Timing advance prediction with accuracy level configuration

Abstract

Systems, methods, apparatuses, and computer program products for predicting timing advance with accuracy level configuration. One method may include receiving, by a user equipment, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; predicting the TA value and an accuracy of the TA value of the at least one candidate network entity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

Description

TIMING ADVANCE PREDICTION WITH ACCURACY LEVELCONFIGURATIONTECHNICAL FIELD

[0001] Some example embodiments may generally relate to mobile or wireless telecommunication systems, such as 3rdGeneration Partnership Project (3GPP) Long Term Evolution (LTE), 5thgeneration (5G) radio access technology (RAT), new radio (NR) access technology, 6thgeneration (6G), and / or other communications systems. For example, certain example embodiments may relate to systems and / or methods for predicting timing advance with accuracy level configuration.BACKGROUND

[0002] Examples of mobile or wireless telecommunication systems may include radio frequency (RF) 5G RAT, the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), LTE Evolved UTRAN (E-UTRAN), LTE-Advanced (LTE-A), LTE-A Pro, NR access technology, and / or MulteFire Alliance. 5G wireless systems refer to the next generation (NG) of radio systems and network architecture. A 5G system is typically built on a 5G NR, but a 5G (or NG) network may also be built on E-UTRA radio. It is expected that NR can support service categories such as enhanced mobile broadband (eMBB), ultra-reliable low-latency- communication (URLLC), and massive machine-type communication (mMTC). NR is expected to deliver extreme broadband, ultra-robust, low-latency connectivity, and massive networking to support the Internet of Things (loT). The next generation radio access network (NG-RAN) represents the radio access network (RAN) for 5G, which may provide radio access for NR, LTE, and LTE-A. It is noted that the nodes in 5G providing radio access functionality to a user equipment (e.g., similar to the Node B in UTRAN or the Evolved Node B (eNB) in LTE) may be referred to as next-generation Node B (gNB) when built on NR radio, and may be referred to as next-generation eNB (NG-eNB) when built on E-UTRA radio.SUMMARY

[0003] In accordance with some example embodiments, a method may include receiving, by a user equipment, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0004] In accordance with certain example embodiments, an apparatus may include means for receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include means for predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The apparatus may further include means for transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0005] In accordance with various example embodiments, a non-transitory computer readable medium may include program instructions that, when executed by an apparatus, cause the apparatus to perform at least a method. The method may include receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0006] In accordance with some example embodiments, a computer program product may perform a method. The method may include receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the atleast one candidate network entity. The method may further include transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0007] In accordance with certain example embodiments, an apparatus may include 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 receive, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to predict the TA value and an accuracy of the TA value of the at least one candidate network entity. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to transmit, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0008] In accordance with various example embodiments, an apparatus may include receiving circuitry configured to perform receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include predicting circuitry configured to perform predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The apparatus may further include transmitting circuitry configured to perform transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0009] In accordance with some example embodiments, a method may include transmitting, by a network entity, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based, at leastpartially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0010] In accordance with certain example embodiments, an apparatus may include means for transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include means for receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity. The apparatus may further include means for scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0011] In accordance with various example embodiments, a non-transitory computer readable medium may include program instructions that, when executed by an apparatus, cause the apparatus to perform at least a method. The method may include transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0012] In accordance with some example embodiments, a computer program product may perform a method. The method may include transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0013] In accordance with certain example embodiments, an apparatus may include 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 transmit, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to receive, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to schedule at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0014] In accordance with various example embodiments, an apparatus may include transmitting circuitry configured to perform transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include receiving circuitry configured to perform receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity. The apparatus may further include scheduling circuitry configured to perform scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0015] In accordance with some example embodiments, a method may include receiving, by a user equipment, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include transmitting, to the network entity, an indication of the at least one candidate network entity based, at least partially,on the predicted TA value of the at least one candidate network entity above a threshold value.

[0016] In accordance with certain example embodiments, an apparatus may include means for receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include means for predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The apparatus may further include means for transmitting, to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0017] In accordance with various example embodiments, a non-transitory computer readable medium may include program instructions that, when executed by an apparatus, cause the apparatus to perform at least a method. The method may include receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include transmitting, to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0018] In accordance with some example embodiments, a computer program product may perform a method. The method may include receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include transmitting, to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0019] In accordance with certain example embodiments, an apparatus may include 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 receive, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to predict the TA value and an accuracy of the TA value of the at least one candidate network entity. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to transmit, to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0020] In accordance with various example embodiments, an apparatus may include receiving circuitry configured to perform receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include predicting circuitry configured to perform predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The apparatus may further include transmitting circuitry configured to perform transmitting, to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0021] In accordance with some example embodiments, a method may include transmitting, by a network entity, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based,at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0022] In accordance with certain example embodiments, an apparatus may include means for transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include means for receiving, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity. The apparatus may further include means for scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0023] In accordance with various example embodiments, a non-transitory computer readable medium may include program instructions that, when executed by an apparatus, cause the apparatus to perform at least a method. The method may include transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0024] In accordance with some example embodiments, a computer program product may perform a method. The method may include transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0025] In accordance with certain example embodiments, an apparatus may include 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 transmit, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to receive, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to schedule circuitry configured to perform scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0026] In accordance with various example embodiments, an apparatus may include transmitting circuitry configured to perform transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include receiving circuitry configured to perform receiving, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity. The apparatus may further include scheduling circuitry configured to perform scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0027] In accordance with some example embodiments, a method may include receiving, by a user equipment, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include comparing the TA prediction to a threshold. The method may further include upon determining that the TA predictionvalue is above the threshold, transmitting, to the network entity, the predicted TA value or beam prediction associated with a capability of the apparatus.

[0028] In accordance with certain example embodiments, an apparatus may include means for receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include means for predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The apparatus may further include means for comparing the TA prediction to a threshold. The apparatus may further include means for upon determining that the TA prediction value is above the threshold, transmitting, to the network entity, the predicted TA value or beam prediction associated with a capability of the apparatus.

[0029] In accordance with various example embodiments, a non-transitory computer readable medium may include program instructions that, when executed by an apparatus, cause the apparatus to perform at least a method. The method may include receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include comparing the TA prediction to a threshold. The method may further include upon determining that the TA prediction value is above the threshold, transmitting, to the network entity, the predicted TA value or beam prediction associated with a capability of the apparatus.

[0030] In accordance with some example embodiments, a computer program product may perform a method. The method may include receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The method may further include comparing the TA prediction to a threshold. The method may further include upon determining that the TAprediction value is above the threshold, transmitting, to the network entity, the predictedTA value or beam prediction associated with a capability of the apparatus.

[0031] In accordance with certain example embodiments, an apparatus may include 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 receive, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to predict the TA value and an accuracy of the TA value of the at least one candidate network entity. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to compare the TA prediction to a threshold. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to upon determining that the TA prediction value is above the threshold, transmit, to the network entity, the predicted TA value or beam prediction associated with a capability of the apparatus.

[0032] In accordance with various example embodiments, an apparatus may include receiving circuitry configured to perform receive, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include predicting circuitry configured to perform predicting the TA value and an accuracy of the TA value of the at least one candidate network entity. The apparatus may further include comparing circuitry configured to perform comparing the TA prediction to a threshold. The apparatus may further include transmitting circuitry configured to perform upon determining that the TA prediction value is above the threshold, transmitting, to the network entity, the predicted TA value or beam prediction associated with a capability of the apparatus.

[0033] In accordance with some example embodiments, a method may include transmitting, by a network entity, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least onecandidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0034] In accordance with certain example embodiments, an apparatus may include means for transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include means for receiving, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity. The apparatus may further include means for scheduling at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0035] In accordance with various example embodiments, a non-transitory computer readable medium may include program instructions that, when executed by an apparatus, cause the apparatus to perform at least a method. The method may include transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity. The method may further include scheduling at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0036] In accordance with some example embodiments, a computer program product may perform a method. The method may include transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The method may further include receiving, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity. The method mayfurther include scheduling at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0037] In accordance with certain example embodiments, an apparatus may include 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 transmit, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to receive, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity. The at least one memory and instructions, when executed by the at least one processor, may further cause the apparatus at least to schedule at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0038] In accordance with various example embodiments, an apparatus may include transmitting circuitry configured to perform transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility. The apparatus may further include receiving circuitry configured to perform receiving, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity. The apparatus may further include scheduling circuitry configured to perform scheduling at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.BRIEF DESCRIPTION OF THE DRAWINGS

[0039] For a proper understanding of example embodiments, reference should be made to the accompanying drawings, wherein:

[0040] FIG. 1 illustrates an example of a signaling procedure;

[0041] FIG. 2 illustrates an example of a signaling diagram according to certain example embodiments;

[0042] FIG. 3 illustrates an example of a signaling diagram according to some example embodiments;

[0043] FIG. 4 illustrates an example of a signaling diagram according to various example embodiments;

[0044] FIG. 5 illustrates an example of a flow diagram of a method according to certain example embodiments;

[0045] FIG. 6 illustrates an example of a flow diagram of a method according to some example embodiments;

[0046] FIG. 7 illustrates an example of a flow diagram of a method according to various example embodiments;

[0047] FIG. 8 illustrates an example of a flow diagram of a method according to certain example embodiments;

[0048] FIG. 9 illustrates an example of a flow diagram of a method according to some example embodiments;

[0049] FIG. 10 illustrates an example of a flow diagram of a method according to various example embodiments;

[0050] FIG. 11 illustrates an example of various network devices according to some example embodiments; and

[0051] FIG. 12 illustrates an example of a 5G network and system architecture according to certain example embodiments.DETAILED DESCRIPTION

[0052] It will be readily understood that the components of certain example embodiments, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of some example embodiments of systems, methods, apparatuses, and computer program products for predicting timing advance withaccuracy level configuration is not intended to limit the scope of certain example embodiments, but is instead representative of selected example embodiments.

[0053] 3GPP Release 18 / 19 supports AI-ML for beam prediction, where AI / ML- based beam management can leverage AI / ML models to predict the best beam(s) based on a limited set of measurements. AI-ML may be used for spatial-domain prediction (z.e., beam prediction based on a limited set of measurements that does not contain any historical information) and time-domain prediction (z.e., beam prediction into the future based on a limited set of measurements that contains historical information).

[0054] Al -ML may perform measurements and prediction based on two beam sets, Set A (z.e., the complete set of beams over which the prediction will operate) and Set B (z.e., the set of beams whose measurements are inputted to the AI / ML model (e.g., Ll-RSRP, etc.)). Set B can differ from Set A (in space-domain and time-domain prediction), be a subset of Set A (in space-domain and time-domain prediction), or be the same as Set A (in time-domain prediction).

[0055] FIG. 1 illustrates an example of a signaling procedure for layer 1 (LI) and / or layer 2 (L2)-triggered mobility (LTM). In the LTM procedures, the gNB receives LI and / or L2 measurement reports from a UE, and in response, the gNB a cell switch command to the UE signaled via a MAC-CE. The cell switch command indicates an LTM candidate cell configuration that the gNB previously prepared and provided to the UE through RRC signalling. The UE then switches to the target cell according to the cell switch command. The LTM procedure can be used to reduce the mobility latency. Throughout this document, lower layer triggered mobility may be L1 / L2 triggered mobility, or layer 1 / layer 2 triggered mobility, or layer 1 and / or layer 2 triggered mobility; in addition, “lower layer” may refer to layer 1 and / or layer 2.

[0056] When the NW configures the UE with the LTM procedure, it is possible to activate candidate TCI states of at least one LTM target cell prior to the switching to the target cell. This allows the UE to be DL synchronized with those cells, thereby facilitating a faster cell switch to one of those cells.

[0057] In early uplink synchronization, the source gNB may trigger the UE to perform timing advance (TA) acquisition for a specific candidate cell. Currently, the PDCCH ordered RACH (z.e., network triggered) and UE based TA estimation (by measurement) methods are supported. In the cell switch command, the network may indicate whether the UE shall access the target cell with a RACH procedure if a TA value is not provided. On the other hand, the network can instruct the UE to perform RACH-less procedure towards target cell if a valid TA value is available.

[0058] Certain example embodiments described herein may have various benefits and / or advantages to overcome the disadvantages described above. For example, certain example embodiments may reduce the latency and resourcing overhead resulting from a RACH procedure. Thus, certain example embodiments discussed below are directed to improvements in computer-related technology.

[0059] In certain example embodiments, the UE may perform TA prediction using one or multiple subset(s) of measurements and / or subset(s) of received time difference(s) between N1 SSB beams of serving cell and N2 SSB beams of Top-M candidate cells as input to AI / ML model. The UE can then predict and report the probability / accuracy / confidence-interval of the predicted TA values in spatial domain and / or temporal domain.

[0060] FIG. 2 illustrates an example of a signaling diagram 200 for predicting timing advance with accuracy level configuration. UE 220 may be similar to UE 1120, and NE 230 (z.e., serving cell) and NE 240 (z.e., neighboring cell) may be similar to NE 1110, as illustrated in FIG. 11, according to certain example embodiments.

[0061] In general, UE 220 UE may be configured to report the predicted TA value of candidate beams for LTM along with the accuracy / probability value (confidence interval) of the predicted TA. For example, UE 220 may be connected to beam 1 on TRP1 of celll, and UE 220 may be configured to report the accuracy level of the TA prediction along with the predicted TA value of candidate beams for LTM. UE 220 may measure beam 2 on TRP2 of cell2 as a candidate beam for LTM, and may predict TA value x for beam 2. The accuracy / probability / confidence interval of the prediction may be estimated by UE 220 at 80%. UE 220 may report beam 2 for LTM along with thepredicted TA value and the accuracy / probability / confidence-interval of the predictedTA.

[0062] At operation 201, UE 220 and NE 230 may place UE 220 into an RRC CONNECTED mode.

[0063] At operation 202, UE 220 may transmit to NE 230 a TA prediction and / or beam prediction as part of the capabilities of UE 220.

[0064] At operation 203, NE 230 may transmit to UE 220 an RRC configuration for LTM, which may include TA prediction, beam prediction, and accuracy thresholds.

[0065] At operation 204, UE 220 may perform an inference procedure.

[0066] In certain example embodiments, UE 220 may perform an inference procedure to generate TA prediction values of NE 230 (z.e., serving cell) and NE 240 (z.e., neighboring cell), and probabilities of TA value predictions for NE 230 (z.e., serving cell) and NE 240 (z.e., neighboring cell).

[0067] In some example embodiments, UE 220 may perform an inference procedure to generate TA prediction values of NE 230 (z.e., serving cell) and NE 240 (z.e., neighboring cell), beam predictions of NE 240 (z.e., neighboring cell), and probabilities of TA value predictions for NE 230 (z.e., serving cell) beams and NE 240 (z.e., neighboring cell).

[0068] At operation 205, UE 220 may transmit to NE 230 a report indicating candidate beams / cells with predicted TA values, which may include an accuracy of a predicted TA.

[0069] At operation 206, NE 230 may schedule RACH resources, based upon a fulfilled accuracy level of the TA prediction by UE 220.

[0070] At operation 207, NE 230 may not transmit allocated RACH resources.

[0071] At operation 208, NE 230 may trigger an LTM procedure.

[0072] At operation 209, NE 240 may transmit PDSCH to UE 220.

[0073] At operation 210, UE 220 may transmit PUSCH to NE 240.

[0074] FIG. 3 illustrates an example of a signaling diagram 300 for predicting timing advance with accuracy level configuration. UE 320 may be similar to UE 1120, and NE330 (z.e., serving cell) and NE 340 (z.e., neighboring cell) may be similar to NE 1110, as illustrated in FIG. 11, according to certain example embodiments.

[0075] In general, UE 320 may be configured with a minimum accuracy / probability value (confidence interval) to apply to at the output of the inference model. UE 320 may only report a candidate beam for LTM if the predicted TA value is above the minimum probability value. For example, UE 320 may be connected to beam 1 on TRP1 of celll, and UE 320 may be configured to only report candidate beam(s) for LTM that fulfill a criterion for the accuracy value of the predicted TA value (e.g., > 70%). UE 320 may measure beam 2 on TRP2 of cell2 as a candidate beam for LTM. UE 320 may predict TA value x for beam 2 and the accuracy / probability / confidence interval of the prediction may be estimated by UE 320 at 80%. UE 320 may measure beam 3 on TRP2 of cell2 (or TRP3 of cell2, or TRP3 of cell3, ...) as a candidate beam for LTM. UE 320 may predict TA value x for beam 3 and the accuracy / probability / confidence interval of the prediction is estimated by UE 320 at 50%. UE 320 may only report beam 2 as candidate beam for LTM (optionally includes 80% accuracy in the reporting as well). Beam 3 may not be reported since it does not fulfill the configured threshold of 70% accuracy.

[0076] In some example embodiments, UE 320 may determine the accuracy of predicted confident interval of predicted TA values. UE 320 may then compare the predicted confident interval with its own defined threshold.

[0077] Operations 301-303 may be similar to operations 201-203.

[0078] At operation 304, UE 320 may perform an inference procedure.

[0079] In certain example embodiments, UE 320 may perform an inference procedure to generate TA prediction values of NE 330 (z.e., serving cell) and NE 340 (z.e., neighboring cell), and probabilities of TA value predictions for NE 330 (z.e., serving cell) and NE 340 (z.e., neighboring cell).

[0080] In some example embodiments, UE 320 may perform an inference procedure to generate TA prediction values of NE 330 (z.e., serving cell) and NE 340 (z.e., neighboring cell), beam predictions of NE 340 (z.e., neighboring cell), and probabilities of TA value predictions for NE 330 (z.e., serving cell) beams and NE 340 (z.e., neighboring cell).

[0081] At operation 305, UE 320 may only report to NE 330 (z.e., serving cell) only beams / cells where predicted TA values are above a configured threshold.

[0082] Operations 306-310 may be similar to operations 206-210.

[0083] FIG. 4 illustrates an example of a signaling diagram 400 for predicting timing advance with accuracy level configuration. UE 420 may be similar to UE 1120, and NE 430 (z.e., serving cell) and NE 440 (z.e., neighboring cell) may be similar to NE 1110, as illustrated in FIG. 11, according to certain example embodiments.

[0084] Operations 401-403 may be similar to operations 201-203.

[0085] At operation 404, UE 420 may perform an inference procedure.

[0086] In certain example embodiments, UE 420 may infer TA prediction values of NE 430 and NE 440, and confidence intervals / probabilities of TA value predictions for NE 430 and NE 440.

[0087] In some example embodiments, UE 420 may infer TA prediction values of NE 430 and NE 440, beam predictions of NE 440, and confidence intervals / probabilities of TA value predictions for NE 430 and NE 440.

[0088] At operation 405, UE 420 may compare the predicted probability / confidence interval of the predicted TA values with the threshold defined by UE 420. If above the threshold, UE 420 may report a predicted TA value, candidate beam / cell, and / or and estimated accuracy. However, if below the threshold, UE 420 may not report the TA value for the candidate beam / cell.

[0089] Operations 406-411 may be similar to operations 205-210.

[0090] FIG. 5 illustrates an example of a flow diagram of a method 500 that may be performed by a UE, such as UE 1120 illustrated in FIG. 11, according to various example embodiments.

[0091] At step 501, the method may include receiving, by a user equipment, from a network entity such as NE 1110 illustrated in FIG. 11, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility.

[0092] In some example embodiments, the network entity may include a beam of a neighboring TRP of the same cell (intra-cell mTRP) or a beam of a neighboring TRPof a neighboring cell (LTM). Furthermore, the TA value estimation may be applicable only to a single beam of the neighboring cell or to the entire neighboring cell, depending on channel propagation (LOS), DL RS, and / or UE capability.

[0093] At step 502, the method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity.

[0094] At step 503, the method may further include transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0095] In certain example embodiments, the predicted TA value and accuracy of the TA value of the at least one candidate network entity may be associated with at least one beam prediction of the at least one candidate network entity.

[0096] In some example embodiments, the method may further include predicting a TA value of the network entity and an accuracy of the predicted TA value of the network entity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the network entity. It is noted that accuracy, probability, and confidence interval may be interchangeable.

[0097] In certain example embodiments, the predicted TA value and accuracy of the TA value of the network entity may be associated with at least one beam prediction of the network entity.

[0098] In various example embodiments, the method may further include transmitting, to the network entity, the at least one beam prediction of the at least one candidate network entity, and the at least one beam prediction of the network entity.

[0099] FIG. 6 illustrates an example of a flow diagram of a method 600 that may be performed by a NE, such as NE 1110 illustrated in FIG. 11, according to various example embodiments.

[0100] At step 601, the method may include transmitting, by a network entity, to a user equipment such as UE 1120 illustrated in FIG. 11, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility.

[0101] At step 602, the method may further include receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity.

[0102] In various example embodiments, neighbor cells may include candidate cells. The UE may predict the TA value (and accuracy) of the neighbor cell (value valid for all SSB of that cell) and / or the UE may predict the TA value (and accuracy) of a specific beam (e.g., best received beam with Ll-RSRP) of the neighbor cell. This may include a single TA and ingle accuracy for all beams of neighbor cell, different TAs per beam but same accuracy of all predicted TA values of the neighbor cell, and / or different TAs per beam predicted with a different accuracy for each beam of the neighbor cell.

[0103] At step 603, the method may further include scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0104] In certain example embodiments, the predicted TA value and accuracy of the TA value of the at least one candidate network entity may be associated with at least one beam prediction of the at least one candidate network entity.

[0105] In some example embodiments, the method may further include receiving, from the user equipment, a predicted TA value of the network entity or user equipment, and accuracy of the predicted TA value of the network entity or user equipment.

[0106] In various example embodiments, the predicted TA value and accuracy of the TA value of the apparatus may be associated with at least one beam prediction of the apparatus.

[0107] In certain example embodiments, the method may further include receiving, from the user equipment, the at least one beam prediction of the at least one candidate network entity, and the at least beam prediction of the network entity or user equipment.

[0108] FIG. 7 illustrates an example of a flow diagram of a method 700 that may be performed by a UE, such as UE 1120 illustrated in FIG. 11, according to various example embodiments.

[0109] At step 701, the method may include receiving, from a network entity such as NE 1110 illustrated in FIG. 11, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility.

[0110] In some example embodiments, the network entity may include a beam of a neighboring TRP of the same cell (intra-cell mTRP) or a beam of a neighboring TRP of a neighboring cell (LTM). Furthermore, the TA value estimation may be applicable only to a single beam of the neighboring cell or to the entire neighboring cell, depending on channel propagation (LOS), DL RS, and / or UE capability.

[0111] At step 702, the method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity.

[0112] At step 703, the method may further include transmitting, to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0113] In certain example embodiments, the predicted TA value and accuracy of the TA value of the at least one candidate network entity may be associated with at least one beam prediction of the at least one candidate network entity.

[0114] In some example embodiments, the method may further include predicting a TA value of the network entity and an accuracy of the predicted TA value of the network entity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the network entity.

[0115] In various example embodiments, the predicted TA value and accuracy of the TA value of the network entity may be associated with at least one beam prediction of the network entity.

[0116] In certain example embodiments, the method may further include transmitting, to the network entity, the at least one beam prediction of the at least one candidate network entity, and the at least one beam prediction of the network entity.

[0117] FIG. 8 illustrates an example of a flow diagram of a method 800 that may be performed by a NE, such as NE 1110 illustrated in FIG. 11, according to various example embodiments.

[0118] At step 801, the method may include transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility.

[0119] At step 802, the method may further include receiving, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity.

[0120] In various example embodiments, neighbor cells may include candidate cells. The UE may predict the TA value (and accuracy) of the neighbor cell (value valid for all SSB of that cell) and / or the UE may predict the TA value (and accuracy) of a specific beam (e.g., best received beam with Ll-RSRP) of the neighbor cell. This may include a single TA and ingle accuracy for all beams of neighbor cell, different TAs per beam but same accuracy of all predicted TA values of the neighbor cell, and / or different TAs per beam predicted with a different accuracy for each beam of the neighbor cell.

[0121] At step 803, the method may further include scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0122] In certain example embodiments, the predicted TA value and accuracy of the TA value of the at least one candidate network entity may be associated with at least one beam prediction of the at least one candidate network entity.

[0123] In some example embodiments, the method may further include receiving, from the user equipment, a predicted TA value of the apparatus and accuracy of the predicted TA value of the apparatus.

[0124] In various example embodiments, the predicted TA value and accuracy of the TA value of the apparatus may be associated with at least one beam prediction of the apparatus.

[0125] In certain example embodiments, the method may further include receiving, from the user equipment, the at least one beam prediction of the at least one candidate network entity, and the at least beam prediction of the apparatus.

[0126] FIG. 9 illustrates an example of a flow diagram of a method 900 that may be performed by a UE, such as UE 1120 illustrated in FIG. 11, according to various example embodiments.

[0127] At step 901, the method may include receiving, by a user equipment, from a network entity such as NE 1110 illustrated in FIG. 11, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility.

[0128] In some example embodiments, the network entity may include a beam of a neighboring TRP of the same cell (intra-cell mTRP) or a beam of a neighboring TRP of a neighboring cell (LTM). Furthermore, the TA value estimation may be applicable only to a single beam of the neighboring cell or to the entire neighboring cell, depending on channel propagation (LOS), DL RS, and / or UE capability.

[0129] At step 902, the method may further include predicting the TA value and an accuracy of the TA value of the at least one candidate network entity.

[0130] At step 903, the method may further include comparing the TA prediction to a threshold.

[0131] At step 904, the method may further include, upon determining that the TA prediction value is above the threshold, transmit, to the network entity, the predicted TA value or beam prediction associated with a capability of the user equipment.

[0132] In certain example embodiments, the predicted TA value and accuracy of the TA value of the at least one candidate network entity may be associated with at least one beam prediction of the at least one candidate network entity.

[0133] In some example embodiments, the method may further include predicting a TA value of the network entity and an accuracy of the predicted TA value of the networkentity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the network entity.

[0134] In various example embodiments, the predicted TA value and accuracy of the TA value of the apparatus may be associated with at least one beam prediction of the apparatus.

[0135] In certain example embodiments, the method may further include transmitting, to the network entity, the at least one beam prediction of the at least one candidate network entity, and the at least one beam prediction of the network entity.

[0136] In some example embodiments, the threshold may be defined by the apparatus.

[0137] In various example embodiments, the method may further include determining that the predicted TA value is above the threshold.

[0138] FIG. 10 illustrates an example of a flow diagram of a method 1000 that may be performed by a NE, such as NE 1110 illustrated in FIG. 11, according to various example embodiments.

[0139] At step 1001, the method may include transmitting, by a network entity, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility.

[0140] At step 1002, the method may further include receiving, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0141] In various example embodiments, neighbor cells may include candidate cells. The UE may predict the TA value (and accuracy) of the neighbor cell (value valid for all SSB of that cell) and / or the UE may predict the TA value (and accuracy) of a specific beam (e.g., best received beam with Ll-RSRP) of the neighbor cell. This may include a single TA and ingle accuracy for all beams of neighbor cell, different TAs per beam but same accuracy of all predicted TA values of the neighbor cell, and / or different TAs per beam predicted with a different accuracy for each beam of the neighbor cell.

[0142] At step 1003, the method may further include scheduling at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0143] In certain example embodiments, the predicted TA value and accuracy of the TA value of the at least one candidate network entity may be associated with at least one beam prediction of the at least one candidate network entity.

[0144] In some example embodiments, the method may further include receiving, from the user equipment, a predicted TA value of the apparatus and accuracy of the predicted TA value of the network entity.

[0145] In various example embodiments, the predicted TA value and accuracy of the TA value of the apparatus may be associated with at least one beam prediction of the apparatus.

[0146] In certain example embodiments, the method may further include receiving, from the user equipment, the at least one beam prediction of the at least one candidate network entity, and the at least beam prediction of the apparatus.

[0147] FIG. 11 illustrates an example of a system according to certain example embodiments. In one example embodiment, a system may include multiple devices, such as, for example, NE 1110 and / or UE 1120.

[0148] NE 1110 may be one or more of a base station (e.g., 3G UMTS NodeB, 4G LTE Evolved NodeB, or 5G NR Next Generation NodeB), a serving gateway, a server, and / or any other access node or combination thereof. NE 1110 may also include a beam of a neighboring TRP of the same cell (intra-cell mTRP) and / or a beam of a neighboring TRP of a neighboring cell (LTM).

[0149] NE 1110 may further include at least one gNB -centralized unit (CU), which may be associated with at least one gNB -distributed unit (DU). The at least one gNB-CU and the at least one gNB -DU may be in communication via at least one Fl interface, at least one Xn-C interface, and / or at least one NG interface via a 5thgeneration core (5GC).

[0150] UE 1120 may include one or more of a mobile device, such as a mobile phone, smart phone, personal digital assistant (PDA), tablet, or portable media player, digital camera, pocket video camera, video game console, navigation unit, such as a globalpositioning system (GPS) device, desktop or laptop computer, single-location device, such as a sensor or smart meter, or any combination thereof. Furthermore, NE 1110 and / or UE 1120 may be one or more of a citizens broadband radio service device (CBSD).

[0151] NE 1110 and / or UE 1120 may include at least one processor, respectively indicated as 1111 and 1121. Processors 1111 and 1121 may be embodied by any computational or data processing device, such as a central processing unit (CPU), application specific integrated circuit (ASIC), or comparable device. The processors may be implemented as a single controller, or a plurality of controllers or processors.

[0152] At least one memory may be provided in one or more of the devices, as indicated at 1112 and 1122. The memory may be fixed or removable. The memory may include instructions stored thereon. Such instructions may include computer program instructions or computer code contained therein. Memories 1112 and 1122 may independently be any suitable storage device, such as a non-transitory computer- readable medium. The term “non-transitory,” as used herein, may correspond to a limitation of the medium itself (z.e., tangible, not a signal) as opposed to a limitation on data storage persistency (e.g., random access memory (RAM) vs. read-only memory (ROM)). A hard disk drive (HDD), random access memory (RAM), flash memory, or other suitable memory may be used. The memories may be combined on a single integrated circuit as the processor, or may be separate from the one or more processors. Furthermore, the computer program instructions stored in the memory, and which may be processed by the processors, may be any suitable form of computer program code, for example, a compiled or interpreted computer program written in any suitable programming language.

[0153] Processors 1111 and 1121, memories 1112 and 1122, and any subset thereof, may be configured to provide means corresponding to the various blocks of FIGs. 2-10. Although not shown, the devices may also include positioning hardware, such as GPS or micro electrical mechanical system (MEMS) hardware, which may be used to determine a location of the device. Other sensors are also permitted, and may beconfigured to determine location, elevation, velocity, orientation, and so forth, such as barometers, compasses, and the like.

[0154] As shown in FIG. 11 , transceivers 1113 and 1123 may be provided, and one or more devices may also include at least one antenna, respectively illustrated as 1114 and 1124. The device may have many antennas, such as an array of antennas configured for multiple input multiple output (MIMO) communications, or multiple antennas for multiple RATs. Other configurations of these devices, for example, may be provided. Transceivers 1113 and 1123 may be a transmitter, a receiver, both a transmitter and a receiver, or a unit or device that may be configured both for transmission and reception.

[0155] The memory and the computer program instructions may be configured, with the processor for the particular device, to cause a hardware apparatus, such as UE, to perform any of the processes described above (z.e., FIGs. 2-10). Therefore, in certain example embodiments, a non-transitory computer-readable medium may be encoded with computer instructions that, when executed in hardware, perform a process such as one of the processes described herein. Alternatively, certain example embodiments may be performed entirely in hardware.

[0156] In certain example embodiments, an apparatus may include circuitry configured to perform any of the processes or functions illustrated in FIGs. 2-10. As used in this application, the term “circuitry” may refer to one or more or all of the following: (a) hardware-only circuit implementations (such as implementations in only analog and / or digital circuitry), (b) combinations of hardware circuits and software, such as (as applicable): (i) a combination of analog and / or digital hardware circuit(s) with software / firmware and (ii) any portions of hardware processor(s) with software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions), and (c) hardware circuit(s) and or processor(s), such as a microprocessor(s) or a portion of a microprocessor(s), that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation. This definition of circuitry applies to all uses of this term in this application, including in any claims. As a further example, as used in this application,the term circuitry also covers an implementation of merely a hardware circuit or processor (or multiple processors) or portion of a hardware circuit or processor and its (or their) accompanying software and / or firmware. The term circuitry also covers, for example and if applicable to the particular claim element, a baseband integrated circuit or processor integrated circuit for a mobile device or a similar integrated circuit in server, a cellular network device, or other computing or network device.

[0157] FIG. 12 illustrates an example of a 5G network and system architecture according to certain example embodiments. Shown are multiple network functions that may be implemented as software operating as part of a network device or dedicated hardware, as a network device itself or dedicated hardware, or as a virtual function operating as a network device or dedicated hardware. The NE and UE illustrated in FIG. 12 may be similar to NE 1110 and UE 1120, respectively. The user plane function (UPF) may provide services such as intra-RAT and inter-RAT mobility, routing and forwarding of data packets, inspection of packets, user plane quality of service (QoS) processing, buffering of downlink packets, and / or triggering of downlink data notifications. The application function (AF) may primarily interface with the core network to facilitate application usage of traffic routing and interact with the policy framework.

[0158] According to certain example embodiments, processors 1111 and 1121, and memories 1112 and 1122, may be included in or may form a part of processing circuitry or control circuitry. In addition, in some example embodiments, transceivers 1113 and 1123 may be included in or may form a part of transceiving circuitry.

[0159] In some example embodiments, an apparatus (e.g., NE 1110 and / or UE 1120) may include means for performing a method, a process, or any of the variants discussed herein. Examples of the means may include one or more processors, memory, controllers, transmitters, receivers, and / or computer program code for causing the performance of the operations.

[0160] In various example embodiments, apparatus 1120 may be controlled by memory 1122 and processor 1121 to receive, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least onecandidate network entity, for lower layer triggered mobility; predict the TA value and an accuracy of the TA value of the at least one candidate network entity; and transmit, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0161] Certain example embodiments may be directed to an apparatus that includes means for performing any of the methods described herein including, for example, means for receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; means for predicting the TA value and an accuracy of the TA value of the at least one candidate network entity; and means for transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

[0162] In various example embodiments, apparatus 1110 may be controlled by memory 1112 and processor 1111 to transmit, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; receive, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity; and schedule at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0163] Certain example embodiments may be directed to an apparatus that includes means for performing any of the methods described herein including, for example, means for transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; means for receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity; and means for scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0164] In various example embodiments, apparatus 1120 may be controlled by memory 1122 and processor 1121 to receive, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; predict the TA value and an accuracy of the TA value of the at least one candidate network entity; and transmit to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0165] Certain example embodiments may be directed to an apparatus that includes means for performing any of the methods described herein including, for example, means for receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; means for predicting the TA value and an accuracy of the TA value of the at least one candidate network entity; and means for transmitting to the network entity, an indication of the at least one candidate network entity based, at least partially, on the predicted TA value of the at least one candidate network entity above a threshold value.

[0166] In various example embodiments, apparatus 1110 may be controlled by memory 1112 and processor 1111 to transmit, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; receive, from the user equipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity; and schedule at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0167] Certain example embodiments may be directed to an apparatus that includes means for performing any of the methods described herein including, for example, means for transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; means for receiving, from the userequipment, a predicted TA value and an accuracy of the predicted TA value of the at least one candidate network entity; and means for scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

[0168] In various example embodiments, apparatus 1120 may be controlled by memory 1122 and processor 1121 to predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; predict the TA value and an accuracy of the TA value of the at least one candidate network entity; compare the TA prediction to a threshold; upon determining that the TA prediction value is above the threshold, transmit, to the network entity, the predicted TA value or beam prediction associated with a capability of the apparatus.

[0169] Certain example embodiments may be directed to an apparatus that includes means for performing any of the methods described herein including, for example, means for receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; means for predicting the TA value and an accuracy of the TA value of the at least one candidate network entity; means for comparing the TA prediction to a threshold; and means for upon determining that the TA prediction value is above the threshold, transmitting, to the network entity, the predicted TA value or beam prediction associated with a capability of the apparatus.

[0170] In various example embodiments, apparatus 1110 may be controlled by memory 1112 and processor 1111 to transmit, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; receive, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity; and schedule at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0171] Certain example embodiments may be directed to an apparatus that includes means for performing any of the methods described herein including, for example,means for transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; means for receiving, from the user equipment, the predicted TA value and accuracy of the TA value of the at least one candidate network entity; and means for scheduling at least one random access channel, RACH, resource based at least upon the received accuracy of each of the at least one TA prediction values.

[0172] The features, structures, or characteristics of example embodiments described throughout this specification may be combined in any suitable manner in one or more example embodiments. For example, the usage of the phrases “various embodiments,” “certain embodiments,” “some embodiments,” or other similar language throughout this specification refers to the fact that a particular feature, structure, or characteristic described in connection with an example embodiment may be included in at least one example embodiment. Thus, appearances of the phrases “in various embodiments,” “in certain embodiments,” “in some embodiments,” or other similar language throughout this specification does not necessarily all refer to the same group of example embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more example embodiments.

[0173] As used herein, “at least one of the following: ” and “at least one of ” and similar wording, where the list of two or more elements are joined by “and” or “or,” mean at least any one of the elements, or at least any two or more of the elements, or at least all the elements.

[0174] Additionally, if desired, the different functions or procedures discussed above may be performed in a different order and / or concurrently with each other. Furthermore, if desired, one or more of the described functions or procedures may be optional or may be combined. As such, the description above should be considered as illustrative of the principles and teachings of certain example embodiments, and not in limitation thereof.

[0175] One having ordinary skill in the art will readily understand that the example embodiments discussed above may be practiced with procedures in a different order,and / or with hardware elements in configurations which are different than those which are disclosed. Therefore, although some embodiments have been described based upon these example embodiments, it would be apparent to those of skill in the art that certain modifications, variations, and alternative constructions would be apparent, while remaining within the spirit and scope of the example embodiments.

[0176] Partial Glossary

[0177] 3GPP 3rdGeneration Partnership Project

[0178] 5G 5thGeneration

[0179] 5GC 5thGeneration Core

[0180] 5GS 5thGeneration System

[0181] 5QI 5thGeneration Quality of Service Indicator

[0182] 6G 6thGeneration

[0183] ACK Acknowledgement

[0184] AF Application Function

[0185] AMF Access and Mobility Management Function

[0186] ARQ Automatic Repeat Request

[0187] ASIC Application Specific Integrated Circuit

[0188] BS Base Station

[0189] BSD Bucket Size Duration

[0190] BSR Buffer Status Report

[0191] CAPC Channel Access Priority Class

[0192] CBSD Citizens Broadband Radio Service Device

[0193] CCCH Common Control Channel

[0194] CE Control Elements

[0195] CG Configured Grant

[0196] CN Core Network

[0197] CPU Central Processing Unit

[0198] CRC Cyclic Redundancy Check

[0199] CU Centralized Unit

[0200] DAI Downlink Assignment Index

[0201] DCCH Dedicated Control Channel

[0202] DCI Downlink Control Information

[0203] DL Downlink

[0204] DMRS Demodulation Reference Signal

[0205] DRB Data Radio Bearer

[0206] DU Distributed Unit

[0207] eMBB Enhanced Mobile Broadband

[0208] eMTC Enhanced Machine Type Communication

[0209] eNB Evolved Node B

[0210] eOLLA Enhanced Outer Loop Link Adaptation

[0211] EPS Evolved Packet System

[0212] FDD Frequency Division Duplex

[0213] FR Frequency Range

[0214] gNB Next Generation Node B

[0215] GPS Global Positioning System

[0216] HARQ Hybrid Automatic Repeat Request

[0217] HARQ PID Hybrid Automatic Repeat Request Process Identifier

[0218] HDD Hard Disk Drive

[0219] IEEE Institute of Electrical and Electronics Engineers

[0220] IMSI International Mobile Subscriber Identity

[0221] loT Internet of Things

[0222] IPTV Internet Protocol Television

[0223] LI Layer 1

[0224] L2 Layer 2

[0225] LBT Listen Before Talk

[0226] LCH Logical Channel

[0227] LCP Logical Channel Prioritization

[0228] LTE Long-Term Evolution

[0229] LTE-A Long-Term Evolution Advanced

[0230] MAC Medium Access Control

[0231] MBS Multicast and Broadcast Systems

[0232] MC Multicast

[0233] MCS Modulation and Coding Scheme

[0234] MEMS Micro Electrical Mechanical System

[0235] MIB Master Information Block

[0236] MIMO Multiple Input Multiple Output

[0237] MME Mobility Management Entity

[0238] mMTC Massive Machine Type Communication

[0239] MPDCCH Machine Type Communication Physical Downlink ControlChannel

[0240] MTC Machine Type Communication

[0241] NACK Negative Acknowledgement

[0242] NAS Non-Access Stratum

[0243] NB-IoT Narrowband Internet of Things

[0244] NE Network Entity

[0245] NG Next Generation

[0246] NG-eNB Next Generation Evolved Node B

[0247] NG-RAN Next Generation Radio Access Network

[0248] NR New Radio

[0249] NR-U New Radio Unlicensed

[0250] OFDM Orthogonal Frequency Division Multiplexing

[0251] OLLA Outer Loop Link Adaptation

[0252] PBR Prioritized Bit Rate

[0253] PDA Personal Digital Assistance

[0254] PDCCH Physical Downlink Control Channel

[0255] PDSCH Physical Downlink Shared Channel

[0256] PDU Protocol Data Unit

[0257] PHY Physical

[0258] PO Paging Occasion

[0259] PQI Packet Quality of Service Identifier

[0260] PRACH Physical Random Access Channel

[0261] PRB Physical Resource Block

[0262] P-RNTI Paging Radio Network Temporary Identifier

[0263] PTM Point-to-Multipoint

[0264] PTP Point-to-Point

[0265] PUCCH Physical Uplink Control Channel

[0266] PUSCH Physical Uplink Shared Channel

[0267] QCI Quality of Service Class Identifier

[0268] QFI Quality of Service Flow Identifier

[0269] QoS Quality of Service

[0270] RAM Random Access Memory

[0271] RAN Radio Access Network

[0272] RAT Radio Access Technology

[0273] RE Resource Element

[0274] RF Radio Frequency

[0275] RLC Radio Eink Control

[0276] RNTI Radio Network Temporary Identifier

[0277] ROM Read-Only Memory

[0278] RRC Radio Resource Control

[0279] RS Reference Signal

[0280] RSRP Reference Signal Received Power

[0281] SC-PTM Single Cell - Point-to-Multipoint

[0282] SDU Service Data Unit

[0283] SFN System Frame Number

[0284] SIB System Information Block

[0285] SMF Session Management Function

[0286] SR Scheduling Report

[0287] SRB Signaling Radio Bearer

[0288] SSB Synchronization Signal Block

[0289] TA Timing Advance

[0290] TB Transport Block

[0291] TDD Time Division Duplex

[0292] TR Technical Report

[0293] TS Technical Specification

[0294] TTI Transmission Time Interval

[0295] Tx Transmission

[0296] UCI Uplink Control Information

[0297] UE User Equipment

[0298] UL Uplink

[0299] UMTS Universal Mobile Telecommunications System

[0300] UPF User Plane Function

[0301] URLLC Ultra- Reliable and Low-Latency Communication

[0302] UTRAN Universal Mobile Telecommunications System TerrestrialRadio Access Network

[0303] WEAN Wireless Local Area Network

Claims

WE CLAIM:

1. An apparatus comprising: 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: receive, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; predict the TA value and an accuracy of the TA value of the at least one candidate network entity; and transmit, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

2. The apparatus of claim 1, wherein the predicted TA value and accuracy of the TA value of the at least one candidate network entity are associated with at least one beam prediction of the at least one candidate network entity.

3. The apparatus of claim 1 or 2, wherein at least one memory stores instructions that, when executed by the at least one processor, further cause the apparatus at least to: predict a TA value of the network entity and an accuracy of the predicted TA value of the network entity; and transmit, to the network entity, the predicted TA value and accuracy of the TA value of the network entity.

4. The apparatus of claim 3, wherein the predicted TA value and accuracy of the TA value of the network entity are associated with at least one beam prediction of the network entity.

5. The apparatus of claim 4, wherein the at least one memory stores instructions that, when executed by the at least one processor, further cause the apparatus at least to: transmit, to the network entity, the at least one beam prediction of the at least one candidate network entity, and the at least one beam prediction of the network entity.

6. An apparatus comprising: 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: transmit, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; receive, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity; and schedule at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

7. The apparatus of claim 6, wherein the predicted TA value and accuracy of the TA value of the at least one candidate network entity are associated with at least one beam prediction of the at least one candidate network entity.

8. The apparatus of claim 6 or 7, wherein at least one memory stores instructions that, when executed by the at least one processor, further cause the apparatus at least to: receive, from the user equipment, a predicted TA value of the apparatus and accuracy of the predicted TA value of the apparatus.

9. The apparatus of claim 8, wherein the predicted TA value and accuracy of the TA value of the apparatus are associated with at least one beam prediction of the apparatus.

10. The apparatus of claim 9, wherein the at least one memory stores instructions that, when executed by the at least one processor, further cause the apparatus at least to: receive, from the user equipment, the at least one beam prediction of the at least one candidate network entity, and the at least beam prediction of the apparatus.

11. A method comprising: receiving, by a user equipment, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; predicting the TA value and an accuracy of the TA value of the at least one candidate network entity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

12. The method of claim 11 , wherein the predicted TA value and accuracy of the TA value of the at least one candidate network entity are associated with at least one beam prediction of the at least one candidate network entity.

13. The method of claim 11 or 12, further comprising: predicting a TA value of the network entity and an accuracy of the predicted TA value of the network entity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the network entity.

14. The method of claim 13, wherein the predicted TA value and accuracy of the TA value of the network entity are associated with at least one beam prediction of the network entity.

15. The method of claim 14, further comprising: transmit, to the network entity, the at least one beam prediction of the at least one candidate network entity, and the at least one beam prediction of the network entity.

16. A method comprising: transmitting, by a network entity, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity; and scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

17. An apparatus comprising means for: receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; predicting the TA value and an accuracy of the TA value of the at least one candidate network entity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

18. An apparatus comprising means for:transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity; and scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

19. A computer program comprising instructions, which, when executed by an apparatus, cause the apparatus to perform at least the following: receiving, from a network entity, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; predicting the TA value and an accuracy of the TA value of the at least one candidate network entity; and transmitting, to the network entity, the predicted TA value and accuracy of the TA value of the at least one candidate network entity.

20. A computer program comprising instructions, which, when executed by an apparatus, cause the apparatus to perform at least the following: transmitting, to a user equipment, a radio resource control configuration comprising predicting a timing advance, TA, value of at least one candidate network entity, for lower layer triggered mobility; receiving, from the user equipment, a predicted TA value and accuracy of the predicted TA value of the at least one candidate network entity; and1. scheduling at least one random access channel, RACH, resource based, at least partially, on the accuracy of the predicted TA value of the at least one candidate network entity.

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