Network-assisted self-positioning of mobile communication devices

Abstract

A location of the mobile communication device is determined. This involves the mobile communication device (101, 551, 801, QQ110) performing receiving (701), from a network node (113, 563, 803, QQ160) serving the mobile communication device (101, 551, 801, QQ110), a request (321, 513, 525) to sense the local area (201) in accordance with one or more parameters that guide how and / or where sensing is to be performed. Sensing data is generated (703) by performing (323, 515, 527) sensing in accordance with one or more parameters in response to a request to sense the local area. The sensing data is delivered (705) to the network node (113, 563, 803, QQ160). In response to delivering the sensed data to the network node (113, 563, 803, QQ160), a location (215) of the mobile communication device (101, 551, 801, QQ110) is received (707).

Description

Technical Field

[0001] The present invention relates to techniques for enabling a mobile communication device to obtain information indicative of its location, and more particularly, to techniques for determining the location of a mobile communication device using guidance from a network node when sensing a local area. Background Art

[0002] Applications in modem-equipped devices increasingly need to know their own geographic location ("self-location") with high accuracy. There are several radio-based positioning technologies related to cellular communications and Bluetooth-compatible technologies that provide positioning accuracy of several meters (in some cases better). In U.S. Patent Publication No. US20170307746A1 (published in 2017), the vehicle compares a radar map with a reference data map to locate itself. In U.S. Patent Publication No. US20190171224A1 (published in 2019), the vehicle creates a map of its environment in a first step and then uses environmental features and static reflections to locate itself; non-stationary objects are identified to avoid positioning errors. The cited patent document mentions: Relative velocity (self-motion) can be derived based on direct measurement of the radial velocity of the reflection point from the stationary object measured relative to the observer. This also allows the determination of rotation when multiple spatially distributed radar sensors are used. Liu et al. used deterministic and random radar responses to build an environmental map and locate the radar in "ARadar-Based Simultaneous Localization and Mapping Paradigm for Scattering Map Modeling" published at the IEEE Asia-Pacific Antennas and Propagation Conference (APCAP) (2018, Auckland, New Zealand). U.S. Patent Publication No. US20200233280A1 discloses a method for determining the location of a vehicle by matching radar detection points with a predetermined navigation map, which includes elements representing static landmarks around the vehicle. The disclosure also mentions that "the navigation map can be derived from a global database based on a given position of the vehicle, such as from the vehicle's global positioning system." The method described by Marck et al. in "Indoor Radar SLAM A Radar Application For Vision And GPS Denied Environments" at the European Microwave Conference in Nuremberg, Germany (2013) involves feeding radar images into a mapping and positioning algorithm and using an iterative closest point algorithm to determine radar position and movement, while a particle filter optimizes measurement performance. As shown in Marck et al., radar-based simultaneous localization and mapping (SLAM) typically requires 360-degree panoramic high-resolution range information, which can be achieved by radar devices with rotating antennas or electronically scanned phased array radars.

[0003] In another disclosure, U.S. Patent Publication No. US 20200256977A1 ​​(published in 2020) describes a vehicle that uses at least one radar sensor to generate an environmental map, and then compares its current measurements with the generated map to locate itself. As similarly disclosed in U.S. Patent Publication No. US20200232801A1, the vehicle uses radar to create a local map, and then retrieves the environmental map and correlates the two to locate itself. And as described in U.S. Patent Publication No. US20190384318A1, the device uses radar signals to create a local grid map and compares it with a map stored in the device's memory to locate itself.

[0004] Other sensor options for positioning include the use of cameras, where technologies such as SLAM can support more precise relative positions. Information from different sensors can be combined in what is known as sensor fusion. Using radar-based SLAM, a device can map an unknown environment and localize itself in that environment.

[0005] There are many problems associated with traditional positioning techniques. For example, radio-based positioning relies entirely on communication between one or a few base stations or anchors and the device, which can only produce results accurate to within a few meters unless a large number of anchor transmitters are provided, clock synchronization is very accurate, or certain assumptions can be made about the environment or relative positions. Such systems scale poorly in terms of accuracy (inconsistent, best around 2 meters, but sometimes around several meters) and cost. In addition, the location of the base stations or access points needs to be known very accurately, which increases the cost of installation and may cause problems if these base stations or access points are later moved.

[0006] Since the primary goal of indoor base station deployment is to meet the coverage of communication services, there are likely to be significant gaps in coverage in areas where sufficiently accurate positions can be obtained. In some cases, it may even lead to areas and locations where traditional positioning technologies do not work well (even though communication may still be possible in some cases).

[0007] An alternative approach, sensor fusion, which combines sensor data from SLAM with data derived, for example, from radio-based positioning, GPS and / or cameras and inertial measurement units (IMUs) for changes in motion can achieve high accuracy but requires multiple sensors, which significantly increases complexity, cost, printed circuit board (PCB) area, and device size.

[0008] And in any case, traditional radar self-positioning methods may not work at all, or at best cannot guarantee high accuracy in certain situations, such as when the device is located in (or moving along) a long corridor where there are no clear landmark structures for the device to detect and determine distance, and when the device moves, the structures and distances within a short distance are constant.

[0009] Another problematic situation arises when the device is located in a very large room where the objects of interest are very far away. In this case, the device may be able to detect the structure via radar, but their distance results in lower sensing accuracy than when the structure is located very close to the device's location. In principle, structures in the ceiling can be used as sensing landmarks by directing the radar upwards, but most of the time there are panels that provide a very flat surface with few obvious structural features. Typical radar sensing has difficulty finding structures from behind such ceiling panels.

[0010] Another scenario that creates difficulties for self-localization occurs in open areas that are primarily occupied by moving people and / or objects that may block traditional radar signals and therefore hide static reference objects that the radar would otherwise detect. Without such detection, traditional radar-assisted localization techniques lack the sensing information that would otherwise be compared to known reference structures with known locations to determine the location of the device.

[0011] In general, indoor walls, floors, ceilings and highly regular areas (such as corridors) typically present a very flat, regular, featureless appearance, and this complicates radar-assisted localization unless there are other significant, unique objects and structures within the sensing distance with known locations.

[0012] PCT Publication No. WO 2017139432 (published on February 9, 2017) proposes a solution for fingerprinting depth-based local sensor data using geometrically structured map data. Fingerprinting is based on geometric analysis. Radar is considered as one of many different types of potential sensors that can be used to generate depth information. However, fingerprinting is not based on radar signals.

[0013] Patent publication number US20190171224A1 (published on June 6, 2019) proposes a radar-based technique for fine-tuning the own position, which is based on first creating a map of the environment and then fine-tuning the own position by correlating with the map. Both map creation and fine-tuning are performed by the device. The target area is, for example, a vehicle for the purpose of achieving autonomous parking.

[0014] Liu, X. et al., "A Radar-Based Simultaneous Localization and Mapping Paradigm for Scattering Map Modeling", IEEE Asia Pacific Conference on Antennas and Propagation (APCAP), Auckland, New Zealand (2018), and Marck et al., "Indoor radar SLAM A radar application for vision and GPS denied environments", European Microwave Conference, Nuremberg, Germany (2013), describe investigations showing that radar SLAM may be used for localization. However, such use requires very intensive radar usage and is therefore an excessive consumption of energy and processing resources if used only to perform self-localization in fast situations with relatively small amounts of modem activity.

[0015] Therefore, there is a need for self-positioning technology that solves the above-mentioned and / or related problems. Summary of the invention

[0016] It should be emphasized that the terms "include" and "comprising" when used in this specification are used to specify the presence of the features, integers, steps or components; but the use of these terms does not exclude the presence or addition of one or more other features, integers, steps, components or groups thereof.

[0017] In addition, in some instances (e.g., in the claims and summary of the invention), reference numerals may be provided to help identify various steps and / or elements. However, the use of reference numerals is not intended to attribute or suggest that the steps and / or elements so referenced will be performed or operated in any particular order.

[0018] According to one aspect of the present invention, the foregoing and other objects are achieved in a technique (e.g., method, apparatus, non-transitory computer-readable storage medium, program component) for determining a location of a mobile communication device. Determining the location includes the mobile communication device receiving a request from a network node serving the mobile communication device to sense a local area according to one or more parameters that direct how and / or where to perform sensing, and in response to the request to sense the local area, generating sensing data by performing sensing according to the one or more parameters. The sensing data is delivered to the network node. In response to delivering the sensing data to the network node, receiving the location of the mobile communication device.

[0019] In another aspect consistent with some but not necessarily all embodiments of the present invention, location determination includes initially obtaining or generating a coarse location of the mobile communication device, wherein the coarse location indicates with a certain accuracy that the mobile communication device is located within a local area portion of a reference coordinate system; and providing the coarse location to a network node, wherein the coarse location is less accurate than the received location; and the received request to sense the local area is responsive to providing the coarse location to the network node. In some but not necessarily all such embodiments, the mobile communication device provides a confidence measure about the accuracy of the coarse location to the network node. And in some but not necessarily all additional embodiments, location determination also includes generating the coarse location of the mobile communication device using non-radar based sensing.

[0020] In yet another aspect consistent with some but not necessarily all embodiments of the invention, the sensing of the local area is radar sensing of the local area; and the one or more parameters define an orientation to be assumed by the first mobile communication device when performing the radar sensing of the local area.

[0021] In yet another aspect consistent with some but not necessarily all embodiments of the invention, the local area sensing is local area radar sensing; and the one or more parameters define a location where the local area radar sensing is to be performed.

[0022] In another aspect consistent with some but not necessarily all embodiments of the invention, the sensing of the local area is millimeter wave synthetic aperture radar (mmWave SAR) sensing. In some but not necessarily all such embodiments, the one or more parameters define a direction and / or orientation and / or device trajectory to be applied when performing mmWave SAR sensing.

[0023] In yet another aspect consistent with some but not necessarily all embodiments of the invention, the sensing of the local area is based on non-radar sensing. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Objects and advantages of the present invention will be understood from the following detailed description read in conjunction with the accompanying drawings, in which:

[0025] Figure 1 is a block diagram of an exemplary system consistent with an embodiment of the invention.

[0026] Figure 2 An exemplary WR frame is shown.

[0027] Figure 3A is a signaling diagram illustrating aspects of a class of embodiments consistent with the present invention.

[0028] Figure 3B is a signaling diagram illustrating aspects of an alternative class of embodiments consistent with the present invention.

[0029] Figure 4 An example is shown when a mobile device (UE) is in a surrounding area.

[0030] Figure 5 is a signaling diagram illustrating aspects of an alternative class of embodiments consistent with the present invention.

[0031] Figure 6 In one aspect is a flow diagram of actions performed by a server according to various embodiments consistent with the invention.

[0032] Figure 7 In one aspect is a flow diagram of actions performed by an exemplary mobile communication device configured to perform sensing in accordance with various embodiments to generate data that can be analyzed to estimate a location of the mobile communication device.

[0033] Figure 8 is a signaling diagram illustrating aspects of an alternative class of embodiments consistent with the present invention.

[0034] Fig. 9 Details of a network node are shown in accordance with one or more embodiments.

[0035] Fig.10 Details of a wireless device are shown in accordance with one or more embodiments. DETAILED DESCRIPTION

[0036] The various features of the present invention will now be described with reference to the drawings, wherein like components are identified with the same reference numerals.

[0037] Various aspects of the present invention will now be described in more detail in conjunction with a number of exemplary embodiments. In order to facilitate understanding of the present invention, many aspects of the present invention are described in terms of a sequence of actions performed by a computer system or other hardware elements capable of executing programming instructions. It will be appreciated that in each embodiment, various actions may be performed by a dedicated circuit (e.g., analog and / or discrete logic gates interconnected to perform a dedicated function), by one or more processors programmed with an appropriate instruction set, or by a combination of the two. The term "circuit is configured to" perform one or more described actions is used here to refer to any such embodiment (i.e., separate one or more dedicated circuits, one or more programmed processors, or any combination of these). In addition, the present invention may also be considered to be fully embodied in any form of non-transitory computer-readable carrier, such as a solid-state memory, a disk or an optical disk, which contains a suitable set of computer instructions that will cause the processor to perform the technology described herein. Therefore, various aspects of the present invention may be embodied in many different forms, and all such forms are considered to be within the scope of the present invention. For each of the various aspects of the present invention, any such form of embodiment as described above may be referred to herein as "logic is configured to" perform the described actions, or alternatively referred to as "logic" that performs the described actions.

[0038] The technology described herein addresses the need for devices to be able to obtain their own precise positioning (so-called "self-positioning") in areas where today's typical technologies (e.g., GPS) do not perform well enough (e.g., in urban canyons, indoors, on factory floors, etc.). Moreover, the goal is to do so without requiring sensing capabilities other than radar (which can be provided by a modem with radar capabilities, or by a separate radar module incorporated into the device). In some but not necessarily all embodiments, an accelerometer or compass may be used in addition. But in all such embodiments, the technology does not require any cameras or expensive base station networks or other high-cost network-based positioning devices.

[0039] The various embodiments described herein are capable of deriving self-positioning information with centimeter-range accuracy when relatively close to objects and structures (several meters away), and slightly lower accuracy when the objects are far away.

[0040] In one aspect of the embodiments described herein, a world reference (WR) map is obtained based on at least other radio-based positioning solutions that can achieve 5-10 meter accuracy (possibly better, but also possibly worse). Starting from the WR map, the information obtained by radar scanning is used to fine-tune the device's own position in the WR framework. In the following, the term "WRP" is used to refer to the world reference position estimated according to a standardized radio-based method, such as but not limited to the observed time difference of arrival ("OTDOA") (other methods can be used to determine the WRP, see the examples below). The term "WR frame" is used herein to refer to a local area around the WRP as defined by the estimated accuracy of the WRP. For example, if the accuracy of the WRP is estimated to be ±5 meters, then the WR frame is an area defined by the WRP of ±5 meters in each direction. More generally, the WR frame is an exemplary embodiment of a local area portion of a reference coordinate system (in this embodiment, a world reference map).

[0041] Fine-tuning its position within the WR framework is accomplished by capturing radar responses according to appropriate settings, uploading the captured radar responses to a Mobile Edge Server Function (MEF), and applying a correlation method (e.g., fingerprinting or correlation relative to map information, or a combination thereof) where the provided radar data is correlated with prior information about the environment. Because the MEF knows that the device is within the WR framework area, it only needs to correlate relative to that area. This can achieve the desired level of positioning accuracy.

[0042] An important aspect consistent with embodiments of the present invention is the offloading of processing within the MEF and the data made available in the MEF, enabling a large set of different optimizations and improvements. Furthermore, with this approach the MEF will have very accurate information about the locations of all devices, as well as estimates of their trajectories, which can be useful for many different tasks and optimizations, and can be included in correlations that provide further information about the dynamics of the environment due to moving objects.

[0043] There are many different embodiments that apply the above aspects, and these embodiments are discussed further below.

[0044] Figure 1 is a block diagram of an exemplary system 100 consistent with an embodiment of the invention. The exemplary system 100 includes:

[0045] - mobile communication devices (or user equipment - UE) 101-1, 101-2, each comprising a modem 103 and provided with a radar functionality 105 (by using the modem 103 or by using e.g. Figure 1 In any particular embodiment, there may be more or fewer such devices.

[0046] - A cellular communication system 107, including a base station 109 with which the devices 101-1, 101-2 communicate. The system 100 also includes or has access to positioning support 111 according to some conventional technology (eg, GPS, OTDOA, etc.). The positioning support 111 provides coarse-grained location information to implement the WRP and WR frameworks.

[0047] - Mobile edge server 113, which is a server preferably located at base station 109, for providing services local to the area served by base station 109 and with lower latency than over-the-top to a more distant data center (not shown). Mobile edge server 113 is preferably located at base station 109, but its location is neither a necessary nor essential aspect of embodiments of the present invention.

[0048] - Device attitude (also called "orientation") estimator 115, for example using an IMU onboard the device (very accurate), or alternatively calculated based on beam alignment towards a known reference (lower accuracy), or in another alternative using radio-based angle measurements (medium accuracy): using the beam direction from the UE antenna panel towards the base station 109 as a reference in the spatial domain. Angle of arrival (AoA) and angle of departure (AoD) can be used together with round trip time (RTT) measurements to produce a rough position towards the base station 109 and panel attitude.

[0049] These elements will be discussed further below.To simplify the description, mobile communication devices will be collectively referred to as mobile communication devices 101 unless it is necessary to distinguish one mobile communication device from another (eg, distinguishing a first mobile communication device 101-1 from a second mobile communication device 101-2).

[0050] Mobile Devices / UE 101

[0051] It is advantageous to utilize a mobile communication device 101 equipped with radar functionality 105. Such functionality may be implemented as, for example, separate circuits and / or components. However, it is more advantageous to achieve this with the aid of a modem 103 which is configured not only to perform communication functions but also to generate and transmit radar beams 117 and to receive reflected radar signals. In a preferred embodiment, the UE modem 103 extends radar capabilities according to known techniques. One such teaching is found in PCT patent application number PCT / EP2020 / 069491. The cost of adding radar functionality over the cost of a normal 5G modem is minimal due to the ability to share antenna panels that occupy valuable space in the device. This means that the modem 103 can be used for the three essential functions of a positioning system:

[0052] - communicate with functions in the base station 109 and the mobile edge server 113;

[0053] - Use network-based positioning 111 for coarse-grained WRP or WR frameworks (see above);

[0054] - Improved quality / accuracy of positioning, as radar sensing can be done at different frequencies, with different beam directions, and with different signaling types and durations, with no or minimal impact on any current 5G communications.

[0055] In some, but not necessarily all, alternative embodiments, radar functionality 105 is implemented as a separate module that needs to be carefully configured to coexist with the 5G modem (without causing significant interference) in order to perform joint operations as described herein. This increases cost and complexity.

[0056] In a further alternative, it should be noted that although reference is made herein to a 5G compliant modem, a person of ordinary skill in the art will readily appreciate that modems compliant with other communication standards or generations of the 3GPP standard may alternatively be used.

[0057] A UE 101 with the above capabilities will typically be used in autonomous vehicles or other mobile units that require high-precision positioning, such as autonomous vehicles deployed in indoor environments (e.g., autonomous transport vehicles in a fully autonomous factory, surveillance drones in factories or dense urban areas, or autonomous transport vehicles in ports, where GPS positioning may be very poor due to off-site line conditions (partially indoors, building walls, high container stacks, etc.).

[0058] For autonomous vehicles, a mobile device may be aware of positioning needs (e.g., frequency and purpose of use), and therefore its positioning functionality may be context-based. For example, a mobile unit that is stationary will also be able to stop or reduce positioning attempts, thereby saving power and freeing up valuable resources. A mobile unit that is close to a structure (such as a large machine on a factory floor) may require more accurate positioning, with the level of accuracy depending on its moving speed. A mobile device that is far away from any structure may have lower requirements for positioning accuracy because it will not be in danger of colliding with any object soon. Therefore, for it to move to a predetermined coordinate, a high-precision position will not be required (assuming that the positioning accuracy can be improved as it approaches its target location).

[0059] The mobile device 101 may be equipped with an IMU or accelerometer, gyro sensor or compass for estimating 115 the orientation of the device and estimating the direction of the radar beam. However, alternative embodiments lacking such support are also described below.

[0060] Cellular systems and base stations 109 support

[0061] There are many known methods of network-based positioning that are capable of providing a coarse-grained position of the mobile communication device 101. Such methods include, for example, the use of observed time difference of arrival (OTDOA), uplink arrival timing (ToA), enhanced cell ID (E-CID), round trip time (RTT) measurements, angle of arrival (AoA) and angle of departure (AoD). Accuracies of 5-10 meters (possibly better, but not guaranteed) can be achieved with radio positioning solutions. The idea adopted in embodiments consistent with the present invention is to use a rough estimate of the position as the World Reference Position (WRP), and then use further sensing (e.g. radar sensing) to fine-tune the position within the WR framework centered on the WRP.

[0062] In the following, the term WRP is used to refer to the world reference position estimated according to a standardized radio-based method (e.g., OTDOA). Other coarse positioning methods can be used as alternatives (see examples below). The term WR frame used in this article refers to the area around the WRP as defined by the estimated accuracy of the WRP (the estimate of accuracy can be based on the method used, the deployment characteristics, and estimates of key components that constitute uncertainty, such as synchronization errors). For example, if the accuracy of the WRP is estimated to be ±5 meters, the WR frame is an area defined by a region centered on the WRP and extending ±5 meters from it in each direction.

[0063] To further illustrate this point, Figure 2 An exemplary WR frame 201 is shown, which is a local area portion of a (larger) reference coordinate system 209. The reference coordinate system 209 is typically much larger (e.g., multiple orders of magnitude larger) than the local area portion 201, and therefore it should be understood that Figure 2 The aspects depicted are not drawn to scale.

[0064] As shown, UE 203 is located at position 207. A rough estimate 211 of its position (WRP) is also shown with an actual error 205 as shown. However, when the rough estimate WRP is estimated, all that is known is that its accuracy is some amount ±ε. For this reason, WR frame 201 is centered around the rough estimate WRP 211. (Note: WR frame 201 may alternatively be another shape, such as a circle. Its particular shape is not an essential aspect of the inventive embodiments.)

[0065] Mobile Edge Function (MEF)

[0066] In some inventive embodiments, a mobile edge server 113 located within a cellular system, such as at a base station 109, is an important element. In one aspect, the mobile edge server 113 has access to a reference map 213 that represents objects and features that sensing is expected to detect within different local area portions 201 of a reference coordinate system 209. It is capable of managing the processing of provided sensor information (e.g., radar signal information provided by a mobile communication device 101) and correlating it with prior data, map information, and other environmental knowledge in order to improve a rough estimate 211 of the location 207 of the mobile communication device. In some but not necessarily all embodiments, the rough estimate 211 of the location is provided to the mobile communication device 101. And in one aspect consistent with embodiments of the present invention, the mobile edge server 113 generates guidance for further sensing in the vicinity of the mobile communication device in order to generate relevant sensing information that can be used to improve the first location estimate (i.e., the rough location) 211 into a more accurate second location estimate 215. The guidance for further sensing can be provided to the mobile communication device 101 via the base station 109. Furthermore, since it communicates with all UEs and knows their locations, further optimizations can be applied system-wide. These aspects are further described below.

[0067] exist Figure 1 In the exemplary embodiment shown, the mobile edge server 113 is an independent entity. However, in alternative embodiments, the mobile edge server 113 can be implemented as an extension of the functionality in the base station 109, or can even be disposed on an Internet-connected server outside the functionality of the base station 109. All such alternatives are considered to be within the scope of the inventive embodiments. However, it is to be noted that given the local relevance of the mobile edge server functionality and the short latency in communication with the UE, it is advantageous for this functionality to be co-located with the base station 109. For limited geographic areas, a database with map information and historical data and optimization based on knowledge of all UEs in the area can be effectively implemented. In addition, for a co-located system, the performance-degrading latency is also significantly less compared to a remote over-the-top data center.

[0068] Later in this description, it is also noted that in some alternative embodiments consistent with the present invention, some mobile edge functionality may be handled in the mobile device itself. However, such embodiments may be less efficient than other embodiments.

[0069] Although in a typical implementation it may be assumed that the mobile edge functionality serves one base station, there are no major obstacles preventing the mobile edge functionality from serving many base stations. Even if the map and correlation and statistics are related to a local area, there may be several antenna sites served by one base station 109 and one mobile edge server 113. In the following, the systems, solutions and examples assume one mobile edge server 113 for this functionality, but the scope of the invention is not limited to having only one such mobile edge server 113 for this purpose.

[0070] To illustrate some aspects of the invention embodiments, reference will now be made to Figure 3A Features depicted with dashed lines and boxes represent aspects that are optional for this exemplary embodiment.

[0071] 1. Device 101: Begins self-positioning (step 301), and accordingly, a request for a network-based location is delivered to base station 109 (step 303). The network performs positioning techniques that produce a coarse-grained location of mobile device 101 (step 305). Coarse-grained positioning techniques are known in the art, and all such techniques are considered to be within the scope of embodiments of the present invention.

[0072] 2. The base station 109 or network function then delivers the rough location 211 to the device (step 307). This action is included in this embodiment to illustrate an environment where this information is not delivered directly from the base station 109 to the mobile edge server 113, so the information is provided by the base station 109 to the mobile device 101, which in turn forwards it to the mobile edge server 113. However, in a scenario such as discussed below, Figure 5 In the illustrated alternative embodiment, the WRP is communicated directly from the base station 559 to the mobile edge server 563, so the mobile device 551 does not need to receive it and then forward it.

[0073] 3. Device 101: Receives a coarse position 211 from the network function, which now constitutes the WRP 211. Device 101 may also receive a confidence indication of the position (eg, an accuracy indication) from network function 109, depending on the method used in the particular embodiment.

[0074] 4. Device 101: Transmits radar sequence and receives response (step 309). The settings of the radar are based on the device's knowledge of the features indicated on the map or based on guidance previously received from the mobile edge server 113. For example, the network can look at a database and determine which directions have a reliable amount of available data that can be correlated with the sensed data from the device and ask the device 101 to use specific panels in those directions. If there is no prior knowledge, the radar parameters are based on default parameters. This will be described further below.

[0075] 5. The device 101 sends the received radar data to the mobile edge server 113 (step 311 ), where the data includes the parameter settings used in the sensing and the WRP 211 .

[0077] 6. The mobile edge server 113 (or similar mobile edge functionality implemented in a network node such as a base station 109) determines the WR frame 201 based on the WRP 211, the confidence level of the potentially received WRP estimate, and the historical information about the WRP accuracy level for that location in the area (based on its database based on previous estimates relative to the historically determined precise locations of all devices in the area) (step 313). The area may be the entire network cell, or may be more narrowly defined based on the WRP. This functionality is further described below.

[0078] 7. The mobile edge server 113 determines a second more accurate estimate 215 of the position 207 based on the WR frame 201 and the received radar data (step 315). This functionality will be further described below.

[0079] 8 (Alternative 1). The mobile edge server 113 sends a second (more accurate) estimate 215 of the location 207 to the device (step 319).

[0080] 9 (Alternative 1). The mobile edge server 113 updates its database with the relevant data from the device and the determined precise location (step 331). This function will be further described below.

[0081] In some cases, the mobile edge functionality (i.e., implemented as a separate mobile edge server 113 or an auxiliary function of a network node such as a base station 109) may not be able to determine the exact location of the device with high confidence / accuracy. The reason may be that the environment has changed, so there is no good correspondence in the data in the database (e.g., map, previous radar signals, etc.), or the WRP is particularly wrong in a specific case for some reason. One of the key advantages of the technical approach described herein is that the mobile edge functionality has a good overview of the potential reasons for low confidence in the map and estimated location, and can provide guidance to the mobile device 101 accordingly to perform additional measurements configured to improve the accuracy of the estimated location. For example, such guidance can be:

[0082] - Move (some estimated distance in a known direction where there are no objects in the way according to radar measurements) and perform new measurements from there and send this new sensor data to the mobile edge function 113 along with the estimated incremental movement.

[0083] - performing additional measurements based on different settings for radar signaling, such as higher power, greater bandwidth, longer signal duration, additional frequencies; and / or based on pointing one or more radar transmissions in a different direction (e.g., using a different antenna panel) than has been previously performed (e.g., directions that are expected to be associated with more distinct and unique radar signatures (e.g., as determined based on available map data and data from previous radar scans at the network)); etc.

[0084] Based on this, the latter part of the above process becomes (such as Figure 3A The dashed box and signal in the figure are shown as follows:

[0085] 8 (Alternative 2). The mobile edge function 113 determines the most appropriate parameters for the execution of additional measurements required to guide a more accurate position (step 317). As described above, this may involve the network looking in a database and determining which directions have a reliable amount of available data that can be correlated with the sensed data from the device, and requiring the device 101 to use specific panels in those directions.

[0086] 9 (Alternative 2). The mobile edge function 113 sends the second position estimate (accurate) 215 (as determined in step 315) to the device with an indication of a (lower) confidence level (step 319)

[0087] 10. The mobile edge function 113 sends parameters to the device 101 to guide the performance of the additional measurements (step 321)

[0088] 11. Device 101 performs additional measurements according to the instructions (step 323)

[0089] 12. Device 101 sends additional collected data to mobile edge function 113 (step 325)

[0090] 13. The mobile edge function 113 determines an updated position based on the additional data (step 327)

[0091] 14. The mobile edge function 113 sends the updated position with updated confidence to the device 101 (step 329)

[0092] 15. The Mobile Edge Function 113 updates its database with the relevant data from the device and the determined precise location (step 331).

[0093] In an alternative class of embodiments, Figure 3B is an exemplary alternative signaling diagram which is similar in most respects to that of Figure 3AThe first (rough) estimate 211 of the position 207 (and possibly also a confidence estimate of the first position) is determined by the mobile device 101 itself, rather than at the base station 109 (eg, Figure 3A This determination may be performed in a variety of different ways, including but not limited to using a global positioning system (GPS) circuit within mobile device 101 (step 351). In all other aspects, Figure 3B The actions described in Figure 3A The corresponding actions described in are the same as those in Figure 3B For a description of the actions depicted in these, see Figure 3A Description.

[0094] Some of these steps are further described later in this document.

[0095] To further illustrate, Figure 4 An example is shown when a mobile device (UE) 401 is in the surrounding area. According to aspects of the steps shown in FIG3 , the mobile edge function 113 has estimated the location 207 of the device as a WRP 211 with a corresponding WR frame 403. It can be seen that the estimated location WRP of the device is in error by an amount δ. The illustrated shapes filled with cross-hatching represent nearby structures / objects (e.g., walls, machines, furniture).

[0096] exist Figure 3A In basic operation of the example shown, UE 401 receives a WRP (i.e., it is an estimated position) and performs radar operations according to the received guidance. In this exemplary case, radar signals are transmitted in four beam directions, and for each beam direction, UE 401 receives reflections and estimates or calculates radar response signal characteristics (e.g., delay, strength, Doppler characteristics, shape, etc.). The WRP and received radar data (e.g., the original reflected radar signals or their processed versions with useful information extracted) are sent to the mobile edge function 113. (UE 401 sending the WRP to the mobile edge function 113 is included here to illustrate an embodiment in which this information is not delivered directly from the base station 109 to the mobile edge server 113. However, in embodiments such as those discussed below, this information is not directly delivered from the base station 109 to the mobile edge server 113.) Figure 5In the illustrated alternative embodiment, the WRP is communicated directly from the base station 559 to the mobile edge server 563, so the mobile device 551 does not need to do so.) The mobile edge function determines the WR frame 403 and correlates the data derived from the radar signal with one or more reference maps 213 and / or previously recorded radar signals generated and maintained at known locations to estimate a possible position within the WR frame 403. Based on its overall knowledge of the map 213 (known objects and their corresponding locations) corresponding to the WR frame 403, as well as the recorded radar signal characteristics from different locations within the WR frame 403, a more accurate estimate of the UE position 207 is determined. In fact, given the different distances and signal characteristics of different objects and structures, it can be determined that only certain points in the WR frame 403 may be possible.

[0097] In some theoretical cases, there may be multiple possible positions within WR frame 403 that could result in the same set of radar responses, but except in very rare circumstances, then one iteration with additional data (e.g., by directing device 401 to move a certain distance and perform another radar measurement that is then analyzed) will typically be sufficient to resolve the uncertainty.

[0098] Since there are multiple beam directions and multiple objects being reflected, the correlation analysis is preferably configured to be able to handle certain deviations, such as when individual objects have moved but the majority of the scene is stable. In some cases, more disruptive scene changes are possible (larger proportions of objects moving). The optimizations described below can help address such situations.

[0099] Note that even though the edge shift function 113 correlates only for positions within the WR frame 403, it also uses reflections from objects and structures outside the WR frame 403 (e.g., from object 405). The radar beam direction, and thus the WR frame 403, need not be contained only in the XY dimensions, but may also include up and down directions depending on the system and needs.

[0100] In some embodiments, radar data from a device may include a timestamp of the scan period and an estimated mobility vector to account for scans from different locations. This enables further analysis and precision in the mobile edge function 113 as it accounts for multiple locations and further incorporates knowledge about the trajectories of all devices in the area.

[0101] Some of the above aspects are further described below:

[0102] Transmit a radar sequence and receive a response

[0103] In a simple implementation, the device 101 may transmit a radar beam in all directions according to some default radar settings, and send received signal responses (in conjunction with the WRP and radar settings) to the mobile edge function 113. However, there are several problems with this:

[0104] - The radar settings may be suboptimal for the actual context (e.g., distances to objects of interest in various directions, beam widths, specific types of objects requiring specific radar settings for optimal performance).

[0105] - If the radar is performed in the spectrum defined by the 3GPP standards, the radar operation needs to consider interference both to other devices caused by the radar signal and to other devices that may disturb radar reflections. Depending on the relative position of the device to other devices and base stations, there may be certain directions, frequencies, and output power levels that must be avoided.

[0106] - For mobile devices, proximity to other devices in motion and certain critical objects may require more stringent real-time operation or caution, while some other situations may be more relaxed in terms of real-time requirements.

[0107] Embodiments consistent with the present invention enable optimized operation because the mobile edge function 113 knows the entire map, as well as the location of all devices and their recent movements, as well as information about the location of all base stations. Depending on the expected distance and type of structure, the optimization enables the radar to adapt to the environment, and the radar output power, waveform and duration may be different in different directions. This enables the following optimizations:

[0108] A. When the mobile edge function 113 sends the precise location to the device 101, it also sends certain key information about the area / nearby: such as proximity / direction to other mobile devices and base stations, proximity to certain key objects or structures, and other key related information as required (e.g., whether there are certain rapid changes in the environment).

[0109] B. When the data in step (7) above is not sufficient to accurately determine the location, for example because some key objects have moved, the mobile edge function 113 can send further instructions to receive additional data: not only to the current device (step (10) above), but also to other nearby devices that can help collect additional updated knowledge about the environment from their respective locations. The exact protocol and rules for such a process are beyond the scope of this description, but there are several different alternative solutions within the capabilities of a person of ordinary skill in the art (for example, if the UE using the positioning service has no problem doing so, it can also be assumed that they help with additional measurements when needed).

[0110] C. Later in this document, an alternative embodiment is described which involves incorporating certain optimization measures in each radar operation.

[0111] By performing several subsequent positionings, possibly with estimates of movement in between (if the device has the capability to estimate movement), the mobile edge functionality 113 can determine the position with even greater accuracy, and in some but not necessarily all embodiments, apply optimizations, such as reducing the size of the WR frame 403 for specific cases, being relevant only to specific parts of the map, etc.

[0112] Determine the mobile edge function 113 of the WR framework 403

[0113] There are a number of ways to determine the WR frame 403. In one of the simpler approaches, a radio-based positioning scheme is used that includes an indication of the expected accuracy (e.g., ±5 meters), and then the WR frame 403 becomes a WRP ±5 meters in each dimension. For example, see Figure 2 And as previously mentioned, the WR frame 403 may alternatively have another shape, such as but not limited to a circular, elliptical, or spherical shape.

[0114] If the position was recently determined, and if the speed (or maximum speed) and direction and acceleration (or maximum acceleration) of the device are known, another way of determining the WR frame 403 can be used. As long as the amount of time since the previous position determination is not large, a much smaller WR frame 403 can be used.

[0115] However, as the confidence intervals become pessimistic (the worst case accuracy of the method must be considered), an aspect of an embodiment of the invention provides further improvement.

[0116] More specifically, for each self-positioning performed, the mobile edge function 113 adds relevant information to the stored WRP history, the method used to reach the WRP, and the precise position ultimately produced from the radar analysis. Over time, the mobile edge function 113 builds excellent statistical knowledge of the actual confidence intervals of different WRP methods in different parts of the entire area - some places may have fairly good WRP accuracy (e.g., line of sight of the base station), while other places have very poor WRP accuracy (e.g., due to challenging radio conditions). The mobile edge function 113 can also collect statistics on the deviation of WRP accuracy between different modem models, etc. This collected information can, for example, be used as a subject for machine learning / analysis to achieve accurate predictions and / or estimates and / or identify how different factors affect accuracy. Therefore, after a large number of precise positioning services have been performed, some but not necessarily all embodiments of the present invention enable the mobile edge function 113 to provide an optimized WR framework 403 taking into account both environmental conditions and modem type differences. This is also beneficial to the positioning accuracy of non-radar UEs.

[0117] Mobile edge capabilities to determine precise location113

[0118] If the mobile device is within the WR framework 403, the task of the mobile edge function 113 is to correlate the radar signal data with the data in the mobile edge server 113. This can be achieved according to several different methods, such as but not limited to:

[0119] A. The radar data provides information on different beams on objects at specific distances. The moving edge function 113 correlates this with the map information and / or previously recorded radar signals obtained at known locations that it is maintaining and determines the most likely location within the WR frame 403 that has the least number of anomalies (reflections that do not correspond to objects in the map or objects that do not have any radar reflections) or any other algorithm that has the best correlation (e.g., an algorithm that takes into account the size of anomalies or deviations). In this regard, it is advantageous to redo or recalibrate the algorithm at certain intervals based on historical data so that it can be determined whether the number of anomalies can be significantly reduced if certain structures or reflections are ignored, for example.

[0120] Anomalies may suggest that an object has moved, or that an object has challenging reflective properties, which are recorded for future correlation analysis and potential updates to map information. Additionally, the mobile edge functionality 113 may detect patterns that vary over time, such as certain objects in the environment that only appear at certain times, in which case the correlation data may include timing variables associated with these objects.

[0121] B. According to fingerprinting techniques (e.g., techniques that rely on known landmarks within the environment), the radar signal is correlated with a database of previous radar signals from different locations in the WR frame 403. Also for this purpose, the detected timing patterns (see previous paragraph) can be determined and utilized.

[0122] C. When there is no previous radar signal from the relevant location, between (A) and (B)

[0123] In this case, the method described in (A) is used.

[0124] However, the radar signal is stored for future use in the method described in (B).

[0125] The mobile edge function 113 updates its database with relevant data

[0126] One aspect consistent with an embodiment of the present invention is the ability of the mobile edge functionality 113 to correlate radar data with recorded map data / database and perform optimizations based on the recorded data, as well as having an overall view of the system status (e.g., the most recent location process of the UE and its trajectory, the most recent location process of relevant major objects, etc.).

[0127] The database of mobile edge functions includes:

[0128] • The form taken facilitates map information related to radar reflections (at different radar parameter settings) with detailed position data of objects and structures.

[0129] Radar reflection characteristics from different directions of those objects and structures identified in the map. These can be initially calculated based on the structure map (as above), given some knowledge about materials and shapes. These can also be initially measured based on enhanced equipment with high precision sensors, and only need to be done once. In one aspect consistent with an embodiment of the invention, this information is continuously updated as the system is in use.

[0130] ● Radar signal reflections from actual equipment in use, with the different parameter settings of the radar annotated during the measurement.

[0131] • The original WRP position and method for each positioning case, together with the precise position derived from the radar correlation.

[0132] In addition, the mobile edge function 113 maintains an updated map for all connected devices using the location service. This enables the mobile edge function 113 to apply optimizations in terms of having devices supplement weak information in certain areas and in terms of which beam directions may be more susceptible to interference from radar transmissions (3GPP band and / or other). Finally, this information can also enable additional types of services based on the detailed location and trajectory information of all devices in the area combined with an updated view of objects and structures in the area, without requiring devices to be equipped with cameras, which would otherwise increase costs and may be considered a privacy issue. Further details on such services are beyond the scope of this description.

[0133] Creating database data for mobile edge function 113

[0134] The database of the Mobile Edge Function 113 needs to be initially populated and then iteratively improved over time through usage - the more it is used and the more devices it has, the better and richer it becomes.

[0135] In one embodiment consistent with the present invention, the initial content can be recorded with an enhanced device that has additional sensors to determine how far it has moved from a known precise location. In addition, a map of the environment can be created with all static objects and structures. The creation of the initial map only needs to be done once (in a factory, this may be walls, large machinery, and other objects of note), but this may exist from the beginning. This enhanced device records radar signals and determines how the radar returns make certain objects visible at different distances. All of this data is recorded in a database, and the map of structures and objects is updated based on their visibility and characteristics from the radar perspective.

[0136] In another embodiment consistent with the present invention, an enhanced device with a camera creates a map of the environment using some kind of simultaneous localization and mapping (SLAM) (there are many solutions compatible with embodiments of the invention) and uses radar to annotate or update the map based on its radar reflection characteristics. This SLAM implementation does not require optimization because this is essentially done only once. It is also possible to redo the process at different intervals, however, not to create an initial map and radar signal content, but to update the database based on certain objects that have been moved or added - in principle to get confirmation from the deviation from the most recent radar measurement in the event that an anomaly has been identified.

[0137] Positioning accuracy

[0138] The positioning accuracy of the techniques described in this article depends on the radar signaling characteristics.

[0139] For example, a wider signal bandwidth enables more precise measurements and resolves more details in the target, thus providing more information for positioning. The signal-to-noise ratio is also crucial to the quality of radar measurements, and this can be improved by increasing the output power or by extending the correlation time. However, the required output power and correlation time grow rapidly with the target distance, and beyond a certain distance, it becomes impractical to resolve small objects. Long correlation times also become increasingly difficult to combine with movement. In order to minimize the resources used and maximize the accuracy of positioning, it is therefore best to target nearby objects with relatively low power and duration but high signal bandwidth, if possible. The position accuracy will be a fraction of the inverse signal bandwidth multiplied by the speed of light. For example, if a signal bandwidth of several GHz is used, the accuracy obtained by correlation of the signal modulation can be several centimeters.

[0140] In general, objects that are further away may also result in less accurate measurements than those that are closer. This is partly due to the longer delay before being received, which gives a larger impact to clock jitter. It is also due to the more potentially unknown properties of such long and wider signal propagation paths (beams have limited opening angles). However, the reduced accuracy if nearby objects are lost is tolerable for most applications, as the closer the device is to the objects around it, the more accurate the positioning needs to be. In addition, other radio-based positioning technologies perform worst near important structures and objects (more challenging radio channels, no line of sight to base stations), which is exactly the situation where the currently described technology can provide positioning with accuracy down to centimeters. Therefore, the nature of the methods makes them complementary.

[0141] It is beyond the scope of this description to list every possible radar characteristic that can be used for a more in-depth evaluation, as this also depends on the radar implementation in the device. However, in summary, an important advantage of the presently described technique is that the mobile edge function 113 has a holistic understanding of the environment, which enables guidance to optimize the radar measurements as needed.

[0142] Alternative Embodiment: Guided Radar Operation

[0143] To illustrate some additional aspects of some, but not necessarily all, alternative embodiments consistent with the present invention, reference will now be made to Figure 5 Features depicted with dashed lines and boxes represent optional aspects of the exemplary embodiment.

[0144] 1. The mobile device 551 starts its self-positioning application (step 501) and therefore sends a self-positioning initialization request to the base station 559 or other network function (step 503).

[0145] 2. The base station 559 or other network function performs an initial network-based positioning function to determine the WRP (possibly with some confidence level) (step 505) and provides it to the mobile edge function 563 (step 507).

[0146] 3. In response, the mobile edge function 563 determines a WR frame corresponding to the location WRP (step 509), and also determines parameters for directing radar operation based on the area, surrounding related objects, permitted use of radar in certain frequency bands, etc. (step 511). In some but not necessarily all embodiments, the guidance may also be based on the device

[0147] 551 has radar capabilities and what kind of radar capabilities (e.g., whether it has SAR capabilities). The device capability information can be provided to the mobile edge function 563 in any number of ways, including but not limited to receiving it from the device 551. By performing sensing according to the guidance of the mobile edge function, the device 551 can always perform its radar operations in an optimized manner that takes into account the mobile edge function's overall knowledge of the map in the area, all other mobile devices and known dynamics in the environment, and previous historical measurements from other devices in the area. The mobile edge function 563 then sends the WR frame and radar guidance parameters to the mobile device 551 (step 513).

[0148] 4. The device 551 then transmits a radar sequence and receives a response (step 515). The settings for the radar are based on the device's knowledge of the features indicated on the map and guidance previously received from the mobile edge server 113. This will be described further below.

[0149] 5. The device 551 then sends the received radar data to the mobile edge server 563 (step 517 ), together with the parameter settings used in the sensing, as these may deviate from the guidance provided by the mobile edge server 563 in some embodiments.

[0150] 6. The mobile edge server 563 determines the precise location based on the WR frame and the received radar data (step 519) and sends it to the mobile device 351 (step 521).

[0151] 7 (Alternative 1). The mobile edge server 363 updates its database with the relevant data from the device 351 and the determined precise location (step 535).

[0152] As in the previously described embodiments, in some cases the mobile edge functionality may not be able to determine the precise location of the device with a high enough confidence / accuracy using the sensor data it has. To address this issue, the mobile edge functionality (which has a good overview of the map and the underlying reasons for the low confidence in the estimated location) provides guidance to the mobile device 551 to perform additional measurements configured to improve the accuracy of the estimated location. For example, such guidance may be:

[0153] -Move (some estimated distance in a known direction where there are no objects in the way based on radar measurements) and perform new measurements from there and send this new sensor data to the mobile edge function 563 along with the estimated incremental movement.

[0154] - Perform additional measurements based on different settings of the radar signal, such as higher power, larger bandwidth, longer signal duration, additional frequencies, etc.

[0155] Alternatively and / or additionally, it may be known with sufficient accuracy that the device 551 is located in a local area where the historical sensing data available to the server 113 does not meet at least one predetermined criterion. For example, the predetermined criterion may be a certain level of sensing data associated with a particular direction at the location. By directing the device 551 to perform sensing in that direction and report the sensing data back to the server 113, the server's database of historical sensing data may be supplemented and thereby improved for future use.

[0156] Based on this, the latter part of the above process becomes (such as Figure 5 The dashed box and signal in the figure are shown as follows:

[0157] 7 (Alternative 2). The moving edge function 563 determines the parameters for the most appropriate additional measurements required to perform a more accurate position (step 523)

[0158] 8. The mobile edge function 563 sends parameters to the device 551 to guide the performance of additional measurements (step 525)

[0159] 9. Device 551 performs additional measurements according to the instructions (step 527)

[0160] 10. Device 551 sends additional collected data to mobile edge function 563 (step 529)

[0161] 11. The mobile edge function 563 determines and updates the position based on the additional data (step 531)

[0162] 12. Mobile edge function 563 sends updated position with updated confidence level to device 551 (step 533)

[0163] 13. The mobile edge function 563 updates its database with the relevant data from the device and the precise location determined (step 535).

[0164] Additional Alternative Embodiments

[0165] Centralized vs. Decentralized Databases

[0166] Portions of the database may be downloaded and stored in the device / UE 101 so that correlation / fingerprinting occurs there rather than in the mobile edge function 113, potentially operating at even higher correlation rates or reducing the use of communication resources (and freeing up even more opportunities for radar operation). In an advantageous embodiment, the results (raw data measurements rather than the actual own position) are shared with the mobile edge function database so that the data is available to serve other UEs.

[0167] Therefore, some embodiments consistent with the present invention do not depend on the mobile edge function 113 containing all the functions described above. Instead, the above aspects are applicable even in distributed solutions, in which part of the processing and data is managed by individual devices, so that they can benefit from shared data, map information, environmental changes and statistics through functions such as the mobile edge function 113. In addition, the knowledge of all the locations of the devices can achieve many advantages, which are described as residing in the mobile edge function 113 in the various embodiments described.

[0168] Those skilled in the art will readily appreciate that the mobile edge function 113 may be partially distributed in terms of actual processing and data access, but the devices need to share and collaborate in a manner naturally managed by the mobile edge function 113 in the above description. Therefore, the functions of the mobile edge function 113 and the devices constitute an advantageous embodiment, but other embodiments are also considered to fall within the scope of the present invention.

[0169] Certain key structures or radar stations

[0170] In some embodiments, certain structures or objects that have different radar reflection signatures and are considered stable in their locations can be identified and given special consideration. In general, this can be any object or structure with different radar reflection characteristics, but in specific cases, this can be a specific reflection designed for this purpose.

[0171] In one class of embodiments, the environment in which the device is located may include several dedicated reference points (e.g., radio reflectors, passive anchors, or iconic objects with specific RF properties). Objects may be broadband reflectors or resonant structures with different properties at specific resonant frequencies. They may be polarized to reflect only one polarization. Further embodiments include combinations of the above. There may also be different properties in different directions. Some structures may change shape with environmental conditions and may also be capable of remote sensing using radar.

[0172] In one aspect, these reference points can be arranged in a particular location pattern in the environment. This can help map correlation or fingerprinting algorithms improve their convergence rate. Additionally, in the case of ambiguity, the mobile edge function 113 can direct the device to direct its radar toward known such objects in order to determine or confirm the location or direction.

[0173] Leverage nearby devices

[0174] Since the mobile edge function 113 maintains an updated view of where all radar-equipped devices are, the system can take advantage of this by requesting and estimating trajectories based on their last known positions, having devices transmit / receive directly between each other to gain further knowledge about their relative positions and for bistatic radar operation to gain a better view of objects between them. The details of this are beyond the scope of this description.

[0175] How to get an alternative coarse-grained world (absolute) reference

[0176] It is expected that a coarse-grained World Reference Position (WRP) can be obtained by a variety of alternative means, which vary in cost in terms of power requirements, position quality, and connectivity requirements. An onboard GPS receiver can be used if available, or combined with network positioning for even higher quality positions, faster acquisition (so-called assisted GPS), etc.

[0177] In another aspect of some but not necessarily all embodiments, the above aspects can be used to provide a coarse-grained starting point by guessing where a device might reside given a map of the environment. This solution is completely self-contained and will not depend on having GPS and line of sight to satellites.

[0178] Yet another embodiment exploits previous data points and, based on how long the data points have been around (generally more recent measurements are preferred) and assumed movement of position over time, reuses historical data obtained by the same system that will provide the most energy efficient generation of a coarse-grained world reference.

[0179] Note that as the positioning system continues to operate and improves the actual position, this also serves to provide new and accurate reference points to device 101, effectively sub-planting a coarse-grained reference with a continuous high-quality position that is limited only by the quality of the map data, the ranging resolution of the onboard radar, etc.

[0180] Alternative device sensors such as IMU, accelerometer, or compass

[0181] Various embodiments consistent with the present invention do not depend on the use of an IMU, compass, or gyroscope, even though the functionality would benefit from an additional sensor that primarily determines direction. Knowing the device orientation simplifies the correlation of radar signals relative to a map and simplifies guided radar operations because the mobile edge function 113 can point in different directions. However, by analyzing the correlation of different beams from multiple locations, it is possible for the mobile edge function 113 to collaborate with the device to determine its orientation without the need for this additional sensor. However, this requires greater effort.

[0182] It is noted that an IMU in the most general sense can be anything that is capable of measuring the orientation and intrinsic motion of a device. Typically, this is done without the need for external information, such as using a micro-electromechanical system (MEMS) sensor setup with a gyroscope, accelerometer, and magnetometer, providing the device with nine degrees of freedom (9DoF). This is not necessary for the functionality of embodiments of the present invention, but when combined with radar-based self-positioning, can be used to provide additional data points to verify measurements and also fine-tune the resulting position. It is noted that typical IMUs are prone to drift over time (when used for dead reckoning functions) and typically require realignment with more stable data points. Radar-based self-positioning as provided by embodiments of the invention described herein provides exactly this functionality.

[0183] The various embodiments will still work accurately in the absence of other means (e.g., intrinsic, such as an IMU) or extrinsic methods (having an external entity that provides tracking of the device's inertial motion and orientation changes, also known as a virtual IMU) because the map correlator functionality not only provides a reliable baseline (once it is locked to the correct and identified radar signature), but also measures the precise offset of (or distance from) the identified (or fingerprinted) feature.

[0184] Adding information from the beam directivity in the communication from the device of a panel known to be used towards the base station will provide the relative orientation of the panel towards the base station 109, which has a known position in the room. This information may already be available as part of the initial network-based positioning that provides the WRP. From this, other sensors can detect changes. Alternatively, if the device performs regular communications towards the base station, it will also get this update during self-positioning tracking.

[0185] Now refer to Figure 6 Describe additional aspects of embodiments of the present invention, Figure 6 In one aspect, a flow chart of actions performed by an exemplary server (e.g., a network component configured with edge mobility functionality) configured to determine a location of a first mobile communication device according to various embodiments. In other aspects, Figure 6 The blocks depicted in may also be considered to represent components 600 (eg, hardwired or programmable circuits or other processing components) for performing the described actions.

[0186] like Figure 6 As shown at the beginning, the process includes a server obtaining a first position estimate of a first mobile communication device, wherein the first position estimate indicates that the first mobile communication device is located within a local area portion of a reference coordinate system with a first accuracy (step 601). The server then determines one or more parameters for sensing the local area (step 603), and sends a request to sense the local area to one or more of the first mobile communication device and another mobile communication device based on the one or more parameters (step 605). In response to the request to sense the local area, the server receives sensed data of the local area (step 607). The server uses the sensed data of the local area to generate a second position estimate of the first mobile communication device, wherein the second position estimate indicates that the first mobile communication device is located within the local area portion of the reference coordinate system with a second accuracy, wherein the second accuracy is more accurate than the first accuracy (step 609).

[0187] In some but not necessarily all embodiments consistent with the present invention, the accuracy of the position estimate is further improved by the server determining even further parameters for directing even further sensing of the local area by the mobile communications device, and using this further sensing data to further improve the estimated position of the first mobile communications device. The number of times the further refinement of the estimated position after the directed sensing may be performed depends on the implementation, and may be, for example, a fixed number of times, or may alternatively be based on reducing the error level to an acceptable level (where the threshold of acceptability depends on the implementation). All such embodiments are Figure 6 This is represented by action 611.

[0188] Given that Figure 6 With reference to the illustrated series of embodiments, it will be appreciated that the term "first position estimate" may be understood to generally refer to a most recently obtained and / or determined position estimate of a mobile communication device, and the term "second position estimate" may be understood to generally refer to a subsequently determined position estimate having a higher accuracy than the first estimate.

[0189] The discussion will now cover exemplary embodiments, with a focus on aspects that reside in the mobile device itself.

[0190] Figure 7 In one aspect, a flow diagram of actions performed by an exemplary mobile communication device configured to perform sensing in accordance with various embodiments to generate data that can be analyzed to estimate the location of the mobile communication device. In other aspects, Figure 7 The blocks depicted in may also be considered to represent components 700 (eg, hardwired or programmable circuits or other processing components) for performing the described actions.

[0191] like Figure 7 As shown, the process includes a mobile communication device receiving a request from a network node serving the mobile communication device to sense a local area according to one or more parameters that direct how and / or where the sensing is to be performed (step 701). In many alternative embodiments, the type of sensing performed is different. For example, some embodiments employ radar sensing as discussed above. However, in alternative embodiments, other types of sensing may be used, such as optical sensing (including but not limited to camera sensors and LIDAR), inertial sensing with the aid of an inertial measurement unit (IMU), acoustic sensing (e.g., ultrasound), sensing via a combination of different antenna panels of a (e.g., mobile) device, and sensing with the aid of a synthetic aperture radar (SAR). An embodiment employing SAR will be described in more detail later in this description.

[0192] In response to the request to sense the local area, the mobile communication device generates sensing data by performing sensing according to one or more parameters (step 703). As discussed above, this may involve the mobile communication device performing sensing in a specific direction and / or moving to a specific location to perform sensing.

[0193] After generating the sensed data (either raw sensed data or, in alternative embodiments, sensed data that is the result of processing the raw sensed data by the mobile communication device), the mobile communication device transmits it to the network node (step 705).

[0194] In response to transmitting the sensing data to the network node, the mobile communication device receives its position (step 707). The position may be generated by the network node as described above, for example.

[0195] As previously mentioned, a mobile communication device may employ a variety of different types of sensing. SAR sensing is one type that may be advantageously used in embodiments of the present invention. SAR sensing involves performing radar measurements from multiple radar antenna positions relative to a target. Known processing techniques are employed to combine the recorded radar sample data to form a SAR radar image having a higher spatial resolution than is possible with a single-shot radar. When SAR is used in embodiments consistent with the present invention, particular benefits are achieved by using mmWave radar signals because the short wavelength and wide available bandwidth result in high resolution, which, when combined with the ability of mmWave signals to penetrate materials better than higher frequency signals, results in the production of high resolution images with increased signal-to-noise ratios. This enables the detection of features that are typically hidden from other sensing technologies (e.g., "seeing through" cloth or "seeing in" walls).

[0196] The technology of implementing mmWave radar in mobile communication devices is known in the art, for example the embodiments shown in the international patent application "Radar Implementation In a Communication Device", PCT / EP2020 / 069491. For example, it has been shown that it is possible to extend the UE modem capabilities to include mmWave SAR functionality. The cost of adding radar functionality on top of the functionality of a normal 5G modem is minimal. This means that the modem can be used for the essential functions of the positioning system, which for example include:

[0197] -Communicate with functions in base stations and mobile edge servers

[0198] - Radar sensing at mmWave frequencies, in different beam directions, and using different signaling types and durations

[0199] Although a 5G modem has been mentioned, this is for exemplary purposes only and is not an essential aspect of the inventive embodiments. Those of ordinary skill in the art will appreciate that other communication standards or generations of the 3GPP standard may alternatively be used in embodiments consistent with the present invention.

[0200] Using the device's modem for radar functionality is not an essential aspect of the inventive embodiments. In an alternative embodiment, radar functionality may be provided by a separate module that communicates through a 5G modem to access network-based aspects in accordance with embodiments consistent with the present invention. However, having a separate radar module adds cost and complexity.

[0201] On the other hand, in some but not necessarily all embodiments, the mobile device is equipped with an IMU or accelerometer, gyroscope, compass or (one or more) other sensors to extract / estimate the SAR scan trajectory. These sensors can also be used to understand the device orientation and relative motion to further support the positioning scheme (e.g., as discussed above, performing network-guided scanning may be required).

[0202] In summary, radar sensing capabilities in mobile devices can then be implemented with minimal hardware changes to their radio communication circuits. For example, in 5G cellular phones, mmWave radar functionality can be implemented using RF beamforming transceivers. By performing mmWave radar measurements from different positions relative to hidden objects (e.g., inside a wall), SAR processing techniques can combine recorded data from multiple radar antenna positions to form a SAR radar image of the hidden object with high resolution. Other sensors, such as IMUs, can be used to estimate / extract radar sampling positions and compensate for variable movement of the SAR scanning trajectory. SAR radar technology can be used to help mobile devices locate themselves in a map or relative to recorded radar data through fingerprinting methods.

[0203] A mobile device equipped with mmWave radar moves around in a scene and performs SAR scans of objects around it (e.g., walls, floors, and ceilings). By seeing through walls (and / or floors, ceilings, etc.) at high resolution, the device can detect detailed structures within the walls. The detected structures can then be used as a fingerprint that is correlated with map information that stores the wall features. Based on the correlation results, the device's position in the map can be estimated.

[0204] The accuracy achievable through the SAR-assisted approach is much better than what can be achieved with traditional radar-based positioning solutions. Applications include autonomous carts driving around on a factory floor, or drones in indoor environments, but there are a host of other potential applications for this technology.

[0205] As described above, a mobile device performing self-localization may find itself in areas where traditional radar sensing from the device cannot capture enough identifiable objects to localize itself. For example, such an area may be a long corridor with flat walls or an area where static identifiable objects may be blocked by moving people / objects that dynamically change the radar environment. If the device is equipped with an IMU, this can help with predictions to some extent (e.g., in corridors), but the accumulated IMU errors may increase and thereby reduce the overall accuracy.

[0206] To invoke SAR-aided self-positioning, a decision should be made as to whether the device has entered such an area, and this may be based on one or a combination of the following:

[0207] -The currently known estimate of the device's position and motion vector

[0208] -Edge cloud knowledge from previous self-localization operations of the device or other devices

[0209] -Building structure knowledge that can be included in maps stored in the edge cloud

[0210] -Indications about areas with dense placement of moving objects (such as crowds at a shopping mall entrance during rush hour) that block radar observation of identifiable objects.

[0211] The radar self-locating performance of the device in such areas may be improved by adding radar reflectors / anchors having certain detectable properties. However, for various reasons (e.g., aesthetic reasons), this may not be a desired and / or feasible alternative.

[0212] Using the mmWave SAR technology described in this article, a device may be able to detect structures inside building materials at high resolution. For example, consider a wall. Walls are typically composed of invisible, equally spaced load-bearing materials of solid wood or metal covered by an exterior drywall cover. Other objects that may be located inside the wall include cables or other electrical items or water pipes. These features can be detected by SAR and used by the device to locate itself.

[0213] Example systems utilizing mmWave SAR technology for self-positioning include:

[0214] -Mobile devices (e.g. smartphones, tablets, XR / VR headsets) with mmWave radar modules or modems (or UE user equipment) extended with mmWave radar functionality. These devices can also be equipped with IMU sensors to estimate / extract radar sampling positions.

[0215] - A cellular communication system, wherein a UE communicates with a base station.

[0216] - Edge cloud server. This may be a separately located network entity, or may alternatively be a server resident at the base station, providing services local to the area, and

[0217] Lower latency than crossing the telecom operator boundary to the data center.

[0218] - In the case where the mobile device performs mmWave radar measurements from different positions relative to the hidden object (e.g., inside a wall, on a ceiling), in some embodiments, the mobile device uses SAR processing techniques to combine recorded data from multiple radar antenna positions to form a SAR radar image of the hidden object with high resolution. Other sensors (e.g., IMU) can be used to estimate / extract radar sampling positions and compensate for variable movement of the SAR scanning track.

[0219] - In an alternative embodiment, a communications modem in the mobile device is used to transmit the radar data to a network, which then processes the radar data to reconstruct and correlate the SAR image with a data set that may be extracted from the building structure or from previous measurements by the device itself or other devices. The processing of the radar data (which can be computationally expensive) and the correlation with a set of known map features can also be done using a cloud server, mobile edge functionality, or even on the device itself (although at the expense of using additional power that can drain the battery). The processing on the device itself assumes that the World Reference Position (WRP) and map data have already been downloaded to the device.

[0220] -In one use case, a mobile device equipped with mmWave radar performs a SAR scan of (one or more) walls while moving along one or more corridors / walls. By looking through the walls at high resolution, the device can detect detailed structures within the walls (as shown in the SAR radar image). The (one or more) detected structures (or features extracted from the SAR radar image) can then be used as fingerprints and correlated with a map storing known features of the walls. Based on the correlation results, the device can estimate its own position in the map. This approach can be further extended to floor (or ceiling) SAR scans.

[0221] To illustrate some additional aspects of some, but not necessarily all, alternative embodiments consistent with the present invention, reference will now be made to Figure 8 801 and 803. The exemplary signaling diagram shown is described. Features depicted with dashed lines and boxes represent optional aspects of the exemplary embodiment. In this example, the mobile device 801 and the mobile edge server 803 are able to communicate directly with each other. Although the mobile device is served by, for example, a base station 805, the base station does not participate in the mmWave SAR-assisted self-positioning action. However, in some alternative embodiments, the mobile device 801 may need to communicate with the mobile edge server 803 via the base station 805 as an intermediary. Those of ordinary skill in the art will readily understand how to apply the teachings presented herein to such embodiments.

[0222] 7. The mobile edge function 803 determines a WRP frame corresponding to the current estimate of the position (WRP) of the mobile device (step 807), which estimate has been determined by other means (e.g., by using any of the methods described above). The WRP may be determined by the mobile device 801 (e.g., see Figure 3A and accompanying text) or by base station 805 (e.g., see Figure 5 and accompanying text).

[0223] 8. The mobile edge function 803 decides (e.g., based on any one or more of the factors outlined above) that network-assisted self-positioning will improve the current estimate of location, and accordingly determines parameters for guiding radar operation based on the area, surrounding relevant objects, its permitted use of radar in certain frequency bands, etc. (step 809). In some but not necessarily all embodiments, the guidance may also be based on whether the device 801 has radar capability and what kind of radar capability it has (e.g., whether it has mmWave SAR capability). The device capability information may be provided to the mobile edge function 803 in any number of ways, including but not limited to receiving it from the device 801. By performing sensing according to the guidance of the mobile edge function, the device 801 may perform its radar operation in an optimized manner that takes into account the mobile edge function's overall knowledge of maps in the area, other mobile devices and known dynamics in the environment, and previous historical measurements from other devices in the area. The mobile edge function 803 then sends a WRP frame and the sensing guidance parameters to the mobile device 801 (step 811).

[0224] 9. The device 801 then begins its self-positioning process (step 813) and performs sensing according to the received parameters (step 815). For example, if conventional radar sensing or mmWave SAR sensing has been requested, the device 801 transmits a radar sequence and receives a response. The setting of the radar is based on the device knowledge of the features indicated on the map and the guidance received from the mobile edge server 803.

[0225] 10. The device 801 sends the resulting sensing data to the mobile edge server 803 (step 819).

[0226] For example, the resulting data may be raw radar data. Alternatively, if mmWave SAR sensing has been performed, the raw data needs to be processed to reconstruct a SAR image.

[0227] 11. (Optional) In some embodiments where mmWave SAR sensing is already performed, the mobile

[0228] The device 801 reconstructs the SAR images (step 817 ), and these are the resulting data.

[0229] 12. (Optional) In some embodiments where mmWave SAR sensing is already performed, the mobile device uses raw radar data as result data instead, and the mobile edge service

[0230] The device 803 reconstructs the SAR image according to the received raw radar data (step 821).

[0231] 13. The mobile edge server 803 correlates the received sensory data with a reference set of reflections previously obtained from known locations stored in its database (step 823).

[0232] 14. Based on the correlation results, the mobile edge server 803 determines a sufficiently accurate estimate of the location of the mobile device (step 825) and sends it to the mobile device 801 (step 827).

[0233] (What constitutes "sufficient" accuracy is implementation dependent and is therefore beyond the scope of this disclosure.) In some embodiments, mobile edge server 803 may also deliver a confidence level regarding the accuracy of the location. In some, but not necessarily all, embodiments, mobile edge server 803 also provides additional guidance for performing further sensor measurements if the confidence level does not meet a predetermined confidence threshold.

[0234] 15. (Optional) If needed (eg, if the delivered confidence level does not meet a predetermined threshold level), the mobile device 801 may (eg, based on the confidence level) perform additional sensing (eg, additional mmWave SAR scans).

[0235] 16. (Optional) If additional sensing is performed, the mobile device 801 delivers the additional sensing data to the mobile edge server (step 831).

[0236] 17. (Optional) If additional sensing data is received, the mobile edge server 803 uses this data to determine an updated precise location of the mobile device 801 (step 833).

[0237] Depending on why the additional sensory data has been obtained, the updated precise location may also be sent to a mobile device (not shown) in this step.

[0238] 18. (Optional) In any of the above options, the mobile edge server 803 that has determined an accurate estimate of the mobile device's location based on the new sensory data can use the device

[0239] 801 and the determined precise location to update its database (step

[0240] 835). The updated database will accordingly enable more accurate positioning estimates to be generated for the mobile device 801 and other mobile devices in subsequent positioning requests.

[0241] Another aspect of some embodiments that perform mmWave SAR sensing for self-localization involves a SAR database of known reflectors to which the sensed data is associated. There are multiple options for creating a SAR fingerprint database. One of these options is to pre-characterize the surfaces to be sensed (e.g., walls, floors, ceilings, etc.) during an initial system calibration process. The process involves performing a SAR scan of a selected portion of the surface, extracting its detectable features (i.e., fingerprints), and storing the fingerprints and corresponding locations in a map.

[0242] Another option is to intentionally embed SAR anchor nodes with known SAR characteristics into known locations within a surface (e.g., a wall, floor, ceiling, etc.). Convenient times to do this include the time of renovation or initial construction of a building, but of course time is not an essential aspect of embodiments of the present invention. Due to the surface penetration properties of mmWave, these built-in anchor points with specific shapes (e.g., physical structures) or RF reflectivity (e.g., patterns painted with RF-sensitive paint) can be made hidden from human perception for aesthetic reasons while remaining visible / detectable to mmWave radar sensing. The specific shape and / or distribution pattern of these anchor points can be selected for a given surface (e.g., a wall), which can be used as a fingerprint of the surface. Such a structure will be completely passive. The shape and / or distribution pattern can be configured based on the fact that the radar structure is considered to be a surface with an incident normal plane relative to the antenna aperture sight. The arrangement of these surface edges significantly increases the characteristics of the reflected signal. Examples of such structures include small radar reflectors suitable for millimeter waves and / or millimeter wave radar reflective paint patterns. The SAR fingerprints and their corresponding locations are then stored in a map.

[0243] The various options may be combined in the sense that a first option (ie, pre-characterized sensing of an area) may be used to fine-tune the position of a built-in anchor point of a second option.

[0244] In all these alternatives, the map with the SAR fingerprint can be stored in a database maintained by the mobile edge server, which uses it as a reference map in correlation with the sensed data.

[0245] Alternatively, a SAR-enabled device with an accurate position estimate can be instructed to scan for objects and provide the data to a central database for future use. This is useful for detecting new objects that were identified from conventional (i.e. non-SAR) radar transmissions, and therefore do not appear in advance, or may be located in an area not covered by the above methods.

[0246] The mobile edge server 803 of the embodiment involving mmWave SAR sensing shares the aspects described above in conjunction with other embodiments. It contains an environmental map and a SAR fingerprint database (and its corresponding location). It can also run a correlation algorithm between the stored fingerprints and the measured SAR image features to estimate the most likely location of the device 801 within a limited geographic area. The estimation result can then be sent back to the device 801. In addition, the positioning functionality can serve all devices within the coverage area of ​​the base station 805. The mobile edge server 803 can further aggregate data from multiple devices, which can be used to update the map and / or fingerprint database.

[0247] And as previously described, the mobile edge server 803 gives initial guidance (eg, based on an initial position estimate) toward suitable SAR objects in close proximity to the device 801 as location-related candidates.

[0248] Furthermore, in alternative embodiments, the functionality of the mobile edge server 803 may be embodied as an extension of the functionality in the base station 805, rather than as a separate (or at least separately located) entity. Therefore, it is not essential to embodiments of the present invention that the functionality resides in the mobile edge server 803. However, there are inherent advantages in co-locating the mobile edge server functionality with the functionality of the base station 805, given that it is closely connected to the base station 805 and thus naturally covers a limited geographic area, has a shorter latency than a remote over-the-top data center, and has a larger storage space and higher computing performance than the UE or mobile device 801.

[0249] Another aspect of some, but not necessarily all, embodiments relates to when to enable SAR mode sensing and when to disable it (e.g., to perform an alternative type of sensing). Since SAR image reconstruction requires more computational resources than conventional radar operation, SAR operation increases processing complexity and may require further data transfer. Whenever a particular embodiment / application finds it necessary, SAR operation may be enabled so that the SAR mode of radar operation of the device may be in addition to its conventional radar operation. Of course, "when necessary" is implementation dependent, so a full discussion is beyond the scope of this disclosure.

[0250] In one exemplary embodiment, the device autonomously enables its mmWave SAR radar mode when entering an area lacking a sufficient number of objects that could provide unique signatures for ordinary radar and the error of its conventional radar-assisted self-localization (or IMU localization) algorithm is above a threshold.

[0251] In an alternative exemplary embodiment, the device's mmWave SAR sensing mode is enabled by a cloud or edge cloud tracking the device. The cloud can guide SAR operation based on the device's initial position (potentially based on the IMU's initial position if supported) and a priori knowledge of the positions of SAR reference objects, which are located in areas where conventional radar-assisted self-positioning accuracy is low (or where application requirements for required positioning accuracy cannot be met at a certain confidence level) or where there are significant identifiable structures that SAR will be able to exploit.

[0252] In another alternative exemplary embodiment, when multiple devices are available in a scene, mmWave SAR self-positioning functionality may be enabled in one (or some) of these devices, while the remaining devices perform only non-SAR radar self-positioning functions. By locating itself with higher accuracy and sharing its position with other devices, a SAR-enabled device can be used as a reference point by an ordinary radar device, thereby improving the positioning accuracy of the ordinary radar device. In addition, which devices and how many devices are enabled for mmWave SAR self-positioning can adapt to the positioning accuracy requirements.

[0253] In another aspect consistent with some but not necessarily all embodiments of the invention, portions of the database may be downloaded and stored on the device so that correlation / fingerprinting occurs there rather than in the edge cloud. (See, e.g., Figure 8 837 in step 837). In a preferred embodiment, the results are still delivered to the edge cloud database so that the database can be updated accordingly and subsequently serve other devices when other devices perform self-positioning. A relevant use case for this embodiment involves a device with limited mobility, such that it can only move within a small area with little or no dynamics in its environment. In such instances, it may be more beneficial to store the relevant parts of the database locally within the device (as long as processing and power permit). In contrast, highly mobile devices with limited processing power operating in an environment with high dynamics may prefer the edge cloud approach.

[0254] To further illustrate aspects consistent with some but not necessarily all embodiments of the present invention, Fig. 9 Details of network node QQ 160 are shown in accordance with one or more embodiments. Fig. 9 In the embodiment, the network node QQ160 includes a processing circuit QQ170, a device readable medium QQ180, an interface QQ190, an auxiliary device QQ184, a power supply QQ186, a power supply circuit QQ187 and an antenna QQ162. Fig. 9The network node QQ160 shown in the example wireless network of can represent a device including the combination of hardware components shown, but other embodiments can include network nodes with different combinations of components. It should be understood that the network node includes any suitable combination of hardware and / or software required to perform the tasks, features, functions and methods disclosed herein. In addition, although the components of the network node QQ160 are depicted as a single box located within a larger box, or nested within multiple boxes, in reality, the network node can include multiple different physical components that make up a single shown component (for example, the device readable medium QQ180 can include multiple separate hard drives and multiple RAM modules).

[0255] Similarly, the network node QQ160 can be composed of multiple physically separated components (e.g., NodeB components and radio network controller (RNC) components, or base transceiver station (BTS) components and base station controller (BSC) components, etc.), which can each have their respective corresponding components. In some cases where the network node QQ160 includes multiple separate components (e.g., BTS and BSC components), one or more separate components can be shared between several network nodes. For example, a single RNC can control multiple NodeBs. In this case, each unique NodeB and RNC pair can be considered as a single separate network node in some instances. In some embodiments, the network node QQ160 can be configured to support multiple radio access technologies (RATs). In such embodiments, some components can be copied (e.g., separate device-readable media QQ180 for different RATs), and some components can be reused (e.g., the same antenna QQ162 that the RATs can share). The network node QQ 160 may also include multiple sets of various components shown for different wireless technologies, such as, for example, GSM, WCDMA, LTE, NR, WiFi, or Bluetooth wireless technologies, integrated into the network node QQ 160. These wireless technologies may be integrated into the same or different chips or chipsets and other components within the network node QQ 160.

[0256] The processing circuit QQ170 is configured to perform any determination, calculation, or similar operation (e.g., certain obtaining operations) described herein as being provided by the network node. Such operations performed by the processing circuit QQ170 may include processing information obtained by the processing circuit QQ170, such as by converting the obtained information into other information, comparing the obtained information or the converted information with information stored in the network node, and / or performing one or more operations based on the obtained information or the converted information, and making a determination as a result of the processing.

[0257] The processing circuit QQ170 may include a combination of one or more of the following: a microprocessor, a controller, a microcontroller, a central processing unit, a digital signal processor, an application specific integrated circuit, a field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide network node QQ160 functionality alone or in conjunction with other network node QQ160 components (e.g., device readable medium QQ180). For example, the processing circuit QQ170 may execute instructions QQ181 stored in the device readable medium QQ180 or in a memory within the processing circuit QQ170. Such functionality may include providing any of the various wireless features, functions, or advantages discussed herein. In some embodiments, the processing circuit QQ170 may include a system on a chip (SOC).

[0258] In some embodiments, the processing circuit QQ170 may include one or more of a radio frequency (RF) transceiver circuit QQ172 and a baseband processing circuit QQ174. In some embodiments, the radio frequency (RF) transceiver circuit QQ172 and the baseband processing circuit QQ174 may be on separate chips (or chipsets), boards, or units (e.g., a radio unit and a digital unit). In alternative embodiments, part or all of the RF transceiver circuit QQ172 and the baseband processing circuit QQ174 may be on the same chip or chipset, board, or unit.

[0259] In certain embodiments, some or all of the functionality described herein as being provided by a network node, base station, eNB, or other such network device may be performed by processing circuit QQ170 executing instructions stored on a device-readable medium QQ180 or a memory within processing circuit QQ170. In alternative embodiments, some or all of the functionality may be provided by processing circuit QQ170 without executing instructions stored on a separate or discrete device-readable medium, such as in a hardwired manner. In any of those embodiments, processing circuit QQ170 may be configured to perform the described functionality regardless of whether instructions stored on a device-readable storage medium are executed. The benefits provided by this functionality are not limited to processing circuit QQ170 itself or other components of network node QQ160, but are enjoyed by network node QQ160 as a whole and / or by end users and wireless networks in general.

[0260] The device-readable medium QQ180 may include any form of volatile or non-volatile computer-readable memory, including but not limited to permanent storage devices, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (e.g., hard disk), removable storage media (e.g., flash drive, compact disk (CD), or digital video disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable storage device that stores information, data, and / or instructions that can be used by the processing circuit QQ170. The device-readable medium QQ180 may store any suitable instructions, data, or information, including computer programs, software, applications, including one or more of the following: logic, rules, codes, tables, etc. and / or other instructions that can be executed by the processing circuit QQ170 and used by the network node QQ160. The device-readable medium QQ180 may be used to store any calculations performed by the processing circuit QQ170 and / or any data received via the interface QQ190. In some embodiments, processing circuitry QQ170 and device readable medium QQ180 may be considered integrated.

[0261] Interface QQ190 is used for wired or wireless communication of signaling and / or data between network node QQ160, network QQ106 and / or WD QQ110. As shown, interface QQ190 includes (one or more) ports / (one or more) terminals QQ194, for example, for sending data to network QQ106 and receiving data from network QQ 106 via a wired connection. Interface QQ190 also includes radio front-end circuit QQ192, which can be coupled to antenna QQ162, or in some embodiments is part of antenna QQ 162. Radio front-end circuit QQ192 includes filter QQ198 and amplifier QQ196. Radio front-end circuit QQ192 can be connected to antenna QQ162 and processing circuit QQ170. The radio front-end circuit can be configured to adjust the signal delivered between antenna QQ162 and processing circuit QQ170. Radio front-end circuit QQ192 can receive digital data to be sent to other network nodes or wireless devices via a wireless connection. The radio front end circuit QQ192 may convert the digital data into a radio signal having appropriate channel and bandwidth parameters using a combination of filters QQ198 and / or amplifiers QQ196. The radio signal may then be transmitted via antenna QQ162. Similarly, when receiving data, antenna QQ162 may collect the radio signal, which is then converted into digital data by the radio front end circuit QQ192. The digital data may be passed to the processing circuit QQ170. In other embodiments, the interface may include different components and / or different combinations of components.

[0262] In some alternative embodiments, the network node QQ160 may not include a separate radio front end circuit QQ192, instead the processing circuit QQ170 may include the radio front end circuit and may be connected to the antenna QQ162 without the separate radio front end circuit QQ192. Similarly, in some embodiments, all or some of the RF transceiver circuit QQ172 may be considered part of the interface QQ190. In still other embodiments, the interface QQ190 may include one or more ports or terminals QQ194, the radio front end circuit QQ192, and the RF transceiver circuit QQ172 as part of a radio unit (not shown), and the interface QQ190 may communicate with the baseband processing circuit QQ174, which is part of the digital unit (not shown).

[0263] Antenna QQ162 may include one or more antennas or antenna arrays configured to send and / or receive wireless signals. Antenna QQ162 may be coupled to the radio front-end circuit QQ190 and may be any type of antenna capable of wirelessly transmitting and receiving data and / or signals. In some embodiments, antenna QQ162 may include one or more omnidirectional, sector or flat panel antennas operable to transmit / receive radio signals, for example, between 2 GHz and 66 GHz. Omnidirectional antennas may be used to transmit / receive radio signals in any direction, sector antennas may be used to transmit / receive radio signals from devices within a specific area, and flat panel antennas may be line-of-sight antennas for transmitting / receiving radio signals in a relatively straight line. In some instances, the use of more than one antenna may be referred to as MIMO. In some embodiments, antenna QQ162 may be separate from network node QQ160 and may be connected to network node QQ160 via an interface or port.

[0264] Antenna QQ162, interface QQ190 and / or processing circuit QQ170 may be configured to perform any receiving operation and / or certain obtaining operations described herein as being performed by a network node. Any information, data and / or signal may be received from a wireless device, another network node and / or any other network device. Similarly, antenna QQ162, interface QQ190 and / or processing circuit QQ170 may be configured to perform any transmission operation described herein as being performed by a network node. Any information, data and / or signal may be transmitted to a wireless device, another network node and / or any other network device.

[0265] The power circuit QQ187 may include or be coupled to a power management circuit and is configured to supply power to the components of the network node QQ160 for performing the functionality described herein. The power circuit QQ187 may receive power from a power source QQ186. The power source QQ186 and / or the power circuit QQ187 may be configured to provide power to the various components of the network node QQ160 in a form suitable for the respective components (e.g., at the voltage and current levels required by each respective component). The power source QQ186 may be included in the power circuit QQ187 and / or the network node QQ160, or may be external to the power circuit QQ 187 and / or the network node QQ160. For example, the network node QQ160 may be connected to an external power source (e.g., a power outlet) via an input circuit or interface such as a cable, whereby the external power source supplies power to the power circuit QQ187. As another example, the power supply QQ186 may include a power source in the form of a battery or battery pack connected to or integrated in the power circuit QQ187. If the external power source fails, the battery may provide backup power. Other types of power sources, such as photovoltaic devices, may also be used.

[0266] Alternative embodiments of network node QQ 160 may include, in addition to Fig. 9 , which may be responsible for providing certain aspects of the network node functionality, including any functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node QQ 160 may include a user interface device to allow input of information to the network node QQ 160 and output of information from the network node QQ 160. This may allow a user to perform diagnostics, maintenance, repair, and other management functions on the network node QQ 160.

[0267] To further illustrate aspects consistent with some but not necessarily all embodiments of the present invention, Fig.10Details of a wireless device QQ110 according to one or more embodiments are shown. As used herein, a wireless device (WD) refers to a device that is capable of, configured, arranged and / or operable to wirelessly communicate with a network node and / or other wireless devices. Unless otherwise specified, the term WD may be used interchangeably with a user equipment (UE) herein. Wireless communication may involve the use of electromagnetic waves, radio waves, infrared waves and / or other types of signals suitable for transmitting information through the air to transmit and / or receive wireless signals. In some embodiments, a WD may be configured to transmit and / or receive information without direct human interaction. For example, a WD may be designed to transmit information to a network according to a predetermined schedule when triggered by an internal or external event, or in response to a request from the network. Examples of WD include, but are not limited to, smart phones, mobile phones, cellular phones, voice over IP (VoIP) phones, wireless local loop phones, desktop computers, personal digital assistants (PDAs), wireless cameras, game consoles or devices, music storage devices, playback devices, wearable terminal devices, wireless endpoints, mobile stations, tablet computers, laptops, laptop embedded devices (LEEs), laptop mounted devices (LMEs), smart devices, wireless client equipment (CPEs). Vehicle-mounted wireless terminal devices, etc. WD can support device-to-device (D2D) communication, such as by implementing the 3GPP standard for sidelink communication, and in this case can be referred to as D2D communication devices. As another specific example, in the Internet of Things (IoT) scenario, WD can represent a machine or other device that performs monitoring and / or measurement, and transmits the results of such monitoring and / or measurement to another WD and / or network node. In this case, WD can be a machine-to-machine (M2M) device, which can be referred to as a machine type communication (MTC) device in the 3GPP context. As a specific example, a WD may be a UE that implements the 3GPP Narrowband Internet of Things (NB-IoT) standard. Specific examples of such machines or devices are sensors, metering devices such as power meters, industrial machinery or household or personal appliances (e.g., refrigerators, televisions, etc.), personal wearable devices (e.g., watches, fitness trackers, etc.). In other cases, a WD may represent a vehicle or other device that is capable of monitoring and / or reporting its operating status or other functions associated with its operation. A WD as described above may represent an endpoint of a wireless connection, in which case the device may be referred to as a wireless terminal. In addition, a WD as described above may be mobile, in which case it may also be referred to as a mobile device or a mobile terminal.

[0268] Fig.10Details of a wireless device QQ110 are shown according to one or more embodiments. As shown, the wireless device QQ110 includes an antenna QQ111, an interface QQ114, a processing circuit QQ120, a device-readable medium QQ130, a user interface device QQ132, an auxiliary device QQ134, a power supply QQ136, and a power supply circuit QQ137. The WD QQ110 may include multiple groups of one or more of the components shown for different wireless technologies supported by the WD QQ110, such as, for example, GSM, WCDMA, LTE, NR, WiFi, WiMAX, or Bluetooth wireless technologies, to name a few. These wireless technologies may be integrated into the same or different chips or chipsets as other components in the WD QQ110.

[0269] Antenna QQ111 may include one or more antennas or antenna arrays configured to send and / or receive wireless signals and connected to interface QQ114. In some alternative embodiments, antenna QQ111 may be separated from WD QQ110 and may be connected to WD QQ110 via an interface or port. Antenna QQ111, interface QQ114 and / or processing circuit QQ120 may be configured to perform any receiving or transmitting operation described herein as being performed by WD. Any information, data and / or signal may be received from a network node and / or another WD. In some embodiments, the radio front-end circuit and / or antenna QQ111 may be considered as an interface.

[0270] As shown, the interface QQ114 includes a radio front-end circuit QQ112 and an antenna QQ111. The radio front-end circuit QQ112 includes one or more filters QQ118 and an amplifier QQ116. The radio front-end circuit QQ114 is connected to the antenna QQ111 and the processing circuit QQ120, and is configured to adjust the signal transmitted between the antenna QQ111 and the processing circuit QQ120. The radio front-end circuit QQ112 may be coupled to the antenna QQ111 or may be part of the antenna QQ 111. In some embodiments, the WD QQ110 may not include a separate radio front-end circuit QQ112; instead, the processing circuit QQ120 may include a radio front-end circuit and may be connected to the antenna QQ111. Similarly, in some embodiments, some or all of the RF transceiver circuit QQ122 may be considered to be part of the interface QQ114. The radio front-end circuit QQ112 may receive digital data to be sent to other network nodes or WDs via a wireless connection. The radio front-end circuit QQ112 may convert the digital data into a radio signal with appropriate channel and bandwidth parameters using a combination of filters QQ118 and / or amplifiers QQ116. The radio signal may then be transmitted via antenna QQ111. Similarly, when receiving data, antenna QQ111 may collect the radio signal, which is then converted into digital data by radio front end circuit QQ112. The digital data may be passed to processing circuit QQ120. In other embodiments, the interface may include different components and / or different combinations of components.

[0271] The processing circuit QQ120 may include a combination of one or more of the following: a microprocessor, a controller, a microcontroller, a central processing unit, a digital signal processor, an application specific integrated circuit, a field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software, and / or encoded logic operable to provide WD QQ110 functionality, either alone or in conjunction with other WD QQ110 components (e.g., device readable medium QQ130). Such functionality may include providing any of the various wireless features or benefits discussed herein. For example, the processing circuit QQ120 may execute instructions QQ131 stored in the device readable medium QQ130 or stored in a memory within the processing circuit QQ120 to provide the functionality disclosed herein.

[0272] As shown, the processing circuit QQ120 includes one or more of the RF transceiver circuit QQ122, the baseband processing circuit QQ124, and the application processing circuit QQ126. In other embodiments, the processing circuit may include different components and / or different combinations of components. In some embodiments, the processing circuit QQ120 of the WD QQ110 may include a system on chip (SOC). In some embodiments, the RF transceiver circuit QQ122, the baseband processing circuit QQ124, and the application processing circuit QQ126 may be on a separate chip or chipset. In an alternative embodiment, part or all of the baseband processing circuit QQ124 and the application processing circuit QQ126 may be combined into one chip or chipset, and the RF transceiver circuit QQ122 may be on a separate chip or chipset. In yet another alternative embodiment, part or all of the RF transceiver circuit QQ122 and the baseband processing circuit QQ124 may be on the same chip or chipset, and the application processing circuit QQ126 may be on a separate chip or chipset. In other alternative embodiments, part or all of the RF transceiver circuit QQ122, the baseband processing circuit QQ124, and the application processing circuit QQ126 may be combined in the same chip or chipset. In some embodiments, the RF transceiver circuit QQ122 may be part of the interface QQ114. The RF transceiver circuit QQ122 may condition the RF signal for the processing circuit QQ120.

[0273] In some embodiments, some or all of the functionality described herein as being performed by the WD may be provided by a processing circuit QQ120 executing instructions stored on a device-readable medium QQ130, which in some embodiments may be a computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuit QQ120 without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hardwired manner. In any of these specific embodiments, the processing circuit QQ120 may be configured to perform the described functionality, regardless of whether instructions stored on a device-readable storage medium are executed. The benefits provided by this functionality are not limited to the processing circuit QQ120 itself or other components of the WD QQ110, but are generally enjoyed by the WD QQ110 as a whole and / or end users and wireless networks.

[0274] Processing circuitry QQ120 may be configured to perform any determination, calculation, or similar operation (e.g., certain acquisition operations) described herein as being performed by the WD. Such operations performed by processing circuitry QQ120 may include processing information obtained by processing circuitry QQ120, such as by converting the obtained information into other information, comparing the obtained information or the converted information with information stored by WD QQ110, and / or performing one or more operations based on the obtained information or the converted information, and making determinations as a result of the processing.

[0275] The device-readable medium QQ130 is operable to store a computer program, software, application including one or more of logic, rules, code, tables, etc. and / or other instructions executable by the processing circuit QQ120. The device-readable medium QQ130 may include a computer memory (e.g., random access memory (RAM) or read-only memory (ROM)), a mass storage medium (e.g., a hard disk), a removable storage medium (e.g., a compact disk (CD) or a digital video disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable storage device that stores information, data, and / or instructions that may be used by the processing circuit QQ120. In some embodiments, the processing circuit QQ120 and the device-readable medium QQ130 may be considered integrated.

[0276] The user interface device QQ132 may provide a component that allows a human user to interact with the WD QQ110. This interaction may be in a variety of forms, such as visual, auditory, tactile, etc. The user interface device QQ132 may be operable to generate output to the user and allow the user to provide input to the WD QQ110. The type of interaction may vary depending on the type of user interface device QQ132 installed in the WD QQ110. For example, if the WD QQ110 is a smart phone, the interaction may be performed via a touch screen; if the WD QQ110 is a smart meter, the interaction may be performed through a screen that provides usage (e.g., the number of gallons used) or a speaker that provides an audible alarm (e.g., if smoke is detected). The user interface device QQ132 may include input interfaces, devices, and circuits, as well as output interfaces, devices, and circuits. The user interface device QQ132 is configured to allow information to be input into the WD QQ110, and is connected to the processing circuit QQ120 to allow the processing circuit QQ120 to process the input information. The user interface device QQ132 may include, for example, a microphone, a proximity sensor or other sensor, a key / button, a touch display, one or more cameras, a USB port or other input circuit. The user interface device QQ132 is also configured to allow information to be output from the WD QQ110, and allows the processing circuit QQ120 to output information from the WD QQ110. The user interface device QQ132 may include, for example, a speaker, a display, a vibration circuit, a USB port, a headphone jack or other output circuits. Using the user interface device QQ132, one or more input and output interfaces, devices and circuits of the WD QQ110, the WD QQ 110 can communicate with end users and / or wireless networks, and allow them to benefit from the functionality described herein.

[0277] The auxiliary device QQ134 is operable to provide more specific functionality that the WD is not normally capable of performing. This may include specialized sensors for taking measurements for various purposes (e.g., radar functionality as described herein), interfaces for additional types of communications such as wired communications, etc. The inclusion and types of components of the auxiliary device QQ134 may vary depending on the embodiment and / or circumstances.

[0278] In some embodiments, the power source QQ136 may be in the form of a battery or a battery pack. Other types of power sources may also be used, such as an external power source (e.g., a power outlet), a photovoltaic device, or a battery. WD QQ110 may also include a power circuit QQ137 for delivering power from the power source QQ136 to various parts of the WD QQ110 that require power from the power source QQ136 to perform any functionality described or indicated herein. In some embodiments, the power circuit QQ137 may include a power management circuit. The power circuit QQ137 may additionally or alternatively be operable to receive power from an external power source; in this case, the WD QQ110 may be connected to an external power source (e.g., a power outlet) via an input circuit or interface (e.g., a cable). In some embodiments, the power circuit QQ137 may also be operable to supply power to the power source QQ136 from an external power source. For example, this may be used for charging the power source QQ136. The power circuit QQ137 may perform any formatting, conversion, or other modifications to the power from the power source QQ136 so that the power is suitable for the corresponding components of the WD QQ110 being powered.

[0279] It will be appreciated that important aspects of the various embodiments involve collaboration between mobile devices with radar capabilities and mobile edge functions (MEFs) with integrated data, having more resources to perform correlation to determine precise location, and serving multiple mobile devices while iteratively improving and updating their data. In this regard, the following aspects are worth noting:

[0280] ● Separate device-mobile edge function (MEF) positioning, so that according to the above embodiment,

[0281] Devices do radar, while MEF does correlation. This opens up many optimizations, such as:

[0282] MEF has access to all dynamic changes from all devices, MEF can guide devices based on maps and surrounding characteristics (no need to preload a lot of data into the device), MEF can perform more advanced fine-tuning through composition techniques, and MEF

[0283] Can learn from combined fine-tuning techniques.

[0284] ● Iterative fine-tuning after moves to address cases where the fine-tuning appears ambiguous / too low confidence in the exact position (due to noise, artifacts, or dynamically changing environment): the movement between the two radar analyses is estimated based on the most likely position (potentially multiple) in the coarse position area, and the new fine-tuning is based on an evaluation of the new radar-based fine-tuning combined with the previous candidate plus incremental movement.

[0285] MEF can identify certain points / structures as "anchors" relative to other reflections very reliably. Areas lacking identifiable unique structures can be identified and used as input for refinements (such as adding structures or anchors).

[0286] ● The base station can perform the above-mentioned MEF. In addition, the base station can benefit from the knowledge of the above-mentioned functions.

[0287] ● Since the MEF has information about the surrounding related radar-UEs, it can guide the radar usage in the UE (which directions, which relative power levels, etc.) for higher efficiency and best use of its resources and minimum interference. It can also benefit from previous measurements and relative positions to structures in the map.

[0288] ●Since MEF has information about all radar-equipped devices in the area, it can filter out environmental dynamics from objects in the vicinity of other UEs - for example, the position and movement of an autonomous cart with a radar-equipped UE will be known and its impact on the radar analysis of other UEs can be compensated accordingly.

[0289] Various aspects of the inventive embodiments described above may be applied to provide a mechanism and technique for UEs and / or mobile devices to obtain their locations with better accuracy than provided by traditional network-based positioning solutions.

[0290] This is particularly useful when applied to, for example, autonomous carts driving on a factory floor or drones in indoor environments. However, this is by no means a complete list of applications; rather, there are a vast number of potential applications for this technology.

[0291] Embodiments consistent with the present invention provide many advantages over conventional techniques, which relate to the fact that very detailed self-positioning can be achieved without the need for classical sensor fusion methods. This is achieved by making clever use of modems and cellular systems in many ways. For example, and not limited to:

[0292] - In some embodiments, a modem is used to obtain a first (less accurate) position from a cellular system as a world reference.

[0293] ●In some embodiments, radar functionality can be built into the 5G modem at little additional cost.

[0294] • In some embodiments, the modem is used to communicate with a mobile edge server, which performs the relevant functions and implements much of the intelligent optimization.

[0295] Note also that the embodiments are not dependent on the radar operating in the 3GPP spectrum, and are not dependent on the radar being implemented as integrated in modem hardware, but this does constitute an advantageous embodiment.

[0296] The above embodiment provides a very accurate positioning solution for all devices with a 5G modem (radar enabled), without the need for dense installation of base stations or radio sources other than what is needed for communication, and without the need for cameras or other complex sensor fusion solutions. This is a solution that can be easily expanded to an entire factory, for example.

[0297] Additional advantages include:

[0298] ● Lower cost than alternative sensor fusion solutions for high-precision positioning, such as adding a camera module

[0299] ● Significantly higher accuracy than traditional radio-based solutions such as those commonly found in cellular or Bluetooth-compatible systems

[0300] ● Adding radar functionality to the modem can also add value for other types of applications, such as a feature-referenced map of what all the (radar-equipped) modems in a base station see and their surroundings, or edge cloud capabilities that enable multiple applications and benefits

[0301] ● Optimization methods to determine the WR frame where correlation occurs. Traditional methods require applying a pessimistic approach, which usually results in a larger WR frame.

[0302] ● Joint operation between edge cloud mapping services and UE-based radar sensing allows several optimizations, such as adapting the signaling and frequency of radar sensing to fit the topology and objects in the estimated area in the map and benefiting from the knowledge of other mobile units in the vicinity of the UE

[0303] ● Embodiments consistent with the present invention improve over time (as the device collects more samples, which can improve overall accuracy), and can then also recognize and adapt to changes in the environment

[0304] ● Devices can contribute insights about mapped areas that can only be seen by devices at that location (e.g., areas where radio signals from base stations alone do not reach).

[0305] Furthermore, embodiments in which mobile devices utilize mmWave SAR sensing as part of a self-positioning method provide several advantages over traditional methods, including:

[0306] ● Lower cost relative to alternative sensor fusion solutions for high-precision positioning, such as adding a separate radar module or camera module, or using a positioning solution with many anchor points or base stations to guarantee line of sight to multiple base stations simultaneously from all locations.

[0307] ●The ability to achieve significantly higher accuracy than traditional radar-based solutions

[0308] ●Achieve improvements over previous work by taking advantage of opportunities to exploit detailed structures beyond walls, floors, or ceilings, and other structures that cannot be clearly distinguished by conventional radar.

[0309] The present invention has been described with reference to specific embodiments. However, it will be apparent to those skilled in the art that it is possible to embody the present invention in specific forms other than those of the embodiments described above.

[0310] For example, various embodiments have referred to mobile edge servers. However, the use of mobile edge servers is not an essential aspect of the inventive embodiments. Instead, any server that performs the functionality described herein (e.g., a cloud server and a server located in a mobile network, such as but not limited to the edge of a mobile network) may be used, and thus the term "server" is used herein to refer to any such embodiments.

[0311] In another example, an embodiment involves only one WRP. However, in some embodiments, it is possible that multiple WRPs are available, each with its own confidence interval (i.e., in terms of precision). In such instances, multiple WR frameworks may be determined, and these WR frameworks may be used in a variety of different ways, such as:

[0312] a. The intersection between multiple WR frames can be determined and only the space that is compatible with all of them is considered for processing.

[0313] b. The union between multiple WR frames may be determined, and processing may then be configured taking into account the combined space(s). Such embodiments may be relevant in situations where multiple WR frames define discontinuous regions and there is no a priori knowledge available about where the device is.

[0314] c. For example, one or more of the multiple WR frameworks may be completely ignored when the system already has some knowledge about the location of the device, or if there are statistics indicating how certain WR methods perform in that particular area.

[0315] Therefore, the described embodiments are merely illustrative and should not be considered limiting in any way.The scope of the invention is further indicated by the appended claims, rather than merely by the foregoing description, and all variations and equivalents falling within the scope of the claims are intended to be embraced therein.

Claims

1. A method for determining a location of a mobile communication device (101, 551, 801, QQ110), the method comprising the mobile communication device (101, 551, 801, QQ110) executing: Receiving (701) from a network node (113, 563, 803, QQ160) serving the mobile communication device (101, 551, 801, QQ110) a request (321, 513, 525) to sense a local area (201) according to one or more parameters directing how and / or where the sensing is to be performed; In response to the request to sense the local area, generating (703) sensing data by performing (323, 515, 527) sensing according to the one or more parameters; delivering (705) the sensed data to the network node (113, 563, 803, QQ 160); and In response to delivering the sensed data to the network node (113, 563, 803, QQ160), receiving (707) a location (215) of the mobile communication device (101, 551, 801, QQ110) from the network node.

2. The method according to claim 1, comprising: Using GPS or network-based positioning, the mobile communication device initially obtains or generates a coarse position (211) of the mobile communication device (101, 551, 801, QQ110), wherein the coarse position (211) indicates with a certain accuracy that the mobile communication device (101, 551, 801, QQ110) is located within a local area portion (201) of a reference coordinate system; and providing the rough position (211) to the network node (113, 563, 803, QQ160), in: The rough position (211) is less precise than the received position (215); and The received request to sense the local area is responsive to providing the coarse location (211) to the network node (113, 563, 803, QQ160).

3. The method according to claim 2, further comprising: A confidence measure regarding the accuracy of the coarse position (211) is provided to the network node (113, 563, 803, QQ160).

4. The method according to any one of claims 2 to 3, comprising: The rough position (211) of the mobile communication device (101, 551, 801, QQ110) is generated using non-radar based sensing.

5. A method according to any one of the preceding claims, wherein: The sensing of the local area is radar sensing (117) of the local area; and The one or more parameters define an orientation for the first mobile communication device to assume when performing radar sensing of the local area.

6. The method according to any one of claims 1 to 4, wherein: The sensing of the local area is radar sensing (117) of the local area; and The one or more parameters define a location where radar sensing (117) of the local area is to be performed.

7. The method according to any one of claims 1 to 4, wherein: The local area sensing is millimeter wave synthetic aperture radar (mmWave SAR) sensing.

8. The method according to claim 7, wherein: The one or more parameters define a direction and / or orientation and / or device trajectory to be applied when performing the mmWave SAR sensing.

9. The method according to any one of claims 1 to 4, wherein: The local area sensing is based on non-radar sensing.

10. An apparatus for determining a position of a mobile communication device (101, 551, 801, QQ110), wherein the apparatus is adapted to perform a method according to any one of claims 1-9.

11. A mobile communication device comprising the apparatus according to claim 10.

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