Positioning anomaly discovery mechanism

Abstract

A positioning anomaly discovery mechanism is provided. According to an embodiment of the present disclosure, a positioning unit (PE, Position Element) determines whether positioning degradation is caused by a destructive signal based on a signal profile. In this way, the cause of positioning degradation can be accurately determined.

Description

Technical Field

[0001] Embodiments of the present disclosure generally relate to communication technologies, and more particularly to methods, devices, and computer-readable media for disruptive signal discovery. Background Art

[0002] Positioning is an important enabler for various vertical domains and use cases that the fifth generation (5G) system aims to support. By obtaining knowledge related to the approximate / exact position of a device, the 5G system can enable applications such as location-based services, autonomous driving, and industrial Internet of Things (IoT). Although global navigation satellite system (GNSS) technologies such as the Global Positioning System (GPS) can generally achieve precise positioning, they may not provide sufficiently accurate positioning for indoor scenarios such as factory automation or warehouse management. Therefore, radio access technology (RAT) related positioning methods based on downlink / uplink signals should be studied. Summary of the Invention

[0003] Generally, embodiments of the present disclosure relate to a method and corresponding device for positioning anomaly discovery.

[0004] In a first aspect, a first device is provided. The first device includes at least one processor; and at least one memory including computer program code; the at least one memory and the computer program code are configured to, together with the at least one processor, cause the first device to: determine a set of measured channel parameters at the first device based on a set of reference signals associated with a second device according to a triggered determination related to the positioning performance of the second device; compare the set of measured channel parameters with a set of reference channel parameters, where the set of reference channel parameters is obtained from previous measurements associated with non-abnormal signals; and determine whether abnormal behavior has occurred at the second device based on the comparison.

[0005] In a second aspect, a method is provided. The method includes: determining a set of measured channel parameters at a first device based on a set of reference signals associated with a second device according to a triggered determination related to the positioning performance of the second device; comparing the set of measured channel parameters with a set of reference channel parameters, where the set of reference channel parameters is obtained from previous measurements associated with non-abnormal signals; and determining whether abnormal behavior has occurred at the second device based on the comparison.

[0006] In a third aspect, there is provided a computer-readable medium comprising program instructions for causing a device to perform at least the method according to the first aspect above.

[0007] It should be understood that the Summary of the Invention section is not intended to identify the key or essential features of the embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Through the following description, other features of the present disclosure will become readily understood. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Some example embodiments will now be described with reference to the accompanying drawings, in which:

[0009] Figure 1 A schematic diagram of a communication system according to an embodiment of the present disclosure is illustrated;

[0010] Figure 2 A flowchart of a method according to some embodiments of the present disclosure is illustrated;

[0011] Figure 3 A clean signal envelope and a corrupted signal envelope according to some embodiments of the present disclosure are illustrated;

[0012] Figure 4A A flowchart of an example method for determining the cause of positioning degradation according to some embodiments of the present disclosure is illustrated;

[0013] Figure 4B A flowchart of an example method for determining the cause of positioning degradation according to some embodiments of the present disclosure is illustrated;

[0014] Figure 5 A simplified block diagram of a device suitable for implementing an embodiment of the present disclosure is illustrated; and

[0015] Figure 6 A block diagram of an example computer-readable medium according to some example embodiments of the present disclosure is illustrated.

[0016] Throughout the drawings, the same or similar reference numerals denote the same or similar elements. DETAILED DESCRIPTION

[0017] The principles of the present disclosure will now be described with reference to some example embodiments. It should be understood that the description of these embodiments is only for the purpose of illustration and to assist those skilled in the art in understanding and implementing the present disclosure, and does not represent any limitation on the scope of the present disclosure. The disclosure described herein can be implemented in various other ways than those described below.

[0018] In the following description and claims, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure pertains.

[0019] In this disclosure, references to "one embodiment", "an embodiment", "example embodiment", etc., indicate that the described embodiments may include a particular feature, structure, or characteristic, but not every embodiment must include the particular feature, structure, or characteristic. Further, such phrases are not necessarily referring to the same embodiment. Moreover, when a particular feature, structure, or characteristic is described in connection with an example embodiment, it is within the knowledge of those skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

[0020] It should be understood that although terms such as "first" and "second" may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the example embodiments, a first element may be termed a second element, and similarly, a second element may be termed a first element. As used herein, the term "and / or" includes any and all combinations of one or more of the listed terms.

[0021] The terms used herein are for the purpose of describing particular embodiments only and are not intended to limit the example embodiments. The singular forms "a", "an", and "the" as used herein also include the plural forms unless the context clearly dictates otherwise. Further understood, the terms "comprises", "comprising", "has", "having", "includes", and / or "including" when used herein specify the presence of the stated features, elements, and / or components, etc., but do not preclude the presence or addition of one or more other features, elements, components, and / or combinations thereof.

[0022] As used in this application, the term "circuitry" may refer to one or more or all of the following:

[0023] (a) A pure hardware circuit implementation (such as an implementation using only analog and / or digital circuitry), and

[0024] (b) A combination of hardware circuitry and software, such as, where applicable:

[0025] (i) A combination of (one or more) analog and / or digital hardware circuitry and software / firmware, and

[0026] (ii) (One or more) hardware processors with software (including any portion of (one or more) digital signal processors, software, and (one or more) memories that work together to cause a device, such as a mobile phone or a server, to perform various functions), and

[0027] (c) one or more hardware circuits and / or one or more processors, such as one or more microprocessors or a part of one or more microprocessors, which require software (e.g., firmware) to operate, but the software can be absent when not needed for operation.

[0028] The definition of the circuitry is suitable for all uses of the term in this application, including in any claim. As another example, as used in this application, the term circuitry also encompasses implementations of only hardware circuits or processors (or a plurality of processors) or a part of a hardware circuit or processor and their accompanying software and / or firmware. For example, if applicable to a particular claim element, the term circuitry also encompasses a baseband integrated circuit or a processor integrated circuit for a mobile device, or a similar integrated circuit in a server, a cellular network device, or other computing or network devices.

[0029] As used herein, the term "communication network" refers to a network that follows any suitable communication standard, such as Long Term Evolution (LTE), LTE-Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed Packet Access (HSPA), Narrow Band IoT (NB-IoT), New Radio (NR), etc. In addition, the communication between the terminal device and the network device in the communication network can be performed according to any suitable generation of communication protocol, including but not limited to the first generation (1G), the second generation (2G), 2.5G, 2.75G, the third generation (3G), the fourth generation (4G), 4.5G, the future fifth generation (5G) communication protocol, and / or any other protocol known currently or to be developed in the future. Embodiments of the present disclosure can be applied to various communication systems. Considering the rapid development of communication, of course, there will also be future types of communication technologies and systems that can be used to embody the present disclosure. It should not be regarded as limiting the scope of the present disclosure to the above systems.

[0030] As used herein, the term "network device" refers to a node in a communication network through which a terminal device accesses the network and receives services from the network. Depending on the terminology and technology applied, the network device may refer to a base station (BS), or an access point (AP), for example, Node B (NodeB or NB), evolved Node B (eNodeB or eNB), NR NB (also known as gNB), remote radio unit (RRU), radio head (RH), remote radio head (RRH), relay, low-power node (such as femto, pico).

[0031] The term "terminal device" refers to any terminal device capable of wireless communication. By way of example and not limitation, the terminal device may also be referred to as a communication device, user equipment (UE), subscriber station (SS), portable subscriber station, mobile station (MS), or access terminal (AT). The terminal device may include, but is not limited to, mobile phones, cellular phones, smart phones, voice over IP (VoIP) phones, wireless local loop phones, tablets, wearable terminal devices, personal digital assistants (PDAs), portable computers, desktop computers, image capture terminal devices (such as digital cameras), game terminal devices, music storage and playback devices, in-vehicle wireless terminal devices, wireless endpoints, mobile stations, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), USB dongles, smart devices, wireless customer-premises equipment (CPE), Internet of Things (IoT) devices, watches or other wearable devices, head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in an industrial and / or automation processing chain environment), consumer electronic devices, devices operating on commercial and / or industrial wireless networks, etc. In the following description, the terms "terminal device", "communication device", "terminal", "user equipment", and "UE" may be used interchangeably.

[0032] As described above, radio access technology (RAT) - related positioning methods based on downlink / uplink signals should be studied. The 5G NR positioning integrity issue has been raised and is worthy of investigation. Integrity represents information related to "how much and / or for how long a positioning estimate result can be trusted". Note that the integrity concept is already an important element of traditional GNSS - based positioning methods and is also an important system design aspect for applications that rely on precise positioning (e.g., autonomous driving).

[0033] One of the main threats to NR positioning integrity is attacks (e.g., physical layer attacks, spoofing attacks, malicious attacks, etc.). Attacks occur when another device fully or partially interferes with a positioning session, resulting in a significant degradation of positioning accuracy. In an attack, either the target location is forged or the network is completely unable to obtain the target location. Such attacks are common in GNSS positioning and pose a real threat to NR positioning integrity because they ultimately enable illegal activities to go undetected. For the reasons stated above, an integrity framework should be defined to allow for the identification, detection, and ultimately the elimination of attacks.

[0034] Positioning integrity is threatened by fraudulent or malicious devices that emit disruptive or malicious signals aimed at interfering with ongoing communications and / or positioning sessions. Malicious signals are emitted in different transmission modes and are aimed at forging the image of the wireless channel / signals. In positioning, attacks attempt to block and / or forge positioning signals, preventing the network from obtaining a reliable target location and ultimately compromising positioning integrity. Thus, positioning integrity is compromised when a fraudulent device impersonates one or more transmitters and, by doing so, implicitly forges the location of legitimate positioning transmitters, or deliberately floods a specific part of the spectrum to reduce the signal - to - interference - and - noise ratio (SINR) of the positioning receiver. In either case, the ultimate result is that the target location estimate is compromised and cannot be trusted.

[0035] Although there are some traditional countermeasures against attacks, new solutions are worthy of study. For example, according to some traditional techniques, this problem can be avoided by using opportunistic spectrum usage, i.e., by frequency hopping. In NR positioning, where positioning resources need to be pre - scheduled and allocated among multiple cells to mitigate interference, this method is not an option. According to some other traditional techniques, malicious devices can be located by assuming that prior information about malicious activities can be obtained at specified sensor nodes. This is an unrealistic assumption for NR positioning because 5G networks are currently not equipped with any protocols capable of detecting attacks.

[0036] To address at least a portion of the above problems and other potential problems, a solution for positioning anomaly detection is proposed. According to an embodiment of the present disclosure, a positioning element (PE) determines whether positioning degradation is caused by a disruptive signal based on a signal profile. In this way, the cause of positioning degradation can be accurately determined.

[0037] Figure 1 A schematic diagram of a communication system in which embodiments of the present disclosure can be implemented is shown. The communication system 100, which is part of a communication network, includes a core network device 110, such as a Location Management Function (LMF). The communication system also includes terminal devices 120-1, terminal devices 120-2, terminal devices 120-3, ……, terminal devices 120-N (which can be collectively referred to as “(multiple) terminal devices 120”). The communication system 100 also includes a network device 130. It should be understood that Figure 1 the number of devices shown is for illustration only and does not represent any limitation. The communication system 100 can include any suitable number of devices and cells. In the communication system 100, the devices 120 can transmit data and control information to each other.

[0038] Communication in the communication system 100 may be implemented according to any suitable communication protocol(s), including but not limited to cellular communication protocols such as the first generation (1G), second generation (2G), third generation (3G), fourth generation (4G), and fifth generation (5G), wireless local area network communication protocols such as Institute of Electrical and Electronics Engineers (IEEE) 802.11, and / or any other protocol known currently or to be developed in the future. Additionally, the communication may utilize any suitable wireless communication technology, including but not limited to: Code Divided Multiple Access (CDMA), Frequency Divided Multiple Access (FDMA), Time Divided Multiple Access (TDMA), Frequency Divided Duplexer (FDD), Time Divided Duplexer (TDD), Multiple-Input Multiple-Output (MIMO), Orthogonal Frequency Divided Multiple Access (OFDMA), and / or any other technology known currently or to be developed in the future.

[0039] Example embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Now refer to Figure 2 , Figure 2 FIG. illustrates a flowchart of a method 200 according to an embodiment of the present disclosure. The method 200 may be implemented at a positioning unit. The positioning unit may be a core network device 110. Alternatively, the positioning unit may be a terminal device, such as terminal device 120-1. In other embodiments, the positioning unit may be a network device 130. In some embodiments, the positioning unit may directly participate in a positioning session. Alternatively, the positioning unit may indirectly participate in a positioning session, such as a Positioning Reference Unit (PRU). The term "Positioning Reference Unit (PRU)" as used herein may refer to a device or network node having a reliable position that the LMF may activate as needed to perform specific positioning operations, such as measurement and / or transmission of specific positioning signals.

[0040] In some embodiments, if the positioning unit is the core network device 110, the positioning unit may receive a location request for a second device from a Location Service Client (LCS). The term "LCS client" used herein may refer to a software and / or hardware entity that interacts with an LCS server to obtain location information of one or more mobile stations. In some embodiments, the second device may be a terminal device. For example, the second device may be any one of the terminal devices 120. For illustrative purposes only, hereinafter, the second device may refer to the terminal device 120-2. The LCS client may request location information of the second device within a specified set of parameters (such as Quality of Service (QoS)) from the positioning unit in a Public Land Mobile Network (PLMN). The LCS client may reside in an entity (including a UE) within the PLMN or in an entity external to the PLMN.

[0041] In some embodiments, the positioning unit may determine on its own whether positioning degradation has occurred. For example, if the positioning unit is the network device 130 or the core network device 110, the positioning unit may determine on its own whether positioning degradation has occurred. Alternatively, the positioning unit may receive an indication of positioning degradation from another entity. For example, if the positioning unit is the terminal device 120, the positioning unit may receive such an indication from the core network device 110 or the network device 130.

[0042] At block 210, if positioning degradation of the second device occurs, the positioning unit determines a set of measurement channel parameters based on a set of reference signals associated with the second device. In some embodiments, if the positioning unit can recover the set of reference signals, the positioning unit may determine the set of measurement channel parameters based on the set of reference signals. Alternatively, if the positioning unit cannot recover the set of reference signals, the positioning unit may receive information indicating the set of measurement channel parameters from another entity or device.

[0043] In some embodiments, the positioning unit may calculate the likelihood that the positioning integrity of the second device has been compromised. The positioning unit may collect data from the most recent positioning session of the second device and information about the traffic of the second device in the serving cell from the serving network device of the second device.

[0044] In some embodiments, the set of measured channel parameters may include channel state information of the serving cell and / or neighboring cells of the second device. The term "channel state information (CSI)" as used herein may refer to the channel attributes of a communication link. This information describes how a signal propagates from a transmitter to a receiver and represents, for example, the combined effects of scattering, fading, and power attenuation over distance. Alternatively or additionally, the set of measured channel parameters may include: the co-channel interference level of the serving cell and / or neighboring cells. In some other embodiments, the set of measured channel parameters may include: the cross-link interference level of the serving cell and / or neighboring cells. In some embodiments, the positioning unit may also obtain the mobility profile of the second device. For example, the mobility profile may include the handover history and rate of the second device. The mobility profile may also include other information indicating how the second device moves.

[0045] In some embodiments, the positioning unit may receive data regarding the positioning quality of service (QoS) of the second device. For example, the data may include an estimated position uncertainty value. For example, such an error may be quantified by the position estimation variance or the time of arrival (TOA) / reference signal time difference (RSTD change between two consecutive estimates). For example, the differential TOA between consecutive measurements may be calculated and compared with a threshold relative to the maximum UE speed. In this case, if the differential TOA is greater than a threshold that may be proportional to the device speed, it indicates a potential error.

[0046] In some embodiments, the data regarding positioning QoS may be the link quality of the network device 130. For example, the link quality may include the reference signal received power (RSRP) associated with the network device 130. Alternatively, the link quality may include the signal-to-noise ratio (SNR) associated with the network device 130. In other embodiments, the link quality may include the line-of-sight (LOS) probability. It should be noted that the link quality may be indicated by any suitable parameter.

[0047] Alternatively or additionally, the data regarding the positioning QoS may include the carriers of the network device 130. The data regarding the positioning QoS may also include the bandwidth of the network device 130. In some embodiments, the data regarding the positioning QoS may include: the sample vectors of each transmission reception point of the signal received at the second device. For example, the data regarding the positioning QoS may include: for the received signal after post-processing (e.g., cross-correlation with a known transmission sequence), the K samples (specifically, the K strongest samples: [r l (1),..., r l (k)]) of each TRP l. For example, Figure 3 shows a snapshot of the received signal.

[0048] The set of measured channel parameters may include a set of parameters describing the channel characteristics. For example, the set of measured channel parameters may include one or more of the following: a first parameter describing the channel characteristics in the spatial domain, a second parameter describing the channel characteristics in the time domain, or a third parameter describing the channel characteristics in the frequency domain. For example, the set of measured channel parameters may include a line-of-sight indication. Alternatively, the set of measured channel parameters may include a line-of-sight probability. In some embodiments, the set of measured channel parameters may include the maximum excess delay. In other embodiments, the set of measured channel parameters may include the coherence time. In some other embodiments, the set of measured channel parameters may include the coherence bandwidth.

[0049] In some embodiments, the positioning unit may receive a first channel profile of the second device towards an adjacent cell. For example, the first channel profile may include the carrier frequency of the adjacent cell of the second device. The first channel profile may include the bandwidth.

[0050] Alternatively or additionally, the first channel profile may include the maximum frequency shift. For example, the maximum frequency shift may indicate the Doppler frequency shift. For example, the maximum frequency shift may indicate the total frequency shift, i.e., the sum of the Doppler frequency shift and the carrier frequency offset (CFO). The frequency offset may also include other components.

[0051] In other embodiments, the first channel profile may indicate the serving beam index of an adjacent cell. In some embodiments, the first channel profile may indicate the link quality of an adjacent cell. For example, the link quality may include the reference signal received power (RSRP) associated with the adjacent cell. Alternatively, the link quality may include the signal-to-interference-plus-noise ratio (SINR) associated with the adjacent cell. In other embodiments, the link quality may include the line-of-sight (LOS) probability. It should be noted that the link quality may be indicated by any suitable parameter. The first channel profile may further include a traffic direction indicator. For example, if the traffic direction indicator is "1", it indicates that the traffic is UL traffic. If the traffic direction indicator is "0", it indicates that the traffic is DL traffic.

[0052] Alternatively or additionally, the first channel profile may include the cross-link interference (CLI) level c. CLI may occur when the DL of the second device is interfered by the UL of a UE served by an adjacent cell (this UE may be referred to as an attacker). Note that 5G NR defines a framework for the serving cell to quantify the CLI level and identify the CLI source using specific UL and DL reference signals. The first channel profile may include the total number T of CLI attackers c 。

[0053] In some embodiments, the first channel profile may include a co-channel interference (CCI) indicator C. CCI may occur when the UL of the second device is interfered by the transmissions of an adjacent cell.

[0054] The first channel profile may include map information of the area where the second device is located. For example, the map information may include a channel radio map from ray tracing results. Alternatively, the map information may include the main reflector location.

[0055] In some embodiments, the positioning unit may determine whether the positioning degradation of the second device is caused by interference unrelated to abnormal behavior. For example, the positioning unit may determine the cause of the positioning degradation based on the estimated SINR and the observed SINR. Alternatively, the positioning unit may determine the cause of the positioning degradation by using a processor to distinguish co-channel or cross-channel interference from other types of spectrum blocking.

[0056] For example, if the estimated position uncertainty value is higher than a threshold, the positioning unit may determine the second channel profile of the second device towards the serving cell. In this case, the positioning unit may determine whether the positioning degradation of the second device is caused by interference based on the second channel profile and the mobility profile of the second device.

[0057] Figure 4AA flowchart of an example method for determining the cause of positioning degradation according to some embodiments of the present disclosure is shown.

[0058] At block 410, the positioning unit may check the use of carriers and frequency bands of the TRP (e.g., network device 130). After determining that the carriers and frequency bands are in use, the positioning unit may reconstruct the inter-carrier interference (ICI) / inter-symbol interference (ISI) of the TRP and the CCI and CLI of the TRP. For example, at block 420, the positioning unit may reconstruct the ICI / ISI based on the mobility profile of the second device. By way of example only, the mobility profile of the second device may include a maximum frequency shift.

[0059] At block 430, the positioning unit may reconstruct the CCI and CLI. For example, as described above, the first channel profile may include the CLI level, the CCI indicator, and the total number of CLI attackers. In this case, the positioning unit may reconstruct the CCI and CLI based on the first channel profile.

[0060] At block 440, the positioning unit may reconstruct the signal and interference based on at least one of the ICI / ISI, CCI, CLI, or link quality. For example, the positioning unit may additionally reconstruct the expected SINR level by assuming that the channel coherence time is greater than the time interval between two measurements and knowing the positioning reference signal (PRS) mute mode. The PRS mute mode may indicate a situation where the TRP disrupts its PRS transmission and accordingly scales the SINR value.

[0061] At block 450, the positioning unit may determine whether the SINR matches an approximation. For example, if the SINR matches the SINR reported for the l-th positioning session, the positioning unit may conclude that an attack is unlikely by returning flag = 0. In other words, if the SINR matches the SINR reported for the l-th positioning session, there is no abnormal behavior at the second device. Alternatively, if the SINR does not match the SINR reported for the l-th positioning session, the positioning unit may conclude that an attack is likely by returning flag = 1. In other words, if the SINR does not match the SINR reported for the l-th positioning session, there may be abnormal behavior at the second device.

[0062] In some embodiments, the network device 130 may know the CCI and CLI and have estimated the mobility profile of the second device. In this case, the network device 130 may trigger the positioning unit to skip the determination of the cause including co-channel interference and cross-link interference. In other words, it may be skippedFigure 4A Steps 410 - 450 as shown.

[0063] Return to block 220, where the positioning unit compares the set of measured channel parameters with the set of reference channel parameters. The set of reference channel parameters is obtained from previous measurements associated with the absence of abnormal signals.

[0064] In some embodiments, the positioning unit can compare the set of measured channel parameters with the set of reference channel parameters based on the probability density function associated with the set of reference channel parameters. In some embodiments, the positioning unit can compare the set of measured channel parameters with the set of reference channel parameters based on a test function that tracks the time variation of the set of reference channel parameters. Alternatively, the positioning unit can use a supervised learning block to compare the set of measured channel parameters with the set of reference channel parameters.

[0065] At block 240, the positioning unit determines whether abnormal behavior has occurred at the second device based on the comparison. The term "abnormal behavior" or "anomaly" as used herein can refer to a behavior or pattern that does not conform to normal behavior. In other words, this means that the instantaneous value of the signal measurement (set) does not match the distribution obtained from past measurements associated with non - abnormal positioning events. Anomaly detection can be a step in data mining that is used to identify data points, events, and / or observations that deviate from the normal behavior of a data set.

[0066] In some embodiments, the positioning unit can determine whether abnormal behavior has occurred at the second device by applying a goodness - of - fit test. Alternatively, the positioning unit can determine whether abnormal behavior has occurred at the second device by time - series analysis. In other embodiments, such a determination can be made by applying machine learning.

[0067] As described above, the positioning unit can first determine whether the positioning degradation is caused by a known reason. In this case, if the positioning unit determines that the positioning degradation is not caused by a known reason, the positioning unit can also determine whether abnormal behavior has occurred at the second device. For example, if there is not enough information to match the SINR, the positioning unit can trigger an analysis of the signal profile. Specifically, complex samples r are extracted from the memory within a time window X (where the selected X is less than or equal to the channel coherence time) l , where each instance corresponds to a past positioning session, such as the occurrence of PRS. Alternatively, the positioning unit can directly determine whether abnormal behavior has occurred at the second device without determining the known reason.

[0068] In some embodiments, a probability density function (PDF) related to the measurement of a clean signal can be used. For example, using all the past X - 1 samples labeled as non - abnormal, the signal r can be calculatedl Empirical PDFs of the envelope and the main delays. The term "probability density function (PDF)" as used herein may refer to a statistical expression that defines the probability distribution (likelihood of outcomes) of a discrete random variable, as opposed to a continuous random variable.

[0069] For example, as Figure 4B shown, the input signal can be signals r l (t), ……, r l (t-X). At block 460, the localization unit may perform a time-frequency transform on the signals. At block 462, the localization unit may determine the power extracted for each frequency bin. At block 464, the localization unit may determine the PDF associated with the power of the past X-1 instances. At block 470, the localization unit may perform a first tap delay extraction. At block 475, the localization unit may determine the PDF associated with delay 1 of the past X-1 instances. At block 480, the localization unit may perform a second tap delay extraction. At block 485, the localization unit may determine the PDF associated with delay 2 of the past X-1 instances. At block 490, the localization unit may determine whether the power, delay 1, and delay 2 of each pin at time 1 belong to their respective PDFs. In some embodiments, such determination may be based on goodness-of-fit methods (e.g., Kolmogorov-Smirnov test, L-moment method). If the main delay and the power of each bin match the corresponding empirical distribution, the localization unit may conclude that there is no attack and return flag = 0, which indicates no abnormal behavior at the second device. Alternatively, the localization unit may conclude that an attack is likely to have occurred and return flag = 1, which indicates abnormal behavior at the second device. In some other embodiments, the goodness-of-fit test may return an attack probability p attack ∈ [0, 1], rather than a binary flag, where p attack = 0 indicates that no attack is detected.

[0070] In some embodiments, pdfFit may be replaced by other tests that track the time variation of these parameters over the same observation window X. For example, as Figure 5 shown, if there is a mismatch between the time instance x1 associated with the pattern change of the total power and the time instances x2 associated with the pattern change of each of the selected Y delays (e.g., Y = 2), the localization unit may determine that abnormal behavior has occurred at the second device. In some embodiments, there may be a mismatch between the expected parameters (such as obtained from time series analysis of past observed values) and the instantaneous estimates. For example, delay estimation may be performed on a per-symbol basis (e.g., 6 different ToAs are obtained in comb 6). If the SNR is high, the six ToAs may be relatively close to each other, and any other behavior indicates an attack.

[0071] Alternatively, as described above, the positioning unit can determine whether abnormal behavior occurs at the second device by applying machine learning. For example, a supervised learning block can be implemented as a classifier and thus output a binary flag indicating the presence (1) or absence (0) of an attack; a regressor that outputs an attack probability p attack ∈ [0, 1]. Alternatively, the block can output an indicator {1, 2, …, k, …}, where the index specifies the type of malicious signal (see the types defined below).

[0072] In some other embodiments, the supervised learning block can take the same signal samples as input within the same observation window of duration X and be implemented as, for example, a decision forest, a convolutional neural network, a deep neural network, etc. using a softmax or sigmoid activation function. In this case, to train the network, artificial signal samples r can be generated in a multi-step method in a simulator: (1) generate clean positioning reference signals with various SNR levels, such as [SNRlow, SNRhigh], for example, SNRlow = -13 dB and SNRhigh = 6 dB; (2) generate different types of destructive signals; (3) generate received signals by superimposing the clean signals with the destructive signals, and (4) label the signals obtained in steps (2) and (3).

[0073] In some embodiments, the destructive signals can be at least of the following types: Type 1: Random signals in time and frequency: The malicious device emits random signals at full power on random physical resource blocks (PRBs) (and then remains silent in random PRBs); Type 2: Continuous in time: The malicious device emits random signals at full power at all time instances but in random subcarriers; Type 3: Continuous in frequency: The malicious device emits random signals at full power at all subcarriers but at random time instances; Type 4: Reactive / power boost: The malicious device emits random signals at all time instances on all PRBs, but from one instance to another, the power increases linearly, exponentially, or according to different rules. In some embodiments, the signal pool can be split into at least a training set and a test set, for example, 30% for testing and 70% for training.

[0074] In some embodiments, the received signal can be generated by superimposing the clean signal with one, two, or three of the above malicious signals: Option 1: Clean signal + 1 random malicious signal of any type; Option 2: Clean signal + 2 random malicious signals of any type; Option 3: Clean signal + 3 random malicious signals of any type.

[0075] In some other embodiments, the signals obtained in steps 2 and 3 can be marked with binary tags. For example, the signal in step 2 has an attack flag = 0, and the signal in step 3 has an attack flag = 1.

[0076] In some embodiments, if the positioning unit is the network device 130, the positioning unit can send an indication of the abnormal behavior via the backhaul (e.g., via the NR Positioning Protocol A (NRPPa) interface). In some embodiments, the indication can be a binary flag. For example, if an abnormality is detected, the binary flag can be "1".

[0077] In some embodiments, an apparatus for performing method 200 (e.g., the core network device 110, the terminal device 120, or the network device 130) can include corresponding components for performing the corresponding steps in method 500. These components can be implemented in any suitable manner. For example, it can be implemented by circuitry or software modules.

[0078] In some embodiments, the apparatus includes: components for determining a set of measurement channel parameters at a first device based on a set of reference signals associated with a second device according to a determination of a trigger related to the positioning performance of the second device; components for comparing the set of measurement channel parameters and a set of reference channel parameters, where the set of reference channel parameters is obtained from previous measurements associated with non-abnormal signals; and components for determining whether abnormal behavior occurs at the second device based on the comparison.

[0079] In some embodiments, the apparatus further includes: components for receiving data on the positioning service quality of the second device, where the data includes at least one of the following items: an estimated position uncertainty value, a first carrier frequency of a transmission reception point, a first bandwidth of a transmission reception point, a first link quality between the second device and the transmission reception point, or a sample vector of each transmission reception point of the signal received at the second device.

[0080] In some embodiments, the apparatus further includes: components for receiving a first channel profile of the second device towards an adjacent cell, where the first channel profile includes at least one of the following items: a second carrier frequency of the adjacent cell, a second bandwidth of the adjacent cell, a maximum frequency shift of the adjacent cell, a serving beam index of the adjacent cell, a link quality of the adjacent cell, a traffic direction indicator of the adjacent cell, a cross-link interference level of the adjacent cell, a total number of cross-link interference attackers, a co-channel interference indicator of the adjacent cell, or map information of the area where the second device is located.

[0081] In some embodiments, the apparatus further includes: a component for determining a second channel profile of the second device towards the serving cell based on a determination that an estimated position uncertainty value is higher than a threshold; and a component for determining whether the positioning degradation of the second device is caused by interference unrelated to abnormal behavior based on the second channel profile and the mobility profile of the second device.

[0082] In some embodiments, the component for determining whether the positioning degradation of the second device is caused by interference includes: a component for determining a signal-to-interference-plus-noise ratio (SINR) based on the second channel profile and the mobility profile of the second device; a component for determining that the positioning degradation of the second device is caused by interference based on a determination that the SINR matches a predetermined SINR; or a component for determining that the positioning degradation of the second device is not caused by interference based on a determination that the SINR does not match the predetermined SINR.

[0083] In some embodiments, the component for determining whether abnormal behavior occurs at the second device based on the comparison includes: a component for determining that abnormal behavior occurs at the second device based on a determination that the distribution of the set of measured channel parameters matches the distribution of the set of reference channel parameters; or a component for determining that abnormal behavior does not occur at the second device based on a determination that the distribution of the set of measured channel parameters does not match the distribution of the set of reference channel parameters.

[0084] In some embodiments, the set of measured channel parameters includes at least one of the following: a first parameter describing channel characteristics in the spatial domain, a second parameter describing channel characteristics in the time domain, or a third parameter describing channel characteristics in the frequency domain.

[0085] In some embodiments, the component for comparing the set of measured channel parameters and the set of reference channel parameters includes one of the following: a component for comparing the set of measured channel parameters and the set of reference channel parameters based on a probability density function associated with the set of reference channel parameters; or a component for comparing the set of measured channel parameters and the set of reference channel parameters based on a test function that tracks the time variation of the set of reference channel parameters.

[0086] In some embodiments, the first device includes one of the following: a location management function, a transmission point, a terminal device, or a positioning reference unit.

[0087] Figure 5 is a simplified block diagram of a device 500 suitable for implementing embodiments of the present disclosure. The device 500 can be provided to implement a communication device, for example, as Figure 1The core network device 110, terminal device 120, or network device 130 shown. As shown in the figure, device 500 includes one or more processors 510, one or more memories 520 coupled to the processors 510, and one or more communication modules 540 coupled to the processors 510.

[0088] The communication module 540 is used for two-way communication. The communication module 540 has at least one antenna to facilitate communication. The communication interface can represent any interface required for communication with other network elements.

[0089] The processor 510 can be of any type suitable for the local technical network, and by way of non-limiting example, can include one or more of the following: general-purpose computer, dedicated computer, microprocessor, digital signal processor (DSP), and processors based on multi-core processor architectures. Device 500 can have multiple processors, such as application-specific integrated circuit chips that are subordinate in time to a clock synchronized with the main processor.

[0090] The memory 520 can include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 524, electrically programmable read-only memory (EPROM), flash memory, hard disk, compact disk (CD), digital video disk (DVD), and other magnetic storage and / or optical storage media. Examples of volatile memories include, but are not limited to, random access memory (RAM) 522 and other volatile memories that do not persist during a power outage.

[0091] The computer program 530 includes computer-executable instructions executed by the associated processor 510. The program 530 can be stored in the ROM 524. The processor 510 can execute any suitable actions and processes by loading the program 530 into the RAM 522.

[0092] Embodiments of the present disclosure can be implemented by the program 520 such that the device 500 can execute any process of the present disclosure referred to Figure 2 and Figure 4B discussed. Embodiments of the present disclosure can also be implemented by hardware or by a combination of software and hardware.

[0093] In some example embodiments, program 530 may be tangibly embodied in a computer-readable medium, which may be included in device 500 (such as in memory 520) or in other storage devices accessible by device 500. Device 500 may load program 530 from the computer-readable medium into RAM 522 for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. Figure 6 An example of a computer-readable medium 600 in the form of a CD or DVD is shown. Program 530 is stored on the computer-readable medium.

[0094] In general, the various embodiments of the present disclosure may be implemented using hardware or dedicated circuits, software, logic, or any combination thereof. Some aspects may be implemented using hardware, while other aspects may be implemented using firmware or software that may be executed by a controller, microprocessor, or other computing device. Although the various aspects of the embodiments of the present disclosure are illustrated and described as block diagrams, flowcharts, or using some other graphical representation, it should be understood that, by way of non-limiting example, the blocks, devices, systems, techniques, or methods described herein may be implemented using hardware, software, firmware, dedicated circuits or logic, general-purpose hardware or a controller or other computing device, or some combination thereof.

[0095] The present disclosure also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as the instructions included in program modules, which are executed in a device on a target real or virtual processor to perform the methods described above with reference to Figures 2 - 4B the methods described. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules may be combined or split as needed among program modules. The machine-executable instructions of program modules may be executed within a local or distributed device. In a distributed device, program modules may be located in both local and remote storage media.

[0096] The program code for performing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that the program codes, when executed by the processor or controller, cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0097] In the context of the present disclosure, computer program code or related data can be carried by any suitable carrier so that a device, apparatus or processor can perform the various processes and operations as described above. Examples of carriers include signals, computer-readable media, etc.

[0098] A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a computer-readable storage medium will include an electrical connection having one or more wires, a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0099] Moreover, although operations are described in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all of the illustrated operations be performed to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure, but rather as descriptions of features that may be specific to particular embodiments. Certain features described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, the various features described in the context of a single embodiment may also be implemented separately or in any suitable sub-combination in multiple embodiments.

[0100] Although the present disclosure has been described in language specific to structural features and / or method acts, it is to be understood that the disclosure defined in the appended claims is not necessarily limited to the above specific features or acts. Rather, the above specific features or acts are disclosed as example forms of implementing the claims.

Claims

1. A first device, comprising: at least one processor; and at least one memory, including computer program code; The at least one memory and the computer program code are configured to, together with the at least one processor, cause the first device to: Based on a triggered determination related to the positioning performance of a second device, determine a set of measurement channel parameters based on a set of reference signals associated with the second device; Compare the set of measurement channel parameters with a set of reference channel parameters, where the set of reference channel parameters is obtained from previous measurements associated with non-abnormal signals; and Based on the comparison, determine whether abnormal behavior has occurred at the second device.

2. The first device according to claim 1, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, further cause the first device to: Receive data on the positioning quality of service of the second device, where the data includes at least one of the following items: Estimated position uncertainty value, First carrier frequency of the transmission and reception point, First bandwidth of the transmission and reception point, First link quality between the second device and the transmission and reception point, or Sample vector of each transmission and reception point of the signal received at the second device.

3. The first device according to claim 1, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, further cause the first device to: Receive a first channel profile of the second device towards an adjacent cell, where the first channel profile includes at least one of the following items: Second carrier frequency of the adjacent cell, Second bandwidth of the adjacent cell, Maximum frequency shift of the adjacent cell, Service beam index of the adjacent cell, Link quality of the adjacent cell, Traffic direction indicator of the adjacent cell, Cross-link interference level of the adjacent cell, Total number of cross-link interference attackers, Co-channel interference indicator of the adjacent cell, or Map information of the area where the second device is located.

4. The first device according to claim 1, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, further cause the first device to: Based on a determination that the estimated position uncertainty value is higher than a threshold, determine a second channel profile of the second device towards the serving cell; and Based on the second channel profile and the mobility profile of the second device, determine whether the positioning degradation of the second device is caused by interference unrelated to the abnormal behavior.

5. The first device according to claim 4, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, cause the first device to determine whether the positioning degradation of the second device is caused by the interference by: Determine the signal-to-interference-plus-noise ratio (SINR) based on the second channel profile and the mobility profile of the second device; Based on the determination that the SINR matches the predetermined SINR, determine that the positioning degradation of the second device is caused by the interference; or Based on the determination that the SINR does not match the predetermined SINR, determine that the positioning degradation of the second device is not caused by the interference.

6. The first device according to claim 1, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, cause the first device to determine whether the abnormal behavior occurs at the second device based on the comparison by: Based on the determination that the distribution of the set of measured channel parameters matches the distribution of the set of reference channel parameters, determine that the abnormal behavior occurs at the second device; or Based on the determination that the distribution of the set of measured channel parameters does not match the distribution of the set of reference channel parameters, determine that the abnormal behavior does not occur at the second device.

7. The first device according to claim 1, wherein the set of measured channel parameters includes at least one of the following: A first parameter describing channel characteristics in the spatial domain, A second parameter describing channel characteristics in the time domain, or A third parameter describing channel characteristics in the frequency domain.

8. The first device according to claim 1, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, cause the first device to compare the set of measured channel parameters and the set of reference channel parameters by one of the following: Based on the probability density function associated with the set of reference channel parameters, compare the set of measured channel parameters and the set of reference channel parameters; or Based on a test function that tracks the time variation of the set of reference channel parameters, compare the set of measured channel parameters and the set of reference channel parameters.

9. The first device according to any one of claims 1 to 8, wherein the first device includes one of the following: A location management function, A transmission point, A terminal device, or A positioning reference unit.

10. A method, comprising: Based on the determination of a trigger related to the positioning performance of a second device, determine a set of measured channel parameters at a first device based on a set of reference signals associated with the second device; Compare the set of measured channel parameters and the set of reference channel parameters, wherein the set of reference channel parameters is obtained from previous measurements associated with non-abnormal signals; and Based on the comparison, determine whether abnormal behavior occurs at the second device.

11. The method according to claim 10, further comprising: Receiving data on the quality of positioning service of the second device, wherein the data includes at least one of the following: An estimated position uncertainty value, The first carrier frequency of the transmission and reception point, The first bandwidth of the transmission and reception point, The first link quality between the second device and the transmission and reception point, or The sample vector of each transmission and reception point of the signal received at the second device.

12. The method according to claim 10, further comprising: Receive a first channel profile of the second device towards an adjacent cell, where the first channel profile includes at least one of the following: A second carrier frequency of the adjacent cell, A second bandwidth of the adjacent cell, A maximum frequency shift of the adjacent cell, A serving beam index of the adjacent cell, A link quality of the adjacent cell, A traffic direction indicator of the adjacent cell, A cross-link interference level of the adjacent cell, A total number of cross-link interference attackers, A co-channel interference indicator of the adjacent cell, or Map information of an area where the second device is located.

13. The method according to claim 10, further comprising: Determine a second channel profile of the second device towards a serving cell according to a determination that an estimated position uncertainty value is higher than a threshold; And Based on the second channel profile and a mobility profile of the second device, determine whether the positioning degradation of the second device is caused by interference unrelated to the abnormal behavior.

14. The method according to claim 13, wherein determining whether the positioning degradation of the second device is caused by the interference includes: Determine a signal-to-interference-plus-noise ratio (SINR) based on the second channel profile and the mobility profile of the second device; According to a determination that the SINR matches a predetermined SINR, determine that the positioning degradation of the second device is caused by the interference; or According to a determination that the SINR does not match a predetermined SINR, determine that the positioning degradation of the second device is not caused by the interference.

15. The method according to claim 10, wherein determining whether the abnormal behavior occurs at the second device based on the comparison includes: According to a determination that a distribution of the set of measured channel parameters matches a distribution of the set of reference channel parameters, determine that the abnormal behavior occurs at the second device; Or According to a determination that a distribution of the set of measured channel parameters does not match a distribution of the set of reference channel parameters, determine that the abnormal behavior does not occur at the second device.

16. The method according to claim 10, wherein the set of measured channel parameters includes at least one of the following items: A first parameter describing channel characteristics in the spatial domain, A second parameter describing channel characteristics in the time domain, or A third parameter describing channel characteristics in the frequency domain.

17. The method according to claim 10, wherein comparing the set of measured channel parameters with the set of reference channel parameters includes one of the following items: Based on a probability density function associated with the set of reference channel parameters, compare the set of measured channel parameters and the set of reference channel parameters; or Based on a test function tracking a time variation of the set of reference channel parameters, compare the set of measured channel parameters and the set of reference channel parameters.

18. The method according to any one of claims 10 to 17, wherein the first device includes one of the following items: A location management function, A transmission point, A terminal device, or A positioning reference unit.

19. A computer-readable storage medium, including program instructions stored thereon, which, when executed by a device, cause the device to perform the method according to any one of claims 10 to 18.

20. A device, including components for performing the method according to any one of claims 10 to 18.

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