Mitigating Non-Line-of-Sight (NLOS) Errors in User Equipment (UE) Positioning

Abstract

Systems, methods, apparatus, and computer program products for non-line-of-sight (NLOS) error mitigation for user equipment (UE)-based positioning. For example, some embodiments described herein may provide for the use of a blind learning algorithm for channel bias distribution estimation for UE-based positioning. The UE may use the NLOS bias distribution received from a network node to perform positioning calculations for the UE, as described elsewhere herein.

Description

Technical Field

[0001] Some example embodiments may generally relate to mobile or wireless telecommunication systems, such as Long Term Evolution (LTE) or fifth generation (5G) radio access technology or new radio (NR) access technology, or may relate to other communication systems. For example, certain embodiments may relate to systems and / or methods for user equipment (UE)-based positioning non-line-of-sight (NLOS) error mitigation. Background Art

[0002] Examples of mobile or wireless telecommunications systems may include the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN), LTE-Advanced (LTE-A), MulteFire, LTE-A Pro, and / or fifth-generation (5G) radio access technology or New Radio (NR) access technology. 5G wireless systems refer to next-generation (NG) radio systems and network architectures. 5G is primarily built on New Radio (NR), but 5G (or NG) networks can also be built on E-UTRA radio. NR is estimated to provide bit rates on the order of 10-20 Gbit / s or higher and support, at a minimum, enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). NR is expected to provide ultra-wideband and ultra-robust low-latency connectivity and large-scale networks to support the Internet of Things (IoT). As IoT and machine-to-machine (M2M) communications become increasingly prevalent, the need for networks that can meet the demands of low power consumption, low data rates, and long battery life will continue to grow. Note that in 5G, a node that can provide radio access functions to user equipment (i.e., similar to a Node B in UTRAN or an eNB in ​​LTE) can be named gNB when built on an NR radio, and can be named NG-eNB when built on an E-UTRA radio. BRIEF DESCRIPTION OF THE DRAWINGS

[0003] For a proper understanding of the example embodiments, reference should be made to the accompanying drawings, in which:

[0004] Figure 1 shows an example signal diagram for UE-based positioning NLOS error mitigation according to some embodiments;

[0005] Figure 2 shows an example probability distribution function for NLOS bias according to some embodiments;

[0006] Figure 3 shows a mixture of Gaussian approximations of NLOS deviation histograms according to some embodiments;

[0007] Figure 4 shows an example downlink time difference of arrival (DL-TDOA) positioning error with a 5 megahertz (MHz) positioning reference signal (PRS) in accordance with some embodiments;

[0008] Figure 5 An example flow chart illustrating a method according to some embodiments is shown;

[0009] Figure 6 An example flow chart illustrating a method according to some embodiments is shown;

[0010] Figure 7a An example block diagram illustrating an apparatus according to one embodiment; and

[0011] Figure 7b An example block diagram of an apparatus according to another embodiment is shown. DETAILED DESCRIPTION

[0012] It will be readily understood that the components of certain example embodiments, as generally described and illustrated in the figures herein, may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of some example embodiments of systems, methods, apparatuses, and computer program products for UE-based positioning NLOS error mitigation is not intended to limit the scope of certain embodiments, but rather represents selected example embodiments.

[0013] The features, structures, or characteristics of the example embodiments described throughout this specification may be combined in any suitable manner in one or more example embodiments. For example, use of the phrases "certain embodiments," "some embodiments," or other similar language throughout this specification means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment. Thus, appearances of the phrases "in certain embodiments," "in some embodiments," "in other embodiments," or other similar language throughout this specification are not necessarily all referring to the same set of embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more example embodiments.

[0014] In addition, if desired, the different functions or operations discussed below can be performed in different orders and / or simultaneously with each other. In addition, if desired, one or more of the functions or operations described can be optional or can be combined. Therefore, the following description should be regarded as merely illustrating the principles and teachings of certain example embodiments, rather than limiting them.

[0015] UE-based positioning may refer to when the UE is the device that is performing the actual positioning calculations. In cellular networks, the network side typically performs positioning calculations based on measurement reports made at the UE or network side (e.g., at the Location Management Function (LMF)). UE-based positioning may reduce the latency required relative to downlink (DL) UE-assisted positioning because the UE may not have to make any measurement reports to the network before the network completes the position calculation. For example, this latency reduction may be important for use cases with strict latency requirements, such as for private networks or vehicle-to-everything (V2X) applications. During UE-based positioning, the location of one or more network nodes (e.g., gNB) may have to be signaled to the UE so that the UE can perform positioning calculations locally.

[0016] In LTE, a commonly used positioning solution is to observe the time difference of arrival (OTDOA). NR OTDOA (which may be called downlink time difference of arrival (DL-TDOA)) can be implemented in NR. Using DL signals, the time difference of arrival (TDOA) between multiple network node transmissions can be estimated at the UE. In LTE, the DL signal used for OTDOA can be called a positioning reference signal (PRS), and PRS can be introduced again. The UE can use PRS from different cells to measure the reference signal time difference (RSTD) and can report the RSTD measurement to a location server, which is an example of a network node. The UE can communicate with the location server using the LTE Positioning Protocol (LPP). The location server (which may be called LMF in NR) can then calculate the position of the UE using the known position of the network node (e.g., base station) and the RSTD measurement. In the case of UE-based positioning, the position of the network node can be transmitted to the UE, so the RSTD measurement report may not have to be sent.

[0017] One challenge of using radio frequency (RF) signals for positioning can include the presence of NLOS conditions. For timing-based techniques, the signal arrival time can deviate from the true propagation time of the signal between devices due to the additional time required for the signal to arrive under NLOS conditions. For example, for NLOS signals in a cellular environment, additional deviations in the signal arrival time on the order of tens to hundreds of nanoseconds (ns) can be irregular. In this example, a 50ns deviation in the signal arrival time can result in a 15-meter (m) ranging error if not compensated. In order to meet many commercial use cases for NR positioning, it may be necessary to address the NLOS deviation in the signal arrival time.

[0018] One possible solution to the NLOS bias problem for positioning is to use a blind learning algorithm for channel bias distribution estimation (which may be called an NLOS mitigation algorithm or channel bias estimation). The blind learning algorithm can learn the distribution of arrival time deviations caused by NLOS conditions and use it to improve positioning accuracy.

[0019] Some embodiments described herein may provide for the use of a blind learning algorithm for channel deviation distribution estimation for UE-based positioning. For example, a UE may use NLOS deviation distribution information received from a network node to perform positioning calculations for the UE, as described elsewhere herein. In this manner, the UE may perform UE-based positioning, which may reduce latency relative to network node-based positioning. Reducing latency may improve communication between devices, particularly URLLC communication.

[0020] Figure 1 Example signal diagrams for UE-based positioning NLOS error mitigation are shown in accordance with some embodiments. Figure 1 Network nodes (eg, LMF, base station, etc.) and UEs are shown.

[0021] As shown in 100, a UE may transmit and a network node may receive a Minimization of Drive Tests (MDT) report including NLOS deviation information. The NLOS deviation information may include reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements. This may provide UE reporting of NLOS deviation information as a new MDT measurement so that it can be collected and used using MDT mechanisms. The UE NLOS deviation information report may include a collection of RSTD measurements over time or a collection of RSTD deviation estimates over time.

[0022] The NLOS deviation information may be reported to a network node (e.g., gNB) in a UEInformationResponse Radio Resource Control (RRC) message, which the network node may distribute to another network node (e.g., LMF) using the New Radio Positioning Protocol A (NRPPa) (in some embodiments, the NLOS deviation information may be reported directly to the network node (e.g., LMF) using the Long Term Evolution Positioning Protocol (LPP)). When the MDT reporting mechanism is used, the full RSTD measurement report used in the LPP may not be required. The set of RSTD measurements and RSTD deviation estimates may be customized for use by the network node (e.g., LMF) for use with a blind learning algorithm, as the RSTD measurements reported in the MDT may not be used by the network node to calculate the UE position. The UE may report locally calculated statistical parameters (described elsewhere herein) or may report the performance of the latest blind learning algorithm model for network evaluation / refinement.

[0023] As shown in 102, the network node may determine at least one estimate of the NLOS bias distribution and at least one statistical parameter associated with representing the NLOS bias distribution. For example, the network node may perform the estimation of the NLOS bias distribution based on one or more reporting mechanisms. Although some embodiments are described in the context of DL-TDOA, certain embodiments described herein may also be applicable to observed time difference of arrival (OTDOA).

[0024] The statistical parameters may include the mean of a mixture of Gaussian distributions of NLOS biases (e.g., the mixture of Gaussian distributions may be a Gaussian distribution among multiple Gaussian distributions), the standard deviation of the mixture of Gaussian distributions of NLOS biases, the weights of the Gaussian distributions included in the mixture of Gaussian distributions, etc. These parameters may be associated with recreating or representing the NLOS bias distribution. The network node may also report how many RSTD measurements it used to calculate the statistical parameters.

[0025] As an example, in some scenarios, two Gaussian distributions may be sufficient to represent the NLOS deviation distribution. In this case, the statistical parameters may include two weights, two means, and two standard deviations. Figure 2 Examples of how a distribution can be visualized and the parameters describing it are described. Each parameter can be represented by a specific number of bits in the message or signaling. The number of bits can depend on the desired overall positioning accuracy. In some embodiments, the statistical parameter can be any statistical parameter that can be used to represent the NLOS deviation distribution, which can be different from the example parameters described above for a mixture of Gaussian distributions. In some embodiments, the NLOS deviation distribution can be different from a Gaussian distribution, such as a Poisson distribution, an exponential distribution, etc.

[0026] In some embodiments, the number of distributions used may vary depending on the type of device executing the blind learning algorithm. For example, the means and standard deviations of three Gaussian distributions may be sufficient for an entity other than a network node to recreate the NLOS bias distribution and thus use the blind learning algorithm.

[0027] As shown in 104, the UE and the network node may communicate with each other to perform a positioning request. As shown in 106, the UE may transmit and the network node may receive a request for NLOS bias distribution information. For example, a UE performing UE-based positioning may request NLOS bias distribution information. The request may be in the form of an accuracy threshold (e.g., the UE may request an accuracy above or below a threshold, and the network node (e.g., LMF) may determine to use a UE-based blind learning algorithm based on this). The accuracy threshold may also be in the form of quality of service (QoS) information. Additionally or alternatively, the request may include user information identifying a user (subscription) of the UE (e.g., the network node may determine the NLOS bias distribution information based on the user). For example, the request may be sent via LPP and may be an extension of the LPP OTDOA-RequestAssistanceData information element (IE).

[0028] The timer may be configured by the network node, and the expiration of the timer may be tracked by the UE to determine when the NLOS deviation distribution information is out of date. In some embodiments, the network node may signal to the UE that new NLOS deviation distribution information is available, and the NLOS deviation distribution information may then be transmitted to the UE. For example, updating the NLOS deviation distribution information may occur in the event of a dynamic environmental change that may have an updated model.

[0029] In some embodiments, the network node may determine to transmit NLOS bias distribution information (e.g., based on the user of the UE) without receiving a request for the NLOS bias distribution information. For example, the network node may store user information for a particular UE and may transmit NLOS bias distribution information based on the user (e.g., the network node may determine which UEs pay for use of a UE-based blind learning algorithm and may signal the parameter to the UE when the UE is configured for DL-TDOA).

[0030] As shown in 108, the network node may transmit and the UE may receive NLOS deviation distribution information. For example, such transmission may occur via LPP and may be an extension of the LPP OTDOA-ProvideAssistanceData IE. The non-line-of-sight (NLOS) deviation distribution information may include statistical parameters associated with representing the NLOS deviation distribution. For example, the NLOS deviation distribution may include the number of Gaussian distributions included in a mixture of Gaussian distributions (which may represent the NLOS deviation distribution), the mean of the Gaussian distribution, the variance of the Gaussian distribution, etc.

[0031] Additionally or alternatively, the NLOS deviation distribution information can be associated with information identifying the location of one or more gNBs (or other network nodes). Due to the relatively consistent operation of the gNBs over time, the deviation statistics can be relatively stable over time. Consequently, to conserve downlink bandwidth, the network node may not need to transmit the deviation parameters to the UE if the UE has already received the values ​​of those parameters and if those values ​​have not changed. Similarly, the gNB locations may not change over time. Therefore, the network node may not need to transmit this information if the UE has previously received it.

[0032] As shown at 110, the UE may perform positioning reference signal (PRS) reception and / or measurement. As shown at 112, the UE may use the NLOS deviation distribution information to perform a position calculation for the UE. In some embodiments, performing this calculation may include calculating a deviation realization of a network node. For example, for a given positioning estimate for the UE (e.g., obtained through use of a blind learning algorithm), the UE may calculate the deviation realization for each gNB by subtracting the measured flight time (derived from the RSTD and estimated transmission time of that gNB) from the line-of-sight (LOS) flight time, where the line-of-sight (LOS) flight time is determined based on the distance between the gNB and the estimated UE position.

[0033] In this way, some embodiments described herein facilitate the use of blind learning algorithms during UE-based positioning by providing signaling to the UE to obtain the NLOS deviation distribution. The use of a blind learning algorithm can facilitate the UE to calculate its position more accurately, while still in a low-latency manner (since these operations are UE-based). Without obtaining the NLOS deviation distribution, UE-based positioning that relies on timing-based techniques (such as DL-TDOA) may be limited in the accuracy that can be achieved. Network derivation of the NLOS deviation distribution can be performed using MDT measurements that are collected and provided to a network node (e.g., a positioning server). Providing this information to the positioning server can facilitate improved calculation of the NLOS deviation distribution based on a large number of UEs reporting NLOS deviation information to the positioning server.

[0034] As mentioned above, providing Figure 1 As an example, other examples are possible according to some embodiments.

[0035] Figure 2 An example probability distribution function for NLOS deviation according to some embodiments is shown. Specifically, Figure 2 An example visualization of the NLOS bias distribution that can be used for a blind learning algorithm and the parameters that can be used to represent it are shown. The NLOS bias distribution can include a mixture of Gaussian distributions n (e.g., n=1, 2). The Gaussian n can be represented by weights (w n), mean (μ n ) and standard deviation (σ n ) can be parameterized. As shown at 200, the NLOS deviation distribution can be based on a first Gaussian distribution (Gaussian1), which can be based on parameters w1, μ1, and σ1. As shown at 202, the NLOS deviation distribution can be based on a second Gaussian distribution (Gaussian2), which can be based on parameters similar to those described for Gaussian1. As shown at 204, the LOS arrival time can be represented as the NLOS deviation distribution.

[0036] As mentioned above, providing Figure 2 As an example, other examples are possible according to some embodiments.

[0037] Figure 3 shows a mixture of Gaussian approximations of NLOS deviation histograms according to some embodiments. For example, Figure 3 A visualization 300 of a mixture of Gaussian approximations of NLOS deviation histograms is shown, where different numbers of Gaussian distributions are included in the model.

[0038] The probability distribution function (PDF) of the NLOS bias can be calculated. For example, the NLOS bias information can be determined based on the following equation:

[0039]

[0040] in is the NLOS deviation of the t-th label message at the j-th anchor point, Indicates that the determination is based on the time of arrival (ToA) of the tag message at all other anchor points except the j-th anchor point. The tag message may include any type of message delivered by the tag over a period of time. The tag may be any type of communication device (s) capable of sending wireless signals (e.g., tag messages) over one or more tag communication channels. The anchor point may include any type of communication device (s) capable of receiving the tag message over an appropriate tag communication channel, determining the ToA of the tag message, and transmitting the ToA information and information identifying the tag message to the server via an appropriate server communication channel. TiA tj is the ToA of the t-th label message at the j-th anchor point. is the estimated transmission time of the label of the t-th label message with reference to the j-th anchor clock, Denotes that the determination is based on the ToA of the tag messages at all other anchor points except the j-th anchor point. is the estimated position of the tag that transmits the t-th tag message, Indicates that the position determination is based on the ToA of the tag messages of all other anchor points except the j-th anchor point. is the known position of the jth anchor point. c is the speed of light.

[0041] This calculation can be done at a network node (e.g., LMF) based on a set of RSTD measurements and corresponding UE position estimates. Given this PDF, the network node can approximate the function using a mixture of Gaussian distributions and can determine the parameters (e.g., weights, mean, standard deviation) using curve fitting techniques (e.g., where a curve or mathematical function that best fits a series of data points is constructed). Figure 3 An example showing how to use a mixture of Gaussian distributions to improve the bias PDF by adding more Gaussians to the model. For example, a mixture of three Gaussian distributions (3 Gaussians) has the closest approximation to the histogram compared to a mixture of one Gaussian distribution (1 Gaussian) and a mixture of two Gaussian distributions (2 Gaussians).

[0042] As mentioned above, providing Figure 3 As an example, other examples are possible according to some embodiments.

[0043] Figure 4 An example downlink time difference of arrival (DL-TDOA) positioning error with a 5 megahertz (MHz) positioning reference signal (PRS) is shown in accordance with some embodiments. For example, Figure 4 A visualization 400 of horizontal positioning errors for DL-TDOA with a 5 megahertz (MHz) bandwidth PRS is shown, both with a blind learning algorithm (in Figure 4 ), as shown in 402, and there is no blind learning algorithm in the urban macro environment (in Figure 4 is marked as “No BLA” in the example), as shown in 404.

[0044] Some embodiments described herein can be used for various carrier frequencies and bandwidths. Using a blind learning algorithm may perform well and, in particular, may be a solution for wide bandwidths in NR. Certain embodiments described herein may have the following advantages: namely, enabling UE-based use of a blind learning algorithm for channel deviation distribution estimation for UE-based positioning, enabling UE-based positioning to perform higher-precision positioning using DL-TDOA.

[0045] As mentioned above, providing Figure 4 As an example, other examples are possible according to some embodiments.

[0046] Figure 5 An example flow chart of a method according to some embodiments is shown. For example, Figure 5 Example operation of a UE (eg, similar to apparatus 20 ) is shown. Figure 5 Some of the operations shown may be similar to Figures 1 to 4 Shown and about Figures 1 to 4 Describes some of the operations.

[0047] In one embodiment, the method may include: receiving non-line-of-sight (NLOS) deviation distribution information at 500. The non-line-of-sight (NLOS) deviation distribution information may include at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution. In one embodiment, the method may include: performing at least one calculation of at least one position using the non-line-of-sight (NLOS) deviation distribution information at 502.

[0048] In some embodiments, the method may include transmitting at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information. In some embodiments, the non-line-of-sight (NLOS) deviation information may include reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements. In some embodiments, the reference signal time difference (RSTD) related information may include at least one of at least one reference signal time difference (RSTD) measurement over time or at least one reference signal time difference (RSTD) deviation estimate over time. In some embodiments, the non-line-of-sight (NLOS) deviation information may also include at least one local non-line-of-sight (NLOS) deviation distribution.

[0049] In some embodiments, the non-line-of-sight (NLOS) deviation information may be included in at least one radio resource control (RRC) message or may be provided using the Long Term Evolution Positioning Protocol (LPP). In some embodiments, the method may include determining whether the non-line-of-sight (NLOS) deviation distribution information is outdated based on at least one timer. In some embodiments, the method may include determining whether the NLOS deviation distribution information is outdated based on local sensor data or measured channel condition changes. In some embodiments, the method may include providing at least one request for the non-line-of-sight (NLOS) deviation distribution information before receiving the non-line-of-sight (NLOS) deviation distribution information. In some embodiments, providing at least one request for the non-line-of-sight (NLOS) deviation distribution information may be based on a user equipment (UE) performing or determining to perform at least one user equipment (UE)-based positioning.

[0050] In some embodiments, the at least one request may include information identifying at least one of: at least one accuracy threshold associated with performing at least one user equipment (UE)-based positioning, or user information associated with the user equipment (UE). In some embodiments, providing the at least one request may further include providing the at least one request using a Long Term Evolution Positioning Protocol (LPP). In some embodiments, providing the at least one request may further include providing the at least one request in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE).

[0051] In some embodiments, providing at least one request may further include providing at least one request based on receiving at least one indication that non-line-of-sight (NLOS) deviation distribution information is available. In some embodiments, receiving the non-line-of-sight (NLOS) deviation distribution information may further include receiving the non-line-of-sight (NLOS) deviation distribution information using the Long Term Evolution Positioning Protocol (LPP). In some embodiments, receiving the non-line-of-sight (NLOS) deviation distribution information may further include receiving the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE). In some embodiments, the at least one statistical parameter may include at least one of the following: at least one mean of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, at least one standard deviation of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, and at least one weight corresponding to a Gaussian distribution included in the at least one mixture of Gaussian distributions.

[0052] In some embodiments, a non-line-of-sight (NLOS) deviation distribution may include at least one of the following: the number of Gaussian distributions in at least one mixture of Gaussian distributions, at least one mean of at least one Gaussian distribution included in at least one mixture of Gaussian distributions, and at least one variance of at least one Gaussian distribution included in at least one mixture of Gaussian distributions. In some embodiments, performing the calculation of at least one position may include calculating at least one deviation realization for at least one network node. In some embodiments, calculating at least one deviation realization may further include calculating at least one deviation realization by subtracting at least one measured flight time from at least one line-of-sight (LOS) flight time, the at least one line-of-sight (LOS) flight time being determined based on at least one distance between the at least one network node and at least one estimated user equipment (UE) position.

[0053] In some embodiments, the non-line-of-sight (NLOS) deviation distribution information may be associated with information identifying a location of at least one network node. In some embodiments, at least one value of at least one statistical parameter may be a value different from at least one previously received parameter. In some embodiments, receiving the non-line-of-sight (NLOS) deviation distribution information may further include receiving the non-line-of-sight (NLOS) deviation distribution information based on at least one user associated with a user equipment (UE).

[0054] As mentioned above, providing Figure 5 As an example, other examples are possible according to some embodiments.

[0055] Figure 6 An example flow chart of a method according to some embodiments is shown. For example, Figure 6Example operation of a network node (eg, similar to apparatus 10 ) is shown. Figure 6 Some of the operations shown may be similar to Figures 1 to 4 Shown and about Figure 6 Describes some of the operations.

[0056] In one embodiment, the method may include: determining to transmit non-line-of-sight (NLOS) deviation distribution information at 600. The non-line-of-sight (NLOS) deviation distribution information may include at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution. In one embodiment, the method may include: transmitting the non-line-of-sight (NLOS) deviation distribution information at 602.

[0057] In some embodiments, the method may include receiving at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information. In some embodiments, the non-line-of-sight (NLOS) deviation information may include reference signal time difference (RSTD) related information or time of arrival (TOA) related measurement. In some embodiments, the reference signal time difference (RSTD) related information may include at least one of at least one reference signal time difference (RSTD) measurement over time or at least one reference signal time difference (RSTD) deviation estimate over time. In some embodiments, the non-line-of-sight (NLOS) deviation information may further include at least one local non-line-of-sight (NLOS) deviation distribution. In some embodiments, the non-line-of-sight (NLOS) deviation information may be included in at least one radio resource control (RRC) message, or may be provided using the New Radio Positioning Protocol A (NRPPa) (e.g., provided to the LMF via the gNB), or may be provided using the Long Term Evolution Positioning Protocol (LPP) (e.g., provided directly to the LMF).

[0058] In some embodiments, the method may include determining at least one estimate of at least one non-line-of-sight (NLOS) bias distribution and at least one statistical parameter associated with representing the at least one non-line-of-sight (NLOS) bias distribution. In some embodiments, determining the at least one estimate of the at least one non-line-of-sight (NLOS) bias distribution may be based on at least one of: at least one network-based downlink time difference of arrival (DL-TDOA) positioning related measurement report, or at least one non-line-of-sight (NLOS) bias report collected using at least one minimization of drive tests (MDT) mechanism. In some embodiments, the at least one network-based downlink time difference of arrival (DL-TDOA) positioning related measurement report may include at least one reference signal time difference (RSTD) related measurement report performed during at least one network-based positioning.

[0059] In some embodiments, at least one non-line-of-sight (NLOS) deviation report collected using at least one minimization of drive test (MDT) mechanism may include at least one of the following: at least one reference signal time difference (RSTD) related measurement, or at least one reference signal time difference (RSTD) related deviation estimate, or wherein the non-line-of-sight (NLOS) deviation information also includes at least one local non-line-of-sight (NLOS) deviation distribution. In some embodiments, at least one statistical parameter may include at least one of the following: at least one mean of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, at least one standard deviation of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, at least one weight corresponding to a Gaussian distribution included in the at least one mixture of Gaussian distributions. In some embodiments, the method may include transmitting information identifying the reference signal time difference (RSTD) related measurement, at least one number of the reference signal time difference (RSTD) related measurements used to calculate at least one number of the at least one statistical parameter.

[0060] In some embodiments, the method may include receiving at least one request for non-line-of-sight (NLOS) deviation distribution information. In some embodiments, the at least one request may further include information identifying at least one of: at least one accuracy threshold associated with at least one user equipment (UE)-based positioning, or at least one user associated with at least one user equipment (UE). In some embodiments, receiving the at least one request may further include receiving the at least one request using the Long Term Evolution Positioning Protocol (LPP).

[0061] In some embodiments, receiving the at least one request may further include receiving the at least one request in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE). In some embodiments, the method may include transmitting at least one indication that non-line-of-sight (NLOS) deviation distribution information is available, and receiving the at least one request may further include receiving the at least one request based on transmitting the at least one indication. In some embodiments, the at least one non-line-of-sight (NLOS) deviation distribution may include at least one of the following: a number of Gaussian distributions in at least one mixture of Gaussian distributions, at least one mean of at least one Gaussian distribution included in the at least one mixture of Gaussian distributions, and at least one variance of at least one Gaussian distribution included in the at least one mixture of Gaussian distributions.

[0062] In some embodiments, determining the at least one statistical parameter may be based on at least one probability distribution function (PDF). In some embodiments, the at least one probability distribution function (PDF) may be based on at least one reference signal time difference (RSTD) measurement and at least one corresponding user equipment (UE) position estimate. In some embodiments, determining the at least one statistical parameter may further include determining the at least one statistical parameter using at least one curve fitting technique. In some embodiments, the non-line-of-sight (NLOS) deviation distribution information may be associated with information identifying at least one location of at least one network node.

[0063] In some embodiments, the method may include determining whether at least one value of the at least one statistical parameter has been previously provided, and transmitting the non-line-of-sight (NLOS) deviation distribution information may further include transmitting the non-line-of-sight (NLOS) deviation distribution information based on determining whether at least one value of the at least one statistical parameter has been previously provided. In some embodiments, transmitting the non-line-of-sight (NLOS) deviation distribution information may further include transmitting the non-line-of-sight (NLOS) deviation distribution information using the Long Term Evolution Positioning Protocol (LPP). In some embodiments, transmitting the non-line-of-sight (NLOS) deviation distribution information may further include transmitting the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE).

[0064] As mentioned above, providing Figure 6 As an example, other examples are possible according to some embodiments.

[0065] Figure 7a An example of an apparatus 10 according to an embodiment is shown. In one embodiment, the apparatus 10 may be a node, host, or server in a communication network or serving such a network. For example, the apparatus 10 may be a network node, satellite, base station, Node B, evolved Node B (eNB), 5G Node B or access point, next generation Node B (NG-NB or gNB), LMF, positioning server, and / or WLAN access point associated with a radio access network (such as an LTE network, 5G, or NR). In an example embodiment, the apparatus 10 may be an eNB in ​​LTE or a gNB in ​​5G.

[0066] It should be understood that in some example embodiments, the device 10 may include an edge cloud server as a distributed computing system, where the server and the radio node may be independent devices that communicate with each other via a radio path or via a wired connection, or they may be located in the same entity that communicates via a wired connection. For example, in certain example embodiments where the device 10 represents a gNB, it may be configured with a central unit (CU) and a distributed unit (DU) architecture that partitions the gNB functionality. In such an architecture, the CU may be a logical node that includes gNB functionality such as transmission of user data, mobility control, radio access network sharing, positioning and / or session management. The CU may control the operation of (multiple) DUs via a fronthaul interface. The DU may be a logical node that includes a subset of the gNB functionality, depending on the functional split option. It should be noted that one of ordinary skill in the art will understand that the device 10 may include Figure 7a Components or features not shown.

[0067] like Figure 7a As shown in the example of , the device 10 may include a processor 12 for processing information and executing instructions or operations. The processor 12 may be any type of general-purpose or special-purpose processor. In fact, for example, the processor 12 may include one or more of the following: a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), a field programmable gate array (FPGA), an application-specific integrated circuit (ASIC), and a processor based on a multi-core processor architecture. Although Figure 7a A single processor 12 is shown in FIG. 1 , but according to other embodiments, multiple processors may be used. For example, it should be understood that in some embodiments, apparatus 10 may include two or more processors that may form a multiprocessor system that can support multiprocessing (e.g., in which case processor 12 may represent a multiprocessor). In some embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

[0068] Processor 12 may perform functions associated with the operation of device 10, which may include, for example, precoding of antenna gain / phase parameters, encoding and decoding of individual bits forming communication messages, formatting of information, and overall control of device 10, including processes associated with management of communication resources.

[0069] The device 10 may also include or be coupled to a memory 14 (internal or external), which may be coupled to the processor 12 and used to store information and instructions that can be executed by the processor 12. The memory 14 may be one or more memories and of any type suitable for the local application environment and may be implemented using any suitable volatile or non-volatile data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and / or removable memory. For example, the memory 14 may include random access memory (RAM), read-only memory (ROM), static storage devices such as magnetic or optical disks, hard disk drives (HDDs), or any other type of non-transitory memory or computer-readable medium. The instructions stored in the memory 14 may include program instructions or computer program code that, when executed by the processor 12, enables the device 10 to perform the tasks described herein.

[0070] In one embodiment, the device 10 may also include or be coupled to a (internal or external) drive or port configured to accept and read an external computer-readable storage medium, such as an optical disc, a USB drive, a flash drive, or any other storage medium. For example, the external computer-readable storage medium may store a computer program or software for execution by the processor 12 and / or the device 10.

[0071] In some embodiments, the device 10 may further include or be coupled to one or more antennas 15 for transmitting and receiving signals and / or data to and from the device 10. The device 10 may further include or be coupled to a transceiver 18 configured to transmit and receive information. The transceiver 18 may include, for example, multiple radio interfaces that may be coupled to the antenna(s) 15. The radio interfaces may correspond to a variety of radio access technologies, including one or more of the following: GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT-LE, NFC, radio frequency identification (RFID), ultra-wideband (UWB), MulteFire, and the like. The radio interfaces may include components such as filters, converters (e.g., digital-to-analog converters), mappers, and fast Fourier transform (FFT) modules to generate symbols for transmission via one or more downlinks and to receive symbols (e.g., via an uplink).

[0072] Thus, the transceiver 18 can be configured to modulate information onto a carrier waveform for transmission by the antenna(s) 15, and to demodulate information received via the antenna(s) 15 for further processing by other elements of the apparatus 10. In other embodiments, the transceiver 18 can be capable of directly transmitting and receiving signals or data. Additionally or alternatively, in some embodiments, the apparatus 10 can include input and / or output devices (I / O devices).

[0073] In one embodiment, memory 14 may store software modules that provide functionality when executed by processor 12. Such modules may include, for example, an operating system that provides operating system functionality for device 10. Memory may also store one or more functional modules, such as applications or programs, to provide additional functionality to device 10. The components of device 10 may be implemented in hardware, or as any suitable combination of hardware and software.

[0074] According to some embodiments, the processor 12 and the memory 14 may be included in or may form part of processing circuitry or control circuitry.Furthermore, in some embodiments, the transceiver 18 may be included in or may form part of transceiver circuitry.

[0075] As used herein, the term "circuitry" may refer to any portion of a hardware circuit implementation (e.g., analog and / or digital circuitry), a combination of hardware circuitry and software, a combination of analog and / or digital hardware circuitry and software / firmware, a hardware processor(s) (including a digital signal processor) with software that work together to cause a device (e.g., device 10) to perform various functions, and / or operate using software but where the software may not be present when not required for operation. As a further example, as used herein, the term "circuitry" may also encompass a hardware circuit or processor(s) alone, or a portion of a hardware circuit or processor, and its implementation with software and / or firmware. The term circuitry may also encompass, for example, a baseband integrated circuit in a server, cellular network node or device, or other computing or network device.

[0076] As described above, in some embodiments, the device 10 can be a network node or a RAN node, such as a base station, an access point, a Node B, an eNB, a gNB, a LMF, a positioning server, a WLAN access point, etc.

[0077] According to some embodiments, the apparatus 10 may be controlled by the memory 14 and the processor 12 to perform functions associated with any of the embodiments described herein, such as Figures 1 to 4 and Figure 6 Some operations shown or described in .

[0078] For example, in one embodiment, the apparatus 10 may be controlled by the memory 14 and the processor 12 to determine and transmit non-line-of-sight (NLOS) deviation distribution information. The non-line-of-sight (NLOS) deviation distribution information may include at least one statistical parameter associated with at least one non-line-of-sight (NLOS) deviation distribution. In one embodiment, the apparatus 10 may be controlled by the memory 14 and the processor 12 to transmit the non-line-of-sight (NLOS) deviation distribution information.

[0079] Figure 7b An example of an apparatus 20 according to another embodiment is shown. In one embodiment, the apparatus 20 may be a node or element in or associated with a communication network, such as a UE, mobile equipment (ME), a mobile station, a mobile device, a fixed device, an IoT device, or other device. As described herein, a UE may alternatively be referred to as, for example, a mobile station, mobile equipment, a mobile unit, a mobile device, a user equipment, a subscriber station, a wireless terminal, a tablet computer, a smartphone, an IoT device, a sensor, or an NB-IoT device. As an example, the apparatus 20 may be implemented in, for example, a wireless handheld device, a wireless plug-in accessory, or the like.

[0080] In some example embodiments, the apparatus 20 may include one or more processors, one or more computer-readable storage media (e.g., memory, storage, etc.), one or more radio access components (e.g., modems, transceivers, etc.), and / or a user interface. In some embodiments, the apparatus 20 may be configured to operate using one or more radio access technologies, such as GSM, LTE, LTE-A, NR, 5G, WLAN, WiFi, NB-IoT, Bluetooth, NFC, MulteFire, and / or any other radio access technology. It should be noted that persons of ordinary skill in the art will appreciate that the apparatus 20 may include Figure 7b Components or features not shown.

[0081] like Figure 7b As shown in the example of , the device 20 may include or be coupled to a processor 22 for processing information and executing instructions or operations. The processor 22 may be any type of general-purpose or special-purpose processor. In practice, the processor 22 may include one or more of the following: a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), a field programmable gate array (FPGA), an application-specific integrated circuit (ASIC), and a processor based on a multi-core processor architecture. Although Figure 7bA single processor 22 is shown in FIG. 1 , but according to other embodiments, multiple processors may be used. For example, it should be understood that in some embodiments, apparatus 20 may include two or more processors that may form a multiprocessor system that can support multiprocessing (e.g., in which case processor 22 may represent a multiprocessor). In some embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

[0082] Processor 22 may perform functions associated with the operation of apparatus 20, including, as some examples, precoding of antenna gain / phase parameters, encoding and decoding of individual bits forming communication messages, formatting of information, and overall control of apparatus 20, including processes associated with management of communication resources.

[0083] The device 20 may also include or be coupled to a memory 24 (internal or external), which may be coupled to the processor 22 and used to store information and instructions that can be executed by the processor 22. The memory 24 may be one or more memories and of any type suitable for the local application environment and may be implemented using any suitable volatile or non-volatile data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and / or removable memory. For example, the memory 24 may include random access memory (RAM), read-only memory (ROM), static storage devices such as magnetic disks or optical disks, hard disk drives (HDDs), or any other type of non-transitory memory or computer-readable media. The instructions stored in the memory 24 may include program instructions or computer program code that, when executed by the processor 22, enables the device 20 to perform the tasks described herein.

[0084] In one embodiment, the device 20 may also include or be coupled to a (internal or external) drive or port configured to accept and read an external computer-readable storage medium, such as an optical disk, a USB drive, a flash drive, or any other storage medium. For example, the external computer-readable storage medium may store a computer program or software for execution by the processor 22 and / or the device 20.

[0085] In some embodiments, the apparatus 20 may further include or be coupled to one or more antennas 25 for receiving downlink signals and for transmitting from the apparatus 20 via an uplink. The apparatus 20 may further include a transceiver 28 configured to transmit and receive information. The transceiver 28 may further include a radio interface (e.g., a modem) coupled to the antenna 25. The radio interface may correspond to a variety of radio access technologies, including GSM, LTE, LTE-A, 5G, NR, WLAN, NB-IoT, Bluetooth, BT-LE, NFC, RFID, UWB, etc. The radio interface may include other components such as filters, converters (e.g., digital-to-analog converters), symbol demappers, signal shaping components, inverse fast Fourier transform (IFFT) modules, etc., to process symbols carried by the downlink or uplink, such as OFDMA symbols.

[0086] For example, the transceiver 28 can be configured to modulate information onto a carrier waveform for transmission by the antenna(s) 25, and to demodulate information received via the antenna(s) 25 for further processing by other components of the apparatus 20. In other embodiments, the transceiver 28 can directly transmit and receive signals or data. Additionally or alternatively, in some embodiments, the apparatus 20 can include input and / or output devices (I / O devices). In certain embodiments, the apparatus 20 can also include a user interface, such as a graphical user interface or a touch screen.

[0087] In one embodiment, the memory 24 stores software modules that provide functionality when executed by the processor 22. The modules may include, for example, an operating system that provides operating system functionality for the device 20. The memory may also store one or more functional modules, such as applications or programs, to provide additional functionality for the device 20. The components of the device 20 may be implemented in hardware, or as any suitable combination of hardware and software. According to an example embodiment, the device 20 may optionally be configured to communicate with the device 10 via a wireless or wired communication link 70 according to any radio access technology, such as NR.

[0088] According to some embodiments, processor 22 and memory 24 may be included in or may form part of processing circuitry or control circuitry.Furthermore, in some embodiments, transceiver 28 may be included in or may form part of transceiver circuitry.

[0089] As described above, according to some embodiments, the apparatus 20 may be, for example, a UE, a mobile device, a mobile station, a ME, an IoT device, and / or an NB-IoT device. According to some embodiments, the apparatus 20 may be controlled by the memory 24 and the processor 22 to perform functions associated with the example embodiments described herein. For example, in some embodiments, the apparatus 20 may be configured to perform one or more of the processes depicted in any flowchart or signaling diagram described herein, such as in Figures 1 to 5 Those described in .

[0090] For example, in one embodiment, the apparatus 20 may be controlled by the memory 24 and the processor 22 to receive non-line-of-sight (NLOS) deviation distribution information. The non-line-of-sight (NLOS) deviation distribution information may include at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution. In one embodiment, the apparatus 20 may be controlled by the memory 24 and the processor 22 to perform at least one calculation of at least one position using the non-line-of-sight (NLOS) deviation distribution information.

[0091] Thus, certain example embodiments provide several technical improvements, enhancements, and / or advantages over prior art procedures. For example, some of the example embodiments provide benefits related to reduced latency in determining UE location and conserving network resources due to reduced signaling. The use of some example embodiments improves the functionality of communication networks and their nodes, thereby constituting improvements in at least the technical field of UE positioning.

[0092] In some example embodiments, the functionality of any method, process, signaling diagram, algorithm, or flow chart described herein may be implemented by software and / or computer program code or code portions stored in a memory or other computer-readable or tangible medium and executed by a processor.

[0093] In some example embodiments, a device may be included in or associated with at least one software application, module, unit, or entity configured to perform (arithmetic operations), or configured to be executed by at least one operating processor, or a program or portion thereof (including added or updated software routines). A program (also referred to as a program product or computer program, including software routines, applets, and macros) may be stored in any device-readable data storage medium and may include program instructions for performing specific tasks.

[0094] The computer program product may include one or more computer executable components that, when the program is run, are configured to perform some example embodiments. The one or more computer executable components may be at least one software code or code portion. Modifications and configurations required to implement the functionality of the example embodiments may be performed as (multiple) routines, which may be implemented as (multiple) added or updated software routines. In one example, (multiple) software routines may be downloaded to the device.

[0095] By way of example, software or computer program code or code portions may be in source code form, object code form, or some intermediate form, and may be stored on some carrier, distribution medium, or computer-readable medium, which may be any entity or device capable of carrying the program. For example, such carriers may include recording media, computer memory, read-only memory, optoelectronic and / or electrical carrier signals, telecommunications signals, and / or software distribution packages. Depending on the required processing power, the computer program may be executed in a single electronic digital computer or distributed across multiple computers. The computer-readable medium or computer-readable storage medium may be a non-transitory medium.

[0096] In other example embodiments, the functions may be performed by hardware or circuitry included in a device (e.g., device 10 or device 20), such as by using an application specific integrated circuit (ASIC), a programmable gate array (PGA), a field programmable gate array (FPGA), or any other combination of hardware and software. In yet another example embodiment, the functions may be implemented as signals, such as intangible devices that may be carried by electromagnetic signals downloaded from the Internet or other networks.

[0097] According to example embodiments, an apparatus such as a node, a device or a corresponding component may be configured as a circuit system, a computer or a microprocessor, such as a single-chip computer element, or as a chipset, which may include at least a memory for providing storage capacity for (multiple) arithmetic operations and / or an operation processor for performing (multiple) arithmetic operations.

[0098] The example embodiments described herein are equally applicable to both singular and plural implementations, regardless of whether singular or plural language is used in conjunction with describing certain embodiments. For example, an embodiment describing the operation of a single network node is equally applicable to an embodiment including multiple instances of the network node, and vice versa.

[0099] Those skilled in the art will readily appreciate that the example embodiments discussed above can be practiced with operations in a different order and / or with hardware elements in a different configuration than disclosed. Therefore, although some embodiments have been described based on these example embodiments, it will be apparent to those skilled in the art that certain modifications, variations, and alternative constructions will be apparent while remaining within the spirit and scope of the example embodiments.

[0100] According to a first embodiment, a method may include receiving non-line-of-sight (NLOS) deviation distribution information. The non-line-of-sight (NLOS) deviation distribution information may include at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution. The method may include performing at least one calculation of at least one position using the non-line-of-sight (NLOS) deviation distribution information.

[0101] In one variant, the method may include transmitting at least one Minimization of Drive Test (MDT) report including non-line-of-sight (NLOS) deviation information, wherein the non-line-of-sight (NLOS) deviation information includes reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements. In one variant, the reference signal time difference (RSTD) related information may include at least one of at least one reference signal time difference (RSTD) measurement over time or at least one reference signal time difference (RSTD) deviation estimate over time. In one variant, the non-line-of-sight (NLOS) deviation information may also include at least one local non-line-of-sight (NLOS) deviation distribution.

[0102] In one variant, non-line-of-sight (NLOS) deviation information may be included in at least one radio resource control (RRC) message or provided using the Long Term Evolution Positioning Protocol (LPP). In one variant, the method may include determining whether the non-line-of-sight (NLOS) deviation distribution information is outdated based on at least one timer. In one variant, the method may include determining whether the NLOS deviation distribution information is outdated based on local sensor data or measured channel condition changes. In one variant, the method may include providing at least one request for non-line-of-sight (NLOS) deviation distribution information before receiving the non-line-of-sight (NLOS) deviation distribution information. In one variant, providing at least one request for non-line-of-sight (NLOS) deviation distribution information may be based on a user equipment (UE) performing or determining to perform at least one user equipment (UE)-based positioning.

[0103] In one variation, the at least one request may include information identifying at least one of: at least one accuracy threshold associated with performing at least one user equipment (UE)-based positioning, or user information associated with the user equipment (UE). In one variation, providing the at least one request may further include providing the at least one request using the Long Term Evolution Positioning Protocol (LPP). In one variation, providing the at least one request may further include providing the at least one request in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE).

[0104] In one variant, providing at least one request may further include providing at least one request based on receiving at least one indication that non-line-of-sight (NLOS) deviation distribution information is available. In one variant, receiving the non-line-of-sight (NLOS) deviation distribution information may further include receiving the non-line-of-sight (NLOS) deviation distribution information using the Long Term Evolution Positioning Protocol (LPP). In one variant, receiving the non-line-of-sight (NLOS) deviation distribution information may further include receiving the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE). In one variant, the at least one statistical parameter may include at least one of the following: at least one mean of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, at least one standard deviation of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, at least one weight corresponding to a Gaussian distribution included in the at least one mixture of Gaussian distributions.

[0105] In one variant, a non-line-of-sight (NLOS) deviation distribution may include at least one of the following: a number of Gaussian distributions in at least one mixture of Gaussian distributions, at least one mean of at least one Gaussian distribution included in at least one mixture of Gaussian distributions, and at least one variance of at least one Gaussian distribution included in at least one mixture of Gaussian distributions. In one variant, performing the calculation of at least one position may include calculating at least one deviation realization for at least one network node. In one variant, calculating at least one deviation realization may further include calculating at least one deviation realization by subtracting at least one measured flight time from at least one line-of-sight (LOS) flight time, the at least one line-of-sight (LOS) flight time being determined based on at least one distance between the at least one network node and at least one estimated user equipment (UE) position.

[0106] In one variant, the non-line-of-sight (NLOS) deviation distribution information may be associated with information identifying a location of at least one network node. In one variant, at least one value of at least one statistical parameter is a different value than at least one previously received parameter. In one variant, receiving the non-line-of-sight (NLOS) deviation distribution information may further include receiving the non-line-of-sight (NLOS) deviation distribution information based on at least one user associated with a user equipment (UE).

[0107] According to a second embodiment, a method may include determining to transmit non-line-of-sight (NLOS) deviation distribution information. The non-line-of-sight (NLOS) deviation distribution information may include at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution. The method may include transmitting the non-line-of-sight (NLOS) deviation distribution information.

[0108] In one variant, the method may include receiving at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information. In one variant, the non-line-of-sight (NLOS) deviation information may include reference signal time difference (RSTD) related information or time of arrival (TOA) related measurement. In one variant, the reference signal time difference (RSTD) related information may include at least one of at least one reference signal time difference (RSTD) measurement over time or at least one reference signal time difference (RSTD) deviation estimate over time. In one variant, the non-line-of-sight (NLOS) deviation information may also include at least one local non-line-of-sight (NLOS) deviation distribution. In one variant, the non-line-of-sight (NLOS) deviation information may be included in at least one radio resource control (RRC) message, or may be provided using the new radio positioning protocol A (NRPPa), or may be provided using the long term evolution positioning protocol (LPP).

[0109] In one variant, the method may include determining at least one estimate of at least one non-line-of-sight (NLOS) bias distribution and at least one statistical parameter associated with representing the at least one non-line-of-sight (NLOS) bias distribution. In one variant, determining the at least one estimate of the at least one non-line-of-sight (NLOS) bias distribution may be based on at least one of: at least one network-based downlink time difference of arrival (DL-TDOA) positioning related measurement report, or at least one non-line-of-sight (NLOS) bias report collected using at least one minimization of drive tests (MDT) mechanism. In one variant, the at least one network-based downlink time difference of arrival (DL-TDOA) positioning related measurement report may include at least one reference signal time difference (RSTD) related measurement report performed during at least one network-based positioning.

[0110] In one variant, at least one non-line-of-sight (NLOS) deviation report collected using at least one minimization of drive test (MDT) mechanism may include at least one of the following: at least one reference signal time difference (RSTD) related measurement, or at least one reference signal time difference (RSTD) related deviation estimate, or wherein the non-line-of-sight (NLOS) deviation information also includes at least one local non-line-of-sight (NLOS) deviation distribution. In one variant, at least one statistical parameter may include at least one of the following: at least one mean of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, at least one standard deviation of at least one mixture of Gaussian distributions of non-line-of-sight (NLOS) deviations, at least one weight corresponding to a Gaussian distribution included in at least one mixture of Gaussian distributions. In one variant, the method may include transmitting information identifying at least one number of reference signal time difference (RSTD) related measurements, the at least one number of reference signal time difference (RSTD) related measurements used to calculate at least one statistical parameter.

[0111] In one variation, the method may include receiving at least one request for non-line-of-sight (NLOS) deviation distribution information. In one variation, the at least one request may further include information identifying at least one accuracy threshold associated with at least one user equipment (UE)-based positioning, or at least one user associated with the at least one user equipment (UE). In one variation, receiving the at least one request may further include receiving the at least one request using the Long Term Evolution Positioning Protocol (LPP).

[0112] In one variant, receiving the at least one request may further include receiving the at least one request in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE). In one variant, the method may include transmitting at least one indication that non-line-of-sight (NLOS) deviation distribution information is available, and receiving the at least one request may further include receiving the at least one request based on transmitting the at least one indication. In one variant, the at least one non-line-of-sight (NLOS) deviation distribution may include at least one of the following: a number of Gaussian distributions in at least one mixture of Gaussian distributions, at least one mean of at least one Gaussian distribution included in the at least one mixture of Gaussian distributions, and at least one variance of at least one Gaussian distribution included in the at least one mixture of Gaussian distributions.

[0113] In one variant, determining the at least one statistical parameter may be based on at least one probability distribution function (PDF). In one variant, the at least one probability distribution function (PDF) may be based on at least one reference signal time difference (RSTD) measurement and at least one corresponding user equipment (UE) position estimate. In one variant, determining the at least one statistical parameter may further include determining the at least one statistical parameter using at least one curve fitting technique. In one variant, the non-line-of-sight (NLOS) deviation distribution information may be associated with information identifying at least one location of at least one network node.

[0114] In one variant, the method may include determining whether at least one value of at least one statistical parameter has been previously provided, and transmitting non-line-of-sight (NLOS) deviation distribution information may further include transmitting the non-line-of-sight (NLOS) deviation distribution information based on determining whether at least one value of the at least one statistical parameter has been previously provided. In one variant, transmitting the non-line-of-sight (NLOS) deviation distribution information may further include transmitting the non-line-of-sight (NLOS) deviation distribution information using the Long Term Evolution Positioning Protocol (LPP). In one variant, transmitting the non-line-of-sight (NLOS) deviation distribution information may further include transmitting the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE).

[0115] According to a third embodiment, a method may include transmitting at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information. The non-line-of-sight (NLOS) deviation information may include reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements.

[0116] A fourth embodiment may be directed to an apparatus comprising at least one processor and at least one memory comprising computer program code. The at least one memory and the computer program code may be configured to, together with the at least one processor, cause the apparatus to at least perform a method according to the first, second, or third embodiment, or any variants thereof, discussed above.

[0117] A fifth embodiment may be directed to an apparatus which may include circuitry configured to perform a method according to the first, second, or third embodiment, or any variants thereof, discussed above.

[0118] A sixth embodiment may be directed to an apparatus that may include components for performing a method according to the first, second, or third embodiment discussed above, or any variants thereof.

[0119] A seventh embodiment may be directed to a computer-readable medium including program instructions stored thereon for performing at least the method according to the first, second, or third embodiment discussed above, or any variations thereof.

[0120] An eighth embodiment may be directed to a computer program product encoding instructions for performing at least the method according to the first, second, or third embodiment or any variants discussed above.

[0121] Partial Glossary

[0122] BLA: Blind Learning Algorithm

[0123] gNB: 5G base station

[0124] LMF: Location Management Function

[0125] LPP: LTE Positioning Protocol

[0126] MDT: Minimized Drive Test

[0127] NLOS: Non-Line-of-Sight

[0128] NR: New Radio (5G)

[0129] NRPPa: New Radiolocation Protocol A

[0130] OTDOA: Observed Time Difference of Arrival

[0131] PDF: Probability Density Function

[0132] PRS: Positioning Reference Signal

[0133] RSTD: Reference Signal Time Difference

[0134] TA: Timing ahead

[0135] TOA: Time of Arrival

[0136] UE: User Equipment

Claims

1. A method of communication, comprising: transmitting, by a user equipment (UE), at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information, wherein the non-line-of-sight (NLOS) deviation information includes reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements; Transmitting, by the user equipment (UE), a request for non-line-of-sight (NLOS) deviation distribution information; Receiving, by the user equipment (UE), the non-line-of-sight (NLOS) deviation distribution information, wherein the non-line-of-sight (NLOS) deviation distribution information comprises at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution, wherein receiving the non-line-of-sight (NLOS) deviation distribution information comprises: receiving the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE); as well as performing, by the user equipment (UE), at least one calculation of at least one position using the non-line-of-sight (NLOS) deviation distribution information; The at least one statistical parameter comprises the following: at least one mean of a Gaussian mixture of non-line-of-sight (NLOS) deviations, at least one standard deviation of said Gaussian distribution mixture of non-line-of-sight (NLOS) deviations, and At least one weight corresponding to a Gaussian distribution included in the Gaussian distribution mixture.

2. The method according to claim 1, wherein the reference signal time difference (RSTD) related information comprises at least one of the following: at least one Reference Signal Time Difference (RSTD) measurement over time, or at least one Reference Signal Time Difference (RSTD) deviation estimate over time, or The non-line-of-sight (NLOS) deviation information further includes at least one local non-line-of-sight (NLOS) deviation distribution.

3. The method of claim 1, wherein the non-line-of-sight (NLOS) deviation information is included in at least one radio resource control (RRC) message or provided using a long term evolution positioning protocol (LPP).

4. The method according to claim 1, further comprising: Whether the non-line-of-sight (NLOS) deviation distribution information is outdated is determined based on at least one timer.

5. A method of communication, comprising: Receiving, by a network node, at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information, wherein the non-line-of-sight (NLOS) deviation information includes reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements; Receiving, by the network node, a request from a user equipment (UE) for non-line-of-sight (NLOS) deviation distribution information; determining, by a network node, to transmit non-line-of-sight (NLOS) deviation distribution information, wherein the non-line-of-sight (NLOS) deviation distribution information comprises at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution, wherein determining the at least one statistical parameter is based on at least one probability distribution function (PDF), wherein the at least one probability distribution function (PDF) is based on at least one reference signal time difference (RSTD) measurement and at least one corresponding user equipment (UE) position estimate; and Transmitting, by the network node, the non-line-of-sight (NLOS) deviation distribution information to the user equipment (UE), wherein transmitting the non-line-of-sight (NLOS) deviation distribution information comprises: transmitting the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE); The at least one statistical parameter comprises the following: at least one mean of a Gaussian mixture of non-line-of-sight (NLOS) deviations, at least one standard deviation of said Gaussian distribution mixture of non-line-of-sight (NLOS) deviations, and At least one weight corresponding to a Gaussian distribution included in the Gaussian distribution mixture.

6. The method according to claim 5, wherein the reference signal time difference (RSTD) related information comprises at least one of the following: at least one Reference Signal Time Difference (RSTD) measurement over time, or at least one Reference Signal Time Difference (RSTD) deviation estimate over time, or The non-line-of-sight (NLOS) deviation information further includes at least one local non-line-of-sight (NLOS) deviation distribution.

7. The method of claim 5, wherein the non-line-of-sight (NLOS) deviation information is included in at least one radio resource control (RRC) message or provided using New Radio Positioning Protocol A (NRPPa) or provided using Long Term Evolution Positioning Protocol (LPP).

8. The method according to claim 5, further comprising: At least one estimate of at least one non-line-of-sight (NLOS) bias distribution and at least one statistical parameter associated with representing the at least one non-line-of-sight (NLOS) bias distribution are determined.

9. An apparatus for communication, comprising: at least one processor; as well as at least one memory including computer program code, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus to at least: transmitting at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information, wherein the non-line-of-sight (NLOS) deviation information includes reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements; Transmitting a request for non-line-of-sight (NLOS) deviation distribution information; receiving the non-line-of-sight (NLOS) deviation distribution information, wherein the non-line-of-sight (NLOS) deviation distribution information comprises at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution, wherein receiving the non-line-of-sight (NLOS) deviation distribution information comprises: receiving the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE); as well as performing at least one calculation of at least one position using the non-line-of-sight (NLOS) deviation distribution information; The at least one statistical parameter comprises the following: at least one mean of a Gaussian mixture of non-line-of-sight (NLOS) deviations, at least one standard deviation of said Gaussian distribution mixture of non-line-of-sight (NLOS) deviations, and At least one weight corresponding to a Gaussian distribution included in the Gaussian distribution mixture.

10. The apparatus according to claim 9, wherein the reference signal time difference (RSTD) related information comprises at least one of the following: at least one Reference Signal Time Difference (RSTD) measurement over time, or at least one Reference Signal Time Difference (RSTD) deviation estimate over time, or The non-line-of-sight (NLOS) deviation information further includes at least one local non-line-of-sight (NLOS) deviation distribution.

11. The apparatus of claim 9, wherein the non-line-of-sight (NLOS) deviation information is included in at least one radio resource control (RRC) message or provided using a long term evolution positioning protocol (LPP).

12. The apparatus of claim 9, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to at least: Whether the non-line-of-sight (NLOS) deviation distribution information is outdated is determined based on at least one timer.

13. A non-transitory computer-readable medium comprising program instructions for causing an apparatus to at least: transmitting at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information, wherein the non-line-of-sight (NLOS) deviation information includes reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements; Transmitting a request for non-line-of-sight (NLOS) deviation distribution information; receiving the non-line-of-sight (NLOS) deviation distribution information, wherein the non-line-of-sight (NLOS) deviation distribution information includes at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) deviation distribution, wherein receiving the non-line-of-sight (NLOS) deviation distribution information comprises: receiving the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE); as well as performing at least one calculation of at least one position using the non-line-of-sight (NLOS) deviation distribution information; The at least one statistical parameter comprises the following: at least one mean of a Gaussian mixture of non-line-of-sight (NLOS) deviations, at least one standard deviation of said Gaussian distribution mixture of non-line-of-sight (NLOS) deviations, and At least one weight corresponding to a Gaussian distribution included in the Gaussian distribution mixture.

14. The non-transitory computer-readable medium of claim 13, wherein the reference signal time difference (RSTD) related information comprises at least one of the following: at least one Reference Signal Time Difference (RSTD) measurement over time, or at least one Reference Signal Time Difference (RSTD) deviation estimate over time, or The non-line-of-sight (NLOS) deviation information further includes at least one local non-line-of-sight (NLOS) deviation distribution.

15. The non-transitory computer-readable medium of claim 13, wherein the non-line-of-sight (NLOS) deviation information is included in at least one radio resource control (RRC) message or provided using a long term evolution positioning protocol (LPP).

16. The non-transitory computer-readable medium of claim 13, further comprising program instructions for causing the apparatus to at least: Whether the non-line-of-sight (NLOS) deviation distribution information is outdated is determined based on at least one timer.

17. An apparatus for communication, comprising: at least one processor; as well as at least one memory including computer program code, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus to at least: receiving at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information, wherein the non-line-of-sight (NLOS) deviation information includes reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements; receiving a request from a user equipment (UE) for non-line-of-sight (NLOS) deviation distribution information; determining transmission non-line-of-sight (NLOS) bias distribution information, wherein the non-line-of-sight (NLOS) bias distribution information comprises at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) bias distribution, wherein determining the at least one statistical parameter is based on at least one probability distribution function (PDF), wherein the at least one probability distribution function (PDF) is based on at least one reference signal time difference (RSTD) measurement and at least one corresponding user equipment (UE) position estimate; and Transmitting the non-line-of-sight (NLOS) deviation distribution information to the user equipment (UE), wherein transmitting the non-line-of-sight (NLOS) deviation distribution information comprises: transmitting the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE); The at least one statistical parameter comprises the following: at least one mean of a Gaussian mixture of non-line-of-sight (NLOS) deviations, at least one standard deviation of said Gaussian distribution mixture of non-line-of-sight (NLOS) deviations, and At least one weight corresponding to a Gaussian distribution included in the Gaussian distribution mixture.

18. A non-transitory computer-readable medium comprising program instructions for causing an apparatus to at least: receiving at least one minimization of drive test (MDT) report including non-line-of-sight (NLOS) deviation information, wherein the non-line-of-sight (NLOS) deviation information includes reference signal time difference (RSTD) related information or time of arrival (TOA) related measurements; receiving a request from a user equipment (UE) for non-line-of-sight (NLOS) deviation distribution information; determining transmission non-line-of-sight (NLOS) bias distribution information, wherein the non-line-of-sight (NLOS) bias distribution information comprises at least one statistical parameter associated with representing at least one non-line-of-sight (NLOS) bias distribution, wherein determining the at least one statistical parameter is based on at least one probability distribution function (PDF), wherein the at least one probability distribution function (PDF) is based on at least one reference signal time difference (RSTD) measurement and at least one corresponding user equipment (UE) position estimate; and Transmitting the non-line-of-sight (NLOS) deviation distribution information to the user equipment (UE), wherein transmitting the non-line-of-sight (NLOS) deviation distribution information includes: transmitting the non-line-of-sight (NLOS) deviation distribution information in association with at least one downlink time difference of arrival (DL-TDOA) information element (IE); The at least one statistical parameter comprises the following: at least one mean of a Gaussian mixture of non-line-of-sight (NLOS) deviations, at least one standard deviation of said Gaussian distribution mixture of non-line-of-sight (NLOS) deviations, and At least one weight corresponding to a Gaussian distribution included in the Gaussian distribution mixture.

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