam. The values of M and N may be configured by the network node 16 based on the WD reported capability and / or the pre-determined / configured condition. The condition may be that M is the number of beams included in the beam prediction report such that the accumulated probability that the best beam is among the reported M beams is over a certain probability threshold X and N is the number of beams included in the beam prediction report such that the accumulated probability that the best beam is among the reported N beams is lower than a certain probability threshold Y, or N is a fixed number. Alternatively, the weakest N beams are determined based on the predicted Ll-RSRP (e.g., the N beams with lowest Ll-RSRP values), or a combination of two or metrics such as (1) the probability of the beam being Top-1 beam is among the lowest and / or (2) the predicted Ll-RSRP of the beam is among the lowest. Apart from the best beams, the network node 16 may use such reported weakest beams as additional information to determine the beamforming weights for multi-user MIMO. For example:

[0173] • In some embodiments, the number of beams included in the beam prediction report depends on both the accumulated probability of the best beam and the weakest beam among the reported beams;

[0174] • In some embodiments, the number of beams included in the beam prediction report depends on the accumulated probability of the best beam among the reported beams with a fixed number (N) of the weakest beams; and / or

[0175] • In some embodiments, the number of beams included in the beam prediction report includes a fixed number (M) of the best beam and a fixed number (N) of the weakest beams.

[0176] Several examples are provided that outline part 1 and part 2 of the beam prediction report. These are non-limiting examples. For example, the beam index may include a beam angle or DL-RS index. The beam index may include a TX-beam ID or a TX / RX beam pair index. The predicted signal quality of Ll-RSRP may also include Ll-SINR; RSRQ or other signal quality metric.

[0177] For spatial domain beam prediction in some embodiments, the first part (Part 1) of the beam prediction report indicates the number of beams reported in the second part (Part 2) of the beam prediction report. In some embodiments, Part 2 includes the information of all M beams. In some embodiments, the first part of the beam prediction report contains a best beam ID, probability that the first beam is best and then an additional bitfield that indicates the number of additional beams in Part 2. One example of how this may look is illustrated in FIG. 14. In some embodiments, also other performance metrics are included for one or more of the reported beams either in Parti and / or Part2, like e.g., predicted absolute RSRP and / or predicted relative RSRP. Please note that not all the bitfields must be included in the report. Other bitfields may be included in the report and the exact order of the bitfields within each CSI part may differ.

[0178] In some embodiments, the bitfi eld(s) to report the probability in Part 2 is encoded assuming a maximum value of (100 - probability of beam #1 is the best beam indicated in Parti). For example, if probability of beam #1 is the best beam is 80%, and the quantization level used to represent the probability values is 1. Then, the bit width to report the probability of one or more of the additional beams in Part 2 is 5 bits, i.e., ceil(log2(20)) (i.e., the reported probability that one or more of the beams in part 2 is the best beam may be a value between 0%to 20%, or similar values).

[0179] In some embodiments, the bitfi eld(s) to report the probability in both Part 1 and Part 2 is encoded assuming a fixed value. For example, if the quantization level used to represent the probability values is 1%, the bit width to report the probability of each of the additional beams in the CSI report (both in Part 1 and Part 2) is 7 bits, i.e., ceil(log2(100)).

[0180] Assume that the best beam reported in Part 1 has the probability X of being the best beam and that the remaining beams are reported in Part 2. In some embodiments, the bitfield(s) to report the probability in Part 1 may for example be fixed as 7 bits, i.e., ceil(log2(100)), and where the bitfield used to report the probability to be the best beam for the beams reported in Part 2 is encoded assuming a relative fixed value based on the probability X of the best reported beam in Part 1. For example, assume X=50 / Then, the encoded bitfield(s) to report the probability of the beams included in Part 2 may assume values between 0% to 50% (since the probability that a beam in Part 2 is the best beam is equal to or smaller than the probability that the beam in Part 1 is the best beam). If the quantization level used to represent the probability values is 1%, then the bit width to report the probability of each of the additional beams in Part 2 is 6 bits in this case, i.e., ceil(log2(50)). Please note that using a granularity of 1% in the above embodiments is just an example, and other granularities are possible.

[0181] In some embodiments, if the sum of all probabilities of the M beams do not fulfill the pre-configured probability threshold, the WD 22 reports only Parti, and skips the transmission of Part 2, i.e., indicates in part 1 that the number of additional beams in part 2 is zero. The value of M may be set by the network node 16 to allow some tolerance of the inaccuracy of the WD model. A value of M that is low, and a threshold probability that is high is an indication that the network node 16 is interested in the beam prediction only if they are highly accurate (i.e., probability of the beam being the best beam is high). There may be some cases in which the network node 16 would set M to be larger, such as for monitoring the performance or behavior of the WD sided model.

[0182] In some embodiments, in case the WD 22 has detected that its AI / ML beam prediction model is outdated or no longer working (due to e.g., hardware issues or any other issues), the WD 22 may report a special case of part 1 of the beam prediction report to indicate that the AI / ML model is not working to the network. For example, by using a specific codepoint of one of the bitfields in Part 1 or use a dedicated bitfield. This may allow the network node 16 to switch to legacy (non- AI / ML) based beam management.

[0183] In some embodiments, the WD 22 only reports a probability in part 1 on whether a new beam is better than the previous beam. The “previous” beam may be defined as the best beam in a previous beam prediction or measurement report or beam used for WD data reception on a physical downlink shared channel (PDSCH). This may allow the network node 16 to understand the likelihood that the WD 22 will achieve similar performance as in a previous time instance. One example is illustrated in FIG. 15.

[0184] For time-domain beam prediction, one or more predicted beams and associated performance metric(s), may be reported for each of F future time instances.

[0185] In some embodiments, the first part (part 1) of the beam prediction report indicates information (e.g., beam index and one or more associated performance metric(s)) only for the first future time instance. The information related to later future time instances are included in part 2 (since this information is less latency sensitive). Note that Part 1 also may include information about what content is included in Part 2. In some embodiments, the first part of the beam prediction report includes the number of beams per future time instance reported in the second part (Part 2) of the beam prediction report.

[0186] In some embodiments, the first part of the beam prediction report contains_per future time instance a beam ID (for the best beam), probability that this beam is the best beam and then an additional bitfield that indicates the number of additional beams indexes (and potentially the associated performance metrics to these beam indexes). One example of how this may look is illustrated in FIG. 16, where the number of future time instances (F) is equal to two. In some embodiments, other performance metrics are included for one or more of the reported beams either in Parti and / or Part2, like e.g., predicted absolute RSRP and / or predicted relative RSRP.

[0187] It is noted that the information fields may be arranged in other orders than that illustrated in FIG. 16. For instance, the fields may be arranged such that for each beam j reported, information about beam j are clustered together as a unit. For example, {Beam index #j; probability that Beam #j is best beam}, if the probability information is reported for each beam. Alternatively, {Beam index #j; Ll-RSRP of Beam # } if RSRP information is reported for each beam. This may be beneficial when discarding is applied, where information about beam j is discarded as a unit.

[0188] Not all the bitfields need be included in the report. Other bitfields may be included in the report and that the exact order of the bitfields within each CSI part may differ.

[0189] In some embodiments, the WD 22 only reports beams for a future time window in case there is a beam update for that future time window compared to the previous time window. In this case, the number of reported future time windows is indicated in Part 1 of the beam prediction report.

[0190] In some embodiments, the WD 22 reports a validity of the prediction of a future time instance, or an indication that the prediction is valid until next future time-instance predicted value. This is useful for the network node 16 to understand for how long the network node 16 may rely on a predicted value, in particular when the network node 16 only receives as single future time-instance prediction (the network node 16 needs to understand the “time-window”). The WD 22 may for example report a time-window in absolute time (e.g., milliseconds), or using LTE / NR measurement time unit, or using slotnumber or other LTE / NR time measurement.

[0191] In some embodiments, a bitfield indicating which of the future time windows that are included in the beam prediction report is indicated. In some embodiments, a bitfield with length equal to configured maximum number of reported future time instances minus 1 is included (since predicted beams for first future time window always may be included in the report), and each bit in the bitfield is associated with one future time window, and if the bit is a 1, then the associated future time window is included in the report, and if a bit is zero, than the associated future time window is not included in the report. One example of this is illustrated in FIG. 17, where the maximum number of future time windows is equal to 4, and the bitfield “Additional future time windows reported” is a 3 bits bitfield indicating which of the second, third and fourth future time window that is included in the report. So, for example, if the bitfield is set to ‘ 101’, then Part2 of the beam prediction report contains information about the second future time window and the fourth future time window, but information related to the third future time window is omitted. The reason for omitting the information related to the third future time window may be that the predicted beam probabilities has changed less than a threshold compared to the predicted beams for the second future time window.

[0192] In some embodiments, the indication of the number of reported future time windows in Part 2 is embedded in the bitfield indicating the number of beams in part 2 for that time window. In a related embodiment, a special value of the bitfield indicating the number of beams in part 2 for that time window is assigned to indicate that the network node 16 may assume that there is no update in the beam prediction information as compared to prior time window.

[0193] In some embodiments, when the maximum number of future time windows is equal to 4, and the bitfield “number of beams in part 2 for F = 2” and bitfield “number of beams in part 2 for F = 3” are set to -1 (or to another dedicated codepoint of the bitfield). The prediction report contains information about the fourth future time window, but information related to the second and third future time window is omitted. The network node 16 may assume that information related to the second and third future time window are the same as the first time window.

[0194] Not all the bitfields need to be included in the report. Other bitfields may be included in the report and that the exact order of the bitfields within each CSI part may differ.

[0195] The text, “if reported” in Parti, is present in case the number of future time instances is configurable. So, for example, if the WD 22 is configured with reporting predicted beams for maximum one future time instance, the fields with “if reported” in Parti may be omitted. The length of the bitfield “Additional future time windows reported” will in this case be equal to zero bits, and may be omitted as well. As will be appreciated by one of skill in the art, the concepts described herein may be embodied as a method, data processing system, computer program product and / or computer storage media storing an executable computer program. Accordingly, the concepts described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects all generally referred to herein as a “circuit” or “module.” Any process, step, action and / or functionality described herein may be performed by, and / or associated to, a corresponding module, which may be implemented in software and / or firmware and / or hardware. Furthermore, the disclosure may take the form of a computer program product on a tangible computer usable storage medium having computer program code embodied in the medium that may be executed by a computer. Any suitable tangible computer readable medium may be utilized including hard disks, CD-ROMs, electronic storage devices, optical storage devices, or magnetic storage devices.

[0196] Some embodiments are described herein with reference to flowchart illustrations and / or block diagrams of methods, systems and computer program products. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer (to thereby create a special purpose computer), special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0197] These computer program instructions may also be stored in a computer readable memory or storage medium that may direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function / act specified in the flowchart and / or block diagram block or blocks.

[0198] The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0199] It is to be understood that the functions / acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality / acts involved. Although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that communication may occur in the opposite direction to the depicted arrows.

[0200] Computer program code for carrying out operations of the concepts described herein may be written in an object oriented programming language such as Python, Java® or C++. However, the computer program code for carrying out operations of the disclosure may also be written in conventional procedural programming languages, such as the "C" programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer. In the latter scenario, the remote computer may be connected to the user's computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0201] Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, all embodiments may be combined in any way and / or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and subcombinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or subcombination.

[0202] In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. A variety of modifications and variations are possible in light of the above teachings. List of embodiments:

[0203] Embodiment Al . A network node configured to communicate with a wireless device (WD), the network node configured to, and / or comprising a radio interface and / or comprising processing circuitry configured to: receive at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information may be reported by the WD in the second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and select for subsequent transmission to the WD at least one beam of the first beam and a beam for which the beam information is reported by the WD.

[0204] Embodiment A2. The network node of Embodiment Al, wherein the first part of the two part beam prediction report includes identifies a best beam and a probability associated with the best beam.

[0205] Embodiment A3. The network node of any of Embodiments Al and A2, wherein the second part of the two part beam prediction report includes a number M of best beams and a number N of weakest beams.

[0206] Embodiment A4. The network node of any of Embodiments A1-A3, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam.

[0207] Embodiment A5. The network node of any of Embodiments A1-A4, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a weakest beam.

[0208] Embodiment Bl. A method implemented in a network node, the method comprising: receiving at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information may be reported by the WD in the second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and selecting for subsequent transmission to the WD at least one beam of the first beam and a beam for which the beam information is reported by the WD.

[0209] Embodiment B2. The method of Embodiment Bl, wherein the first part of the two part beam prediction report includes identifies a best beam and a probability associated with the best beam.

[0210] Embodiment B3. The method of any of Embodiments Bl and B2, wherein the second part of the two part beam prediction report includes a number M of best beams and a number N of weakest beams.

[0211] Embodiment B4. The method of any of Embodiments B 1-B3, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam.

[0212] Embodiment B5. The method of any of Embodiments B 1-B4, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a weakest beam.

[0213] Embodiment Cl . A wireless device (WD) configured to communicate with a network node, the WD configured to, and / or comprising a radio interface and / or processing circuitry configured to: configure at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information may be reported by the WD in the second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and transmit at least the first part of the two part beam prediction report.

[0214] Embodiment C2. The WD of Embodiment Cl, wherein the first part of the two part beam prediction report includes identifies a best beam and a probability associated with the best beam. Embodiment C3. The WD of any of Embodiments Cl and C2, wherein the second part of the two part beam prediction report includes a number M of best beams and a number N of weakest beams.

[0215] Embodiment C4. The WD of any of Embodiments C1-C3, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam.

[0216] Embodiment C5. The WD of any of Embodiments C1-C4, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a weakest beam.

[0217] Embodiment DI . A method implemented in a wireless device (WD), the method comprising: configuring at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information may be reported by the WD in the second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and transmitting at least the first part of the two part beam prediction report.

[0218] Embodiment D2. The method of Embodiment DI, wherein the first part of the two part beam prediction report includes identifies a best beam and a probability associated with the best beam.

[0219] Embodiment D3. The method of any of Embodiments DI and D2, wherein the second part of the two part beam prediction report includes a number M of best beams and a number N of weakest beams.

[0220] Embodiment D4. The method of any of Embodiments D1-D3, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam. Embodiment D5. The method of any of Embodiments D1-D4, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a weakest beam.

Claims

CLAIMS1. A wireless device, WD, (22) configured to communicate with a network node, the WD comprising processing circuitry configured to: configure a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to be reported by the WD in a second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and transmit the first part of the two part beam prediction report.

2. The WD of claim 1, wherein the first part of the two part beam prediction report indicates a best beam based on reference signal received power (RSRP) values and a probability that the first beam is the best beam.

3. The WD of any claims 1-2, wherein the first part of the two part beam prediction report indicates a predicted RSRP associated with the first beam.

4. The WD of any of claims 1-3, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam.

5. The WD of any of the claims 1-4, where the second part of the two part beam report includes one or more of the following information for each of the one or more of the number of beams for which beam information is to be reported by the WD the reported beams in the second part of the two part beam reportBeam indexProbability of a beam being the best beamPredicted RSRP for a beam.

6. The WD of any of the claims 1-5, wherein the first part of the two part beam prediction report indicates a number of additional beams for each of multiple future time instances included in the second part of the two part beam prediction report.

7. The WD of any of the claims 1-6, wherein the first part of the two part beam prediction report indicates a number of future time instances included in the second part of the two part beam prediction report.

8. The WD of claim 7, wherein the first part of the two part beam prediction report indicates which future time instances that are included in the second part of the two part beam prediction report.

9. The WD of any of claims 6-8, where the second part of the two part beam prediction report, includes one or more of the following information for each of the reported beams for one or more of the future time instancesBeam indexProbability of a beam being the best beamPredicted RSRP for a beam.

10. A method implemented in a wireless device WD that is configured to communicate with a network node, the method comprising: configuring (SI 38) a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to be reported by the WD in a second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and transmitting (S140) the first part of the two part beam prediction report.

11. The method of claim 10, wherein the first part of the two part beam prediction report indicates a best beam based on reference signal received power (RSRP) values and a probability that the first beam is the best beam.

12. The method of any of the claims 10-11, wherein the first part of the two part beam prediction report indicates a predicted RSRP associated with the first beam.

13. The method of any of claims 10-12, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam.

14. The method of any of claims 10-13, where the second part of the two part beam report includes one or more of the following information for each of the number of beams for which beam information is to be reported by the WDBeam index- Probability of abeam being the best beam- Predicted RSRP for a beam.

15. The method of any of the claims 10-14, wherein the first part of the two part beam prediction report indicates a number of additional beams for each of multiple future time instances included in the second part of the two part beam prediction report.

16. The method of any of the claims 10-15, wherein the first part of the two part beam prediction report indicates a number of future time instances included in the second part of the two part beam prediction report.

17. The method of claim 16, wherein the first part of the two part beam prediction report indicates which future time instances that are included in the second part of the two part beam prediction report.

18. The method of any of claims 16-17, where the second part of the two part beam prediction report, includes one or more of the following information for each of the reported beams for one or more of the future time instancesBeam index- Probability of a beam being the best beam- Predicted RSRP for a beam.

19. A computer program comprising program code to be executed by processing circuitry of a wireless device (22), whereby execution of the program code causes the communication device to perform operations comprising: configuring (SI 38) a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to be reported by the WD in a second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; andtransmitting (S140) the first part of the two part beam prediction report.

20. The computer program of Claim 19 the operations further comprising any of the steps of Claims 11-18.

21. A computer program product comprising a storage medium comprising program code to be executed by processing circuitry of a wireless device (22), whereby execution of the program code causes the communication device to perform any of the methods of Claims 10-18.

22. A network node (16) configured to communicate with a wireless device, WD, (22) the network node comprising processing circuitry configured to: receive a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam, information is to be reported by the WD in a second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and select for subsequent transmission to the WD at least one beam as the first beam configured in the first part of the two part beam prediction report and a beam for which the beam information is reported by the WD in the second part of the two part beam prediction report.

23. The network node of claim 22, wherein the first part of the two part beam prediction report indicates a best beam based on reference signal received power (RSRP) values and a probability that the first beam is the best beam.

24. The network node of any of claims 22 or 23, wherein the first part of the two part beam prediction report indicates a predicted RSRP associated with the first beam.

25. The network node of any of claims 22-24, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam.

26. The network node of any of the claims 22-25, where the second part of the two part beam report includes one or more of the following information for each of the number of beams for which beam information is to be reported by the WD the reported beams in the second part of the two part beam reportBeam indexProbability of a beam being the best beam Predicted RSRP for a beam.

27. The network node of any of the claims 22-26, wherein the first part of the two part beam prediction report indicates a number of additional beams for each of multiple future time instances included in the second part of the two part beam prediction report.

28. The network node of any of the claims 22-27, wherein the first part of the two part beam prediction report indicates a number of future time instances included in the second part of the two part beam prediction report.

29. The network node of claim 28, wherein the first part of the two part beam prediction report indicates which future time instances that are included in the second part of the two part beam prediction report.

30. The network node of any of claims 28-29, where the second part of the two part beam prediction report, includes one or more of the following information for each of the reported beams for one or more of the future time instances• Beam index• Probability of a beam being the best beam• Predicted RSRP for a beam.

31. A method implemented in a network node that is configured to communicate with a wireless device, the method comprising: receiving (SI 34) at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to be reported by the WD in a second part of the two part beamprediction report, the second part of the two part beam prediction report being variable in size; and selecting (S136) for subsequent transmission to the WD at least one beam as the first beam configured in the first part of the two part beam prediction report and a beam for which the beam information is reported by the WD in the second part of the two part beam prediction report.

32. The method of claim 31, wherein the first part of the two part beam prediction report indicates a best beam based on reference signal received power (RSRP) values and a probability that the first beam is the best beam.

33. The method of any of claims 31 or 32, wherein the first part of the two part beam prediction report indicates a predicted RSRP associated with the first beam.

34. The method of any of claims 31-33, wherein the number of beams for which beam information is to be reported by the WD is based at least in part on an accumulated probability of a best beam.

35. The method of any of the claims 31-33, where the second part of the two part beam report includes one or more of the following information for each of the number of beams for which beam information is to be reported by the WD the reported beams in the second part of the two part beam reportBeam indexProbability of a beam being the best beamPredicted RSRP for a beam.

36. The method of any of the claims 31-35, wherein the first part of the two part beam prediction report indicates a number of additional beams for each of multiple future time instances included in the second part of the two part beam prediction report.

37. The method of any of the claims 31-36, wherein the first part of the two part beam prediction report indicates a number of future time instances included in the second part of the two part beam prediction report.

38. The method of claim 37, wherein the first part of the two part beam prediction report indicates which future time instances that are included in the second part of the two part beam prediction report.

39. The method of any of claims 37-38, where the second part of the two part beam prediction report, includes one or more of the following information for each of the reported beams for one or more of the future time instances• Beam index• Probability of a beam being the best beam• Predicted RSRP for a beam.

40. A computer program comprising program code to be executed by processing circuitry of a network node (16), whereby execution of the program code causes the communication device to perform operations comprising: receiving (SI 34) at least a first part of a two part beam prediction report, the first part of the two part beam prediction report being fixed in size and configured to include transmit beam information for a first beam and an indication of a number of beams for which beam information is to be reported by the WD in a second part of the two part beam prediction report, the second part of the two part beam prediction report being variable in size; and selecting (S136) for subsequent transmission to the WD at least one beam as the first beam configured in the first part of the two part beam prediction report and a beam for which the beam information is reported by the WD in the second part of the two part beam prediction report.

41. The computer program of Claim 40 the operations further comprising any of the steps of Claims 32-39.

42. A computer program product comprising a storage medium comprising program code to be executed by processing circuitry of a network node (16), whereby execution of the program code causes the communication device to perform any of the methods of Claims 31-39.

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