Method and apparatus for determining the location of a mobile radio in a radio communications network

Abstract

A method of determining a position of a mobile wireless device in a wireless communication network is disclosed. The method includes measuring, for a plurality of transmission reception point (TRP) clusters associated with the mobile wireless device, a parameter of a first reference signal transmitted between the mobile wireless device and a single TRP in each TRP cluster. The method includes selecting a TRP cluster from the plurality of TRP clusters based on the respective measured parameters of the first reference signal. A position estimate information is determined from a second reference signal transmitted between the mobile wireless device and a plurality of TRPs in the selected TRP cluster. The determined position estimate information is used to determine the position of the mobile wireless device.

Description

TECHNICAL FIELD

[0001] The present application relates to, but is not limited to, a method and apparatus for determining the position of a mobile wireless device in a wireless communication network, and in particular to a method and apparatus for reference signal based mobile wireless device positioning in a Fifth Generation (5G) New Radio (NR) communication network. BACKGROUND

[0002] The Third Generation Partnership Project (3 rd Release 16 involves Long-Term Evolution (LTE) Positioning Functionality, which is extended to accommodate 5G enablers such as wideband signals, low latency, and flexible architecture. For example, wireless devices in 5G NR networks require more accurate positioning methods to meet regulatory and commercial application NR positioning requirements.

[0003] In existing NR reference signal based positioning methods, there are two general positioning methods, i.e. time based positioning methods and angle based positioning methods. Time based positioning methods include Downlink Time Difference of Arrival (DL-TDOA), Uplink Time Difference of Arrival (UL-TDOA), and Multi-cell Round Trip Time (RTT). Angle based positioning methods include Downlink Angle-of-Departure (DL-AOD) and Uplink Angle-of-Arrival (UL-AOA). These methods are to meet the initial 5G positioning requirements.

[0004] In the process of reference signal based positioning, if all Transmission Reception Points (TRPs) are applied in the positioning calculation, it will result in high computational complexity. Since measurement uncertainty is inevitable in any positioning process, the final positioning result will have a position estimation error. Therefore, it is desirable to reduce the computational complexity and / or the position estimation error caused by measurement uncertainty, which is crucial for most positioning systems.

[0005] CN107367277B discloses an indoor location fingerprint positioning method based on twice K-means clustering operation. The fingerprint positioning method comprises: performing a first K-means clustering operation on a location fingerprint library to determine cluster centers; and then performing a second K-means clustering operation on the location fingerprint library to determine final cluster centers. This method requires the establishment of a fingerprint database, and a large amount of measurement data needs to be collected according to the required resolution. It also requires the K-means algorithm to be run twice until all data points in the fingerprint database are divided.

[0006] CN107295636A relates to the field of TDOA positioning technology, and particularly relates to a mobile station positioning device and method based on TDOA positioning. A positioning engine performs data processing on a mobile station, and multiple modes are used to realize positioning of the mobile station. All positioning stations can perform synchronous processing; all positioning stations broadcast position information; all positioning stations receive the position information broadcast by other positioning stations, and upload the relevant time stamp and position information corresponding to the positioning stations to a positioning engine in real time for storage; the positioning engine obtains distance values or distance differences related to the mobile station according to the fixed station position information and the relevant time stamp; and the positioning engine obtains the coordinates of the mobile station by using relevant positioning methods according to the distance values or distance differences and the fixed station position coordinate information. This process requires obtaining position data and time stamps of all TRPs, which involves high computational overhead in an actual positioning system. It establishes a positioning result by using at least three distance difference equations, but does not consider the reliability of the result.

[0007] Therefore, there is a need for an improved method for positioning a mobile wireless device in a 5G NR communication network based on reference signals, preferably with reduced computational complexity.

[0008] Object of the invention

[0009] It is an object of the present invention to mitigate one or more problems associated with known methods of determining a position of a mobile wireless device in a wireless communication network, in particular to mitigate one or more problems associated with known methods of positioning a mobile wireless device in a 5G NR communication network based on reference signals to some extent.

[0010] The above object is achieved by the combination of features of the independent claims; the dependent claims disclose further advantageous embodiments of the invention.

[0011] It is another object of the present invention to provide a node configured to implement an improved method of positioning a mobile wireless device based on reference signals in a 5G NR communication network, preferably with reduced computational complexity, reduced measurement uncertainty and / or reduced estimation error.

[0012] Another object of the present invention is to provide a scheme for an improved method of positioning mobile wireless devices based on reference signals in 5G NR communication networks, preferably reducing location estimation errors caused by measurement uncertainties. Other objects of the invention will become apparent to those skilled in the art from the following description. Therefore, the foregoing statements of objects are not exhaustive and are merely illustrative of some of the many objects of the invention. Summary of the Invention

[0013] In a first principal aspect, the present invention provides a method for determining the location of a mobile wireless device in a wireless communication network. The method includes, for a plurality of Transmitter Receiver Points (TRP) clusters associated with the mobile wireless device, measuring parameters of a first reference signal transmitted between the mobile wireless device and a single TRP in each TRP cluster. The method includes, based on corresponding measured parameters of the first reference signal, selecting one TRP cluster from the plurality of TRP clusters. Determining location estimation information from the second reference signal transmitted between the mobile wireless device and the plurality of TRPs in the selected TRP cluster. The determined location estimation information is used to determine the location of the mobile wireless device.

[0014] The proposed invention can reduce complexity and / or positioning estimation error by considering only the results from TRP with reliable measurements, and can further improve accuracy based on schemes with favorable weight settings.

[0015] In a second principal aspect, the present invention provides a node in a wireless communication system, including a memory storing machine-readable instructions and a processor for executing the machine-readable instructions, such that when the processor executes the machine-readable instructions, it configures the node to implement the steps of the first principal aspect of the present invention.

[0016] In a third principal aspect, the present invention provides a non-transitory computer-readable medium storing machine-readable instructions, wherein, when executed by a processor or controller, the machine-readable instructions configure the processor or controller to implement the steps of the first principal aspect of the present invention.

[0017] This invention does not necessarily disclose all the features necessary to define the invention; the invention may exist in sub-combinations of the disclosed features.

[0018] The features of the invention have been broadly outlined above to provide a better understanding of the detailed description that follows. Other features and advantages of the invention, which form the subject of the claims, will be described below. Those skilled in the art will understand that the disclosed concepts and specific embodiments can be readily used as the basis for modifications or the design of other structures to achieve the same objectives of the invention. Attached Figure Description

[0019] The above and further features of the present application will become apparent from the following description of preferred embodiments, which are provided by way of example only, taken in conjunction with the accompanying drawings, wherein:

[0020] Figure 1 is a known schematic diagram of a 5G NR wireless network architecture supporting positioning;

[0021] Figure 2 shows a known use of Positioning Reference Signals (PRS) and / or Sounding Reference Signals (SRS) to determine the position of a UE in a 5G NR wireless network;

[0022] Figure 3 is a schematic diagram of a network environment in a 5G NR wireless network including multiple TPRs;

[0023] Figure 4 is a schematic block diagram of a node including a Location Management Function (LMF) in a 5G NR wireless network;

[0024] Figure 5 is a flowchart of a positioning method of the present application;

[0025] Figure 6 shows a local area or region consisting of a network environment initialized by multiple TRPs in a 5G NR wireless network;

[0026] Figure 7 shows Figure 6 a network environment wherein multiple TPRs have been divided into clusters;

[0027] Figure 8 shows a method of selecting one of the TPR clusters as a "trusted" cluster in the network environment of Figure 7

[0028] Figure 9 shows Figure 8 a network environment wherein one of the TPR clusters has been selected as a "trusted" cluster; and

[0029] Figure 10 shows a method of using reference signal weighting values in combination with multiple positioning estimates to enhance or improve the final positioning result of a UE. DETAILED DESCRIPTION

[0030] The following description is merely exemplary in nature and is not intended to limit the combinations of necessary features required to practice the application.

[0031] ​Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Moreover, various features are described which can be exhibited by some embodiments and not by others. Similarly, various requirements are described which can be requirements in some embodiments but not in others.

[0032] It should be appreciated that the elements in the figures are illustrated for simplicity and clarity and that in practice there can be numerous other elements, mitigating features, and adaptations that are not shown, described or not described in detail. It is to be understood that the elements illustrated in the figures can be implemented in various forms of hardware, software or combinations thereof. These elements can be implemented in the combination of hardware and software in one or more appropriately programmed general purpose devices, which can include a processor, a memory and input / output interfaces.

[0033] The specification illustrates the principles of the application. It thus should be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the application and are included within its spirit and scope.

[0034] Furthermore, the description herein of the principles, aspects and embodiments of the application, as well as the specific examples thereof, is intended to embrace their structural and functional equivalents. Additionally, it is intended to cover any equivalents whatsoever of structures or functional arrangements described herein, as such equivalents are encompassed by the spirit and scope of the application.

[0035] Thus, for example, it will be appreciated by those skilled in the art that the block diagrams herein represent conceptual views of the systems and devices embodying the principles of the application.

[0036] The functions of the various elements shown in the figures can be provided through the use of dedicated hardware as well as hardware capable of executing software in association with appropriate software. When provided by a processor, the functions can be provided by a single dedicated processor, by a single shared processor, or by a plurality of individual processors, some of which can be shared. Moreover, explicit use of the term "processor" or "controller" should not be construed to refer exclusively to hardware capable of executing software, and can implicitly include, without limitation, digital signal processor ("DSP") hardware, read-only memory ("ROM") for storing software, random access memory ("RAM"), and non-volatile storage.

[0037] In the claims, any means-plus-function clause is intended to cover the structures described herein as performing the recited function and also material elements of which the structure and the function were described. All claims that recite a means-plus-function clause are intended to invoke the provisions of 35 U.S.C. § 112, paragraph 6 under 35 U.S.C. § 101. As such, claims in dependent form that end with a means-plus-function clause are intended to cover, not only the structures described using the words "means", but also structure as well as material indispensable for the proper exercise of the function. Likewise, any claim that recites a business method is intended to invoke the provisions of 35 U.S.C. § 101 under 35 U.S.C. § 101. As such, it is not intended that any claim depend on the patentability of the recited business method under 35 U.S.C. § 101 unless the claim explicitly depen

[0038] 5G NR wireless networks need to support massive connectivity, high capacity, ultra-reliability, and low latency. Such diverse application scenarios require a disruptive approach to enable such 5G NR wireless networks. Multiple TRPs (multi-TRP) are envisioned in 5G NR wireless networks to improve reliability, coverage, and capacity performance through flexible deployment scenarios. For example, to be able to support the exponential growth of mobile data traffic in 5G NR wireless networks and improve coverage, it is expected that mobile wireless devices will access networks composed of multi-TRPs (i.e., macrocells, small cells, pico cells, femto cells, remote radio heads, relay nodes, etc.).

[0039] Figure 1Figure 1 is a schematic diagram of a known 5G NR wireless network architecture 10 that supports positioning. This is described by way of background only. One network entity that contains a location management function (LMF) 12 is a node in this known 5G NR wireless network positioning architecture 10. The LMF 12 receives measurements and assistance information from a next generation radio access network (NG-RAN) 14 and a mobile wireless device 16 (also known as a user equipment (UE) 16) over an NLs interface from an access and mobility management function (AMF) 18 to determine a location of the UE 16. Due to the new next generation interface between the NG-RAN 14 and the core network (not shown), a new NR positioning protocol A (NRPPa) protocol is introduced to carry positioning information between the NG-RAN 14 and the LMF 12 over the next generation control plane interface (NG-C). These new additions in the 5G NR wireless architecture 10 provide a framework for positioning for 5G. The LMF 12 configures the UE 16 using the LTE positioning protocol (LPP) through the AMF 18. The NG RAN 14 configures the UE 16 using the radio resource control (RRC) protocol over the LTE-Uu interface or the NR-Uu interface. The Uu interface is the interface that the UE communicates with the base station, supporting uplink unicast communication from the UE to the base station and downlink unicast communication from the base station to the UE. The NLs interface between the LMF and the AMF is transparent to all UE related, gNB related, and ng-eNB related positioning procedures. It is only used as a transport link for the LTE positioning protocol LPP and the NRPPa.

[0040] To enable more accurate positioning measurements than previously offered by LTE, new reference signals have been added to the 5G NR specification. These signals are the Positioning Reference Signal in the downlink (NR PRS or PRS) and the Sounding Reference Signal (SRS) for positioning in the uplink. The downlink PRS is the main reference signal to support downlink-based positioning methods. Although other signals can be used, the PRS is specifically designed to provide the highest possible accuracy, coverage, and interference avoidance and mitigation. To design an effective PRS, special attention is needed to give the signal a large delay spread range, as it must be received from possibly far away neighboring base stations for position estimation. This is achieved by covering the entire 5G NR bandwidth and transmitting the PRS over multiple symbols, which can be aggregated to accumulate power. The density of subcarriers in one given PRS symbol is referred to as the comb size. There are several configurable comb-based PRS patterns, namely comb-2, 4, 6, and 12, which are suitable for different scenarios, serving different application cases. For example, comb patterns of several base stations can be multiplexed in one time slot time. For comb-N PRS, N symbols can be combined to cover all subcarriers in the frequency domain. Then, each base station (gNB 20) can transmit in different groups of subcarriers to avoid interference. Since several gNBs 20 can transmit at the same time without interfering with each other, this solution is also delay efficient. Furthermore, PRS from one or more gNBs 20 can be muted at a given time according to a muting pattern, further reducing potential interference. For application cases with higher transmission loss (e.g., in macro cell deployments), PRS can also be configured to be repeated to improve reception.

[0041] Figure 2 It is shown that the position of the UE 16 is determined using PRS and / or SRS. The LMF 12 communicates with the TRPs 22 using the NRPPa protocol. The LMF 12 communicates with the UE 16 using the LLP protocol. A plurality of PRSs 24 make up a PRS resource set.

[0042] As Figure 2As shown, the UE 16 receives at least one PRS 24 from one or more TRPs 22 and reports to the LMF 12 any or all of the following UE-based measurement reports for each received PRS for positioning: downlink reference signal reference power (DL RSRP) for each beam of each gNB 20; downlink reference signal time difference (DL RSTD); UE receive-transmit (RX-TX) time difference. The LMF 12 uses some or all of this information to determine or compute the location of the UE 16. The location of the UE 16 can be determined or computed as geographic coordinates.

[0043] Also as Figure 2 As shown, the UE 16 receives at least one PRS 24 or other DL reference signal (DL-DMRS) from one or more TRPs 22 and, in response, transmits SRS 26 or other UL reference signal (UL-DMRS) to the one or more TRPs 22 for each received PRS. In response, each of the one or more TRPs 22 reports to the LMF 12 any or all of the following gNB-based measurement reports for each received SRS for positioning: uplink angle of arrival (UL-AoA); uplink reference signal received power (UL-RSRP); uplink relative time of arrival (UL-RTOA); gNB RX-TX time difference. The LMF 12 uses some or all of this information to determine or compute the location of the UE 16.

[0044] The foregoing approach can result in high computational complexity and high positioning error rates if all TRPs 22 associated with the UE 16 are included in the positioning determination or computation. In addition, high computational complexity and poor communication quality of some TRPs with the UE 16 can result in an undesirable increase in the estimated error of the final location result. This is particularly true in Figure 3 is illustrated by way of example, Figure 3 A plurality of TRPs 22 are shown arranged in an indoor environment 32. One UE 16 is associated with the plurality of TRPs 22 in that the UE 16 receives signals from some or all of the TRPs 22 when the UE 16 is in the environment 32. In such an environment 32, some signals from some TRPs 22 to the UE 16 are strong, e.g., have good signal quality, but many signals from other TRPs 22 have poor signal quality. For ease of reference, the high quality signals are shown in Figure 3The solid arrows in the figure represent signals of good signal quality, while the dashed arrows represent signals of poor signal quality. If UE-based positioning measurement reports and / or gNB-based positioning measurement reports are included in the position determination or calculation of the UE 16 in the environment 32, this can result in a huge error of the resulting position. This is caused, inter alia, by the transmitted positioning measurement reports of many low-quality signals received by the UE 16. Figure 3 The dashed areas 36 in the figure represent TRPs 22 whose signals are received by the UE 16 with high signal quality. Typically, such TRPs 22 are those TRPs 22 that are closest to the UE 16 at the appropriate point in time. However, it is understood that, depending on the arrangement of the environment 32, the TRPs 22 that are closest to the UE 16 do not always provide the best quality signals.

[0045] Figure 3 The example environment 32 in the figure is described as an indoor environment, but this should not be seen as limiting the inventive method described below to use only in indoor environments.

[0046] The present invention recognizes that by considering, using or involving TRPs 22 with reliable measurement data, i.e. TRPs 22 that provide good signal quality signals to the UE 16, a reduction in computational complexity can be achieved without using all TRPs 22 associated with the UE 16. The present invention at least addresses the need of reducing computational complexity and, advantageously, also achieves an increase in accuracy and a reduction in data processing time.

[0047] Figure 4 It is shown that the LMF 12 comprises at least one processor 28 and at least one memory 30. The at least one memory 30 stores machine-readable instructions. The at least one processor 28 executes the machine-readable instructions, thereby configuring the LMF 12 to carry out the steps of the inventive method described below.

[0048] Figure 5 A flowchart of the inventive method 100 is shown. The method comprises three main parts: a first part 110, which involves arranging the TRPs 22 into respective clusters; a second part 120, which involves using only one selected cluster of TRPs from the clusters of TRPs to determine which cluster of TRPs will be used for positioning and calculating the position of the UE 16; and a third part 130, which involves further improving the accuracy of the position result obtained from the second part 120.

[0049] The first part 110 of the method 100 is advantageously able to be implemented offline. The second part 120 and the third part 130 of the present application are implemented online, i.e. in real time. It will be appreciated that the first part 110 of the method 100 can only need to be implemented once for an established environment 32, but if there are any changes to the network environment 32, the first part 110 can be implemented again, either offline or online. The third part 130 of the method 100 is preferably implemented, but it will be appreciated that for some embodiments it can be an optional part of the method 100.

[0050] Figure 6 A local area or region making up the environment 32 is shown at the initialization of the plurality of TRPs 22, and thus before the use of a clustering algorithm, such as a K-means clustering algorithm, to arrange the TRPs 22 into respective clusters to identify or select a subset of TRPs 22 with reliable measurements. The TRPs 22 are able to communicate with any UE 16 entering the environment 32. One UE 16 is shown in the figure for reference.

[0051] The first part 110 of the method 100 of the present application comprises a first step 110A of initializing the TRPs 22, although this step is optional as the TRPs 22 can already be pre-initialized.

[0052] In a next step 110B of the first main part 110 of the method 100, the TRPs 22 are partitioned and clustered using a clustering algorithm. Any suitable clustering algorithm can be used, but a K-means clustering algorithm is preferred.

[0053] Step 110B can comprise determining or selecting a number K of TRP cluster centers in the environment 32, where each TRP cluster center will correspond to a cluster of TRPs 22, and K > 2. The number K can be predefined, or can be calculated depending on the number of TRPs 22 and the size of the environment 32 and / or the signal quality of the TRPs 22. Step 110B comprises determining a distance and / or signal quality between each TRP 22 and each of the K TRP cluster centers. The TRPs 22 are then partitioned or assigned into respective TRP clusters corresponding to the K TRP cluster centers. This can be done by arranging each TRP 22 into the TRP cluster with the minimum distance and / or maximum measured signal strength from that TRP cluster center. In Figure 7 In the example, the respective TRP clusters are denoted as “1”, “2” and “3”, where K is selected as K = 3.

[0054] In a next step 110C of the first main part 110 of the method 100, the method preferably comprises determining or calculating new TRP cluster centers. This can be achieved by calculating an average distance value for each TRP cluster and selecting the TRP 22 that is closest to this average value from the respective TRP cluster center and considering the position of the selected TRP 22 as the new TRP cluster center or randomly selecting one of the TRPs 22 in the cluster as the new TRP cluster center, since all TRPs 22 in one cluster should have the same signal quality level between each other.

[0055] The first main part 110 of the method 100 can comprise repeating steps 110A and 110B until the K cluster centers remain unchanged, which then constitute the final cluster centers and thus the final clusters “1”, “2” and “3”, as shown in Figure 7

[0056] Referring to Figure 8 , the second part 120 of the method 100 comprises a first step 120A of measuring a parameter of a first reference signal transmitted between the UE 16 and a single TRP 22 in each of the TRP clusters “1”, “2” and “3”. The first reference signal can be received at the UE 16, but in some embodiments, the first reference signal of each selected single TRP 22 can be received at the TRP. The first reference signal can comprise a PRS or a SRS. The single TRP 22 determined or selected from each TRP cluster can be the cluster center TRP of the respective TRP cluster or it can be another TRP 22 selected from the TRP cluster. For example, it can comprise the TRP 22 located in the center of its respective cluster “1”, “2” and “3”. In any case, the respective measured parameter of the first reference signal can comprise a signal quality parameter. The signal quality parameter can comprise any of: a signal-to-noise ratio (SNR); a received signal strength indicator (RSSI); a reference signal received power (RSRP); a reference signal received quality (RSRQ) or any other suitable signal quality parameter.

[0057] ​In a next step 120B of the second part 120 of the method 100, the method involves determining or selecting one of the plurality of TRP clusters "1", "2" and "3" as a "trusted" TRP cluster. The determination or selection of the "trusted" TRP cluster is preferably based on the respective measurement parameters of the first reference signals, and preferably causes the "trusted" TRP cluster to be selected as the TRP cluster of the TRP clusters "1", "2" and "3" having the highest, best, largest or optimal value of the measured signal quality parameter. In Figure 8 the example of Fig. 1 1, the TRP cluster denoted as "2" is selected as the "trusted" TRP cluster.

[0058] Referring back to Fig. 1 1, Figure 9 In a next step 120C of the second part 120 of the method 100, the method involves determining position estimate information comprising a plurality of positioning estimate results from the transmission of the second reference signals between the UE 16 and the part but preferably all of the TRPs 22 of the "trusted" TRP cluster "2". This reduces the computational complexity and shortens the data processing time in the positioning method. Figure 9 The TRP clusters "1" and "3" are not shown in Fig. 1 1. The determined plurality of positioning estimate results derived from the second reference signals are combined and used to determine the position of the UE 16. Preferably, a time-based positioning algorithm 120D Figure 5 ) is used to determine the plurality of positioning estimate results from the second reference signals. This can include a multi-cell round trip time or TDOA algorithm. The plurality of positioning estimate results is determined or computed using timing measurements from all of the TRPs 22 of the preferred "trusted" TRP cluster "2". The timing measurements preferably include time delay estimates of the first arriving paths of the received signals from or to each of the TRPs 22 of the "trusted" TRP cluster "2".

[0059] The plurality of positioning estimate results can be obtained from a single TRP 22 of the "trusted" TRP cluster "2", but is preferably obtained from a subset of the TRPs 22. In one embodiment, a subset of 3 TRPs 22 of the "trusted" TRP cluster "2" is used to obtain individual ones of the plurality of positioning estimate results. The plurality of positioning estimate results is combined to obtain a final positioning result for the UE 16.

[0060] In one embodiment, where the second reference signals comprise PRS, the plurality of position estimates can be derived from any or all of the following UE-based positioning measurement reports: downlink PRS reference signal received power (DL PRS-RSRP) per gNB 20 per beam; downlink reference signal time difference (DL RSTD); UE receive-transmit (RX-TX) time difference. The LMF 12 uses some or all of this information to determine or compute the position of the UE 16. The position of the UE 16 can be determined or computed as geographic coordinates.

[0061] In another embodiment, the UE 16 receives PRS from some, but preferably all, of the TRPs 22 of the "trusted" TRP cluster "2" and transmits SRS to one of the TRPs 22 located at a gNB. The TRP 22 reports any or all of the following gNB-based measurement reports for each received SRS to the LMF 12 for positioning: uplink angle of arrival (UL-AoA); uplink SRS reference signal received power (UL SRS-RSRP); UL relative time of arrival (UL-RTOA); gNB RX-TX time difference. The LMF 12 uses some or all of this information to determine or compute a plurality of position estimates of the UE 16 and determines the position of the UE 16 from these results. The position of the UE 16 can be determined or computed as geographic coordinates.

[0062] The third optional part 130 of the method 100 uses weighting values in combination with the plurality of position estimates. However, while the use of weighting values is highly preferred and reduces the risk of unpredictable results in the positioning from low received signal quality signals, it will be appreciated that the use of weighting values is preferred for the implementation of the method 100.

[0063] Referring again to Figure 5 , the third optional part 130 of the method 100 comprises a first step 130A of measuring parameters of the second reference signals transmitted between the UE 16 and the TRPs 22 of the "trusted" TRP cluster "2". The respective measured parameters of the second reference signals preferably comprise signal quality parameters and respective weight values are calculated based on the respective measured signal quality of the second reference signals. The respective weight values are calculated to enhance the influence of the plurality of position estimates of any second reference signal having a high measured signal quality parameter value and to reduce the influence of the plurality of position estimates of any second reference signal having a low measured signal quality value.

[0064] A third optional portion 130 of method 100 includes a second step 130B: combining weight values ​​calculated from the measured parameter values ​​of the second reference signal with the plurality of positioning estimation results to provide weighted location estimation results. The weighted location estimation results are then used to determine the enhanced location of the UE 16. The weighted location estimation results are preferably normalized before being used to determine the location of the UE 16.

[0065] exist Figure 10 In the example, the first estimated location value p1 of UE 16 is derived from a second reference signal transmitted between UE 16 and a first subset of TRP 22 of the "trusted" TRP cluster "2". The second estimated location value p2 of UE 16 is derived from a second reference signal transmitted between UE 16 and a second subset of TRP 22, and so on, up to the last Kth estimated location value p of UE 16. K It is derived from the Kth subset of TRP22. For each subset of the first to Kth subsets of TRP 22, the corresponding weight values ​​w1 to w2 are determined or calculated based on the signal quality of the second reference signal of each subset of the first to Kth subsets of TRP 22. K Transfer their respective weight values ​​w1 to w K Compared with the estimated location values ​​p1 to p K Combined to provide the final positioning result

[0066] In one embodiment, for any three TRPs 22 in the "trusted" TRP cluster "2", the location estimation result p can be obtained by using the TDOA location algorithm. i (i, = 1, 2, ..., K = 3). Then, for each TRP 22 or any three TRP 22, the quality (e.g., RSSI) of the three corresponding reference signals can be measured, and this can then be used to generate the weighting function f(RSSI). i1 RSSI i2 RSSI i3 Then, the weight function is normalized to obtain normalized weight values, and combined with multiple positioning estimation results to obtain the final positioning result. In this embodiment, the weighting function can be expressed as:

[0067] Where K = 3, w i There are three values, i = 1, 2, 3. Therefore, the normalized value of the weight function can be obtained using the following formula:

[0068] w1 = w1 / (w1 + w2 + w3);

[0069] w2 = w2 / (w1 + w2 + w3);

[0070] w3 = w3 / (w1 + w2 + w3).

[0071] Thus and p1 = (x1, y1, z1), p2 = (x2, y2, z2) and p3 = (x3, y3, z3).

[0072] In the method 100 of the present application, the time-based 2D positioning algorithm includes TDOA or RTT.

[0073] For two-dimensional coordinate system: TDOA (at the i-th estimated positioning result):

[0074]

[0075] where p i = (p x,i , p y,i ) T is the coordinate position of the user to be estimated, p i1 = (p x,i1 , p y,i1 ) T , p i2 = (p x,i2 , p y,i2 ) T , p i3 = (p x,i3 , p y,i3 ) T are the coordinate positions of TRP i1 , TRP i2 and TRP i3 respectively; T i1 , T i2 and T i3 are the timing measurement results of TRP i1 , TRP i2 and TRP i3 respectively; c is the speed of light.

[0076] For two-dimensional coordinate system: RTT (at the i-th estimated positioning result):

[0077]

[0078] where RTT i1 , RTT i2 and RTT i3 are the round-trip times of the user to TRP i1 , TRP i2 and TRP i3 respectively; p i= (p x,i , y,i ) T = (p i1 , x,i1 , y,i1 ) T = (p i2 , x,i2 , y,i2 ) T = (p i3 , x,i3 , y,i3 ) T are the coordinate positions of TRP i1 , TRP i2 , and TRP i3 , respectively; c is the speed of light.

[0079] In the method 100 of the present application, the time-based 3D positioning algorithm includes RTT. Thus, for a 3D coordinate system: RTT (at the i-th estimated positioning result)

[0080]

[0081]

[0082] where RTT i1 , RTT i2 , and RTT i3 are the round trip times from the UE 16 to TRP i1 , TRP i2 , and TRP i3 , respectively; p i = (p x,i , p y,i , p z,i ) T is the coordinate position of the user to be estimated; p i1 = (p x,i1 , p y,i1 , p z,i1 ) T , p i2 = (p x,i2 , p y,i2 , p z,i2 ) T , p i3 = (p x,i3 , p y,i3 , p z,i3 ) T are the coordinate positions of TRP i1 , TRP i2 , and TRP i3 , respectively; c is the speed of light.

[0083] The above-described devices can be implemented at least in part using software. Those skilled in the art will appreciate that the above-described devices can be implemented using a general purpose computer device or using custom devices, at least in part.

[0084] Herein, various aspects of the methods and devices described herein can be performed on any device comprising a communication system. Program aspects of the technology can be considered a "product" or "article of manufacture" typically in the form of executable code and / or associated data that is carried or embodied in a type of machine-readable medium. "Storage" type media include any or all of the memory of the mobile stations, computers, processors, or the like, or associated modules thereof, such as various semiconductor memories, tape drives, disk drives and the like, which can provide storage at any time for the software programming. All or portions of the software can at times be communicated by an applicable medium to or from a network connecting computer processors. Such communications, for example, can enable loading of the software from one computer or processor to another. Thus, another type of media that can bear the software elements includes optical, electrical and electromagnetic waves, such as used across physical interfaces, through a physical distribution media and / or through a physical interface that can carry data between a computer processor and a device or between devices. A physical interface can include, for example, physical interface standards set by entities such as IEEE, USB, and the like. The physical interface standards can sometimes be implemented with physical connectors such as electrical connectors, optical connectors, and the like, which connect devices such as hard drive disks, memory devices, and the like, with a computer system. The term "computer readable medium" as used herein is intended to include both application specific computer readable medium and non-specific computer readable medium.

[0085] While the application has been illustrated and described in detail in the drawings and foregoing description, the same is to be considered as illustrative and not restrictive in character, it being understood that only exemplary embodiments have been shown and described and that all changes and modifications that come within the spirit of the application are desired to be protected. It is understood that any feature described herein can be used in any embodiment. Illustrative embodiments do not preclude each other or additional embodiments not described herein. Thus, embodiments also include combinations of one or more of the described illustrative embodiments. Modifications and variations are possible in light of the above teachings. It is, therefore, to be understood that changes can be made in the particular embodiments described and / or shown in the drawings and / or detailed description without departing from the spirit and scope of the application as set forth in the appended claims.

[0086] In the appended claims and in the preceding description of the application, except where the context requires otherwise owing to express language or necessary implication, the word "comprise" or variations such as "comprises an" or "comprising" is used in the sense of "including but not limited to", that is, specifying the presence of the stated features but not precluding the presence or addition of further features in various embodiments of the application.

[0087] It is to be understood that if any prior art publication is referred to herein, such reference does not constitute an admission that the publication forms part of the common general knowledge in the art.

Claims

1. A method of determining a position of a mobile wireless device in a wireless communication network, the method comprising the steps of: arranging transmission reception points (TRPs) associated with the mobile wireless device into a plurality of TRP clusters using a clustering algorithm; measuring parameters of a first reference signal transmitted between the mobile wireless device and a selected or predetermined single TRP in each TRP cluster; selecting a TRP cluster from the plurality of TRP clusters based on respective measured parameters of the first reference signal; determining position estimate information from a second reference signal transmitted between the mobile wireless device and a plurality of TRPs in the selected TRP cluster; measuring parameters of the second reference signal transmitted between the mobile wireless device and the plurality of TRPs in the selected TRP cluster; combining respective weight values calculated from respective values of the measured parameters of the second reference signal with respective position estimate information determined from the second reference signal to provide respective weighted position estimate information; and determining the position of the mobile wireless device based on the respective weighted position estimate information.

2. The method of claim 1, wherein, the selected or predetermined single TRP from each TRP cluster comprises a TRP located at a respective cluster center of the TRP cluster.

3. The method of claim 1, wherein, the position estimate information determined from the second reference signal is determined using a time-based positioning algorithm or other positioning algorithm.

4. The method of claim 1, wherein, the respective measured parameters of the first reference signal comprise a signal quality parameter, and the selected TRP cluster from the plurality of TRP clusters is selected on the basis of the TRP cluster having the highest, best, maximum or optimal signal quality parameter.

5. The method of claim 4, wherein, the signal quality parameter comprises any one of: a signal-to-noise ratio (SNR); a received signal strength indicator (RSSI); a reference signal received power (RSRP); and a reference signal received quality (RSRQ). the position estimate information is determined from the second reference signal transmitted between the mobile wireless device and all TRPs of the selected TRP cluster.

6. The method of claim 1, wherein, the respective measured parameters of the second reference signal comprise a signal quality parameter, and the respective weight values are calculated from respective measured signal quality of the second reference signal.

7. The method of claim 1, wherein, the calculation of the respective weight values is to enhance position estimate information determined from any second reference signal having a high measured signal quality parameter value and to reduce position estimate information determined from any second reference signal having a low measured signal quality parameter value.

8. The method of claim 7, wherein, the weight values calculated from respective values of the measured parameters of the second reference signal are normalized prior to combining the normalized weight values with the respective position estimate information.

9. The method of claim 1, wherein, ​ 10. The method of claim 1, wherein, The step of determining position estimate information from second reference signals transmitted between the mobile wireless device and the plurality of TRPs of the selected cluster of TRPs comprises determining the position of the mobile wireless device based on second reference signals comprising positioning reference signals (PRS) or DL-DMRS; or determining the position of the mobile wireless device based on second reference signals comprising sounding reference signals (SRS) or UL-DMRS; or determining the position of the mobile wireless device based on sounding reference signals (SRS) sent by the mobile wireless device to the node in response to receiving second reference signals comprising positioning reference signals (PRS).

11. The method of claim 1, wherein, The clustering algorithm comprises a K-means clustering algorithm.

12. The method of claim 1, wherein arranging the TRPs associated with the mobile wireless device into a plurality of clusters of TRPs is performed offline.

13. The method of claim 1, wherein, The TRPs are divided into clusters by: (a) determining or selecting K cluster centers of TRPs within a local area or region, where each cluster center of TRPs corresponds to a cluster of TRPs, and K > 2; (b) determining the distance between each TRP and the K cluster centers of TRPs; and (c) dividing the TRPs into respective clusters of TRPs corresponding to the K cluster centers of TRPs by assigning each TRP to the cluster of TRPs to which the closest cluster center of TRPs belongs.

14. The method of claim 13, comprising the step of: (d) calculating an average distance value for each cluster of TRPs, and selecting the TRP closest to the average distance value of the corresponding cluster center of TRPs as a new cluster center of TRPs.

15. The method of claim 14, wherein, Steps (b), (c) and (d) are repeated until the K clusters no longer change, which they are taken as final cluster centers and clusters.

16. The method of claim 1, wherein, The TRPs are divided into clusters by: (a) determining or selecting K cluster centers of TRPs within a local area or region, where each cluster center of TRPs corresponds to a cluster of TRPs, and K > 2; (b) measuring the signal quality between each TRP and the K cluster centers of TRPs; and (c) dividing the TRPs into respective clusters of TRPs corresponding to the K cluster centers of TRPs by assigning each TRP to the cluster of TRPs to which the corresponding cluster center of TRPs belongs according to the measured signal quality.

17. A node in a wireless communication system, comprising a memory storing machine readable instructions and a processor for executing the machine readable instructions, such that when the processor executes the machine readable instructions it configures the node to implement the method of any of claims 1-16.

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