Network-assisted self-positioning of mobile communication devices

Abstract

The location of the mobile communication device is determined. This involves the mobile communication device (101, 551, 801, QQ110) receiving (701) a request (321, 513, 525) for sensing of the local area (201) according to one or more parameters from a network node (113, 563, 803, QQ160) serving the mobile communication device (101, 551, 801, QQ110), the one or more parameters guiding how and / or where the sensing should be performed. In response to the request for sensing of the local area, sensing data is produced (703) by performing sensing according to the one or more parameters. The sensing data is communicated (705) to the network node (113, 563, 803, QQ160). In response to communicating the sensed data to the network node (113, 563, 803, QQ160), a location (215) of the mobile communications device (101, 551, 801, QQ110) is received (707).

Description

[Background technology]

[0001] The present invention relates to techniques that enable a mobile communication device to obtain information indicative of its location, and more particularly to techniques that utilize guidance from network nodes when sensing a local area to determine the position of a mobile communication device.

[0002] There is an increasing need for applications in modem-equipped devices to be aware of their own geographic location ("self-position") with high accuracy. There are several radio-based positioning technologies related to cellular communications, as well as Bluetooth-based technologies that provide positioning accuracy of a few meters (better under some conditions). In U.S. Patent Application Publication No. 20170307746(A1) (published in 2017), a vehicle compares a radar map with a reference data map to determine its own location. In U.S. Patent Application Publication No. 20190171224(A1) (published in 2019), a vehicle creates a map of its environment in a first step, then uses environmental features and stationary reflections to determine its own location, with non-stationary objects identified so as not to cause location errors. The referenced patent documents state that relative velocity (self-movement) can be derived based on direct measurements of the radial speed of a reflecting point from a stationary object, measured relative to an observer. This also enables the determination of rotation when using multiple spatially distributed radar sensors. Deterministic and probabilistic radar responses are used to map the environment and identify radar locations in Liu 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). U.S. Patent Application Publication No. 20200233280(A1) discloses a method for determining the location of a vehicle by matching radar detection points with a predefined navigation map comprising elements representing static landmarks around the vehicle. The publication also states that "the navigation map may be derived from a global database based on the vehicle's given location, e.g., from the vehicle's global position system."The approach described in Marck et al., "Indoor Radar SLAM: A Radar Application For Vision And GPS Denied Environments," European Microwave Conference, Nuremberg, Germany (2013), involves feeding radar images into a mapping and localization algorithm and using an iterative closest point algorithm to determine radar location and movement, while a particle filter optimizes measurement performance. As shown in Marck et al., radar-based simultaneous localization and mapping (SLAM) generally requires 360-degree panoramic high-resolution range information, which can be achieved either by a radar device with a rotating antenna or by an electronically scanned phased array radar.

[0003] In another disclosure, U.S. Patent Application Publication No. 20200256977(A1) (published in 2020) describes a vehicle using at least one radar sensor to generate a map of the environment and then comparing the vehicle's current measurements to the generated map to determine its own location. As also disclosed in U.S. Patent Application Publication No. 20200232801(A1), the vehicle uses radar to create a local map, then retrieves a map of the environment and correlates the two to determine its own location. Also described in U.S. Patent Application Publication No. 20190384318(A1), a device uses radar signals to create a local grid map and compares it to a map stored in the device's memory to determine its own location.

[0004] Other sensor options for localization include the use of cameras, where techniques such as SLAM can support more accurate relative positioning. Information from different sensors can be combined in so-called sensor fusion. Using radar-based SLAM, a device can map an unknown environment and determine its position in that environment.

[0005] There are several problems associated with conventional positioning technologies. For example, radio-based positioning, which relies solely on communication between one or a few base stations or anchor points and a device, produces results that are accurate to within only a few meters unless multiple anchor transmitters are provided, clock synchronization is extremely accurate, or several assumptions can be made about the environment or relative location. Such systems scale poorly in terms of accuracy (which is inconsistent, from about 2 meters at best, but sometimes a few meters) and cost. Furthermore, the location of the base station or access point must also be known extremely accurately, which increases installation costs and can cause problems if they are later moved.

[0006] Because indoor base station deployments are primarily targeted to meet the coverage demands of communication services, it is highly likely that there may be significant gaps in coverage of areas where sufficiently accurate location can be obtained. In some cases, this may even lead to zones and spots where traditional positioning techniques work poorly (although in some cases communication may still be possible).

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

[0008] Also, in any case, conventional radar self-location methods may not work at all, or at best cannot guarantee high accuracy, in some scenarios, such as when a device is located in (or moving along) a long hallway where there are no obvious landmark structures for the device to detect and determine distances, and where structures located within short range and distances are constant as the device is moved.

[0009] Another problematic situation occurs when the device is located in a very large room where relevant objects are very far away. In such a situation, the device may be able to detect structures via radar, but their distance results in lower detection accuracy compared to when the structures are located much closer to the device's location. In principle, structures in the ceiling could be used as detection landmarks by pointing the radar upward, but in most cases there are panels that present a very flat surface with few distinctive structural features. It is difficult for general radar detection to reveal structures from behind such ceiling panels.

[0010] Another scenario that presents self-positioning difficulties occurs in open areas dominated by moving people and / or objects that can obscure conventional radar signals and therefore hide static reference objects that the radar would otherwise detect. Without this detection, conventional radar-aided positioning techniques lack sensing information that could otherwise be compared with known reference structures with known locations to ascertain the device's location.

[0011] Overall, highly regular areas such as indoor walls, floors, ceilings, and hallways generally present a very flat, regular, featureless appearance, which complicates radar-aided positioning unless there are other significant, distinctive objects and structures within detection distance and with known locations.

[0012] PCT Publication No. WO2017139432 (published February 9, 2017) presents a solution for fingerprinting local depth-based sensor data using geometrically structured map data. The fingerprinting is based on geometric analysis. Radar is mentioned as one of many different types of potential sensors that can be used to generate depth-related information. However, the fingerprinting is not based on radar signals.

[0013] U.S. Patent Application Publication No. 20190171224(A1) (published June 6, 2019) presents a radar-based technique for fine-tuning self-location based on first creating a map of the environment and then fine-tuning self-location by correlating with the map. Both the map and the fine-tuning are performed by the device. The target area is, for example, a vehicle with the goal of enabling 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 research studies demonstrating the possible use of radar SLAM for positioning. However, such use requires extremely strong radar usage and is therefore an excessive consumption of energy and processing resources when it is only used to perform self-positioning in rapid succession with a relatively low amount of modem activity.

[0015] Therefore, there is a need for a self-positioning technique that addresses the above and / or related problems. Summary of the Invention

[0016] It should be emphasized that the terms "comprises" and "comprising" as used herein are taken to specify the presence of stated 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] Moreover, reference characters may be provided in some instances (e.g., in the claims and Summary) to facilitate identification of various steps and / or elements, although the use of reference characters does not imply or suggest that the so-referenced steps and / or elements should be performed or operated in a particular order.

[0018] According to one aspect of the present invention, the above and other objects are achieved in a technique (e.g., a method, an apparatus, a non-transitory computer-readable storage medium, a program means) 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 for sensing of a local area according to one or more parameters, the one or more parameters guiding how and / or where the sensing should be performed; and, in response to the request for sensing of the local area, producing sensing data by performing sensing according to the one or more parameters. The sensing data is communicated to the network node. In response to communicating the sensing data to the network node, a location of the mobile communication device is received.

[0019] In another aspect of some but not necessarily all embodiments according to the present invention, position determination includes initially obtaining or generating a coarse location of the mobile communications device, the coarse location indicating, with a degree of accuracy, that the mobile communications device is located within a local area portion of a reference coordinate system, and providing the coarse location to a network node, the coarse location being less accurate than the received location, and the received request for local area sensing is in response to providing the coarse location to the network node. In some but not necessarily all such embodiments, the mobile communications device provides to the network node a measure of confidence regarding the accuracy of the coarse location. Also, in some but not necessarily all still further embodiments, position determination also includes using non-radar-based sensing to generate the coarse location of the mobile communications device.

[0020] In yet another aspect of some, but not necessarily all, embodiments according to the present invention, the detection of the local area is a radar detection of the local area, and the one or more parameters define an orientation that the first mobile communications device should assume when performing the radar detection of the local area.

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

[0022] In another aspect of some but not necessarily all embodiments according to the present 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 the mmWave SAR sensing.

[0023] In yet another aspect of some but not necessarily all embodiments according to the present invention, the sensing of the local area is non-radar based sensing.

[0024] The objects and advantages of the present invention will be understood from a reading of the following detailed description in conjunction with the drawings. [Brief explanation of the drawings]

[0025] [Figure 1] FIG. 1 is a block diagram of an exemplary system according to an embodiment of the present invention. [Figure 2] FIG. 1 illustrates an exemplary WR frame. [Figure 3A] FIG. 1 is a signaling diagram illustrating aspects of one class of embodiments according to the present invention. [Figure 3B] FIG. 10 is a signaling diagram illustrating aspects of an alternative class of embodiments in accordance with the present invention. [Figure 4] FIG. 1 illustrates an example when a mobile device (UE) is in a surrounding area. [Figure 5] FIG. 10 is a signaling diagram illustrating aspects of an alternative class of embodiments in accordance with the present invention. [Figure 6] 4 is a flowchart of actions performed by a server in accordance with some embodiments of the present invention at some points. [Figure 7] 1 is a flowchart of actions performed by an exemplary mobile communication device configured to perform sensing to generate data that can be analyzed to estimate the location of the mobile communication device, in accordance with some embodiments. [Figure 8] FIG. 10 is a signaling diagram illustrating aspects of an alternative class of embodiments in accordance with the present invention. [Figure 9] FIG. 2 illustrates details of a network node, according to one or more embodiments. [Figure 10] FIG. 2 illustrates details of a wireless device according to one or more embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0026] Various features of the present invention will now be described with reference to the drawings, in which like parts are identified with the same reference numerals.

[0027] Various aspects of the present invention will now be described in more detail with reference to several exemplary embodiments. To facilitate an understanding of the invention, many aspects of the present invention are described in terms of sequences of actions to be performed by a computer system or other hardware elements capable of executing programmed instructions. It will be recognized that in each of the embodiments, various actions may be performed by specialized circuitry (e.g., analog and / or discrete logic gates interconnected to perform a specialized function), by one or more processors programmed with a suitable set of instructions, or by a combination of both. The term "circuitry configured to" perform one or more described actions is used herein to refer to any such embodiment (i.e., one or more specialized circuits only, one or more programmed processors, or any combination thereof). Moreover, the present invention may also be considered to be embodied entirely in any form of non-transitory computer-readable carrier, such as a solid-state memory, a magnetic disk, or an optical disk, containing a suitable set of computer instructions that will cause a processor to perform the techniques described herein. Accordingly, various aspects of the present invention may be embodied in many different forms, and all such forms are contemplated to be within the scope of the present invention. For each of the various aspects of the present invention, any such form of the embodiments described above may be referred to herein as "logic configured to" perform the described actions, or alternatively, as "logic" that performs the described actions.

[0028] The technology described herein addresses the need for devices to be able to obtain an accurate positioning of themselves (so-called "self-location") in areas where today's common technologies (e.g., GPS) do not perform well (e.g., in urban canyons, indoors, on factory floors, etc.). Furthermore, the goal is for devices to obtain an accurate positioning of themselves without the need for sensing capabilities other than radar (which may be provided by a radar-capable modem or by a separate radar module built into the device); in some, but not necessarily all, embodiments, an accelerometer or compass may also be used. However, in all such embodiments, the technology does not require cameras or extensive networks of base stations or other high-cost network-based positioning equipment.

[0029] 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 with slightly less accuracy when the objects are farther away.

[0030] In one aspect of the embodiments described herein, a world reference (WR) map is obtained based on other radio-based position solutions that can achieve at least 5-10 meter accuracy (potentially better, but also potentially worse). With the WR map as a starting point, information obtained by radar scanning is used to fine-tune the device's self-location within the WR frame. Hereinafter, the term "WRP" is used to refer to an estimated world reference position according to a standardized radio-based method, such as, but not limited to, Observed Time Difference of Arrival (OTDOA) (other techniques may be used to determine the WRP; see examples below). The term "WR frame" is used herein to refer to a local area around the WRP defined by the estimated accuracy of the WRP. For example, if the accuracy of the WRP is estimated to be ±5 meters, the WR frame is the area defined by the WRP ±5 meters in each direction. More generally, the WR frame is an exemplary embodiment of a local area portion of a reference coordinate system (which, in this embodiment, is the world reference map).

[0031] Fine-tuning the self-position within the WR frame is done by capturing radar responses according to preferred settings, uploading the captured radar responses to a Mobile Edge Server Function (MEF), and applying a correlation method (e.g., fingerprinting, or correlation against map information, or a combination) in which the provided radar data is correlated with previous information about the environment. Since the MEF knows that the device is within the WR frame area, it only needs to correlate against it. This can achieve the required level of positioning accuracy.

[0032] An important aspect of embodiments according to the present invention is the offloading of processing within the MEF and the data made available in the MEF, which allows for a large set of different optimizations and improvements. Furthermore, with this approach, the MEF will have highly accurate information of the positions of all devices, along with estimates of their trajectories, which is useful for many different tasks and optimizations and can be involved in correlations and provide further information about the environmental dynamics due to moving objects.

[0033] There are several different embodiments that apply the aspects described above, which are further described below.

[0034] 1 is a block diagram of an exemplary system 100 according to an embodiment of the present invention. The exemplary system 100 includes: - Mobile communication devices (or user equipment - UE) 101-1, 101-2, each equipped with a modem 103 and configured with radar functionality 105 (implemented either by using the modem 103 or with a separate radar circuit as shown in Figure 1). There may be more or fewer such devices in any particular embodiment. - A cellular communication system 107 comprising a base station 109 with which devices 101-1, 101-2 communicate. System 100 also includes or has access to positioning support 111 by any conventional technology (e.g., GPS, OTDOA, etc.), which provides coarse-grained location information for achieving WRP and WR frames. - A mobile edge server 113, which is a server preferably resident at the base station 109, to provide services that are local to the area served by the base station 109 and with lower latency than going over-the-top to a more distant data center (not shown). The mobile edge server 113 is preferably resident at the base station 109, although its location is not a necessary or essential aspect of embodiments of the present invention. - Device Attitude (also known as "Orientation") Estimator 115: uses the beam direction from the UE antenna panel towards the base station 109 as a reference in the spatial domain, for example using an IMU onboard the device (highly accurate), or alternatively calculated based on beam alignment towards a known reference (less accurate), or in another alternative using radio-based angle measurements (moderately accurate). The Angle of Arrival (AoA) and Angle of Departure (AoD), together with Round Trip Time (RTT) measurements, can produce a coarse position and panel attitude towards the base station 109.

[0035] These elements are further described below. For ease of description, unless it is necessary to distinguish one mobile communication device from another (e.g., distinguishing a first mobile communication device 101-1 from a second mobile communication device 101-2), the mobile communication devices will be referred to generically as mobile communication devices 101.

[0036] Mobile Device / UE101 It would be advantageous to utilize a mobile communication device 101 equipped with radar functionality 105. Such functionality could be implemented, for example, as a separate circuit and / or component. However, it would be more advantageous to do this via a modem 103 configured not only to perform communication functions but also to generate and transmit radar beams 117 and receive reflected radar signals. In a preferred embodiment, the UE modem 103 is extended with radar capabilities in accordance with known techniques. One such teaching is found in PCT Patent Application No. PCT / EP2020 / 069491. The added cost of the radar functionality over and above the cost of a regular 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. - communicating with functions in the base station 109 and the mobile edge server 113; - Use Network-Based Positioning 111 for coarse-grained WRP or WR frames (see above) - Improve positioning quality / accuracy as radar detection can be performed at different frequencies, different beam directions, and with different signaling types and durations with no or minimal impact on current 5G communications.

[0037] In some, but not necessarily all, alternative embodiments, the radar function 105 is implemented as a separate module that must be carefully set up to coexist (without causing significant interference) with the 5G modem to perform cooperative operation as described herein, which adds cost and complexity.

[0038] In yet a further alternative, it should be noted that despite references to 5G compliant modems herein, those skilled in the art will readily understand that modems compliant with other communications standards, or generations of the 3GPP standard, may be used instead.

[0039] UE101 with the above-described capabilities will typically be used in autonomous vehicles or other mobile units with a need for high-precision location, such as autonomous vehicles deployed in indoor environments (e.g., autonomous transport carts in a fully autonomous factory, surveillance drones in factories or dense urban areas, or autonomous transport vehicles at ports where GPS location may be quite poor due to non-line-of-sight conditions (partially indoors, building walls, highly stacked containers, etc.)).

[0040] In the case of autonomous vehicles, the need for positioning (e.g., frequency and purpose of use) may be known by the mobile device, and therefore its positioning capabilities may be context-based. For example, a mobile unit that is stationary may be able to stop or reduce positioning attempts, thus saving power and freeing up valuable resources. A mobile unit close to a structure, such as large machinery on a factory floor, may require a more accurate position, with a rate that depends on how fast it is moving. A mobile device farther away from a structure may have lower demands on positioning accuracy because it is not in imminent danger of colliding with something soon. Therefore, a very accurate position is not necessary for the mobile device to navigate to its intended coordinates (assuming that positioning accuracy can be increased as the mobile device gets closer to its target location).

[0041] The mobile device 101 may be equipped with an IMU or accelerometer, a gyroscope sensor, or a compass for device orientation estimation 115 to estimate the direction of the radar beam, however, alternative embodiments without such support are also described below.

[0042] Cellular System and Base Station 109 Support There are many known methods for network-based positioning that are capable of providing a coarse-grained location of a mobile communication device 101. Such methods include, for example, the use of Observed Time Difference of Arrival (OTDOA), Uplink Arrival Timing (ToA), Extended Cell ID (E-CID), Round Trip Time (RTT) measurements, Angle of Arrival (AoA), and Angle of Departure (AoD). Radio-based position solutions can achieve an accuracy of 5-10 meters (potentially better, but not guaranteed). The idea employed in embodiments according to the present invention is to use a coarse estimate of location as a World Reference Position (WRP) and then use additional sensing (e.g., radar sensing) to fine-tune the location within a WR frame centered on the WRP.

[0043] In the following, the term WRP is used to refer to an estimated world reference position according to a standardized radio-based method, such as OTDOA. Other coarse positioning techniques may be used as alternatives (see examples below). The term WR frame is used herein to refer to an area around the WRP defined by the estimated accuracy of the WRP (the accuracy estimate may be based on the method used, deployment characteristics, and estimates of key components that make up the uncertainty, such as synchronicity error). For example, if the accuracy of the WRP is estimated to be ±5 meters, then the WR frame is the area defined by a region centered at the WRP and extending ±5 meters from the WRP in each direction.

[0044] To further illustrate this point, Figure 2 shows an exemplary WR frame 201 that is a local area portion of a (larger) reference coordinate system 209. It should be understood that the reference coordinate system 209 is generally much larger (e.g., by several orders of magnitude) than the local area portion 201, and for this reason the embodiment shown in Figure 2 is not drawn to scale.

[0045] The UE 203 is at location 207 as shown. A coarse estimate (WRP) 211 of the location of the UE 203 is also shown, and as shown has an actual error 205. However, when the coarse estimate, WRP, is estimated, the degree of accuracy of the WRP is only known to be a certain amount ±ε. For this reason, the WR frame 201 is centered at the coarse estimate WRP 211. (Note: The WR frame 201 may alternatively be another shape, such as circular. The particular shape of the WR frame 201 is not a required aspect of embodiments of the present invention.)

[0046] Mobile Edge Server Function (MEF) A mobile edge server 113 located within the cellular system, for example in a base station 109, is a key element in some embodiments of the present invention. In one aspect, the mobile edge server 113 has access to a reference map 213 that represents objects and features that sensing will be expected to detect within different local area portions 201 of a reference coordinate system 209. The mobile edge server 113 manages the processing of provided sensor information (e.g., radar signal information provided by the mobile communication device 101) and has the ability to correlate with prior data, map information, and other knowledge of the environment to improve a coarse estimate 211 of the mobile communication device's location 207. The coarse estimate 211 of location is provided to the mobile communication device 101 in some, but not necessarily all, embodiments. Also, in one aspect of an embodiment consistent with the present invention, the mobile edge server 113 generates guidance for further sensing in the vicinity of the mobile communication device to generate relevant sensing information that can be used to refine the first estimate of location (i.e., coarse location) 211 into a second, more accurate estimate 215. Further sensing guidance can be provided to the mobile communication device 101 via the base station 109. Furthermore, because it is in communication with all UEs and knows their locations, further optimizations can be applied on a system-wide scale. These aspects are described further below.

[0047] In the exemplary embodiment shown in FIG. 1 , the mobile edge server 113 is a standalone entity. However, in alternative embodiments, the mobile edge server 113 may be implemented as an extension to functionality in the base station 109, or even handled on an Internet-connected server other than that of the base station 109. All such alternatives are contemplated as falling within the scope of embodiments of the present invention. However, it should be noted that it is advantageous for the mobile edge server functionality to be co-located with the base station 109, given the local relevance of this functionality and the low latency in communicating with UEs. For limited geographic areas, a database with map information and historical data, as well as optimizations based on knowledge of all UEs in the area, can be implemented efficiently. Furthermore, there is also significantly less performance-degrading latency in the case of a co-located system compared to a remote over-the-top data center.

[0048] It will also be pointed out later in this description that in some alternative embodiments in accordance with the present invention, some of the mobile edge functionality may be handled on the mobile device itself, however, such embodiments may be less efficient than other embodiments.

[0049] In a typical implementation, the mobile edge function may be assumed to serve one base station, although there is no major obstacle preventing the mobile edge function from serving many base stations. While the maps and correlations and statistics pertain 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 function, but the scope of the invention is not limited to having only one such mobile edge server 113 for this function.

[0050] To illustrate some aspects of embodiments of the present invention, the description now refers to the exemplary signaling diagram shown in Figure 3A. Features shown with dotted lines and boxes represent aspects that are optional to this exemplary embodiment. 1. Device 101: Self-positioning is initiated (step 301), resulting in a request for network-based position being communicated to base station 109 (step 303). The network performs a positioning technique (step 305) that produces a coarse-grained location for mobile device 101. Coarse-grained positioning techniques are known in the art, and all are contemplated as falling within the scope of embodiments of the present invention. 2. The base station 109 or network function then communicates the coarse location 211 to the device (step 307). This action is included in this embodiment to illustrate an environment where there is no direct communication of this information from the base station 109 to the mobile edge server 113, and thus this information is provided by the base station 109 to the mobile 101, which forwards this information to the mobile edge server 113. However, in alternative embodiments, such as that shown in Figure 5 described below, the WRP is passed directly from the base station 559 to the mobile edge server 563, and therefore there is no need for the mobile device 551 to receive and then forward the WRP. 3. Device 101: Receives a coarse position 211 from the network function, which then configures the WRP 211. Depending on the method used in a particular embodiment, device 101 may also receive an indication of the confidence level of its position (e.g., an indication of the degree of accuracy) from the network function 109. 4. Device 101: Emits radar sequence and receives response (step 309). Settings for the radar are based on the device's knowledge of features indicated on a map or on previously received guidance from the mobile edge server 113. For example, the network can look at a database to 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 a particular panel in those directions. In the absence of prior knowledge, the radar parameters are based on default parameters. This is explained further below. 5. The device 101 sends the received radar data to the mobile edge server 113 (step 311), the data including the parameter settings used in this detection, as well as the WRP 211. 6. The mobile edge server 113 (or an equivalent mobile edge function implemented in a network node, such as base station 109) determines a WR frame 201 (step 313) based on the WRP 211, the potentially received confidence level of that WRP estimate, and historical information regarding the WRP accuracy level of its location in that area (historically based on the mobile edge server's 113 database of previous estimates for determined accurate locations for all devices in that area). The area can be the entire network cell or more narrowly defined based on the WRP. This function is described further below. 7. The mobile edge server 113 determines (step 315) a second, more accurate estimate 215 of the location 207 based on the WR frame 201 and the received radar data. This function is described further below. 8 (Alternative 1). The mobile edge server 113 sends a second (more accurate) estimate 215 of the location 207 to the device (step 319). 9 (Alternative 1). The mobile edge server 113 updates its database with the relevant data from the device, as well as the determined precise location (step 331). This function is described further below.

[0051] In some cases, the mobile edge function (i.e., implemented as a separate mobile edge server 113 or as an auxiliary function of a network node, such as a base station 109) may not be able to determine the device's exact location with high reliability / accuracy. The reason may be that the environment changes and therefore there is no good correspondence in the data in the database (e.g., maps, previous radar signals, etc.), or that the WRP is particularly wrong in a particular case for some reason. One of the important advantages of the technology approach described herein is that the mobile edge function has a good overview of the map and potential reasons for insufficient reliability of the estimated location, and can therefore provide guidance to the mobile device 101 to perform additional measurements designed to improve the accuracy of the estimated location. Such guidance may, for example, - Move (an estimated distance in a known direction free of obstructing objects according to radar measurements) and take new measurements from there, sending the new sensor data along with the estimated delta movement to the mobile edge function 113. - Performing additional measurements based on different settings of radar signaling, e.g., higher power, larger bandwidth, longer signal duration, additional frequencies, and / or based on directing one or more radar transmissions in a different direction (e.g., using a different antenna panel) than that implemented earlier (e.g., with the expectation that the direction will be associated with a clearer and more distinctive radar signature (e.g., as determined from available map data and data from previous radar scans in the network)).

[0052] Based on this, the second half of the above flow becomes (as shown in the dotted box and signals in FIG. 3A): 8 (Alternative 2). The mobile edge function 113 determines the most suitable parameters to guide the performance of additional measurements needed for more accurate location (step 317). As mentioned above, this may involve the network looking at a database to determine which directions have a reliable amount of available data that can be correlated with the sensed data from the device, and requesting the device 101 to use a particular panel in those directions. 9 (Alternative 2). The mobile edge function 113 sends the second (accurate) estimate 215 of the location (determined in step 315) to the device along with an indication of the (lower) confidence level (step 319). 10. The mobile edge function 113 sends parameters to the device 101 to guide the performance of additional measurements (step 321). 11. The device 101 performs additional measurements as prompted (step 323). 12. The device 101 sends any additional collected data to the mobile edge function 113 (step 325). 13. The mobile edge function 113 determines an updated location based on the additional data (step 327) 14. The mobile edge function 113 sends the updated location along with the updated reliability to the device 101 (step 329) 15. The mobile edge function 113 updates its database with the relevant data from the device, as well as the determined precise location (step 331).

[0053] In an alternative class of embodiments, Figure 3B is an exemplary alternative signaling diagram that is equivalent in most respects to Figure 3A, except with respect to the determination of a coarse position. Instead of this being determined at the base station 109 (as shown in Figure 3A), a first (coarse) estimate 211 of position 207 (and possibly an estimate of the reliability of the first position) is determined by the mobile device 101 itself. This determination can be performed in several different ways (step 351), including, but not limited to, the use of Global Positioning System (GPS) circuitry within the mobile device 101. In all other respects, the actions shown in Figure 3B are the same as the corresponding actions shown in Figure 3A, and for this reason, reference is made to the description of Figure 3A for a description of these illustrated actions in Figure 3B.

[0054] Further explanation of some of the above steps is provided later in this specification.

[0055] For further explanation, Figure 4 shows an example when a mobile device (UE) 401 is in a surrounding area. According to aspects of the steps shown in Figure 3, the mobile edge function 113 estimated the device's location 207 as WRP 211 with a corresponding WR frame 403. It can be seen that the device's estimated location WRP is inaccurate by an amount δ. The shapes shown, filled with cross-hatching, represent nearby structures / objects (e.g., walls, machinery, furniture).

[0056] 3A, the UE 401 receives the WRP (i.e., the WRP is an estimated position) and performs radar operations according to the received guidance. In this exemplary case, radar signals are emitted in four beam directions, and for each beam direction, the UE 401 receives reflections and estimates or calculates radar response signal characteristics (e.g., latency, intensity, Doppler characteristics, shape, etc.). The WRP and the received radar data (e.g., raw reflected radar signals or processed versions of those radar signals with useful information extracted) are sent to the mobile edge function 113. (To illustrate an embodiment in which there is no direct communication of this information from the base station 109 to the mobile edge server 113, it is included here that the UE 401 sends the WRP to the mobile edge function 113. However, in an alternative embodiment, such as that shown in FIG. 5 described below, the WRP is passed directly from the base station 559 to the mobile edge server 563, thus eliminating the need for the mobile device 551 to do this.) 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 generated and maintained at known locations and / or previously recorded radar signals to estimate possible locations within the WR frame 403. Based on the mobile edge function's collective knowledge of the maps 213 corresponding to the WR frame 403 (known objects and their respective locations), as well as recorded radar signal characteristics from different locations within the WR frame 403, a more accurate estimate of the UE's location 207 is determined. In effect, it may be determined that only certain points in the WR frame 403 may be possible, given different distances and signal characteristics from different objects and structures.

[0057] In some theoretical situations, there may be multiple possible positions within the WR frame 403 that could lead to the same set of radar responses, but then one iteration with additional data (e.g., by guiding the device 401 to move a distance and perform another radar measurement that is further analyzed) will generally be sufficient to resolve the uncertainty, except in extremely rare circumstances.

[0058] Because there are multiple beam directions and multiple objects being reflected, the correlation analysis is preferably configured to be able to handle some deviations, for example, when individual objects have moved but the majority of the scene remains stable. In some cases, more confusing changes in the scene may occur (larger portions of the objects have moved). The optimizations described below can help resolve such situations.

[0059] Note that even though the edge mobile function 113 correlates only for positions within the WR frame 403, the edge mobile function 113 uses reflections from objects and structures outside the WR frame 403 (e.g., from object 405). The radar beam direction, and also the WR frame 403, need not be contained only in the XY dimension, but can also include an upward and downward direction depending on the system and needs.

[0060] In some embodiments, radar data from a device can include timestamps and estimated mobility vectors during the scan to take into account scans made from different locations. This allows for more analysis and accuracy in the mobile edge function 113 as it takes multiple locations into account, allowing for more consolidated knowledge of the trajectories of all devices in the area.

[0061] Some of the aspects described above are further described below.

[0062] Emitting radar sequences and receiving responses In a simplistic implementation, device 101 can emit a radar beam in all directions according to some default radar settings and send received signal responses (along with the WRP and radar settings) to mobile edge function 113. However, there are several problems with this. - Radar settings may be suboptimal with respect to the real context (e.g. distances to relevant objects in different directions, width of the beam, some types of objects requiring some radar settings for optimal performance). - When radar is implemented in the spectrum specified by the 3GPP standards, radar operation must take interference into account, both with respect to interference caused by the radar signal to other devices and interference from other devices that may disrupt the radar return. Depending on the relative position of the device with respect to other devices and base stations, there may be some directions, frequencies, and output power levels that must be avoided. - In the case of a moving device, close proximity to other devices under mobility and to some important objects may require closer real-time action or attention, while some other situations may be more relaxed regarding real-time requirements.

[0063] An embodiment according to the present invention allows for optimized operation since the mobile edge function 113 has knowledge of the entire map, where all devices are located and their recent movements, as well as information about all base station locations. The optimization allows the radar to adapt to the environment depending on the expected distance and type of structures; the radar output power, waveform, and duration may be different in different directions. This allows for optimization of: A. When the mobile edge function 113 sends the precise location to the device 101, it also sends certain important information about the area / neighborhood, such as proximity / direction to other mobile devices and base stations, proximity to some important objects or structures, and other important relevant information that is needed (e.g., whether there are some rapid changes in the environment). B. When the data in step (7) above is not sufficient for an accurate determination of the position, for example because some important object has moved, the mobile edge function 113 can send further invitations to receive additional data not only to the current device (step (10) above) but also to other nearby devices, which can help gather additional updated knowledge about the environment from their respective positions. The exact protocols and rules for such a procedure are beyond the scope of this description, but there are several different alternative solutions that are within the capabilities of one skilled in the art (e.g., a UE using this positioning service can also be assumed to support additional measurements when needed, if the UE has no issues supporting additional measurements). C. Further herein below, an alternative embodiment is described which involves integrating certain optimized measurements into every radar operation.

[0064] By performing several subsequent positioning fixes, potentially using intermediate movement estimates (if the device has the ability to estimate movement), the mobile edge function 113 can determine location with greater accuracy and, in some, but not necessarily all, embodiments, can apply optimizations such as reducing the size of the WR frame 403 for certain cases, correlating to only some parts of the map, etc.

[0065] The mobile edge function 113 determines the WR frame 403. There are several ways to determine the WR frame 403. One of the simpler approaches uses a radio-based positioning scheme that includes indicating the degree of accuracy that can be expected (e.g., ±5 meters), and the WR frame 403 would then be WRP ±5 m in each dimension. See, for example, FIG. 2. Also, as previously mentioned, the WR frame 403 could alternatively have another shape, such as, but not limited to, circular, ellipsoidal, or spherical.

[0066] If the position has been 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 utilized. A much smaller WR frame 403 can be used as long as the amount of time since the previous location determination is not large.

[0067] However, when the confidence interval becomes pessimistic (the worst case degree of accuracy for the method must be taken into account), one aspect of an embodiment of the present invention provides a further improvement.

[0068] More specifically, for each performed self-positioning, the mobile edge function 113 adds relevant information to the stored history of WRP, the methodology employed to arrive at the WRP, and the final precise location produced from the radar analysis. Over time, the mobile edge function 113 builds up good statistical knowledge of the actual confidence intervals for different WRP methods in different parts of the overall area; some locations may have reasonably good WRP accuracy (e.g., line of sight with a base station), while others have extremely poor WRP accuracy (e.g., due to difficult radio conditions). The mobile edge function 113 can further collect statistics regarding, for example, deviations in WRP accuracy between different modem models. Such collected information can be used as the subject of machine learning / analysis, for example, to enable accurate predictions and / or estimates and / or to identify how different factors affect accuracy. Therefore, after implementing a number of precise positioning services, some, but not necessarily all, embodiments according to the present invention enable the mobile edge function 113 to be able to take into account both environmental conditions as well as modem type differences to provide an optimized WR frame 403. This also benefits the positioning accuracy of non-radar UEs.

[0069] Mobile edge function 113 determines precise location Given the knowledge that the mobile device is within the WR frame 403, the task is for the mobile edge function 113 to correlate the radar signal data with the data in the mobile edge server 113. This can be done according to several different approaches, including but not limited to: A. The radar data provides information about different beams to objects at a certain distance. The mobile edge function 113 correlates this against map information and / or previously recorded radar signals acquired at known locations maintained by the mobile edge function 113, and determines the most likely location within the WR frame 403 by the smallest number of anomalies (reflections without object correspondence in the map, or objects without radar reflections), or any other algorithm (e.g., an algorithm that takes into account the size of the anomaly or deviation) using the best correlation. In this regard, it may be advantageous to run the algorithm again or recalibrate it based on historical data for several intervals, for example, so that it can be determined whether the number of anomalies can be significantly reduced if some structures or reflections are ignored. Anomalies may indicate objects that have been moved or that have troublesome reflective properties, which are recorded for future correlation analysis and potential updates to the map information. Additionally, the mobile edge function 113 may detect patterns that change over time, such as some objects in the environment that are only present at some times, in which case the correlation data may include timing variables associated with these objects. B. The radar signal is correlated with a database of previous radar signals from different locations in the WR frame 403 according to fingerprinting techniques (e.g., techniques that rely on known landmarks in the environment). Again, detected timing patterns can be determined and exploited (see paragraph above). C. A combined approach between (A) and (B) when there is no previous radar signal from the location of interest. In such a case, the methodology described in (A) is used, but the radar signal is stored for future application of the methodology described in (B).

[0070] The mobile edge function 113 updates its database with the relevant data. An aspect of embodiments in accordance with the present invention is the ability of the mobile edge function 113 to correlate radar data against recorded map data / databases, perform optimizations based on the recorded data, and have an overall view of the system status (e.g., recent position processes of the UE and its trajectory, recent position processes of key objects of interest, etc.).

[0071] The database of mobile edge capabilities includes: Map information with detailed location data of objects and structures in a form that lends itself to correlation against radar returns (at different radar parameter settings). Radar reflectivity characteristics from different directions of those objects and structures identified in the map. These can be initially calculated based on the structure map (described above), given some knowledge of the material and shape. These can also be initially measured based on an augmented device with high-precision sensors and need only be done once. In one aspect of an embodiment according to the invention, this information is continuously updated when the system is in use. Radar signal returns from real devices in use, annotated with different parameter settings of the radar in the measurements. · The original WRP location and method for each positioning instance, along with the precise location derived from radar correlation.

[0072] Additionally, the mobile edge function 113 maintains an updated map with all connected devices using this positioning service. This allows the mobile edge function 113 to apply optimizations with respect to having devices compensate for weak information in some areas and with respect to which beam directions may experience more interference from radar transmissions (3GPP bands and / or other). Finally, this information also enables additional types of services based on detailed positioning and trajectory information of all devices in the area, along with updated views of objects and structures in the area, without requiring the devices to be equipped with cameras, which in some cases would add cost and may be seen as a privacy issue. Further details regarding such services are beyond the scope of this description.

[0073] Creating database data for mobile edge functions 113 The mobile edge function 113 database needs to be initially populated and then later iteratively refined through use; the more the database is used and the more devices there are, the better and more complete the database becomes.

[0074] In one embodiment according to the present invention, initial content can be recorded using an augmented device that has additional sensors to determine the distance the augmented device has been moved from a known precise location. Furthermore, a map of the environment with all static objects and structures can be created. Creating the initial map only needs to be done once (in a factory, this can be walls, large machinery, and other prominent objects), but it can exist from the start. The augmented device records radar signals and determines how radar echoes make some objects visible at different distances. All this data is recorded in a database, and the map of structures and objects is updated from a radar perspective based on their visibility and characteristics.

[0075] In another embodiment in accordance with the present invention, an augmented device with a camera creates a map of the environment using some kind of simultaneous localization and mapping (SLAM) (there are many solutions that are compatible with embodiments of the present invention) and then uses radar to annotate or update the map based on its radar reflectivity characteristics. This SLAM implementation does not need to be optimized, as it is essentially done only once. It is also possible to perform this procedure again at a different interval, but in that case, it is not to create the initial map and radar signal content, but to update the database based on some objects having moved or been added, i.e., essentially based on confirmation from recent radar measurements that an anomaly has been identified.

[0076] Positioning accuracy The positioning accuracy of the techniques described herein depends on radar signaling characteristics.

[0077] For example, a wider signal bandwidth enables more accurate measurements, resolves more details in the target, and therefore provides more information for positioning. Furthermore, the signal-to-noise ratio is fundamentally important to radar measurement quality, and this can be improved by increased output power or a longer correlation time. However, the required output power and correlation time increase rapidly with target distance, and beyond a certain distance, resolving small objects becomes infeasible. Long correlation times also become increasingly difficult to combine with movement. To minimize resources used and maximize positioning accuracy, it is therefore better, when possible, to target nearby objects with relatively low power and duration, but with a high signal bandwidth. The position accuracy will be a fraction of the inverse signal bandwidth multiplied by the speed of light. For example, when a multi-GHz signal bandwidth is used, the accuracy obtained by correlation of signal modulation can be several centimeters.

[0078] In general, more distant objects will likely also result in somewhat less accurate measurements than those in the immediate vicinity. This is due, in part, to the longer delay before reception, which impacts clock jitter more. This is also due to the more potential unknowns of such long and wide signal propagation paths (beams have finite opening angles). However, for most applications, reduced accuracy is acceptable when nearby objects are missing; positioning needs to be more accurate as the device approaches objects in its vicinity. Furthermore, other radio-based positioning technologies perform worst when significant structures and objects are nearby (more difficult radio channel, no line of sight to the base station), which is precisely the scenario in which the currently described technology can provide accurate positioning down to centimeters. Thus, the nature of the methods makes them complementary.

[0079] A listing of all possible radar characteristics that can be leveraged for a more thorough assessment is beyond the scope of this description, as it also depends on the radar implementation in the device, but overall, a key advantage of the currently described technology is that the mobile edge function 113 has a holistic understanding of the environment that allows guidance to optimize radar measurements as needed.

[0080] Alternative embodiment: Guided radar operation To illustrate some further aspects of some, but not necessarily all, alternative embodiments in accordance with this invention, the description now refers to the exemplary signaling diagram shown in Figure 5. Features shown with dotted lines and boxes represent aspects that are optional to this exemplary embodiment. 1. The mobile device 551 starts its self-positioning application (step 501) and therefore sends a self-location initialization request (step 503) to the base station 559 or other network function. 2. The base station 559 or other network function performs an initial network-based positioning function to determine a WRP (potentially with a level of reliability) (step 505) and provides this to the mobile edge function 563 (step 507). 3. The mobile edge function 563, in response, determines the WR frame corresponding to the location WRP (step 509) and also determines parameters for guiding radar operation based on the area, relevant objects in the vicinity, its allowed use of radar in certain frequency bands, etc. (step 511). In some, but not necessarily all, embodiments, the guidance may also be based on whether and what kind of radar capability the device 551 has (e.g., whether the device 551 has SAR capability). Device capability information may be provided to the mobile edge function 563 in any number of ways, including, but not limited to, receiving device capability information from the device 551. By performing sensing according to the mobile edge function's guidance, the device 551 can always perform its radar operation in an optimized manner that takes into account the mobile edge function's holistic knowledge of the map in its 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). 4. The device 551 then emits a radar sequence and receives a response (step 515). The settings for the radar are based on the device's knowledge of features indicated on the map or previously received guidance from the mobile edge server 113. This is described further below. 5. The device 551 then sends the received radar data to the mobile edge server 563 (step 517) along with the parameter settings used in this detection, since in some embodiments these may deviate from the guidance provided by the mobile edge server 563. 6. The mobile edge server 563 determines the precise location based on the WR frame and the received radar data (step 519) and sends this to the mobile device 351 (step 521). 7 (Alternative 1). The mobile edge server 363 updates its database with the relevant data from the device 351 as well as the determined precise location (step 535).

[0081] As in the previously described embodiments, in some cases, the mobile edge function may not be able to determine the device's exact location with sufficient reliability / accuracy using the sensor data it has. To address this issue, the mobile edge function, having a good overview of the map and potential reasons for the insufficient reliability of the estimated location, provides guidance to the mobile device 551 to perform additional measurements designed to improve the accuracy of the estimated location. Such guidance may, for example, - Move (an estimated distance in a known direction that is free of obstructing objects according to radar measurements) and take a new measurement from there, sending the new sensor data along with the estimated delta movement to the mobile edge function 563. - Performing additional measurements based on different settings of radar signaling, e.g., higher power, larger bandwidth, longer signal duration, additional frequencies, etc.

[0082] 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 its location. By directing the device 551 to perform sensing in that direction and report the sensing data to the server 113, the server's database of historical sensing data may be supplemented and thereby improved for future use.

[0083] Based on this, the second half of the above flow becomes the following (as shown in the dotted box and signals in FIG. 5): 7 (Alternative 2). The mobile edge function 563 determines the parameters for performing the most suitable additional measurements needed for more accurate location (step 523). 8. The mobile edge function 563 sends parameters to the device 551 to guide the performance of additional measurements (step 525) 9. The device 551 performs additional measurements as prompted (step 527). 10. The device 551 sends any additional collected data to the mobile edge function 563 (step 529). 11. The mobile edge function 563 determines an updated location based on the additional data (step 531) 12. The mobile edge function 563 sends the updated location along with the updated trust level to the device 551 (step 533) 13. The mobile edge function 563 updates its database with the relevant data from the device, as well as the determined precise location (step 535).

[0084] Additional Alternative Embodiments Centralized vs. Decentralized Databases Portions of the database may be downloaded and stored on the device / UE 101 such that the correlation / fingerprinting is performed at the device / UE 101 rather than at the mobile edge function 113, potentially to operate at even higher correlation rates or to reduce communication resource usage (and free up even more opportunities for radar operation). In an advantageous embodiment, the results (raw data measurements, not actual self-location) are shared with the mobile edge function database so that the data may be available to serve other UEs.

[0085] Thus, some embodiments in accordance with the present invention do not rely on the mobile edge function 113 including all of the functionality described above. To the contrary, the aspects described above are applicable even in a distributed solution where portions of the processing and data are managed by individual devices, allowing those devices to benefit from sharing data, map information, environmental changes, and statistics through functions such as the mobile edge function 113. Furthermore, knowledge of all of the device locations allows for many advantages, which in various described embodiments are described as residing in the mobile edge function 113.

[0086] 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 that the devices will need to share and collaborate in a manner that is naturally managed by the mobile edge function 113 in the description set forth above. Thus, while the mobile edge function 113 and device functionality constitute an advantageous embodiment, other embodiments are contemplated that are within the scope of the present invention.

[0087] Some important structures or radar posts In some embodiments, certain structures or objects that have a distinct radar reflective signature and are considered stable in their location may be identified and given special consideration. In the general case, this may be an object or structure with distinct radar reflective properties, but in specific cases, this may be a specific reflective object designed for this purpose.

[0088] In one class of embodiments, the environment in which the device is located may include several dedicated reference points (e.g., radio reflectors with distinct RF characteristics, passive anchor points, or iconic objects). The objects may be broadband reflectors or resonant structures with different properties at specific resonant frequencies. The objects may be polarized to reflect only one polarization. Still further embodiments include combinations of the above. There may also be different properties in different directions. Some structures may change shape with environmental conditions, enabling remote sensing using radar.

[0089] In one aspect, these reference points can be placed in environments with specific location patterns, which can help map correlation or fingerprinting algorithms increase their convergence rate. Additionally, when there is ambiguity, the mobile edge function 113 can guide the device to beam its radar toward such known objects to determine or confirm location or orientation.

[0090] Leveraging nearby devices Because the mobile edge function 113 maintains an updated view of where all radar-equipped devices are located, the system can leverage this by having the devices transmit / receive directly between each other to gain further knowledge about their relative locations, as well as, in the case of bistatic radar operation, a better view of objects between the devices, based on their last known positioning requests and estimated trajectories. The details of this are beyond the scope of this description.

[0091] How to obtain an alternative coarse-grained world (absolute) reference It is expected that coarse-grained World Reference Position (WRP) can be obtained by several alternative means with varying costs in terms of power requirements, position quality, and connectivity requirements. On-board GPS receivers can be used, if available, or combined with network positioning for even higher quality position, faster collection (so-called assisted GPS), etc.

[0092] In another aspect of some, but not necessarily all, embodiments, the aspects described above can be used to provide a coarse-grained starting point by inferring where a device might be, given a map of the environment. Such a solution would be completely self-contained and would not depend on having GPS and line-of-sight to a satellite.

[0093] Yet another embodiment utilizes previous data points and reuses historical data acquired by the same system based on the age of the data points (more recent measurements are generally preferred) and the assumed shift in position over time, which will provide the most energy-efficient generation of a coarse-grained world reference.

[0094] It should be noted that as the positioning system operates and continues to refine its actual location, it also functions to provide new and accurate reference points to device 101, effectively sub-planting the 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.

[0095] Alternative device sensors, such as an IMU, accelerometer, or compass Although various embodiments in accordance with the present invention do not rely on the use of an IMU, compass, or gyro, the functionality would benefit from that additional sensor, primarily to determine orientation. Knowing the device's orientation simplifies correlation of radar signals to maps and simplifies guided radar operations, as different directions can be pointed to by the mobile edge function 113. However, by analyzing correlations from different beams across multiple locations, it is possible for the mobile edge function 113, in cooperation with the device, to determine the device's orientation without this additional sensor. However, this requires more effort.

[0096] Note that an IMU in the most general sense can be anything 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 microelectromechanical systems (MEMS) sensor setup with gyros, accelerometers, and magnetometers, giving the device nine degrees of freedom (9DoF). While this is not necessary for the functionality of embodiments of the present invention, it can be used to provide additional data points to validate measurements and also to fine-tune the resulting position when combined with radar-based self-positioning. Note that typical IMUs are prone to drift over time (when used as a dead reckoning function) and generally need to be realigned with more fixed data points. The radar-based self-location provided by the embodiments of the present invention described herein provides just that functionality.

[0097] In the absence of other means (e.g., intrinsic, such as an IMU) or extrinsic methods (using an external entity, a.k.a. a virtual IMU, that provides tracking of device inertial motion and orientation changes), various embodiments will still work accurately as the map correlator function not only provides a reliable baseline (once it locks onto the correct and identified radar feature), but also measures the exact offset (or distance) from the identified (or fingerprinted) feature.

[0098] Adding information from beam directionality in communications from a device that knows the panel being used towards a base station will provide the relative orientation of this panel towards a base station 109 with 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 may detect changes. Or, if the device periodically performs communications towards the base station, the device will also have this updated during self-positioning tracking.

[0099] Additional aspects of embodiments of the present invention will now be described with reference to Figure 6, which is a flowchart of actions performed by an exemplary server (e.g., a network component configured with edge mobility functionality) configured to determine the location of a first mobile communication device in some respects, in accordance with some embodiments. In other respects, the blocks shown in Figure 6 may also be considered to represent a means 600 (e.g., hardwired or programmable circuitry or other processing means) for performing the described actions.

[0100] As shown beginning in FIG. 6 , the process includes a server obtaining a first estimate of a location of a first mobile communication device, the first estimate of location indicating, with a first degree of accuracy, that the first mobile communication device is located within a local area portion of a reference coordinate system (step 601). The server then determines one or more parameters for local area sensing (step 603) and sends a request for local area sensing according to the one or more parameters to one or more of the first mobile communication device and another mobile communication device (step 605). In response to the request for local area sensing, the server receives local area sensing data (step 607). The server uses the local area sensing data to produce a second estimate of a location of the first mobile communication device, the second estimate of location indicating, with a second degree of accuracy, that the first mobile communication device is located within the local area portion of a reference coordinate system, the second degree of accuracy being more accurate than the first degree of accuracy (step 609).

[0101] In some, but not necessarily all, embodiments according to the present invention, the accuracy of the location estimate is further improved by the server guiding even further sensing of the local area by the mobile communication device and using this further sensing data to determine even further parameters for further improving the estimated location of the first mobile communication device. The number of times that guided sensing and subsequent further refinement of the estimated location may be performed is implementation dependent and may, for example, be a fixed number of times or alternatively, may be based on reducing the error level to an acceptable level (the threshold for acceptability is implementation dependent). All such embodiments are represented in FIG. 6 by action 611.

[0102] In view of the scope of the embodiment represented by FIG. 6 , it will be understood that the term “first estimate of location” may generally be understood to refer to the most recently obtained and / or determined estimate of the location of the mobile communications device, and the term “second estimate of location” may generally be understood to refer to a subsequently determined location estimate having greater accuracy than the accuracy of the first estimate.

[0103] The description then encompasses exemplary embodiments that focus on certain aspects of the mobile device itself.

[0104] 7 is a flowchart of actions performed by an exemplary mobile communication device configured to perform sensing to generate data that can be analyzed to estimate the location of the mobile communication device, in accordance with some embodiments. In other respects, the blocks shown in FIG. 7 may also be considered to represent a means 700 (e.g., hardwired or programmable circuitry or other processing means) for performing the described actions.

[0105] As shown in FIG. 7 , the process includes a mobile communication device receiving a request from a network node serving the mobile communication device for sensing of a local area according to one or more parameters guiding how and / or where the sensing should be performed (step 701). The type of sensing performed varies in some alternative embodiments. For example, some embodiments employ radar sensing as described 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 an inertial measurement unit (IMU), acoustic sensing (e.g., ultrasound), sensing via a combination of different antenna panels on the (e.g., mobile) device, and sensing with synthetic aperture radar (SAR). Embodiments employing SAR are described in more detail later in this description.

[0106] In response to the request for local area sensing, the mobile communications device produces sensing data by performing sensing according to one or more parameters (step 703). As previously described, this may involve the mobile communications device performing sensing in a particular direction and / or moving to a particular location where sensing is performed.

[0107] After producing the sensory data (either raw sensory data or, in an alternative embodiment, sensory data that is the result of processing the raw sensory data by the mobile communication device), the mobile communication device communicates the sensory data to a network node (step 705).

[0108] In response to communicating the sensing data to the network node, the mobile communications device receives a location of the mobile communications device (step 707). The location may be generated by the network node, for example, as described above.

[0109] As mentioned above, mobile communication devices can employ several different types of sensing. SAR sensing is one type that can be advantageously used in embodiments of the present invention. SAR sensing involves making radar measurements from multiple radar antenna positions relative to a target. Known processing techniques are employed to combine recorded radar sampling data to form SAR radar images with higher spatial resolution than is possible using single-shot radar. When SAR is used in embodiments in accordance with the present invention, particular benefits are achieved by using mmWave radar signals because the short wavelength and wide available bandwidth lead to high resolution, which, when combined with the ability of mmWave signals to penetrate materials better than higher frequency signals, leads to the creation of high-resolution images with an increased signal-to-noise ratio. This enables the detection of features that are normally hidden against other sensing techniques (e.g., “seeing through” fabric or “seeing through” walls).

[0110] Techniques for implementing mmWave radar in mobile communication devices are known in the art, such as the embodiment shown in 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 added cost of radar functionality on top of the cost of a regular 5G modem is minimal. This means that the modem can be used for essential functions of the positioning system, including, for example: - Communicating with functions in base stations and mobile edge servers - Radar detection at mmWave frequencies, different beam directions, and with different signaling types and durations

[0111] While a 5G modem is mentioned, this is for illustrative purposes only and is not a required aspect of embodiments of the present invention. Those skilled 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.

[0112] Using the device's modem for radar functionality is not a required aspect of embodiments of the present invention. In alternative embodiments, radar functionality may be provided by a separate module that communicates through a 5G modem to access network-based aspects according to embodiments in accordance with the present invention. However, having a separate radar module adds cost and complexity.

[0113] In another aspect, mobile devices in some, but not necessarily all, embodiments are equipped with an IMU or accelerometer, gyro, compass, or other sensor(s) to extract / estimate SAR scan trajectories, which may also be used to understand the device's orientation and relative movement to further support positioning schemes (e.g., as may be required to implement the network-guided scan described above).

[0114] Generally, radar detection capabilities in mobile devices can then be achieved with minimal hardware modifications to the mobile device's wireless communication circuitry. For example, in 5G cellular phones, mmWave radar functionality can be implemented by using an RF beamforming transceiver. By performing mmWave radar measurements from varying positions relative to a hidden object (e.g., within a wall), SAR processing techniques can combine recorded data from multiple radar antenna positions to form a high-resolution SAR radar image of the hidden object. Other sensors, such as an IMU, can be used to estimate / extract radar sampling positions and compensate for variable movement of the SAR scan trajectory. SAR radar technology can be leveraged to help mobile devices locate themselves in a map or against recorded radar data through fingerprinting methods.

[0115] A mobile device equipped with mmWave radar moves around a scene and performs SAR scans on objects surrounding the mobile device (e.g., walls, floors, and ceilings). By looking 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 fingerprints by which wall features can be correlated with stored map information. From the correlation results, the device's location in the map can be estimated.

[0116] The accuracy achievable with SAR-assisted methods is far better than what can be achieved with older radar-based positioning solutions. Application examples include autonomous carts driving around on a factory floor, or drones in indoor environments, but there are many other potential applications for this technique.

[0117] As mentioned above, a mobile device performing self-positioning may find itself in some areas where conventional radar detection from the device cannot capture enough recognizable objects to locate the device itself. Such areas may be, for example, long hallways with flat walls or areas where static recognizable objects may be occluded by moving people / objects that dynamically change the radar environment. If the device is equipped with an IMU, this can assist to some extent in making predictions (e.g., within a hallway), but cumulative IMU error may be increased, thereby reducing overall accuracy.

[0118] To invoke SAR-assisted self-location, a determination should be made whether the device has entered such an area, which may be based on one or a combination of the following: - Currently known estimates of the location and movement vector of the device - Edge cloud knowledge from previous self-positioning actions of the device or other devices - Knowledge of architectural structures that may be included in maps stored in the edge cloud - Knowledge of densely populated areas where moving objects (such as people at the entrance to a shopping mall at peak hours) block the radar view towards recognizable objects

[0119] The radar self-positioning performance of devices in such areas may be improved by adding radar reflectors / anchors with some detectable characteristics, however, for various reasons (e.g., aesthetic reasons), this may not be a desirable and / or feasible alternative.

[0120] The mmWave SAR techniques described herein allow a device to detect structures within building materials with high resolution. Consider, for example, a wall. A wall generally consists of an invisible, equidistant load-bearing material, either hard wood or metal, covered by an exterior plasterboard. Other objects that may be located within the wall include cables or other electrical components or water pipes. These features can be detected by SAR and utilized by the device to determine its own location.

[0121] An exemplary system utilizing mmWave SAR technology for self-positioning comprises: - A mobile device (e.g., smartphone, tablet, XR / VR headset) with either an mmWave radar module or a modem (or UE (User Equipment)) enhanced with mmWave radar capabilities. The device may also be equipped with an IMU sensor to estimate / extract radar sampling position. - A cellular communication system in which the UE is in communication with a base station. Edge Cloud Server: This can be a separately located network entity, or alternatively, a server residing in a base station to provide services that are local to the area and with lower latency than going over-the-top to a data center beyond the telecom operator's perimeter. When a mobile device performs mmWave radar measurements from varying positions on a hidden object (e.g., in a wall, above a ceiling), SAR processing techniques are employed by the mobile device in some embodiments to combine recorded data from multiple radar antenna positions to form a high-resolution SAR radar image of the hidden object. Other sensors (e.g., an IMU) may be used to estimate / extract the radar sampling position and compensate for variable movement of the SAR scan trajectory. In an alternative embodiment, a communications modem in the mobile device is used to transfer radar data to a network, which then processes the radar data to reconstruct a SAR image and correlates 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 (possibly computationally expensive) processing of the radar data and correlation with a set of known map features may also be performed using a cloud server, a mobile edge function, or even on the device itself (albeit at the cost of using additional power that may drain the battery). On-device processing assumes that the World Reference Position (WRP) and map data have been downloaded to the device. In one use case, a mobile device equipped with mmWave radar performs SAR scans on the wall(s) as it moves along one or more corridors / walls. By seeing through the wall at high resolution, the device can detect detailed structures within the wall (as shown in the SAR radar image). The detected structure(s) (or features extracted from the SAR radar image) can then be used as a fingerprint and correlated to a map where known features of the wall are stored. From the correlation results, the device can estimate its own location in the map. The method can be further extended to floor (or ceiling) SAR scans.

[0122] To illustrate some further aspects of some, but not necessarily all, alternative embodiments in accordance with the present invention, the description now refers to the exemplary signaling diagram shown in FIG. 8 . Features indicated by dotted lines and boxes represent aspects that are optional to this exemplary embodiment. In this example, a mobile device 801 and a mobile edge server 803 can communicate directly with each other. The mobile device is served by, for example, a base station 805, but the base station does not participate in mmWave SAR-assisted self-positioning actions. 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 skilled in the art will readily understand how to adapt the teachings presented herein for use in such embodiments. 7. The mobile edge function 803 determines a WRP frame corresponding to a current estimate of the mobile device's position (WRP) determined by other means (e.g., by using any of the methods described above) (step 807). The WRP may be determined by the mobile device 801 (e.g., see FIG. 3A and accompanying text) or by the base station 805 (e.g., see FIG. 5 and accompanying text). 8. The mobile edge function 803 determines that network-assisted self-positioning will improve its current estimate of location (e.g., based on any one or more of the factors outlined above) and therefore determines parameters for guiding radar operation (step 809) based on the area, relevant objects in the vicinity, its allowed use of radar in certain frequency bands, etc. In some, but not necessarily all, embodiments, the guidance may also be based on whether and what kind of radar capability the device 801 has (e.g., whether the device 801 has mmWave SAR capability). Device capability information may be provided to the mobile edge function 803 in any number of ways, including, but not limited to, receiving device capability information from the device 801. By performing sensing according to the mobile edge function's guidance, the device 801 can perform its radar operation in an optimized manner that takes into account the mobile edge function's holistic knowledge of maps in its area, other mobile devices and known dynamics in the environment, and previous historical measurements from other devices in its area. The mobile edge function 803 then sends the WRP frame and the sensing guide parameters to the mobile device 801 (step 811). 9. The device 801 then begins its self-positioning procedure (step 813) and performs detection according to the received parameters (step 815). For example, if conventional radar detection or mmWave SAR detection is requested, the device 801 emits a radar sequence and receives a response. The settings for the radar are based on the device's knowledge of features indicated on the map or guidance received from the mobile edge server 803. 10. The device 801 sends the resulting sensing data to the mobile edge server 803 (step 819). For example, the resulting data can be raw radar data. Alternatively, if mmWave SAR sensing is performed, the raw data needs to be processed to reconstruct a SAR image. 11. (Optional) In some embodiments where mmWave SAR sensing is performed, the mobile device 801 reconstructs SAR images (step 817), and these are the resulting data. 12. (Optional) In some embodiments where mmWave SAR sensing is performed, the mobile device instead uses raw radar data as the derived data, and the mobile edge server 803 reconstructs the SAR image from the received raw radar data (step 821). 13. The mobile edge server 803 correlates the received sensing data with a reference set of previously acquired reflections from known locations stored in the mobile edge server 803 database (step 823). 14. Based on the correlation results, the mobile edge server 803 determines a sufficiently accurate estimate of the mobile device's location (step 825) and sends this to the mobile device 801 (step 827). (What constitutes "sufficient" accuracy is implementation dependent and, therefore, beyond the scope of this disclosure.) The mobile edge server 803 may also, in some embodiments, communicate a confidence level regarding the location accuracy. In some, but not necessarily all, embodiments, the mobile edge server 803 also provides additional guidance for performing further sensor measurements if the confidence level does not meet a predetermined confidence threshold. 15. (Optional) The mobile device 801 may perform additional detections (e.g., additional mmWave SAR scans) (e.g., based on the confidence level) if necessary (e.g., if the communicated confidence level does not meet a predetermined threshold level) (step 829). 16. (Optional) If additional sensing has been performed, the mobile device 801 communicates the additional sensing data to the mobile edge server (step 831). 17. (Optional) If additional sensory data is received, the mobile edge server 803 uses the additional sensory data to determine (step 833) an updated precise location of the mobile device 801. Depending on why the additional sensory data was obtained, the updated precise location in this step may also be sent to the mobile device (not shown). 18. (Optional) In any of the options indicated above, the mobile edge server 803, having determined a precise estimate of the mobile device's location based on the new sensing data, may update its database with the relevant data from the device 801 and the determined precise location (step 835). The updated database will thus enable subsequent positioning requests to produce more accurate positioning estimates for this mobile device 801 as well as others.

[0123] Another aspect of some embodiments in which mmWave SAR sensing is performed for self-location relates to a SAR database of known returns to which sensed data is correlated. There are several options for creating a SAR fingerprint database. One of these is to pre-characterize the surfaces to be sensed (e.g., walls, floors, ceilings, etc.) during an initial system calibration procedure. This process involves performing SAR scans on selected portions of the surfaces, extracting their detectable features (i.e., fingerprints), and storing the fingerprints and corresponding locations in a map.

[0124] Another option is to intentionally embed SAR anchor nodes with known SAR characteristics in known locations within a surface (e.g., a wall, floor, ceiling, etc.). Convenient times to do this include during building renovations or initial construction, although of course, this timing is not a required aspect of embodiments of the present invention. Due to the surface-penetrating nature of mmWaves, these embedded anchor points with specific shapes (e.g., physical structures) or RF reflectivities (e.g., patterns applied using RF-sensitive paint) can be hidden from human perception for aesthetic reasons while remaining visible / detectable to mmWave radar detection. A 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 for that surface. Such structures would be completely passive. The shape and / or distribution pattern can be set based on the recognition of the radar structure as a surface with an incident normal plane relative to the antenna boresight. The configuration of the edges of these surfaces significantly increases the quality of the reflected signal. Examples of such structures include small sized radar reflectors suitable for millimeter wave and / or patterns of millimeter wave radar reflective paint. The SAR fingerprints and their corresponding locations are then stored in a map.

[0125] The various options may be combined in the sense that the first option (i.e., pre-characterizing the detection of an area) may be used to fine-tune the location of the built-in anchor points of the second option.

[0126] In all of these alternatives, the map with the SAR fingerprints may be stored in a database maintained by the mobile edge server, which uses the map as a reference map against which sensed data is correlated.

[0127] Alternatively, a SAR-enabled device with an accurate estimate of its location can be instructed to scan for objects and provide the data to a central database for future use. This may be useful for detecting new objects that are identified from regular (i.e., non-SAR) radar transmissions and therefore not previously present, or which may be in areas not covered by the methods described above.

[0128] The mobile edge server 803 for embodiments involving mmWave SAR sensing shares aspects described above with respect to other embodiments. The mobile edge server 803 includes a map of the environment as well as a database of SAR fingerprints (with their corresponding locations). The mobile edge server 803 can also run a correlation algorithm between stored fingerprints and measured SAR image features to estimate the most likely location of the device 801 within a limited geographic area. The estimation results can then be sent to the device 801. Additionally, positioning capabilities can serve all devices within the coverage of the base station 805. The mobile edge server 803 can also aggregate data from multiple devices, which can be used to update the map and / or fingerprint database.

[0129] Also, as previously mentioned, the mobile edge server 803 provides initial guidance in the direction towards suitable SAR objects in close proximity to the device 801 (e.g., based on the initial position estimate) as candidates for positioning correlation.

[0130] Furthermore, in alternative embodiments, the functionality of the mobile edge server 803 may be embodied as an extension to functionality in the base station 805, rather than being a separate (or at least separately located) entity. Thus, it is not necessary for embodiments of the present invention for this functionality to reside in the mobile edge server 803. However, given the close connectivity of the mobile edge server functionality to the base station 805, the mobile edge server functionality then naturally covering a limited geographic area and having lower latency than a remote over-the-top data center, and the mobile edge server functionality having more storage and computing capabilities than the UE or mobile device 801, there are natural advantages to colocating the mobile edge server functionality with that of the base station 805.

[0131] Another aspect of some, but not necessarily all, embodiments involves when to enable SAR mode detection and when to disable SAR mode detection (e.g., to perform an alternative type of detection). Because SAR image reconstruction requires more computational resources than conventional radar operation, SAR operation may add processing complexity and require additional data transfer. SAR operation may be enabled whenever a particular embodiment / application deems it necessary, and thus the SAR mode of radar operation of a device may be complementary to its conventional radar operation. Of course, "when necessary" is implementation-dependent, and thus a complete description is beyond the scope of this disclosure.

[0132] In one exemplary embodiment, the device autonomously enables the device's mmWave SAR radar mode when it enters an area without a sufficient number of objects that can provide a distinctive signature for conventional radar and the error in the device's customary radar-aided self-location (or IMU location) algorithm exceeds a threshold.

[0133] In an alternative exemplary embodiment, the mmWave SAR sensing mode of the device is enabled by a cloud or edge cloud that tracks the device. The cloud can guide SAR operation based on the initial location of the device (and potentially the IMU, if supported) and a priori knowledge of the location of SAR reference objects in areas where conventional radar-aided self-positioning has low accuracy (or cannot meet application requirements with the required positioning accuracy at a certain confidence level), or in areas with prominent recognizable structures that SAR will be able to utilize.

[0134] 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, with the rest of the devices performing only non-SAR radar self-positioning functionality. By positioning itself with greater accuracy and sharing its location with other devices, the SAR-capable device may be used as a reference point by a standard radar device so that the positioning accuracy of the standard radar device may be improved. Furthermore, which devices and how many of the devices should be enabled for mmWave SAR self-positioning may be adapted to positioning accuracy requirements.

[0135] In another aspect of some, but not necessarily all, embodiments according to the present invention, portions of the database may be downloaded and stored on the device, such that correlation / fingerprinting occurs on the device rather than in the edge cloud. (See, e.g., step 837 in FIG. 8 .) In a preferred embodiment, the results are still communicated to the edge cloud database, so that the database can be updated accordingly and can then serve other devices as they perform self-positioning. A relevant use case for this embodiment involves devices with limited mobility, and therefore, the device moves only within small areas with little or no dynamics in its environment. In such cases, it may be more beneficial to have the relevant portions of the database stored locally within the device (as processing and power allow). In contrast, highly mobile devices with limited processing capabilities operating in environments with high dynamics may prefer the edge cloud approach.

[0136] To further illustrate aspects of some, but not necessarily all, embodiments in accordance with the present invention, FIG. 9 illustrates details of network node QQ160 according to one or more embodiments. In FIG. 9, network node QQ160 includes processing circuitry QQ170, device-readable medium QQ180, interface QQ190, auxiliary equipment QQ184, power supply QQ186, power circuitry QQ187, and antenna QQ162. While network node QQ160 illustrated in the exemplary wireless network of FIG. 9 may represent a device including the depicted combination of hardware components, other embodiments may comprise network nodes with different combinations of components. It should be understood that a network node comprises any suitable combination of hardware and / or software required to perform the tasks, features, functions, and methods disclosed herein. Moreover, although the components of network node QQ160 are shown as a single box located within a larger box or as a single box nested within multiple boxes, in reality the network node may comprise multiple different physical components that make up the single depicted component (e.g., device-readable medium QQ180 may comprise multiple separate hard drives as well as multiple RAM modules).

[0137] Similarly, network node QQ160 may be assembled from multiple physically separate components (e.g., a Node B component and a radio network controller (RNC) component, or a base transceiver station (BTS) component and a base station controller (BSC) component, etc.), each of which may have its own respective components. In some scenarios in which network node QQ160 comprises multiple separate components (e.g., a BTS component and a BSC component), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple Node Bs. In such scenarios, each unique Node B and RNC pair may, in some instances, be considered a single separate network node. In some embodiments, network node QQ160 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate device-readable media QQ180 for different RATs) and some components may be reused (e.g., the same antenna QQ162 may be shared by the RATs). Network node QQ160 may also include multiple sets of the various illustrated components for different wireless technologies, such as, for example, GSM, WCDMA, LTE, NR, WiFi, or Bluetooth wireless technologies, integrated into network node QQ160. These wireless technologies may be integrated into the same or different chips or sets of chips and other components within network node QQ160.

[0138] Processing circuit QQ170 is configured to perform any decision, calculation, or similar operations (e.g., some acquisition operations) described herein as being provided by a network node. These operations performed by processing circuit QQ170 may include processing information acquired by processing circuit QQ170, for example, by transforming the acquired information into other information, comparing the acquired or transformed information with information stored in the network node, and / or performing one or more operations based on the acquired or transformed information and as a result of said processing making a decision.

[0139] Processing circuit QQ170 may comprise one or more combinations of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software, and / or coded logic operable to provide network node QQ160 functionality, either alone or in conjunction with other network node QQ160 components, such as device-readable medium QQ180. For example, processing circuit QQ170 may execute instructions QQ181 stored on device-readable medium QQ180 or in memory within processing circuit QQ170. Such functionality may include providing any of the various wireless features, functions, or benefits described herein. In some embodiments, processing circuit QQ170 may include a system-on-chip (SOC).

[0140] 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 sets of chips), boards, or units such as a radio unit and a digital unit. In alternative embodiments, some or all of the RF transceiver circuit QQ172 and the baseband processing circuit QQ174 may be on the same chip or set of chips, board, or unit.

[0141] In some 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 circuitry QQ170 executing instructions stored in device-readable medium QQ180 or memory within processing circuitry QQ170. In alternative embodiments, some or all of the functionality may be provided by processing circuitry QQ170 without executing instructions stored in a separate or distinct device-readable medium, such as in a hardwired manner. In any of these embodiments, processing circuitry QQ170 may be configured to perform the described functionality, regardless of whether it executes instructions stored in a device-readable storage medium. Benefits provided by such functionality are enjoyed by network node QQ160 as a whole, and / or by end users and the wireless network generally, without being limited to processing circuitry QQ170 alone or other components of network node QQ160.

[0142] The device-readable medium QQ180 may comprise any form of volatile or non-volatile computer-readable memory, including, but not limited to, persistent storage, 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 disc (CD) or digital video disc (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory 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 applications including one or more of computer programs, software, logic, rules, code, tables, etc., and / or other instructions that can be executed by the processing circuit QQ170 and utilized by the network node QQ160. The device-readable medium QQ180 may be used to store calculations performed by the processing circuit QQ170 and / or data received via the interface QQ190. In some embodiments, the processing circuit QQ170 and the device-readable medium QQ180 may be considered to be integrated.

[0143] The interface QQ190 is used in wired or wireless communication of signaling and / or data between the network node QQ160, the network QQ106, and / or the WD QQ110. As shown, the interface QQ190 includes a port(s) / terminal(s) QQ194 for sending and receiving data to and from the network QQ106, e.g., over a wired connection. The interface QQ190 also includes a radio front-end circuit QQ192 that is coupled to the antenna QQ162 or, in some embodiments, may be part of the antenna QQ162. The radio front-end circuit QQ192 includes a filter QQ198 and an amplifier QQ196. The radio front-end circuit QQ192 may be connected to the antenna QQ162 and the processing circuit QQ170. The radio front-end circuit may be configured to condition signals communicated between the antenna QQ162 and the processing circuit QQ170. The radio front-end circuit QQ192 may receive digital data to be sent to another network node or wireless device via a wireless connection. The radio front-end circuit QQ192 may convert the digital data into a radio signal with appropriate channel and bandwidth parameters using a combination of a filter QQ198 and / or an amplifier QQ196. The radio signal may then be transmitted via the antenna QQ162. Similarly, when receiving data, the 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.

[0144] 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 a radio front-end circuit and may be connected to the antenna QQ162 without a separate radio front-end circuit QQ192. Similarly, in some embodiments, all or a portion 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 a baseband processing circuit QQ174 that is part of a digital unit (not shown).

[0145] Antenna QQ162 may include one or more antennas or antenna arrays configured to transmit and / or receive wireless signals. Antenna QQ162 may be coupled to 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 comprise one or more omnidirectional, sector, or panel antennas operable to transmit / receive wireless signals, for example, between 2 GHz and 66 GHz. An omnidirectional antenna may be used to transmit / receive wireless signals in any direction, a sector antenna may be used to transmit / receive wireless signals from devices within a specific area, and a panel antenna may be a line-of-sight antenna used to transmit / receive wireless signals in a relatively straight line. In some instances, the use of two or more antennas may be referred to as MIMO. In some embodiments, antenna QQ162 may be separate from network node QQ160 and connectable to network node QQ160 through an interface or port.

[0146] Antenna QQ162, interface QQ190, and / or processing circuit QQ170 may be configured to perform any receiving operation and / or some acquisition operation described herein as being performed by a network node. Any information, data, and / or signals may be received from a wireless device, another network node, and / or any other network equipment. Similarly, antenna QQ162, interface QQ190, and / or processing circuit QQ170 may be configured to perform any transmitting operation described herein as being performed by a network node. Any information, data, and / or signals may be transmitted to a wireless device, another network node, and / or any other network equipment.

[0147] The power circuit QQ187 may include or be coupled to a power management circuit and be configured to supply power to the components of the network node QQ160 for performing the functions described herein. The power circuit QQ187 may receive power from the 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 each component (e.g., at the voltage and current levels required for each respective component). The power source QQ186 may either be included in the power circuit QQ187 and / or the network node QQ160 or may be external to the power circuit QQ187 and / or the network node QQ160. For example, the network node QQ160 may be connectable to an external power source (e.g., an electrical outlet) via an input circuit or interface, such as an electrical cable, whereby the external power source supplies power to the power circuit QQ187. As a further example, power supply QQ186 may include a power source in the form of a battery or battery pack connected to or integrated into power circuit QQ187. The battery may provide backup power if the external power source fails. Other types of power sources, such as photovoltaic devices, may also be used.

[0148] 9 that may be responsible for providing some aspects of the network node's functionality, including any of the functionality described herein and / or functionality necessary to support the subject matter described herein. For example, network node QQ160 may include user interface devices to enable input of information into network node QQ160 and output of information from network node QQ160. This may enable a user to perform diagnostic, maintenance, repair, and other management functions for network node QQ160.

[0149] To further illustrate aspects of some, but not necessarily all, embodiments in accordance with the present invention, FIG. 10 illustrates details of a wireless device QQ110 according to one or more embodiments. As used herein, a wireless device (WD) refers to a device capable of, configured to, and / or operable to communicate wirelessly with network nodes and / or other wireless devices. Unless otherwise noted, the term WD may be used interchangeably herein with user equipment (UE). Communicating wirelessly may involve transmitting and / or receiving radio signals using electromagnetic, radio, infrared, and / or other types of signals suitable for conveying information over the air. 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 on a predetermined schedule, when triggered by an internal or external event, or in response to a request from the network. Examples of WDs include, but are not limited to, smartphones, mobile phones, cell phones, voice-over-IP (VoIP) phones, wireless local loop phones, desktop computers, personal digital assistants (PDAs), wireless cameras, gaming consoles or devices, music storage devices, playback appliances, wearable terminal devices, wireless endpoints, mobile stations, tablets, laptop computers, laptop embedded devices (LEEs), laptop mounted devices (LMEs), smart devices, wireless customer premises equipment (CPEs), in-vehicle wireless terminal devices, etc. A WD may support device-to-device (D2D) communications, e.g., by implementing 3GPP standards for sidelink communications, in which case it may be referred to as a D2D communications device. As yet another specific example, in an Internet of Things (IoT) scenario, a WD may represent a machine or other device that performs monitoring and / or measurements and transmits results of such monitoring and / or measurements to another WD and / or network node. The WD, in this case, may be a machine-to-machine (M2M) device, which may be referred to as a machine-type communications (MTC) device in the 3GPP context.As one specific example, a WD may be a UE implementing 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.), and personal wearables (e.g., watches, fitness trackers, etc.). In other scenarios, a WD may represent a vehicle or other equipment capable of monitoring and / or reporting on its operational status or other functions related to its operation. The WD described above may represent an endpoint of a wireless connection, in which case the device may be referred to as a wireless terminal. Furthermore, the WD described above may be mobile, in which case the device may be referred to as a mobile device or mobile terminal.

[0150] FIG. 10 illustrates details of a wireless device QQ110 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, auxiliary devices QQ134, a power supply QQ136, and a power circuit QQ137. The WD QQ110 may include multiple sets of one or more of the illustrated components for different wireless technologies supported by the WD QQ110, such as GSM, WCDMA, LTE, NR, WiFi, WiMAX, or Bluetooth wireless technologies, to name just a few. These wireless technologies may be integrated on the same or different chips or sets of chips as other components within the WD QQ110.

[0151] The antenna QQ111 may include one or more antennas or antenna arrays configured to send and / or receive wireless signals and is connected to the interface QQ114. In some alternative embodiments, the antenna QQ111 may be separate from the WD QQ110 and connectable to the WD QQ110 through an interface or port. The antenna QQ111, the interface QQ114, and / or the processing circuit QQ120 may be configured to perform any receiving or transmitting operation described herein as being performed by a WD. Any information, data, and / or signals may be received from a network node and / or another WD. In some embodiments, the wireless front-end circuit and / or the antenna QQ111 may be considered an interface.

[0152] 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 condition signals communicated between the antenna QQ111 and the processing circuit QQ120. The radio front-end circuit QQ112 may be coupled to or part of the antenna QQ111. In some embodiments, the WD QQ110 may not include a separate radio front-end circuit QQ112; rather, the processing circuit QQ120 may include the radio front-end circuit and be connected to the antenna QQ111. Similarly, in some embodiments, some or all of the RF transceiver circuit QQ122 may be considered part of the interface QQ114. The radio front-end circuit QQ112 may receive digital data to be sent to another network node or WD 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 a filter QQ118 and / or an amplifier QQ116. The radio signal may then be transmitted via the antenna QQ111. Similarly, when receiving data, the antenna QQ111 may collect the radio signal, which is then converted into digital data by the radio front-end circuit QQ112. The digital data may be passed to the processing circuit QQ120. In other embodiments, the interface may include different components and / or different combinations of components.

[0153] The processing circuit QQ120, either alone or in conjunction with other WD QQ110 components such as the device-readable medium QQ130, may comprise one or more combinations of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field-programmable gate array, or any other suitable computing device, resource, or combination of hardware, software, and / or coded logic operable to provide WD QQ110 functionality. Such functionality may include providing any of the various wireless features or benefits described herein. For example, the processing circuit QQ120 may execute instructions QQ131 stored on the device-readable medium QQ130 or in memory within the processing circuit QQ120 to provide the functionality disclosed herein.

[0154] As shown, the processing circuit QQ120 includes one or more of an RF transceiver circuit QQ122, a baseband processing circuit QQ124, and an application processing circuit QQ126. In other embodiments, the processing circuit may comprise different components and / or different combinations of components. In some embodiments, the processing circuit QQ120 of the WD QQ110 may comprise 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 separate chips or sets of chips. In alternative embodiments, some or all of the baseband processing circuit QQ124 and the application processing circuit QQ126 may be combined into one chip or set of chips, and the RF transceiver circuit QQ122 may be on a separate chip or set of chips. In further alternative embodiments, some or all of the RF transceiver circuitry QQ122 and the baseband processing circuitry QQ124 may be on the same chip or set of chips, and the application processing circuitry QQ126 may be on a separate chip or set of chips. In yet other alternative embodiments, some or all of the RF transceiver circuitry QQ122, the baseband processing circuitry QQ124, and the application processing circuitry QQ126 may be combined in the same chip or set of chips. In some embodiments, the RF transceiver circuitry QQ122 may be part of the interface QQ114. The RF transceiver circuitry QQ122 may condition the RF signals for the processing circuitry QQ120.

[0155] In some embodiments, some or all of the functionality described herein as being performed by the WD may be provided by the processing circuitry 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 circuitry QQ120 without executing instructions stored on a separate or distinct device-readable storage medium, such as in a hardwired manner. In any of these particular embodiments, the processing circuitry QQ120 may be configured to perform the described functionality, regardless of whether it executes instructions stored on a device-readable storage medium. Benefits provided by such functionality are enjoyed by the processing circuitry QQ120 alone or by other components of the WD QQ110, but are not limited to the processing circuitry QQ120 alone or by the WD QQ110 as a whole and / or by end users and wireless networks generally.

[0156] The processing circuit QQ120 may be configured to perform any of the decision, calculation, or similar operations (e.g., some acquisition operations) described herein as being performed by the WD. These operations as performed by the processing circuit QQ120 may include processing information acquired by the processing circuit QQ120, for example, by converting the acquired information to other information, comparing the acquired or converted information with information stored by the WD QQ110, and / or performing one or more operations based on the acquired or converted information and as a result of the processing making a decision.

[0157] The device-readable medium QQ130 may be operable to store applications, including one or more of computer programs, software, logic, rules, codes, tables, etc., and / or other instructions that can be executed by the processing circuit QQ120. The device-readable medium QQ130 may include computer memory (e.g., random access memory (RAM) or read-only memory (ROM)), mass storage media (e.g., hard disks), removable storage media (e.g., compact discs (CDs) or digital video discs (DVDs)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory devices that store information, data, and / or instructions that can be used by the processing circuit QQ120. In some embodiments, the processing circuit QQ120 and the device-readable medium QQ130 may be considered to be integrated.

[0158] The user interface device QQ132 may provide components that allow a human user to interact with the WD QQ110. Such interaction may be in many forms, such as visual, auditory, or tactile. The user interface device QQ132 may be operable to generate output to the user and to 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 on the WD QQ110. For example, if the WD QQ110 is a smartphone, interaction may be via a touchscreen; if the WD QQ110 is a smart meter, interaction may be 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 to 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, proximity or other sensors, keys / buttons, a touch display, one or more cameras, a USB port, or other input circuitry. The user interface device QQ132 is also configured to enable the output of information from the WD QQ110 and to enable 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 interface, or other output circuitry. Using one or more input and output interfaces, devices, and circuits of the user interface device QQ132, the WD QQ110 may communicate with end users and / or wireless networks, enabling the end users and / or wireless networks to benefit from the functionality described herein.

[0159] Ancillary device QQ 134 is operable to provide more specific functionality that may not generally be performed by a WD. It may include specialized sensors for taking measurements for various purposes (e.g., radar functionality as described herein), interfaces for additional types of communication such as wired communication, etc. The inclusion and types of components of ancillary device QQ 134 may vary depending on the embodiment and / or scenario.

[0160] The power source QQ136 may be in the form of a battery or battery pack in some embodiments. Other types of power sources, such as an external power source (e.g., an electrical outlet), a photovoltaic device, or a battery, may also be used. The WD QQ110 may further include a power circuit QQ137 for delivering power from the power source QQ136 to various portions of the WD QQ110 that require power from the power source QQ136 to perform any of the functions described or indicated herein. The power circuit QQ137 may, in some embodiments, include a power management circuit. The power circuit QQ137 may additionally or alternatively be operable to receive power from an external power source, in which case the WD QQ110 may be connectable to an external power source (such as an electrical outlet) via an input circuit or interface, such as a power cable. The power circuit QQ137 may also, in some embodiments, be operable to deliver power from the external power source to the power source QQ136. This may be, for example, for charging the power source QQ136. The power circuit QQ137 may perform any formatting, conversion, or other modification on the power from the power supply QQ136 to make the power suitable for each component of the WD QQ110 being powered.

[0161] It will be appreciated that an important aspect of various embodiments relates to collaboration between mobile devices with radar capabilities and a Mobile Edge Function (MEF) that has the overall data, has more resources to perform correlation to determine precise location, and serves multiple mobile devices while iteratively improving and updating that data. In this regard, among the notable aspects are the following: Split Device - Mobile Edge Function (MEF) positioning, so the device performs the radar and the MEF performs the correlation according to the embodiment described above. This results in several optimizations, such as the MEF having access to all dynamic changes from all devices, the MEF being able to guide the device based on a map and characteristics of the surroundings (without having to preload a lot of data onto the device), the MEF being able to perform higher level fine-tuning by combining techniques, the MEF being able to learn from the combined fine-tuning techniques, etc. Iterative fine-tuning after a move to resolve situations where the fine-tuning indicates ambiguity / too low confidence in the exact location (due to noise, artifacts, or a dynamically changing environment), where the move between the two radar analyses is estimated based on the most likely location in the coarse location area(s), and the new fine-tuning is based on an assessment of the previous candidate and the new radar-based fine-tuning combined with the delta move. MEF can identify some points / structures as being highly reliable as "anchor points" for other reflections. Areas with no discernible distinctive structure can be identified and serve as input for refinements such as adding structure or anchor points. The base station is capable of implementing the MEF described above. Furthermore, the base station can benefit from knowledge of the above functions. · Because the MEF has information about the radar UE regarding its surroundings, it can guide the radar usage at the UE (which direction, what relative power levels, etc.) for better efficiency and best use of its resources and minimum interference. The MEF can also benefit from previous measurements and from its relative position to structures in the map. · Since the MEF has information about all radar-equipped devices in the area, the MEF can filter out dynamic changes in the environment resulting from the object of other nearby UEs, for example the position and movement of an autonomous cart with radar-equipped UEs will be known and its effect on the radar analysis of other UEs can be compensated accordingly.

[0162] Various aspects of embodiments of the present invention as described above may be applied to provide mechanisms and techniques for a UE and / or mobile device to obtain the location of the UE and / or mobile device with much better accuracy than traditional network-based positioning solutions provide.

[0163] This can be particularly useful when applied, for example, in autonomous carts driving around a factory floor, or drones in indoor environments. However, this is by no means an exhaustive list of applications; to the contrary, there are many potential applications for this technology.

[0164] Embodiments in accordance with the present invention offer several advantages over conventional techniques, including that highly detailed self-positioning is made possible without the need for classical sensor fusion techniques. This is achieved by making some clever use of modems and cellular systems. For example, and without limitation: In some embodiments, a modem is used to obtain a first (less accurate) position from a cellular system as a global reference. In some embodiments, radar functionality may be integrated into 5G modems at little or no additional cost. In some embodiments, a modem is used to communicate with the mobile edge server, which performs the correlation function as well as enables a large set of sophisticated optimizations.

[0165] Furthermore, it should be noted that the embodiments do not depend on the radar being operated in the 3GPP spectrum, nor do they depend on the radar being implemented as integrated in the modem hardware, although this constitutes an advantageous embodiment.

[0166] The embodiments described above provide an extremely accurate positioning solution for all devices with a 5G modem (radar enabled) without the need for a dense installation of base stations or wireless sources other than those required for communication, and without the need for cameras or other complex sensor fusion solutions - a solution that easily scales across, for example, a factory.

[0167] Further advantages include: Low cost of alternative sensor fusion solutions for high accuracy positioning, e.g. adding a camera module Significantly higher accuracy than traditional radio-based solutions traditionally found in, for example, cellular or Bluetooth-based systems The addition of radar functionality in the modem can also add value to other types of applications, such as maps with feature references that can be seen by all (radar-equipped) modems in the base station and their surroundings, or edge cloud functionality, which can enable several applications and benefits. An optimized method for determining the WR frame on which the correlation is performed. Conventional methods require applying a pessimistic approach which often leads to larger WR frames. Collaboration between edge cloud map services and UE-based radar detection allows several optimizations, such as adapting the signaling and frequency of radar detection to fit the topology and objects of the estimated area in the map and benefit from the knowledge of other mobile units in close proximity to the UE. Embodiments in accordance with the present invention improve over time (as the device collects more samples, which may improve overall accuracy) and may also identify and adapt to changes in the environment. The device may provide insight into precisely defined areas that can only be seen by devices in that location (eg, not reached by radio signals from base stations only).

[0168] Moreover, embodiments in which a mobile device utilizes mmWave SAR sensing as part of a self-positioning methodology offer several advantages over conventional approaches, including: · Lower cost due to alternative sensor fusion solutions for high accuracy positioning, e.g., versus adding separate radar or camera modules, or the cost of positioning solutions with many anchor points or base stations to ensure line of sight with multiple base stations from all locations simultaneously. The ability to achieve significantly higher accuracy than older radar-based solutions Improvements over previous work due to opportunities to exploit structural details other than walls, floors or ceilings, as well as other structures that are less clearly distinguished by conventional radar.

[0169] Although the present invention has been described with reference to specific embodiments, it will be readily 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.

[0170] For example, various embodiments have referred to a mobile edge server. However, the use of a mobile edge server is not a required aspect of embodiments of the present invention. To the contrary, any server that performs the functions described herein (e.g., cloud servers, as well as servers in a mobile network, such as, but not limited to, at the edge of a mobile network) may be used, and thus the term "server" is used herein to refer to any such embodiment.

[0171] In another example, the embodiments have referred to only one WRP. However, in some embodiments, multiple WRPs may be available, each with its own confidence interval (i.e., regarding accuracy). In such cases, multiple WR frames may be determined, which may be used in several different ways, such as: a. Intersections between multiple WR frames can be determined and the process considers only spaces that conform to all of them. b. The fusion between multiple WR frames can be determined and processing can then be set to consider the combined space(s). This class of embodiments can be relevant when multiple WR frames define disjoint areas and there is no prior knowledge available about where the device is located. c. One or more of the WR frames may be completely ignored, for example, when the system already has some understanding of where the device is, or if there is statistical data that dictates how some WR methods will perform in that particular area.

[0172] Accordingly, the described implementations are illustrative only and should not be considered limiting in any way. The scope of the present invention is further indicated by the appended claims, rather than by the foregoing description alone, and all variations and equivalents that fall within the scope of the claims are intended to be embraced therein.

Claims

1. A method for determining the location of a mobile communication device (101, 551, 801, QQ110) having a coarse position (211) within a local area portion (201) of a reference coordinate system, accompanied by a measure of reliability of network-based positioning, the method comprising: receiving (701) a request (321, 513, 525) for radar detection of the local area portion (201) according to one or more parameters from a network node (113, 563, 803, QQ160) serving the mobile communication device (101, 551, 801, QQ110), the request (321, 513, 525) guiding how and / or where the radar detection should be performed; In response to the request for the radar detection of the local area portion (201), producing detection data (703) by performing the radar detection according to the one or more parameters (323, 515, 527); communicating (705) said sensing data to said network node (113, 563, 803, QQ160); receiving (707) a location (215) of the mobile communication device (101, 551, 801, QQ110) in response to communicating the sensed data to the network node (113, 563, 803, QQ160); [0033] The method, wherein the coarse position (211) is less accurate than the received position (215).

2. initially obtaining or generating the coarse location (211) of the mobile communication device (101, 551, 801, QQ110); providing said coarse location (211) to said network node (113, 563, 803, QQ160); Including, the received request for detection of the local area portion is in response to providing the coarse location (211) to the network node (113, 563, 803, QQ160); The method of claim 1.

3. the one or more parameters define an orientation that the first mobile communications device should assume when performing the radar detection of the local area portion; 3. The method according to claim 1 or 2.

4. The one or more parameters define a location at which the radar detection (117) of the local area portion should be performed.

3. The method according to claim 1 or 2.

5. The method of claim 1 or 2, wherein the radar detection of the local area portion is a millimeter wave synthetic aperture radar (mmWave SAR) detection.

6. The method of claim 5 , wherein the one or more parameters define a direction and / or orientation and / or device orbit to be applied when performing the mmWave SAR sensing.

7. A computer program comprising instructions (QQ131) that, when executed by at least one processor (QQ120), cause the at least one processor (QQ120) to perform the method (700) of any one of claims 1 to 6.

8. An apparatus for determining the location of a mobile communication device (101, 551, 801, QQ110), said apparatus being configured to perform the method of any one of claims 1 to 6.

9. A mobile communication device comprising the apparatus of claim 8.

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