Downlink channel profile measurement for machine learning positioning
Downlink channel sample-based measurement profiles using machine learning improve UE location estimation in wireless communication systems by managing resource overhead and enhancing accuracy in complex environments.
Patent Information
- Application Number
- PCT/IB2025/051568
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2024-02-16
- Filing Date
- 2025-02-13
- Publication Date
- 2025-07-17
AI Technical Summary
Existing wireless communication systems face challenges in accurately determining the location of user equipment (UE) using conventional positioning methods, particularly in indoor environments, due to the complexity of multipath propagation and the need for efficient resource management in channel profile measurements.
The implementation of downlink channel sample-based measurement profiles using machine learning techniques, where UEs and positioning equipment conduct and transmit measurements on reference signals, enabling a machine learning model to determine UE location based on power delay profiles, angular delay profiles, and angle spectrum functions, with configurable measurement configurations to manage overhead.
Enhances positioning accuracy and reduces resource consumption by leveraging machine learning to analyze channel profiles, providing precise UE location estimation even in complex environments while optimizing signaling overhead.
Smart Images

Figure IB2025051568_17072025_PF_FP_ABST
Abstract
Description
DOWNLINK CHANNEL PROFILE MEASUREMENTFOR MACHINE LEARNING POSITIONINGRELATED APPLICATION
[0001] This application claims priority to U.S. Provisional Application Serial No. 63 / 554,783 filed February 16, 2024 entitled “Downlink Channel Profile Measurement for Machine Learning Positioning,” the disclosure of which is incorporated by reference herein in its entirety.TECHNICAL FIELD
[0002] The present disclosure relates to wireless communications, and more specifically to machine learning techniques for wireless device positioning.BACKGROUND
[0003] A wireless communications system may include one or multiple network communication devices, which may be otherwise known as network equipment (NE), supporting wireless communications for one or multiple user communication devices, which may be otherwise known as user equipment (UE), or other suitable terminology. The wireless communications system may support wireless communications with one or multiple user communication devices by utilizing resources of the wireless communication system (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like)) or frequency resources (e.g., subcarriers, carriers, or the like). Additionally, the wireless communications system may support wireless communications across various radio access technologies including third generation (3G) radio access technology, fourth generation (4G) radio access technology, fifth generation (5G) radio access technology, among other suitable radio access technologies beyond 5G (e.g., sixth generation (6G)).
[0004] The wireless communications system may support wireless device positioning and location, such as to estimate positioning and determine a location of a UE in the wireless communications system. The wireless communications system may also include one or more wireless devices, such as UEs and / or NE, among other devices, that transmit and / or receive signaling. Location services that enable positioning estimations may be supported in the wirelesscommunications system, such as to determine the location of a UE to receive transmitted signals in the wireless communications system.SUMMARY
[0005] An article “a” before an element is unrestricted and understood to refer to “at least one” of those elements or “one or more” of those elements. The terms “a,” “at least one,” “one or more,” and “at least one of one or more” may be interchangeable. As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of’ or “one or more of’ or “one or both of’) indicates an inclusive list such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C). Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an example step that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on.” Further, as used herein, including in the claims, a “set” may include one or more elements.
[0006] A UE for wireless communication is described. The UE may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the UE may be configured to, capable of, or operable to receive, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; and transmit, to the positioning equipment for a positioning estimation, the one or more downlink channel sample -based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
[0007] A processor (e.g., a standalone processor chipset, or a component of a UE) for wireless communication is described. The processor may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the processor may be configured to, capable of, or operable to receive, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; and transmit, to the positioning equipment for a positioning estimation, the one ormore downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
[0008] A method performed or performable by a UE for wireless communication is described. The method may include receiving, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; and transmitting, to the positioning equipment for a positioning estimation, the one or more downlink channel sample -based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
[0009] In some implementations of the UE, the processor, and the method described herein, the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured. In some implementations of the UE, the processor, and the method described herein, the one or more downlink channel sample -based measurement profile measurements are associated with one or more channel profiles comprising one or more of a power delay profile (PDP), an angular delay profile (ADP), an angle spectrum function (ASF), or a delay profile (DP). In some implementations of the UE, the processor, and the method described herein, the UE, the processor, and the method may be configured to, capable of, or operable to perform the one or more downlink channel sample -based measurement profile measurements on the reference signal based at least in part on a capability of the UE to perform the one or more downlink channel sample-based measurement profile measurements. In some implementations of the UE, the processor, and the method described herein, the one or more downlink channel sample -based measurement profile measurements are input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation. In some implementations of the UE, the processor, and the method described herein, the input data is usable to train the machine learning model to determine the positioning estimation. In some implementations of the UE, the processor, and the method described herein, the UE is configured as a positioning reference unit (PRU) UE that has a known location. In some implementations of the UE, the processor, and the method described herein, the positioning equipment is at least one of a location server, a location management function (LMF), an additional UE, or a PRU UE. In some implementations of the UE, the processor, and the method described herein, the reference signal is at least one of a downlink positioning reference signal (DL-PRS), a synchronization signal block (SSB), a channel stateinformation reference signal (CSI-RS), a demodulation reference signal (DM-RS), a tracking reference signal (TRS), or a phase tracking reference signal (PT-RS). In some implementations of the UE, the processor, and the method described herein, the configuration parameters of the measurement configuration to conduct the one or more downlink channel sample-based measurement profile measurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths.
[0010] In some implementations of the UE, the processor, and the method described herein, the UE, the processor, and the method may be configured to, capable of, or operable to maintain the one or more downlink channel sample -based measurement profile measurements as one or more of a one-dimensional (ID), a two-dimensional (2D), a three-dimensional (3D), or a multi-dimensional signature or fingerprint vector that represents a known location of a transmission-reception point (TRP). In some implementations of the UE, the processor, and the method described herein, the one or more downlink channel sample -based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal. In some implementations of the UE, the processor, and the method described herein, the one or more downlink channel sample-based measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length. In some implementations of the UE, the processor, and the method described herein, the UE, the processor, and the method may be configured to, capable of, or operable to report the one or more downlink channel sample -based measurement profile measurements as a configuration of at least one of a power threshold or a power interval. In some implementations of the UE, the processor, and the method described herein, a number of the one or more downlink channel sample-based measurement profile measurements to be conducted is reduced based at least in part on one or more of a prioritization of TRPs to be measured, one or more quality metrics of a channel profile, or a number of additional UEs reporting the one or more downlink channel samplebased measurement profile measurements. In some implementations of the UE, the processor, and the method described herein, the UE, the processor, and the method may be configured to, capable of, or operable to transmit at least one of the one or more downlink channel sample-basedmeasurement profile measurements and associated one or more measurement quality metrics. In some implementations of the UE, the processor, and the method described herein, to conduct the one or more downlink channel sample -based measurement profile measurements on the reference signal, configuration parameters of the measurement configuration include an indication of one or more of a channel delay spread, frequency synchronization parameters comprising carrier phase offset or Doppler shift, or time synchronization parameters comprising transmitter or receiver time offsets.
[0011] A positioning equipment for wireless communication is described. The positioning equipment may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the positioning equipment may be configured to, capable of, or operable to transmit, to a UE, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; receive, from the UE, the one or more downlink channel sample -based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration; perform a positioning estimation based at least in part on the one or more downlink channel sample -based measurement profile measurements; and determine a location of the UE based at least in part on the positioning estimation.
[0012] A processor (e.g., a standalone processor chipset, or a component of a positioning equipment) for wireless communication is described. The processor may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the processor may be configured to, capable of, or operable to transmit, to a UE, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; receive, from the UE, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration; perform a positioning estimation based at least in part on the one or more downlink channel sample-based measurement profile measurements; and determine a location of the UE based at least in part on the positioning estimation.
[0013] A method performed or performable by a positioning equipment for wireless communication is described. The method may include transmitting, to a UE, a measurement configuration to conduct one or more downlink channel sample-based measurement profilemeasurements on a reference signal; receiving, from the UE, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration; performing a positioning estimation based at least in part on the one or more downlink channel sample -based measurement profile measurements; and determining a location of the UE based at least in part on the positioning estimation.
[0014] In some implementations of the positioning equipment, the processor, and the method described herein, the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured. In some implementations of the positioning equipment, the processor, and the method described herein, the one or more downlink channel sample-based measurement profile measurements are associated with one or more channel profiles comprising one or more of a PDP, an ADP, an ASF, or a DP. In some implementations of the positioning equipment, the processor, and the method described herein, the positioning equipment, the processor, and the method may be configured to, capable of, or operable to use the one or more downlink channel sample-based measurement profile measurements as input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation. In some implementations of the positioning equipment, the processor, and the method described herein, the positioning equipment, the processor, and the method may be configured to, capable of, or operable to use the input data to train the machine learning model to determine the positioning estimation.
[0015] In some implementations of the positioning equipment, the processor, and the method described herein, the positioning equipment is at least one of a location server, a LMF, an additional UE, or a PRU UE. In some implementations of the positioning equipment, the processor, and the method described herein, the reference signal is at least one of a DL-PRS, a SSB, a CSI-RS, a DM- RS, a TRS, or a PT-RS. In some implementations of the positioning equipment, the processor, and the method described herein, the configuration parameters of the measurement configuration to conduct the one or more downlink channel sample -based measurement profile measurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths. In some implementations of the positioning equipment, the processor, and the method described herein, the one or more downlink channel sample-based measurement profile measurements includechannel profile measurement information determined over a configured bandwidth of the reference signal. In some implementations of the positioning equipment, the processor, and the method described herein, the one or more downlink channel sample-based measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length.BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 illustrates an example of a wireless communications system in accordance with aspects of the present disclosure.
[0017] Figure 2 illustrates an example of a system for NR beam-based positioning, in accordance with aspects of the present disclosure.
[0018] Figure 3 illustrates an example of a multi-cell round trip time (RTT) signaling procedure, in accordance with aspects of the present disclosure.
[0019] Figure 4 illustrates an example system of a functional framework for a machine learning model and NR air interface, in accordance with aspects of the present disclosure.
[0020] Figure 5 illustrates an example of a machine learning model functional framework for RAN intelligence, in accordance with aspects of the present disclosure.
[0021] Figure 6 illustrates an example procedure diagram for using DL-based PDP, ADP, ASF, DP measurements by a machine learning model to determine and output a location of a UE, in accordance with aspects of the present disclosure.
[0022] Figure 7 illustrates an example (P)RS received power delay profile, in accordance with aspects of the present disclosure.
[0023] Figure 8 illustrates an example (P)RS received power-angle profile and angle-delay profile as a signature, in accordance with aspects of the present disclosure.
[0024] Figure 9 illustrates an example (P)RS transmitted AoD profile as a signature, in accordance with aspects of the present disclosure.
[0025] Figure 10 illustrates an example (P)RS received delay profile, in accordance with aspects of the present disclosure.
[0026] Figure 11 illustrates an example OFDM slot and RB grid in an enhanced TRS layout, in accordance with aspects of the present disclosure.
[0027] Figure 12 illustrates an example of a UE in accordance with aspects of the present disclosure.
[0028] Figure 13 illustrates an example of a processor in accordance with aspects of the present disclosure.
[0029] Figure 14 illustrates an example of a network equipment (NE) in accordance with aspects of the present disclosure.
[0030] Figure 15 illustrates a flowchart of a method performed by a UE in accordance with aspects of the present disclosure.
[0031] Figure 16 illustrates a flowchart of a method performed by a positioning equipment in accordance with aspects of the present disclosure.DETAILED DESCRIPTION
[0032] A wireless communications system may support location services that enable positioning estimations (e.g., determining, tracking, identifying, monitoring, estimating) of wireless device locations in the wireless communications system. The wireless communications system includes one or more wireless devices, such as UEs and / or NEs, among other devices, that transmit and / or receive signaling. For example, a UE may establish a wireless connection with a NE for transmitting and / or receiving control signaling, data signaling, or both. Reference is made herein to communicating data or information, such as signaling communication resources and / or communications that are transmitted or received between devices. It is to be appreciated that other terms may be used interchangeably with communicating, such as signaling, transmitting, receiving, outputting, forwarding, retrieving, obtaining, and so forth.
[0033] Features and characteristics of a transmitted signal in the wireless communications system may include a received signal strength, a delay profile, a power delay profile (e.g., referencesignal received power (RSRP), reference signal received path power (RSRPP), a received signal strength indicator (RSSI) of a particular reference signal), and / or a channel impulse response (CIR) of a received signal. A CIR of a received signal is a measure of how a wireless channel affects a transmitted signal over time, and can be used to characterize the multipath propagation, delay spread, and frequency selectivity of the channel. The CIR can support time domain characterization of the signal power and angular components of a received signal, and therefore may be considered more accurate representation of the signal, rather than considering only the received signal strength characteristics of the signal. A radio frequency signature, or fingerprint, may include any one or more of these features and characteristics of a transmitted signal, and therefore, an identifying signature or fingerprint of the signal may be detectable.
[0034] Aspects of the present disclosure support using artificial intelligence (Al) and / or machine learning (ML), and are directed to ascertaining the measurements, signaling, and features that support location management component (LCM) operations for direct and / or assisted Al and / or ML positioning. In a context of positioning estimations, a location estimation of a wireless device in the wireless communications system may be performed using Al and / or ML for NR air interface based at least in part on the identifying signature or fingerprint of a received signal that has been transmitted by the wireless device, such as a UE. The location of the UE may be determined based on the radio frequency signature and other features associated with the signal at the particular location. The location may be characterized and represented by the unique channel observations that are measured and / or determined as the signature or fingerprint of a transmitted signal from a wireless device at the particular location. This also supports positioning estimations of wireless device locations in indoor environments.
[0035] Aspects of the present disclosure support using a ML model or algorithm (e.g., a neural network, artificial intelligence (Al) algorithms). For example, a positioning equipment (e.g., a location management function (LMF)) implemented at least in part with a machine learning model may include Al, a ML model or algorithm, a neural network, and / or any other type of machine learning model to implement the described techniques. As used herein, a machine learning model refers to a computer representation that is trainable based on inputs to approximate unknown functions. For example, a machine learning model can utilize algorithms to learn from, and make predictions on, inputs of known data (e.g., training and / or reference data) by analyzing the knowndata to learn to generate outputs. In aspects of the present disclosure, a machine learning model may receive input data as one or more channel profile measurements and determine positioning estimations, such as a location of a UE in a wireless communications system. A channel profile may be based on signal characteristics, such as a downlink-based PDP, an ADP, and / or a DP of a reference signal (e.g., DL positioning reference signal (PRS), CSI RS, etc.).
[0036] Additional aspects of the present disclosure are directed to establishing a channel profile that can be derived for a downlink transmission at a particular location based on the signature or fingerprint of a transmitted signal. A channel profile may depend on the signal characteristics of a captured signal and the link to be measured, such as the downlink-based PDP, ADP, ASF, and / or DP of a reference signal (e.g., DL PRS, CSI RS, etc.). These channel profile measurements of a signal may be provided as input data to a machine learning model (e.g., an Al and / or ML model) that can train on the input data, as well as infer or determine the location of a wireless device in the wireless communications system based on positioning estimation.
[0037] As training data for the machine learning model, the input data (e.g., as one or more channel profile measurements) are configurable, such as depending on the application or scenario in which an Al and / or ML process (e.g., for training or inference) manages processing and resources overhead for training and / or performing positioning estimation, while maintaining accuracy of the measurements and estimations. The channel profile measurements support the Al and / or ML positioning techniques, such as based on a signal signature or fingerprinting of the signal. In addition to providing support for Al and / or ML positioning, the described techniques support managing signaling overhead, such as by allowing a signal measurement vector that represents the channel profile measurements to be configurable depending on aspects such as the number of samples, the sampling resolution, as well as the power, time, angle, and domain characteristics.
[0038] Aspects of the present disclosure are described in the context of a wireless communications system.
[0039] Figure 1 illustrates an example of a wireless communications system 100 in accordance with aspects of the present disclosure. The wireless communications system 100 may include one or more NE 102, one or more UE 104, and a core network (CN) 106. The wireless communications system 100 may support various radio access technologies. In some implementations, the wirelesscommunications system 100 may be a 4G network, such as an LTE network or an LTE- Advanced (LTE-A) network. In some other implementations, the wireless communications system 100 may be a NR network, such as a 5G network, a 5G-Advanced (5G-A) network, or a 5G ultrawideband (5G-UWB) network. In other implementations, the wireless communications system 100 may be a combination of a 4G network and a 5G network, or other suitable radio access technology including Institute of Electrical and Electronics Engineers (IEEE) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20. The wireless communications system 100 may support radio access technologies beyond 5G, for example, 6G. Additionally, the wireless communications system 100 may support technologies, such as time division multiple access (TDMA), frequency division multiple access (FDMA), or code division multiple access (CDMA), etc.
[0040] The one or more NE 102 may be dispersed throughout a geographic region to form the wireless communications system 100. One or more of the NE 102 described herein may be or include or may be referred to as a network node, a base station, a network element, a network function, a network entity, network infrastructure (or infrastructure), a radio access network (RAN), a NodeB, an eNodeB (eNB), a next-generation NodeB (gNB), or other suitable terminology. An NE 102 and a UE 104 may communicate via a communication link, which may be a wireless or wired connection. For example, an NE 102 and a UE 104 may perform wireless communication (e.g., receive signaling, transmit signaling) over a Uu interface.
[0041] An NE 102 may provide a geographic coverage area for which the NE 102 may support services for one or more UEs 104 within the geographic coverage area. For example, an NE 102 and a UE 104 may support wireless communication of signals related to services (e.g., voice, video, packet data, messaging, broadcast, etc.) according to one or multiple radio access technologies. In some implementations, an NE 102 may be moveable, for example, a satellite associated with a non-terrestrial network (NTN). In some implementations, different geographic coverage areas associated with the same or different radio access technologies may overlap, but the different geographic coverage areas may be associated with different NE 102.
[0042] The one or more UEs 104 may be dispersed throughout a geographic region of the wireless communications system 100. A UE 104 may include or may be referred to as a remote unit, a mobile device, a wireless device, a remote device, a subscriber device, a transmitter device, a receiver device, or some other suitable terminology. In some implementations, the UE 104 may bereferred to as a unit, a station, a terminal, or a client, among other examples. Additionally, or alternatively, the UE 104 may be referred to as an Internet-of-Things (loT) device, an Internet-of- Everything (loE) device, or machine-type communication (MTC) device, among other examples.
[0043] A UE 104 may be able to support wireless communication directly with other UEs 104 over a communication link. For example, a UE 104 may support wireless communication directly with another UE 104 over a device-to-device (D2D) communication link. In some implementations, such as vehicle-to-vehicle (V2V) deployments, vehicle-to-everything (V2X) deployments, or cellular-V2X deployments, the communication link may be referred to as a sidelink. For example, a UE 104 may support wireless communication directly with another UE 104 over a PC5 interface.
[0044] An NE 102 may support communications with the CN 106, or with another NE 102, or both. For example, an NE 102 may interface with other NE 102 or the CN 106 through one or more backhaul links (e.g., SI, N2, N6, or other network interface). In some implementations, the NE 102 may communicate with each other directly. In some other implementations, the NE 102 may communicate with each other indirectly (e.g., via the CN 106). In some implementations, one or more NE 102 may include subcomponents, such as an access network entity, which may be an example of an access node controller (ANC). An ANC may communicate with the one or more UEs 104 through one or more other access network transmission entities, which may be referred to as a radio heads, smart radio heads, or transmission-reception points (TRPs).
[0045] The CN 106 may support user authentication, access authorization, tracking, connectivity, and other access, routing, or mobility functions. The CN 106 may be an evolved packet core (EPC), or a 5G core (5GC), which may include a control plane entity that manages access and mobility (e.g., a mobility management entity (MME), an access and mobility management functions (AMF)) and a user plane entity that routes packets or interconnects to external networks (e.g., a serving gateway (S-GW), a packet data network (PDN) gateway (P-GW), or a user plane function (UPF)). In some implementations, the control plane entity may manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management (e.g., data bearers, signal bearers, etc.) for the one or more UEs 104 served by the one or more NE 102 associated with the CN 106.
[0046] The CN 106 may communicate with a packet data network over one or more backhaul links (e.g., via an SI, N2, N6, or other network interface). The packet data network may include an application server. In some implementations, one or more UEs 104 may communicate with the application server. A UE 104 may establish a session (e.g., a protocol data unit (PDU) session, or the like) with the CN 106 via an NE 102. The CN 106 may route traffic (e.g., control information, data, and the like) between the UE 104 and the application server using the established session (e.g., the established PDU session). The PDU session may be an example of a logical connection between the UE 104 and the CN 106 (e.g., one or more network functions of the CN 106).
[0047] In the wireless communications system 100, the NEs 102 and the UEs 104 may use resources of the wireless communications system 100 (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers)) to perform various operations (e.g., wireless communications). In some implementations, the NEs 102 and the UEs 104 may support different resource structures. For example, the NEs 102 and the UEs 104 may support different frame structures. In some implementations, such as in 4G, the NEs 102 and the UEs 104 may support a single frame structure. In some other implementations, such as in 5G and among other suitable radio access technologies, the NEs 102 and the UEs 104 may support various frame structures (i.e., multiple frame structures). The NEs 102 and the UEs 104 may support various frame structures based on one or more numerologies.
[0048] One or more numerologies may be supported in the wireless communications system 100, and a numerology may include a subcarrier spacing and a cyclic prefix. A first numerology (e.g., / r=0) may be associated with a first subcarrier spacing (e.g., 15 kHz) and a normal cyclic prefix. In some implementations, the first numerology (e.g., / r=0) associated with the first subcarrier spacing (e.g., 15 kHz) may utilize one slot per subframe. A second numerology (e.g., / r=l) may be associated with a second subcarrier spacing (e.g., 30 kHz) and a normal cyclic prefix. A third numerology (e.g., / r=2) may be associated with a third subcarrier spacing (e.g., 60 kHz) and a normal cyclic prefix or an extended cyclic prefix. A fourth numerology (e.g., / r=3) may be associated with a fourth subcarrier spacing (e.g., 120 kHz) and a normal cyclic prefix. A fifth numerology (e.g., / r=4) may be associated with a fifth subcarrier spacing (e.g., 240 kHz) and a normal cyclic prefix.
[0049] A time interval of a resource (e.g., a communication resource) may be organized according to frames (also referred to as radio frames). Each frame may have a duration, for example, a 10 millisecond (ms) duration. In some implementations, each frame may include multiple subframes. For example, each frame may include 10 subframes, and each subframe may have a duration, for example, a 1 ms duration. In some implementations, each frame may have the same duration. In some implementations, each subframe of a frame may have the same duration.
[0050] Additionally, or alternatively, a time interval of a resource (e.g., a communication resource) may be organized according to slots. For example, a subframe may include a number (e.g., quantity) of slots. The number of slots in each subframe may also depend on the one or more numerologies supported in the wireless communications system 100. For instance, the first, second, third, fourth, and fifth numerologies (i.e., / r=0, jU=l , / r=2, / r=3, / r=4) associated with respective subcarrier spacings of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz may utilize a single slot per subframe, two slots per subframe, four slots per subframe, eight slots per subframe, and 16 slots per subframe, respectively. Each slot may include a number (e.g., quantity) of symbols (e.g., OFDM symbols). In some implementations, the number (e.g., quantity) of slots for a subframe may depend on a numerology. For a normal cyclic prefix, a slot may include 14 symbols. For an extended cyclic prefix (e.g., applicable for 60 kHz subcarrier spacing), a slot may include 12 symbols. The relationship between the number of symbols per slot, the number of slots per subframe, and the number of slots per frame for a normal cyclic prefix and an extended cyclic prefix may depend on a numerology. It should be understood that reference to a first numerology (e.g., / r=0) associated with a first subcarrier spacing (e.g., 15 kHz) may be used interchangeably between subframes and slots.
[0051] In the wireless communications system 100, an electromagnetic (EM) spectrum may be split, based on frequency or wavelength, into various classes, frequency bands, frequency channels, etc. By way of example, the wireless communications system 100 may support one or multiple operating frequency bands, such as frequency range designations FR1 (410 MHz - 7.125 GHz), FR2 (24.25 GHz - 52.6 GHz), FR3 (7.125 GHz - 24.25 GHz), FR4 (52.6 GHz - 114.25 GHz), FR4a or FR4-1 (52.6 GHz - 71 GHz), and FR5 (114.25 GHz - 300 GHz). In some implementations, the NEs 102 and the UEs 104 may perform wireless communications over one or more of the operating frequency bands. In some implementations, FR1 may be used by the NEs 102 and the UEs 104, among other equipment or devices for cellular communications traffic (e.g.,control information, data). In some implementations, FR2 may be used by the NEs 102 and the UEs 104, among other equipment or devices for short-range, high data rate capabilities.
[0052] FR1 may be associated with one or multiple numerologies (e.g., at least three numerologies). For example, FR1 may be associated with a first numerology (e.g., / r=0), which includes 15 kHz subcarrier spacing; a second numerology (e.g., / r=l), which includes 30 kHz subcarrier spacing; and a third numerology (e.g., / r=2), which includes 60 kHz subcarrier spacing. FR2 may be associated with one or multiple numerologies (e.g., at least 2 numerologies). For example, FR2 may be associated with a third numerology (e.g., / r=2), which includes 60 kHz subcarrier spacing; and a fourth numerology (e.g., / r=3), which includes 120 kHz subcarrier spacing.
[0053] According to implementations, one or more of the NEs 102 and the UEs 104 are operable to implement various aspects of the techniques described with reference to the present disclosure. In one or more implementations, a UE 104 receives, from a positioning equipment (e.g., a NE 102 implemented as a positioning equipment), a measurement configuration to conduct one or more downlink channel profile measurements on a reference signal. The UE 104 transmits, to the positioning equipment for a positioning estimation, the one or more downlink channel profile measurements performed on the reference signal based on the measurement configuration. In one or more implementations, a positioning equipment (e.g., a NE 102 implemented as a positioning equipment) transmits, to a UE 104, a measurement configuration to conduct one or more downlink channel profile measurements on a reference signal. The positioning equipment receives, from the UE 104, the one or more downlink channel profile measurements performed on the reference signal based on the measurement configuration. The positioning equipment can then perform a positioning estimation based on the one or more downlink channel profile measurements, and determine a location of the UE 104 based on the positioning estimation. In one or more implementations, a UE 104 is configured as a PRU UE that has a known location, and the positioning equipment is at least one of a location server, a LMF, an additional UE, or a PRU UE. In further one or more implementations, the one or more downlink channel profile measurements are input data to a machine learning model that determines a location of the UE 104 based on the positioning estimation. The input data is also usable to train the machine learning model to determine the positioning estimation.
[0054] Separate positioning techniques, as indicated in Table (1) below, can be currently configured and performed based on the requirements of the LMF and UE capabilities. The transmission of PRSs enable a UE to perform UE positioning -related measurements, enable computation of a UE’s location estimate, and are configured per TRP, where a TRP may transmit one or more beams.Table (1): Supported Rel-16 UE Positioning Methods
[0055] Figure 2 illustrates an example of system 200 for NR beam-based positioning in accordance with aspects of the present disclosure. The system 200 illustrates a UE 104 and NEs 102 (e.g., gNBs). The PRS can be transmitted by different base stations (serving and neighboring) using narrow beams over FR1 and FR2 as illustrated in the example system 200, which is relatively different when compared to LTE where the PRS was transmitted across the whole cell. The PRS can be locally associated with a PRS resource identifier (ID) and resource set ID for a base station (e.g., a TRP). Similarly, UE positioning measurements, such as reference signal time difference(RSTD) and PRS RSRP measurements are performed on a per beam basis (e.g., based on downlink (DL) PRS resources, or DL PRS resource sets) as opposed to different cells, as was the case in LTE. In addition, there are additional uplink (UL) positioning methods that the network can use to compute the location of a target UE.
[0056] A reference signal (RS) to measurements mapping is shown below in Table (2) and in Table (3), which indicate the RS to measurements mapping for each of the supported RAT- dependent positioning techniques at a UE and at a gNB, respectively. RAT-dependent positioning techniques involve the 3 GPP RAT and core network entities to perform a position estimation of a UE, which are differentiated from RAT-independent positioning techniques that rely on the global navigation satellite system (GNSS), inertial measurement unit (IMU) sensor, wireless local area network (WLAN), and Bluetooth technologies for performing target device (UE) positioning.Table (2): UE Measurements for RAT-dependent Positioning TechniquesTable (3): gNB Measurements for RAT-dependent Positioning Techniques.
[0057] Various RAT-dependent positioning techniques are supported in Rel-16, such as downlink time difference of arrival (DL-TDoA), DL-angle of departure (AoD), multi-RTT, enhanced cell-ID (E-CID) / NR E-CID, UL-TDoA, and UL-AoA. The DL-TDoA positioning method makes use of the measured DL PRS RSRP of downlink signals received from multiple transmission points (TPs), at the UE. The UE measures the DL PRS RSRP of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to locate the UE in relation to the neighboring TPs.
[0058] The DL AoD positioning method makes use of the measured DL PRS RSRP of downlink signals received from multiple TPs, at the UE. The UE measures the DL PRS RSRP of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to locate the UE in relation to the neighboring TPs.
[0059] Figure 3 illustrates an example 300 of a multi-cell RTT signaling procedure in accordance with aspects of the present disclosure. The multi-RTT positioning technique makes use of the UE Rx-Tx measurements and DL PRS RSRP of downlink signals received from multiple TRPs, as measured by the UE, as well as the measured gNB Rx-Tx measurements and uplink sounding reference signal (SRS) RSRP (UL SRS-RSRP) at multiple TRPs of uplink signals transmitted from a UE. The UE measures the UE Rx-Tx measurements (and optionally DL PRSRSRP of the received signals) using assistance data received from the positioning server (also referred to herein as a location server, or positioning equipment), and the TRPs the gNB Rx-Tx measurements (and optionally UL SRS-RSRP of the received signals) using assistance data received from the positioning server. The measurements are used to determine the RTT at the positioning server, which are used to estimate the location of the UE. The multi-RTT is only supported for UE-assisted and NG-RAN assisted positioning techniques as noted in Table (1).
[0060] For the E-CID positioning technique, the position of a UE is estimated with the knowledge of its serving ng-eNB, gNB, and cell, and is based on LTE signals. The information about the serving ng-eNB, gNB, and cell may be obtained by paging, registration, or other methods. The NR E-CID positioning refers to techniques which use additional UE measurements and / or NR radio resources and other measurements to improve the UE location estimate using NR signals. Although NR E-CID positioning may utilize some of the same measurements as the measurement control system in the RRC protocol, the UE may not (or is not expected to) make additional measurements for the sole purpose of positioning (e.g., the positioning procedures do not supply a measurement configuration or measurement control message, and the UE reports the measurements that it has available rather than being required to take additional measurement actions).
[0061] The UL-TDoA positioning technique makes use of the UL RTOA (and optionally UL SRS-RSRP) at multiple reception points (RPs) of uplink signals transmitted from UE. The RPs measure the UL-RTOA (and optionally UL SRS-RSRP) of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to estimate the location of the UE.
[0062] The UL-AoA positioning technique makes use of the measured azimuth and the zenith of arrival at multiple RPs of uplink signals transmitted from UE. The RPs measure azimuth- AoA (A-AoA) and zenith- AoA (Z-AoA) of the received signals using assistance data received from the positioning server (also referred to herein as the location server, or positioning equipment), and the resulting measurements are used along with other configuration information to estimate the location of the UE.
[0063] Various RAT-independent positioning techniques may also be used, such as network- assisted GNSS techniques, barometric pressure sensor positioning, WLAN positioning, Bluetoothpositioning, terrestrial beacon system (TBS) positioning, and motion sensor positioning. The network-assisted GNSS techniques make use of UEs that are equipped with radio receivers capable of receiving GNSS signals. In 3GPP specifications, the term GNSS encompasses both global and regional / augmentation navigation satellite systems. Examples of global navigation satellite systems include Global Positioning System (GPS), Modernized GPS, Galileo, Global Navigation Satellite System (GLONASS), and BeiDou Navigation Satellite System (BDS). Regional navigation satellite systems include Quasi Zenith Satellite System (QZSS), while the many augmentation systems are classified under the generic term of Space Based Augmentation Systems (SBAS) and provide regional augmentation services. The network-assisted GNSS techniques may use different GNSSs (e.g., GPS, Galileo, etc.) separately or in combination to determine the location of a UE.
[0064] The barometric pressure sensor positioning technique makes use of barometric sensors to determine the vertical component of the position of the UE. The UE measures barometric pressure, optionally aided by assistance data, to calculate the vertical component of its location or to send measurements to the positioning server for position calculation. This technique can be combined with other positioning techniques to determine the 3D position of a UE.
[0065] The WLAN positioning technique makes use of the WLAN measurements (access point (AP) identifiers and optionally other measurements) and databases to determine the location of the UE. The UE measures received signals from WLAN access points, optionally aided by assistance data, to send measurements to the positioning server for position calculation. Using the measurement results and a references database, the location of a UE can be calculated. Additionally, or alternatively, a UE makes use of WLAN measurements, and optionally WLAN AP assistance data provided by the positioning server to determine its location.
[0066] The Bluetooth positioning technique makes use of Bluetooth measurements (beacon identifiers and optionally other measurements) to determine the location of a UE. The UE measures received signals from Bluetooth beacons, and using the measurement results and a references database, the location of the UE can be calculated. The Bluetooth technique may be combined with other positioning techniques (e.g., WLAN) to improve positioning accuracy of a UE.
[0067] The TBS positioning technique includes a network of ground-based transmitters that broadcast signals for positioning purposes. Examples of types of TBS positioning signals areMetropolitan Beacon System (MBS) signals and PRSs. A UE measures received TBS signals, optionally aided by assistance data, to calculate its location and / or to send measurements to a positioning server for position calculation.
[0068] The motion sensor positioning techniques make use of different sensors, such as accelerometers, gyros, magnetometers, and so forth to calculate the displacement of a UE. The UE can estimate a relative displacement based on a reference position and / or a reference time. The UE can send a report that includes the determined relative displacement, which can be used to determine the absolute position of the UE. This technique can be used with other positioning techniques for hybrid positioning.
[0069] Different downlink measurements, such as used for RAT-dependent positioning measurements and techniques, include DL PRS-RSRP, DL RSTD, and UE Rx-Tx time difference, such as the supported RAT-dependent positioning techniques shown below in Table (4).Measurement configurations that may be used include four (4) pair of DL RSTD measurements, which may be performed per pair of cells, and each measurement is performed between a different pair of DL PRS resources and / or resource sets with a single reference timing. Additionally, eight (8) DL PRS RSRP measurements can be performed on different DL PRS resources from the same cell.Table (4): Positioning Measurement Definitions for DL-based and UL-based positioning
[0070] Figure 4 illustrates an example system 400 of a functional framework for a machine learning model and NR air interface, in accordance with aspects of the present disclosure. In this example system 400, the functional framework includes multiple processes that enable AI / ML functionality over the air interface. Data collection 402 is a function that provides input data to model training 404, management 406, and inference 408 functions. Training data 410 is a data input to the AI / ML model training 404, and monitoring data 412 is a data input to the management 406 of the AI / ML model or for AI / ML functionalities. Similarly, inference data 414 is a data input to the AI / ML function for inference 408.
[0071] The model training 404 is a function that performs AI / ML model training, validation, and testing, which may generate model performance metrics that can be used as part of the model testing procedure. The model training 404 is also responsible for data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) based on the training data 410 that is received from data collection 402, if required. A model storage 416 can be used to deliver trained, validated, and tested AI / ML models (e.g., a trained and / or updated model 418), or can receive an updated version of a model at the model storage.
[0072] The management 406 is a function that oversees the operation (e.g., selection, (de)activation, switching, and / or fallback) and monitoring (e.g., performance) of Al / ML models and / or AI / ML functionalities. This function is also implemented to make decisions to ensure the proper inference operation based on data received from the functions for data collection 402 and inference 408. A management instruction 420 from management 406 to inference 408 is information provided as an input to manage the inference function. This information may include selection, (de) activation and / or switching of AI / ML models and / or AI / ML-based functionalities, or as a fallback to non-AI / ML operations (i.e., not relying on an inference process), etc. A model transfer and / or delivery request 422 from management 406 to the model storage 416 is used to request model(s) from the model storage. A performance feedback and / or retraining request 424 from management 406 to model training 404 is information used as an input for the model training function (e.g., for model (re)training or updating purposes).
[0073] The function for inference 408 provides outputs from the process of applying AI / ML models and / or AI / ML functionalities, using the data that is provided by data collection 402 (i.e., the inference data 414 from data collection 402 as a data input to inference 408). The function of inference 408 is also responsible for data preparation (e.g., data pre-processing and cleaning, formatting, and transformation) based on the inference data 414 delivered by data collection 402, if required. An inference output 426 is data used by the function of management 406 to monitor the performance of AI / ML models and / or AI / ML functionalities.
[0074] The model storage 416 is a function responsible for storing the trained and / or updated models 418 that can be used to perform the inference function. The function of model storage 416 is representative of a reference point (if any) when applicable for protocol terminations, model transfer and / or delivery, and related processes. It should be noted that its purpose does not encompass restricting the actual storage locations of models, and all data, information, and instruction input and outputs to / from the model storage are case by case, as needed. The model transfer and / or delivery 428 is used to deliver an AI / ML model to the inference function.
[0075] With reference to positioning accuracy enhancements, some selected representative sub-use cases may include direct AI / ML positioning, with an AI / ML model output indicating a UE location (e.g., fingerprinting or signature based on channel observation as the input of the AI / ML model). An AI / ML assisted positioning, with an AI / ML model output indicating a newmeasurement and / or enhancement of an existing measurement (e.g., a line of sight (LOS) or NLOS identification, timing, and / or angle of measurement, likelihood of measurement). More specifically, additional use cases may include a case 1 for UE-based positioning with a UE-side model, direct AI / ML, or Al / ML assisted positioning; a case 2a for UE-assisted and / or LMF-based positioning with a UE-side model, or AI / ML assisted positioning; a case 2b for UE-assisted and / or LMF-based positioning with a LMF-side model, or direct AI / ML positioning; a case 3a for NG-RAN node assisted positioning with a gNB-side model, or AI / ML assisted positioning; and a case 3b for NG- RAN node assisted positioning with a LMF-side model, or direct AI / ML positioning. Additionally, a one-sided model with inference may be performed entirely at a UE, or at the network (e.g., as prioritized in Rel-18 SI).
[0076] Figure 5 illustrates an example of a machine learning model functional framework 500 for RAN intelligence, in accordance with aspects of the present disclosure. In this example, the functional framework 500 includes data collection 502 as a function that provides input data to model training 504 and model inference 506 functions. The AI / ML algorithm specific data preparation (e.g., data pre-processing and cleaning, formatting, and transformation) may not be implemented in the function for data collection 502. Examples of input data may include measurements from UEs or different network entities, feedback from an actor 508, and / or output from an AI / ML model. Training data 510 is a data input to the AI / ML model training 504, and inference data 512 is a data input to the AI / ML function for model inference 506. The model training 504 may provide a model deployment and / or update 514 to the function for model inference 506.
[0077] The function for model inference 506 provides AI / ML model inference output 516 (e.g. predictions or decisions), and in implementations, may provide model performance feedback 518 to the model training 504. The function for model inference 506 may also implemented for data preparation (e.g. data pre-processing and cleaning, formatting, and transformation) based on the inference data 512 delivered from data collection 502, if required. The inference output 516 of the AI / ML model is generated or determined by the model inference function, and details of the inference output are specific for various use cases. Additionally, the model performance feedback 518 from model inference 506 may be used to monitor the performance of the AI / ML model, when available. The actor 508 is a function that receives the output 516 from the model inference 506 andtriggers or performs corresponding actions. The actor 508 may trigger actions directed to other entities, or to itself. The feedback 520 back to data collection 502 is information that may be needed to derive the training data 510, the inference data 512, or to monitor the performance of the AI / ML model and its impact to the network through updating of KPIs and performance counters.
[0078] The following are some non-limiting examples of entities and terminologies that may be referred to in this disclosure. A transmission point (TP) is a set of geographically co-located transmit antennas (e.g. an antenna array, such as with one or more antenna elements) for one cell, part of one cell, or one PRS-only TP. Transmission points can include base station (eNodeB) antennas, remote radio heads, a remote antenna of a base station, an antenna of a PRS-only TP, etc. One cell can be formed by one or multiple transmission points. For a homogeneous deployment, each transmission point may correspond to one cell.
[0079] A reception point (RP) is a set of geographically co-located receive antennas (e.g. an antenna array, such as with one or more antenna elements) for one cell, part of one cell, or one UL- SRS-only RP. Reception points can include base station (ng-eNB or gNB) antennas, remote radio heads, a remote antenna of a base station, an antenna of a UL-SRS-only RP, etc. One cell can include one or multiple reception points. For a homogeneous deployment, each reception point may correspond to one cell. A transmission-reception point (TRP) is a set of geographically co-located antennas (e.g. an antenna array, such as with one or more antenna elements) supporting TP and / or RP functionality. A PRS-only TP is a TP that only transmits PRS signals or DL-PRS for PRS-based TBS positioning and is not associated with a cell.
[0080] A positioning reference unit (PRU) at a known location can perform positioning measurements (e.g., RSTD, RSRP, UE Rx-Tx time difference measurements, etc.) and report these measurements to a location server. In addition, the PRU can transmit SRS to enable TRPs to measure and report UL positioning measurements (e.g., RTOA, UL-AoA, gNB Rx-Tx time difference, etc.) from a PRU at a known location. The PRU measurements can be compared by a location server with the measurements expected at the known PRU location to determine correction terms for other nearby target devices. The DL and / or UL location measurements for other target devices can then be corrected based on the previously determined correction terms. A PRU may also comprise of a TRP with a known location.
[0081] Additionally, a target-UE may be referred to as a UE of interest, having a position or location (absolute or relative) that is to be obtained or determined by the network or by the UE itself. Further, any reference made to a device or UE position or location information may refer to a 2D or 3D absolute position, a 2D or 3D relative position, a distance, a relative direction with respect to another node or network entity, ranging in terms of distance, ranging in terms of direction, and / or any combination thereof. As described in the present disclosure, the terms Al and ML may be used interchangeably to refer to an intelligent software component or system, such as a machine learning model.
[0082] In aspects of this disclosure, a DL-based PDP, ADP, ASF, and / or DP measurement is an aspect to enable direct AI / ML-based positioning. For direct AI / ML positioning, techniques such as fingerprinting can be leveraged by AI / ML models to obtain enhanced location estimates based on the type of RF signatures associated with a given location. The present disclosure provides for DL- based PDP, ADP, ASF, and / or DP measurements that support implementations of direct AI / ML positioning, and provides for configurability to manage the CIR measurement overhead. In aspects of the described techniques, a first technique supports defining a multi-dimensional DL-based raw PDP vector signature or fingerprint for supporting UE-based positioning with a UE-side model, as well as UE-assisted and / or LMF-based positioning with a LMF-side model.
[0083] A second technique is described to define a multi-dimensional DL-based PDP, ADP, ASF, and / or DP vector signature or fingerprint on a sample level. It is noted that, in defining channel observations, they are a function of a number of samples and are performed over a time period and over a certain frequency, which could result in higher overhead measurements that may affect air interface resources. A third technique is described to define a single dimensional DL- based DP on a system-level (e.g., reduced TRPs to be measured and quality of the PDPs to be measured). A fourth technique is described to reduce the overhead that may occur for multidimensional DL-based PDP, ADP, ASF, and / or DP measurements, particularly on the system level (e.g., based on reducing the number of TRPs to be measured and a quality of the PDPs to be measured). A fifth technique is described, which takes into account time, frequency, and channel doppler variations of the channel through measurement of an enhanced RS on the downlink. It should be noted that any of the described techniques may be implemented in combination with each other.
[0084] With reference to the first described technique for DL-PRS fingerprint measurement and power delay profile, a fingerprint measurement is generated based on a power delay profile measurement of a received DL-PRS signal at a target-UE or PRU UE. In other implementations, other reference signals may be used to derive a fingerprint measurement including SSB, CSLRS, PT-RS, etc. In an example implementation, the DL-PRS fingerprint may be derived based on multiple transmitted DL-PRS resources that include one or more of positioning frequency layers (PFLs), TRPs, DL-PRS resource sets, DL-PRS resources, or a combination thereof. This RF fingerprint represents a unique RF signature of the received DL-PRS at a given location.
[0085] According to a current positioning framework, it is possible to obtain the first arrival path of the time-of-arrival (ToA) measurement, including up to eight (8) additional paths (as of Rel-17), which may be reported to the LMF. This implies that a total of nine (9) paths (including first path) of a supported positioning measurement (e.g., DL-RSTD and UE Rx-Tx time difference measurement) may be reported to the LMF. This effectively constitutes a delay profile of the received DL-PRS, which can serve as one type of input data. Additionally, a DL-PRS RSRPP measurement is defined, which is the power of the linear average of the channel response at the i'thpath delay of the resource elements that carry the DL-PRS signal configured for the measurement, which together with the additional paths, may implicitly constitute a power delay profile (PDP) of the received DL-PRS. Aside from the limited number of paths, the responsibility is on the data collection entity to piece together a type of measurement profile associated to a certain measurement data (e.g., RSTD, RTT measurements). Furthermore, a consolidated measurement capturing all of the power delay profile or delay profile characteristics has not yet been defined.
[0086] Figure 6 illustrates an example procedure diagram 600 for using DL-based PDP, ADP, ASF, and / or DP measurements by a machine learning model to determine and output a location of a UE, in accordance with aspects of the present disclosure. This example procedure diagram 600 represents an overview of the process from the perspective of receiver 602 (e.g., a UE, or a PRU UE that has a known location). An advantage of a PRU is that it can perform multiple measurements at a known location of the UE, store the captured data associated with the known location, which may then be used to train a machine learning model based on the stored and captured data.
[0087] At 604 (step 1), a UE or a PRU UE performs a DL-based PDP, ADP, ASF, and / or DP measurement per location per TRP based on the received DL-PRS and sample size. The UE may beconfigured for a type of PDP, ADP, ASF, and / or DP measurement to be performed (e.g., raw PDP, ADP, ASF, and / or DP measurements, or overhead reduced measurements). At 606 (step 2), the UE or the PRU UE performs associated receiver processing on the DL-based PDP, ADP, ASF, and / or DP measurements to remove any hardware and / or software imperfections of the measurement, or to assist in reducing the overall PDP.
[0088] At 608 (step 3), a data collection entity 610, which may include a UE, a PRU UE, or a network entity (e.g., a LMF, a network data analytics function (NWDAF)) may pre-process the DL PDP, ADP, ASF, and / or DP measurement inputs based on the techniques described for overhead reduction with pre-processing techniques, or remove outliers or add labels (e.g., reference location, timestamp information, PDP or DP quality metrics, etc.) to filter the measurement data. At 612 (step 4) the raw measurements (e.g., the unfiltered measurements from receiver processing at 606), or the processed input data (e.g., the filtered measurements for overhead reduction at 608), is provided as input data to an AI / ML model 614. At 616 (steps 5a, 5b), classification or regression techniques, or unsupervised learning techniques, are performed with a trained AI / ML model (also referred to herein as a machine learning model) with the goal of determining an output 618 as the location of a UE based on the DL-based PDP, ADP, ASF, and / or DP measurements. At 620 (step 6), the configured AI / ML model 614 outputs 2D and / or 3D location information of a target UE based on the trained, multi-dimensional PDP, ADP, ASF, and / or DP signatures or vectors.
[0089] Figure 7 illustrates an example (P)RS received power delay profile 700, in accordance with aspects of the present disclosure. A power delay profile measurement is generated based on a received DL-PRS signal at a target-UE or PRU UE, which has been transmitted from a gNB or TRP. It indicates the relative amplitude of multipath components arriving at different times and / or delays. It is normally computed by performing a spatial average of the complex valued CIR, which is shown at 702 in Figure 7 for a reference signal received with L paths or cluster paths, where Pt(at 704) is the transmit power, Pr0, Prl, ... PrLis received average power at each time instance with a delay t + TL, and the number of signal paths = [0,..., L].
[0090] The power delay profile is then defined by equation(l):S(T) = E[| / i(t, T) |2] (1)
[0091] Based on the discrete PDP shown in Figure 7, the root mean square (RMS) delay spread may be given as equation(2):where Pr(;) is the average received power of the Ithpath, r(is the delay of the Ithpath, while themean delay is given by T = — - - . The equation(2) is normally compared with the symbol Ll=i Pr(l) duration to determine the effect of inter-symbol interference but can also be used as a characteristic of a unique fingerprint for a particular location.
[0092] According to an aspect of the techniques, a consolidated power delay profile comprising of the received reference signal (RS) power and / or amplitude and delay may be extracted from a received signal, which may serve as input data for an AI / ML model or algorithm. For example, the DL-PRS power delay profile may be expressed as a 2D vector comprising of [Pr(p, r(] where I paths or cluster path may range from [0...L].
[0093] In one or more implementations, the DL-PRS PDP may include the raw DL-PRS PDP, which is generated using equation(l) and equation(2). This resulting DL-PRS provides an insight on the power-delay over a certain bandwidth and period of time. However, a full wideband PDP may have data overhead for transferring such information (e.g., in the case of UE-assisted and / or LMF- based positioning with LMF-side model, direct AI / ML positioning), where a UE or PRU UE may need to transfer such information to the LMF via LPP control plane or user plane signaling. This considers that the DL-PRS PDP is generated based on various factors.
[0094] The factors include a number of PDP profiles for each DL-PRS symbol r (resource element transmission), which depends on the DL-PRS configuration including comb-size, a number of symbols, RE offset, slot offset, and / or bandwidth in terms of PRB allocations. The PDP may also be generated based on multiple downlink subcarriers and multiple symbols within a slot, subframe, and / or frame. The PRB allocations defines the bandwidth for which the PDP is measured (e.g., up to 100 MHz for FR1 and up to 400 MHz for FR2). Factors may include over NTx-Rxantenna pairs. Other factors include based on a total number of NTPTPs (transmission points) given by a vector nTP=[EP(1), TP(2), TP(NTP) . Additionally, or alternatively, factors include a vector ofreference locations or ground truth locations given by Q = [1, ... , q]. In such an implementation, for simplicity, a 2D location (xi,yi) is given a label 1, a 2D location (X2,y2) is given a label 2, a 2D location (xq,yq) is given a label q, and so on. In other implementations, a 3D location may also be utilized within a given environment. In another implementation a combination of the TRP location and UE or PRU UE reference location may result in a unique location pair that may be associated with DL-based fingerprint.
[0095] A DL power delay profile is indicated below in Table (5) as a function of the various parameters detailed above. In different implementations one or more combinations of the parameters may be used to define the DL PDP, ADP, ASF, and / or DP measurements.Table (5): DL Power Delay Profile
[0096] With reference to the second described technique for DL-PRS fingerprint measurement and angular profile, a fingerprint measurement is generated based on an ADP (angle-delay domain) measurement or an ASF (power-angle domain) of a received DL-PRS signal at a target-UE or PRU UE. In other implementations, other reference signals may be used to derive a fingerprint measurement including SSB, CSLRS, PT-RS, DM-RS, TRS, etc. In an example implementation, the DL-PRS fingerprint may be derived based on multiple transmitted DL-PRS resources comprising one or more of positioning frequency layers (PFLs), transmission reception points (TRPs), a DL-PRS resource set, DL-PRS resources, or a combination thereof. This RF fingerprint represents a unique RF signature of the received DL-PRS at a given location.
[0097] Figure 8 illustrates an example 800 of a (P)RS received power-angle profile and angledelay profile as a signature, in accordance with aspects of the present disclosure. In one or more implementations, an ADP or an angle spectrum function (power-angle domain) measurement is generated based on a received DL-PRS signal at a target-UE or PRU UE, which has been transmitted from a gNB or TRP. It indicates the relative power (at 802) of different angle of arrivals of each multipath component or relative angle-of-arrival (AoAs) of the multipath components (at 804) arriving at different times and / or delays. These angles of arrivals may include azimuth angle of arrivals, or zenith and / or elevation angles at the UE or PRU UE. It is normally computed by performing by determining the phase and / or angle of the complex valued CIR, which is shown in the figure for a reference signal received with L paths or cluster paths received at each antenna element, where <pLis the PRS azimuth angle of arrival or elevation angle of arrival, Pr0, Prl, ... PrLis received average power at each angle of arrival, and the number of signal paths = [0,..., L].
[0098] The angular spectrum function in Figure 8 is then defined by equation(3):
[0099] Based on the discrete PDP in Figure 7, the root mean square (RMS) delay spread may be given as equation(4):where Pr(;) is the average received power of the Ithpath, pLis the AoA of the Ithpath, while themean AoA is given by <p = — - — — . The equation(3) could be used as characteristic of a unique Z!=1 Pr(I) fingerprint for a particular location, while equation(4) could be further used as a fingerprint characteristic to determine the mean angular spread.
[0100] According to an aspect of the techniques, a consolidated power delay profile comprising the received reference signal (RS) power and / or amplitude and delay may be extracted from a received signal, which may serve as input data for an AI / ML model or algorithm. For example, the DL-PRS angular spectrum function may be expressed as 2D vector comprising of [Pr(;)< Pi where 1 paths or cluster path may range from [0...L] at each Rx antenna element.
[0101] In one or more implementations, the DL-PRS ADP or an ASF (power-angle domain) measurement may include the raw DL-PRS ADP or ASF, which is generated using equation(3) and equation(4). This resulting received DL-PRS angular profile provides an insight on the angle-delay or power-angle spread over a certain bandwidth and period of time. However, a full wideband angle-delay or power-angle spread may have data overhead for transferring such information (e.g., in the case of UE-assisted or LMF-based positioning with LMF-side model, or direct AI / ML positioning), where a UE or PRU UE may need to transfer such information to the LMF via LPP control plane or user plane signaling (LCS-UPP). This considers that the DL-PRS ADP and / or ASF is generated based on various factors.
[0102] The factors include a number of angle-delay or power-angle spread profiles for each DL- PRS symbol r (resource element transmission), which depends on the DL-PRS configuration including comb-size, a number of symbols, a RE offset, a slot offset, and / or bandwidth in terms of PRB allocations. The PRB allocations defines the bandwidth for which the ADP and / or ASF is measured (e.g., up to 100 MHz for FR1 and up to 400 MHz for FR2). Factors may be over NTx-Rxantenna pairs, or based on a total number of NTPTPs (transmission points) given by a vector nTP= [TP(1), TP(2), , TP(NTpy]. Other factors include a vector of reference locations or ground truth locations given by Q = [1, ... , q]. In such an implementation, for simplicity, a 2D location (xi,yi) is given a label 1, a 2D location (X2,y2) is given a label 2, a 2D location (xq,yq) is given a label q, and so on. In other implementations, a 3D location may also be utilized within a given environment. Inanother implementation a combination of the TRP location and UE or PRU UE reference location may result in a unique location pair that may be associated with DL-based fingerprint.
[0103] A DL angular delay profile is indicated below in Table (6) as a function of the various parameters detailed above.Table (6): DL Angular Delay Profile
[0104] Figure 9 illustrates an example 900 of a (P)RS transmitted AoD profile as a signature, in accordance with aspects of the present disclosure. According to one aspect of the embodiment, an angular delay profile (ADP) or an angle spectrum function (power-angle domain) measurement is generated based on a transmitted DL-PRS signal at a gNB, TRP, PRU TRP, and / or reference TRP, which indicates the relative power of different angle of departures of each transmitted DL-PRSresource or relative angle-of-departure (AoDs) of the multipath components arriving at different times and / or delays. These angles of departures may include azimuth angle of departures, or zenith and / or elevation angles at the gNB, TRP, PRU TRP, and / or reference TRP, as shown in Figure 9.
[0105] With reference to the third described technique for DL-PRS fingerprint measurement and delay profile, a fingerprint measurement is generated based on a delay profile of the received DL-PRS signal at a target-UE or PRU UE. In other implementations, other reference signals may be used to derive a fingerprint measurement including SSB, CSLRS, PT-RS, DM-RS, TRS, etc. In an example implementation, the DL-PRS fingerprint may be derived based on multiple transmitted DL-PRS resources, including one or more of positioning frequency layers (PFLs), TRPs, a DL-PRS resource set, DL-PRS resources, or any combination thereof. This RF fingerprint represents a unique RF signature of the received DL-PRS at a given location.
[0106] Figure 10 illustrates an example (P)RS received delay profile 1000, in accordance with aspects of the present disclosure. According to an aspect of the techniques, a DP measurement is generated based on a received DL-PRS signal at a target UE or PRU UE, which has been transmitted from a gNB or TRP. It indicates the relative time-of-arrival (ToA) of each multipath component or describes the multipath components arriving at different times and / or delays. It is normally computed by determining the ToA of the complex valued CIR, which is shown for a reference signal received with L paths or cluster paths at each Rx antenna element.
[0107] According to an aspect of the techniques, a consolidated delay profile measurement comprising of the received reference signal (RS) multipath delay may be extracted from a received signal, which may serve as input data for an AI / ML model or algorithm. For example, the DL-PRS delay profile may be expressed as a ID vector comprising of ToAs of the received signal (T() where I paths or cluster path may range from [0...L] at each Rx antenna element.
[0108] In one or more implementations, the DL-PRS delay may include the raw DL-PRS delay profile. This resulting DL-PRS provides an insight on the delay of multipath over a certain bandwidth and period of time. However, a full wideband DP may incur overhead data for transferring such information (e.g., in the case of UE-assisted or LMF-based positioning with LMF- side model, or direct AI / ML positioning), where a UE or PRU UE may need to transfer such information to the LMF via LPP control plane or user plane signaling. This overhead is comparablyless than that of the CIR and PDP. This considers that the DL-PRS DP is generated based on various factors.
[0109] The factors can include a number of DP profiles for each DL-PRS symbol r (resource element transmission), which depends on the DL-PRS configuration including comb-size, number of symbols, a RE offset, a slot offset, and / or bandwidth in terms of PRB allocations. The PRB allocations defines the bandwidth for which the CIR is measured (e.g., up to 100 MHz for FR1 and up to 400 MHz for FR2). Factors may be over NTx-Rxantenna pairs, or based on a total number of NTPTPS (transmission points) given by a vector nTP= [TP(1), TP(2), , TP( / Vrp)]. Additionally, or alternatively, factors may include a vector of reference locations or ground truth locations given by Q = [1, ... , q]. In such an implementation, for simplicity, a 2D location (xi,yi) is given a label 1, a 2D location (X2,y2) is given a label 2, a 2D location (xq,yq) is given a label q, and so on. In other implementations, a 3D location may also be utilized within a given environment.
[0110] A DE delay profile is indicated below in Table (7) as a function of the various parameters detailed above.Table (7): DE Delay Profile
[0111] Aspects of the described techniques are directed to solutions for DE-based PDP, ADP, ASF, and / or DP measurement overhead reduction. Given that a DL-PRS configuration may includeat least a comb size {2, 4, 6 and 12} and at least a number of symbols including {2, 4, 6, and 12} in a given PRB, the DL-based channel profile reporting overhead may scale up considering the bandwidth requirements. According to an aspect of the techniques, a post-processing window is defined where a PDP, ADP, ASF, and / or DP processing window is defined and the CIR samples fall within the window duration are reported. In an implementation, the window may be static window, while in another implementation the window may be a rolling window over the total number of samples. The PDP, ADP, ASF, and / or DP window configuration may include a start sample, a length of samples, an end sample, or any combination thereof. The PDP, ADP, ASF, and / or DP window configuration may be periodic over a total sample length (i.e., multiple windows with a fixed sample spacing between each window). The averaging function of each of these profiles may be performed within the window defined by the configuration.
[0112] In other implementations, the PDP, ADP, ASF, and / or DP measurement window may be aperiodic with multiple windows configured with a variable sample apart from each other. The PDP, ADP, ASF, and / or DP window configuration including a start sample, a length of samples, and an end sample may be provided to the UE from the location server (e.g., LMF via LPP ProvideAssistanceData or RequestLocationlnformation, or equivalent signaling). In another implementation, the UE may self-determine the PDP, ADP, ASF, and / or DP measurement window configuration and then report this to the location server. In another implementation, such assistance data may also be signaled from LMF to a UE or device, or hardcoded in a UE or device, preconfigured based on certain validity criteria (e.g., area-based validity or time-based validity).
[0113] According to an aspect of the techniques, PDP and ASF samples are reported via configuration of a power threshold or power interval, Xi<a <X2, where a may be the power or normalized power, while Xi and X2 represent the lower and upper bounds of the thresholding criteria. The values, Xi, X2 may be provided to the UE from the location server (e.g., LMF via LPP ProvideAssistanceData or RequestLocationlnformation, or equivalent signaling). In another implementation, the UE may self-determine X / and X2 and then report this to the location server. In another implementation, such assistance data may also be signaled from LMF to a UE or device, or hardcoded in a UE or device, pre-configured based on certain validity criteria (e.g., area-based validity or time -based validity).
[0114] In another implementation, lower and upper angular thresholds may be defined to limit reporting ranges of the ADP and may be used in conjunction with the PDP, ADP, ASF, and / or DP window configuration. According to an implementation, the above-described PDP, ADP, ASF, and / or DP overhead reduction configurations may also be broadcast to multiple target users, UE, or PRU UEs within a cell using system information broadcast (SIB) or positioning system information broadcast (posSIB) messages. The applicable target UEs or PRU UEs may also request such configurations in an on-demand using the on-demand SIB framework.
[0115] In one or more implementations, the UE may be configured via network signaling (e.g., LPP) to provide a set of TRPs to be measured in order to reduce PDP, ADP, ASF, and / or DP overhead from a system perspective. The TRPs to be measured may be provided using an explicit or implicit prioritization criteria, implying that PDP, ADP, ASF, and / or DP measurements from higher TRP priority may be considered, while lower priority TRPs may be discarded. In an implementation, the network may determine so-called higher priority and lower priority TRPs and indicate this to the UE along with the assigned priorities to the TRPs. In another implementation, the higher priority and lower priority TRPs may be up to UE implementation. An explicit priority may be assigned along with the TRP ID or related identifying information and signaled to the UE via network signaling (e.g., LPP signaling, such as LPP ProvideAssistanceData or RequestLocationlnformation) in order to determine which PDP, ADP, ASF, and / or DP measurements originating from which TRP should be measured. An implicit priority may also be signaled to the UE, where the order of appearance may indicate which TRPs or TRP ID are to be measured (e.g., descending order of priority, i.e., first appearance in the TRP index or list has the highest priority, while last appearance in the TRP index or list has the lowest priority).Alternatively, ascending order of priority may be implemented, where first appearance in the TRP index or list has the lowest priority, while last appearance in the TRP index or list has the highest priority.
[0116] In one or more implementations, the quality of PDP, ADP, ASF, and / or DP measurements may be determined based on signal-noise-ratio (SNR), signal-to-interference-plus- noise ratio (SINR), timing quality, angle / phase quality, or other received signal quality metrics. The PDP, ADP, ASF, and / or DP measurements received from a certain TRP, that are deemed to have low SNR or SINR may be discarded, where the criteria for discarding samples may be based on aconfigured SNR or SINR threshold. This SNR or SINR threshold may be provided to the UE via network signaling (e.g., LPP signaling, such as LPP ProvideAssistanceData or RequestLocationlnformation).
[0117] In implementations, the network may determine and restrict the number of PDP, ADP, ASF, and / or DP measurements to be reported for a given fingerprint or signature based on the number of UEs actively performing PDP, ADP, ASF, and / or DP measurements within a given predefined area. The pre-defined area may be in the form of physical cell ID (PCI), NCGI ID, TRP ID, RAN area, tracking area, NR absolute radio frequency channel number (NRFCN) frequency list, or any combination thereof. This would control and manage the PDP, ADP, ASF, and / or DP measurement reporting overhead across a number of UEs, which may be more resource efficient from a system perspective at the potential cost of individual UE accuracy.
[0118] In an aspect of the techniques, general quality metrics may be associated to PDP, ADP, ASF, and / or DP measurements and may be reported to the location server from the UE using e.g., EPP ProvideLocationlnformation message along with the PDP, ADP, ASF, and / or DP measurements (e.g., SNR, SINR). These quality metrics can assist the positioning calculation entity to discard any so-called bad PDP, ADP, ASF, and / or DP measurements or PDP, ADP, ASF, and / or DP measurements samples. Additionally, or alternatively, and subject to UE capability, the UE or PRU UE may report DL-based PDP, ADP, ASF, and / or DP measurements along with quality metrics or sample resolution. Different sample resolutions may be supported by different UEs or PRU UEs based on UE capability.
[0119] Aspects of the described techniques are directed to time and frequency correlation information of a channel, where the maximum propagation delay in a multipath scenario between the first and the last arriving path above a certain threshold corresponds to a measure of the delay spread, where an inverse of the delay spread is related to the coherence BW of the corresponding channel. Assuming a multi-path propagation of a signal, the delay spread, tos, corresponds to a propagation delay difference between the first and last arriving dominant paths. The propagation delay difference, A tprop, can be mapped to a distance between the two path, dP, where dP= c.A tprop, A tprop= tDS, and c is the speed of light. For example, if a difference in distance cut between two paths is dP= 600 m., A tprop= 2qs, implying that the coherence bandwidth, Bc«— = 500kHz. Assuming a PMI subband size of 4 RBs with 30 kHz SCS, the BW of PMI tDS reporting, BWpM, = 1.44 MHz, which is larger than the coherence BW. Thereby, more synchronization correction between a base station and a UE is needed to capture the path information. The measured delay spread may be transmitted from the measuring device, UE, and / or PRU UE to the location server along with the above described one or more channel profile measurements using (e.g., LPP ProvideLocationlnformation message).
[0120] In the case of frequency synchronization, assume the CFO is 0.01 ppm, i.e., 0.01xl0-6x / c, the maximum offset across two TRPs is 10-8X 5 X 109= 50 Hz, assuming fc= 5GHz. The phase difference caused assuming a delay of 5ms for CSI reporting is 2n ft = 360 x 50 x 5 x l0-3= 90°. Considering the doppler component for a mobile UE, assuming that a UE is moving at 54 km / h, the Doppler shift becomes fD= -fc= 250Hz, leading to a total of 300Hz of frequency shift. The above-described time, frequency and doppler shift may affect the accuracy of the captured path delay profile characteristics. Note that in the case of time synchronization mismatch, various factors may be considered, such as local clock synchronization errors. While it is assumed that the synchronization between cells can be ensured via satellite positioning (e.g., GPS-based, synchronization errors vary from 10 ns to up to 1 / rs). Also hardware imperfections. Even if RRHs are synchronized via GPS, the signal transmission timeline can be impacted by hardware issues (e.g., transmission delay due to RF issues). Also, a propagation delay due to the different time propagation of signals from two non-co-located sources to the same destination.
[0121] In OFDM systems, a symbol over one sub-carrier incurs a frequency-flat channel as long as the delay spread is within the CP duration (as shown below in Table (8)). However, precoding resolution may need to be improved for channels with high delay spread (i.e., reduce PMI / CQI SB size, since the smallest precoding unit spans multiple sub-carriers). On the other hand, frequency synchronization mismatch can be caused by 2 factors, including CFO as a shift in carrier frequency at the RF front end compared with nominal carrier frequency, and Doppler shift caused by the relative motion of the receiver with respect to the transmitter(s). Unlike the delay spread, frequency shifted signals at the UE are more challenging to deal with and require complicated receiver architectures.Table (8): NR Numerology Illustrating SCS, Symbol and CP Durations
[0122] Figure 11 illustrates an example OFDM slot and RB grid in an enhanced TRS layout 1100, in accordance with aspects of the present disclosure. In one or more implementations, a technique to enable measurement of the time domain and frequency domain channel correlation is via a higher resolution RS. In order to enable such measurement, an enhanced TRS layout, or alternatively a new RS for temporal and / or frequency correlation measurement, can be implemented as shown in the figure. Note that under such design, different correlation scales can be captured, including small-scale correlation based on RSs over contiguous symbols / SCs, medium scale correlation based on RSs over non-contiguous symbols / SCs per slot or RB, and large-scale correlation based on measurement over RSs across slots or RBs. The proposed RS may be configured per BWP and can be limited to a subset of consecutive RBs of the BWP, and may span only a number of consecutive slots for each transmission occasion.
[0123] Note that a higher temporal and / or frequency correlation resolution may be captured via phase tracking, where the phase evolution is based on a sinusoidal factor corresponding to cos(2?r / t), where / , t correspond to frequency and time values, respectively. In a first example, a frequency drift is measured based on a phase drift between a received RS at symbol n+1, SC k+1 with respect to the received RS at symbol n, SC k, where the frequency drift is based on a predetermined time sample index (e.g., at the midpoint of a symbol, i.e., the value of / can be inferred from the measured phase drift and At). In a second example, a time drift is measured based on aphase drift between a received RS at symbol n+1, SC k+1 with respect to the received RS at symbol n, SC k, where the time drift is based on a pre-determined frequency sample index (e.g., at the midpoint of a SC value, i.e., the value of t can be inferred from the measured phase drift and A ). According to implementations, the measurement of TRS may also serve as input data to enable direct AI / ML positioning (e.g., fingerprinting). This measurement is designed to capture, small- scale, medium-scale, and large-scale channel correlations across time and frequency, which could contribute as valuable information when constructing the multidimensional fingerprint.
[0124] Figure 12 illustrates an example of a UE 1200 in accordance with aspects of the present disclosure. The UE 1200 may include a processor 1202, a memory 1204, a controller 1206, and a transceiver 1208. The processor 1202, the memory 1204, the controller 1206, or the transceiver 1208, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. These components may be coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces.
[0125] The processor 1202, the memory 1204, the controller 1206, or the transceiver 1208, or various combinations or components thereof may be implemented in hardware (e.g., circuitry). The hardware may include a processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or other programmable logic device, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure.
[0126] The processor 1202 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, an ASIC, an FPGA, or any combination thereof). In some implementations, the processor 1202 may be configured to operate the memory 1204. In some other implementations, the memory 1204 may be integrated into the processor 1202. The processor 1202 may be configured to execute computer-readable instructions stored in the memory 1204 to cause the UE 1200 to perform various functions of the present disclosure.
[0127] The memory 1204 may include volatile or non-volatile memory. The memory 1204 may store computer-readable, computer-executable code including instructions when executed by the processor 1202 cause the UE 1200 to perform various functions described herein. The code may bestored in a non-transitory computer-readable medium such as the memory 1204 or another type of memory. Computer-readable media includes both non-transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer.
[0128] In some implementations, the processor 1202 and the memory 1204 coupled with the processor 1202 may be configured to cause the UE 1200 to perform one or more of the functions described herein (e.g., executing, by the processor 1202, instructions stored in the memory 1204). For example, the processor 1202 may support wireless communication at the UE 1200 in accordance with examples as disclosed herein. The UE 1200 may be configured to or operable to support a means for receiving, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; and transmitting, to the positioning equipment for a positioning estimation, the one or more downlink channel sample -based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
[0129] Additionally, the UE 1200 may be configured to support any one or combination of the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured. The one or more downlink channel sample-based measurement profile measurements are associated with one or more channel profiles comprising one or more of a PDP, an ADP, an ASF, or a DP. The method further comprising performing the one or more downlink channel sample -based measurement profile measurements on the reference signal based at least in part on a capability of the UE to perform the one or more downlink channel sample-based measurement profile measurements. The one or more downlink channel sample -based measurement profile measurements are input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation. The input data is usable to train the machine learning model to determine the positioning estimation. The UE is configured as a PRU UE that has a known location. The positioning equipment is at least one of a location server, a LMF, an additional UE, or a PRU UE. The reference signal is at least one of a DL-PRS, a SSB, a CSI-RS, a DM-RS, a TRS, or a PT-RS. The configuration parameters of the measurement configuration to conduct the one or more downlink channel sample-based measurement profilemeasurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths. The method further comprising maintaining the one or more downlink channel sample-based measurement profile measurements as one or more of a ID, a 2D, a 3D, or a multi-dimensional signature or fingerprint vector that represents a known location of a TRP. The one or more downlink channel sample -based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal. The one or more downlink channel sample-based measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length. The method further comprising reporting the one or more downlink channel sample-based measurement profile measurements as a configuration of at least one of a power threshold or a power interval. A number of the one or more downlink channel sample-based measurement profile measurements to be conducted is reduced based at least in part on one or more of a prioritization of TRPs to be measured, one or more quality metrics of a channel profile, or a number of additional UEs reporting the one or more downlink channel sample-based measurement profile measurements. The method further comprising transmitting at least one of the one or more downlink channel sample -based measurement profile measurements and associated one or more measurement quality metrics. To conduct the one or more downlink channel sample-based measurement profile measurements on the reference signal, configuration parameters of the measurement configuration include an indication of one or more of a channel delay spread, frequency synchronization parameters comprising carrier phase offset or Doppler shift, or time synchronization parameters comprising transmitter or receiver time offsets.
[0130] Additionally, or alternatively, the UE 1200 may support at least one memory (e.g., the memory 1204) and at least one processor (e.g., the processor 1202) coupled with the at least one memory and configured to cause the UE to receive, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; and transmit, to the positioning equipment for a positioning estimation, the one or more downlink channel sample -based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
[0131] Additionally, the UE 1200 may be configured to support any one or combination of the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured. The one or more downlink channel sample-based measurement profile measurements are associated with one or more channel profiles comprising one or more of a PDP, an ADP, an ASF, or a DP. The at least one processor is configured to cause the UE to perform the one or more downlink channel sample-based measurement profile measurements on the reference signal based at least in part on a capability of the UE to perform the one or more downlink channel sample -based measurement profile measurements. The one or more downlink channel sample-based measurement profile measurements are input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation. The input data is usable to train the machine learning model to determine the positioning estimation. The UE is configured as a PRU UE that has a known location. The positioning equipment is at least one of a location server, a LMF, an additional UE, or a PRU UE. The reference signal is at least one of a DL-PRS, a SSB, a CSI-RS, a DM-RS, a TRS, or a PT-RS. The configuration parameters of the measurement configuration to conduct the one or more downlink channel sample-based measurement profile measurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths. The at least one processor is configured to cause the UE to maintain the one or more downlink channel sample -based measurement profile measurements as one or more of a ID, a 2D, a 3D, or a multi-dimensional signature or fingerprint vector that represents a known location of a TRP. The one or more downlink channel sample-based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal. The one or more downlink channel samplebased measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length. The at least one processor is configured to cause the UE to report the one or more downlink channel sample-based measurement profile measurements as a configuration of at least one of a power threshold or a power interval. A number of the one or more downlink channel sample -based measurement profile measurements to be conducted is reduced based at least in part on one or more of a prioritization of TRPs to be measured, one or more quality metrics of a channel profile, or anumber of additional UEs reporting the one or more downlink channel sample-based measurement profile measurements. The at least one processor is configured to cause the UE to transmit at least one of the one or more downlink channel sample-based measurement profile measurements and associated one or more measurement quality metrics. To conduct the one or more downlink channel sample-based measurement profile measurements on the reference signal, configuration parameters of the measurement configuration include an indication of one or more of a channel delay spread, frequency synchronization parameters comprising carrier phase offset or Doppler shift, or time synchronization parameters comprising transmitter or receiver time offsets.
[0132] The controller 1206 may manage input and output signals for the UE 1200. The controller 1206 may also manage peripherals not integrated into the UE 1200. In some implementations, the controller 1206 may utilize an operating system such as iOS®, ANDROID®, WINDOWS®, or other operating systems. In some implementations, the controller 1206 may be implemented as part of the processor 1202.
[0133] In some implementations, the UE 1200 may include at least one transceiver 1208. In some other implementations, the UE 1200 may have more than one transceiver 1208. The transceiver 1208 may represent a wireless transceiver. The transceiver 1208 may include one or more receiver chains 1210, one or more transmitter chains 1212, or a combination thereof.
[0134] A receiver chain 1210 may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receiver chain 1210 may include one or more antennas to receive a signal over the air or wireless medium. The receiver chain 1210 may include at least one amplifier (e.g., a low-noise amplifier (LNA)) configured to amplify the received signal. The receiver chain 1210 may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receiver chain 1210 may include at least one decoder for decoding the demodulated signal to receive the transmitted data.
[0135] A transmitter chain 1212 may be configured to generate and transmit signals(e.g., control information, data, packets). The transmitter chain 1212 may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniquessuch as amplitude modulation (AM), frequency modulation (FM), or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM). The transmitter chain 1212 may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmitter chain 1212 may also include one or more antennas for transmitting the amplified signal into the air or wireless medium.
[0136] Figure 13 illustrates an example of a processor 1300 in accordance with aspects of the present disclosure. The processor 1300 may be an example of a processor configured to perform various operations in accordance with examples as described herein. The processor 1300 may include a controller 1302 configured to perform various operations in accordance with examples as described herein. The processor 1300 may optionally include at least one memory 1304, which may be, for example, an L1 / L2 / L3 cache. Additionally, or alternatively, the processor 1300 may optionally include one or more arithmetic-logic units (ALUs) 1306. One or more of these components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses).
[0137] The processor 1300 may be a processor chipset and include a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) in accordance with examples as described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to or included in the processor chipset (e.g., the processor 1300) or other memory (e.g., random access memory (RAM), read-only memory (ROM), dynamic RAM (DRAM), synchronous dynamic RAM (SDRAM), static RAM (SRAM), ferroelectric RAM (FeRAM), magnetic RAM (MRAM), resistive RAM (RRAM), flash memory, phase change memory (PCM), and others).
[0138] The controller 1302 may be configured to manage and coordinate various operations (e.g., signaling, receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) of the processor 1300 to cause the processor 1300 to support various operations in accordance with examples as described herein. For example, the controller 1302 may operate as a control unit of the processor 1300, generating control signals that manage the operation of various components of the processor 1300. These control signalsinclude enabling or disabling functional units, selecting data paths, initiating memory access, and coordinating timing of operations.
[0139] The controller 1302 may be configured to fetch (e.g., obtain, retrieve, receive) instructions from the memory 1304 and determine subsequent instruction(s) to be executed to cause the processor 1300 to support various operations in accordance with examples as described herein. The controller 1302 may be configured to track memory addresses of instructions associated with the memory 1304. The controller 1302 may be configured to decode instructions to determine the operation to be performed and the operands involved. For example, the controller 1302 may be configured to interpret the instruction and determine control signals to be output to other components of the processor 1300 to cause the processor 1300 to support various operations in accordance with examples as described herein. Additionally, or alternatively, the controller 1302 may be configured to manage flow of data within the processor 1300. The controller 1302 may be configured to control transfer of data between registers, ALUs 1306, and other functional units of the processor 1300.
[0140] The memory 1304 may include one or more caches (e.g., memory local to or included in the processor 1300 or other memory, such as RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc. In some implementations, the memory 1304 may reside within or on a processor chipset (e.g., local to the processor 1300). In some other implementations, the memory 1304 may reside external to the processor chipset (e.g., remote to the processor 1300).
[0141] The memory 1304 may store computer-readable, computer-executable code including instructions that, when executed by the processor 1300, cause the processor 1300 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. The controller 1302 and / or the processor 1300 may be configured to execute computer-readable instructions stored in the memory 1304 to cause the processor 1300 to perform various functions. For example, the processor 1300 and / or the controller 1302 may be coupled with or to the memory 1304, the processor 1300, and the controller 1302, and may be configured to perform various functions described herein. In some examples, the processor 1300 may include multiple processors and the memory 1304 may include multiple memories. One or more of the multiple processors may be coupled with one or more of the multiplememories, which may, individually or collectively, be configured to perform various functions herein.
[0142] The one or more ALUs 1306 may be configured to support various operations in accordance with examples as described herein. In some implementations, the one or more ALUs 1306 may reside within or on a processor chipset (e.g., the processor 1300). In some other implementations, the one or more ALUs 1306 may reside external to the processor chipset (e.g., the processor 1300). One or more ALUs 1306 may perform one or more computations such as addition, subtraction, multiplication, and division on data. For example, one or more ALUs 1306 may receive input operands and an operation code, which determines an operation to be executed. One or more ALUs 1306 may be configured with a variety of logical and arithmetic circuits, including adders, subtractors, shifters, and logic gates, to process and manipulate the data according to the operation. Additionally, or alternatively, the one or more ALUs 1306 may support logical operations such as AND, OR, exclusive-OR (XOR), not-OR (NOR), and not-AND (NAND), enabling the one or more ALUs 1306 to handle conditional operations, comparisons, and bitwise operations.
[0143] The processor 1300 may support wireless communication in accordance with examples as disclosed herein. The processor 1300 may be configured to or operable to support at least one controller (e.g., the controller 1302) coupled with at least one memory (e.g., the memory 1304) and configured to cause the processor to receive, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; and transmit, to the positioning equipment for a positioning estimation, the one or more downlink channel sample -based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
[0144] Additionally, the processor 1300 may be configured to or operable to support any one or combination of the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured. The one or more downlink channel samplebased measurement profile measurements are associated with one or more channel profiles comprising one or more of a PDP, an ADP, an ASF, or a DP. The one or more downlink channel sample-based measurement profile measurements are input data to a machine learning model that determines a location of a UE based at least in part on the positioning estimation. The input data is usable to train the machine learning model to determine the positioning estimation. The positioningequipment is at least one of a location server, a LMF, a UE, or a PRU UE. The reference signal is at least one of a DL-PRS, a SSB, a CSI-RS, a DM-RS, a TRS, or a PT-RS. The configuration parameters of the measurement configuration to conduct the one or more downlink channel samplebased measurement profile measurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths. The at least one controller is configured to cause the processor to maintain the one or more downlink channel sample-based measurement profile measurements as one or more of a ID, a 2D, a 3D, or a multi-dimensional signature or fingerprint vector that represents a known location of a TRP. The one or more downlink channel sample-based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal. The one or more downlink channel samplebased measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length. The at least one controller is configured to cause the processor to report the one or more downlink channel sample-based measurement profile measurements as a configuration of at least one of a power threshold or a power interval. A number of the one or more downlink channel sample-based measurement profile measurements to be conducted is reduced based at least in part on one or more of a prioritization of TRPs to be measured, one or more quality metrics of a channel profile, or a number of additional UEs reporting the one or more downlink channel sample-based measurement profile measurements. The at least one controller is configured to cause the processor to transmit at least one of the one or more downlink channel sample -based measurement profile measurements and associated one or more measurement quality metrics. To conduct the one or more downlink channel sample-based measurement profile measurements on the reference signal, configuration parameters of the measurement configuration include an indication of one or more of a channel delay spread, frequency synchronization parameters comprising carrier phase offset or Doppler shift, or time synchronization parameters comprising transmitter or receiver time offsets.
[0145] Figure 14 illustrates an example of a positioning equipment 1400 in accordance with aspects of the present disclosure. In one or more implementations, the positioning equipment 900 may be implemented by one or more NE 102. The positioning equipment 1400 may include aprocessor 1402, a memory 1404, a controller 1406, and a transceiver 1408. The processor 1402, the memory 1404, the controller 1406, or the transceiver 1408, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. These components may be coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces.
[0146] The processor 1402, the memory 1404, the controller 1406, or the transceiver 1408, or various combinations or components thereof may be implemented in hardware (e.g., circuitry). The hardware may include a processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or other programmable logic device, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure.
[0147] The processor 1402 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, an ASIC, an FPGA, or any combination thereof). In some implementations, the processor 1402 may be configured to operate the memory 1404. In some other implementations, the memory 1404 may be integrated into the processor 1402. The processor 1402 may be configured to execute computer-readable instructions stored in the memory 1404 to cause the positioning equipment 1400 to perform various functions of the present disclosure.
[0148] The memory 1404 may include volatile or non-volatile memory. The memory 1404 may store computer-readable, computer-executable code including instructions when executed by the processor 1402 cause the positioning equipment 1400 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as the memory 1404 or another type of memory. Computer-readable media includes both non-transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer.
[0149] In some implementations, the processor 1402 and the memory 1404 coupled with the processor 1402 may be configured to cause the positioning equipment 1400 to perform one or more of the functions described herein (e.g., executing, by the processor 1402, instructions stored in the memory 1404). For example, the processor 1402 may support wireless communication at thepositioning equipment 1400 in accordance with examples as disclosed herein. The positioning equipment 1400 may be configured to or operable to support a means transmitting, to a UE, a measurement configuration to conduct one or more downlink channel sample -based measurement profile measurements on a reference signal; receiving, from the UE, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration; performing a positioning estimation based at least in part on the one or more downlink channel sample-based measurement profile measurements; and determining a location of the UE based at least in part on the positioning estimation.
[0150] Additionally, the positioning equipment 1400 may be configured to or operable to support any one or combination of the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured. The one or more downlink channel sample-based measurement profile measurements are associated with one or more channel profiles comprising one or more of a PDP, an ADP, an ASF, or a DP. The method further comprising using the one or more downlink channel sample-based measurement profile measurements as input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation. The method further comprising using the input data to train the machine learning model to determine the positioning estimation. The positioning equipment is at least one of a location server, a LMF, an additional UE, or a PRU UE. The reference signal is at least one of a DL-PRS, a SSB, a CSI-RS, a DM-RS, a TRS, or a PT-RS. The configuration parameters of the measurement configuration to conduct the one or more downlink channel sample-based measurement profile measurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths. The one or more downlink channel sample-based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal. The one or more downlink channel sample-based measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length.
[0151] Additionally, or alternatively, the positioning equipment 1400 may support at least one memory (e.g., the memory 1404) and at least one processor (e.g., the processor 1402) coupled withthe at least one memory and configured to cause the positioning equipment to transmit, to a UE, a measurement configuration to conduct one or more downlink channel sample -based measurement profile measurements on a reference signal; receive, from the UE, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration; perform a positioning estimation based at least in part on the one or more downlink channel sample-based measurement profile measurements; and determine a location of the UE based at least in part on the positioning estimation.
[0152] Additionally, the positioning equipment 1400 may be configured to support any one or combination of the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured. The one or more downlink channel samplebased measurement profile measurements are associated with one or more channel profiles comprising one or more of a PDP, an ADP, an ASF, or a DP. The at least one processor is configured to cause the positioning equipment to use the one or more downlink channel samplebased measurement profile measurements as input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation. The at least one processor is configured to cause the positioning equipment to use the input data to train the machine learning model to determine the positioning estimation. The positioning equipment is at least one of a location server, a LMF, an additional UE, or a PRU UE. The reference signal is at least one of a DL-PRS, a SSB, a CSI-RS, a DM-RS, a TRS, or a PT-RS. The configuration parameters of the measurement configuration to conduct the one or more downlink channel sample-based measurement profile measurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths. The one or more downlink channel sample -based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal. The one or more downlink channel samplebased measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length.
[0153] The controller 1406 may manage input and output signals for the positioning equipment 1400. The controller 1406 may also manage peripherals not integrated into the positioningequipment 1400. In some implementations, the controller 1406 may utilize an operating system such as iOS®, ANDROID®, WINDOWS®, or other operating systems. In some implementations, the controller 1406 may be implemented as part of the processor 1402.
[0154] In some implementations, the positioning equipment 1400 may include at least one transceiver 1408. In some other implementations, the positioning equipment 1400 may have more than one transceiver 1408. The transceiver 1408 may represent a wireless transceiver. The transceiver 1408 may include one or more receiver chains 1410, one or more transmitter chains 1412, or a combination thereof.
[0155] A receiver chain 1410 may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receiver chain 1410 may include one or more antennas to receive a signal over the air or wireless medium. The receiver chain 1410 may include at least one amplifier (e.g., a low-noise amplifier (LNA)) configured to amplify the received signal. The receiver chain 1410 may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receiver chain 1410 may include at least one decoder for decoding the demodulated signal to receive the transmitted data.
[0156] A transmitter chain 1412 may be configured to generate and transmit signals(e.g., control information, data, packets). The transmitter chain 1412 may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM), frequency modulation (FM), or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM). The transmitter chain 1412 may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmitter chain 1412 may also include one or more antennas for transmitting the amplified signal into the air or wireless medium.
[0157] Figure 15 illustrates a flowchart of a method 1500 in accordance with aspects of the present disclosure. The operations of the method may be implemented by a UE as described herein. In some implementations, the UE may execute a set of instructions to control the function elementsof the UE to perform the described functions. It should be noted that the method described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.
[0158] At 1502, the method may include receiving, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample -based measurement profile measurements on a reference signal. The operations of 1502 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1502 may be performed by a UE as described with reference to Figure 12.
[0159] At 1504, the method may include transmitting, to the positioning equipment for a positioning estimation, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration. The operations of 1504 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1504 may be performed by a UE as described with reference to Figure 12.
[0160] Figure 16 illustrates a flowchart of a method 1600 in accordance with aspects of the present disclosure. The operations of the method may be implemented by a positioning equipment as described herein. In some implementations, the positioning equipment may execute a set of instructions to control the function elements of the positioning equipment to perform the described functions. It should be noted that the method described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.
[0161] At 1602, the method may include transmitting, to a UE, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal. The operations of 1602 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1602 may be performed by a positioning equipment as described with reference to Figure 14.
[0162] At 1604, the method may include receiving, from the UE, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration. The operations of 1604 may be performed inaccordance with examples as described herein. In some implementations, aspects of the operations of 1604 may be performed by a positioning equipment as described with reference to Figure 14.
[0163] At 1606, the method may include performing a positioning estimation based at least in part on the one or more downlink channel sample-based measurement profile measurements. The operations of 1606 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1606 may be performed a positioning equipment as described with reference to Figure 14.
[0164] At 1608, the method may include determining a location of the UE based at least in part on the positioning estimation. The operations of 1608 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1608 may be performed a positioning equipment as described with reference to Figure 14.
[0165] The description herein is provided to enable a person having ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to a person having ordinary skill in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.
Claims
CLAIMSWhat is claimed is:
1. A user equipment (UE) for wireless communication, comprising: at least one memory; and at least one processor coupled with the at least one memory and operable to cause the UE to: receive, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample -based measurement profile measurements on a reference signal; and transmit, to the positioning equipment for a positioning estimation, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
2. The UE of claim 1 , wherein the measurement configuration indicates one or more types of downlink channel sample -based measurement profiles to be measured.
3. The UE of claim 1, wherein the one or more downlink channel sample-based measurement profile measurements are associated with one or more channel profiles comprising one or more of a power delay profile (PDP), an angular delay profile (ADP), an angle spectrum function (ASF), or a delay profile (DP).
4. The UE of claim 1 , wherein the at least one processor is operable to cause the UE to perform the one or more downlink channel sample-based measurement profile measurements on the reference signal based at least in part on a capability of the UE to perform the one or more downlink channel sample-based measurement profile measurements.
5. The UE of claim 1, wherein the one or more downlink channel sample-based measurement profile measurements are input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation, and wherein the input data is usable to train the machine learning model to determine the positioning estimation.
6. The UE of claim 1, wherein: the UE is configured as a positioning reference unit (PRU) UE that has a known location; and the positioning equipment is at least one of a location server, a location management function (LMF), an additional UE, or a positioning reference unit (PRU) UE.
7. The UE of claim 1, wherein the reference signal is at least one of a downlink positioning reference signal (DL-PRS), a synchronization signal block (SSB), a channel state information reference signal (CSI-RS), a demodulation reference signal (DM-RS), a tracking reference signal (TRS), or a phase tracking reference signal (PT-RS).
8. The UE of claim 1, wherein configuration parameters of the measurement configuration to conduct the one or more downlink channel sample-based measurement profile measurements comprises one or more of power-delay parameters, a start sample, a length of samples, a number of samples, a sampling resolution, an end sample, or time of arrival of multiple received signal paths.
9. The UE of claim 1, wherein the at least one processor is operable to cause the UE to maintain the one or more downlink channel sample-based measurement profile measurements as one or more of a one-dimensional (ID), a two-dimensional (2D), a three-dimensional (3D), or a multi-dimensional signature or fingerprint vector that represents a known location of a transmission-reception point (TRP).
10. The UE of claim 1, wherein the one or more downlink channel sample-based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal.
11. The UE of claim 1 , wherein the one or more downlink channel sample-based measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length.
12. The UE of claim 1, wherein the at least one processor is operable to cause the UE to report the one or more downlink channel sample -based measurement profile measurements as a configuration of at least one of a power threshold or a power interval.
13. A method performed by a user equipment (UE), the method comprising: receiving, from a positioning equipment, a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; and transmitting, to the positioning equipment for a positioning estimation, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration.
14. A positioning equipment for wireless communication, comprising: at least one memory; and at least one processor coupled with the at least one memory and operable to cause the positioning equipment to: transmit, to a user equipment (UE), a measurement configuration to conduct one or more downlink channel sample -based measurement profile measurements on a reference signal; receive, from the UE, the one or more downlink channel sample-based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration; perform a positioning estimation based at least in part on the one or more downlink channel sample -based measurement profile measurements; and determine a location of the UE based at least in part on the positioning estimation.
15. The positioning equipment of claim 14, wherein the measurement configuration indicates one or more types of downlink channel sample-based measurement profiles to be measured.
16. The positioning equipment of claim 14, wherein the one or more downlink channel sample-based measurement profile measurements are associated with one or more channel profiles comprising one or more of a power delay profile (PDP), an angular delay profile (ADP), an angle spectrum function (ASF), or a delay profile (DP).
17. The positioning equipment of claim 14, wherein the at least one processor is operable to cause the positioning equipment to: use the one or more downlink channel sample-based measurement profile measurements as input data to a machine learning model that determines a location of the UE based at least in part on the positioning estimation; and use the input data to train the machine learning model to determine the positioning estimation.
18. The positioning equipment of claim 14, wherein: the positioning equipment is at least one of a location server, a location management function (LMF), an additional UE, or a positioning reference unit (PRU) UE; and the reference signal is at least one of a downlink positioning reference signal (DL-PRS), a synchronization signal block (SSB), a channel state information reference signal (CSI-RS), a demodulation reference signal (DM-RS), a tracking reference signal (TRS), or a phase tracking reference signal (PT-RS).
19. The positioning equipment of claim 14, wherein: the one or more downlink channel sample-based measurement profile measurements include channel profile measurement information determined over a configured bandwidth of the reference signal; and the one or more downlink channel sample-based measurement profile measurements are performed within a defined measurement time duration that includes one or more of a start time, a periodicity, an end time, a start sample, a length of samples, an end sample, a power threshold, a power threshold interval, or a time duration length.
20. A method performed by a positioning equipment, the method comprising: transmitting, to a user equipment (UE), a measurement configuration to conduct one or more downlink channel sample-based measurement profile measurements on a reference signal; receiving, from the UE, the one or more downlink channel sample -based measurement profile measurements performed on the reference signal based at least in part on the measurement configuration; performing a positioning estimation based at least in part on the one or more downlink channel sample-based measurement profile measurements; and determining a location of the UE based at least in part on the positioning estimation.
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