Prediction related assistance information

Abstract

Embodiments of a method in a first network node, the method includes receiving, from a second node, predictions relating to one or more metrics, and receiving, from the second node, prediction assistance information relating to the predictions. The first network node may perform one or more management tasks based at least in part on the received predictions and received prediction assistance information.

Description

Prediction related assistance informationTechnical Field

[0001] The present disclosure relates to data collection in a radio access network, and in particular to data collection methods utilizing prediction related assistance information. BackgroundData Collection Reporting for collecting predictions

[0002] In 3GPP Release 18 (Rel-18), RAN3 introduced new XnAP procedures to request and obtain predicted information pertaining to various metrics (such as, for example Radio Resource Status, Number of Active UEs, Number of RRC Connections etc.), namely the Data Collection Reporting Initiation and the Data Collection Reporting procedures. The procedures work in tandem: with the Data Collection Reporting Initiation procedure, an NG-RAN node 1 sends to an NG-RAN node 2 a DATA COLLECTION REQUEST XnAP message, indicating a request for the reporting of information to support, e.g., AI / ML in NG-RAN. The granularity for which a piece of information is requested by NG-RAN node 1 and reported by NG-RAN node 2 is modeled as a “measured object” (for example, a cell, or a gNB, or a UE). For a certain measured object, the NG-RAN node 1 can request to obtain a number of predictions from NG-RAN node 2, for instance the Predicted Number of Active UEs and the Predicted RRC Connections.

[0003] The NG-RAN node 2 sends the requested predictions to the NG-RAN node 1 using the DATA COLLECTION UPDATE message specified for the Data Collection Reporting procedure.

[0004] Upon reception of the DATA COLLECTION REQUEST message, the NG-RAN node 2 shall initiate the requested information reporting according to the parameters given in the request in case the Registration Request for Data Collection IE is set to "start"; or the NG-RAN node 2 shall stop all measurements and predictions and terminate the reporting in case the Registration Request for Data Collection IE is set to "stop".

[0005] If the Reporting Periodicity for Data Collection IE is present in the DATA COLLECTION REQUEST message, this indicates the periodicity for the reporting of configured measurement objects. The NG-RAN node 2 shall report only once, unless otherwise requested within the Reporting Periodicity for Data Collection IE.

[0006] If the Requested Prediction Time IE is present in the DATA COLLECTION REQUEST message, it indicates the specific point in time to which the prediction of the requested information applies. The NG-RAN nod 2 shall take it into account when generating the requested predicted information.

[0007] The current definitions for Reporting Periodicity for Data Collection IE and Requested Prediction Time IE are shown in the table of FIG. 1 (ref: TS 38.423, vl8.4.0)

[0008] There currently exist certain challenge(s). One problem with the existing solution is that when predictions are sent from a network node to another network node, there is no consideration on any possible relation between a prediction sent at time T1 and another prediction sent at a time T2>T1. The sender may have produced the prediction sent at time T2 in light of pieces of information that were not available when the prediction sent at time T1 was generated.

[0009] For instance, a first prediction sent at time T1 is generated with the knowledge that at Tl+30 seconds a certain cell will be inactive. But when the second prediction, sent at time T2 is generated, the producer of the prediction has the opposite information, i.e., that at Tl+30 seconds the same cell will instead be active. The sender cannot tell this information to the receiver, it will just send a second prediction, which, from the perspective of the receiver, is independent from the previous one.

[0010] With the current solution, the network node that initiated a request to receive predictions, according to a certain periodicity, may take decisions (e.g., mobility decisions) based on invalid data (more specifically based on invalid predictions).

[0011] Referring to FIG. 2, we provide an example of limitation in current specification. A first network node, gNBl, has requested periodic predictions to a second network node, gNB2. At time tl, gNB2 sends a first DATA COLLECTION UPDATE message with a Predicted Radio Resource Status “X” which refers to tl+30 seconds. If the Reporting Periodicity for Data Collection is 5 seconds, at time t2=tl+5 seconds, gNB2 sends a second prediction which refers to 11+30+5 seconds.

[0012] However, in the time interval between tl and 11 +5 s, events may happen that can invalidate the prediction signaled at time tl . For example, if gNB2 generated a Predicted Radio Resource Status IE for a given cell, it might happen that some neighbour cell is deactivated after the prediction is generated, hence changing the conditions on the basis of which the prediction on cell load was calculated. In this case, the prediction signaled bygNB2 at time tl is invalid, but the receiving node does not know that, and it operates believing that the prediction is still good.

[0013] As an example, the future load on gNB2 cell could be much higher than what was stated by the prediction generated at time tl (for prediction time 11+3 Os) . This may result in wrong mobility actions from gNBl towards gNB2’s cell with consequent performance degradation and possible failures.

[0014] In the situation described, the problem is the following: a RAN node (node 1) that requested periodic predictions for a specific metric from a neighbor RAN node (node 2), receives periodic metric predictions referring to prediction times in the future. Even if it becomes known to the node generating the predictions, i.e., node 2, that the network conditions on the basis of which a prediction in the future was derived have changed to the point that such prediction is invalid, it is not possible for such node to inform node 1 that an already signaled prediction is invalid, or that it is inaccurate.Summary

[0015] Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges.

[0016] In the disclosed solution, a first network node that receives predictions on one or more metrics from a second network node (typically on the basis of a subscription initiated by the first network node), also receives assistance information on predictions, in particular if one or more of the previously received predictions are not valid anymore. In one option of the solution, the assistance information on predictions is an information provided with a per-metric granularity, i.e., the first network node receives the information whether previously received prediction(s) for a given metric (or object) is(are) not valid anymore, i.e., the previous prediction(s) is(are) cancelled.

[0017] Accordingly, an aspect of this disclosure provide a method performed by a second network node for sending predictions to a first network node, the predictions relating to one or more metrics, the method comprising the second network node sending, to the first network node, prediction assistance information relating to the predictions.

[0018] In some embodiments, sending the prediction assistance information to the first network node comprises sending a Data Collection Update message containing predictions and prediction assistance information relating to predictions contained in a previously sent Data Collection Update message.

[0019] In some embodiments, the prediction assistance information has a granularity corresponding to any one of:• per metric;• per reporting period;• per reporting object;• per reporting message.

[0020] In some embodiments, the prediction assistance information comprises a bit string or a bitmap, wherein each bit of the bit string or a bitmap corresponds to a respective metric, and a value of each bit indicates whether or not a previously sent prediction relating to the respective metric is still valid.

[0021] In some embodiments, the prediction assistance information comprises any one or more of:• an indication that a previously sent prediction is still valid; and• an indication that the previously sent prediction is not valid or is cancelled.

[0022] In some embodiments, the indication comprises an identifier of a first message containing the previously sent prediction. The identifier may comprise any one or more of:• a sequence number associated with either the first message or the previously sent prediction;• a hash of the first message;• a name associated with the previously sent prediction; and• a count value indicative of a number of successive messages sent after the first message.

[0023] A further aspect of this disclosure provides a method performed by a first network node. The method comprises: receiving, from a second node, predictions relating to one or more metrics; receiving, from the second node prediction assistance information relating to the predictions; and performing one or more management tasks based at least in part on the received predictions and received prediction assistance information.

[0024] In some embodiments, the prediction assistance information a granularity corresponding to any one of:• per metric;• per reporting period;• per reporting object;• per reporting message.

[0025] In some embodiments, the prediction assistance information comprises any one or more of:• an indication that a previously sent prediction is still valid; and• an indication that the previously sent prediction is not valid or is cancelled.

[0026] In some embodiments, the prediction assistance information comprises a bit string or a bitmap, wherein each bit of the bit string or a bitmap corresponds to a respective metric, and a value of each bit indicates whether or not a previously sent prediction relating to the respective metric is still valid.

[0027] Certain embodiments may provide one or more of the following technical advantage(s). One advantage of the proposed solution is to enable more accurate decisions taken by network entities (e.g., decisions related to mobility or network energy saving) when predictions are used in the decision process. The teachings of certain embodiments may improve any one or more of the data rate, latency, and power consumption of the network.Brief Description of the Drawings

[0028] The accompanying drawing figures incorporated in and forming a part of this specification illustrate several aspects of the disclosure, and together with the description serve to explain principles of the disclosure.

[0029] FIG. 1 is a table showing current definitions for Reporting Periodicity for Data Collection IE and Requested Prediction Time IE known from TS 38.423, vl8.4.0;

[0030] FIG. 2 shows an example of where a first network node receiving predictions from a second network node can take a wrong decision because the received prediction is no longer valid;

[0031] FIG. 3 an example message flow in accordance with embodiments of the present disclosure;

[0032] FIG. 4 is a flow chart showing an example method in a node in accordance with embodiments of the present disclosure;

[0033] FIG. 5 illustrates an example operation in accordance with embodiments of the present disclosure;

[0034] FIG. 6 shows an example of a communication system in accordance with some embodiments;

[0035] FIG. 7 shows a UE in accordance with some embodiments;

[0036] FIG. 8 shows a network node in accordance with some embodiments;

[0037] FIG. 9 is a block diagram illustrating a virtualization environment in which functions implemented by some embodiments may be virtualized.Detailed Description

[0038] Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0039] At least some of the following abbreviations and terms may be used in this disclosure.

[0040] Radio Node: As used herein, a “radio node” is either a radio access node or a wireless device.

[0041] Radio Access Node: As used herein, a “radio access node” or “radio network node” is any node in a radio access network of a cellular communications network that operates to wirelessly transmit and / or receive signals. Some examples of a radio access nodeinclude, but are not limited to, a base station (e.g., a New Radio (NR) base station (gNB) in a Third Generation Partnership Project (3GPP) Fifth Generation (5G) NR network or an enhanced or evolved Node B (eNB) in a 3GPP Long Term Evolution (LTE) network), a high-power or macro base station, a low-power base station (e.g., a micro base station, a pico base station, a home eNB, or the like), and a relay node.

[0042] Core Network Node: As used herein, a “core network node” is any type of node in a core network. Some examples of a core network node include, e.g., a Mobility Management Entity (MME), a Packet Data Network Gateway (P-GW), a Service Capability Exposure Function (SCEF), or the like.

[0043] Wireless Device: As used herein, a “wireless device” is any type of device that has access to (i.e., is served by) a cellular communications network by wirelessly transmitting (and / or receiving) signals to (and / or from) a radio access node. Some examples of a wireless device include, but are not limited to, a User Equipment device (UE) in a 3GPP network and a Machine Type Communication (MTC) device.

[0044] Network Node: As used herein, a “network node” is any node that is either part of the radio access network or the core network of a cellular communications network / system.

[0045] Cell: As used herein, a “cell” is a combination of radio resources (such as, for example, antenna port allocation, time and frequency) that a wireless device may use to exchange radio signals with a radio access node, which may be referred to as a host node or a serving node of the cell. However, it is important to note that beams may be used instead of cells, particularly with respect to 5G NR. As such, it should be appreciated that the techniques described herein are equally applicable to both cells and beams.

[0046] Note that references in this disclosure to various technical standards (such as 3GPP TS 38.211 V15.1.0 (2018-03) and 3GPP TS 38.214 V15.1.0 (2018-03), for example) should be understood to refer to the specific version(s) of such standard(s) that is(were) current at the time the present application was filed, and may also refer to applicable counterparts and successors of such versions.

[0047] The description herein focuses on a 3GPP cellular communications system and, as such, 3GPP terminology or terminology similar to 3GPP terminology is oftentimes used. However, the concepts disclosed herein are not limited to a 3GPP system.

[0048] The methods described herein can be applied without any loss of meaning to any network signaling interface, e.g., for NG-RAN to XnAP, F1AP, E1AP, NGAP, and to any Radio Access Technology, e.g., 5G and 6G.

[0049] As non-limiting examples, a network node can be a gNB, an NG-RAN node, a gNB-DU, a gNB-CU, a gNB-CU-CP, a gNB-CU-UP, a 6G node, an eNB, an ng-eNB, a Core Network node (e.g., an AMF, an UPF, an SMF, an NWDAF), an O-CU, an 0-DU, an O-gNB, an 0-RU, a Near-Real Time Radio Intelligent Controlled (Near-RT RIC), a Non Real Time RIC; an SMO. Also note that the first network node and the second network node may be of the same type or different types. For instance, both first and second network nodes can be a gNB-CU, but it could also be that the first network node is a gNB-CU and the second network node is a gNB-DU. No combination is precluded.

[0050] Systems and methods are disclosed herein that provide for the exchange, between network nodes, of additional information concerning predictions which have been previously sent between the nodes. Thus, referring to FIG. 3, a first network node (e.g Node 1) may optionally subscribe to receive predictions about one or more metrics from a second network node (e.g. Node 2). Accordingly, Node 2 periodically sends the predictions to Node 1. In addition, Node 2 sends assistance information on predictions (also referred to herein as prediction assistance information) pertaining to previously sent predictions.

[0051] Accordingly, referring to FIG. 4, this disclosure provides a method in a first node (i.e. Node 1), comprising:• receiving, from a second node (i.e. Node 2), predictions relating to one or more metrics;• receiving, from the second node prediction assistance information relating to the predictions; and• performing one or more management tasks based at least in part on the received predictions and received prediction assistance information.

[0052] In one embodiment, the first network node receives a FIRST MESSAGE from the second network node comprising predictions for one or more metrics (e.g., Ml, M2, ... Mn), together with assistance information on predictions (also referred to herein as prediction assistance information) providing additional information concerning previous predictions which the second network node sent to the first network node for the one or more metrics before the FIRST MESSAGE.

[0053] For example, the first network node (e.g., NG-RAN node 1) receives a FIRST MESSAGE (e g., a DATA COLLECTION UPDATE XnAP message) which comprises two parts:• predicted values of one or more metrics Ml, M2, M3, ... Mn (e.g., Ml=Predicted Radio Resource Status, M2=Predicted Number of Active UEs, M3=Predicted RRC Connections).• assistance information on predictions - for example realized with new information element (e.g., a Prediction Characteristics IE) - providing additional information on predictions for the one or more metrics which were sent by the second network node to the first network node in a message preceding the FIRST MESSAGE.

[0054] In one option, the assistance information on predictions is a per-metric information and indicates whether the last prediction of each metric Ml, M2, ... Mn which the second network node sent to the first network node before the FIRST MESSAGE is not valid (or inaccurate).

[0055] In one option, the assistance information on predictions is a per-metric information and indicates whether, for a certain subset of the metrics included in the FIRST MESSAGE (e.g., for metrics Ml and M2, but not for M3), the corresponding last prediction sent from the second network node to the first network node before the FIRST MESSAGE is not valid anymore.• In a possible implementation, the assistance information on predictions is realized by a single Information Element (IE), for instance as a bit string or a bitmap, where the bit in position “i” is associated to one and only one predicted metric Mi and the value of the i-th bit indicates whether the last prediction sent by the second network node to the first network node for the metric Mi is not valid anymore.• In another possible implementation, the assistance information on predictions is realized by multiple Information Elements (IE), each IE indicating whether the last prediction sent for a certain metric is not valid anymore.

[0056] In one option, the assistance information on predictions is a per-metric information and indicates whether, for a certain subset of the metrics included in the FIRST MESSAGE (e.g., for metrics Ml and M2, but not for M3) a certain number of predictionssent from the second network node to the first network node before the FIRST MESSAGE are not valid anymore.• In a possible implementation, the assistance information on predictions is a per- metric information and is realized by an Information Elements (IE) comprising a sequence of two sub-IEs, where:• a first sub-IEs is a bitmap, where the bit in position “i” is associated to one and only one predicted metric Mi and the value of the i-th element indicates whether at least one of the previous predictions sent by the second network node to the first network node for the metric Mi are not valid anymore• a second sub-IEs is a list of elements (e.g., a list of INTEGER) where the i-th element indicates a number of previous predictions for metric Mi that the second network node sent to the first network node and are not valid anymore

[0057] In one option, the assistance information on predictions is a per-metric information and indicates whether the predictions for the one or more metrics included in the FIRST MESSAGE replace (or override, or update) the last prediction (or a number N of predictions) sent from the second network node to the first network node before the FIRST MESSAGE.• In a possible implementation, the assistance information on predictions is realized by a single Information Element (IE), for instance as a bit string or a bitmap, where the bit in position “i” is associated to one and only one predicted metric Mi and the value of the i-th bit indicates whether the last prediction sent by the second network node to the first network node for the metric Mi is replaced by the prediction for the same metric in the FIRST MESSAGE.• In another possible implementation, the assistance information on predictions is realized by multiple Information Elements (IE), each IE indicating whether the last prediction sent for a certain metric is replaced by the prediction for the same metric in the FIRST MESSAGE.• In a possible implementation, the assistance information on predictions is a per- metric information and is realized by an Information Elements (IE) comprising a sequence of two sub-IEs, where:• a first sub-IEs is a bitmap, where the bit in position “i” is associated to one and only one predicted metric Mi and the value of the i-th element indicates whetherat least one of the previous predictions sent by the second network node to the first network node for the metric Mi replaced by the prediction for the same metric in the FIRST MESSAGE• a second sub-IEs is a list of elements (e.g., a list of INTEGER) where the i-th element indicates a number of previous predictions for metric Mi that the second network node sent to the first network node and that are replaced by the prediction for the same metric in the FIRST MESSAGE

[0058] In one option, the assistance information on predictions is an indication stating that the whole set of last sent predictions is not valid (or inaccurate).

[0059] For instance, the first network node received from the second network node a first, second, ... (N-l) DATA COLLECTION UPDATE messages containing respectively a first, second, (N-l)th prediction for one or more metrics (e.g., Ml, ... Mn). Then, the first network node receives from the second network node an Nth DATA COLLECTION UPDATE message containing an Nth prediction for the same metrics, and an indication, indicating that the following is cancelled, or that the Nth prediction of each metric (Ml, ... Mn) supersedes, or overrides, or updates one of the following:• the last (i.e., the (N-l)th) prediction of the respective metrics,• any of the prediction received before the Nth prediction (for the respective metric)• all the predictions received before the Nth prediction (for the respective metric) • a set of predictions received before the Nth prediction (e.g., the first and the second prediction)

[0060] An example of the method is illustrated in FIG. 5. The first network node is gNBl, the second network node is gNB2. The gNB2 generates prediction “X” and sends it to gNBl at time Tl. After Tl, something happens, e.g., network conditions at gNB2 or gNBl which invalidate the prediction generated at Tl. The second network node (gNB2) sends to the first network node (gNBl) another prediction “Y”, e.g., according to a periodicity of 5 seconds stipulated in the subscription request issued by the gNB 1. The second prediction “Y” is sent together with an indication, indicating that prediction “X” is not valid anymore. The gNBl can take this into account in its decisions.

[0061] In one embodiment, a first network node sends a SECOND MESSAGE to a second network node, which comprises:• (legacy) a first indication indicating a request to obtain from the second network node predictions for one or more metrics (e.g., Ml, M2, ... Mn), and • (new) a second indication to receive per-metric assistance information on previous predictions.

[0062] For example, an NG-RAN node 1 sends a DATA COLLECTION REQUEST XnAP message to NG-RAN node 2 and the DATA COLLECTION REQUEST message includes a (legacy) Report Characteristics for Data Collection IE to request metrics Ml, M2, ... Mn, and a (new) Prediction Characteristics Request IE

[0063] In one embodiment, a first network node receives from a second network node assistance information on predictions consisting of a timing indication, indicating a reference time in the past until when preceding prediction(s) of a metric M is(are) not valid anymore, or superseded, or overridden, or canceled, or updated by a new prediction. The first network node may receive the assistance information on predictions and the new prediction to which the indication refers from the second network node in the same message or in different messages.

[0064] In one extension of the previous embodiments, the first network node receives from the second network node timing indication(s) referred to predictions of more than one metric.Embodiments for referring / pointing to a previously provided prediction

[0065] In this set of embodiments, the second network node (which provides prediction(s) to the first network node via a series of periodic DATA COLLECTION UPDATE messages) can provide one or more of the following assistance information on predictions:• a sequence number to each DATA COLLECTION UPDATE message in the series of periodic messages,• a hash, e.g., calculated by the second network node and added to the DATA COLLECTION UPDATE message which the second network node sends to the first network node,• a sequence number to each prediction in a series of predictions provided via a sequence of periodic DATA COLLECTION UPDATE messages, e.g., DATA COLLECTION UPDATE (PredictionA[l]), DATA COLLECTION UPDATE (PredictionA[2]),..., DATA COLLECTION UPDATE (PredictionA[n]),

[0066] Later in time, when the second network node wants to indicate as not valid, or overwrite, or cancel a prediction previously sent to the first network node, it can send to the first network node a DATA COLLECTION UPDATE message containing a pointer to the prediction to be made invalid, or to be replaced, or to be canceled. This pointer can consist of:• The sequence number of the message that contained the prediction and the name of the prediction, e.g. (DATA COLLECTION UPDATE [n], PredictionA), • The hash of the message that carried the prediction and the name of the prediction, e g. (DATA COLLECTION UPDATE [HASH], PredictionA), • The sequence number associated with the initial prediction, e.g., PredictionA [m],

[0067] In another embodiment, the second network node, which provides a series of periodic predictions (e.g., via periodic DATA COLLECTION UPDATE messages) to a first network node), can indicate that a previous prediction is no longer valid (or inaccurate), or can cancel it, or overwrite it, by sending an integer value that points to the particular message were the prediction was sent. The integer value indicates the position, counting backwards from the message where it was received, of the message in question in the series of periodic predictions. For example, an integer value “1” indicates that the prediction to be invalidated, or cancelled, or overwritten, is found in the last message sent, while an integer value “2” indicates that the prediction is found in the previous-to-last message, and so on.

[0068] In a related embodiment, the second network node can indicate that several predictions are no longer valid (or inaccurate), or can cancel them, or overwrite them by sending a list of integer values where each value points to the particular message were one of the predictions was sent, in a similar way as the previous embodiment described.

[0069] In one example the indication can be given by the time Tl+N* Reporting Periodicity for Data Collection that was analyzed above referring to the Requested Prediction Time IE as in Tl+N* Reporting Periodicity for Data Collection the only variable is N and can thus clearly indicate which prediction it refers to.Additional embodiments for indirect indication that some predictions are not valid

[0070] In one embodiment, the first network node determines that certain already received predictions are not valid determining a match between first assistance information on predictions and second assistance information on predictions. For instance, the first andthe second assistance information on predictions consist of an identifier and / or a timestamp which identifies the reporting interval associated to certain predictions. According to this embodiment, there is a first phase during which the first network node receives from a second network node one or more FIRST MESSAGES (e.g., one or more DATA COLLECTION UPDATE messages) comprising predictions AND first assistance information on predictions. In a second phase, the first network node receives from the second network node a THIRD MESSAGE (which can be of the same type of the FIRST MESSAGE, for example a DATA COLLECTION UPDATE) comprising second assistance information on predictions. The first network node determines if first assistance information on predictions is the same as second assistance information on predictions. If the two pieces of information are the same, then the first network node determines that the predictions received for the reporting interval identified by the first / second assistance information on predictions are not valid.Additional embodiments for assistance information on predictions at various granularities.

[0071] In one embodiment, the assistance information on predictions is an information with a per-reporting period / per-reporting interval granularity and indicates that all the predictions of the metrics Ml, M2, ... Mn which the second network node sent to the first network node in relation to one or more reporting intervals are not valid (or inaccurate), or are canceled.• In one option the assistance information on predictions indicates that the predictions related to the reporting interval to which the FIRST MESSAGE refers to are not valid, or canceled• In one option the assistance information on predictions indicates that the predictions related to the last reporting interval before the one to which the FIRST MESSAGE refers to are not valid, or canceled• In one option the assistance information on predictions indicates that the predictions related to the last N (with N>1) reporting intervals, including the reporting interval to which the FIRST MESSAGE refers to, are not valid, or canceled• In one option the assistance information on predictions indicates that the predictions related to the last N (with N>1) reporting intervals before thereported interval to which the FIRST MESSAGE refers to are not valid, or canceled• In one option the assistance information on predictions indicates that the predictions related to certain reporting intervals before and / or including the reported interval to which the FIRST MESSAGE refers to are not valid, or canceled. For example, the assistance information can selectively indicate that predictions related to the 4th to last reporting interval and the 2nd to last reporting interval before the reporting interval to which the FIRST MESSAGE refers to are not valid

[0072] In one embodiment, the assistance information on predictions is an information with a per-reporting object granularity and indicates that all the predictions of the metrics Ml, M2, ... Mn which the second network node sent to the first network node in relation to one or more reporting objects are not valid (or inaccurate), or canceled. Non-limiting examples of object can be: a cell, a network slice, a network node, a set of network slices, a set of cells, a set of SSBs.• In one option the assistance information on predictions indicates that the predictions related to one or more cells to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to one or more cells and which the second network node sent to the first network node in relation to the last reporting interval before the one to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to one or more network slices to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to one or more network slices and which the second network node sent to the first network node in relation to the last reporting interval before the one to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to the second network node to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to the second network node and which the second network node sent to the first network node in relation to the last reporting interval before the one to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to one or more UEs to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to one or more UEs and which the second network node sent to the first network node in relation to the last reporting interval before the one to which the FIRST MESSAGE refers to are not valid, or canceled.• In one option the assistance information on predictions indicates that the predictions related to one or more cells (or to one or more network slices, or to the second network node, or to one or more UEs), and also related to the last N (with N>1) reporting intervals, including the reporting interval to which the FIRST MESSAGE refers to, are not valid, or canceled• In one option the assistance information on predictions indicates that the predictions to one or more cells (or to one or more network slices, or to the second network node, or to one or more UEs), and also related to the last N (with N>1) reporting intervals before the reported interval to which the FIRST MESSAGE refers to are not valid, or canceled• In one option the assistance information on predictions indicates that the predictions related to one or more cells (or to one or more network slices, or to the second network node, or to one or more UEs), and also related to certain reporting intervals before and / or including the reported interval to which the FIRST MESSAGE refers to are not valid, or canceled.Additional embodiments for assistance information on non-periodic predictions

[0073] In one embodiment, which can be combined with other embodiments of the disclosure, the assistance information on predictions which the first network node receives from the second network node, refers to predictions sent from the second network node to the first network node in a non-periodic wayIn one case, predictions were requested to be sent only one time• In one case, predictions were requested upon the second network node detecting a certain event (e.g., an event can be the detection of a CCO issue) • In one case, predictions were requested upon the second network node predicting a certain event (e.g., an event can be the prediction of a CCO issue) • In one case, predictions were requested upon the second network node performing a certain action (e.g., an action can be, the deactivation of a cell, or the activation of a cell)

[0074] FIG. 6 shows an example of a communication system 600 in accordance with some embodiments.

[0075] In the example, the communication system 600 includes a telecommunication network 602 that includes an access network 604, such as a radio access network (RAN), and a core network 606, which includes one or more core network nodes 608. The access network 604 includes one or more access network nodes, such as network nodes 610a and 610b (one or more of which may be generally referred to as network nodes 610), or any other similar 3rdGeneration Partnership Project (3GPP) access nodes or non-3GPP access points. Moreover, as will be appreciated by those of skill in the art, a network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunication network 602 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 602 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other nodes to implement one or more functionalities of any node in the telecommunication network 602, including one or more network nodes 610 and / or core network nodes 608.

[0076] Examples of an ORAN network node include an open radio unit (O-RU), an open distributed unit (O-DU), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller (near-real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). The network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an Al, Fl, Wl, El, E2, X2, Xn interface, anopen fronthaul user plane interface, or an open fronthaul management plane interface.Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the O-RAN Alliance or comparable technologies. The network nodes 610 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs 612a, 612b, 612c, and 612d (one or more of which may be generally referred to as UEs 612) to the core network 606 over one or more wireless connections.

[0077] Example wireless communications over a wireless connection include transmitting and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system 600 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that may facilitate or participate in the communication of data and / or signals whether via wired or wireless connections. The communication system 600 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0078] The UEs 612 may be any of a wide variety of communication devices, including wireless devices arranged, configured, and / or operable to communicate wirelessly with the network nodes 610 and other communication devices. Similarly, the network nodes 610 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs 612 and / or with other network nodes or equipment in the telecommunication network 602 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunication network 602.

[0079] In the depicted example, the core network 606 connects the network nodes 610 to one or more host computing systems, such as host 616. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network 606 includes one more core network nodes (e.g., core network node 608) that are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, network nodes, and / or hosts, such that the descriptions thereof aregenerally applicable to the corresponding components of the core network node 608.Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-concealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0080] The host 616 may be under the ownership or control of a service provider other than an operator or provider of the access network 604 and / or the telecommunication network 602. The host 616 may host a variety of applications to provide one or more service.Examples of such applications include live and pre-recorded audio / video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0081] As a whole, the communication system 600 of FIG. 6 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (WiFi); and / or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, LiFi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox.

[0082] In some examples, the telecommunication network 602 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network 602 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 602. For example, the telecommunications network 602 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing Enhanced Mobile Broadband (eMBB) services to other UEs,and / or Massive Machine Type Communication (mMTC)ZMassive loT services to yet further UEs.

[0083] In some examples, the UEs 612 are configured to transmit and / or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network 604 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 604.Additionally, a UE may be configured for operating in single- or multi-RAT or multistandard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LTE, i.e. being configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network) New Radio - Dual Connectivity (EN-DC).

[0084] In the example, the hub 614 communicates with the access network 604 to facilitate indirect communication between one or more UEs (e.g., UE 612c and / or 612d) and network nodes (e.g., network node 610b). In some examples, the hub 614 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 614 may be a broadband router enabling access to the core network 606 for the UEs. As another example, the hub 614 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes 610, or by executable code, script, process, or other instructions in the hub 614. As another example, the hub 614 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub 614 may be a content source. For example, for a UE that is a VR device, display, loudspeaker, or other media delivery device, the hub 614 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 614 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 614 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0085] The hub 614 may have a constant / persistent or intermittent connection to the network node 610b. The hub 614 may also allow for a different communication scheme and / or schedule between the hub 614 and UEs (e.g., UE 612c and / or 612d), and between the hub 614 and the core network 606. In other examples, the hub 614 is connected to the corenetwork 606 and / or one or more UEs via a wired connection. Moreover, the hub 614 may be configured to connect to an M2M service provider over the access network 604 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 610 while still connected via the hub 614 via a wired or wireless connection. In some embodiments, the hub 614 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node 610b. In other embodiments, the hub 614 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node 610b, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0086] FIG. 7 shows a UE 700 in accordance with some embodiments. The UE 700 presents additional details of some embodiments of the UE 612 of FIG. 6. As used herein, a UE refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes and / or other UEs. Examples of a UE include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage / playback device, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), an Augmented Reality (AR) or Virtual Reality (VR) device, wireless customer-premise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3rd Generation Partnership Project (3GPP), including a narrow band internet of things (NB-loT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0087] A UE may support device -to-de vice (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle -to-everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0088] The UE 700 includes processing circuitry 702 that is operatively coupled via a bus 704 to an input / output interface 706, a power source 708, a memory 710, a communication interface 712, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in FIG. 7. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0089] The processing circuitry 702 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory 710. The processing circuitry 702 may be implemented as one or more hardware-implemented state machines (e.g., in discrete logic, field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs, general-purpose processors, such as a microprocessor or digital signal processor (DSP), together with appropriate software; or any combination of the above. For example, the processing circuitry 702 may include multiple central processing units (CPUs).

[0090] In the example, the input / output interface 706 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into the UE 700. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g., a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, atilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0091] In some embodiments, the power source 708 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricityoutlet), photovoltaic device, or power cell, may be used. The power source 708 may further include power circuitry for delivering power from the power source 708 itself, and / or an external power source, to the various parts of the UE 700 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 708. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 708 to make the power suitable for the respective components of the UE 700 to which power is supplied.

[0092] The memory 710 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 710 includes one or more application programs 714, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 716. The memory 710 may store, for use by the UE 700, any of a variety of various operating systems or combinations of operating systems.

[0093] The memory 710 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD-DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a USIM and / or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 710 may allow the UE 700 to access instructions, application programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory 710, which may be or comprise a device-readable storage medium.

[0094] The processing circuitry 702 may be configured to communicate with an access network or other network using the communication interface 712. The communicationinterface 712 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 722. The communication interface 712 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another UE or a network node in an access network). Each transceiver may include a transmitter 718 and / or a receiver 720 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 718 and receiver 720 may be coupled to one or more antennas (e.g., antenna 722) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0095] In the illustrated embodiment, communication functions of the communication interface 712 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented in according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / intemet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0096] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 712, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0097] As another example, a UE comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts thecontrol surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0098] A UE, when in the form of an Internet of Things (loT) device, may be a device for use in one or more application domains, these domains comprising, but not limited to, city wearable technology, extended industrial application and healthcare. Non-limiting examples of such an loT device are a device which is or which is embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an loT device comprises circuitry and / or software in dependence of the intended application of the loT device in addition to other components as described in relation to the UE 700 shown in FIG. 7.

[0099] As yet another specific example, in an loT scenario, a UE may represent a machine or other device that performs monitoring and / or measurements, and transmits the results of such monitoring and / or measurements to another UE and / or a network node. The UE may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3GPP NB-IoT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0100] In practice, any number of UEs may be used together with respect to a single use case. For example, a first UE might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second UE that is a remote controller operating the drone. When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g. by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second UE can also include more than one ofthe functionalities described above. For example, a UE might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.

[0101] FIG. 8 shows a network node 800 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunication network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NRNodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e.g., O-RU, O-DU, O-CU).

[0102] Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. A base station may be a relay node or a relay donor node controlling a relay. A network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node) and / or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0103] Other examples of network nodes include multiple transmission point (multi-TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).

[0104] The network node 800 includes a processing circuitry 802, a memory 804, a communication interface 806, and a power source 808. The network node 800 may be composed of multiple physically separate components (e.g., a NodeB component and a RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the network node 800 comprisesmultiple separate components (e.g., BTS and BSC components), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, the network node 800 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory 804 for different RATs) and some components may be reused (e.g., a same antenna 810 may be shared by different RATs). The network node 800 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 800, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node 800.

[0105] The processing circuitry 802 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other network node 800 components, such as the memory 804, to provide network node 800 functionality.

[0106] In some embodiments, the processing circuitry 802 includes a system on a chip (SOC). In some embodiments, the processing circuitry 802 includes one or more of radio frequency (RF) transceiver circuitry 812 and baseband processing circuitry 814. In some embodiments, the radio frequency (RF) transceiver circuitry 812 and the baseband processing circuitry 814 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry 812 and baseband processing circuitry 814 may be on the same chip or set of chips, boards, or units.

[0107] The memory 804 may comprise any form of volatile or non-volatile computer-readable memory including, without limitation, persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computerexecutable memory devices that store information, data, and / or instructions that may be usedby the processing circuitry 802. The memory 804 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and / or other instructions capable of being executed by the processing circuitry 802 and utilized by the network node 800. The memory 804 may be used to store any calculations made by the processing circuitry 802 and / or any data received via the communication interface 806. In some embodiments, the processing circuitry 802 and memory 804 is integrated.

[0108] The communication interface 806 is used in wired or wireless communication of signaling and / or data between a network node, access network, and / or UE. As illustrated, the communication interface 806 comprises port(s) / terminal(s) 816 to send and receive data, for example to and from a network over a wired connection. The communication interface 806 also includes radio front-end circuitry 818 that may be coupled to, or in certain embodiments apart of, the antenna 810. Radio front-end circuitry 818 comprises filters 820 and amplifiers 822. The radio front-end circuitry 818 may be connected to an antenna 810 and processing circuitry 802. The radio front-end circuitry may be configured to condition signals communicated between antenna 810 and processing circuitry 802. The radio front-end circuitry 818 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry 818 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 820 and / or amplifiers 822. The radio signal may then be transmitted via the antenna 810. Similarly, when receiving data, the antenna 810 may collect radio signals which are then converted into digital data by the radio front-end circuitry 818. The digital data may be passed to the processing circuitry 802. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0109] In certain alternative embodiments, the network node 800 does not include separate radio front-end circuitry 818, instead, the processing circuitry 802 includes radio front-end circuitry and is connected to the antenna 810. Similarly, in some embodiments, all or some of the RF transceiver circuitry 812 is part of the communication interface 806. In still other embodiments, the communication interface 806 includes one or more ports or terminals 816, the radio front-end circuitry 818, and the RF transceiver circuitry 812, as part of a radio unit (not shown), and the communication interface 806 communicates with the baseband processing circuitry 814, which is part of a digital unit (not shown).

[0110] The antenna 810 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 810 may be coupled to the radio frontend circuitry 818 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 810 is separate from the network node 800 and connectable to the network node 800 through an interface or port.[oni] The antenna 810, communication interface 806, and / or the processing circuitry 802 may be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna 810, the communication interface 806, and / or the processing circuitry 802 may be configured to perform any transmitting operations described herein as being performed by the network node. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0112] The power source 808 provides power to the various components of network node 800 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 808 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 800 with power for performing the functionality described herein. For example, the network node 800 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 808. As a further example, the power source 808 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.

[0113] Embodiments of the network node 800 may include additional components beyond those shown in FIG. 8 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node 800 may include user interface equipment to allow input of information into the network node 800 and to allow output of information from the network node 800. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 800. In some embodiments providing a core network node, such as core network node108 of FIG. 6. some components, such as the radio front-end circuitry 818 and the RF transceiver circuitry 812 may be omitted.

[0114] FIG. 9 is a block diagram illustrating a virtualization environment 900 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments 900 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, UE, core network node, or host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment 900 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an O-2 interface. Virtualization may facilitate distributed implementations of a network node, UE, core network node, or host.

[0115] Applications 902 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0116] Hardware 904 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers 906 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 908a and 908b (one or more of which may be generally referred to as VMs 908), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 906 may present a virtual operating platform that appears like networking hardware to the VMs 908.

[0117] The VMs 908 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 906. Different embodiments of the instance of a virtual appliance 902 may be implemented on one or more of VMs 908, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.

[0118] In the context of NFV, a VM 908 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 908, and that part of hardware 904 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs 908 on top of the hardware 904 and corresponds to the application 902.

[0119] Hardware 904 may be implemented in a standalone network node with generic or specific components. Hardware 904 may implement some functions via virtualization.Alternatively, hardware 904 may be part of a larger cluster of hardware (e.g. such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration 910, which, among others, oversees lifecycle management of applications 902. In some embodiments, hardware 904 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system 912 which may alternatively be used for communication between hardware nodes and radio units.

[0120] Although the computing devices described herein (e.g., UEs, network nodes) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions and methods disclosedherein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.

[0121] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.

Claims

ClaimsWhat is claimed is:

1. A method performed by a second network node for sending predictions to a first network node, the predictions relating to one or more metrics, the method comprising the second network node sending, to the first network node, prediction assistance information relating to the predictions.

2. The method claim 1, wherein sending the prediction assistance information to the first network node comprises sending a Data Collection Update message containing predictions and prediction assistance information relating to predictions contained in a previously sent Data Collection Update message.

3. The method of claim 1, wherein the prediction assistance information has a granularity corresponding to any one of:per metric;per reporting period;per reporting object;per reporting message.

4. The method of claim 1, wherein the prediction assistance information comprises a bit string or a bitmap, wherein each bit of the bit string or a bitmap corresponds to a respective metric, and a value of each bit indicates whether or not a previously sent prediction relating to the respective metric is still valid.

5. The method of claim 1 , wherein the prediction assistance information comprises any one or more of:an indication that a previously sent prediction is still valid; andan indication that the previously sent prediction is not valid or is cancelled.

6. The method of claim 5, wherein the indication comprises an identifier of a first message containing the previously sent prediction.

7. The method of claim 6, wherein the identifier comprises any one or more of:a sequence number associated with either the first message or the previously sent prediction;a hash of the first message;a name associated with the previously sent prediction; anda count value indicative of a number of successive messages sent after the first message.

8. A method performed by a first network node, the method comprising:receiving, from a second node, predictions relating to one or more metrics; receiving, from the second node prediction assistance information relating to the predictions; andperforming one or more management tasks based at least in part on the received predictions and received prediction assistance information.

9. The method of claim 8, wherein the prediction assistance information a granularity corresponding to any one of:per metric;per reporting period;per reporting object;per reporting message.

10. The method of claim 8, wherein the prediction assistance information comprises any one or more of:an indication that a previously sent prediction is still valid; andan indication that the previously sent prediction is not valid or is cancelled.

11. The method of claim 10, wherein the prediction assistance information comprises a bit string or a bitmap, wherein each bit of the bit string or a bitmap corresponds to a respective metric, and a value of each bit indicates whether or not a previously sent prediction relating to the respective metric is still valid.

12. A network node comprising:processing circuitry configured to perform any of the steps of any of claims 1-11; power supply circuitry configured to supply power to the processing circuitry.

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