Collaborative 5g positioning for enhanced 2d & 3D location services

Abstract

An exemplary embodiment of the present disclosure provides a method for determining positions of one or more devices within a wireless communication system, the method comprising: determining, by a central controller, a position of one or more first devices in a plurality of wireless communication devices; receiving, at a central controller, one or more communications from one or more devices in the plurality of wireless communication devices, each communication comprising one or more estimated ranging measurements between the respective device and a respective other device in the plurality of wireless communication devices, wherein each ranging measurement is derived from a respective measurement signal transmitted by the other device; and determining, by the central controller, based at least in part on the position of the one or more first devices and the one or more communications, a position of each of the plurality of wireless communication devices.

Description

COLLABORATIVE 5G POSITIONING FOR ENHANCED 2D & 3D LOCATIONSERVICESCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application Serial No. 63 / 676,050, filed on 26 July 2024, which is incorporated herein by reference in its entirety as if fully set forth below.GOVERNMENT LICENSE RIGHTS

[0002] This invention was made with government support under 2208761, awarded by National Science Foundation. The government has certain rights in the invention.FIELD OF THE DISCLOSURE

[0003] The various embodiments of the present disclosure relate generally to positioning systems using wireless devices.BACKGROUND

[0004] Large bandwidths, wide coverage, and network configuration flexibility, make 5G a natural candidate for delivering the wide-area device positioning that is central to advancing numerous industry verticals (automation, robotics, fleet management, public safety, etc.). Indeed, armed with its dedicated, wide-bandwidth reference signals, positioning serves as the poster child of 5G’s first offering under the theme of “joint communication and sensing”.

[0005] We consider an exemplary application in public safety, namely enhanced 911 (E911) services. The FCC’s mandate for E911 wireless calls today is for mobile operators to locate indoor callers to within 50 m and ±3 m accuracy in horizontal and vertical (i.e. floor-level in multi-story buildings) planes respectively, for 80% of the calls. Notwithstanding these modest 2D accuracy requirements, it has proved to be a significant challenge and current solutions solicit heavy assistance from non-wireless infrastructure, e.g. the deployment and use of reference points / masts with barometric sensors (for calibrating devices’ altitude for vertical accuracy), fixed-location landline phones (for non-wireless calls), etc. Given 5G’s capability, it raises the natural question: Can we provide high (e.g. ±3m) accuracy in both 2D and 3D using only 5G’s wireless air interface, significantly increasing the performance, scope, and availability of numerous future mobile location services?

[0006] 5G adopts an infrastructure-based positioning (IPos) approach, where wide-bandwidth reference signals are transmitted to / from multiple base stations (BSs, or gNBs in 5G) by / towards the client devices (UEs) and subsequently used for multilaterating UE location. While wide-band reference signals provide the potential for higher accuracy, they are unable to reach, and thus position, UEs located inside multi-story buildings or in urban canyons. Indeed, our evaluations in realistic deployments reveal that over 50% of indoor UEs and 20% of outdoor UEs are unable to obtain a sufficient SNR to / from at least 3 (4+) gNBs directly, which is needed to enable 2D (3D) positioning, even with a reasonably dense deployment of small / pico cells. This highlights the fundamental limitation of IPos in catering to the ambitious requirements of future location services that cannot be addressed with just the higher bandwidths of 5G.BRIEF SUMMARY

[0007] An exemplary embodiment of the present disclosure provides a method for determining positions of one or more devices within a wireless communication system, the method comprising: determining, by a central controller, a position of one or more first devices in a plurality of wireless communication devices; receiving, at a central controller, one or more communications from one or more devices in the plurality of wireless communication devices, each communication comprising one or more estimated ranging measurements between the respective device and a respective other device in the plurality of wireless communication devices, wherein each ranging measurement is derived from a respective measurement signal transmitted by the other device; and determining, by the central controller, based at least in part on the position of the one or more first devices and the one or more communications, a position of each of the plurality of wireless communication devices.

[0008] In any of the embodiments disclosed herein, the method can further comprise generating, based at least in part on the position of each of the plurality of wireless communication devices, a network topology of each of the plurality of communication devices.

[0009] In any of the embodiments disclosed herein, the method can further comprise accessing, by the central controller, a timing advance value for each of the one or more devices, wherein each timing advance value can be configured by the wireless communication system; and can comprise calculating one or more corrected ranging measurements between the respective device and a respective other device by compensating each of the one or more estimated ranging measurements using the respective timing advance value of the respective other device.

[0010] In any of the embodiments disclosed herein, the position of each of the plurality of wireless communication devices can be determined, by the central controller, based at least in part on, the one or more corrected ranging measurements.

[0011] In any of the embodiments disclosed herein, each of the plurality of wireless communication devices can be User Equipments (UEs), and the measurement signals can be Sidelink signals or Sounding Reference Signals (SRS).

[0012] In any of the embodiments disclosed herein, the central controller can be a near realtime RAN Intelligent Controller (near-RT RIC).

[0013] In any of the embodiments disclosed herein, the one or more communications can be received by the near-RT RIC from a base station (gNB) over an E2 interface.

[0014] In any of the embodiments disclosed herein, the measurement signals can be transmitted by the respective other devices within a set of allocated time slots according to a distributed access protocol.

[0015] In any of the embodiments disclosed herein, the allocated time slots can be within a Sidelink resource region.

[0016] In any of the embodiments disclosed herein, the distributed access protocol can comprise each UE independently determining whether to transmit the measurement signals based on a stochastic policy that prioritizes transmissions contributing to an overall network positioning accuracy.

[0017] In any of the embodiments disclosed herein, the stochastic policy can be based on a collaborative positioning utility function that can account for a diminishing incremental utility of additional measurement signal transmissions to the same set of neighboring devices.

[0018] In any of the embodiments disclosed herein, upon determining to transmit a measurement signal, the respective other device can select a specific time slot from the set of allocated time slots using a hash function.

[0019] In any of the embodiments disclosed herein, the method can further comprise dynamically adapting, with the central controller, a quantity of the allocated time slots based, at least in part, on an aggregated collision probability received from a plurality of the UEs.

[0020] In any of the embodiments disclosed herein, the dynamic adaptation can be performed using an inverse additive-increase multiplicative-decrease (AIMD) algorithm, wherein the quantity of allocated time slots can be additively increased when the aggregated collision probability is above a threshold and multiplicatively decreased when the aggregated collision probability is below the threshold.

[0021] The method of claim 4, wherein the measurement signal can be a broadcast signal containing a Sounding Reference Signal (SRS) that is spread over an entire available bandwidth within the last four symbols of a time slot.

[0022] In any of the embodiments disclosed herein, the one or more communications from the one or more devices in the plurality of communication devices can comprise a structure as a MeasurementObjectSL-SRS object at a Radio Resource Control (RRC) layer.

[0023] In any of the embodiments disclosed herein, determining the position of the one or more first devices can comprise implementing an infrastructure-based positioning algorithm with three or more base stations.

[0024] In any of the embodiments disclosed herein, the one or more communications from the one or more devices can further comprise a collision probability experienced by the one or more devices.

[0025] In any of the embodiments disclosed herein, the position of each of the plurality of wireless communication devices can be a 3D position, and wherein determining the position of each of the plurality of wireless communication devices can utilize at least four corrected ranging measurements to four different devices.

[0026] In any of the embodiments disclosed herein, determining the position of each of the plurality of wireless communication devices can comprise using a Multi-dimensional Scaling (MDS) based algorithm on a matrix of corrected ranging measurements.

[0027] In any of the embodiments disclosed herein, prior to using the MDS-based algorithm, a sequential multi-lateration process can be used to estimate missing ranging measurements within the matrix of corrected ranging measurements, and after the sequential multi-lateration process, a location perturbation step using gradient descent can be performed to diminish cascading localization errors.

[0028] Another embodiment can comprise a system for determining positions of a plurality of user devices, the system comprising: one or more processors; and one or more memories, the one or more memories, individually or collectively, comprising logical instructions that, when executed by the one or more processors, individually or collectively, cause the one or more processors, individually or collectively, to perform the method, or a portion of the method, of any of the embodiments disclosed herein.

[0029] These and other aspects of the present disclosure are described in the Detailed Description below and the accompanying drawings. Other aspects and features of embodimentswill become apparent to those of ordinary skill in the art upon reviewing the following description of specific, exemplary embodiments in concert with the drawings. While features of the present disclosure may be discussed relative to certain embodiments and figures, all embodiments of the present disclosure can include one or more of the features discussed herein. Further, while one or more embodiments may be discussed as having certain advantageous features, one or more of such features may also be used with the various embodiments discussed herein. In similar fashion, while exemplary embodiments may be discussed below as device, system, or method embodiments, it is to be understood that such exemplary embodiments can be implemented in various devices, systems, and methods of the present disclosure.BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The following detailed description of specific embodiments of the disclosure will be better understood when read in conjunction with the appended drawings. For the purpose of illustrating the disclosure, specific embodiments are shown in the drawings. It should be understood, however, that the disclosure is not limited to the precise arrangements and instrumentalities of the embodiments shown in the drawings.

[0031] FIG. 1 provides an overall system architecture and high-level description of a system for determining the positions of a plurality of devices, in accordance with some embodiments of the present disclosure.

[0032] FIG. 2 illustrates a Sidelink Access Protocol, in accordance with some embodiments of the present disclosure.

[0033] FIG. 3 illustrates a multi-dimensional scaling-based localization algorithm, in accordance with some embodiments of the present disclosure.

[0034] FIG. 4 provides a central controller architecture and software process flow, in accordance with some embodiments of the present disclosure.DETAILED DESCRIPTION

[0035] Although preferred exemplary embodiments of the disclosure are explained in detail, it is to be understood that other exemplary embodiments are contemplated. Accordingly, it is not intended that the disclosure is limited in its scope to the details of construction and arrangement of components set forth in the following description or illustrated in the drawings. The disclosure is capable of other exemplary embodiments and of being practiced or carried out invarious ways. Also, in describing the preferred exemplary embodiments, specific terminology will be resorted to for the sake of clarity.

[0036] To facilitate an understanding of the principles and features of the present disclosure, various illustrative embodiments are explained below. The components, steps, and materials described hereinafter as making up various elements of the embodiments disclosed herein are intended to be illustrative and not restrictive. Many suitable components, steps, and materials that would perform the same or similar functions as the components, steps, and materials described herein are intended to be embraced within the scope of the disclosure. Such other components, steps, and materials not described herein can include, but are not limited to, similar components or steps that are developed after development of the embodiments disclosed herein.

[0037] As used in the specification and the appended claims, the singular forms “a,” “an” and “the” include plural referents unless the context clearly dictates otherwise.

[0038] Also, in describing the preferred exemplary embodiments, terminology will be resorted to for the sake of clarity. It is intended that each term contemplates its broadest meaning as understood by those skilled in the art and includes all technical equivalents which operate in a similar manner to accomplish a similar purpose.

[0039] Ranges can be expressed herein as from “about” or “approximately” one particular value and / or to “about” or “approximately” another particular value. When such a range is expressed, another exemplary embodiment includes from the one particular value and / or to the other particular value.

[0040] Similarly, as used herein, “substantially free” of something, or “substantially pure”, and like characterizations, can include both being “at least substantially free” of something, or “at least substantially pure”, and being “completely free” of something, or “completely pure”.

[0041] By ‘ ‘comprising” or “containing” or “including” is meant that at least the named compound, member, particle, or method step is present in the composition or article or method, but does not exclude the presence of other compounds, materials, particles, method steps, even if the other such compounds, material, particles, method steps have the same function as what is named.

[0042] Mention of one or more method steps does not preclude the presence of additional method steps or intervening method steps between those steps expressly identified. Similarly, it is also to be understood that the mention of one or more components in a device or systemdoes not preclude the presence of additional components or intervening components between those components expressly identified.

[0043] The materials described as making up the various members of the invention are intended to be illustrative and not restrictive. Many suitable materials that would perform the same or a similar function as the materials described herein are intended to be embraced within the scope of the invention. Such other materials not described herein can include, but are not limited to, for example, materials that are developed after the time of the development of the invention.

[0044] Reference will now be made in detail to exemplary embodiments of the disclosed technology, examples of which are illustrated in the accompanying drawings and disclosed herein. Wherever convenient, the same references numbers will be used throughout the drawings to refer to the same or like parts.

[0045] As shown in FIG. 1, an exemplary embodiment of the present disclosure provides a wireless communication system 100. The system 100 can comprise a central controller 110, one or more base stations 120, and a plurality of wireless communication devices 130. The communication devices 130 can be, but are not limited to, User Equipments (UEs) in a 5G network. The central controller 110 can be a network entity responsible for orchestrating the positioning process and calculating the final positions of devices 130. In some embodiments, the central controller 110 can be implemented as a near real-time RAN Intelligent Controller (near-RT RIC). The central controller 110 can host one or more specialized applications, including but not limited to, a positioning xApp 112. This xApp 112 can be configured to execute collaborative positioning algorithms.

[0046] The base station 120 can be an infrastructure element, such as a 5G gNB, that facilitates communication between the central controller 1 10 and the wireless devices 130. The base station 120 can communicate with the central controller 110 over a specified interface, such as an E2 interface 122 in an O-RAN architecture. The plurality of wireless communication devices 130 can include one or more first devices 132 and one or more other devices 134. The method fro determining positions can begin with the central controller 110 determining a position of the one or more first devices 132. This initial positioning can be performed using various techniques, including infrastructure -based positioning (IPos) where the device location is multilaterated using signals from multiple base stations 120. The first devices 132, once located, can serve as anchor nodes for the collaborative positioning of the other devices 134.

[0047] The system can comprise many communication paths. Communication between the base station 120 and the devices 130 can occur over a downlink 144 and an uplink 142. The downlink 144 can be used, for example, to inform devices of their computed positions or to provide scheduling information. The uplink 142 can be used by the devices 130 to send measurement reports to the network for processing by the central controller 110.

[0048] One component of the system is peer-to-peer communication via measurement signals 140. These communications allow devices 130 to perform direct ranging measurements with each other without the data path going through a base station 120. This can be enabled by protocols including, but not limited to, 5G NR’s Sidelink protocol. The measurement signals 140 exchanged between devices can comprise known reference signals, such as the Sounding Reference Signal (SRS) or the Positioning Reference Signal (PRS), or Sidelink signals. Using these measurement signals 140, the system can create a topology of range estimates that can be used to accurately locate even those devices 134 that have poor connectivity to the infrastructure base stations 120.

[0049] To enable scalable and efficient collaborative positioning, the system can utilize a novel distributed Sidelink access protocol. An exemplary embodiment of this protocol is shown in FIG. 2. This protocol intelligently manages peer-to-peer method by splitting control between the network and the individual devices, operating on two distinct time scales. On a course time scale the network performs dynamic side link resource scheduling 210. A network entity such as a base station operating under the direction of the central controller, can dynamically adapt the quantity of allocated slots 240 that are available for positioning measurements. This adaptation can be based on an aggregated collision probability experienced by the devices in the network, which they can report in a measurement report 200.

[0050] In some embodiments, the network can use an inverse additive increase multiplicative decrease (AIMD) algorithm to control the number of slots, increasing them when collision rates are high and decreasing them rates are low to optimize resource utilization. On a much finer time scale, each individual device can execute a two-step contention resolution process to access these allocated slots the first step can be a stochastic access process 220. Here, each device independently and probabilistically determines whether it should transmit the measurement signal. This decision can be governed by a stochastic policy derived from a collaborative positioning utility function. This utility function can account for the diminishing incremental benefit of additional measurements to the same set of neighbors, thereby prioritizing transmissions that contribute most to the overall networks positioning accuracy. Ifa device decides to transmit based on this statistic process, the second step can involve selecting a specific slot from the allocated SL slots 240. This selection can be performed using a mechanism such as a universal hash function, which maps the device's unique identifier to a particular slot. This hashing method helps orthogonalized transmissions among different devices, significantly reducing the probability of simultaneous transmissions and collisions.

[0051] The transmitted measurement signal 230 itself can be a broadcast signal, such as a side link signal or a sounding reference signal (SRS), design port high resolution ranging. By using a broadcast, a single transmission from one device can be overheard by multiple nearby “passive” receiving devices, allowing them all to perform ranging measurements simultaneously. This “passive arranging” capability dramatically improves the scalability of the measurement process. The results of these measurements are then compiled by each receiving device into a measurement report 200, which can be broken down into a transmitted signal report 242, which is then sent back to the network for processing.

[0052] Once the central controller has received enough ranging measurements from the devices in the network, a back-end positioning algorithm can be executed to compute the location of each device. As shown in FIG. 3 an exemplary embodiment provides a collaborative positioning algorithm. The input to the algorithm can be set a set of corrected ranging measurements between pairs of devices, which can be organized into a data structure such as a Euclidean distance matrix (EDM) 320. In some embodiments, it may not be feasible to obtain a direct measurement between every pair of devices, resulting in an incomplete EDM 320. To address this, the algorithm can first employ a process of sequential multilateration 300 to estimate the missing range values. This process can start with a few anchor nodes, such as the one or more devices 132 whose positions are already known, and iteratively localize other devices in the topology that have enough links you already localized nodes.

[0053] A potential challenge with sequential multilateration is that localized errors can accumulate and propagate through the network as more devices are localized, which can reduce overall accuracy. To mitigate this after the EDM 320 is populated, a location perturbation 310 step can be performed. This step can refine the estimated locations of the devices, for example, by using a gradient descent method to diminish the impact of cascading errors and find a set of locations that better fits the measured ranges.

[0054] After the EDM 320 has been completed and refined, a core localization method such as multidimensional scaling (MDS) 330 can be applied. The MDS algorithm 330 can take the completed EDM 320 and compute the relative locations of all the devices in the network withrespect to one another. This can be accomplished by converting the EDM into a gram matrix and using a process like eigenvalue decomposition to find the relative coordinates of each device in a multidimensional space.

[0055] The final step of the algorithm can be to convert these relative locations into absolute geographical coordinates. This can be accomplished through a rigid transform 440. This transform can use the known absolute positions of the anchor devices (the one or more first device is 132) to find the optimal scale, rotation, and translation to map the entire network of relative positions into an absolute coordinate system, resulting in the final absolute locations 350 for all devices in the plurality of wireless communication devices one 130. This transformation can be computed using techniques including, but not limited to, singular value decomposition (SVD).

[0056] For some embodiments of the present disclosure, the systems or methods herein can be employed, independently or in any combination, as a near real-time RAN Intelligent Controller (near RT-RCI) 400. This near RT-RIC 400 can be a component within modem wireless frameworks, such as the Open-RAN (O-RAN) framework, which supports custom applications called xApps. The near RT-RIC 400 can host a positioning xApp 430 that executes the logic for the positioning service. The near RT -RIC 400 communicates with one or more base stations 410 via a standardized E2 interface 440. An E2 agent 420 residing on the base station 410 can act as a proxy for this communication. The operational flow can begin with an initialization phase where the positioning xApp 430 and the relevant E2 nodes are set up. This can involve the xApp 430 registering the E2 nodes 431, receiving a setup response 432, and completing the xApp setup 433. Once initialized, the positioning xApp 430 can subscribe to receive measurement reports from the network 434.

[0057] The system then enters a continuous location loop 435. In this loop, the xApp 430 receives measurement reports 436 from the devices via the E2 interface 440. Based on these reports, the xApp 430 can compute the positions of the devices 437 using a collaborative positioning algorithm. Finally, the xApp 430 can inform the devices of their newly calculated positions 438 via the base station 410.

[0058] Some embodiments of the present disclosure have additional features involved. One of these features can be a timing advance correction. This allows high accuracy peer-to-peer ranging with precise correction of measurements using network provided timing advance (TA) values. In modem cellular systems like 5G, which can use orthogonal frequency division multiple access (OFDMA) for uplink transmissions, precise time synchronization at the basestation is critical. A base station 120 expects to receive uplink signals from all devices within its cell and synchronous alignment. Since devices are at varying distances, their signals would naturally arrive at different times. To counteract this, the base station 120 issue a specific TA command to each device, instructing it to advance its transmission clock. This can help signals from all devices, regardless of their distance, arrive at the base station simultaneously, preventing inter-symbol interference.

[0059] This network function can have a direct consequence for sideline positioning. When a device transmits a signal link measurement signal, its transmission can be advanced or delayed according to its assigned TA value. This timing offset can be applied to any time with light measurement performed by a receiving peer device, creating a bias in the raw distance calculation. To obtain a true geometric range, this bias may need to be removed. The central controller 110, having access to network wide parameters can be ideally positioned to perform this correction. After a listening device reports a raw, estimated ranging measurement to a transmitting device, decentral controller 1 10 receives the TA value assigned to that specific transmitter. It then calculates the corrected, true ranging measurement by compensating for the offset.

[0060] Various embodiments of the present disclosure may find different physical layer signal design and control plane communication structures. The design and structures can be engineered for high performance and seamless integration with existing wireless standards. The transmitted measurement signal 230 can be a broadcast signal containing an SRS. To achieve high resolution changing, this SRS can be configured to span the entire bandwidth of the channel. The fundamental ranging resolution can be inversely proportional to the signal’s bandwidth. Using a wide bandwidth, including but not limited to 40MHz or 95 MHz, can directly translate to a higher potential for ranging accuracy. In some embodiments, the rest can occupy the last four symbols of a time slot. This specific placement can allow the preceding data symbols within the same slot to carry other crucial information, such as the unique identifier of the transmitting device, which can be useful for peer identification in a broadcast scenario. The reference signals themselves, such as Zadoff-Chu sequences used for SRS, possess excellent autocorrelation properties, enabling precise channel estimation and a time- of- flight detection at the receiver.

[0061] The measurement report 200 containing the ranging data can be structured in a 5G compliant manner for interoperability in various embodiments disclosed herein. As provided for in three GPP standards, the radio resource control (arc) protocol layer can handle controlplane signaling, including the configuration, and reporting of measurements. An embodiment of the invention can find a new measurement object, for example, a “MeasurementObjectSL- SRS” object at the RRC layer. Some embodiments of the present disclosure can have the network configuring devices with this object, specifying the periodicity and content of the report 200. The measurement report 200 can encapsulate not only the list of ranging measurements but also the collision probability experienced by the reporting device. This collision metric can be a piece of feedback, which can be used by the network for the dynamic resource scheduling 210 and by the device itself or its stochastic access process 220.

[0062] The various embodiments disclosed herein can be applicable to both 2D and 3D positioning, with specific considerations possible to be applied for the more challenging 3D case. While 2D positioning can theoretically be achieved with three anchor measurements, determining a 3D position can utilize four such measurements. Furthermore, 3D positioning can be highly sensitive to the geometric dilution of precision problem, where the spatial geometry of the anchor node significantly impacts the accuracy of the final position estimate. If the anchors are poorly distributed, small errors in the range measurements can be magnified into large errors in these computed 3D coordinates. For this reason, purely infrastructure-based 3D positioning may utilize signals from many base stations (e.g., 6-7) to ensure a favorable geometry. The collaborative approach can inherently mitigate this issue. By creating a dense mesh of peer-to-peer links, the system can leverage a large and diverse set of potential anchors at various locations and, crucially, at different elevations, which dramatically improves the geometry and reduces the geometric dilution of precision. For initial anchor positioning, the positioning process can be bootstrapped using a set of trusted anchored nodes. The determination of the positions for these one or more first devices 132 can be accomplished by implementing a standard infrastructure-based positioning algorithm, which can involve multilateration using signals from three or more base stations 120.

[0063] The methods, processes, in systems described herein or any of the embodiments disclosed herein can be implemented in a variety of hardware and software configurations. The central controller 110, for example, can be a dedicated physical server, a virtual machine running in a data center, or a distributed computing system. It can comprise one or more hardware processors and one or more forms of non transitory computer readable media. The memory can store program code and logical instructions which, when executed by the amount of more processors, cause the system to perform the methods described herein, including receiving and parsing measurement reports, annlvina timing advance corrections, executingthe distributed access scheduling, and performing the multistep collaborative positioning algorithm to determine the final device locations. Given these methods, processes, and systems, the explicit implementations can include any of the aforementioned examples, but are not limited to the aforementioned examples.

[0064] The various embodiments of the present disclosure find many use cases. For example, some embodiments can be useful for minimally invasive cranial endoscopic procedures such as brain tumor surgery, pediatric neurosurgery, treatment of hydrocephalus and intracranial cysts, and other neurosurgical procedures. Some embodiments can be useful for natural orifice transluminal endoscopic surgery procedures. Some embodiments can be useful for minimally invasive surgery procedures requiring endoscopic tools.

[0065] It is to be understood that the embodiments and claims disclosed herein are not limited in their application to the details of construction and arrangement of the components set forth in the description and illustrated in the drawings. Rather, the description and the drawings provide examples of the embodiments envisioned. The embodiments and claims disclosed herein are further capable of other embodiments and of being practiced and carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein are for the purposes of description and should not be regarded as limiting the claims.

[0066] Accordingly, those skilled in the art will appreciate that the conception upon which the application and claims are based may be readily utilized as a basis for the design of other structures, methods, and systems for carrying out the several purposes of the embodiments and claims presented in this application. It is important, therefore, that the claims be regarded as including such equivalent constructions.

[0067] Furthermore, the purpose of the foregoing Abstract is to enable the United States Patent and Trademark Office and the public generally, and especially including the practitioners in the art who are not familiar with patent and legal terms or phraseology, to determine quickly from a cursory inspection the nature and essence of the technical disclosure of the application. The Abstract is neither intended to define the claims of the application, nor is it intended to be limiting to the scope of the claims in any way.

Claims

CLAIMSWhat is claimed is:

1. A method for determining positions of one or more devices within a wireless communication system, the method comprising: determining, by a central controller, a position of one or more first devices in a plurality of wireless communication devices; receiving, at a central controller, one or more communications from one or more devices in the plurality of wireless communication devices, each communication comprising one or more estimated ranging measurements between the respective device and a respective other device in the plurality of wireless communication devices, wherein each ranging measurement is derived from a respective measurement signal transmitted by the other device; and determining, by the central controller, based at least in part on the position of the one or more first devices and the one or more communications, a position of each of the plurality of wireless communication devices.

2. The method of claim 1, further comprising: generating, based at least in part on the position of each of the plurality of wireless communication devices, a network topology of each of the plurality of communication devices.

3. The method of claim 1, further comprising: accessing, by the central controller, a timing advance value for each of the one or more devices, wherein each timing advance value is configured by the wireless communication system; and calculating one or more corrected ranging measurements between the respective device and a respective other device by compensating each of the one or more estimated ranging measurements using the respective timing advance value of the respective other device.

4. The method of claim 3, wherein the position of each of the plurality of wireless communication devices is determined, by the central controller, based at least in part on, the one or more corrected ranging measurements.

5. The method of claim 1, wherein each of the plurality of wireless communication devices are User Equipments (UEs), and the measurement signals are Sidelink signals or Sounding Reference Signals (SRS).

6. The method of claim 1, wherein the central controller is a near real-time RAN Intelligent Controller (near-RT RIC).

7. The method of claim 6, wherein the one or more measurements is received by the near- RT RIC from a base station (gNB) over an E2 interface.

8. The method of claim 5, wherein the measurement signals are transmitted by the respective other devices within a set of allocated time slots.

9. The method of claim 8, wherein the allocated time slots can be within a Sidelink resource region.

10. The method of claim 8, wherein the distributed access protocol comprises each UE independently determining whether to transmit the measurement signals based on a stochastic policy that prioritizes transmissions contributing to an overall network positioning accuracy.

11. The method of claim 10, wherein the stochastic policy is based on a collaborative positioning utility function that accounts for a diminishing incremental utility of additional measurement signal transmissions to the same set of neighboring devices.

12. The method of claim 11, wherein upon determining to transmit a measurement signal, the respective other device selects a specific time slot from the set of allocated time slots using a hash function.

13. The method of claim 8, further comprising dynamically adapting, with the central controller, a quantity of the allocated time slots based, at least in part, on an aggregated collision probability received from a plurality of the UEs.

14. The method of claim 13, wherein the dynamic adaptation is performed using an inverse additive-increase multiplicative-decrease (AIMD) algorithm, wherein the quantity of allocated time slots is additively increased when the aggregated collision probability is above a threshold and multiplicatively decreased when the aggregated collision probability is below the threshold.

15. The method of claim 5, wherein the measurement signal is on a broadcast channel in the Sidelink.

16. The method of claim 5, wherein the one or more measurements from the one or more devices in the plurality of communication devices comprise a structure as a MeasurementObjectSL-SRS object at a Radio Resource Control (RRC) layer.

17. The method of claim 1, wherein determining the position of the one or more first devices comprises implementing an infrastructure -based positioning algorithm with three or more base stations.

18. The method of claim 1, wherein the one or more communications from the one or more devices further comprises a collision probability experienced by the one or more devices.

19. The method of claim 1, wherein the position of each of the plurality of wireless communication devices is a 3D position, and wherein determining the position of each of the plurality of wireless communication devices utilizes at least four corrected ranging measurements to four different devices.

20. The method of claim 1, wherein determining the position of each of the plurality of wireless communication devices comprises using a Multi-dimensional Scaling (MDS) based algorithm on a matrix of corrected ranging measurements.

21. The method of claim 20, wherein prior to using the MDS-based algorithm, a sequential multi-lateration process is used to estimate missing ranging measurements within the matrix of corrected ranging measurements, and after the sequential multi-lateration process, a location perturbation step using gradient descent is performed to diminish cascading localization errors.

22. A system for determining positions of a plurality of user devices, the system comprising: one or more processors; and one or more memories, the one or more memories, individually or collectively, comprising logical instructions that, when executed by the one or more processors, individually or collectively, cause the one or more processors, individually or collectively, to perform the method, or a portion of the method, of any of claims 1-19.

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