WO2025209682A1

WO2025209682A1 - Determination of measurement opportunities

Info

Publication number: WO2025209682A1
Application number: PCT/EP2025/052620
Authority: WO
Inventors: Stefano PARIS; Jorma Johannes Kaikkonen; Lars Dalsgaard; Klaus Ingemann Pedersen; Jian Song
Original assignee: Nokia Technologies Oy
Current assignee: Nokia Technologies Oy
Priority date: 2024-04-04
Filing date: 2025-02-03
Publication date: 2025-10-09
Anticipated expiration: 2026-10-04
Also published as: GB2642807A

Abstract

The disclosure may enable determining measurement opportunities during expected wireless traffic. For example, a UE may be configured to: obtain, from a network node, parameter data relating to a timing pattern of windows of expected traffic activity; determine, based at least in part on the parameter data, at least one window in the timing pattern of windows of expected traffic activity; determine, whether a window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with a measurement opportunity; and prioritize, based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, either receiving operations and/or transmitting operations associated with the expected traffic activity or measurements associated with the measurement opportunity.

Description

DETERMINATION OF MEASUREMENT OPPORTUNITIES

TECHNICAL FIELD

Various example embodiments relate to the field of wireless communication, and, more particularly, to determining measurement opportunities during overlapping traffic.

BACKGROUND

Radio resource management (RRM) is a set of mechanisms and procedures that enable optimization of the utilization of radio resources within an access network. User equipment (UE) requires measurement gaps to perform interfrequency and intra-f requency measurements.

Scheduling restrictions may be imposed by the access network during Synchronization Signal Block (SSB) based measurements. During at least some of the measurements, UE is not expected to transmit on an uplink channel (e.g., PUCCH/PUSCH/SRS ) or receive on a downlink channel

(PDCCH/PDSCH/CSI-RS) .

Traffic may overlap with the measurement gaps, which may severely diminish end-user experience at the UE side. Example of such traffic may be, for example, traffic related to extended reality applications.

SUMMARY

According to some aspects, there is provided the sub ect-matter of the independent claims. Some example embodiments are defined in the dependent claims. The scope of protection sought for various example embodiments is set out by the independent claims. The example embodiments and features, if any, described in this specification that do not fall under the scope of the independent claims are to be interpreted as examples useful for understanding various example embodiments.

It is an object of the invention to at least allow a device, such as a user equipment, and a network node to enable determination of pattern of expected traffic activity, and based on the pattern of expected traf fic activity, determine to prioriti ze di f ferent operations , such as measurements or data transmission and/or reception .

According to a first aspect , a device is disclosed . The device may comprise : at least one processor ; and at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : obtain, from a network node , parameter data relating to a timing pattern of windows of expected traf f ic activity; determine , based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determine , whether a window o f the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and; prioriti ze , based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, one of : receiving operations and/or transmitting operations associated with the windows of expected traf fic activity or measurements associated with the measurement opportunity .

In an implementation form of the first aspect , the at least one memory stores instructions which, when executed by the at least one processor, cause the device to at least to : determine that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity; and prioriti ze , based on the determination that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity, receiving operations and/or transmitting operations associated with the expected traf fic activity .

In an implementation form of the first aspect , the at least one memory stores instructions which, when executed by the at least one processor, cause the device to at least to : determine that the at least one window in the timing pattern of the windows of expected traf fic activity partially overlaps with the measurement opportunity; prioriti ze receiving operations and/or transmitting operations associated with the expected traf fic activity in an overlapping portion of the window of the at least one window in the timing pattern of the windows of expected traf fic activity and the measurement opportunity; and prioriti ze the measurements in a non-overlapping portion or in non-overlapping portions of the window of the at least one window in the timing pattern of the windows of expected traffic activity and the measurement opportunity .

In an implementation form of the first aspect , the parameter data may comprise : a reference time for the at least one window in the timing pattern of the windows of expected traf fic activity; and a periodicity of the windows of expected traf fic activity .

In an implementation form of the first aspect , the at least one memory stores instructions which, when executed by the at least one processor, cause the device to at least to : determine time parameters of at least one measurement , based on the determining whether a window of the at least one window in the timing parameters of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity, the time parameters of the at least one measurement comprising at least a starting time of the at least one measurement , So, and a duration of the at least one measurement T_o ; and based on the time parameters o f the at least one measurement , prioriti ze at least one of : receiving operations and/or transmitting operations associated with the windows of expected traffic activity or measurements associated with the measurement opportunity .

In an implementation form of the first aspect , the at least one memory stores instructions which, when executed by the at least one processor, cause the device to at least to : determine an expected starting time of the at least one window in the timing pattern of the windows of expected traf fic activity, S_XR, at least based on the reference time , R, and the periodicity P .

In an implementation form of the first aspect , P is a rational number comprising a numerator and a denominator, and wherein the numerator and the denominator are both integers .

In an implementation form of the first aspect , S_XR is determined based on : wherein t is an integer indicating system frame time , P_D is the denominator of P and P_N is the numerator of P .

In an implementation form of the first aspect , the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity comprises evaluation of one or more conditional statements and at least one arithmetic operation .

In an implementation form of the first aspect , the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity may comprise : determining a portion of the measurement opportunity that does not overlap with the window of the at least one window in the timing pattern of the windows of expected traf fic activity, by at least evaluating the value of S_XR against a value of a starting time of the measurement opportunity, S_M and at least evaluating an ending time of the at least one window in the timing pattern of the windows of expected traf fic activity, E_XR against an ending time of the measurement opportunity, E_M .

According to a second aspect , a network node i s disclosed . The network node may comprise : at least one processor ; and at least one memory storing instructions which, when executed by the at least one processor , cause the network node to at least to : obtain parameter data relating to a timing pattern of windows of expected traf fic activity; transmit the parameter data to a device ; determine , based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determine , whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and determine , based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, at least one of : skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity or consider the device unavailable for scheduling relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity .

In an implementation form of the second aspect , the at least one memory stores instructions which, when executed by the at least one processor, cause the network node to at least to : determine that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity; and determine , based on the determination that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity, to skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity .

In an implementation form of the second aspect , the at least one memory stores instructions which, when executed by the at least one processor, cause the network node to at least to : determine that the at least one window in the timing pattern of the windows of expected traf fic activity partially overlaps with the measurement opportunity; determine to skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity in an overlapping portion of the at least one window in the timing pattern of the windows of expected traf fic activity and the measurement opportunity; and consider the device unavailable for scheduling relating receiving operations and/or transmitting operations associated with the windows of expected traffic activity in a nonoverlapping portion of the at least one window in the timing pattern of the windows of expected traf fic activity .

In an implementation form of the second aspect , the parameter data may comprise at least : a reference time for the at least one window in the timing pattern of the windows of expected traf fic activity; and a periodicity of the windows of expected traf fic activity .

In an implementation form of the second aspect , the at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : determine time parameters of at least one measurement , based on the determining whether a window of the at least one window in the timing parameters of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity, the time parameters of the at least one measurement comprising at least a starting time of the at least one measurement , So, and a duration of the at least one measurement T_o ; and based on the time parameters of the of the at least one measurement , determine at least one of : skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity or consider the device unavailable for scheduling relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity .

In an implementation form of the second aspect , the at least one memory stores instructions which, when executed by the at least one processor, cause the device to at least to : determine an expected starting time of the at least one window in the timing pattern of the windows of expected traf fic activity, S_XR, at least based on R and P .

In an implementation form of the second aspect , P is a rational number comprising a numerator and a denominator, and wherein the numerator and the denominator are both integers .

In an implementation form of the second aspect , S_XR is determined based on : wherein t is an integer indicating system frame time , P_D is the denominator of P and P_N is the numerator of P .

In an implementation form of the second aspect , the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity comprises evaluation of one or more conditional statements and at least one arithmetic operation .

In an implementation form of the second aspect , the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity comprises : determining a portion of the measurement opportunity that does not overlap with the at least one window in the timing pattern of the windows of expected traf fic activity, by at least evaluating the value of S_XR against a value of a starting time of the measurement opportunity, S_M and at least evaluating an ending time of the at least one window in the timing pattern of the windows of expected traf fic activity, E_XR against an ending time of the measurement opportunity, E_M .

According to a third aspect , a method is disclosed, the method may comprise : obtaining, from a network node , parameter data relating to a timing pattern of windows of expected traf fic activity; determining, based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determining, whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and prioriti zing, based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, one of : receiving operations and/or transmitting operations associated with the windows of expected traf fic activity; or measurements associated with the measurement opportunity .

According to a fourth aspect , a method is disclosed, the method may comprise : obtaining parameter data relating to a timing pattern of windows of expected traf fic activity; transmitting the parameter data to a device ; determining, based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determining, whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and determining, based on the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, at least one of : skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traffic activity; or consider the device unavailable for scheduling relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity .

According to a f i fth aspect , a computer program is disclosed . The computer program may comprise instructions to cause an apparatus to carry out the method according to the third aspect .

According to a s ixth aspect , a computer program is disclosed . The computer program may comprise instructions to cause an apparatus to carry out the method of according to the fourth aspect .

Many of the attendant features wil l be more readily appreciated as they become better understood by reference to the following detai led description considered in connection with the accompanying drawings .

DESCRIPTION OF THE DRAWINGS

In the following, example embodiments are described in more detail with reference to the attached figures and drawings , in which : Fig . 1 is a timing diagram illustrating overlapping between measurement opportunities and windows of expected traf fic activity;

Fig . 2 is a timing diagram illustrating various parameters on measurement opportunities and on windows of expected traf fic activity;

Fig . 3 is a signal ing diagram according to an example embodiment ;

Fig 4A is an operation flow diagram according to an example embodiment , illustrating operations at a user equipment side ;

Fig . 4B is an operation flow diagram according to an example embodiment , illustrating operations at a network node side ;

Fig . 5 illustrates four di f ferent cases of overlapping between a measurement opportunity and a window of the expected traf fic activity according to one or more example embodiments ;

Fig . 6A is a block diagram illustrating a device according to an example embodiment ; and

Fig . 6B is a block diagram illustrating a network node according to an example embodiment .

In the following, identical reference signs refer to identical or at least functionally equivalent features .

DETAILED DESCRIPTION

In the following description, reference is made to the accompanying drawings , which form part of the disclosure , and in which are shown, by way of illustration, speci fic aspects in which the invention may be placed . It is understood that other aspects may be utili zed, and structural or logical changes may be made without departing from the scope of the invention . The following detailed description, therefore , is not to be taken in a limiting sense , as the scope of the invention is defined in the appended claims .

For instance , it is understood that a disclosure in connection with a described method may also hold true for a corresponding device , network node or system configured to perform the method and vice versa . For example , i f a speci fic method step is described, a corresponding device may include a unit to perform the described method step, even if such unit is not explicitly described or illustrated in the figures. On the other hand, for example, if a specific apparatus is described based on functional units, a corresponding method may include a step performing the described functionality, even if such step is not explicitly described or illustrated in the figures. Further, it is understood that the features of the various example aspects described herein may be combined with each other, unless specifically noted otherwise .

Scheduling restrictions may apply for user equipment, UE, during time-intervals where the UE may be performing Synchronization Signal Block, SSB, -based measurements. Configurations of the SSB-based measurements may be according to SS/PBCH Block Measurement Timing Configuration, SMTC. Different SMTC configurations allow different size of measurement gaps. Some configurations such as a 5 ms (millisecond) window occurring every 20 ms may pose scheduling restrictions that may diminish networks capability to efficiently schedule and provide different traffic to the UE .

As will be discussed in more detail below, at least some of the disclosed embodiments may allow determination of measurement opportunities during expected traffic activity, in particular, during traffic activity with non-integer periodicity, however, example embodiments enable determining measurement opportunities during traffic activity of integer periodicity. One example of such non-integer periodic traffic is extended reality, XR, applications, wherein desired traffic can be tied to a target framerate (i.e., 30 fps, 60 fps, 120 fps etc.) . Measurement opportunities may comprise radio resource management, RRM, measurement opportunities.

Fig. 1 illustrates an example timing diagram 100, wherein a SMTC configuration comprises a measurement window 110i of 5 ms duration occurring every 20 ms (i.e., measurement gap/periodicity ) and measurement window 110i comprises scheduling restrictions. In other words, a UE expects a measurement window 110i from a network node every 20 ms and the measurement window length, where the UE is performing RRM measurements, is 5 ms . The subindex 'i' in measurement window 110i refers generally to any single one from the measurement windows IIOQ-5 illustrated in Fig. 1.

In the example of Fig. 1, the UE is also expected to receive a traffic window 120j with a non-integer periodicity of 16.67 ms. An example of such a traffic window may comprise an extended reality, XR, related traffic window, which may be configured to operate on 60 frames per second (i.e., 1/60 = 16.67 ms) . Dashed arrows 122 indicates time variance information of traffic window 120. In other words, time variance information may comprise, for example, jitter, minimum value of jitter and/or maximum value of jitter.

The subindex 'j' in traffic window 120j refers generally to any single one from the traffic windows 12O_o-6 illustrated in Fig. 1.

The example illustrates a first traffic window 12O_o occurring the same time as a first measurement window 110₀ for description purposes. It can be seen from Fig. 1 that due to the non-integer periodicity of traffic window 120j, even without any time variance on traffic window 120j, measurement windows and traffic windows are expected to overlap. Due to the overlapping, the network might need to, for example, delay the transmitting schedule of certain traffic windows, which might be undesirable for an end-user.

Fig. 2 illustrates a timing diagram 200 illustrating different parameters for traffic window (s) and measurement opportunities (or measurement windows in particular) . Windows of expected traffic activity, XR_k, comprise a non- integer periodicity, P. Each window from the windows of expected traffic activity may comprise a length of the window (or duration) , T_XR, an expected starting time S_XR,k, and an expected ending time E_XRfk. It will be noted that Fig. 2 does not illustrate any time variance parameters, such as jitter, on the windows of expected traffic activity, XR_k, to maintain clarity in the description.

Furthermore in Fig. 2, measurement opportunities, MG_k, are expected to occur in an integer periodic fashion. The periodicity for the measurement opportunities is marked as MGP (measurement gap periodicity) and each measurement opportunity may comprise a starting time S_M,k, and a window length T_M (e.g., measurement gap length) . Each measurement opportunity may further comprise an ending time, E_Mfk.

It will be noted that the subindex 'k' used in reference to the windows of expected traffic activity XR_k and measurement opportunities MG_k in relation to Fig. 2 generally refers to a plurality of windows of expected traffic activity or to a plurality of measurement opportunities, whereas a singular window would be referred to as a specific number, for example, MG_k or XR₃, or the like. It will be appreciated that some terms referring to a measurement opportunity (e.g., MGi) may be used interchangeably, such as ' (RRM) measurement window' or 'measurement gap' , or the like. The plurality of measurement opportunities (e.g., MG1-3) may be referred to as 'windows of measurement opportunities' , ' (RRM) measurement windows' , 'measurement windows' or 'RRM measurement opportunities' .

Terms that refer to the windows of expected traffic activity (e.g, XRx-a) may be used interchangeably, such as 'windows of traffic activity' , 'expected traffic activity' , or 'traffic windows' , or 'expected traffic windows' or 'expected traffic arrivals' .

A singular window from the expected traffic activity may be referred to as 'a window from the expected traffic activity' , 'at least one window from the expected traffic activity' , 'a window of the at least one window of the expected traffic activity' , 'a window of the expected traffic activity' , 'expected traffic window' , 'window of expected traffic arrivals' and such.

Disclosed embodiments may enable determining timing parameters for more than one window.

Furthermore, embodiments may comprise determining, based on a parameter data relating to a timing pattern of windows of expected traffic activity, and the embodiment comprises determining at least one window based on the parameter data relating to a timing pattern of windows of expected traffic activity. Therefore, a singular window of expected traffic activity that has been determined by an embodiment, for example a UE or a network node, may be referred to as 'at least one window in the timing pattern of the windows of (the) expected traffic activity' , or 'a window of the at least one window in the timing pattern of the windows of (the) expected traffic activity' .

Furthermore, referring to Fig. 2, the traffic windows (XR_k) exhibit periodic pattern where a burst is expected to be regularly generated within a certain time window. This window repeats over time according to a constant period and models the jitter (time variance) due to processing in application-layer codecs and network transmission procedures. This regular pattern can be used to predict periods of traffic activity colliding with measurement opportunities, hence, skipping measurements in order to prioritize reception and/or transmission during a window of expected traffic activity. Additionally, when the window of expected traffic activity collides only partially with a measurement opportunity, a UE may still perform some measurements in a portion of the measurement opportunity that does not overlap with the window of expected traffic activity.

The description discloses a UE, a network node, a method and a computer program that may enable solving the issues discussed above.

It will be appreciated that some terms referring to 'skipping scheduling restrictions' may be used interchangeably, such as 'skipping measurement opportunities' , 'skipping measurement occasions, 'prioritize transmission/recep- tion over (RRM) measurements' , 'relax scheduling restrictions' .

Some example embodiments may enable transmitting, by a network node, to a UE, pattern information of (noninteger) periodic traffic, and based on the pattern information, enable determining information on occurrence of the (non-integer ) periodic traffic and based on the information on the occurrence of the (non-integer) periodic traffic, prioritize, for example, receiving/decoding from an expected window of traffic activity, when the expected window of traffic activity overlaps with a measurement opportunity.

Other disclosed embodiments may enable additionally, when the window of expected traffic activity collides only partially with the measurement opportunity, that a UE may still perform some measurements in a portion of the measurement opportunity that does not overlap with the window of expected traffic activity.

It will be noted that disclosed example embodiments may be applied to other SMTC configurations than what is presented in Fig. 1, for example, to a SMTC configuration with a measurement gap (periodicity) of 80 ms and 3 ms window duration (measurement gap length) or an SMTC configuration with a measurement gap of 40 ms and a 5.5 ms window duration.

Furthermore, it will be noted that disclosed example embodiments may be applied to other types of expected traffic activity with and/or without non-integer periodicity, for example, a traffic window of 18.5 ms periodicity or a traffic window of 25 ms periodicity.

Some example embodiments may enable solving rounding errors due to a product of an integer and a non-integer value when determining an overlap.

Fig. 3 illustrates a signaling diagram 300 according to an example embodiment, between a user equipment, UE, and a network (e.g., network node, access node etc.) .

At operation 302, the network may provide the UE with parameter data relating to a timing pattern of windows of expected traffic activity. The parameter data may comprise, for example, the periodicity of the expected traffic activity (e.g., 'P' of Fig. 2) . The parameter data may further comprise time variance information on the windows of expected traffic activity, for example, jitter, maximum amount of jitter and/or minimum amount of jitter. The parameter data may further comprise a reference time for the windows of expected traffic activity. The reference time may comprise the time offset of the windows of expected traffic activity in relation to, for example, system frame number, subframe number and/or total number of subframes. In some embodiments, the reference time may comprise an offset between measurement opportunities and the windows of expected traffic activity, or an offset between a subframe of a measurement opportunity and a subframe of a window of expected traffic activity, (i.e., the reference time may comprise an integer) . The parameter data may be transmitted from the network to the UE for example, during radio resource control, RRC, configuration.

The measurements opportunities or measurement gaps may have been configured to the UE, e.g. as disclosed in TS 38.331.

At operation 304, when the UE has obtained (i.e., received) from the network, the parameter data, the UE may be configured to determine the pattern of the windows of expected traffic activity. The UE may determine, based at least in part on the parameter data, at least one window in the timing pattern of windows of expected traffic activity.

In other words, determining the pattern of the windows of expected traffic activity or determining at least one window in the timing pattern of the windows of expected traffic activity may comprise determining time related data on the at least one window in the timing pattern of the windows of expected traffic activity, such as an expected starting time of the at least one window in the timing pattern of the windows of expected traffic activity (e.g., 'S_XR,k' ^{of Fi}U- ²) •

The determining the at least one window from the windows of expected traffic activity may further comprise determining an expected ending time of the at least one window in the timing pattern of the windows of expected traffic activity (e.g., 'E_XR,k' of Fig. 2) . The ending time of the at least one window in the timing pattern of the windows of expected traffic activity may be determined by, for example, the starting time of the at least one window in the timing pattern of the windows of expected traffic activity and the time variance information encoded in the parameter data. Examples of deriving the expected starting time and/or the expected ending time are provided later the description .

At operation 306, after determining the at least one window in the timing pattern of the windows of expected traffic activity, the UE may be configured to determine, whether a window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with a measurement opportunity. A measurement opportunity may comprise a radio resource management, RRM, measurement opportunity. As described earlier, measurement opportunities may be expected by the UE to occur in an integer periodic fashion, due to, for example, SMTC configuration. The UE may be configured with SMTC configuration as described, for example, in TS 38.331. In other words, the UE may be configured to determine an amount of overlapping between the at least one window in the timing pattern of the windows of expected traffic activity and for example, at least one measurement opportunity.

Determining the amount of overlapping may comprise, for example, conditional statements such as OR, IF, ELSE, ELSE IF, AND, less than, more than, less than or equal to, more than or equal to, etc, and arithmetic operations such as addition, subtraction, division, multiplication, exponentiation, modulo, etc. For example, if the at least one window in the timing pattern of the windows of expected traffic activity is to occur earlier than the measurement opportunity, and if the at least one window in the timing pattern of the windows of expected traffic activity is expected to end later than the measurement opportunity, it could be determined that the windows fully overlap (e.g., the amount of overlap is full overlap, or the amount of overlap is a full overlap condition) .

In some embodiments, when determining, whether the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, a UE can, for example, determine more than one measurement opportunity from measurement opportunities, as the measurement opportunities are expected to occur in a periodic fashion. The network may provide parameters on RRM measurement opportunities during RRC configuration (e.g., SMTC) , and the UE may determine one measurement opportunity from the RRM measurement opportunities by those RRM measurement opportunity parameters.

The parameters on the measurement opportunities may comprise, for example, a system frame number, SEN, subframe of the SEN, a periodicity of the RRM measurement opportunities (e.g., MGR of Fig. 2) and/or an offset (e.g., reference time ) of the RRM measurement opportunities . In some embodiments , the of fset of the measurement opportunities may be referred to as a ' gap of fset ' and the periodicity of the measurement opportunities may be referred to as 'measurement gap (MGRP ) ' . The parameters on the measurement opportunities may be comprised in SMTC configuration, for example . The length of the measurement opportunities ( e . g . , T_M in Fig . 2 ) may be further comprised in the parameters on the RRM measurement opportunities .

The determining whether the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity may comprise , for example , that ' the at least one window in the timing pattern of the windows of expected traf fic activity and the measurement opportunity fully overlap' , or that ' the at least one window in the timing pattern of the windows of expected traffic activity and the measurement opportunity partially overlaps ' , or that ' the at least one window in the timing pattern o f the windows of expected traf fic activity and the measurement opportunity overlap during a time interval ' . More details in relation to the amount of overlapping is described in reference to Fig . 5

At operation 308 , the UE may be configured to prioriti ze , based on the determination whether the window of the at least one window in the timing pattern of the windows expected traf fic activity at least partially overlaps with the measurement opportunity, either receiving operations and/or transmitting operations associated with the windows of expected traf fic activity or measurements associated with the measurement opportunity .

For example , when the UE is configured to prioriti ze receiving operations and/or transmitting operations associated with the expected traf fic activity, the network side may provide , to the UE , data requested by the UE without any delay . In other words , the network disables scheduling restrictions and proceeds with receiving/ transmission of the traf fic windows as per normal procedure . Prioriti zing receiving operations and/or transmitting operations at the UE side may include decoding the control channel and encoding or decoding the information carried on shared data channels . Referring back to Fig. 3, the network performs its own operations.

The network node may be configured to obtain the parameter data relating to the timing pattern of windows of expected traffic activity and transmit it to the UE (operation 302) . It can be obtained from, for example, an extended reality service configured to operate on the network (e.g., internet-based communications) .

At operation 314, the network (e.g., a network node/access node) may determine a pattern of the traffic activity and a pattern of scheduling restrictions or a pattern of RRM measurement opportunities.

In other words, operation 314 may comprise the network determining, based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traffic activity.

At operation 316, the network may be configured to determine, similarly to operation 306 at UE side, whether a window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with a measurement opportunity.

Generally, on the network side, when referring to a 'measurement opportunity' , it comprises 'scheduling restrictions' associated with the measurement opportunity, i.e., the network may determine the operation at 316 by comparing the at least one window in the timing pattern of the windows of expected traffic activity to a pattern of scheduling restrictions.

At operation 318, based on operation 316, the network may determine either to i) skip a scheduling restriction associated with the measurement opportunity, wherein the scheduling restriction relates to receiving operations and/or transmitting operations associated with the expected traffic activity; or ii) consider the device unavailable for scheduling relating to receiving operations and/or transmitting operations associated with the expected traffic activity.

In other words, the network determines that scheduling restrictions in next measurement opportunity can be, for example , relaxed based on the overlap . In some embodiments , scheduling restrictions associated with the measurement opportunities can be , for example , disabled for the next measurement opportunity or disabled during a portion of the next measurement opportunity .

At operation 320 , the network may schedule data transmission associated with the expected traf fic activity without restriction . This may comprise , for example , that there is no delay in between consecutive transmissions of traf fic windows .

After operation 320 , the network and UE may proceed normal procedure by, for example , as illustrated in Fig . 3 , performing, by the network, a data transmission and the UE may reply with a HARQ feedback (HARQ, Hybrid Automatic Repeat Request ) .

Fig . 4A illustrates a method 400 according to an example embodiment . Method 400 may be performed by a device , UE , or the like , comprising at least a processor and a memory . An example embodiment of a device configured to practice embodiments of method 400 is described in reference to Fig . 6A.

At operation 402 , method 400 may comprise obtaining, from a network node , parameter data relating to a timing pattern of windows of expected traf fic activity .

At operation 404 , method 400 may comprise determining, based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity .

At operation 406 , method 400 may comprise determining, whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity .

In some embodiments , at operation 406 , method 400 may comprise at least one conditional statement to determine the amount of overlapping, or an overlap condition, for examp 1 e .

In some embodiments , at operation 406 , method 400 may further comprise at least one conditional statement and at least one or a plurality of arithmetic operations to determine the amount of overlapping, or an overlap condition, for example .

In an implementation form of method 400 , method 400 may further comprise : determining that the window of the at least one window in the timing pattern of windows of the expected traf fic activity ful ly overlaps with the measurement opportunity .

In an implementation form of method 400 , method 400 may further comprise : determining that the at least one window in the timing pattern of windows of the expected traf fic activity partially ( only partially) overlaps with the measurement opportunity .

At operation 408 , method 400 may comprise prioriti zing, based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, either i ) receiving operations and/or transmitting operations associated with the expected traf fic activity or ii ) measurements associated with the measurement opportunity .

In an implementation form of method 400 , method 400 may further comprise : prioriti zing, based on the determination that the window of the at least one window in the timing pattern of windows of the expected traf fic activity fully overlaps with the measurement opportunity, receiving operations and/or transmitting operations associated with the expected traf fic activity .

In an implementation form of method 400 , method 400 may further comprise : prioriti zing receiving operations and/or transmitting operations associated with the expected traf fic activity in an overlapping portion of the window of the at least one window in the timing pattern of windows of the expected traf fic activity and the measurement opportunity; and prioriti zing the measurements in a non-over- lapping portion or in non-overlapping portions of the window of the at least one window in the timing pattern of windows of the expected traf fic activity and the measurement opportunity .

At operation 410 , after prioriti zing (based on determining to prioriti ze or based on prioriti zing) receiving operations and/or transmitting operations , method 400 may comprise at least partially skipping the measurement opportunity, or method 400 may comprise performing measurements associated with the measurement opportunity during those portions of the measurement opportunity, when there is no overlapping and/or performing receiving operations and/or transmitting operations in such a portion, when there i s an overlapping . Or after prioriti zing measurements (based on determining to prioriti ze measurements or based on prioriti zing) , method 400 may comprise performing a measurement in the next measurement opportunity .

The method as disclosed herein enables determination of the applicability of scheduling restrictions , and ensuring data reception/ transmission by the UE .

Fig . 4B illustrates a method 420 according to an example embodiment . Method 420 may be performed by a network node , such as gNb, for example . An example embodiment of a network node configured to practice embodiments of method 420 is described in reference to Fig . 6B .

At operation 422 , method 420 may comprise obtaining parameter data relating to a timing pattern of windows of expected traf fic activity .

At operation 424 , method 420 may comprise transmitting the parameter data to a device .

At operation 426 , method 420 may comprise determining, based at least in part on the parameter data, at least one window in the timing pattern of windows of expected traf fic activity .

At operation 428 , method 420 may comprise determining, whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity .

In other words , method 420 may comprise at least one conditional statement to determine the amount of overlapping, an overlap condition, or the like .

In some embodiments , method 420 may further comprise at least one conditional statement and at least one or a plurality of arithmetic operations to determine the amount of overlapping, an overlap condition, or the like . At operation 430 , method 420 may comprise determining, based on the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, either to skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting associated with the expected traf fic activity or consider the device unavailable for scheduling relating receiving operations and/or transmitting operations associated with the expected traf fic activity .

At operation 432 , after determining to skip a scheduling restriction associated with measurement opportunity, method 420 may comprise considering the device available for scheduling during next measurement opportunity . In other words , the device (UE ) would prioriti ze Tx/Rx ( Transmit- ting/Receiving) operations associated with the at least one window of expected traf fic activity and the network would determine to perform the Tx/Rx operations . Tx/Rx operations may include the decoding or encoding of the control channel ( s ) and the decoding and encoding of shared data channel ( s ) .

At operation 434 , after determining to consider UE available , method 420 may comprise the device unavailable for scheduling during next measurement opportunity .

In new radio , RRC is responsible for providing measurement gap pattern configuration to UE . During measurement gaps , measurements are performed on SSB' s of neighbour cel ls ( i . e . , not serving cell ) . The network provides timing data of neighbour cell SSB' s using SMTC . Measurement gap and SMTC duration are configured such that the UE can identi fy and measure the SSB' s within a SMTC window .

For SSB based intra- f requency measurements , the network configures measurement gap in the case i f any of the UE configured bandwidth parts , BWP ' s , do not contain the frequency domain resources of the SSB associated with the initial downlink BWP .

For SSB based inter- frequency measurement , the network configures measurement gaps i f the UE supports per-FR (frequency range) measurement gaps and if the carrier frequency to be measured is in the same frequency range as any of the serving cells, or if the UE only supports per-UE measurement gaps, the UE can be configured to any frequency range (FR1 or FR2 ) .

The network may provide the UE a configuration data comprising system frame number, SEN and subframe -pair of a serving cell, a gap offset, measurement gap periodicity and a measurement gap length during the configuration. Measurement gap (i.e., measurement window) can be determined from the SFN-subframe pair, the gap length and the gap offset. In some embodiments, the configuration data may comprise only integers .

One method to determine an occurrence of a measurement opportunity in a system frame, SEN, from the configuration data, is to determine, a modulo operation between at least system frame information and a periodicity of the measurement gap. For example, determining a measurement opportunity may comprise following conditions: wherein mod is the modulo operation, MGP is the measurement gap periodicity (see Fig. 2) , gapOffset is the offset of the measurement gap in relation to the first SFN- subframe -pair, FLOOR () is the greatest integer function and CEIL() is the smallest integer function and subframe is the subframe of the current SEN (i.e., subframe varies from 0 to 10 each SEN) .

Example embodiments related to determining the at least one window in the timing pattern of windows of expected traffic activity are described below.

These example embodiments may be supported by mathematical equations, conditional statements etc., to provide context on the example embodiments of operations described above. It will be appreciated that if an example embodiment comprises, for example, a mathematical equation, the mathematical equation may be applied in an example embodiment of a device, UE, network node, a method and/or a computer program comprising instructions.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, a UE or a network may determine an occurrence of an expected traffic window, after obtaining the parameter data relating to a timing pattern of windows of expected traffic activity (See operation 302 in Fig. 2) .

The parameter data may comprise at least: a reference time for the windows of expected traffic activity, R, and a periodicity of the windows of expected traffic activity, P.

In some embodiments, the parameter data may further comprise time variance information on the windows of expected traffic activity.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining, whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with a measurement opportunity, is based at least on a system frame information, and the periodicity of the windows of expected traffic activity. The system frame information may comprise, for example, a system frame number, SEN, and a subframe number, or a SFN-subframe -pair (e.g. an integer array or the like) .

An embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, may comprise determining an expected starting time of the least one window in the timing pattern of the windows of expected traffic activity, S_XR, at least based on R and P.

In some embodiments, P is a rational number comprising a numerator and a denominator, and wherein the numerator and the denominator are both integers .

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining, whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, comprises at least a modulo operation between the system frame information and the periodicity of the windows of expected traffic activity.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining, whether the window of the at least one window in time timing pattern of the expected traffic activity at least partially overlaps with the measurement opportunity, is further based on the reference time of the windows of expected traffic activity.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining, whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, further comprises a greatest integer function operating at least on the modulo operation between the system frame information the periodicity of the windows of expected traffic activity.

For example, S_XR can be determined by following wherein P_N and P_D are the numerator and the denominator of P respectively.

Furthermore, Eq. 2 may be expressed as per Eq. 3, for the purposes of clarity. wherein t = SFN*10 + subframe, i.e., the total system frame time.

For example, if the reference time, R, is 14, SFN=3, subframe=l, P_N=50 and PD=3, then Eq. 2 yields 1, which may indicate that the at least one from the timing pattern of the windows of expected traffic activity would occur at the next frame (hence Eq. 2 yields 1) . A person-skilled in the art may manipulate Eq. 2 to determine an occurrence of the next traffic window. For example, each first subframe of a SEN, a UE or a network node may loop Eq. 2 for each subframe to yield a subframe number the traffic is expected to happen.

In an embodiment, a greatest integer function can be imposed to R in Eq. 2, if R is not an integer, for example.

In some embodiments, it may be beneficial to further increase the precision of a modulo operation when using it on a rational number (e.g., a floating point) .

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining, whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the RRM measurement opportunities, may further comprise using/applying a derivation based on the definition of congruence modulo relation on at least the modulo operation between the system frame information the periodicity of the windows of expected traffic activity.

For example, when using definition of congruence modulo relation as per Eq. 4: ined as per Eq. 5:

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining, whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, may further comprise a greatest integer function operating on a difference between a system frame time and a product between the periodicity of the windows of expected traffic activity and the reciprocal of the periodicity of the windows of expected traffic activity and the system frame time.

Even further modifications may be made to Eq. 5. Depending on the numeral precision used to represent noninteger numbers, result of a product operation may change. For example: then a one number precision of PN/PD = 16.6, and the product in Eq. 5 is 16.6*15=249.

And for example, a three number precision of a rational number results in PN/PD = 16.666 and therefore a three number precision of the product in Eq. 5 is 16.666*15=249.99.

In an embodiment of the disclosure, S_XR may be determined to be as per Eq. 6.

Eq. 6 may be derived from Eq. 5 by expanding the factors inside FLOOR ( ) by P_D. The embodiment disclosed in Eq. 6 removes the product error due to the rational number, as t, P_D and P_N are all integers.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining, whether the window of the at least one window in the timing pattern of the expected traffic activity at least partially overlaps with the RRM measurement opportunities, may further comprise expanding factors on the difference between the system frame time and the product between the periodicity of the windows of expected traffic activity and the reciprocal of the periodicity of the windows of expected traffic activity and the system frame time.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the determining whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity comprises evaluation of one or more conditional statements . The one or more conditional statements may be associated with S_XR .

In an embodiment of the disclosure , e . g . , a device , network node , a method and/or a computer program, the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity further evaluation of one or more conditional statements and execution of at least one or a plurality of arithmetic operations . The one or more conditional statements and the execution of the at least one or plurality of arithmetic operations may be associated with S_XR .

In other words , the one or more conditional statements and the at least one arithmetic operation may be related at least to a starting time of the window of the at least one window in the timing pattern of the expected traffic activity and a starting time of the measurement opportunity .

In some embodiments , the one or more conditional statements and the at least one arithmetic operation may be further related to an ending time of the window of the at least one window in the timing pattern of the expected traffic activity ( E_XR in Fig . 2 ) and an ending time of the measurement opportunity (E_M in Fig . 2 ) .

In some embodiments , the one or more conditional statements and the at least one arithmetic operations may be further related to a duration of the window of the at least one window in the timing pattern of the expected traf fic activity ( T_XR in Fig . 2 ) and/or a duration of an ending time of the measurement opportunity ( T_M in Fig . 2 ) .

One or more conditional statements and the at least one arithmetic operation may be performed on the window o f the at least one window in the timing pattern of the windows of expected traf fic activity, and a measurement opportunity by, for example , evaluating di f ferent logical conditions between S_XR, SM, T_XR, T_M, E_M, E_XR etc . i . e . , the parameters described in relation to Fig . 2 . In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the one or more conditional statements may comprise:

ABS(S_XR S_M) < T_M OR ABS(S_XR 5_M) < T_XR, (7) wherein ABS ( ) is the absolute value function, T_M = E_M-S_M, TXR = EXR-SXR = JR-JI, wherein J₂ is a maximum value of jitter of the window of the at least one window in the timing pattern of the windows of expected traffic activity and Ji is a minimum value of jitter of the window of the at least one window in the timing pattern of the windows of expected traffic activity.

If the conditional statement of Eq. 7 is true, a UE may completely skip the next measurement opportunity, and the network may skip any scheduling restrictions associated with the next measurement opportunity.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the one or more conditional statements may comprise:

ABS(S_XR S_M) < T_M + 7 OR ABS(S_XR S_M) < T_XR + T_lf (8) wherein Th is an additional time parameter indicating a time threshold for a measurement opportunity.

If the conditional statement of Eq. 8 is true, a UE may completely skip the next measurement opportunity, and the network may skip any scheduling restrictions associated with the next measurement opportunity.

Fig. 5 illustrates four different cases of overlapping 500 between a window of expected traffic activity and a measurement opportunity.

Example embodiments may be configured to determine time parameters of at least one measurement, based on the determining whether a window of the at least one window in the timing parameters of the windows of expected traffic activity at least partially overlaps with a measurement opportunity. The time parameters of the at least one measurement after (based on) the determining, whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, may comprise at least a starting time of the at least one measurement, So, and a duration of the at least one measurement T_o.

Referring back to Fig. 5, a full overlap case 502 may comprise, that a measurement opportunity window is smaller than the traffic window, occurs later in time and ends earlier in time. If full overlap case 502 is true, a UE may completely skip the next measurement opportunity, and the network may skip any scheduling restrictions associated with the next measurement opportunity.

S_M > S_XR AND E_M < E_XR . ( 9 ) wherein eq. 9 comprises at least a portion of the full overlap case 502.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, if the conditional statement of Eq. 9 is determined to be true, the starting time of the at least one measurement, So, may be determined to be equal to S_M, and the duration of the at least one measurement, T_o, may be determined to be equal to zero (i.e., in a full overlap case, the duration of the measurement is zero) .

A first partial overlap case 504 may comprise, that a measurement opportunity window is larger than the traffic window, starts earlier in time and ends later in time. If first partial overlap case 504 is true, a UE may determine that at least some measurements may be performed during nonoverlapping portions 505.

S_M < S_XR AND E_M > E_XR , (10) wherein Eq. 10 comprises at least a portion of the first overlap case 504.

An embodiment of the disclosure may be configured to determine time parameters for more than one measurement opportunity. For example, a starting time for a first measurement opportunity, So, a starting time for a second measurement opportunity, Si, a duration of the first measurement opportunity, T_o, and a duration of the second measurement opportunity, Ti . In other words, in some embodiments, two measurement opportunities may be performed even if an overlapping is determined.

In an embodiment of the disclosure, if the conditional statement of Eq. 10 is true, So may be determined to be equal to S_M, To may be determined to be equal to S_XR-S_M, SI may be determined to be equal to E_XR and Ti may be determined to be equal E_M-E_XR.

A second partial overlap case 506 may comprise, that a measurement opportunity window starts later in time than a traffic window and ends later in time than the traffic window. If second partial overlap case 506 is true, a UE may determine that at least some RRM measurements may be performed during a non-overlapping portion 505.

S_M > S_XR AND E_M > E_XR , (11) wherein Eq. 11 comprises at least a portion of the second overlap case 506.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, if the conditional statement of Eq. 11 is determined to be true, So may be determined to be equal to E_XR, and T_o may be determined to be equal to T_M+S_M-E_XR.

A third overlap case 508 may comprise, that a measurement opportunity window starts earlier in time than a traffic window and ends earlier in time than the traffic window. If third partial overlap case 508 is true, a UE may determine that at least some RRM measurements may be performed during a non-overlapping portion 509.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, the one or more conditional statements may comprise: wherein Eq. 12 comprises at least a portion of the third overlap case 508.

In an embodiment of the disclosure, e.g., a device, network node, a method and/or a computer program, if the conditional statement of Eq. 12 is determined to be true, SO may be determined to be equal to SM, and TO may be determined to be equal to T_M+S_XR-E_M.

It will be noted that some conditional statements may be expressed in a way than is not given in the description but will yield the same result. For example, changing the order of the parameters in a statement, or replacing E_M with S_M+T_M, or the like, are intended to be within the scope of the claims. I.e., some conditional statements and arithmetic operations are interchangeable.

Fig. 6A illustrates an example of a device 600 configured to practice one or more example embodiments. Device 600 may comprise, for example a UE configured to perform example embodiments of methods disclosed herein, such as the method according to the description in reference to Fig. 4A.

Device 600 may comprise: at least one processor 602 and at least one memory 604 storing instructions which, when executed by at least one processor 602, cause device 600 to at least to: obtain, from a network node, parameter data relating to a timing pattern of windows of expected traffic activity; determine, based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traffic activity; determine, whether a window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with a measurement opportunity; and; prioritize, based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, one of : receiving operations and/or transmitting operations associated with the windows of expected traf fic activity; or measurements associated with the measurement opportunity .

Device 600 may further comprise a communication interface 608 configured to enable device 600 to transmit and/or receive information . Communication interface 608 may comprise an internal or external communication interface , such as for example a Wi/ Fi module or ethernet module capable of handling TCP/ IP based communication between devices .

Communication interface 608 may be configured to input/output the receiving/ transmitting operations associated with the at least one window of traf f ic activity . Communication interface 608 may be further configured to obtain the parameter data relating to the timing pattern of the windows of expected traf fic activity . Communication interface 608 may be configured to input/output operations associated with RRM measurement opportunities , such as intrafrequency measurements and/or inter- frequency measurements .

Device 600 may further comprise a user interface 610 . User interface 610 may comprise , for example , a graphical interface .

Fig . 6B illustrates an example of a network node 620 configured to practice one or more example embodiments . Network node 620 may comprise , for example a gNb configured to perform example embodiments of methods disclosed herein, such as the method according to the description in reference to Fig . 4B .

Network node 620 may comprise : at least one processor 622 and at least one memory 624 storing instructions which, when executed by at least one processor 622 , cause network node 620 to at least to : obtain parameter data relating to a timing pattern of windows of expected traf fic activity; transmit the parameter data to a device ; determine , based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determine , whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and determine , based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, at least one of : skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity; or consider the device unavailable for scheduling relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity .

Network node 620 may comprise for example , an access node , an access point , a node B, an evolved node B, eNb, a next-generation node B, gNb, RCS , BSC or a BTS .

Network node 620 may further comprise a communication interface 628 configured to enable network node 620 to transmit and/or receive information .

Communication interface 628 may comprise a communication interface capable of handl ing TCP/ IP based communication between various devices .

Communication interface 628 may be configured to output RRM measurement opportunities to a device , such as device 600 . Communication interface 628 may be further configured to obtain the parameter data relating to the timing pattern of the windows of expected traf fic activity . Communication interface 628 may be further configured to transmit the parameter data to a device , such as device 600 . Communication interface 628 may be configured to transmit the at least one window in the timing pattern of the expected traffic activity to a device , such as device 600 .

The functionality described herein can be performed, at least in part , by one or more computer program product components such as software components . Alternatively, or in addition, the functionality described herein can be performed, at least in part , by one or more hardware logic components . For example , and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays ( FPGAs ) , Application-speci fic Integrated Circuits (AS ICs ) , Application- specific Standard Products (ASSPs) , System-on-a-chip systems (SOCs) , Complex Programmable Logic Devices (CPLDs) , and Graphics Processing Units (GPUs) .

At least one processor 602, 622, may comprise, for example, one or more of various processing devices, such as for example a co-processor, a microprocessor, a controller, a digital signal processor (DSP) , a processing circuitry with or without an accompanying DSP, or various other processing devices including integrated circuits such as, for example, an application specific integrated circuit (ASIC) , a field programmable gate array (FPGA) , a microcontroller unit (MCU) , a hardware accelerator, a special-purpose computer chip, or the like.

At least one memory 604, 624 may be configured to store, for example, computer program code or the like, for example operating system software and application software. At least one memory 604, 624 may comprise one or more volatile memory devices, one or more non-volatile memory devices, and/or a combination thereof. For example, the memory may be embodied as magnetic storage devices (such as hard disk drives, etc.) , optical magnetic storage devices, or semiconductor memories (such as mask ROM, PROM (programmable ROM) , EPROM (erasable PROM) , flash ROM, RAM (random access memory) , etc.) . Memory 604, 624 is provided as an example of a (non- transitory) computer readable medium. The term "non-transi- tory, " as used herein, is a limitation of the medium itself (i.e., tangible, not a signal) as opposed to a limitation on data storage persistency (e.g., RAM vs. ROM) . At least one memory 604, 624 may be also embodied separate from device 600 or from network node 620, for example as a computer readable (storage) medium, examples of which include memory sticks, compact discs (CD) , or the like.

Any range or device value given herein may be extended or altered without losing the effect sought. Also, any embodiment may be combined with another embodiment unless explicitly disallowed.

Further, a computer program, a computer program product, or a (non-transitory ) computer-readable medium may comprise instructions for causing, when executed by an apparatus, an apparatus, such as a UE, device, network node, or the like , to perform any aspect of the method ( s ) described herein . Further, an apparatus may comprise means for performing any aspect of the method ( s ) described herein . According to an example embodiment , the means comprises at least one processor ; and at least one memory storing instructions that , when executed by the at least one processor, cause the apparatus at least to perform any aspect of the method ( s ) .

For example , a network node may comprise means to perform any aspect of the method ( s ) described in relation to Fig . 4B and a UE may comprise the means to perform any aspect of the method ( s ) described in relation to Fig . 4A.

Although the subj ect matter has been described in language speci fic to structural features and/or acts , it is to be understood that the subj ect matter defined in the appended claims is not necessarily limited to the speci fic features or acts described above . Rather, the speci fic features and acts described above are disclosed as examples of implementing the claims and other equivalent features and acts are intended to be within the scope of the claims .

It will be understood that the benefits and advantages described above may relate to one embodiment or may relate to several embodiments . The embodiments are not limited to those that solve any or all of the stated problems or those that have any or all of the stated benefits and advantages . It will further be understood that reference to ' an ' item may refer to one or more of those items .

Aspects of any of the embodiments described above may be combined with aspects of any of the other embodiments described to form further embodiments without losing the ef fect sought .

The term ' comprising ' is used herein to mean including the method, blocks or elements identi fied, but that such blocks or elements do not comprise an exclusive list and a method or apparatus may contain additional blocks or elements .

It will be understood that the above description i s given by way of example only and that various modi fications may be made by those skilled in the art . The above speci fication, examples and data provide a complete description of the structure and use of exemplary embodiments . Although various embodiments have been described above with a certain degree of particularity, or with reference to one or more individual embodiments , those skilled in the art could make numerous alterations to the disclosed embodiments without departing from the spirit or scope of this speci fication .

Claims

CLAIMS : l . A device comprising : at least one processor ; and at least one memory storing instructions which, when executed by the at least one proces sor, cause the device to at least to : obtain, from a network node , parameter data relating to a timing pattern of windows of expected traf fic activity; determine , based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determine , whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and; prioriti ze , based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, one of :

-receiving operations and/or transmitting operations associated with the windows of expected traf fic activity; or

- measurements associated with the measurement opportunity .

2 . The device of claim 1 , the at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : determine that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity; and prioriti ze , based on the determination that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity, receiving operations and/or transmitting operations associated with the expected traf fic activity .

3 . The device of claim 1 , the at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : determine that the at least one window in the timing pattern of the windows of expected traf fic activity partially overlaps with the measurement opportunity; prioriti ze receiving operations and/or transmitting operations associated with the expected traf fic activity in an overlapping portion of the window of the at least one window in the timing pattern of the windows of expected traf fic activity and the measurement opportunity; and prioriti ze the measurements in a non-overlapping portion or in non-overlapping portions of the window of the at least one window in the timing pattern of the windows of expected traf fic activity and the measurement opportunity .

4 . The device o f any one of claims 1 to 3 , wherein the parameter data comprises : a reference time for the at least one window in the timing pattern of the windows of expected traf fic activity; and a periodicity of the windows of expected traf fic activity .

5 . The device of claim 4 , the at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : determine time parameters of at least one measurement , based on the determining whether a window of the at least one window in the timing parameters of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity, the time parameters of the at least one measurement comprising at least a starting time of the at least one measurement , So, and a duration of the at least one measurement T_o ; and based on the time parameters of the at least one measurement , prioriti ze at least one of :

- measurements associated with the measurement opportunity .

6 . The device of claims 4 to 5 , the at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : determine an expected starting time of the at least one window in the timing pattern of the windows of expected traf fic activity, S_XR, at least based on the reference time , R, and the periodicity P .

7 . The device of any one o f claims 4 to 6 , wherein P is a rational number comprising a numerator and a denominator, and wherein the numerator and the denominator are both integers .

8 . The device of claim 7 dependent on claim 6 , wherein S_XR is determined based on : wherein t is an integer indicating system frame time , P_D is the denominator of P and P_N is the numerator of P .

9 . The device o f any one o f claims 6 to 8 , wherein the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity comprises evaluation of one or more conditional statements and at least one arithmetic operation .

10 . The device of any one of claims 6 - 9 , wherein determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity comprises : determining a portion of the measurement opportunity that does not overlap with the at least one window in the timing pattern of the windows of expected traf fic activity, by

- at least evaluating the value of S_XR against a value of a starting time of the measurement opportunity, S_M; and

- at least evaluating an ending time of the at least one window in the timing pattern of the windows of expected traf fic activity, E_XR against an ending time of the measurement opportunity, E_M .

11 . A network node , comprising : at least one processor ; and at least one memory storing instructions which, when executed by the at least one processor , cause the network node to at least to : obtain parameter data relating to a timing pattern of windows of expected traf fic activity; transmit the parameter data to a device ; determine , based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determine , whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and determine , based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, at least one of :

- skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity; or

- consider the device unavailable for scheduling relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity .

12 . The network node o f claim 11 , the at least one memory storing instructions which, when executed by the at least one processor, cause the network node to at least to : determine that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity; and determine , based on the determination that the window of the at least one window in the timing pattern of the windows of expected traf fic activity fully overlaps with the measurement opportunity, to skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity .

13 . The network node of claim 11 , the at least one memory storing instructions which, when executed by the at least one processor, cause the network node to at least to : determine that the at least one window in the timing pattern of the windows of expected traf fic activity partially overlaps with the measurement opportunity; determine to skip a scheduling restriction associated with the measurement opportunity relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity in an overlapping portion of the at least one window in the timing pattern of the windows of expected traf fic activity and the measurement opportunity; and consider the device unavailable for schedul ing relating receiving operations and/or transmitting operations associated with the windows of expected traf fic activity in a non-overlapping portion of the at least one window in the timing pattern of the windows of expected traf fic activity .

14 . The network node o f any one of claims 11 - 13 , wherein the parameter data comprises at least : a reference time for the at least one window in the timing pattern of the windows of expected traf fic activity; and a periodicity of the windows of expected traf fic activity .

15 . The network node of claim 14 , the at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : determine time parameters of at least one measurement , based on the determining whether a window of the at least one window in the timing parameters of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity, the time parameters of the at least one measurement comprising at least a starting time of the at least one measurement , S_o, and a duration of the at least one measurement T_o ; and based on the time parameters of the of the at least one measurement , determine at least one of :

16 . The network node of claims 14 to 15 , the at least one memory storing instructions which, when executed by the at least one processor, cause the device to at least to : determine an expected starting time of the at least one window in the timing pattern of the windows of expected traf fic activity, S_XR, at least based on R and P .

17 . The network node o f claims 14 to 16 , wherein P is a rational number comprising a numerator and a denominator, and wherein the numerator and the denominator are both integers .

18 . The network node of claim 17 dependent on claim

16 , wherein S_XR is determined based on : wherein t is an integer indicating system frame time , is the denominator of P and P_N is the numerator of

P .

19 . The network node of any of claims 16 to 18 , wherein determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity comprises evaluation of one or more conditional statements and at least one arithmetic operation .

20 . The network node o f any one of claims 16 - 19 , wherein determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity comprises : determining a portion of the measurement opportunity that does not overlap with the at least one window in the timing pattern of the windows of expected traf fic activity, by

21 . A method, comprising : obtaining, from a network node , parameter data relating to a timing pattern of windows of expected traf fic activity; determining, based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determining, whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and prioriti zing, based on the determination whether the window of the at least one window in the timing pattern of the windows of expected traffic activity at least partially overlaps with the measurement opportunity, one of :

- measurements associated with the measurement opportunity .

22 . A method, comprising : obtaining parameter data relating to a timing pattern of windows of expected traf fic activity; transmitting the parameter data to a device ; determining, based at least in part on the parameter data, at least one window in the timing pattern of the windows of expected traf fic activity; determining, whether a window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with a measurement opportunity; and determining, based on the determining whether the window of the at least one window in the timing pattern of the windows of expected traf fic activity at least partially overlaps with the measurement opportunity, at least one of :

23 . A computer program comprising instructions for causing an apparatus to carry out the method of claim 21 .

24 . A computer program comprising instructions for causing an apparatus to carry out the method of claim 22 .