Real-time navigation route assisted positioning engine

Abstract

Aspects presented herein may enable a navigation application of a UE to feed calculated navigation route information of the navigation application to a PE of the UE to assist the PE in calculating a positioning estimate to improve positioning accuracy. In one aspect, a UE estimates a current location of the UE using a positioning engine based on a set of positioning measurements and a set of temporal update predictions. The UE calculates real-time navigation route information using at least one navigation application based on the current location of the UE, a destination of the UE, and map information. The UE changes or verifies a set of positioning estimates performed by the positioning engine based on the real-time navigation route information from the at least one navigation application.

Description

[0001] Cross - Reference to Related Applications

[0002] This application claims the benefit of U.S. Non - Provisional Patent Application Serial No. 18 / 063,435, filed on December 8, 2022, entitled "REAL - TIME NAVIGATION ROUTEAIDING POSITIONING ENGINE", which is hereby incorporated by reference in its entirety. Field of the Invention

[0003] The present disclosure generally relates to communication systems and, more particularly, to wireless communication regarding positioning. Background Art

[0004] Wireless communication systems are widely deployed to provide various telecommunication services such as telephony, video, data, messaging, and broadcasting. A typical wireless communication system may employ multiple access technologies capable of supporting communication with multiple users by sharing available system resources. Examples of such multiple access technologies include Code Division Multiple Access (CDMA) systems, Time Division Multiple Access (TDMA) systems, Frequency Division Multiple Access (FDMA) systems, Orthogonal Frequency Division Multiple Access (OFDMA) systems, Single - Carrier Frequency Division Multiple Access (SC - FDMA) systems, and Time - Division Synchronous Code Division Multiple Access (TD - SCDMA) systems.

[0005] These multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different wireless devices to communicate at the urban, national, regional, and even global levels. An example telecommunication standard is 5G New Radio (NR). 5G NR is part of the ongoing evolution of mobile broadband promulgated by the Third Generation Partnership Project (3GPP) to meet new requirements associated with latency, reliability, security, scalability (e.g., related to the Internet of Things (IoT)), and other requirements. 5G NR includes services associated with enhanced mobile broadband (eMBB), massive machine - type communication (mMTC), and ultra - reliable low - latency communication (URLLC). Certain aspects of 5G NR may be based on the 4G Long - Term Evolution (LTE) standard. Further improvements to 5G NR technology are needed. These improvements may also be applicable to other multiple access technologies and telecommunication standards that employ these technologies. Summary of the Invention

[0006] A simplified overview of one or more aspects is presented below to provide a basic understanding of these aspects. This summary is not an extensive review of all contemplated aspects. The summary neither identifies key or critical elements of all aspects nor describes the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.

[0007] In one aspect of the present disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus uses a positioning engine to estimate the current location of a user equipment (UE) based on a set of positioning measurements and a set of time update predictions. The apparatus uses at least one navigation application to calculate real-time navigation route information based on the current location of the UE, the destination of the UE, and map information. The apparatus changes or validates the set of positioning estimates performed by the positioning engine based on the real-time navigation route information from the at least one navigation application.

[0008] To achieve the foregoing and related purposes, one or more aspects may include the features described in detail hereinafter and particularly pointed out in the claims. The following description and the drawings set forth in detail some exemplary features of one or more aspects. However, these features indicate only some of the various ways in which the principles of the various aspects may be employed. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a diagram illustrating an example of a wireless communication system and an access network.

[0010] Figure 2A is a diagram illustrating an example of a first frame according to various aspects of the present disclosure.

[0011] Figure 2B is a diagram illustrating an example of a downlink (DL) channel within a subframe according to various aspects of the present disclosure.

[0012] Figure 2C is a diagram illustrating an example of a second frame according to various aspects of the present disclosure.

[0013] Figure 2D is a diagram illustrating an example of an uplink (UL) channel within a subframe according to various aspects of the present disclosure.

[0014] Figure 3 is a diagram illustrating an example of a base station and a user equipment (UE) in an access network.

[0015] Figure 4 is a diagram illustrating an example of UE positioning based on reference signal measurements.

[0016] Figure 5 is a diagram illustrating an example of global navigation satellite system (GNSS) positioning according to various aspects of the present disclosure.

[0017] Figure 6 is a diagram illustrating an example of a navigation application according to various aspects of the present disclosure.

[0018] Figure 7 is a diagram illustrating an example of a navigation application according to various aspects of the present disclosure.

[0019] Figure 8 is a diagram illustrating an example closed-loop configuration for a positioning engine and a navigation application in accordance with various aspects of the present disclosure.

[0020] Figure 9 is a flowchart illustrating an example algorithm that enables a UE to switch between an open-loop configuration and a closed-loop configuration in accordance with various aspects of the present disclosure.

[0021] Figure 10 is a diagram illustrating an example accuracy comparison between an open-loop configuration and a closed-loop configuration in accordance with various aspects of the present disclosure.

[0022] Figure 11 is a flowchart of a method of wireless communication.

[0023] Figure 12 is a flowchart of a method of wireless communication.

[0024] Figure 13 is a diagram illustrating an example of a hardware implementation for a device or a network entity. Detailed Description

[0025] Aspects presented herein can improve the performance and accuracy of a positioning engine (PE) by configuring the positioning engine to receive feedback from a navigation application. For example, in one aspect of the present disclosure, the navigation application can feed the computed navigation route information of the navigation application to the positioning engine (PE) to assist the PE in calculating a positioning estimate based on a Kalman filter (KF) process / algorithm. These positioning estimates can then be used by the navigation application to calculate future navigation route information or update the navigation route information (e.g., for performing a KF time update and a KF measurement update associated with the KF process / algorithm). This process / call flow can continue to repeat between the PE and the navigation application to create a closed-loop configuration / solution. In some examples, for the KF time update, the navigation route information can be used as a more accurate dynamic model, and for the KF measurement update, the navigation route information can be used for measurement outlier detection (e.g., for detecting incorrect measurements or measurements that exceed an error threshold).

[0026] The detailed description set forth below in connection with the appended drawings is a description of various configurations and is not intended to represent the only configurations in which the concepts described herein can be practiced. For the purpose of providing a thorough understanding of the various concepts, the detailed description includes specific details. However, the concepts may be practiced without these specific details. In some instances, well-known structures and components are shown in block diagram form to avoid obscuring such concepts.

[0027] Certain aspects of a telecommunications system are presented with reference to various apparatus and methods. These apparatus and methods are described in the following detailed description, and illustrated in the accompanying drawings by various blocks, components, circuits, processes, algorithms, etc. (collectively referred to as "elements"). The elements can be implemented using electronic hardware, computer software, or any combination thereof. Whether an element is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system.

[0028] By way of example, an element, or any portion of an element, or any combination of elements can be implemented as a "processing system" that includes one or more processors. Examples of processors include a microprocessor, a microcontroller, a graphics processing unit (GPU), a central processing unit (CPU), an application processor, a digital signal processor (DSP), a reduced instruction set computing (RISC) processor, a system on a chip (SoC), a baseband processor, a field programmable gate array (FPGA), a programmable logic device (PLD), a state machine, gated logic, discrete hardware circuits, and other suitable hardware configured to perform the various functions described throughout this disclosure. The one or more processors in the processing system can execute software. Software should be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software components, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, or any combination thereof, regardless of whether it is referred to as software, firmware, middleware, microcode, hardware description language, or other terms.

[0029] Thus, in one or more example aspects, embodiments, and / or use cases, the described functionality can be implemented in hardware, software, or any combination thereof. If implemented in software, the functionality can be stored or encoded on a computer-readable medium as one or more instructions or code. Computer-readable media includes computer storage media. Storage media can be any available media that can be accessed by a computer. By way of example, such computer-readable media can include random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of these types of computer-readable media, or any other media that can be used to store computer-executable code in the form of instructions or data structures that can be accessed by a computer.

[0030] Although aspects, embodiments, and / or use cases are described by way of some examples in this application, additional or different aspects, embodiments, and / or use cases may arise in many different arrangements and scenarios. The aspects, embodiments, and / or use cases described herein may be implemented across many different platform types, devices, systems, shapes, sizes, and packaging arrangements. For example, the aspects, embodiments, and / or use cases may be embodied via integrated chips and other devices based on non-module components (e.g., end-user devices, vehicles, communication devices, computing devices, industrial equipment, retail / purchase devices, medical devices, artificial intelligence (AI)-enabled devices, etc.). Although some examples may or may not be specifically targeted at use cases or applications, the described examples may have broad applicability. The aspects, embodiments, and / or use cases may range from chip-level or modular components to non-modular, non-chip-level embodiments, and further to aggregated, distributed, or original equipment manufacturer (OEM) devices or systems incorporating one or more of the technologies herein. In some practical settings, devices incorporating the described aspects and features may also include additional components and features for implementing and practicing the claimed and described aspects. For example, the transmission and reception of wireless signals necessarily includes multiple components for analog and digital purposes (e.g., hardware components including antennas, RF chains, power amplifiers, modulators, buffers, processors, interleavers, adders / summers, etc.). The technologies described herein may be practiced in a wide variety of devices, chip-level components, systems, distributed arrangements, aggregated components, or disaggregated components, end-user devices, etc., of various sizes, shapes, and configurations.

[0031] The deployment of a communication system (such as a 5G NR system) can be arranged with various components or constituent parts in a variety of ways. In a 5G NR system or network, network nodes, network entities, mobility elements of the network, radio access network (RAN) nodes, core network nodes, network elements, or network equipment (such as a base station (BS)) or one or more units (or one or more components) performing base station functionality may be implemented in an aggregated architecture or a disaggregated architecture. For example, a BS (such as a Node B (NB), evolved NB (eNB), NR BS, 5G NB, access point (AP), transmit receive point (TRP), or cell, etc.) may be implemented as an aggregated base station (also referred to as a stand-alone BS or monolithic BS) or a disaggregated base station.

[0032] A centralized base station may be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node. A split base station may be configured to utilize a protocol stack that is physically or logically distributed between two or more units, such as one or more central or centralized units (CUs), one or more distributed units (DUs), or one or more radio units (RUs). In some aspects, a CU may be implemented within a RAN node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed among one or more other RAN nodes. A DU may be implemented to communicate with one or more RUs. Each of the CU, DU, and RU may be implemented as a virtual unit, i.e., a virtual central unit (VCU), a virtual distributed unit (VDU), or a virtual radio unit (VRU).

[0033] Base station operation or network design may consider the aggregation characteristics of base station functionality. For example, split base stations may be utilized in an integrated access backhaul (IAB) network, an open radio access network (O-RAN, such as a network configuration initiated by the O-RAN Alliance), or a virtualized radio access network (vRAN, also known as a cloud radio access network (C-RAN)). Splitting may include distributing functionality across two or more units at various physical locations and virtually distributing the functionality of at least one unit, which may enable flexibility in network design. The various units of a split base station or split RAN architecture may be configured for wired or wireless communication with at least one other unit.

[0034] Figure 1 FIG. 100 is a diagram illustrating an example of a wireless communication system and an access network. The illustrated wireless communication system includes a split base station architecture. The split base station architecture may include one or more CUs 110, which may communicate directly with the core network 120 via a backhaul link, or indirectly with the core network 120 through one or more split base station units, such as a near real-time (near-RT) RAN intelligent controller (RIC) 125 via an E2 link or a non-real-time (non-RT) RIC 115 associated with a service management and orchestration (SMO) framework 105 or both. The CU 110 may communicate with one or more DUs 130 via a respective midhaul link, such as an F1 interface. The DU 130 may communicate with one or more RUs 140 via a respective fronthaul link. The RU 140 may communicate with a respective UE 104 via one or more radio frequency (RF) access links. In some embodiments, the UE 104 may be served simultaneously by multiple RUs 140.

[0035] Each of these units (i.e., CU 110, DU 130, RU 140, and the near RT RIC 125, non-RT RIC 115, and SMO framework 105) may include one or more interfaces or be coupled to one or more interfaces that are configured to receive or transmit signals, data, or information (collectively referred to as signals) via a wired transmission medium or a wireless transmission medium. Each of these units or an associated processor or controller that provides instructions to the communication interfaces of these units may be configured to communicate with one or more of the other units via the transmission medium. For example, these units may include a wired interface that is configured to receive signals or transmit signals to one or more of the other units via a wired transmission medium. Additionally, these units may include a wireless interface that may include a receiver, transmitter, or transceiver (such as an RF transceiver) that is configured to receive signals or transmit signals or both to one or more of the other units via a wireless transmission medium.

[0036] In some aspects, the CU 110 may host one or more higher layer control functions. Such control functions may include radio resource control (RRC), packet data convergence protocol (PDCP), or service data adaptation protocol (SDAP), etc. Each control function may utilize an interface that is configured to convey signals with other control functions hosted by the CU 110. The CU 110 may be configured to handle user plane functionality (i.e., Central Unit - User Plane (CU-UP)), control plane functionality (i.e., Central Unit - Control Plane (CU-CP)), or a combination thereof. In some specific implementations, the CU 110 may be logically split into one or more CU-UP units and one or more CU-CP units. When implemented in an O-RAN configuration, the CU-UP units may communicate bidirectionally with the CU-CP units via an interface (such as an E1 interface). As needed, the CU 110 may be implemented to communicate with the DU 130 for network control and signaling.

[0037] The DU 130 may correspond to a logical unit that includes one or more base station functions for controlling the operation of one or more RUs 140. In some aspects, the DU 130 may host one or more of the radio link control (RLC) layer, the media access control (MAC) layer, and one or more high physical (PHY) layers (such as modules for forward error correction (FEC) encoding and decoding, scrambling, modulation, or demodulation, etc.) at least partially according to a functional split (such as those defined by 3GPP). In some aspects, the DU 130 may further host one or more low PHY layers. Each layer (or module) may be implemented using an interface that is configured to communicate signals with other layers (and modules) hosted by the DU 130 or with control functions hosted by the CU 110.

[0038] Lower layer functionality may be implemented by one or more RUs 140. In some deployments, the RUs 140 controlled by the DU 130 may correspond to logical nodes that host RF processing functions or low PHY layer functions (such as performing fast Fourier transform (FFT), inverse FFT (iFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, etc.) or both at least partially based on a functional split (such as a lower layer functional split). In such an architecture, the RUs 140 may be implemented to handle over-the-air (OTA) communication with one or more UEs 104. In some embodiments, the real-time and non-real-time aspects of the control plane communication and user plane communication with the RUs 140 may be controlled by the corresponding DU 130. In some scenarios, this configuration may enable the DU 130 and the CU 110 to be implemented in a cloud-based RAN architecture (such as a vRAN architecture).

[0039] The SMO framework 105 can be configured to support the RAN deployment and orchestration of non-virtualized network elements and virtualized network elements. For non-virtualized network elements, the SMO framework 105 can be configured to support the deployment of dedicated physical resources for RAN coverage requirements, and these dedicated physical resources can be managed via operation and maintenance interfaces (such as the O1 interface). For virtualized network elements, the SMO framework 105 can be configured to interact with a cloud computing platform (such as the Open Cloud (O-Cloud) 190) to perform network element lifecycle management (such as instantiating virtualized network elements) via a cloud computing platform interface (such as the O2 interface). Such virtualized network elements can include, but are not limited to, the CU 110, DU 130, RU 140, and the near RT RIC 125. In some specific implementations, the SMO framework 105 can communicate with the hardware aspects of the 4G RAN (such as the Open eNB (O-eNB) 111) via the O1 interface. Additionally, in some specific implementations, the SMO framework 105 can communicate directly with one or more RUs 140 via the O1 interface. The SMO framework 105 can also include a non-RT RIC 115 configured to support the functionality of the SMO framework 105.

[0040] The non-RT RIC 115 can be configured to include a logical function that enables non-real-time control and optimization of RAN elements and resources, an artificial intelligence (AI) / machine learning (ML) (AI / ML) workflow including model training and updating, or policy-based guidance of applications / features in the near RT RIC 125. The non-RT RIC 115 can be coupled to or communicate with the near RT RIC 125 (such as via the A1 interface). The near RT RIC 125 can be configured to include a logical function that enables near-real-time control and optimization of RAN elements and resources through an interface (such as via the E2 interface) via data collection and actions, and this interface connects one or more CUs 110, one or more DUs 130, or both, and the O-eNB to the near RT RIC 125.

[0041] In some embodiments, to generate the AI / ML models to be deployed in the near-RT RIC 125, the non-RT RIC 115 may receive parameters or external enrichment information from an external server. Such information may be utilized by the near-RT RIC 125 and may be received from non-network data sources or from network functions at the SMO framework 105 or the non-RT RIC 115. In some examples, the non-RT RIC 115 or the near-RT RIC 125 may be configured to regulate RAN behavior or performance. For example, the non-RT RIC 115 may monitor long-term trends and patterns of performance and employ AI / ML models to perform corrective actions via the SMO framework 105 (such as reconfiguration via O1) or via the creation of RAN management policies (such as A1 policies).

[0042] At least one of the CU 110, DU 130, and RU 140 may be referred to as the base station 102. Thus, the base station 102 may include one or more of the CU 110, DU 130, and RU 140 (each component is indicated by a dashed line to indicate that each component may or may not be included in the base station 102). The base station 102 provides an access point to the core network 120 for the UE 104. The base station 102 may include macro cells (high-power cellular base stations) and / or small cells (low-power cellular base stations). Small cells include femto cells, pico cells, and micro cells. A network including both small cells and macro cells may be referred to as a heterogeneous network. The heterogeneous network may also include a home evolved Node B (HeNB), which may provide services to a restricted group called a closed subscriber group (CSG). The communication link between the RU 140 and the UE 104 may include an uplink (UL) (also referred to as a reverse link) transmission from the UE 104 to the RU 140 and / or a downlink (DL) (also referred to as a forward link) transmission from the RU 140 to the UE 104. The communication link may use multiple-input multiple-output (MIMO) antenna technology, including spatial multiplexing, beamforming, and / or transmit diversity. The communication link may pass through one or more carriers. For each carrier allocated in carrier aggregation with a total of up to Yx MHz (x component carriers) for transmission in each direction, the base station 102 / UE 104 may use a spectrum with a bandwidth of up to Y MHz (e.g., 5 MHz, 10 MHz, 15 MHz, 20 MHz, 100 MHz, 400 MHz, etc.). These carriers may or may not be adjacent to each other. The allocation of carriers may be asymmetric with respect to the DL and UL (e.g., more or fewer carriers may be allocated for the DL compared to the UL). The component carriers may include a primary component carrier and one or more secondary component carriers. The primary component carrier may be referred to as the primary cell (PCell) and the secondary component carriers may be referred to as secondary cells (SCells).

[0043] Some UEs 104 may communicate with each other using device-to-device (D2D) communication links 158. The D2D communication links 158 may use DL / UL wireless wide area network (WWAN) spectrum. The D2D communication links 158 may use one or more sidelink channels, such as the Physical Sidelink Broadcast Channel (PSBCH), Physical Sidelink Discovery Channel (PSDCH), Physical Sidelink Shared Channel (PSSCH), and Physical Sidelink Control Channel (PSCCH). D2D communication may be through various wireless D2D communication systems, such as, for example, Bluetooth, Wi-Fi based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards, LTE, or NR.

[0044] The wireless communication system may also include a Wi-Fi AP 150 that communicates with the UE 104 (also referred to as a Wi-Fi station (STA)) via a communication link 154, such as in the 5 GHz unlicensed spectrum, etc. When communicating in the unlicensed spectrum, the UE 104 / AP 150 may perform a Clear Channel Assessment (CCA) before communication to determine if the channel is available.

[0045] The electromagnetic spectrum is generally subdivided into various categories, bands, channels, etc. based on frequency / wavelength. In 5G NR, two initial operating bands have been identified as Frequency Range Designation FR1 (410 MHz – 7.125 GHz) and FR2 (24.25 GHz – 52.6 GHz). Although a part of FR1 is greater than 6 GHz, in various documents and articles, FR1 is generally (interchangeably) referred to as the “sub-6 GHz” band. Regarding FR2, a similar naming issue sometimes occurs, which is generally (interchangeably) referred to as the “millimeter wave” band in documents and articles, although it is different from the Extremely High Frequency (EHF) band (30 GHz – 300 GHz) identified by the International Telecommunication Union (ITU) as the “millimeter wave” band.

[0046] The frequencies between FR1 and FR2 are generally referred to as mid-band frequencies. Recent 5G NR research has identified operating bands for these mid-band frequencies as Frequency Range Designation FR3 (7.125 GHz – 24.25 GHz). The bands falling within FR3 may inherit FR1 characteristics and / or FR2 characteristics, and thus can effectively extend the features of FR1 and / or FR2 to the mid-band frequencies. In addition, higher bands are currently being explored to extend 5G NR operation beyond 52.6 GHz. For example, three higher operating bands have been identified as Frequency Range Designation FR2-2 (52.6 GHz - 71 GHz), FR4 (71 GHz - 114.25 GHz), and FR5 (114.25 GHz - 300 GHz). Each of these higher bands in these higher bands falls within the EHF band.

[0047] Taking into account the above aspects, unless otherwise specifically stated, if terms such as "below 6 GHz" are used herein, they can broadly represent frequencies that can be less than 6 GHz, can be within FR1, or can include mid-band frequencies. Additionally, unless otherwise specifically stated, if terms such as "millimeter wave" are used herein, they can broadly represent frequencies that can include mid-band frequencies, can be within FR2, FR4, FR2-2, and / or FR5, or can be within the EHF band.

[0048] Base station 102 and UE 104 may each include a plurality of antennas (such as antenna elements, antenna panels, and / or antenna arrays) to facilitate beamforming. Base station 102 may transmit a beamformed signal 182 to UE 104 in one or more transmission directions. UE 104 may receive the beamformed signal from base station 102 in one or more reception directions. UE 104 may also transmit a beamformed signal 184 to base station 102 in one or more transmission directions. Base station 102 may receive the beamformed signal from UE 104 in one or more reception directions. Base station 102 / UE 104 may perform beam training to determine the optimal reception direction and the optimal transmission direction for each of base station 102 / UE 104. The transmission direction and the reception direction of base station 102 may be the same or may not be the same. The transmission direction and the reception direction of UE 104 may be the same or may not be the same.

[0049] Base station 102 may include and / or be referred to as a gNB, Node B, eNB, access point, base station transceiver, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP, network node, network entity, network equipment, or some other suitable term. Base station 102 may be implemented as an integrated access and backhaul (IAB) node, a relay node, a sidelink node, an aggregated (monolithic) base station having a baseband unit (BBU) (including a CU and a DU) and an RU, or may be implemented as a disaggregated base station including one or more of a CU, a DU, and / or an RU. A set of base stations that may include disaggregated base stations and / or aggregated base stations may be referred to as a next generation (NG) RAN (NG-RAN).

[0050] The core network 120 may include an Access and Mobility Management Function (AMF) 161, a Session Management Function (SMF) 162, a User Plane Function (UPF) 163, a Unified Data Management (UDM) 164, one or more Location Servers 168, and other functional entities. The AMF 161 is a control node that processes signaling between the UE 104 and the core network 120. The AMF 161 supports registration management, connection management, mobility management, and other functions. The SMF 162 supports session management and other functions. The UPF 163 supports packet routing, packet forwarding, and other functions. The UDM 164 supports the generation of Authentication and Key Agreement (AKA) credentials, user identity handling, access authorization, and subscription management. One or more Location Servers 168 are illustrated as including a Gateway Mobile Location Center (GMLC) 165 and a Location Management Function (LMF) 166. However, in general, one or more Location Servers 168 may include one or more location / locationing servers, and the one or more location / locationing servers may include one or more of the GMLC 165, LMF 166, a Position Determination Entity (PDE), a Serving Mobile Location Center (SMLC), or a Mobile Positioning Center (MPC), etc. The GMLC 165 and LMF 166 support UE location services. The GMLC 165 provides an interface for clients / applications (e.g., emergency services) to access UE location information. The LMF 166 receives measurement and assistance information from the NG-RAN and the UE 104 via the AMF 161 to calculate the location of the UE 104. The NG-RAN may utilize one or more positioning methods to determine the location of the UE 104. Positioning the UE 104 may involve signal measurements, location estimation, and optional speed calculation based on these measurements. The signal measurements may be performed by the UE 104 and / or the base station 102 serving the UE 104. The measured signals may be based on a Satellite Positioning System (SPS) 170 (e.g., a Global Navigation Satellite System (GNSS), a Global Positioning System (GPS), a Non-Terrestrial Network (NTN), or one or more of other satellite positioning / location systems), an LTE signal, a Wireless Local Area Network (WLAN) signal, a Bluetooth signal, a Terrestrial Beacon System (TBS), sensor-based information (e.g., an atmospheric pressure sensor, a motion sensor), an NR Enhanced Cell ID (NR E-CID) method, an NR signal (e.g., multi-round-trip time (multi-RTT), DL departure angle (DL-AoD), DL time difference of arrival (DL-TDOA), UL time difference of arrival (UL-TDOA), and UL arrival angle (UL-AoA) positioning), and / or one or more of other systems / signals / sensors.

[0051] Examples of the UE 104 include cellular phones, smart phones, Session Initiation Protocol (SIP) phones, laptop computers, personal digital assistants (PDAs), satellite radios, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, tablet computers, smart devices, wearable devices, vehicles, electricity meters, gas pumps, large or small kitchen appliances, healthcare devices, implants, sensors / actuators, displays, or any other similar functional devices. Some of the UEs in the UE 104 may be referred to as IoT devices (e.g., parking meters, gas pumps, toasters, vehicles, heart monitors, etc.). The UE 104 may also be referred to as a station, mobile station, subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, cell phone, user agent, mobile client, client, or some other suitable term. In some scenarios, the term UE may also apply to one or more companion devices, such as in a device constellation arrangement. One or more of these devices may access the network jointly and / or access the network individually.

[0052] Referring again to Figure 1 , in some aspects, the UE 104 may be configured to estimate the current location of the UE based on a set of positioning measurements and a set of time update predictions using a positioning engine; calculate real-time navigation route information using at least one navigation application based on the current location of the UE, the destination of the UE, and map information; and change or verify the set of positioning estimates performed by the positioning engine based on the real-time navigation route information from at least one navigation application (e.g., via the navigation component 198). As Figure 1 Further shown, the base station 102 may include a map data component 199.

[0053] Figure 2A FIG. 200 is a diagram illustrating an example of a first subframe within a 5G NR frame structure. Figure 2B FIG. 230 is a diagram illustrating an example of a DL channel within a 5G NR subframe. Figure 2C FIG. 250 is a diagram illustrating an example of a second subframe within a 5G NR frame structure. Figure 2D FIG. 280 is a diagram illustrating an example of a UL channel within a 5G NR subframe. The 5G NR frame structure may be frequency division duplexing (FDD) (wherein for a specific set of subcarriers (carrier system bandwidth), the subframes within that set of subcarriers are dedicated to DL or UL), or may be time division duplexing (TDD) (wherein for a specific set of subcarriers (carrier system bandwidth), the subframes within that set of subcarriers are dedicated to both DL and UL). In Figure 2A , Figure 2CIn the provided example, the 5G NR frame structure is assumed to be TDD, where subframe 4 is configured with slot format 28 (where most are DL), where D is DL, U is UL, and F is flexibly available between DL / UL, and subframe 3 is configured with slot format 1 (where all are UL). Although subframes 3 and 4 are shown as having slot formats 1 and 28 respectively, any particular subframe can be configured with any of the various available slot formats 0 to 61. Slot formats 0 and 1 are all-DL and all-UL respectively. The other slot formats 2 to 61 include a mixture of DL, UL, and flexible symbols. The UE is configured with the slot format by receiving a slot format indicator (SFI) (configured dynamically by DL control information (DCI) or semi-statically / statically by radio resource control (RRC) signaling). Note that the following description also applies to the 5G NR frame structure as TDD.

[0054] Figures 2A to 2D The frame structure is illustrated, and aspects of the present disclosure may be applicable to other wireless communication technologies that may have different frame structures and / or different channels. One frame (10 ms) can be divided into 10 equal-sized subframes (1 ms). Each subframe can include one or more slots. A subframe can also include mini-slots, which can include 7, 4, or 2 symbols. Each slot can include 14 or 12 symbols, depending on whether the cyclic prefix (CP) is normal or extended. For normal CP, each slot can include 14 symbols, and for extended CP, each slot can include 12 symbols. The symbols on the DL can be cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) symbols. The symbols on the UL can be CP-OFDM symbols (for high-throughput scenarios) or discrete Fourier transform (DFT) spread OFDM (DFT-s-OFDM) symbols (for power-constrained scenarios; limited to single-stream transmission). The number of slots within a subframe is based on the CP and the parameter set. The parameter set defines the subcarrier spacing (SCS) (see Table 1). The symbol length / duration can be scaled by 1 / SCS.

[0055]

[0056] Table 1: Parameter Set, SCS, and CP

[0057] For normal CP (14 symbols / slot), the different parameter sets µ 0 to 4 allow 1, 2, 4, 8, and 16 slots per subframe respectively. For extended CP, parameter set 2 allows 4 slots per subframe. Thus, for normal CP and parameter set µ, there are 14 symbols per slot and 2 µ slots per subframe. The subcarrier spacing can be equal to where For parameter sets 0 to 4. Thus, the subcarrier spacing for parameter set μ = 0 is 15 kHz, and the subcarrier spacing for parameter set μ = 4 is 240 kHz. The symbol length / duration is negatively correlated with the subcarrier spacing. Figures 2A to 2D An example of parameter set μ = 2 with normal CP having 14 symbols per time slot and 4 time slots per subframe is provided. The time slot duration is 0.25 ms, the subcarrier spacing is 60 kHz, and the symbol duration is approximately 16.67 μs. Within a frame set, there may be one or more different bandwidth parts (BWPs) (see Figure 2B ). Each BWP may have a specific parameter set and CP (normal or extended).

[0058] A resource grid can be used to represent the frame structure. Each time slot includes resource blocks (RBs) (also referred to as physical RBs (PRBs)) that extend 12 consecutive subcarriers. The resource grid is divided into multiple resource elements (REs). The number of bits carried by each RE depends on the modulation scheme.

[0059] As Figure 2A illustrated, some of the REs carry reference (pilot) signals (RSs) for the UE. The RSs can include demodulation RSs (DM-RSs) (designated as R for a particular configuration, but other DM-RS configurations are possible) and channel state information reference signals (CSI-RSs) for channel estimation at the UE. The RSs can also include beam measurement RSs (BRSs), beam refinement RSs (BRRSs), and phase tracking RSs (PT-RSs).

[0060] Figure 2BIllustrates examples of various DL channels within a subframe of a frame. The Physical Downlink Control Channel (PDCCH) carries DCI within one or more Control Channel Elements (CCEs) (e.g., 1, 2, 4, 8, or 16 CCEs), where each CCE includes six Resource Element Groups (REGs), and each REG includes 12 consecutive Resource Elements (REs) in the OFDM symbols of a Resource Block (RB). The PDCCH within a Bandwidth Part (BWP) can be referred to as a Control Resource Set (CORESET). The UE is configured to monitor PDCCH candidates in the PDCCH search space (e.g., common search space, UE-specific search space) during the PDCCH monitoring occasion on the CORESET, where the PDCCH candidates have different DCI formats and different aggregation levels. Additional BWPs can be located at higher and / or lower frequencies on the channel bandwidth. The Primary Synchronization Signal (PSS) can be in symbol 2 of a specific subframe of the frame. The PSS is used by the UE 104 to determine subframe / symbol timing and the physical layer identity. The Secondary Synchronization Signal (SSS) can be in symbol 4 of a specific subframe of the frame. The SSS is used by the UE to determine the physical layer cell identity group number and the radio frame timing. Based on the physical layer identity and the physical layer cell identity group number, the UE can determine the Physical Cell Identifier (PCI). Based on the PCI, the UE can determine the location of the Demodulation Reference Signals (DM-RS). The Physical Broadcast Channel (PBCH) carrying the Master Information Block (MIB) can be logically grouped with the PSS and SSS to form a Synchronization Signal (SS) / PBCH block (also referred to as an SS block (SSB)). The MIB provides the number of RBs in the system bandwidth and the System Frame Number (SFN). The Physical Downlink Shared Channel (PDSCH) carries user data, broadcast system information not sent via the PBCH (such as System Information Blocks (SIBs)), and paging messages.

[0061] As Figure 2C Illustrated, some of the REs carry DM-RS (indicated as R for a specific configuration, but other DM-RS configurations are possible) for channel estimation at the base station. The UE can transmit DM-RS for the Physical Uplink Control Channel (PUCCH) and DM-RS for the Physical Uplink Shared Channel (PUSCH). The PUSCH DM-RS can be transmitted in the previous one or two symbols of the PUSCH. Depending on whether a short PUCCH or a long PUCCH is transmitted and according to the specific PUCCH format used, the PUCCH DM-RS can be transmitted in different configurations. The UE can transmit a Sounding Reference Signal (SRS). The SRS can be transmitted in the last symbol of the subframe. The SRS can have a comb structure, and the UE can transmit the SRS on one of the teeth of the comb. The SRS can be used by the base station for channel quality estimation to enable frequency-dependent scheduling of the UL.

[0062] Figure 2DExamples of various UL channels within a subframe of a frame are illustrated. The PUCCH can be located at the position indicated in one configuration. The PUCCH carries uplink control information (UCI), such as a scheduling request, a channel quality indicator (CQI), a precoding matrix indicator (PMI), a rank indicator (RI), and a hybrid automatic repeat request (HARQ) acknowledgement (ACK) (HARQ-ACK) feedback (i.e., one or more HARQ ACK bits indicating one or more ACKs and / or negative ACKs (NACKs)). The PUSCH carries data and can additionally be used to carry a buffer status report (BSR), a power headroom report (PHR), and / or UCI.

[0063] Figure 3 Is a block diagram of a base station 310 in an access network communicating with a UE 350. In the DL, Internet Protocol (IP) packets can be provided to a controller / processor 375. The controller / processor 375 implements layer 3 and layer 2 functionality. Layer 3 includes a radio resource control (RRC) layer, and layer 2 includes a service data adaptation protocol (SDAP) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a media access control (MAC) layer. The controller / processor 375 provides RRC layer functionality associated with the broadcast of system information (e.g., MIB, SIB), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter-radio access technology (RAT) mobility, and measurement configuration for UE measurement reporting; PDCP layer functionality associated with header compression / decompression, security (encryption, decryption, integrity protection, integrity verification), and handover support functions; RLC layer functionality associated with the transfer of upper layer packet data units (PDUs), error correction via ARQ, concatenation, segmentation, and reassembly of RLC service data units (SDUs), re-segmentation of RLC data PDUs, and re-ordering of RLC data PDUs; and MAC layer functionality associated with the mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction via HARQ, priority handling, and logical channel prioritization.

[0064] The transmit (TX) processor 316 and the receive (RX) processor 370 implement the layer 1 functionality associated with various signal processing functions. Layer 1, which includes the physical (PHY) layer, may include error detection on the transport channel, forward error correction (FEC) encoding / decoding of the transport channel, interleaving, rate matching, mapping to the physical channel, modulation / demodulation of the physical channel, and MIMO antenna processing. The TX processor 316 handles the mapping to the signal constellation based on various modulation schemes such as binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), and M-quadrature amplitude modulation (M-QAM). Then, the encoded and modulated symbols may be split into parallel streams. Each stream may then be mapped to OFDM subcarriers, multiplexed with a reference signal (e.g., pilot) in the time domain and / or frequency domain, and subsequently combined together using an inverse fast Fourier transform (IFFT) to generate a physical channel carrying a stream of time-domain OFDM symbols. The OFDM stream is space precoded to generate multiple spatial streams. Channel estimates from the channel estimator 374 may be used to determine the encoding and modulation schemes, as well as for spatial processing. The channel estimates may be derived from reference signals transmitted by the UE 350 and / or channel state feedback. Then, each spatial stream may be provided to a different antenna 320 via a separate transmitter 318Tx. Each transmitter 318Tx may modulate a radio frequency (RF) carrier using the corresponding spatial stream for transmission.

[0065] At the UE 350, each receiver 354Rx receives signals via its corresponding antenna 352. Each receiver 354Rx recovers the information modulated onto the RF carrier and provides the information to the receive (RX) processor 356. The TX processor 368 and the RX processor 356 implement the layer 1 functionality associated with various signal processing functions. The RX processor 356 may perform spatial processing on the information to recover any spatial streams destined for the UE 350. If multiple spatial streams are destined for the UE 350, they may be combined by the RX processor 356 into a single OFDM symbol stream. Then, the RX processor 356 uses a fast Fourier transform (FFT) to convert the OFDM symbol stream from the time domain to the frequency domain. The frequency-domain signal includes a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbols and reference signals on each subcarrier are recovered and demodulated by determining the most likely signal constellation points transmitted by the base station 310. These soft decisions may be based on the channel estimates computed by the channel estimator 358. Then, the soft decisions are decoded and deinterleaved to recover the data and control signals originally transmitted by the base station 310 on the physical channel. The data and control signals are then provided to the controller / processor 359, which implements the layer 3 and layer 2 functionality.

[0066] The controller / processor 359 may be associated with a memory 360 that stores program code and data. The memory 360 may be referred to as a computer-readable medium. In the UL, the controller / processor 359 provides demultiplexing between transport channels and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover IP packets. The controller / processor 359 is also responsible for supporting HARQ operations using error detection with ACK and / or NACK protocols.

[0067] Similar to the functionality described in connection with DL transmissions performed by the base station 310, the controller / processor 359 provides RRC layer functionality associated with system information (e.g., MIB, SIB) acquisition, RRC connection, and measurement reporting; PDCP layer functionality associated with header compression / decompression and security (encryption, decryption, integrity protection, integrity verification); RLC layer functionality associated with the transfer of upper layer PDUs, error correction via ARQ, concatenation, segmentation, and reassembly of RLC SDUs, re-segmentation of RLC data PDUs, and re-ordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto TBs, demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction via HARQ, priority handling, and logical channel prioritization.

[0068] Channel estimates derived by the channel estimator 358 based on reference signals or feedback transmitted by the base station 310 may be used by the TX processor 368 to select appropriate decoding and modulation schemes and to facilitate spatial processing. The spatial streams generated by the TX processor 368 may be provided to different antennas 352 via a separate transmitter 354Tx. Each transmitter 354Tx may modulate an RF carrier using the corresponding spatial stream for transmission.

[0069] UL transmissions are processed at the base station 310 in a manner similar to that described in connection with the receiver functionality at the UE 350. Each receiver 318Rx receives signals via its corresponding antenna 320. Each receiver 318Rx recovers the information modulated onto the RF carrier and provides the information to the RX processor 370.

[0070] The controller / processor 375 may be associated with a memory 376 that stores program code and data. The memory 376 may be referred to as a computer-readable medium. In the UL, the controller / processor 375 provides demultiplexing between transport channels and logical channels, packet reassembly, decryption, header decompression, control signal processing to recover IP packets. The controller / processor 375 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operations.

[0071] At least one of TX processor 368, RX processor 356, and controller / processor 359 may be configured to perform aspects in conjunction with Figure 1 navigation component 198.

[0072] Figure 4 FIG. 400 is a diagram illustrating an example of UE positioning based on reference signal measurements (which may also be referred to as “network-based positioning”) in accordance with various aspects of the present disclosure. UE 404 may transmit UL-SRS 412 at time T SRS_TX and receive a downlink positioning reference signal (PRS) (DL-PRS) 410 at time T PRS_RX . TRP 406 may receive UL-SRS 412 at time T SRS_RX and transmit DL-PRS 410 at time T PRS_TX . UE 404 may receive DL-PRS 410 before transmitting UL-SRS 412, or may transmit UL-SRS 412 before receiving DL-PRS 410. In both cases, a positioning server (e.g., location server 168) or UE 404 may determine RTT 414 based on ||T SRS_RX – T PRS_TX | – |T SRS_TX – T PRS_RX ||. Thus, multi-RTT positioning may utilize UE Rx-Tx time difference measurements of downlink signals received from multiple TRPs 402, 406 and measured by UE 404 (i.e., |T SRS_TX – T PRS_RX |) and DL-PRS reference signal received power (RSRP) (DL-PRS-RSRP), as well as measured TRP Rx-Tx time difference measurements of uplink signals transmitted from UE404 at multiple TRPs 402, 406 (i.e., |T SRS_RX – T PRS_TX |) and UL-SRS-RSRP. UE 404 uses assistance data received from the positioning server to measure UE Rx-Tx time difference measurements (and optionally DL-PRS-RSRP of received signals), and TRPs 402, 406 use assistance data received from the positioning server to measure gNB Rx-Tx time difference measurements (and optionally UL-SRS-RSRP of received signals). These measurements may be used at the positioning server or UE 404 to determine an RTT that is used to estimate the location of UE 404. Other methods for determining RTT are possible, such as, for example, using DL-TDOA and / or UL-TDOA measurements.

[0073] The PRS can be defined for network-based positioning (e.g., NR positioning) such that the UE can detect and measure more adjacent transmit and receive points (TRPs), where multiple configurations are supported to enable various deployments (e.g., indoor, outdoor, sub-6, mmW, etc.). To support PRS beam operation, beam scanning can also be configured for the PRS. The UL positioning reference signal can be based on the sounding reference signal (SRS) with enhancements / modifications for positioning purposes. In some examples, the UL-PRS can be referred to as the "SRS for positioning", and new information elements (IEs) can be configured for the SRS for positioning in RRC signaling.

[0074] The DL PRS-RSRP can be defined as the linear average of the power contributions (in [W]) of the resource elements of the antenna port carrying the DL PRS reference signal configured for RSRP measurement within the considered measurement frequency bandwidth. In some examples, for FR1, the reference point for the DL PRS-RSRP can be the antenna connector of the UE. For FR2, the DL PRS-RSRP can be measured based on the combined signal from the antenna elements corresponding to a given receiver branch. For FR1 and FR2, if the UE uses receiver diversity, the reported DL PRS-RSRP value may not be lower than the corresponding DL PRS-RSRP of any individual receiver branch in the individual receiver branches. Similarly, the UL SRS-RSRP can be defined as the linear average of the power contributions (in [W]) of the resource elements carrying the sounding reference signal (SRS). The UL SRS-RSRP can be measured within the considered measurement frequency bandwidth, in the configured measurement occasion, by the configured resource elements. In some examples, for FR1, the reference point for the UL SRS-RSRP can be the antenna connector of the base station (e.g., gNB). For FR2, the UL SRS-RSRP can be measured based on the combined signal from the antenna elements corresponding to a given receiver branch. For FR1 and FR2, if the base station uses receiver diversity, the reported UL SRS-RSRP value may not be lower than the corresponding UL SRS-RSRP of any individual receiver branch in the individual receiver branches.

[0075] The PRS-path RSRP (PRS-RSRPP) can be defined as the power of the linear average of the channel response at the i-th path delay of the resource elements carrying the DL PRS signal configured for measurement, where the DL PRS-RSRPP of the first path delay is the power contribution corresponding to the path first detected in time. In some examples, the PRS path phase measurement can refer to the phase associated with the i-th path of the channel derived using the PRS resources.

[0076] DL-AoD positioning can utilize the measured DL-PRS-RSRP of the downlink signals received at the UE 404 from multiple TRPs 402, 406. The UE 404 uses the assistance data received from the positioning server to measure the DL-PRS-RSRP of the received signals, and the resulting measurements, together with the azimuth angle of departure (A-AoD), zenith angle of departure (Z-AoD), and other configuration information, are used to position the UE 404 relative to the neighboring TRPs 402, 406.

[0077] DL-TDOA positioning can utilize the DL reference signal time difference (RSTD) (and optionally DL-PRS-RSRP) of the downlink signals received at the UE 404 from multiple TRPs 402, 406. The UE 404 uses the assistance data received from the positioning server to measure the DL RSTD (and optionally DL-PRS-RSRP) of the received signals, and the resulting measurements, together with other configuration information, are used to position the UE 404 relative to the neighboring TRPs 402, 406.

[0078] UL-TDOA positioning can utilize the UL relative time of arrival (RTOA) (and optionally UL-SRS-RSRP) of the uplink signals transmitted from the UE 404 at multiple TRPs 402, 406. The TRPs 402, 406 use the assistance data received from the positioning server to measure the UL-RTOA (and optionally UL-SRS-RSRP) of the received signals, and the resulting measurements, together with other configuration information, are used to estimate the location of the UE 404.

[0079] UL-AoA positioning can utilize the measured azimuth angle of arrival (A-AoA) and zenith angle of arrival (Z-AoA) of the uplink signals transmitted from the UE 404 at multiple TRPs 402, 406. The TRPs 402, 406 use the assistance data received from the positioning server to measure the A-AoA and Z-AoA of the received signals, and the resulting measurements, together with other configuration information, are used to estimate the location of the UE 404. For the purposes of this disclosure, a positioning operation in which the UE provides measurements to a base station / location entity / server for use in calculating the UE location may be described as "UE-assisted", "UE-assisted positioning", and / or "UE-assisted location calculation", while a positioning operation in which the UE measures and calculates its own location may be described as "UE-based", "UE-based positioning", and / or "UE-based location calculation".

[0080] Additional positioning methods can be used to estimate the location of UE 404, such as UE-side UL-AoD and / or DL-AoA. It should be noted that data / measurements from various techniques can be combined in various ways to increase accuracy, determine and / or enhance certainty, supplement / complete measurements, and / or replace / provide missing information. For example, some UE positioning mechanisms can be radio access technology (RAT)-dependent (e.g., the positioning of the UE is RAT-based), such as downlink positioning (e.g., measurements of observed time difference of arrival (OTDOA)), uplink positioning (e.g., measurements of uplink time difference of arrival (UTDOA)), and / or combined positioning based on DL and UL (e.g., measurements of RTT relative to neighboring cells), etc. Some wireless communication systems may also support an enhanced cell ID (E-CID) positioning process based on radio resource management (RRM) measurements. On the other hand, some UE positioning mechanisms can be RAT-independent (e.g., the positioning of the UE does not depend on RAT), such as enhanced GNSS, and / or positioning techniques based on WLAN, Bluetooth, terrestrial beacon system (TBS), and / or sensors (e.g., barometric pressure sensors, motion sensors), etc. Some UE positioning mechanisms can be based on a hybrid model, where multiple positioning methods are used, which may include both RAT-dependent positioning techniques and RAT-independent positioning techniques (e.g., GNSS-OTDOA hybrid positioning).

[0081] Note that the terms "positioning reference signal" and "PRS" generally refer to specific reference signals used for positioning in NR and LTE systems. However, as used herein, the terms "positioning reference signal" and "PRS" may also refer to any type of reference signal that can be used for positioning, such as but not limited to: PRS, TRS, PTRS, CRS, CSI-RS, DMRS, PSS, SSS, SSB, SRS, UL-PRS, etc., as defined in LTE and NR. In addition, the terms "positioning reference signal" and "PRS" may refer to downlink or uplink positioning reference signals, unless otherwise indicated by the context. To further distinguish the types of PRS, downlink positioning reference signals may be referred to as "DL PRS", and uplink positioning reference signals (e.g., SRS, PTRS for positioning) may be referred to as "UL-PRS". In addition, for signals that can be transmitted in both uplink and downlink (e.g., DMRS, PTRS), these signals may be prefixed with "UL" or "DL" to distinguish the direction. For example, "UL-DMRS" can be distinguished from "DL-DMRS".

[0082] A device (e.g., a UE) equipped with a Global Navigation Satellite System (GNSS) receiver (which may include a Global Positioning System (GPS) receiver) can determine its location based on GNSS positioning. GNSS is a satellite network that broadcasts timing and orbital information for navigation and positioning measurements. GNSS can include multiple groups of satellites called constellations, which broadcast signals (which may be referred to as GNSS signals) to the control stations and users of GNSS. Based on the broadcast signals, users may be able to determine their location (e.g., via a trilateration process). For the purposes of this disclosure, a device (e.g., a UE) equipped with a GNSS receiver or capable of receiving GNSS signals can be referred to as a GNSS device, and a device capable of transmitting GNSS signals (such as a satellite) can be referred to as a Space Vehicle (SV).

[0083] Figure 5 FIG. 500 is a diagram illustrating an example of GNSS positioning in accordance with various aspects of the present disclosure. A GNSS device 506 can estimate its position and time based at least in part on data received from multiple Space Vehicles (SVs) 502 (e.g., GNSS signals 504), where each SV 502 can carry a record of its position and time and can send that data (e.g., the record) to the GNSS device 506. Each SV 502 can also include a clock that is synchronized with other clocks of the SV and with a ground clock. If the SV 502 detects a deviation from the time maintained on the ground, the SV 502 can correct it. The GNSS device 506 can also include a clock, but the clock of the GNSS device 506 may be less stable and precise compared to the clocks of each SV 502.

[0084] Since the speed of radio waves can be constant and independent of the satellite speed, the time delay between the time when the SV 502 transmits the GNSS signal 504 and the time when the GNSS device 506 receives the GNSS signal 504 can be proportional to the distance from the SV 502 to the GNSS device 506. In some examples, the GNSS device 506 can use at least four SVs to calculate / estimate one or more unknowns associated with the position (e.g., three position coordinates and a clock offset from the satellite time, etc.).

[0085] Each SV 502 can continuously broadcast GNSS signals 504 (e.g., with a modulated carrier), which can include a pseudorandom code known to the GNSS device 506 (e.g., a sequence of ones and zeros), and can also include a message that includes the transmission time and the SV's location at that time. In other words, each GNSS signal 504 can carry two types of information: time and a carrier (e.g., a modulated waveform of an input signal to be transmitted electromagnetically). Based on the GNSS signals 504 received from each SV 502, the GNSS device 506 can measure the time of arrival (TOA) of the GNSS signals 504 and calculate the time of flight (TOF) of the GNSS signals 504. Then, based on the TOF, the GNSS device 506 can calculate its three-dimensional location and clock bias, and the GNSS device 506 can determine its location on the Earth. For example, the location of the GNSS device 506 can be converted to latitude, longitude, and altitude relative to an ellipsoidal Earth model. These coordinates can be displayed on, for example, a moving map display, or recorded or used by some other system (such as a vehicle guidance system).

[0086] Although the distance between the GNSS device and the SV can be estimated based on the time it takes for the GNSS signal to reach the GNSS device, the signal sequence of the SV can be delayed relative to the sequence of the GNSS device. Thus, in some examples, a delay can be applied to the sequence of the GNSS device so that the two sequences are aligned. For example, to estimate the delay, the GNSS device can align the pseudorandom binary sequence included in the SV signal with an internally generated pseudorandom binary sequence. Since the GNSS signal of the SV takes time to reach the GNSS device, the sequence of the SV can be delayed relative to the sequence of the GNSS device. By gradually delaying the sequence of the GNSS device, the two sequences can eventually be aligned.

[0087] The accuracy of GNSS-based positioning can depend on various factors, such as satellite geometry, signal blockage, atmospheric conditions, and / or receiver design features / quality, etc. For example, GNSS receivers used by smartphones or smartwatches can have lower accuracy compared to GNSS receivers used by vehicles and exploration equipment.

[0088] In some examples, software or an application that receives location-related measurements from a GNSS chipset and / or sensors to estimate the location, speed, and / or altitude of a device may be referred to as a positioning engine (PE). Additionally, a positioning engine that can achieve a specific high accuracy level (e.g., centimeter / decimeter level accuracy) and / or latency may be referred to as a precise positioning engine (PPE). On the other hand, a navigation application may refer to an application in a user device (e.g., a smart phone, a vehicle navigation system, a GPS device, etc.) that can provide navigation guidance in real time. In the past few years, users have become increasingly reliant on these navigation applications due to the various benefits they offer. For example, navigation applications can facilitate users by enabling them to find their way to their destinations, and also allow users to contribute information and mark important locations, thereby generating the most accurate description of the location. In some examples, navigation applications can also provide professional guidance to users, where the navigation application can direct the user to the destination via the best, most direct, or most time-saving route. For example, the navigation application can obtain the current state of traffic and then locate the shortest and fastest path for the user to reach the destination, and also provide an estimate of how long it will take the user to reach the destination. Thus, navigation applications can use an Internet connection and a GPS / GNSS navigation system to provide turn-by-turn guidance instructions on how to reach a given destination.

[0089] Figure 6 FIG. 600 is a diagram illustrating an example of a navigation application in accordance with various aspects of the present disclosure. As shown at 602, the navigation application can provide turn-by-turn guidance to a destination and an estimated time to reach the destination to a user (e.g., via a display or an interface) based on real-time information. For example, the navigation application can receive / download real-time traffic information, road condition information, local traffic rules (e.g., speed limits), and / or map information / data from a server. Then, the navigation application can calculate a route to the destination based at least on the map information and other available information. The map information can include a map of the area in which the user is traveling such as the streets, buildings, and / or terrain of the area, or a map compatible with the navigation application and the GPS / GNSS system. In some examples, the route calculated by the navigation application can be the shortest or the fastest route. For the purposes of the present disclosure, the information associated with the calculated route may be referred to as navigation route information. For example, the navigation route information can include the predicted / estimated location, speed, acceleration, direction, and / or altitude of the user at different time points.

[0090] For example, as shown at 604, based on the map information, speed limits, and real-time road condition information, the navigation application can generate navigation route information 606 that guides user 608 to the destination. In some examples, the navigation route information 606 can include the location of the user and the speed of the user relative to / about time, which can be represented as and For example, a navigation application can estimate that at a first time point (T1), a user can reach a first point / location at a specific speed (e.g., reach the intersection of 59th Street and Vista Drive at a speed of 35 miles per hour), and at a second time point (T2), the user can reach a second point / location at a specific speed (e.g., reach the intersection of 60th Street and Vista Drive at a speed of 15 miles per hour), and so on until the Nth time point (TN).

[0091] Figure 7 FIG. 700 is a diagram illustrating an example of a navigation application in accordance with various aspects of the present disclosure. In some examples, since positioning and navigation technologies using GNSS and maps (sometimes plus an inertial measurement unit (IMU) and magnetometer) have become ubiquitous in people's daily lives and are achieved through various precise and robust positioning technologies, a particular navigation application may be capable of providing / implementing lane-level navigation, which can provide a much better navigation solution at the application level to the user. For example, when a user is driving on a road, the navigation application may be able to determine the current lane in which the user is located, and the navigation application can notify the user to change to another lane when appropriate (e.g., if the current lane will take the user to the wrong exit or cause the user to miss an exit). However, in order to implement such advanced navigation (e.g., lane-level navigation), the integration of precise state estimation, motion planning, and HD maps can be important for an end-to-end navigation application.

[0092] As described in connection with Figure 6 the application (AP)-level navigation route information can provide the device's positioning relative to time and speed relative to time to some extent based on speed limits and / or real-time road conditions / traffic information. In the case of advanced / lane-level navigation, the uncertainty of this information (e.g., the allowed uncertainty level) can be specified to be much smaller. For example, a general navigation application may specify the distance uncertainty as plus / minus 5 meters and the speed uncertainty as plus / minus 10 miles per hour, while an advanced / lane-level navigation application may specify the distance uncertainty as plus / minus 1 meter and the speed uncertainty as plus / minus 1 mile per hour, etc.

[0093] Some UEs (e.g., smartphones, in-vehicle navigation systems, GPS devices, etc.) can be configured to calculate a positioning estimate (e.g., the current location of the UE) based on current measurements, while some UEs can use both current measurements and a short history of the immediately computed solutions and trajectory information. Additionally, these UEs can use a least squares (LS) approximation or a Kalman filter (KF) solution to calculate the positioning estimate. The difference between the LS solution and the KF solution can lie in whether the UE uses previous user trajectory information. For example, a UE using the LS algorithm can calculate its positioning estimate based on measurements from the current time epoch. On the other hand, a UE using the KF algorithm can combine the measurements from the current time epoch with the estimated previous UE behavior (e.g., trajectory, speed, and acceleration). To avoid affecting the current positioning estimate with irrelevant distant positioning estimates, the UE can limit the historical information to a time window immediately preceding the current time and ignore old positioning estimates. Thus, the UE can use an immediate window of historical information, but once used by the KF algorithm, the UE can discard the historical information. The KF solution can rely on steps that are continuously executed, namely, time update (which can also be referred to as "time update prediction" or "KF time update") and measurement update (which can also be referred to as "measurement update correction" or "KF measurement update"). The time update can represent the propagation of unknown parameters (e.g., the KF state to be estimated) over time, and the measurement update can be responsible for incorporating newly assigned measurements into the KF filter.

[0094] Most UEs (e.g., smartphones, in-vehicle navigation systems, GPS devices, etc.) can perform navigation calculations / estimations based on an open-loop configuration. For example, a UE can use an IMU sensor (via a measurement engine) to measure its speed, direction, and / or acceleration and provide these measurements to a positioning engine. Then, the positioning engine can calculate a positioning estimate (which can also be referred to as "positioning estimation") of the UE based on the KF process / algorithm and the measurements. A high-level operating system (HLOS) or an application (e.g., a navigation application) can use the positioning estimate from the positioning engine to perform other functions. For example, a navigation application can use the positioning estimate to perform map, motion, and navigation planning, such as estimating the time for a user to reach their destination based on the user's current speed and location. This process / call flow can be referred to as an "open-loop" configuration because the positioning engine does not receive any feedback from the HLOS and the application. In other words, the positioning engine only provides the positioning estimate to another entity (e.g., the HLOS or the application), and the process / call flow is completed.

[0095] Aspects presented herein can improve the performance and accuracy of a positioning engine (PE) by configuring the positioning engine to receive feedback from a navigation application. For example, in one aspect of the present invention, the navigation application can feed the calculated navigation route information (e.g., navigation route information 606) of the navigation application to the PE to assist the PE in calculating a positioning estimate based on a KF process / algorithm. These positioning estimates can then be used by the navigation application to calculate future navigation route information or update the navigation route information (e.g., for performing a KF time update and a KF measurement update associated with the KF process / algorithm). This process / call flow can continue to repeat between the PE and the navigation application to create a closed-loop configuration / solution. In some examples, for the KF time update, the navigation route information can be used as a more accurate dynamic model, and for the KF measurement update, the navigation route information can be used for measurement outlier detection (e.g., for detecting incorrect measurements or measurements exceeding an error threshold).

[0096] Figure 8 FIG. 800 is a diagram illustrating an example of an example closed-loop configuration for a positioning engine and a navigation application in accordance with various aspects of the present disclosure. In one aspect, the UE 802 can include a plurality of functional modules (which can also be referred to as "functional logic" or simply "logic") capable of performing positioning, calculating positioning estimates, generating navigation route information, and / or performing navigation. For example, the plurality of functional modules can at least include a positioning engine module 804 and a navigation application module 806, among others.

[0097] In one example, when the UE 802 is configured / triggered to perform positioning (e.g., calculate / estimate its position), the UE 802 can first obtain a set of measurements designated for positioning, such as via a measurement engine module. For example, as shown at 820, the UE 802 can use one or more sensors (e.g., an IMU sensor, a speed sensor, etc.) to measure the speed, acceleration, altitude, and / or orientation of the UE, use the UE's antenna to measure GNSS signals, and / or use one or more sensing components to perform radio frequency (RF) sensing.

[0098] As shown at 822, after the measurement engine module obtains a set of measurements designated for positioning, the measurement engine module may pass the set of measurements to the positioning engine module 804. Then, the positioning engine module 804 may use the KF process / algorithm based on the set of measurements to calculate a positioning estimate of the UE 802 (e.g., estimate the positioning of the UE 802). In some examples, as shown at 824, the calculation of the positioning estimate may be further based on a time update prediction set, which may be generated by the dynamic model of the UE 802. For the KF process / algorithm, each positioning estimate may take two steps (i.e., time update prediction and measurement update correction). The time update prediction may come from the dynamic model of the UE. The dynamic model may refer to a model that can be trained online, where data continuously enters the system and the data is incorporated into the model through continuous updates. For example, the dynamic model of the UE 802 (e.g., the simplest model) may calculate the distance traveled by the UE 802 based on the time of travel (e.g., the difference between the start time and the end time) and the speed of the UE 802 (e.g., distance = delta_t speed). Thus, this dynamic model of the UE (or the time update prediction from this dynamic model) may be used by the positioning engine module 804 (initially) to calculate the positioning estimate (e.g., to determine the current positioning of the UE 802). Thus, in some examples, the KF time update model may be a dynamic model.

[0099] As shown at 826, the high-level operating system and / or one or more applications may use the positioning estimate from the positioning engine module 804 to perform other functions. For example, as shown at 828, the navigation application module 806 may use the positioning estimate from the positioning engine module 804 to calculate a navigation route from the current estimated positioning of the UE 802 to the destination (e.g., generate real-time navigation route information 808). As combined Figure 6 as described, the navigation route information 808 may include the estimated positioning of the UE 802 relative to / about time (e.g., at different times) and speed . In some examples, the calculation of the navigation route may be further based on available map data / information, the destination, the navigation route type (e.g., car, bicycle, pedestrian walk, public transportation, etc.), real-time traffic information, local traffic rules (e.g., speed limits, street directions, etc.), real-time crowdsourcing information (e.g., traffic conditions, road construction, temporary detour signs, speed limit changes, etc. reported by multiple users in real-time or within a certain time period), or a combination thereof.

[0100] In one aspect of the present disclosure, to improve the performance and accuracy of the positioning engine module 804, as shown at 830, the navigation application module 806 may feed its navigation route information 808 to the positioning engine module 804. The navigation route information 808 may be used to assist the positioning engine module 804, such as to calculate a positioning estimate based on a KF process / algorithm. In other words, the UE 802 or the positioning engine module 804 may change or verify the positioning estimate performed by the positioning engine module 804 based on the navigation route information 808. For example, the navigation route information may be used to change, modify, or upgrade the dynamic model of the UE 802. For example, the initial dynamic model of the UE 802 may calculate the distance traveled based on the time elapsed and the speed. If the navigation route information 808 is available, the dynamic model may be modified / upgraded to calculate the distance traveled using additional information, such as also considering the acceleration and direction of the UE 802. In other words, the navigation route information may be used as a more accurate dynamic model.

[0101] Then, the positioning engine module 806 may receive another set of measurements designated for calculating a positioning estimate from the measurement engine module, and the positioning engine module 806 may estimate the current positioning of the UE 802 based on the new set of measurements and the navigation route information 808 (which may be used to perform a time update and a measurement update associated with the KF process / algorithm in the positioning engine module 804). Similarly, the navigation application module 806 may use the current estimated positioning of the UE 802 to continue performing navigation, generate / update / modify the navigation route information 808, and feed the navigation route information 808 (e.g., real-time navigation route information) to the positioning engine module 804. This process may continue and repeat, thus forming a closed-loop configuration between the positioning engine module 804 and the navigation application module 806.

[0102] In one aspect, when the user of the UE 802 is following the navigation route planned / generated by the navigation application module 806 to make the next move (e.g., continue driving or perform a turn, etc.), the navigation route information 808 may be used as a more robust KF time update model. For example, as described in conjunction with Figure 6 certain navigation systems may be configured to have a high uncertainty value (e.g., + / - 10 meters), such that they may not be able to detect subtle movements (e.g., a vehicle changing to an adjacent lane). However, by enabling the use of the navigation route information 808 to perform a KF time update, the UE 802 may be able to detect more subtle movements (e.g., a pedestrian walking to the other side of the street), because the KF of the positioning engine module 806 may use more information for the KF time update.

[0103] In one example, the closed-loop configuration described herein (e.g., using navigation route information 808 for KF time updates) may be suitable for KFs with a low measurement update rate (e.g., a measurement update rate below an update threshold) and / or KFs with few measurement updates (e.g., a number of positioning measurements below a quantity threshold), such as when the UE 802 is in a deep urban area or a tunnel where GNSS signals are sporadic or unavailable. In another example, the closed-loop configuration may also be suitable for KFs with a time update model having low accuracy (e.g., an accuracy level below an accuracy threshold) and / or for highly dynamic scenarios, such as turning at a highway exit or intersection, etc. (a KF time update model without using navigation route information 808 may not be very accurate).

[0104] In another example, to use navigation route information 808 for KF time updates, the current location of the UE 802 may be specified to accurately reflect on the navigation route planned by the navigation application module 806. Thus, in another aspect of the present disclosure, a map matching function / algorithm may be used by the UE 802 to verify whether the current location of the UE 802 is (at a specific accuracy level) reflected on the navigation route. Map matching may refer to a procedure of assigning geographical objects to positions on a digital map, such as mapping an original GPS location to a road segment on a road network to create an estimate of the route taken. In some examples, sensor fusion (e.g., using inputs from sensors) may also be used to verify whether the current location of the UE 802 is reflected on the navigation route, or to determine the uncertainty of the KF time update model. For example, an image captured by the UE may be used to verify whether the UE is at a specified location (e.g., at an intersection, on a highway, etc.).

[0105] In some scenarios, when the closed-loop configuration described herein is used in a stable route application (e.g., a public transportation system such as a bus, a railway, etc.), the assumption that the user is following the planned navigation route and the current location of the UE is accurately reflected on the planned navigation route is more likely to be more reliable. For an autonomous driving scenario, the navigation route information 808 (or the motion planning associated with autonomous driving) may also include real-time control from the vehicle. Then, the KF time update may be more dependent on the real-time navigation route information 808 and / or the motion planning data. For some scenarios, the feedback navigation route information 808 may only include the motion surface from the navigation application module 806 and .

[0106] In another aspect of the present disclosure, the navigation route information 808 may also be used by the positioning engine module 804 for measurement outlier detection (e.g., for detecting incorrect measurements, measurements with errors exceeding an error threshold, etc.). Thus, instead of directly manipulating / updating the KF time update model, a secondary KF time update state may be used for more accurate measurement outlier detection. For example, the navigation route information 808 may be used to verify measurements from the measurement engine module and / or positioning estimates calculated by the positioning engine module 804. For example, the navigation route information 808 may indicate that at a specified time point, it is expected that the UE 802 is at a specified position at an estimated speed, such as in combination with Figure 6 as described. However, if at the specified time point, the measurement engine module is providing a speed measurement that is very different from the estimated speed (e.g., exceeding a difference threshold) and / or the positioning of the UE 802 estimated by the positioning engine module 804 exceeds a distance threshold, the UE 802 may perform additional measurements or use additional sensors to verify whether the measurements from the measurement engine module and / or the input to the positioning engine module 804 are accurate or include errors.

[0107] In some examples, using the navigation route information 808 for measurement outlier detection may be suitable for pre-fit receiver autonomous integrity monitoring (RAIM), post-fit RAIM, and / or integer ambiguity resolution (IAR) (e.g., least squares (LS) ambiguity decorrelation adjustment (LAMBDA)) verification processes. RAIM may refer to techniques developed to evaluate the integrity of GPS signals in a GPS receiver system. This can be important for safety-critical GPS applications (such as in aviation or marine navigation). For example, the GPS system may not include any internal information about the integrity of its signals. GPS satellites may broadcast slightly incorrect information that may cause navigation information to be incorrect, but the GPS receiver may not be able to detect this incorrect information. RAIM uses redundant signals to generate several GPS positioning bearings and compares them, and statistical functions determine whether a fault can be associated with any of the signals.

[0108] In some scenarios, when generating a low-confidence positioning solution (e.g., high horizontal estimated positioning error (HEPE), high dilution of precision (DOP), etc.), the UE 802 (or the positioning engine module 804) may use map matching and motion planning (e.g., the navigation route information 808) to perform measurement outlier detection instead of using the predicted state from the KF time update. For the purposes of the present disclosure, a solution may refer to a set of parameters associated with the KF or KF state. For example, the set of parameters associated with the KF or KF state may include positioning, speed, receiver clock, receiver clock rate, inter-satellite type bias (ISTB), and / or ambiguity terms, etc.

[0109] In another example, if the UE 802 is using one or more IMU sensors to perform dead reckoning (DR), the navigation route information 808 can be used to calibrate the biases of one or more IMU sensors. In navigation, DR can refer to the process of calculating the current location of a moving object (e.g., UE 802) by using a previously determined location or orientation and then combining estimates of speed, direction of travel, and course over elapsed time, which estimates can be measured or obtained via sensors (e.g., IMU, camera, inertial sensors, speed and velocity sensors, etc.). For example, by knowing the estimated direction, speed, and / or acceleration of the UE 802 at a particular point in time, the UE 802 can perform sensor calibration at that point in time. Sensor calibration can refer to the adjustment or set of adjustments performed on a sensor or instrument to make the instrument operate as accurately or error - free as possible.

[0110] In another example, when it comes to cameras and computer vision, the navigation route information 808 (e.g., real - time navigation solution) can be used to cross - check with real - time features captured by the camera. The corresponding feedback can be used to optimize the weighting between different sensors. For example, based on the navigation route information 808, the UE 802 can determine that the features captured by its front - facing camera or first sensor are more accurate than the features captured by its rear - facing camera or second sensor. Therefore, the UE 802 can assign more weight to the features captured by the front - facing camera or first sensor.

[0111] Figure 9 FIG. 900 is a flowchart illustrating an example algorithm according to various aspects of the present disclosure that enables a UE to switch between an open - loop configuration and a closed - loop configuration.

[0112] At 902, the UE (e.g., UE 802) can monitor key performance indicators (KPIs) of its PE (e.g., positioning engine module 804), such as HEPE, DOP, and / or number of measurements, etc., during a normal PE process (e.g., during an open - loop configuration where the navigation application does not feed back information to the PE).

[0113] At 904, once the PE solution converges and stabilizes (e.g., low HEPE, low DOP, etc.), and with additional verification, it can be assumed that the current location of the UE is consistent with the navigation route plan from the navigation application (e.g., navigation application module 806). The UE can continue to perform positioning and navigation based on the open - loop configuration.

[0114] At 906, if the monitored KPIs exceed a specific threshold (e.g., HEPE / DOP increases and exceeds the error threshold), the UE can switch to a closed - loop configuration, in which the navigation application can feed its navigation route information (e.g., navigation route information 808) to the PE, enabling the PE to involve additional dynamic models in the KF time update to assist in positioning estimation, such as in combination withFigure 8 As described above. If the monitored KPI drops below a threshold after a certain period of time, the UE may switch back to the open-loop configuration.

[0115] Figure 10 FIG. 1000 is an illustration showing an example accuracy comparison between an open-loop configuration and a closed-loop configuration in accordance with various aspects of the present disclosure. As shown in the illustration, the horizontal positioning accuracy can be significantly improved when the positioning engine is configured to perform the closed-loop configuration as compared to the open-loop configuration.

[0116] In another aspect of the present disclosure, feeding navigation route information to the positioning engine can also be used to identify incorrect map matching. In some scenarios, the map matching solution may place the current location of the UE (e.g., UE 802) on the wrong road. For example, at a traffic / road exit, by verifying the real-time navigation route information with the KF dynamic state, the UE or the navigation application can detect a potential incorrect lane determination.

[0117] In another aspect of the present disclosure, the UE (e.g., UE 802) can be further configured to verify the validity of the navigation route information (e.g., navigation route information 808) provided by the navigation application (e.g., navigation application module 806) based on sensors. For example, for vehicle-related applications / solutions, the camera of the vehicle can be a good sensor for verifying the navigation route information. For example, at a traffic exit location, the camera and / or computer vision of the vehicle can be used to verify whether the vehicle exits from the exit. If the vehicle does not exit from the exit as planned by the navigation application, it can be indicated that the navigation route information is no longer accurate (e.g., for a certain period of time until new / updated navigation route information is generated). In another example, for a smart phone, the motion sensor (e.g., IMU sensor) of the smart phone can be used to determine the motion pattern of the smart phone (or its user). This can assist the smart phone or the navigation application in determining whether the current navigation mode (e.g., traveling by car, train, or bicycle, etc.) is valid. For example, the navigation application of the smart phone can generate navigation route information based on the assumption that the smart phone is in a vehicle. If the sensors of the smart phone detect that the smart phone is on a bicycle (e.g., based on the movement of the user of the smart phone), the smart phone can determine that the navigation route information is invalid and not suitable for feeding to the positioning engine.

[0118] In another example, for a stable route scenario (e.g., on a train), there may be identification of mode transition points and benefits of changing the weighting used by the PE from different sensors. For example, if the UE is on a train, the UE may be configured to be in a sensing mode. However, when the UE gets off the train (especially if it is an underground scenario), the PE of the UE may be configured to switch to dead reckoning. If the sensing result determines that the UE is on the train, the PE may give a much higher weight to the navigation route information available from the train network. In other words, the UE may use its sensors to determine whether to apply a closed-loop configuration.

[0119] Figure 11 is a flowchart 1100 of a method of wireless communication. The method may be performed by a UE (e.g., UE 104, 404, 802; GNSS device 506; mobile station device 604; device 1304). The method may enable the navigation application of the UE to feed the calculated navigation route information of the UE to the PE of the UE to assist the PE in calculating a positioning estimate based on a KF process / algorithm. Then, these positioning estimates may be used by the navigation application to calculate future navigation route information or update the navigation route information, thereby improving the performance and accuracy of positioning.

[0120] At 1104, the UE may use a positioning engine to estimate the current position of the UE based on a set of positioning measurements and a set of time update predictions, such as in conjunction with Figure 8 as described. For example, at 822, the positioning engine module 804 may use a KF process / algorithm based on the set of measurements to calculate a position estimate of the UE 802 (e.g., estimate the positioning of the UE 802). In some examples, as shown at 824, the calculation of the positioning estimate may be further based on a set of time update predictions, which may be generated by a dynamic model of the UE 802. The estimation of the current position of the UE may be performed by, for example, Figure 13 the navigation component 198, the application processor 1306, the cellular baseband processor 1324, and / or the transceiver 1322 of the device 1304 in

[0121] At 1106, the UE may use at least one navigation application to calculate real-time navigation route information based on the current position of the UE, the destination of the UE, and map information, such as in conjunction with Figure 8 as described. For example, at 828, the navigation application module 806 may use the positioning estimate from the positioning engine module 804 to calculate a navigation route from the current estimated positioning of the UE 802 to the destination. In some examples, the calculation of the navigation route may be further based on available map data / information. The calculation of the real-time navigation route information using at least one navigation application may be performed by, for example, Figure 13by the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the device 1304 in

[0122] In one example, the real-time navigation route information may include at least a set of estimated future positions and speeds of the UE relative to time.

[0123] In another example, the real-time navigation route information may be further calculated based on real-time crowdsourcing information.

[0124] In another example, the real-time navigation route information is further calculated based on the navigation route type.

[0125] At 1112, the UE may change or verify a set of positioning estimates performed by the positioning engine based on real-time navigation route information from at least one navigation application, such as in conjunction with Figure 8 described. For example, at 830, the navigation application module 806 may feed its navigation route information 808 to the positioning engine module 804. The UE 802 or the positioning engine module 804 may change or verify the positioning estimates performed by the positioning engine module 804 based on the navigation route information 808. The change or verification of the set of positioning estimates performed by the positioning engine may be performed by, for example, Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the device 1304 in

[0126] In one example, to change or verify a set of positioning estimates performed by the positioning engine based on real-time navigation route information, the UE may perform the set of positioning estimates via the positioning engine based on a KF process, and the UE may change the KF time update model associated with the KF process or verify the existence of a measurement error associated with the KF process based on the real-time navigation route information. In such an example, the KF process has a measurement update rate below an update threshold, the KF process includes a number of positioning measurements below a quantity threshold, or the KF process is associated with a time update model including an accuracy level below an accuracy threshold.

[0127] In another example, at 1102, the UE may perform a set of positioning measurements via at least one of a sensor, an antenna, or RF, such as in conjunction with Figure 8 described. For example, at 820, the UE 802 may use one or more sensors (e.g., IMU sensors, speed sensors, etc.) to measure the speed, acceleration, altitude, and / or orientation of the UE, use the antenna of the UE to measure GNSS signals, and / or use one or more sensing components to perform RF sensing. The set of positioning measurements may be performed by, for example, Figure 13by the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the device 1304 in

[0128] In another example, at 1108, the UE may use at least one sensor to verify the validity of real-time navigation route information, such as in conjunction with Figure 8 as described. For example, for vehicle-related applications / solutions, the camera of the vehicle can be a good sensor for verifying navigation route information. The verification of real-time navigation route information can be performed by, for example, Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the device 1304 in Figure 8 as described. For example, when it comes to cameras and computer vision, the navigation route information 808 (e.g., real-time navigation solution) can be used for cross-checking with real-time features captured by the camera. The verification of whether at least one feature captured by the UE's camera is associated with an error can be performed by, for example, Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the device 1304 in

[0129] In another example, at 1110, the UE may verify whether the UE's current location is aligned with the real-time navigation route information based on at least one of a map matching function or a sensor fusion function, such as in conjunction with Figure 8 as described. For example, in order to perform KF time updates using the navigation route information 808, the current positioning of the UE 802 can be specified to accurately reflect the navigation route planned by the navigation application module 806. Thus, the map matching function / algorithm can be used by the UE 802 to verify whether the current positioning of the UE 802 is (at a specific accuracy level) reflected on the navigation route. The verification of whether the UE's current location is aligned with the real-time navigation route information can be performed by, for example, Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the device 1304 in

[0130] In another example, at 1114, the UE may calibrate at least one sensor of the UE based on the real-time navigation route information, such as in conjunction with Figure 8As described. For example, if UE 802 is using one or more IMU sensors to perform dead reckoning, the navigation route information 808 can be used to calibrate the biases of one or more IMU sensors. The calibration of at least one sensor of the UE can be performed by, for example Figure 13 the navigation component 198, the application processor 1306, the cellular baseband processor 1324, and / or the transceiver 1322 of the apparatus 1304 in

[0131] In another example, the UE can monitor a set of KPIs associated with a positioning engine, where, in order to change or verify a set of positioning estimates performed by the positioning engine, the UE can change or verify the set of positioning estimates performed by the positioning engine based on the set of KPIs exceeding a threshold.

[0132] In another example, the UE can estimate a new position of the UE based on the changed or verified set of positioning estimates performed by the positioning engine, and the UE can update the real-time navigation route information based on the new position of the UE.

[0133] Figure 12 is a flowchart 1200 of a method of wireless communication. The method can be performed by a UE (e.g., UE 104, 404, 802; GNSS device 506; mobile station device 604; apparatus 1304). The method can enable the navigation application of the UE to feed the calculated navigation route information of the UE to the PE of the UE to assist the PE in calculating positioning estimates based on the KF process / algorithm. Then, these positioning estimates can be used by the navigation application to calculate future navigation route information or update the navigation route information, thereby improving the performance and accuracy of positioning.

[0134] At 1204, the UE can use a positioning engine to estimate the current position of the UE based on a set of positioning measurements and a set of time update predictions, such as in conjunction with Figure 8 as described. For example, at 822, the positioning engine module 804 can use the KF process / algorithm to calculate a position estimate of UE 802 (e.g., estimate the positioning of UE 802) based on the set of measurements. In some examples, as shown at 824, the calculation of the positioning estimate can further be based on a set of time update predictions, which can be generated by the dynamic model of UE 802. The estimation of the current position of the UE can be performed by, for example Figure 13 the navigation component 198, the application processor 1306, the cellular baseband processor 1324, and / or the transceiver 1322 of the apparatus 1304 in

[0135] At 1206, the UE can use at least one navigation application to calculate real-time navigation route information based on the current position of the UE, the destination of the UE, and map information, such as in conjunction with Figure 8As described. For example, at 828, the navigation application module 806 may use the positioning estimate from the positioning engine module 804 to calculate a navigation route from the current estimated position of the UE 802 to the destination. In some examples, the calculation of the navigation route may be further based on available map data / information. The calculation of real-time navigation route information using at least one navigation application may be performed by, for example Figure 13 the navigation component 198, the application processor 1306, the cellular baseband processor 1324, and / or the transceiver 1322 of the device 1304 in

[0136] In one example, the real-time navigation route information may at least include a set of estimated future positions and speeds of the UE relative to time.

[0137] In another example, the real-time navigation route information may be further calculated based on real-time crowdsourcing information.

[0138] In another example, the real-time navigation route information is further calculated based on the navigation route type.

[0139] At 1212, the UE may change or verify the set of positioning estimates performed by the positioning engine based on the real-time navigation route information from at least one navigation application, such as in conjunction with Figure 8 As described. For example, at 830, the navigation application module 806 may feed its navigation route information 808 to the positioning engine module 804. The UE 802 or the positioning engine module 804 may change or verify the positioning estimates performed by the positioning engine module 804 based on the navigation route information 808. The change or verification of the set of positioning estimates performed by the positioning engine may be performed by, for example Figure 13 the navigation component 198, the application processor 1306, the cellular baseband processor 1324, and / or the transceiver 1322 of the device 1304 in

[0140] In one example, to change or verify the set of positioning estimates performed by the positioning engine based on the real-time navigation route information, the UE may perform the set of positioning estimates via the positioning engine based on the KF process, and the UE may change the KF time update model associated with the KF process or verify whether there is a measurement error associated with the KF process based on the real-time navigation route information. In such an example, the KF process has a measurement update rate below an update threshold, the KF process includes a number of positioning measurements below a quantity threshold, or the KF process is associated with a time update model including an accuracy level below an accuracy threshold.

[0141] In another example, the UE may perform a set of positioning measurements via at least one of a sensor, an antenna, or RF, such as in conjunction with Figure 8As described. For example, at 820, the UE 802 may use one or more sensors (e.g., IMU sensors, speed sensors, etc.) to measure the speed, acceleration, altitude, and / or orientation of the UE, use the UE's antenna to measure GNSS signals, and / or use one or more sensing components to perform RF sensing. The set of positioning measurements may be performed by, for example Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the apparatus 1304 in

[0142] In another example, the UE may use at least one sensor to verify the validity of real-time navigation route information, such as in combination with Figure 8 as described. For example, for vehicle-related applications / solutions, the camera of the vehicle can be a good sensor for verifying navigation route information. The verification of real-time navigation route information may be performed by, for example Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the apparatus 1304 in Figure 8 as described. For example, when it comes to cameras and computer vision, the navigation route information 808 (e.g., real-time navigation solution) can be used to cross-check with real-time features captured by the camera. The verification of whether at least one feature captured by the UE's camera is associated with an error may be performed by, for example Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the apparatus 1304 in

[0143] In another example, the UE may verify whether the UE's current location is aligned with the real-time navigation route information based on at least one of a map matching function or a sensor fusion function, such as in combination with Figure 8 as described. For example, to perform KF time update using the navigation route information 808, the current positioning of the UE 802 may be specified to accurately reflect on the navigation route planned by the navigation application module 806. Thus, the map matching function / algorithm may be used by the UE 802 to verify whether the current positioning of the UE 802 is (at a specific accuracy level) reflected on the navigation route. The verification of whether the UE's current location is aligned with the real-time navigation route information may be performed by, for example Figure 13 the navigation component 198, application processor 1306, cellular baseband processor 1324, and / or transceiver 1322 of the apparatus 1304 in. In such an example, in the case where the UE's current location is not aligned with the real-time navigation route information, the UE may avoid changing or verifying the set of positioning estimates performed by the positioning engine based on the real-time navigation route information.

[0144] In another example, the UE may calibrate at least one sensor of the UE based on real-time navigation route information, such as in conjunction with Figure 8 as described. For example, if the UE 802 is using one or more IMU sensors to perform dead reckoning, the navigation route information 808 may be used to calibrate the bias of one or more IMU sensors. Calibration of at least one sensor of the UE may be performed by, for example, Figure 13 the navigation component 198, the application processor 1306, the cellular baseband processor 1324, and / or the transceiver 1322 of the apparatus 1304 in

[0145] In another example, the UE may monitor a set of KPIs associated with a positioning engine, wherein in order to change or verify a set of positioning estimates performed by the positioning engine, the UE may change or verify the set of positioning estimates performed by the positioning engine based on the set of KPIs exceeding a threshold.

[0146] In another example, the UE may estimate a new location of the UE based on the changed or verified set of positioning estimates performed by the positioning engine, and the UE may update the real-time navigation route information based on the new location of the UE.

[0147] Figure 13FIG. 1300 is a diagram illustrating an example of a hardware implementation for apparatus 1304. Apparatus 1304 may be a UE, a component of a UE, or may implement UE functionality. In some aspects, apparatus 1304 may include a cellular baseband processor 1324 (also referred to as a modem) coupled to one or more transceivers 1322 (e.g., cellular RF transceivers). The cellular baseband processor 1324 may include on-chip memory 1324'. In some aspects, apparatus 1304 may also include one or more subscriber identity module (SIM) cards 1320 and an application processor 1306, which is coupled to a secure digital (SD) card 1308 and a screen 1310. The application processor 1306 may include on-chip memory 1306'. In some aspects, apparatus 1304 may also include a Bluetooth module 1312, a WLAN module 1314, an SPS module 1316 (e.g., GNSS module), one or more sensor modules 1318 (e.g., barometric pressure sensor / altimeter; motion sensors such as an inertial measurement unit (IMU), gyroscope, and / or accelerometer; light detection and ranging (LIDAR), radio assisted detection and ranging (RADAR), sound navigation and ranging (SONAR), magnetometer, audio, and / or other technologies for positioning), an additional memory module 1326, a power source 1330, and / or a camera 1332. The Bluetooth module 1312, the WLAN module 1314, and the SPS module 1316 may include on-chip transceivers (TRX) (or in some cases, only receivers (RX)). The Bluetooth module 1312, the WLAN module 1314, and the SPS module 1316 may include their own dedicated antennas and / or communicate using antenna 1380. The cellular baseband processor 1324 communicates with UE 104 and / or with a RU associated with network entity 1302 via one or more antennas 1380 through transceiver 1322. The cellular baseband processor 1324 and the application processor 1306 may each separately include computer-readable media / memory 1324', 1306'. The additional memory module 1326 may also be considered computer-readable media / memory. Each computer-readable media / memory 1324', 1306', 1326 may be non-transitory. The cellular baseband processor 1324 and the application processor 1306 are each responsible for general processing, including executing software stored on the computer-readable media / memory. The software, when executed by the cellular baseband processor 1324 / application processor 1306, causes the cellular baseband processor 1324 / application processor 1306 to perform the various functions described above. The computer-readable media / memory may also be used to store data manipulated by the cellular baseband processor 1324 / application processor 1306 when executing the software.The cellular baseband processor 1324 / application processor 1306 can be a component of the UE 350 and can include the memory 360 and / or at least one of the TX processor 368, the RX processor 356, and the controller / processor 359. In one configuration, the device 1304 can be a processor chip (modem and / or application) and include only the cellular baseband processor 1324 and / or the application processor 1306, and in another configuration, the device 1304 can be the entire UE (e.g., see. Figure 3 of 350) and include additional modules of the device 1304.

[0148] As discussed above, the navigation component 198 is configured to estimate the current location of the UE using a positioning engine based on a set of positioning measurements and a set of time update predictions. The navigation component 198 can be further configured to calculate real-time navigation route information using at least one navigation application based on the current location of the UE, the destination of the UE, and map information. The navigation component 198 can be further configured to change or verify the set of positioning estimates performed by the positioning engine based on the real-time navigation route information from at least one navigation application. The navigation component 198 can be within the cellular baseband processor 1324, the application processor 1306, or both within the cellular baseband processor 1324 and the application processor 1306. The navigation component 198 can be one or more hardware components specifically configured to perform the processes / algorithms, implemented by one or more processors configured to perform the processes / algorithms, stored in a computer-readable medium for implementation by one or more processors, or some combination of the above. As shown, the device 1304 can include various components configured for various functions. In one configuration, the device 1304 (and specifically, the cellular baseband processor 1324 and / or the application processor 1306) includes components for estimating the current location of the UE using a positioning engine based on a set of positioning measurements and a set of time update predictions. The device 1304 can also include components for calculating real-time navigation route information using at least one navigation application based on the current location of the UE, the destination of the UE, and map information. The device 1304 can also include components for changing the set of positioning estimates performed by the positioning engine based on the real-time navigation route information from at least one navigation application or for verifying the set of positioning estimates based on the real-time navigation route information.

[0149] In one configuration, the real-time navigation route information can include at least a set of estimated future positions and speeds of the UE relative to time.

[0150] In another configuration, the real-time navigation route information can be further calculated based on real-time crowdsourcing information.

[0151] In another configuration, the real-time navigation route information is further calculated based on the navigation route type.

[0152] In another configuration, the components for changing or validating a set of positioning estimates performed by a positioning engine based on real-time navigation route information include configuring the device 1304 to: perform a set of positioning estimates via the positioning engine based on a KF process, and change a KF time update model associated with the KF process or validate whether there is a measurement error associated with the KF process based on the real-time navigation route information. In this configuration, the KF process has a measurement update rate below an update threshold, the KF process includes a number of positioning measurements below a quantity threshold, or the KF process is associated with a time update model including an accuracy level below an accuracy threshold.

[0153] In another configuration, the device 1304 may further include components for performing a set of positioning measurements via at least one of a sensor, an antenna, or RF.

[0154] In another configuration, the device 1304 may further include components for validating the validity of real-time navigation route information using at least one sensor.

[0155] In another configuration, the device 1304 may further include components for validating whether the current position of the UE is aligned with the real-time navigation route information based on at least one of a map matching function or a sensor fusion function. In this configuration, the device 1304 may further include components for avoiding changing or validating a set of positioning estimates performed by the positioning engine based on the real-time navigation route information when the current position of the UE is not aligned with the real-time navigation route information.

[0156] In another configuration, the device 1304 may further include components for calibrating at least one sensor of the UE based on the real-time navigation route information.

[0157] In another configuration, the device 1304 may further include components for validating whether at least one feature captured by a camera of the UE is associated with an error based on the real-time navigation route information.

[0158] In another configuration, the device 1304 may further include components for monitoring a set of KPIs associated with the positioning engine, wherein the components for changing or validating a set of positioning estimates performed by the positioning engine include configuring the device 1304 to: change or validate a set of positioning estimates performed by the positioning engine based on the set of KPIs exceeding a threshold.

[0159] In another configuration, the device 1304 may further include components for estimating a new position of the UE based on the changed or validated set of positioning estimates performed by the positioning engine and components for updating the real-time navigation route information based on the new position of the UE.

[0160] The component can be the navigation component 198 of the device 1304 configured to perform the functions described by the component. As described above, the device 1304 can include a TX processor 368, an RX processor 356, and a controller / processor 359. Thus, in one configuration, the component can be the TX processor 368, the RX processor 356, and / or the controller / processor 359 configured to perform the functions described by the component.

[0161] It should be understood that the specific order or hierarchy of the blocks in the disclosed process / flowchart is merely illustrative of example approaches. It should be understood that based on design preferences, the specific order or hierarchy of the blocks in the process / flowchart can be rearranged. Additionally, some blocks can be combined or omitted. The appended method claims present the elements of the various blocks in a sample order, but are not limited to the specific order or hierarchy presented.

[0162] The foregoing description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects. Thus, the claims are not limited to the aspects described herein, but are to be accorded the full scope consistent with the language of the claims. References to elements in the singular form are not intended to mean "one and only one" unless specifically stated, but rather "one or more." Terms such as "if," "when," and "while" do not imply a direct temporal relationship or reaction. That is, these phrases (e.g., "when...") do not imply an immediate action in response to the occurrence of an action or during the occurrence of an action, but simply imply that the action will occur if the condition is met, without requiring a specific or immediate time limitation for the occurrence of the action. The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any aspect described herein as "exemplary" is not necessarily to be construed as preferred or having an advantage over other aspects. Unless specifically stated, the term "some" refers to one or more. Combinations such as "at least one of A, B, or C," "one or more of A, B, or C," "at least one of A, B, and C," "one or more of A, B, and C," and "any combination of A, B, C, or any of them," including any combination of A, B, and / or C, may include multiple A's, multiple B's, or multiple C's. Specifically, combinations such as "at least one of A, B, or C," "one or more of A, B, or C," "at least one of A, B, and C," "one or more of A, B, and C," and "any combination of A, B, C, or any of them" may be only A, only B, only C, A and B, A and C, B and C, or A and B and C, where any such combination may include one or more members of A, B, or C. A set should be construed as a collection of elements, where the number of elements is one or more. Thus, for a set of X, X will include one or more elements. If a first device receives data from or transmits data to a second device, the data may be received / transmitted directly between the first device and the second device, or indirectly between the first device and the second device through a collection of devices. All structural and functional equivalents of the elements of the aspects described throughout this disclosure that are known or will later be known to those of ordinary skill in the art are expressly incorporated herein by reference and are covered by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public, whether or not such disclosure is expressly recited in the claims. The words "module," "mechanism," "element," "device," etc. do not substitute for the word "component." Thus, no claim element shall be construed as a means-plus-function unless the element is expressly recited using the phrase "means for..."

[0163] As used herein, the phrase "based on" should not be construed to refer to a closed set of information, one or more conditions, one or more factors, etc. In other words, the phrase "based on A" (where "A" can be information, a condition, a factor, etc.) should be construed as "at least based on A", unless specifically stated otherwise.

[0164] The following aspects are merely illustrative and can be combined with other aspects or teachings described herein without limitation.

[0165] Aspect 1 is a method for wireless communication at a UE, the method comprising: using a positioning engine to estimate a current position of the UE based on a set of positioning measurements and a set of time update predictions; using at least one navigation application to calculate real-time navigation route information based on the current position of the UE, a destination of the UE, and map information; and changing or validating a set of positioning estimates performed by the positioning engine based on the real-time navigation route information from the at least one navigation application.

[0166] Aspect 2 is the method according to aspect 1, the method further comprising: performing the set of positioning measurements via at least one of a sensor, an antenna, or radio frequency.

[0167] Aspect 3 is the method according to aspect 1 or 2, wherein the real-time navigation route information at least includes a set of estimated future positions and speeds of the UE relative to time.

[0168] Aspect 4 is the method according to any one of aspects 1 to 3, wherein changing or validating the set of positioning estimates performed by the positioning engine based on the real-time navigation route information includes: performing the set of positioning estimates via the positioning engine based on a KF process; and changing a KF time update model associated with the KF process or validating the existence of a measurement error associated with the KF process based on the real-time navigation route information.

[0169] Aspect 5 is the method according to aspect 4, wherein the KF process has a measurement update rate below an update threshold, the KF process includes a number of positioning measurements below a quantity threshold, or the KF process is associated with a time update model including an accuracy level below an accuracy threshold.

[0170] Aspect 6 is the method according to any one of aspects 1 to 5, the method further comprising: using at least one sensor to verify the validity of the real-time navigation route information.

[0171] Aspect 7 is the method according to any one of aspects 1 to 6, wherein the real-time navigation route information is further calculated based on real-time crowdsourcing information.

[0172] Aspect 8 is the method according to any one of Aspects 1 to 7, the method further comprising: verifying whether the current location of the UE is aligned with the real-time navigation route information based on at least one of a map matching function or a sensor fusion function.

[0173] Aspect 9 is the method according to Aspect 8, the method further comprising: in the case where the current location of the UE is not aligned with the real-time navigation route information, avoiding changing or verifying the set of positioning estimates executed by the positioning engine based on the real-time navigation route information.

[0174] Aspect 10 is the method according to any one of Aspects 1 to 9, the method further comprising: calibrating at least one sensor of the UE based on the real-time navigation route information.

[0175] Aspect 11 is the method according to any one of Aspects 1 to 10, the method further comprising: verifying whether at least one feature captured by the camera of the UE is associated with an error based on the real-time navigation route information.

[0176] Aspect 12 is the method according to any one of Aspects 1 to 11, the method further comprising: monitoring a set of KPIs associated with the positioning engine; wherein changing or verifying the set of positioning estimates executed by the positioning engine includes: changing or verifying the set of positioning estimates executed by the positioning engine based on the set of KPIs exceeding a threshold.

[0177] Aspect 13 is the method according to any one of Aspects 1 to 12, wherein the real-time navigation route information is further calculated based on a navigation route type.

[0178] Aspect 14 is the method according to any one of Aspects 1 to 13, the method further comprising: estimating a new location of the UE based on the changed or verified set of positioning estimates executed by the positioning engine; and updating the real-time navigation route information based on the new location of the UE.

[0179] Aspect 15 is a device for wireless communication at a UE, the device comprising: a memory; and at least one processor coupled to the memory, and at least partially based on information stored in the memory, the at least one processor being configured to implement any one of Aspects 1 to 14.

[0180] Aspect 16 is the device according to Aspect 15, the device further comprising: at least one of a transceiver or an antenna coupled to the at least one processor.

[0181] Aspect 17 is a device for wireless communication, the device comprising: components for implementing any one of Aspects 1 to 14.

[0182] Aspect 18 is a computer-readable medium (e.g., a non-transitory computer-readable medium) storing computer-executable code, where the code, when executed by a processor, causes the processor to implement any one of aspects 1 to 14.

Claims

1. An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: a memory; and at least one processor coupled to the memory and configured to, at least in part based on second information stored in the memory: estimate a current location of the UE using a positioning engine based on a set of positioning measurements and a set of time update predictions; calculate real-time navigation route information using at least one navigation application based on the current location of the UE, a destination of the UE, and map information; and change or verify a set of positioning estimates performed by the positioning engine based on the real-time navigation route information from the at least one navigation application.

2. The apparatus according to claim 1, wherein the at least one processor is further configured to: perform the set of positioning measurements via at least one of a sensor, an antenna, or radio frequency (RF).

3. The apparatus according to claim 1, wherein the real-time navigation route information at least includes a set of estimated future locations and speeds of the UE relative to time.

4. The apparatus according to claim 1, wherein, in order to change or verify the set of positioning estimates performed by the positioning engine based on the real-time navigation route information, the at least one processor is configured to: perform the set of positioning estimates via the positioning engine based on a Kalman filter (KF) process; and change a KF time update model associated with the KF process or verify the existence of a measurement error associated with the KF process based on the real-time navigation route information.

5. The apparatus according to claim 4, wherein the KF process has a measurement update rate below an update threshold, the KF process includes a number of positioning measurements below a quantity threshold, or the KF process is associated with a time update model having an accuracy level below an accuracy threshold.

6. The apparatus according to claim 1, wherein the at least one processor is further configured to: verify the validity of the real-time navigation route information using at least one sensor.

7. The apparatus according to claim 1, wherein, in order to calculate the real-time navigation route information, the at least one processor is configured to: further calculate the real-time navigation route information based on real-time crowdsourcing information.

8. The apparatus according to claim 1, wherein the at least one processor is further configured to: verify whether the current location of the UE is aligned with the real-time navigation route information based on at least one of a map matching function or a sensor fusion function.

9. The apparatus according to claim 8, wherein the at least one processor is further configured to: avoid changing or verifying the set of positioning estimates performed by the positioning engine based on the real-time navigation route information when the current location of the UE is not aligned with the real-time navigation route information.

10. The apparatus according to claim 1, wherein the at least one processor is further configured to: calibrate at least one sensor of the UE based on the real-time navigation route information.

11. The apparatus according to claim 1, wherein the at least one processor is further configured to: Verify whether at least one feature captured by the UE's camera is associated with an error based on the real-time navigation route information.

12. The apparatus according to claim 1, wherein the at least one processor is further configured to: Monitor a set of key performance indicators (KPIs) associated with the positioning engine; Wherein, in order to change or verify the set of positioning estimates performed by the positioning engine, the at least one processor is configured to change or verify the set of positioning estimates performed by the positioning engine based on the set of KPIs exceeding a threshold.

13. The apparatus according to claim 1, wherein the at least one processor is further configured to: Calculate the real-time navigation route information further based on the navigation route type.

14. The apparatus according to claim 1, wherein the at least one processor is further configured to: Estimate a new position of the UE based on the changed or verified set of positioning estimates performed by the positioning engine; and Update the real-time navigation route information based on the new position of the UE.

15. A method for wireless communication at a user equipment (UE), the method comprising: Estimate a current position of the UE using a positioning engine based on a set of positioning measurements and a set of time update predictions; Calculate real-time navigation route information using at least one navigation application based on the current position of the UE, the destination of the UE, and map information; And Change or verify a set of positioning estimates performed by the positioning engine based on the real-time navigation route information from the at least one navigation application.

16. The method according to claim 15, the method further comprising: Perform the set of positioning measurements via at least one of a sensor, an antenna, or radio frequency (RF).

17. The method according to claim 15, wherein the real-time navigation route information at least includes a set of estimated future positions and speeds of the UE relative to time.

18. The method according to claim 15, wherein changing or verifying the set of positioning estimates performed by the positioning engine based on the real-time navigation route information includes: Performing the set of positioning estimates via the positioning engine based on a Kalman filter (KF) process; And Changing a KF time update model associated with the KF process or verifying the existence of a measurement error associated with the KF process based on the real-time navigation route information.

19. The method according to claim 18, wherein the KF process has a measurement update rate lower than an update threshold, the KF process includes a number of positioning measurements lower than a quantity threshold, or the KF process is associated with a time update model including an accuracy level lower than an accuracy threshold.

20. The method according to claim 15, the method further comprising: Verify the validity of the real-time navigation route information using at least one sensor.

21. The method according to claim 15, wherein the real-time navigation route information is further calculated based on real-time crowdsourcing information.

22. The method according to claim 15, the method further comprising: Verifying whether the current location of the UE is aligned with the real-time navigation route information based on at least one of a map matching function or a sensor fusion function.

23. The method according to claim 22, the method further comprising: In the case where the current location of the UE is not aligned with the real-time navigation route information, avoiding changing or verifying the set of positioning estimates performed by the positioning engine based on the real-time navigation route information.

24. The method according to claim 15, the method further comprising: Calibrating at least one sensor of the UE based on the real-time navigation route information.

25. The method according to claim 15, the method further comprising: Verifying whether at least one feature captured by a camera of the UE is associated with an error based on the real-time navigation route information.

26. The method according to claim 15, the method further comprising: Monitoring a set of key performance indicators (KPIs) associated with the positioning engine; Wherein changing or verifying the set of positioning estimates performed by the positioning engine includes: changing or verifying the set of positioning estimates performed by the positioning engine based on the KPI set exceeding a threshold.

27. The method according to claim 15, wherein the real-time navigation route information is further calculated based on a navigation route type.

28. The method according to claim 15, the method further comprising: Estimating a new location of the UE based on the changed or verified set of positioning estimates performed by the positioning engine; And Updating the real-time navigation route information based on the new location of the UE.

29. An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: Components for using a positioning engine to estimate the current location of the UE based on a set of positioning measurements and a set of time update predictions; Components for calculating real-time navigation route information using at least one navigation application based on the current location of the UE, the destination of the UE, and map information; And Components for changing or verifying the set of positioning estimates performed by the positioning engine based on the real-time navigation route information from the at least one navigation application.

30. A computer-readable medium that stores computer-executable code at a user equipment (UE), the code causing the processor, when executed by the processor, to: Use a positioning engine to estimate the current location of the UE based on a set of positioning measurements and a set of time update predictions; Calculate real-time navigation route information using at least one navigation application based on the current location of the UE, the destination of the UE, and map information; And Change or verify the set of positioning estimates performed by the positioning engine based on the real-time navigation route information from the at least one navigation application.

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