Systems and methods for performing period requirement measurement and report enhancements for positioning
AI/ML-based enhancements in wireless communication systems address inefficiencies in 3GPP standards by defining measurement period requirements and supporting UE reporting capabilities, improving network performance and positioning accuracy in complex environments.
Patent Information
- Application Number
- PCT/CN2024/101189
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-06-25
- Publication Date
- 2025-07-17
AI Technical Summary
Current 3GPP standards face challenges in efficiently managing complex device collaboration and positioning accuracy in cellular networks, particularly in industrial settings, due to inadequate measurement and reporting protocols for wireless communication.
Implement AI/ML-based enhancements for network performance and positioning accuracy by defining measurement period requirements and supporting UE reporting capabilities, including configurations for channel measurements and model monitoring metrics, utilizing AI/ML models located on the LMF side to improve positioning processes.
Enhances network performance and positioning accuracy by optimizing measurement protocols, allowing for more precise and efficient device collaboration in complex environments.
Smart Images

Figure CN2024101189_17072025_PF_FP_ABST
Abstract
Description
SYSTEMS AND METHODS FOR PERFORMING PERIOD REQUIREMENT MEASUREMENT AND REPORT ENHANCEMENTS FOR POSITIONINGTECHNICAL FIELD
[0001] The disclosure relates generally to wireless communications, including but not limited to systems and methods for performing period requirement measurement and report enhancements for positioning.BACKGROUND
[0002] Coverage is a key consideration in cellular network deployments. With the rise of interconnected devices, there is a growing focus on effective device communication. The current 3GPP standards, spanning from 3G to 5G and beyond, focus on the importance of seamless communication among various devices, from smart home devices to wearable devices. In industrial settings, the complexity of tasks often requires collaboration. This calls for several cooperative operational management systems, with the aim of creating workgroups and managing different types of devices to complete the required tasks.SUMMARY
[0003] The example embodiments disclosed herein are directed to solving the issues relating to one or multiple of the problems presented in the prior art, as well as providing additional features that will become readily apparent by reference to the following detailed description when taken in conjunction with the accompany drawings. In accordance with various embodiments, example systems, methods, devices and computer program products are disclosed herein. It is understood, however, that these embodiments are presented by way of example and are not limiting, and it will be apparent to those of ordinary skill in the art who read the present disclosure that various modifications to the disclosed embodiments can be made while remaining within the scope of this disclosure.
[0004] At least one aspect is directed to a system, method, apparatus, or computer-readable medium. A first network entity (e.g., UE / TRP) can send / transmit / provide a message for positioning to a second network entity (LMF) . The first network entity can send / transmit / provide capability and / or request for monitoring to the second network entity. The first network entity can receive / obtain / acquire a configuration for positioning from the second network entity. In certain implementations, the message can include UE capability for a first measurement and / or a second measurement, where the UE capability can include at least one of the following: one or more supported numbers of samples / paths; one or more supported timing granularity factors; one or more indicators and / or supported numbers of extent additional samples / paths; and / or a supported sample or path selection criterion.
[0005] In certain implementations, the configuration can include a measurement request for a first measurement and / or a second measurement, where the configuration can include at least one of the following: one or more requested numbers of samples / paths; one or more requested timing granularity factors; a requested number of extent additional samples / paths; an expected sample / path selection criterion; or one or more indicators associated with each request. In certain implementations, the number of samples / paths can include at least one of the following: a number of continuous and / or discontinuous samples / paths; a number of continuous and / or discontinuous samples / paths in groups; a number of continuous and / or discontinuous samples / paths in each group; or a number of additional samples / paths. In certain implementations, each of the one or more supported timing granularity factors can include one or more integer ranges.
[0006] In certain implementations, each of the one or more indicators can indicate whether a UE supports measurement and / or reports for extend additional samples / paths. In certain implementations, each of the one or more indicators can indicate whether a UE / TRP is to conform to the configured measurement request. In certain implementations, each of the one or more indicators can be a soft and / or hard value.
[0007] In certain implementations, the message can include measurement information of a reference signal, and the measurement information can be associated with one or more indicators. In certain implementations, each of the one or more indicators can indicate that a measurement and / or a report conforms to the measurement configuration. In certain implementations, each of the one or more indicators can indicate that a measurement and / or a report conforms to one or more of the following measurement configurations: a number of samples / paths; a timing granularity factor; a number of extent additional samples / paths; and / or a sample / path selection criterion. In certain implementations, the selection criterion can be one or more of the following: report (several) strongest power samples, or report (several) extremum strongest power samples.
[0008] In certain implementations, the configuration can include at least one of the following: an error range, a maximum range, or location error group (ID) information. In certain implementations, the error range, the maximum range, and the location error group (ID) information can each be associated with corresponding measurement / location information. In certain implementations, the message can include a valid (time) duration. In certain implementations, the valid (time) duration can correspond to a location error range, a maximum range, and / or a location error group (ID) .
[0009] In certain implementations, the capability for monitoring can include at least one of the following: an indicator indicating whether a UE has capability for monitoring; one or more time interval values; or a response time. In certain implementations, the request for monitoring can include at least one of the following: a number of models; a preferred monitoring window configuration; or a time interval for monitoring. In certain implementations, the time interval can indicate a time difference between two adjacent model monitoring behaviors / procedures. In certain implementations, the response time can indicate a time difference between a starting time and an ending time of a monitoring procedure.
[0010] In certain implementations, the message can include one or more of the following: SL-PRS resource ID; UE ID; an indicator; and / or measurement information of the SL-PRS resource. In certain implementations, the indicator can refer to whether the first network entity detects SL-PRS. In certain implementations, the message can include one or more of the following: model ID; model configuration information; associated ID; quality indicator; accuracy or range indicator; and / or recommended model ID / associated ID. In certain implementations, the configuration can include one or more of the following: model ID; model configuration information; associated ID; quality indicator; accuracy or range indicator; and / or recommended model ID / associated ID.
[0011] In certain implementations, a first network entity can report capability of the first network entity for a first measurement and / or a second measurement to a second network entity. The first network entity can receive / obtain / acquire a configuration for positioning from the second network entity. In certain implementations, the method can further include determining, by the first network entity, the measurement period requirement for the first measurement and / or a second measurement. In certain implementations, the measurement period requirement can be related to the capability of the first network entity and / or the configuration for positioning. In certain implementations, the capability can include one or more of the following: ppw-durationOfPRS-ProcessingSymbolsT; ppw-durationOfPRS-ProcessingSymbolsN; maxNumOfDL-PRS-ResProcessedPerSlot; supportedDL-PRS-ProcessingSamples-RRC-Inactive; durationOfPRS-ProcessingSymbolsInEveryTms; durationOfPRS-ProcessingSymbols; maxNumOfDL-PRS-ResProcessedPerSlot-RRC-Inactive; or TEG / beam sweeping capability. In certain implementations, the configuration for positioning can include one or more of the following: downlink positioning reference signal samples / instances; or uplink sounding reference signal samples / instances.
[0012] The system of the technical solutions disclosed herein can provide AI / ML based enhancements in wireless communication systems, particularly for improving network performance and positioning accuracy. The system of the technical solutions can achieve this through at least one of the following example configurations (e.g., features or solutions) :
[0013] · Example configuration 1: Defining Measurement Period Requirement for Channel Measurement.
[0014] · Example configuration 2: Supporting UE Reporting Capability for Channel Measurement.BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Various example embodiments of the present solution are described in detail below with reference to the following figures or drawings. The drawings are provided for purposes of illustration only and merely depict example embodiments of the present solution to facilitate the reader’s understanding of the present solution. Therefore, the drawings should not be considered limiting of the breadth, scope, or applicability of the present solution. It should be noted that for clarity and ease of illustration, these drawings are not necessarily drawn to scale.
[0016] FIG. 1 illustrates an example cellular communication network in which techniques disclosed herein may be implemented, in accordance with an embodiment of the present disclosure;
[0017] FIG. 2 illustrates a block diagram of an example base station and a user equipment device, in accordance with some embodiments of the present disclosure;
[0018] FIG. 3 illustrates an example configuration of a capability transfer procedure, in accordance with some embodiments of the present disclosure;
[0019] FIG. 4 illustrates an example configuration of a location information transfer procedure, in accordance with some embodiments of the present disclosure;
[0020] FIG. 5 illustrates an example configuration of calculating a model monitoring metric, in accordance with some embodiments of the present disclosure;
[0021] FIG. 6 illustrates another example configuration of calculating a model monitoring metric, in accordance with some embodiments of the present disclosure;
[0022] FIG. 7 illustrates an example configuration of a UE capability, in accordance with some embodiments of the present disclosure;
[0023] FIG. 8 illustrates an example of comparison between different N and k configurations, in accordance with some embodiments of the present disclosure;
[0024] FIG. 9 illustrates example reports, in accordance with some embodiments of the present disclosure;
[0025] FIG. 10 illustrates an example error range explanation, in accordance with some embodiments of the present disclosure;
[0026] FIG. 11 illustrates an example model monitoring flow, in accordance with some embodiments of the present disclosure;
[0027] FIG. 12 illustrates another example model monitoring flow, in accordance with some embodiments of the present disclosure;
[0028] FIG. 13 illustrates another example model monitoring flow, in accordance with some embodiments of the present disclosure; and
[0029] FIG. 14 illustrates a flow diagram of an example method for performing period requirement measurement and report enhancements for positioning, in accordance with an embodiment of the present disclosure.DETAILED DESCRIPTION
[0030] 1. Mobile Communication Technology and Environment
[0031] FIG. 1 illustrates an example wireless communication network, and / or system, 100 in which techniques disclosed herein may be implemented, in accordance with an embodiment of the present disclosure. In the following discussion, the wireless communication network 100 may be any wireless network, such as a cellular network or a narrowband Internet of things (NB-IoT) network, and is herein referred to as “network 100. ” Such an example network 100 includes a base station 102 (hereinafter “BS 102” ; also referred to as wireless communication node) and a user equipment device 104 (hereinafter “UE 104” ; also referred to as wireless communication device) that can communicate with each other via a communication link 110 (e.g., a wireless communication channel) , and a cluster of cells 126, 130, 132, 134, 136, 138 and 140 overlaying a geographical area 101. In Figure 1, the BS 102 and UE 104 are contained within a respective geographic boundary of cell 126. Each of the other cells 130, 132, 134, 136, 138 and 140 may include at least one base station operating at its allocated bandwidth to provide adequate radio coverage to its intended users.
[0032] For example, the BS 102 may operate at an allocated channel transmission bandwidth to provide adequate coverage to the UE 104. The BS 102 and the UE 104 may communicate via a downlink radio frame 118, and an uplink radio frame 124 respectively. Each radio frame 118 / 124 may be further divided into sub-frames 120 / 127 which may include data symbols 122 / 128. In the present disclosure, the BS 102 and UE 104 are described herein as non-limiting examples of “communication nodes, ” generally, which can practice the methods disclosed herein. Such communication nodes may be capable of wireless and / or wired communications, in accordance with various embodiments of the present solution.
[0033] FIG. 2 illustrates a block diagram of an example wireless communication system 200 for transmitting and receiving wireless communication signals (e.g., OFDM / OFDMA signals) in accordance with some embodiments of the present solution. The system 200 may include components and elements configured to support known or conventional operating features that need not be described in detail herein. In one illustrative embodiment, system 200 can be used to communicate (e.g., transmit and receive) data symbols in a wireless communication environment such as the wireless communication environment 100 of Figure 1, as described above.
[0034] System 200 generally includes a base station 202 (hereinafter “BS 202” ) and a user equipment device 204 (hereinafter “UE 204” ) . The BS 202 includes a BS (base station) transceiver module 210, a BS antenna 212, a BS processor module 214, a BS memory module 216, and a network communication module 218, each module being coupled and interconnected with one another as necessary via a data communication bus 220. The UE 204 includes a UE (user equipment) transceiver module 230, a UE antenna 232, a UE memory module 234, and a UE processor module 236, each module being coupled and interconnected with one another as necessary via a data communication bus 240. The BS 202 communicates with the UE 204 via a communication channel 250, which can be any wireless channel or other medium suitable for transmission of data as described herein.
[0035] As would be understood by persons of ordinary skill in the art, system 200 may further include any number of modules other than the modules shown in Figure 2. Those skilled in the art will understand that the various illustrative blocks, modules, circuits, and processing logic described in connection with the embodiments disclosed herein may be implemented in hardware, computer-readable software, firmware, or any practical combination thereof. To clearly illustrate this interchangeability and compatibility of hardware, firmware, and software, various illustrative components, blocks, modules, circuits, and steps are described generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware, or software can depend upon the particular application and design constraints imposed on the overall system. Those familiar with the concepts described herein may implement such functionality in a suitable manner for each particular application, but such implementation decisions should not be interpreted as limiting the scope of the present disclosure.
[0036] In accordance with some embodiments, the UE transceiver 230 may be referred to herein as an “uplink” transceiver 230 that includes a radio frequency (RF) transmitter and a RF receiver each comprising circuitry that is coupled to the antenna 232. A duplex switch (not shown) may alternatively couple the uplink transmitter or receiver to the uplink antenna in time duplex fashion. Similarly, in accordance with some embodiments, the BS transceiver 210 may be referred to herein as a “downlink” transceiver 210 that includes a RF transmitter and a RF receiver each comprising circuity that is coupled to the antenna 212. A downlink duplex switch may alternatively couple the downlink transmitter or receiver to the downlink antenna 212 in time duplex fashion. The operations of the two transceiver modules 210 and 230 may be coordinated in time such that the uplink receiver circuitry is coupled to the uplink antenna 232 for reception of transmissions over the wireless transmission link 250 at the same time that the downlink transmitter is coupled to the downlink antenna 212. Conversely, the operations of the two transceivers 210 and 230 may be coordinated in time such that the downlink receiver is coupled to the downlink antenna 212 for reception of transmissions over the wireless transmission link 250 at the same time that the uplink transmitter is coupled to the uplink antenna 232. In some embodiments, there is close time synchronization with a minimal guard time between changes in duplex direction.
[0037] The UE transceiver 230 and the base station transceiver 210 are configured to communicate via the wireless data communication link 250, and cooperate with a suitably configured RF antenna arrangement 212 / 232 that can support a particular wireless communication protocol and modulation scheme. In some illustrative embodiments, the UE transceiver 210 and the base station transceiver 210 are configured to support industry standards such as the Long Term Evolution (LTE) and emerging 5G standards, and the like. It is understood, however, that the present disclosure is not necessarily limited in application to a particular standard and associated protocols. Rather, the UE transceiver 230 and the base station transceiver 210 may be configured to support alternate, or additional, wireless data communication protocols, including future standards or variations thereof.
[0038] In accordance with various embodiments, the BS 202 may be an evolved node B (eNB) , a serving eNB, a target eNB, a femto station, or a pico station, for example. In some embodiments, the UE 204 may be embodied in various types of user devices such as a mobile phone, a smart phone, a personal digital assistant (PDA) , tablet, laptop computer, wearable computing device, etc. The processor modules 214 and 236 may be implemented, or realized, with a general purpose processor, a content addressable memory, a digital signal processor, an application specific integrated circuit, a field programmable gate array, any suitable programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, designed to perform the functions described herein. In this manner, a processor may be realized as a microprocessor, a controller, a microcontroller, a state machine, or the like. A processor may also be implemented as a combination of computing devices, e.g., a combination of a digital signal processor and a microprocessor, a plurality of microprocessors, one or multiple microprocessors in conjunction with a digital signal processor core, or any other such configuration.
[0039] Furthermore, the steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in firmware, in a software module executed by processor modules 214 and 236, respectively, or in any practical combination thereof. The memory modules 216 and 234 may be realized as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. In this regard, memory modules 216 and 234 may be coupled to the processor modules 210 and 230, respectively, such that the processors modules 210 and 230 can read information from, and write information to, memory modules 216 and 234, respectively. The memory modules 216 and 234 may also be integrated into their respective processor modules 210 and 230. In some embodiments, the memory modules 216 and 234 may each include a cache memory for storing temporary variables or other intermediate information during execution of instructions to be executed by processor modules 210 and 230, respectively. Memory modules 216 and 234 may also each include non-volatile memory for storing instructions to be executed by the processor modules 210 and 230, respectively.
[0040] The network communication module 218 generally represents the hardware, software, firmware, processing logic, and / or other components of the base station 202 that enable bi-directional communication between base station transceiver 210 and other network components and communication nodes configured to communicate with the base station 202. For example, network communication module 218 may be configured to support internet or WiMAX traffic. In a typical deployment, without limitation, network communication module 218 provides an 802.3 Ethernet interface such that base station transceiver 210 can communicate with a conventional Ethernet based computer network. In this manner, the network communication module 218 may include a physical interface for connection to the computer network (e.g., Mobile Switching Center (MSC) ) . The terms “configured for, ” “configured to” and conjugations thereof, as used herein with respect to a specified operation or function, refer to a device, component, circuit, structure, machine, signal, etc., that is physically constructed, programmed, formatted and / or arranged to perform the specified operation or function.
[0041] The Open Systems Interconnection (OSI) Model (referred to herein as, “open system interconnection model” ) is a conceptual and logical layout that defines network communication used by systems (e.g., wireless communication device, wireless communication node) open to interconnection and communication with other systems. The model is broken into seven subcomponents, or layers, each of which represents a conceptual collection of services provided to the layers above and below it. The OSI Model also defines a logical network and effectively describes computer packet transfer by using different layer protocols. The OSI Model may also be referred to as the seven-layer OSI Model or the seven-layer model. In some embodiments, a first layer may be a physical layer. In some embodiments, a second layer may be a Medium Access Control (MAC) layer. In some embodiments, a third layer may be a Radio Link Control (RLC) layer. In some embodiments, a fourth layer may be a Packet Data Convergence Protocol (PDCP) layer. In some embodiments, a fifth layer may be a Radio Resource Control (RRC) layer. In some embodiments, a sixth layer may be a Non-Access Stratum (NAS) layer or an Internet Protocol (IP) layer, and the seventh layer being the other layer.
[0042] Various example embodiments of the present solution are described below with reference to the accompanying figures to enable a person of ordinary skill in the art to make and use the present solution. As would be apparent to those of ordinary skill in the art, after reading the present disclosure, various changes or modifications to the examples described herein can be made without departing from the scope of the present solution. Thus, the present solution is not limited to the example embodiments and applications described and illustrated herein. Additionally, the specific order or hierarchy of steps in the methods disclosed herein are merely example approaches. Based upon design preferences, the specific order or hierarchy of steps of the disclosed methods or processes can be re-arranged while remaining within the scope of the present solution. Thus, those of ordinary skill in the art will understand that the methods and techniques disclosed herein present various steps or acts in a sample order, and the present solution is not limited to the specific order or hierarchy presented unless expressly stated otherwise.
[0043] 2. Systems and Methods for Performing Period Requirement Measurement and Report Enhancements for Positioning
[0044] Artificial intelligence / machine learning (AI / ML) can improve network performance with a trained dataset. In a positioning session or process, a target user equipment (UE) (e.g., a UE to be positioned) can receive the downlink positioning reference signal (DL-PRS) transmitted by a transmission reception point (TRP) and / or transmit an uplink sounding reference signal (UL-SRS) to gNB. In some implementations, the UE and / or gNB can perform signal measurements. In some implementations, the location of the target UE can be calculated / estimated based on the measurement results. In the positioning session / process, where the AI / ML model is located on the location management function (LMF) side, the UE / TRP can report the measurement results to the LMF. In some implementations, the AI / ML based positioning can include direct AI / ML positioning and / or AI / ML assisted positioning. The model input for AI / ML positioning can be the channel measurement of the received reference signal, which can be different from the current measurement. The present disclosure can include the measurement period requirement for channel measurement and / or support for UE report capability for channel measurement. In some implementations, the network can configure the measurement request to UE / TRP based on the capability information. In the following, UE / TRP’s capability / report is sent from UE / TRP / PRU to LMF. And the configuration is sent from LMF to UE / TRP / PRU.
[0045] In some implementations, for downlink time difference of arrival (DL TDOA) , when the physical layer receives the last NR-TDOA-ProvideAssistanceData message and NR-TDOA-RequestLocationInformation message from the LMF via the LTE positioning protocol (LPP) , the UE can measure multiple DL RSTD measurements during the measurement period TRSTD, Total, defined as:
[0046] where, i is the index of positioning frequency layer, L is the total number of positioning frequency layers, and Teffect, i is the periodicity of the PRS RSTD measurement in the positioning frequency layer i. TRSTD, i is the measurement period for PRS RSTD measurement in positioning frequency layer i, as specified below:
[0047] Where, NRxBeam, i is the UE Rx beam sweeping factor, Kcarrier_PRS is a scaling factor for PRS-based NR positioning measurements in RRC_INACTIVE, NRx, TEG, i is the Rx TEG specific scaling factor, is the maximum number of DL PRS resources in positioning frequency layer i configured in a slot, and Nsample is the number of PRS RSTD samples. Teffect, i is the periodicity of the PRS RSTD measurement in positioning frequency layer i, defined as:
[0048] where, N’ and N are associated with UE capability.
[0049] In some implementations, for reference signal timing difference (RSTD) , round trip time (RTT) , reference signal received power (RSRP) , and per path RSRP (RSRPP) , when UE is in RRC_INACTIVE, RRC_CONNECTED, and / or for UE configured with a measurement gap / PRS processing window, the parameters in the measurement period requirement can be replaced with corresponding configuration information and / or UE capability information.
[0050] In a positioning process, the capability transfer procedure can include one or more steps, as shown in FIG. 3. In Step 1, the server can send / transmit / provide a RequestCapabilities message to the target. The server can indicate the types of capabilities needed. In Step 2, the target can respond with a ProvideCapabilities message to the server. The capabilities can correspond to any capability types specified in Step 1 (if the step is included) . In some implementations, the target can send / transmit / provide a ProvideCapabilities message to the server in an unsolicited manner, e.g., Step 1 can be an optional step.
[0051] The location information transfer procedure can include one or more steps, as shown in FIG. 4. In Step 1, the server can send / transmit / provide a RequestLocationInformation message to the target to request location information, indicating the type of location information desired and the associated quality of service (QoS) . In Step 2, the target can send / transmit / provide a ProvideLocationInformation message to the server to transfer location information. The location information transferred can match or be a subset of the location information requested in Step 1. In some implementations, the server can allow additional location information to be transferred. In some implementations, the target can send a ProvideLocationInformation message to the server in an unsolicited manner, e.g., Step 1 can be an optional step.
[0052] In AI / ML positioning, model monitoring indicators can be calculated in various ways. For example, in some implementations, the model monitoring metric can be calculated based on the measurement results of UE and corresponding labels, as shown in FIG. 5. As shown, the channel measurement of the UE can be used as model input to obtain / acquire UE location #1. The UE location #2 can be the location information obtained through existing methods or the measurement information calculated based on the UE location information (the label information can be the location information sent by LMF to the UE) . The UE can calculate a metric for model monitoring by comparing the UE location #1 and UE location #2. In some implementations, the label information obtained by existing methods may not be accurate (especially in NLOS scenarios) , resulting in inaccurate calculations of the model monitoring metrics.
[0053] In some implementations, the model monitoring metric can be calculated based on the measurement results of PRU and corresponding labels, as shown in FIG. 6. As shown, the channel measurements of the PRU can be used as model input to obtain the location #1 of the PRU. The PRU location #2 can be the known location information, or the measurement information (the label information) calculated based on the PRU position information. The UE / LMF can calculate the metric for model monitoring by comparing the two-location information of the PRU. In some implementations, the example configuration can maintain the accuracy of label information. In some implementations, it is preferable for the positioning reference unit (PRU) to be in the same scene or in similar positions as the target UE to ensure that UE and PRU are suitable for the same AI / ML model. In some implementations, the network is to provide sufficient auxiliary information to the UE, such as PRU measurement information and / or PRU location information.
[0054] In TDOA positioning procedure, when physical layer receives the last NR-TDOA-ProvideAssistanceData message and NR-TDOA-RequestLocationInformation message from the LMF, the UE can measure multiple DL RSTD measurements during the measurement period TRSTD, Total, defined as:
[0055] where, max () is an operation for maximum. TRSTD, i is the measurement period for PRS RSTD measurement in positioning frequency layer i, as specified below:
[0056] In some implementations, the MPR in RRC_INACTIVE / RRC_CONNECTED state with or without MG for the first measurement can be applied for the second measurement. In some implementations, the parameters in MPR for RRC_INACTIVE / RRC_CONNECTED state with or without MG for the first and / or second measurement can be updated.
[0057] In some implementations, the UE can report at least one of the following UE capabilities for the first measurement and / or the second measurement: ppw-durationOfPRS-ProcessingSymbolsT, ppw-durationOfPRS-ProcessingSymbolsN, maxNumOfDL-PRS-ResProcessedPerSlot, supportedDL-PRS-ProcessingSamples-RRC-Inactive, durationOfPRS-ProcessingSymbolsInEveryTms, durationOfPRS-ProcessingSymbols, and / or maxNumOfDL- PRS-ResProcessedPerSlot-RRC-Inactive. In some implementations, the UE capability or the UE feature groups 13-1, 13-1a, and / or 27-1-1 / 27-1-3 / 27-1-4 / 27-1-4a / 27-3-1 / 27-3-2 / 27-3-3 / 27-6 / 27-9 / 27-17 can be applicable for all positioning methods or the first measurement and the second measurement.
[0058] In some implementations, the parameters for determining the MPR in RRC_INACTIVE / RRC_CONNECTED state with or without MG for the second measurement can be based on the reported UE capability for the second measurement. In some implementations, the first measurement can include at least one of the following: the measurement for RSTD, UE-RxTx Time Difference, PRS-RSRP, and / or PRS-RSRPP. In some implementations, the second measurement includes at least one of the following: channel measurement, PDP / CIR / DP, sample-based measurement, and / or path-based measurement.
[0059] The model input for AI / ML positioning can be determined based on several implementations. The second measurement, e.g., for AI / ML model input, can be measured with one DL PRS / UL SRS sample / instance. In a timing report, the measurement can be performed using one or more samples / instances. The UE / TRP can obtain the time measurement by calculating the average receiving time of different samples / instances. In some implementations, the channel measurement can differ from the timing measurement, making it less meaningful / valuable for the UE / TRP to calculate the average power / timing / phase of different samples / instances. In some implementations, the channel measurement can be limited within / to one sample / instance.
[0060] In some implementations, the maximum power reduction (MPR) for the second measurement can be defined as the measurement duration for the PRS channel measurement sample in positioning frequency layer i, including the sampling time and processing time. In RRC_INACTIVE state, the measurement duration can be Ti + Tavailable_PRS, i, where Tavailable_PRS, i is the least common multiple between PRS periodicity and the DRX cycle length. In RRC_CONNECTED state, if the PRS resource to be measured is available on the same MG occasion during Tavailabe, the measurement duration can be Ti +MGL, where MGL is the length of the measurement gap. In some implementations, the measurement duration can be Ti +Tavailable_PRS, i, where Tavailable_PRS, i is the least common multiple between TPRS, i and the MGRPi (if MG is configured) or PPWRPi (if PPW is configured) , MGRPi is the repetition periodicity of the measurement gap applicable for measurement in the PRS / positioning frequency layer i, PPWRPi is the repetition periodicity of the PRS processing window applicable for measurements in the positioning frequency layer i, and TPRS, i is the periodicity of DL PRS resource with muting (if configured) on positioning frequency layer i.
[0061] For a positioning process, the UE can measure RSTD / RTT / RSRP / RSRPP (afirst measurement) for positioning purposes. For AI / ML positioning, the UE can perform channel measurement (asecond measurement) to determine the model input. In some implementations, where the UE can perform the first measurement together with the second measurement simultaneously, the MPR (measurement period requirement) for such a measurement can be different from the MPR, e.g., the MPR for supporting simultaneous measurement can be different from (e.g., larger / greater than) the MPR for the first measurement.
[0062] In some implementations, the scaling factor determining the measurement period requirement can be updated. For RRC_CONNECTED, the carrier-specific scaling factor for determining the measurement period requirement can be CSSFPRS, i*F1 and / or CSSFPRS, i+f1, where CSSFPRS, i is the carrier-specific scaling factor for NR PRS-based positioning measurements in positioning frequency layer i for the first measurement. For RRC_INACTIVE, the scaling factor for PRS-based NR positioning measurements (for determining the measurement period requirement) can be Kcarrier_PRS*F2 and / or Kcarrier_PRS+f2 , where Kcarrier_PRS is the scaling factor for PRS-based NR positioning measurements in RRC_INACTIVE for the first measurement. In some implementations, F1 / F2 / f1 / f2 can be a (n) (appended) factor, and / or the factor can be reported by a UE / TRP and / or configured by LMF.
[0063] In some implementations, where the UE cannot perform the first measurement and the second measurement simultaneously, the scaling factor for determining the MPR for the first measurement can differ from the MPR used for the second measurement. The scaling factor for PRS-based NR positioning measurement can depend on the measurement priority of different signals. In some implementations, where the measurement priority of the first measurement is higher than the second measurement, the scaling factor for the first measurement can be CSSFPRS, i or the scaling factor for the second measurement can be CSSFPRS, i+1 or CSSFPRS, i*KPfactor, where KPfactor is a priority factor. In some implementations, where the measurement priority of the first measurement is lower than the second measurement, the scaling factor for the first measurement can be CSSFPRS, i+1 or CSSFPRS, i*KPfactor or the scaling factor for the second measurement can be CSSFP2S, i. In some implementations, the UE can report the priority level (s) / indicator (s) for the first measurement and / or the second measurement. In some implementations, the UE can report an indicator, indicating whether the UE can support performing the first measurement and the second measurement simultaneously.
[0064] For the first measurement, kmultiTEG, i (for RRC_CONNECTED state) or NRx, TEG, i, NRxTx, TEG, i (for RRC_INACTIVE state) can be the TEG specific scaling factors for the measurement of the same PRS resource with multiple TEGs. In some implementations, the UE can report one or more indicators for TEG / beam sweeping capability. The indicators can indicate whether the TEG / beam sweeping capability is applicable for the first and / or second measurement (s) . In some implementations, one indicator can indicate whether the TEG capability is applicable for the first measurement, one indicator can indicate whether the TEG capability is applicable for the second measurement, and one indicator can indicate whether the TEG / beam sweeping capability is applicable for the first measurement and the second measurement. In some implementations, the NR-UE-TEG-Capability can be applicable for the first measurement. In some implementations, the TEG specific scaling factor / UE Rx beam sweeping factor for determining the MPR of the second measurement can be determined by the reported TEG / beam sweeping capability. In some implementations, where the UE does not support TEG / beam sweeping capability for the second measurement, the TEG specific scaling factor / UE Rx beam sweeping factor for determining the MPR can be kmultiTEG, i=1 or NRx, TEG, i=1 or NRxTx, TEG, i=1 or NRxBeam, i=1.
[0065] For the measurement report, the UE can report the TEG ID / UE Rx beam information along with the second measurement result. In some implementations, for one channel measurement, the UE can report one or more measurement results. Each measurement result can be obtained using different TEG ID / UE Rx beam information. In some implementations, with the reported TEG ID / UE Rx beam, the network can compensate for the timing / angle error, thereby further improving positioning performance.
[0066] In some implementations, where the UE measures PRS within the active BWP, the measurement can be performed in the PRS processing window (PPW) . In some implementations, where the UE measures PRS outside the active BWP or within the active BWP but with a different subcarrier spacing (SCS) from the active BWP, the measurement can be performed in the measurement gap (MG) . The MG and PPW can be pre-configured and activated through DL MAC CE.
[0067] To support UE measurement of PRS to derive channel measurements or PDP / DP / CIR, or to get / obtain sample-based measurement or path-based measurement within the MG, various implementations / configurations can be considered. In some implementations, the measurement gap and / or the UE for measurements of DL-PRS can be associated with a first measurement and / or a second measurement, thereby updating the field description for PPW / MG configuration. For posMeasGapPreConfigToAddModList, all (or a certain number of) gaps configured can be associated with a first measurement and / or a second measurement. In some implementations, one or more indicators can be added for PPW / MG configuration, indicating whether the configuration is applicable for a first measurement or a second measurement, or whether the configuration is applicable for a first and a second measurement. In some implementations, the PPW / MG or gapAssociationPRS for a second measurement can be configured. The configuration can include at least one of the following: Gap ID, Gapoffset, MG length (mgl) , MG repetition (mgrp) , MG timing advance (mgta) , gaptype, and / or priority. The priority can indicate the priority of the configured PPW / MG for the second measurement. The priority can be compared with the PPW / MG for the first measurement and / or the third measurement. The third measurement can be the measurement of RS, other than PRS. In some implementations, the mgl-n for a second measurement in GapConfig can be configured. The mgl-n can be applicable for a first measurement or a second measurement. The mgl-n can be applicable for a first and a second measurement. In some implementations, where the mgl-n is present, the UE can ignore the mgl-r16.
[0068] The MG configuration can include at least one of the following: GapConfig, Cond PRS in GapConfig, gapAssocationPRS in gapToAddModeList, Gap combination configuration, and / or posMeasGapPreConfigToAddModList. In some implementations, where the MG is configured for the first measurement and the second measurement separately, the (MG specific) scaling factor of MPR for the first / second measurement can be updated as Kp, PRS, i=Ntotal / Navailable, where Ntotal is the total number of associated gap occasions covering PRS occasions within in the window and Navailable is the number of non-dropped associated gap occasions covering PRS occasion for the first / second measurement within the window. In some implementations, where the first measurement and the second measurement use the same MG, the (MG specific) scaling factor of MPR for the first / second measurement can be updated as Kp,PRS, i*KMGfactor and / or Kp, PR、, i+KMGfactor, where KMGfactor is a measurement gap scaling factor.
[0069] In some implementations, the UE / TRP can report one or more indicators, which can indicate whether the UE has the capability for the second measurement and / or report. The UE / TRP can report capability for the second measurement to the LMF, where the capability can include at least one of the following: the UE capability N’t, which can indicate the supported number of samples / paths, and the UE capability k, which can indicate the supported timing granularity (factor) . In some implementations, the UE can report the supported finer timing report granularity for PRS for the second measurement in an integer range, e.g., (X1…X2) , where X1 is the minimum timing granularity factor and X2 is the maximum timing granularity factor. The supported timing granularity can be calculated as T=2kxTc, where k represents the reported timing granularity factor, and Tc is the basic time unit for NR.
[0070] For the supported number of samples / paths, the UE can report one or more capabilities to the LMF. In some implementations, if the UE reports samples / paths / channel measurement information in one information element (IE) , the capabilities can include: UE capability N1, indicating the supported number of samples / paths; UE capability N1, indicating the supported number of (time domain) continuous samples / paths; UE capability N2, indicating the supported number of (time domain) discontinuous samples / paths; UE capability N3, indicating the supported number of samples / paths group, and / or UE capability N4, indicating the supported number of (time domain) discontinuous samples / paths in each group. In each group, the sample / paths can be (time domain) continuous or discontinuous. An example of the UE capability of the samples / paths group is illustrated in FIG. 7. In some implementations, if the UE reports samples / paths / channel measurement information in separate IEs, the capabilities can include UE capability N3, indicating the supported number of additional samples / paths. In some implementations, the UE can report a combination of supported numbers of samples / paths and timing granularity factors. The reporting format can be {N’t1, k1} , {N’t2, k2} , …, meaning / indicating that the UE can report N’t1 samples with timing granularity factor k1 and / or report N’t2 samples with timing granularity factor k2.
[0071] For the first measurement, the UE can report the capability indicator, indicating whether the UE can support measurement and / or report on the extended additional paths. The UE can report the number of extended additional paths for measurement and / or report (alternatively for Rel-19) . If the extended additional path for measurement and / or report is reported by UE, the following explanations can be supported: the UE / LMF will ignore the reported additionalPathsExtSupport-r17; and / or the reported extended additional path is an augment on top of the reported additionalPathsExtSupport-r17. For example, if the reported additionalPathsExtSupport-r17 is n8 and the reported extended additional path is n6, the total supported number of additional paths can be 8 + 6 = 14.
[0072] In some implementations, the LMF can configure the measurement request to UE / TRP for the first / second measurement and / or report. The configuration information for the second measurement can include the number of samples / paths and / or the timing granularity factor for the sample / paths measurement and / or report. Each of the configuration elements can be associated with an indicator. The indicator can include a hard and / or a soft value, indicating whether the UE / TRP can obey / follow and / or can conform the configuration information. In some implementations, the configuration can include at least one of the following: one or more (candidate) values or value ranges on the number of samples / paths for measurement and / or report; an indicator on the number of samples / paths for measurement and / or report; one or more (candidate) values or value ranges on the timing granularity factor for measurement and / or report; and / or an indicator on the timing granularity factor for measurement and / or report. In some implementations, the hard / soft value of 1 can indicate that the UE / TRP can be instructed to restrict report measurement information based on the configuration. In some implementations, the larger / higher the indicator value, the more LMF desires / expects UE / TRP to comply with configuration rules.
[0073] In some implementations, the configuration information for the first measurement can include the number of extended additional paths. The configuration information for the first measurement can be associated with an indicator, indicating whether the UE / TRP can obey / follow and / or can conform the configured number of extended additional paths. In some implementations, the LMF can prefer the UE / TRP to closely follow the configuration rules regarding time granularity. For example, as shown in FIG. 8, the consistency of model training is not significantly affected by different numbers of samples / paths (e.g., situations A and B sharing the same timing granularity factor) . In some implementations, the LMF may assume that the power of other samples that have not been reported is 0. In some implementations, the consistency of situations A and C can be difficult to ensure, even if the reported number of samples is the same.
[0074] In some implementations, the LMF can configure a combination of the expected number of samples / paths and timing granularity factors. The configuration format can be {N’t1, k1} , {N’t2, k2} …, meaning / indicating that the UE / TRP can be expected to report N’t1 samples with timing granularity factor k1 and / or report N’t2 samples with timing granularity factor k2. In some implementations, where the LMF can have multiple models, such as {N1, K1} , corresponding to the input requirements of model 1, and {N2, K2} , corresponding to the input requirements of model 2, the LMF can train different models with different data formats. In some implementations, one or more indicators can be associated with different configured combinations. In some implementations, the configuration information can be determined based on the UE / TRP capability report.
[0075] In some implementations, the UE / TRP can report the measurement information based on the LMF’s configuration. The LMF can determine whether UE / TRP obeys / follows the configured measurement request. In some implementations, the UE / TRP can report an indicator associated with the measurement information. The indicator can indicate whether UE / TRP (fully / totally) obeys / follows the configured measurement request. In some implementations, the UE / TRP can report multiple indicators associated with each report element, including the number of samples / paths, the timing granularity factors, and the number of extended additional samples / paths. In some implementations, the indicators can indicate whether UE / TRP obeys the configured number of samples / paths, the timing granularity factors, and the number of extended additional samples / paths requirements. With the reported indicator, the LMF can discard parts of measurement reports that are not applicable to LMF side models.
[0076] For measurement report, the UE / TRP can select the first and / or strongest power sample / path as the reference sample / path for the measurement report. The timing information of the reference sample / path can be reported by UE / TRP to LMF. In some implementations, as shown in FIG. 9, the UE / TRP can report the samples / paths with the (extremum) strongest power. In report #1, the UE / TRP can select the strongest power sample for the measurement report. In report #2, the UE / TRP can select the (extremum) strongest power sample for the measurement report. In some implementations, the sample / path selection for the second measurement can be the additional samples / paths within a certain time span of the first sample / path. In some implementations, the sample / path selection for the second measurement can be the strongest sample / path and the additional sample / paths between the first and strongest samples / paths. By comparing the reports, it can be determined that the selected samples differ. The UE / TRP can report the selected criterion and / or time span associated with the measurement report. In some implementations, the sample report / select criterion and / or time span can be configured by LMF.
[0077] In some implementations, for training data collection of AI / ML based positioning, if a training data sample includes both measurement information and label information, the reported measurement and label information can be for the same UE / PRU and for the same location associated with the label. For example, as shown in FIG. 10, for DL positioning, the measurement information can be reported by a UE / PRU at location A. In some implementations, the label information can be collected by the same UE / PRU at location A, around location A, or within a certain range.
[0078] In some implementations, the data collection node can configure the location error range, maximum range, and / or location error group (ID) for measurement / label information. In response, the data generation node can report the valid (time) duration corresponding to the configured location error range, maximum range, and / or location error group (ID) . In some implementations, the location error range can be an error range of the location difference between the label and measurement information in units of meters / metres or in the time domain, e.g., ms. Each location error group (ID) can be associated with an error range. The mapping relation between location error group (ID) and error range can be pre-configured by the data collection node. For example, error group ID #1 can indicate that the error range can be 0~5m and the valid duration time of the measurement and / or label can be the time duration of UE / PRU stationed within 5 meters of location A. The entity for data collection and data generation can depend on the positioning use case. In some implementations, the data collection node can be UE / TRP / LMF. In some implementations, the data generation node can be UE / PRU / TRP / LMF. For example, in the LMF side model, the data collection node can be the LMF, and the data generation can be UE / PRU (for DL positioning) and / or TRP / gNB (for UL positioning) . In some implementations, the model training entity can pair the channel measurement information with the label for the model training.
[0079] In some implementations, model monitoring can refer to a procedure that monitors the inference performance of the AI / ML model. For the UE-side model, e.g., if the model is located on the UE side, the entity for model monitoring (metric calculation) can be LMF and / or UE. In some implementations, where the UE calculates the model monitoring metric and / or performs model monitoring, the UE can report the monitoring-related capability and / or request to the network. An example of a model monitoring flow is illustrated in FIG. 11. As shown, the UE can report an indicator to the network, which can indicate whether the UE has the capability for model monitoring and / or monitoring metric calculation. For example, a value of 0 for the indicator can indicate that the UE may not have the corresponding capability, and a value of 1 for the indicator can indicate that the UE has the corresponding capability.
[0080] In some implementations, the UE can report one or more time interval value (s) for the monitoring procedure, e.g., the time intervals between two adjacent model monitoring behaviors / procedures. In some implementations, each reported time interval value can be associated with one or more models / associated ID (s) , indicating that the monitoring interval can be applicable to one or more model (s) . In some implementations, each model / associated ID can be associated with one or more time interval value (s) for model monitoring (metric calculation) . In some implementations, the UE can report the supported response time for each monitoring procedure, e.g., the time duration between the start and end of the monitoring procedure. In some implementations, the time duration / response time can be associated with a number and / or a confidence indicator and / or a quality indicator, where the number can indicate the number of datasets used for monitoring. The response time for model monitoring can be related to the model quality requirement and / or the number / size of the available dataset.
[0081] In some implementations, multiple models, e.g., several models for positioning, several models for beam management, and several models for CSI prediction / compression, etc., can be located on the UE side. The supported response time and / or monitoring capability can be related to the number of models. In some implementations, where the UE has to monitor all the models, the reported response time and / or capability can be associated with the number of models. In some implementations, the UE can send the monitoring request information to the network to request a network configuration monitoring window. In some implementations, the monitoring request information can include one or more of the following: the number of models, the preferred monitoring window configuration, or the time interval for monitoring. In response, the network can configure the monitoring window (s) corresponding to UE’s request. In some implementations, the UE can perform model monitoring (metric calculation) associated with UE-specific capability.
[0082] In some implementations, new model monitoring methods can be used to improve model monitoring performance and maintain the accuracy of ground truth labels. For example, some model monitoring methods can include supporting / providing UE and / or PRUs with accurate location information around / surrounding the UE to assist the target UE in model monitoring. In this regard, several approaches / implementations can be considered. In some implementations, the first approach can include the LMF / network forwarding / transmitting / sending of monitoring-related information between the target UE and other UE / PRU. This approach can include / support several steps. For example, Step 0 can include selecting a UE / PRU for the target UE’s model monitoring to make sure that the selected UE / PRU and the target UE are within a similar / the same area or share the same / similar channel conditions / scenarios.
[0083] In some implementations, the selection of UE / PRU can include several methods. In Method 1, the target UE can send / transmit the SL-PRS, and the UE / PRU that can detect the target UE’s SL-PRS can be selected as an auxiliary node for model monitoring. The target UE can report the SL-PRS resource ID and / or UE ID to the LMF for monitoring node detection. The LMF can send / transmit the SL-PRS resource ID and / or UE ID of the target UE for monitoring node detection in the surrounding area. The UE / PRU around the target that detects the corresponding SL-PRS resources can report an indicator to the LMF, which can indicate that the UE / PRU can receive the SL-PRS of the target UE. In some implementations, the UE / PRU can report SL-PRS resource and / or UE ID and / or be associated with the measurement information of the received SL-PRS, such as RSTD, RTT, RSRP / RSRPP, etc., to the LMF (to estimate the distance between the UE / PRU and the target UE) . In Method 2, the LMF can select UE / PRU to assist the target UE in model monitoring based on the known UE / PRU location information in the network (e.g., some prior location information, such as calculated based on existing measurement information) .
[0084] After UE / PRU selection, the process of model monitoring can be illustrated through FIG. 12. As shown, the configuration can include several steps, as specified below:
[0085] Step 1: The target UE can send / transmit / provide a monitoring request to LMF, where at least one of the following can be included in the monitoring request:
[0086] · Model ID and / or model configuration information of the UE side model. In some implementations, considering that UE can have multiple models, it can be desirable to make sure that the target UE and other UE / PRUs have the same understanding of different models (model alignment) .
[0087] · Quality indicator / accuracy requirement or range indicator of UE side model monitoring (can be associated with model ID / functionality) , and LMF can select UE / PRU closer to UE for model monitoring based on the indicator.
[0088] Step 2: The LMF can send / transmit / provide model monitoring request / configuration to nodes / selected UE / PRUs around the target UE, which can include at least one of the following: model ID / Associated ID and / or related configuration of the model that is to be monitored; and / or quality indicators / accuracy requirements of the model monitoring.
[0089] Step 3: The UE / PRU can report the monitoring-related information to LMF. The monitoring-related information can include at least one of the following: model ID / associated ID and / or the accuracy indicator; model ID / associated ID and / or the availability indicator; and / or recommended model ID / associated ID. The UE / PRU can send / transmit recommended models with better performance and the corresponding model IDs to the network (if the requested model ID is not available) . If all UEs download models from the OTT server and all UEs / PRUs have the same model information, the available models can be directly recommended to the target UE. Step 4: The LMF can send / transmit the monitoring-related information to the target UE. The monitoring-related information can include at least one of the following: model ID / associated ID and / or the accuracy indicator; model ID / associated ID and / or the availability indicator; and / or recommended model ID / associated ID.
[0090] In some implementations, regarding how to align the target UE with other UE / PRU side models, it can be assumed that the UE / PRU is obtained from the OTT server and has the same understanding of the model ID / associated ID when in the same cell.
[0091] In some implementations, the second approach can include supporting sidelink communication between the target UE and other UE / PRU. This approach can include / support several steps. For example, the target UE can send / transmit / provide SL-PRS and / or an SL broadcast message, which carries the SL-PRS resource ID. The surrounding UE / PRU can detect the resource ID and provide feedback to the target UE. After receiving instructions, the target UE can obtain / receive the UE / PRU ID that can be used for model monitoring. After selection, the process of requesting model monitoring and reporting monitoring results can be triggered. The general flow can be illustrated through FIG. 13. As shown, the example configuration can include a monitoring request step and a monitoring response step. In the monitoring request step, the target UE can send / transmit / provide a monitoring request to other UE / PRU. In the monitoring response step, other UE / PRU can send / transmit / provide monitoring-related information to the target UE. In some implementations, the monitoring request / monitoring-related information can be the same as in the first approach.
[0092] Referring now to FIG. 14, which illustrates a flow diagram of a method 1400 for performing period requirement measurement and report enhancements for positioning. The method 1400 may be implemented using any of the components and devices detailed herein in conjunction with FIGS. 1–13. In an overview, the method 1400 may include a first network entity sending a message for positioning to a second network entity (STEP 1402) . The method may include the first network entity sending capability and / or request for monitoring to the second network entity (STEP 1404) . The method may include the first network entity reporting capability for a first measurement and / or a second measurement to a second network entity (STEP 1406) . The method may include the first network entity receiving a configuration for positioning from the second network entity (STEP 1408) .
[0093] In certain configurations, a first network entity (e.g., UE / TRP) can send / transmit / provide a message for positioning to a second network entity (LMF) (STEP 1402) . The first network entity can send / transmit / provide capability and / or request for monitoring to the second network entity (STEP 1404) . The first network entity can receive / obtain / acquire a configuration for positioning from the second network entity (STEP 1408) . In certain configurations, the message can include UE capability for a first measurement and / or a second measurement, where the UE capability can include at least one of the following: one or more supported numbers of samples / paths; one or more supported timing granularity factors; one or more indicators and / or supported numbers of extent additional samples / paths; and / or a supported sample or path selection criterion. In certain configurations, each of the one or more supported timing granularity factors can include one or more integer ranges. In certain configurations, each of the one or more indicators can indicate whether a UE supports measurement and / or reports for extend additional samples / paths.
[0094] In certain configurations, the configuration can include a measurement request for a first measurement and / or a second measurement, where the configuration can include at least one of the following: one or more requested numbers of samples / paths; one or more requested timing granularity factors; a requested number of extent additional samples / paths; an expected sample / path selection criterion; or one or more indicators associated with each request. In certain configurations, the number of samples / paths can include at least one of the following: a number of continuous and / or discontinuous samples / paths; a number of continuous and / or discontinuous samples / paths in groups; a number of continuous and / or discontinuous samples / paths in each group; or a number of additional samples / paths. In certain configurations, each of the one or more indicators can indicate whether a UE / TRP is to conform to the configured measurement request. In certain configurations, each of the one or more indicators can be a soft and / or hard value.
[0095] In certain configurations, the message can include measurement information of a reference signal, and the measurement information can be associated with one or more indicators. In certain implementations, each of the one or more indicators can indicate that a measurement and / or a report conforms to the measurement configuration. In certain configurations, each of the one or more indicators can indicate that a measurement and / or a report conforms to one or more of the following measurement configurations: a number of samples / paths; a timing granularity factor; a number of extent additional samples / paths; and / or a sample / path selection criterion. In certain configurations, the selection criterion can be one or more of the following: report (several) strongest power samples, or report (several) extremum strongest power samples.
[0096] In certain configurations, the configuration can include at least one of the following: an error range, a maximum range, or location error group (ID) information. In certain configurations, the error range, the maximum range, and the location error group (ID) information can each be associated with corresponding measurement / location information. In certain configurations, the message can include a valid (time) duration. In certain configurations, the valid (time) duration can correspond to a location error range, a maximum range, and / or a location error group (ID) .
[0097] In certain configurations, the capability for monitoring can include at least one of the following: an indicator indicating whether a UE has capability for monitoring; one or more time interval values; or a response time. In certain configurations, the request for monitoring can include at least one of the following: a number of models; a preferred monitoring window configuration; or a time interval for monitoring. In certain configurations, the time interval can indicate a time difference between two adjacent model monitoring behaviors / procedures. In certain configurations, the response time can indicate a time difference between a starting time and an ending time of a monitoring procedure.
[0098] In certain configurations, the message can include one or more of the following: SL-PRS resource ID; UE ID; an indicator; and / or measurement information of the SL-PRS resource. In certain configurations, the indicator can refer to whether the first network entity detects SL-PRS. In certain configurations, the message can include one or more of the following: model ID; model configuration information; associated ID; quality indicator; accuracy or range indicator; and / or recommended model ID / associated ID. In certain configurations, the configuration can include one or more of the following: model ID; model configuration information; associated ID; quality indicator; accuracy or range indicator; and / or recommended model ID / associated ID.
[0099] In certain configurations, a first network entity can report capability of the first network entity for a first measurement and / or a second measurement to a second network entity (STEP 1406) . The first network entity can receive / obtain / acquire a configuration for positioning from the second network entity. In certain configurations, the method can further include determining, by the first network entity, the measurement period requirement for the first measurement and / or a second measurement. In certain configurations, the measurement period requirement can be related to the capability of the first network entity and / or the configuration for positioning. In certain configurations, the capability can include one or more of the following: ppw-durationOfPRS-ProcessingSymbolsT; ppw-durationOfPRS-ProcessingSymbolsN; maxNumOfDL-PRS-ResProcessedPerSlot; supportedDL-PRS-ProcessingSamples-RRC-Inactive; durationOfPRS-ProcessingSymbolsInEveryTms; durationOfPRS-ProcessingSymbols; maxNumOfDL-PRS-ResProcessedPerSlot-RRC-Inactive; or TEG / beam sweeping capability. In certain configurations, the configuration for positioning can include one or more of the following: downlink positioning reference signal samples / instances; or uplink sounding reference signal samples / instances.
[0100] While various embodiments / implementations of the present solution have been described above, it should be understood that they have been presented by way of example only, and not by way of limitation. Likewise, the various diagrams may depict an example architecture or configuration, which are provided to enable persons of ordinary skill in the art to understand example features and functions of the present solution. Such persons would understand, however, that the solution is not restricted to the illustrated example architectures or configurations but can be implemented using a variety of alternative architectures and configurations. Additionally, as would be understood by persons of ordinary skill in the art, one or multiple features of one embodiment / implementation can be combined with one or multiple features of another embodiment / implementation described herein. Thus, the breadth and scope of the present disclosure should not be limited by any of the above-described illustrative embodiments.
[0101] It is also understood that any reference to an element herein using a designation such as “first, ” “second, ” and so forth does not generally limit the quantity or order of those elements. Rather, these designations can be used herein as a convenient means of distinguishing between two or more elements or instances of an element. Thus, a reference to first and second elements does not mean that only two elements can be employed, or that the first element must precede the second element in some manner.
[0102] Additionally, a person having ordinary skill in the art would understand that information and signals can be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, and symbols, which may be referenced in the above description, can be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.
[0103] A person of ordinary skill in the art would further appreciate that any of the various illustrative logical blocks, modules, processors, means, circuits, methods and functions described in connection with the aspects disclosed herein can be implemented by electronic hardware (e.g., a digital implementation, an analog implementation, or a combination of the two) , firmware, various forms of program or design code incorporating instructions (which can be referred to herein, for convenience, as “software” or a “software module) , or any combination of these techniques. To clearly illustrate this interchangeability of hardware, firmware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware or software, or a combination of these techniques, depends upon the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in various ways for each particular application, but such implementation decisions do not cause a departure from the scope of the present disclosure.
[0104] Furthermore, a person of ordinary skill in the art would understand that various illustrative logical blocks, modules, devices, components, and circuits described herein can be implemented within or performed by an integrated circuit (IC) that can include a general purpose processor, a digital signal processor (DSP) , an application specific integrated circuit (ASIC) , a field programmable gate array (FPGA) or other programmable logic device, or any combination thereof. The logical blocks, modules, and circuits can further include antennas and / or transceivers to communicate with various components within the network or within the device. A general purpose processor can be a microprocessor, but in the alternative, the processor can be any conventional processor, controller, or state machine. A processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or multiple microprocessors in conjunction with a DSP core, or any other suitable configuration to perform the functions described herein.
[0105] If implemented in software, the functions can be stored as one or multiple instructions or code on a computer-readable medium. Thus, the steps of a method or algorithm disclosed herein can be implemented as software stored on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that can be enabled to transfer a computer program or code from one place to another. A storage media can be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer.
[0106] In this document, the term “module” as used herein, refers to software, firmware, hardware, and any combination of these elements for performing the associated functions described herein. Additionally, for purpose of discussion, the various modules are described as discrete modules; however, as would be apparent to one of ordinary skill in the art, two or more modules may be combined to form a single module that performs the associated functions according to embodiments of the present solution.
[0107] Additionally, memory or other storage, as well as communication components, may be employed in embodiments of the present solution. It will be appreciated that, for clarity purposes, the above description has described embodiments of the present solution with reference to different functional units and processors. However, it will be apparent that any suitable distribution of functionality between different functional units, processing logic elements or domains may be used without detracting from the present solution. For example, functionality illustrated to be performed by separate processing logic elements, or controllers, may be performed by the same processing logic element, or controller. Hence, references to specific functional units are only references to a suitable means for providing the described functionality, rather than indicative of a strict logical or physical structure or organization.
[0108] Various modifications to the embodiments described in this disclosure will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments without departing from the scope of this disclosure. Thus, the disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the novel features and principles disclosed herein, as recited in the claims below.
Claims
1.A wireless communication method, comprising:sending, by a first network entity to a second network entity, a message for positioning;sending, by the first network entity to the second network entity, capability and / or request for monitoring; andreceiving, by the first network entity from the second network entity, a configuration for positioning.2.The wireless communication method of claim 1, wherein the message includes UE capability for a first measurement and / or a second measurement, wherein the UE capability includes at least one of: one or more supported number of samples / paths, one or more supported timing granularity factors, one or more indicators and / or supported number of extent additional samples / paths, or one or more supported sample / path selection criterion / criteria.3.The wireless communication method of claim 1, wherein the configuration includes a measurement request for a first measurement and / or a second measurement, wherein the configuration includes at least one of: one or more requested number of samples / paths, one or more requested timing granularity factors, requested number of extent additional samples / paths, expected sample / paths selection criterion / criteria, or one or more indicators associated with each request.4.The wireless communication method of any of claim 2 or 3, wherein the number of samples / paths includes at least one of: a number of continuous and / or discontinuous samples / paths, a number of continuous and / or discontinuous samples / paths groups / in groups, a number of continuous and / or discontinuous samples / paths in each group, or a number of additional samples / paths.5.The wireless communication method of claim 2, wherein each of the one or more supported timing granularity factors includes one or more integer ranges.6.The wireless communication method of claim 2, wherein each of the one or more indicators indicates whether a UE supports measurement and / or reports for extend additional samples / paths.7.The wireless communication of claim 3, wherein each of the one or more indicators indicates whether a UE / TRP should conform to the configured measurement request.8.The wireless communication of claim 3, wherein each of the one or more indicators can be a soft and / or a hard value.9.The wireless communication method of claim 1, wherein the message includes measurement information of a reference signal, and the measurement information can be associated with one or more indicators.10.The wireless communication method of claim 9, wherein each of the one or more indicators indicates that a measurement and / or a report conforms to the measurement configuration.11.The wireless communication method of claim 9, wherein each of the one or more indicators indicates that a measurement and / or a report conforms to one or more of the following measurement configurations: a number of samples / paths, a timing granularity factor, a number of extent additional samples / paths, and one or more sample / path selection criterion / criteria.12.The wireless communication method of any of claim 2, 3, or 11, wherein the selection criterion / criteria can be one or more of: report (several) strongest power samples / paths, or report (several) extremum strongest power samples / paths.13.The wireless communication method of claim 1, wherein the configuration comprises at least one of: an error range, a maximum range, or location error group (ID) information.14.The wireless communication method of claim 13, wherein the error range, the maximum range, and the location error group (ID) information are each associated with corresponding measurement / location information.15.The wireless communication method of claim 1, wherein the message comprises a valid (time) duration.16.The wireless communication method of claim 15, wherein the valid (time) duration corresponds to a location error range, a maximum range, and / or a location error group (ID) .17.The wireless communication method of claim 1, wherein the capability for monitoring includes at least one of: an indicator indicating whether a UE has capability for monitoring, one or more time interval values, or a response time.18.The wireless communication method of claim 1, wherein the request for monitoring includes at least one of: a number of models, a preferred monitoring window configuration, or a time interval for monitoring.19.The wireless communication method of claim 17, wherein the time interval indicates a time difference between two adjacent model monitoring behaviors / procedures.20.The wireless communication method of claim 17, wherein the response time indicates a time difference between a starting time and an ending time of a monitoring procedure.21.The wireless communication method of claim 1, wherein the message includes one or more of: SL-PRS resource ID, UE ID, one or more indicators, or measurement information of the SL-PRS resource.22.The wireless communication method of claim 21, wherein each of the one or more indicators refers to whether the first network entity detects SL-PRS.23.The wireless communication method of claim 1, wherein the message includes one or more of: model ID, model configuration information, associated ID, quality indicator, accuracy or range indicator, recommended model ID / associated ID.24.The wireless communication method of claim 1, wherein the configuration includes one or more of: model ID, model configuration information, associated ID, quality indicator, accuracy or range indicator, recommended model ID / associated ID.25.A wireless communication method, comprising:reporting, by a first network entity to a second network entity, capability of the first network entity for a first measurement and / or a second measurement.receiving, by the first network entity from the second network entity, a configuration for positioning.26.The wireless communication method of claim 25, further comprising determining, by the first or the second network entity, the measurement period requirement for the first measurement and / or a second measurement.27.The wireless communication method of claim 26, wherein the measurement period requirement is related to the capability of the first network entity and / or the configuration for positioning.28.The wireless communication method of claim 25 or 27, wherein the capability includes TEG / beam sweeping capability, and / or an indicator.29.The wireless communication method of 25 or 27, wherein the configuration for positioning includes one or more of: downlink positioning reference signal samples / instances; or uplink sounding reference signal samples / instances.30.The wireless communication method of 25, wherein the configuration includes one or more of: PPW configuration, MG configuration for the first measurement and / or the second measurement.31.The wireless communication method of 30, wherein the PPW / MG configuration is associated to a first and / or second measurement.32.The wireless communication method of 25 or 30, wherein the configuration and / or PPW / MG configuration includes one or more indicators.33.The wireless communication method of 32, wherein the indicator indicates the configuration only applicable for a first / second measurement.34.The wireless communication method of 32, wherein the indicator indicates the configuration applicable for a first and a second measurement.35.A wireless communications apparatus comprising a processor and a memory, wherein the processor is configured to read code from the memory and implement a method recited in any of claims 1 to 34.36.A computer program product comprising a computer-readable program medium code stored thereupon, the code, when executed by a processor, causing the processor to implement a method recited in any of claims 1 to 34.
Citation Information
Patent Citations
Location information in communications networks
CN107852582A
Measurements and reporting for user equipment (UE) positioning in wireless networks
US20220113365A1
Access point assisted positioning for a user equipment (UE)
US20230328678A1
Systems and methods for improving accuracy of UE location determinations in a wireless communications network
WO2023110161A1