Communication method and related apparatus

Abstract

The present application provides a communication method and a related apparatus, which can protect user privacy in sensing scenarios. The method comprises: a first apparatus and a second apparatus determine the type of a target scrambling function corresponding to a first sensing scenario and parameters comprised in the target scrambling function; the first apparatus generates a first signal and a second signal, the second signal being obtained by performing phase adjustment on the first signal on the basis of the target scrambling function, and the target scrambling function being determined on the basis of the type of the target scrambling function and the parameters; the first apparatus outputs the first signal and the second signal, sends the first signal by means of a first antenna corresponding to the first apparatus, and sends the second signal by means of a second antenna corresponding to the first apparatus; and correspondingly, the second apparatus receives the signals from the first apparatus, and obtains a sensing result on the basis of the received signals and the target scrambling function.

Description

Communication method and related device

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on November 29, 2023, with application number 202311626414.0 and application name “Communication Methods and Related Devices”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of communication technology, and in particular to a communication method and related devices. Background Art

[0003] Perception involves measuring the channel using wireless signals and inferring information about the environment or objects within it based on the measurement results (e.g., channel state information (CSI) or channel impulse response (CIR)). The measurement signals typically used for perception in wireless systems have a public signal structure, potentially exposing privacy. For example, unauthorized users can eavesdrop on and measure these measurement signals to perceive the physical environment and infer user location and behavioral characteristics.

[0004] Therefore, there is an urgent need for a perception protection technology to protect user privacy.

[0005] Summary of the Invention

[0006] The present application provides a communication method and related devices that can protect user privacy in perception scenarios.

[0007] In a first aspect, the present application provides a communication method that can be applied to a first device. For example, the first device can be a terminal or a network device, or a component configured in the terminal or network device (such as a chip, a chip system, or a circuit, etc.), or a logic module or software that can implement all or part of the functions of the terminal or network device, which is not limited by the present application.

[0008] The method includes: determining the type of target scrambling function corresponding to a first perception scene and the parameters included in the target scrambling function; generating a first signal and a second signal, wherein the second signal is obtained by phase-adjusting the first signal based on the target scrambling function, and the target scrambling function is determined based on the type of the target scrambling function and the parameters; outputting the first signal and the second signal, wherein the first signal is sent through a first antenna corresponding to the first device, and the second signal is sent through a second antenna corresponding to the first device.

[0009] In one possible implementation, the above-mentioned first perception scene is one of the following multiple perception scenes: physiological feature detection scene, biological presence detection scene and activity recognition scene; wherein, the physiological feature detection scene is a scene for detecting physiological feature parameters, the biological presence detection scene is a scene for detecting whether there are biological organisms in the environment, and the activity recognition scene is a scene for detecting biological activities.

[0010] In one possible implementation, the type of the target scrambling function is one of a variety of random functions: a sine function, a linear combination of sine functions, a double sine function, a linear combination of two sets of sine functions, or a function obtained by interpolating S random numbers based on an interpolation algorithm, where S is an integer greater than 1.

[0011] Exemplarily, the ratio of the first signal to the second signal is equal to e jθ(t) is proportional to, or the ratio of the first signal to the second signal is proportional to e jθ(t) Inversely proportional to θ(t), θ(t) is the target scrambling function.

[0012] Based on the above technical content, the first device predetermines the target scrambling function corresponding to the scene to be perceived by the type of scrambling function corresponding to the scene to be perceived and the parameters included in the scrambling function, and then sends multiple signals processed by the target scrambling function to the second device, so that the receiving end obtains the perception result based on the received signal and the determined target scrambling function. Since the type of scrambling function and the parameters included in the scrambling function are only shared by the authorized sender and receiver (for example, the first device and the second device in this application), only the authorized sender and receiver can obtain accurate perception results, while unauthorized devices cannot make accurate estimates due to the unknown scrambling function, so they cannot obtain relevant information about the user, thereby protecting user privacy.

[0013] In a second aspect, the present application provides a communication method that can be applied to a second device. For example, the second device can be a terminal or network device, or a component configured in the terminal or network device (such as a chip, chip system, or circuit, etc.), or a logic module or software that can implement all or part of the terminal or network device functions, which is not limited by the present application.

[0014] The method includes: determining the type of a target scrambling function corresponding to a first perception scene and the parameters included in the target scrambling function; obtaining a perception result based on the target scrambling function and a signal received from a first device, wherein the target scrambling function is determined based on the type of the target scrambling function and the parameters.

[0015] Based on the above technical content, the second device predetermines the target scrambling function corresponding to the scene to be perceived by the type of scrambling function corresponding to the scene to be perceived and the parameters included in the scrambling function, so that after receiving multiple signals from the first device after being processed by the target scrambling function, the second device can obtain the perception result based on the received signals and the predetermined target scrambling function. Since the type of scrambling function and the parameters included in the scrambling function are only shared by the authorized sender and receiver (for example, the first device and the second device in this application), only the authorized sender and receiver can obtain accurate perception results, while unauthorized devices cannot make accurate estimates due to the unknown scrambling function, and thus cannot obtain relevant information about the user, thereby protecting the user's privacy.

[0016] For the description of the first perception scenario and the type of target scrambling function, please refer to the description of the first aspect and will not be repeated here.

[0017] Exemplarily, the above-mentioned obtaining of the perception result based on the target scrambling function and the signal received from the first device includes: performing channel estimation based on the target scrambling function and the signal received from the first device to obtain channel state information; and obtaining the perception result based on the channel state information.

[0018] For example, the first perception scenario is a physiological characteristic detection scenario, and the above perception results may be physiological characteristic parameters such as heart rate or breathing rate; the first perception scenario is a biological presence detection scenario, and the above perception results may be the presence of biological organisms in the environment or the absence of biological organisms in the environment; the first perception scenario is an activity recognition scenario, and the above perception results may be the activity types of biological organisms in the environment.

[0019] In combination with the first aspect (or the second aspect), in some possible implementations, after determining the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function, the method also includes: sending first information, which indicates the type of the target scrambling function.

[0020] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: receiving first information, where the first information indicates a type of the target scrambling function.

[0021] For the description of the target scrambling function, please refer to the description of the first aspect above and will not be repeated here.

[0022] In combination with the first aspect (or the second aspect), in some possible implementations, before determining the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function, the method also includes: receiving first information indicating the type of the target scrambling function.

[0023] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: sending first information, where the first information indicates the type of the target scrambling function.

[0024] Based on this method, the first device and the second device can obtain the type of the target scrambling function corresponding to the first perception scenario, and thus determine the target scrambling function based on the obtained type of the target scrambling function and the parameters included in the target scrambling function to achieve channel estimation and perception.

[0025] In combination with the first aspect (or the second aspect), in some possible implementations, after determining the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function, the method also includes: sending second information, which indicates the parameters included in the target scrambling function.

[0026] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: receiving second information, where the second information indicates parameters included in the target scrambling function.

[0027] In combination with the first aspect (or the second aspect), in some possible implementations, before determining the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function, the method also includes: receiving second information, which indicates the parameters included in the target scrambling function.

[0028] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: sending second information, where the second information indicates parameters included in the target scrambling function.

[0029] Based on this method, the first device and the second device can obtain the parameters included in the target scrambling function corresponding to the first perception scenario, and thus determine the target scrambling function based on the type of the obtained target scrambling function and the parameters included in the target scrambling function to achieve channel estimation and perception.

[0030] In combination with the first aspect (or the second aspect), in some possible implementations, after determining the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function, the method also includes: sending third information, which indicates the generation algorithm of the parameters.

[0031] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: receiving third information, where the third information indicates an algorithm for generating the parameters.

[0032] In combination with the first aspect (or the second aspect), in some possible implementations, before determining the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function, the method also includes: receiving third information, which indicates an algorithm for generating the parameters.

[0033] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: sending third information, where the third information indicates an algorithm for generating the parameters.

[0034] Similar to sending the second information, based on this method, the first device and the second device can obtain the generation algorithm of the parameters included in the target scrambling function corresponding to the first perception scenario, and then determine the parameters included in the target scrambling function based on the obtained parameter generation algorithm, and then determine the target scrambling function based on the type of the target scrambling function and the parameters included in the target scrambling function to achieve channel estimation and perception.

[0035] Optionally, before determining the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function, the method further includes: determining that the scene to be perceived is the first perception scene.

[0036] In combination with the first aspect (or the second aspect), in some possible implementations, after determining that the scene to be perceived is the first perception scene, the method also includes: sending fourth information, which indicates that the scene to be perceived is the first perception scene.

[0037] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: receiving fourth information, where the fourth information indicates that the scene to be perceived is a first-field perception scene.

[0038] In combination with the first aspect (or the second aspect), in some possible implementations, before determining that the scene to be perceived is a first perception scene, the method also includes: receiving fourth information, which indicates that the scene to be perceived is a first perception scene.

[0039] Accordingly, in combination with the second aspect (or the first aspect), in some possible implementations, the method further includes: sending fourth information, where the fourth information indicates that the scene to be perceived is a first perception scene.

[0040] Based on this method, the fourth information is exchanged between the first device and the second device, so that the device for providing perception services can determine the current perception scenario, and then determine the corresponding perception algorithm based on the acquired perception scenario, thereby realizing perception.

[0041] The methods of the first and second aspects include one or more of the following possible implementations:

[0042] In some possible implementations, the first perception scenario is the physiological feature detection scenario, the function type of the target scrambling function is the sine function, the parameters include the frequency of the sine function, and the frequency of the sine function is within the frequency range corresponding to the physiological activity.

[0043] Optionally, the parameters further include the amplitude and / or phase of the sine function.

[0044] Exemplarily, the frequency range corresponding to the physiological activity may include a frequency range corresponding to breathing, a frequency range corresponding to heartbeat, or a frequency range corresponding to other physiological activities.

[0045] Exemplarily, when the type of the target scrambling function is a sine function, the target scrambling function θ(t) satisfies:

[0046] Among them, F q ∈[F l1 ,F l2 ],[F l1 ,F l2 ] represents the frequency range corresponding to physiological activities, F q For [F l1 ,F l2 ] frequency value randomly selected within the frequency range, is a real number.

[0047] Alternatively, the amplitude A may be equal to π.

[0048] Optionally, the initial phase φ may be equal to 0.

[0049] When A=π, φ=0, the target scrambling function θ(t) satisfies: θ(t)=πcos2πF q t.

[0050] In some possible implementations, the first perception scenario is the physiological feature detection scenario, the type of the target scrambling function is the linear combination of sinusoidal functions, the parameters include the frequency of each sinusoidal function in the linear combination of sinusoidal functions and the number of sinusoidal functions included in the linear combination of sinusoidal functions, and the frequency of each sinusoidal function is within the frequency range corresponding to the physiological activity.

[0051] Optionally, the parameters further include the amplitude and / or phase of at least one sine function in the linear combination of sine functions.

[0052] It can be understood that among the multiple sine functions in the linear combination of sine functions, the frequencies of any two sine functions can be the same or different, the amplitudes of any two sine functions can be the same or different, or the phases of any two sine functions can be the same or different.

[0053] For the description of the frequency range corresponding to physiological activities, please refer to the previous description and will not be repeated here.

[0054] Exemplarily, when the type of the target scrambling function is a linear combination of sine functions, the target scrambling function θ(t) satisfies:

[0055] Among them, F qi ∈[F l1 ,F l2 ],[F l1 ,F l2 ] represents the frequency range corresponding to physiological activities, F qi For [F l1 ,F l2 ] frequency value randomly selected within the frequency range, is a non-zero real number, n a is an integer greater than 1, is a real number.

[0056] It is understandable that the above n a The initial phases of any two sine functions in the sine functions can be the same or different.

[0057] For example, n a When the initial phases of all sine functions are 0, the target scrambling function θ(t) satisfies:

[0058] It can also be understood that the above n a The amplitudes of any two of the sine functions can be the same or different.

[0059] In some possible implementations, the first perception scenario is the biological presence detection scenario, the type of the target scrambling function is the double sine function, and the double sine function includes a first sine function and a second sine function; the parameters include the frequency of the first sine function and the frequency of the second sine function, the frequency of the first sine function is within the frequency range corresponding to breathing, and the frequency of the second sine function is within the frequency range corresponding to heartbeat.

[0060] The double sine function is a linear combination of two sine functions of different frequencies, and the frequencies of the two sine functions belong to the frequency range corresponding to different physiological characteristics.

[0061] Optionally, the parameters further include one or more of the following: the amplitude of the first sine function, the phase of the first sine function, the amplitude of the second sine function, or the phase of the second sine function.

[0062] It is understood that if the biological presence detection scenario also includes the detection of other physiological characteristics, the dual-sine function can be replaced with a triple-sine function, which includes the first sine function, the second sine function, and the third sine function, and the frequency of the third sine function is within the frequency range corresponding to the other physiological characteristics. The third sine function can include at least one sine function, and the frequency of at least one sine function is within the frequency range corresponding to different physiological characteristics.

[0063] Exemplarily, when the target scrambling is a double sine function, the target scrambling function θ(t) satisfies:

[0064] Among them, F a1 ∈[F m1 ,F m2 ],[F m1 ,F m2 ] represents the frequency range corresponding to breathing, F a1 For [F m1 ,F m2 ] is a frequency value randomly selected within the frequency range, F b1 ∈[F n1 ,F n2 ],[F n1 ,F n2 ] represents the frequency range corresponding to the heartbeat, F b1 For [F n1 ,F n2 ] frequency value randomly selected within the frequency range, and are all non-zero real numbers, and All are real numbers.

[0065] It can be understood that in the dual sine function, the initial phases of the two sine functions can be the same or different.

[0066] Exemplarily, when the initial phases of the two sine functions in the above double sine function are both 0, the target scrambling function θ(t) satisfies:

[0067] It can also be understood that in the dual sine function, the amplitudes of the two sine functions can be the same or different.

[0068] In some possible implementations, the first perception scenario is the biological presence detection scenario, the type of the target scrambling function is a linear combination of the two groups of sinusoidal functions, the parameters include the frequency of each sinusoidal function in the linear combination of the two groups of sinusoidal functions, and the number of sinusoidal functions included in each group of sinusoidal functions; the linear combination of the two groups of sinusoidal functions includes a first group of sinusoidal functions and a second group of sinusoidal functions, the frequency of each sinusoidal function in the first group of sinusoidal functions is within the frequency range corresponding to breathing, and the frequency of each sinusoidal function in the second group of sinusoidal functions is within the frequency range corresponding to heartbeat.

[0069] Optionally, the parameters further include the amplitude and / or phase of each sine function.

[0070] Similar to the double sine function described above, the linear combination of these two sine functions is a linear combination of two sine functions within different frequency ranges. Similarly, if the biological presence detection scenario also includes the detection of other physiological characteristics, the two sine functions can be expanded to a linear combination of more sine functions, where the frequencies of different sine functions in these linear combinations fall within the frequency ranges corresponding to different physiological characteristics.

[0071] Exemplarily, when the target scrambling function is a linear combination of the two groups of sine functions, the target scrambling function θ(t) satisfies:

[0072] Among them, F ai ∈[F m1 ,F m2 ],[F m1 ,F m2 ] represents the frequency range corresponding to breathing, F ai For [F m1 ,F m2 ] is a frequency value randomly selected from the bi ∈[F n1 ,F n2 ],[F n1 ,F n2 ] represents the frequency range corresponding to the heartbeat, F bi For [F n1 ,F n2 ] frequency value randomly selected within the frequency range, and are all non-zero real numbers, n a and n b are all integers greater than 1, and All are real numbers.

[0073] It can be understood that the linear combination of the above two groups of sine functions includes (na +n b ) sine functions, the initial phases of any two sine functions can be the same or different.

[0074] For example, in (n a +n b ) When the initial phases of the sine functions are all 0, the target scrambling function θ(t) satisfies:

[0075] It can also be understood that the linear combination of the above two groups of sine functions includes (n a +n b ) sine functions, the amplitudes of any two sine functions can be the same or different.

[0076] In some possible implementations, the first perception scenario is the activity recognition scenario, the type of the target scrambling function is a function obtained by interpolating S random numbers based on an interpolation algorithm, the parameters are the S random numbers, and S is an integer greater than 1.

[0077] The interpolation algorithm includes a cubic Hermite interpolation algorithm or other types of interpolation algorithms, which are not limited in this application.

[0078] Exemplarily, the S satisfies:

[0079] Among them, F max is the maximum value of the maximum Doppler frequency shift caused by various actions to be identified, F max The value of is determined by the sensing scenario and carrier frequency, M is the number of sensing rounds, Δt is the duration of each sensing round, α is a number greater than 0 and less than 1, and M is an integer greater than 1.

[0080] In some possible implementations, the method further includes: obtaining the target scrambling function based on the type of the target scrambling function and the parameters.

[0081] Exemplarily, the functional form of the target scrambling function can be obtained based on the type of the target scrambling function; based on the parameters, other parameters in the functional form except the independent variable and the dependent variable can be determined, thereby obtaining the target scrambling function.

[0082] In a third aspect, the present application provides a communication device, which can be used for the first device of the first aspect, or the communication device can be used for the second device of the second aspect, and the communication device includes a module or unit for implementing the method of any of the above aspects and any possible implementation of any of the aspects. The module or unit can be a hardware circuit, or software, or a combination of hardware circuit and software. For example, each module or unit can implement the corresponding function by executing a computer program.

[0083] In a fourth aspect, the present application provides a communication device, comprising a processor, wherein the processor is configured to execute the method described in any of the above aspects and any possible implementation of any of the aspects.

[0084] The apparatus may further include a memory for storing instructions and data. The memory is coupled to the processor, and when the processor executes the instructions stored in the memory, the method described in the above aspects may be implemented.

[0085] The apparatus may further include a communication interface, where the communication interface is used for the apparatus to communicate with other devices. Exemplarily, the communication interface may be a transceiver, a circuit, a bus, a module, or other types of communication interfaces.

[0086] In a fifth aspect, the present application provides a chip system comprising at least one processor for supporting the implementation of the functions involved in any of the above aspects and any possible implementation of any aspect, for example, receiving or processing the data and / or information involved in the above method.

[0087] In one possible design, the chip system further includes a memory, which is used to store program instructions and data, and the memory is located inside or outside the processor.

[0088] The chip system can be composed of chips, or can include chips and other discrete devices.

[0089] In a sixth aspect, the present application provides a computer-readable storage medium comprising a computer program, which, when executed on a computer, enables the computer to implement the method in any of the above aspects and any possible implementation of any of the aspects.

[0090] In the seventh aspect, the present application provides a computer program product, which includes: a computer program (also referred to as code, or instructions), which, when executed, enables a computer to execute the method in any of the above aspects and any possible implementation of any aspect.

[0091] In an eighth aspect, the present application provides a communication system, comprising the aforementioned first apparatus and a second apparatus, wherein the first apparatus is configured to implement the method in the first aspect and any possible implementation of the first aspect, and the second apparatus is configured to implement the method in the second aspect and any possible implementation of the second aspect.

[0092] It should be understood that the third to eighth aspects of the present application correspond to the technical solutions of the first or second aspect of the present application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation methods are similar and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] FIG1 is a schematic diagram of the architecture of a communication system applicable to the method provided in an embodiment of the present application;

[0094] FIG2 is a schematic diagram of an application scenario applicable to the method provided in an embodiment of the present application;

[0095] 3 and 4 are schematic flow charts of the communication method provided in the embodiments of the present application;

[0096] FIG5 is a schematic diagram showing the effect of the scrambling function designed for the physiological feature detection scenario on the perception results provided by the present application;

[0097] Figures 6 and 7 are schematic diagrams showing the effect of the scrambling function designed for human presence scenarios on perception results provided by this application;

[0098] FIG8 is a schematic diagram of an embodiment of the present application showing that a high energy impact is dispersed into a frequency range;

[0099] FIG9 is a schematic diagram showing the effect of a scrambling function designed for an activity recognition scenario on a perception result according to an embodiment of the present application;

[0100] 10 and 11 are schematic block diagrams of the apparatus provided in the embodiments of the present application. DETAILED DESCRIPTION

[0101] The technical solution in this application will be described below with reference to the accompanying drawings.

[0102] To facilitate understanding of the embodiments of the present application, the following points are first explained:

[0103] First, in the embodiments of this application, prefixes such as "first" and "second" are used solely to distinguish and describe different things belonging to the same category, and do not restrict the order, size, or quantity of the things. For example, "first device" and "second device" are simply different devices, and do not limit the number of devices or their priority relationship; for another example, "first signal" and "second signal" are simply different signals, and there is no temporal order, size, or priority relationship between the two.

[0104] Second, the “sending” and “receiving” in the embodiments of the present application indicate the direction of signal transmission. For example, “sending first information to the second device” can be understood as the destination end of the information being the second device, which can include direct sending through the air interface, and also includes indirect sending through the air interface by other units or modules. “Receiving third information from the second device” can be understood as the source end of the configuration information being the second device, which can include direct receiving from the second device through the air interface, and also includes indirect receiving from the second device through the air interface from other units or modules. “Sending” can also be understood as the “output” of the chip interface, and “receiving” can also be understood as the “input” of the chip interface.

[0105] In other words, sending and receiving can be performed between devices, for example, between a first device and a second device; or it can be performed within a device, for example, sending or receiving between components, modules, chips, software modules or hardware modules within the device through a bus, wiring or interface.

[0106] It is understood that before information is sent from the source to the destination, it may undergo necessary processing, such as encoding and modulation. After receiving the information from the source, the destination may also perform corresponding processing, such as decoding and demodulation, to interpret the valid information from the source. Similar expressions in this application can be understood similarly and will not be repeated here.

[0107] Third, in the embodiments of the present application, "at least one" refers to one or more, and "more" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: the existence of A alone, the existence of A and B at the same time, and the existence of B alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship, but does not exclude the situation where the previous and next associated objects are in an "and" relationship. The specific meaning can be understood in conjunction with the context. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c; a and b; a and c; b and c; or a and b and c. Where a, b, c can be single or multiple.

[0108] Fourth, in the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information (such as the indication information described below) is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, directly indicating the information to be indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated may also be indirectly indicated by indicating other information, wherein the other information has an association relationship with the information to be indicated; or only a part of the information to be indicated may be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information may be achieved by means of the arrangement order of each information agreed in advance (such as predefined by the protocol), thereby reducing the indication overhead to a certain extent. The present application does not limit the specific method of indication.

[0109] It can be understood that, for the sender of the indication information, the indication information can be used to indicate the information to be indicated, and for the receiver of the indication information, the indication information can be used to determine the information to be indicated.

[0110] Fifth, the tables in the embodiments of the present application are only examples. The values ​​of the information in each table are only examples and can be configured as other values, which are not limited by the present application. The tables do not limit the scope of protection of the present application. For example, appropriate deformation adjustments can be made based on the tables in the above text, such as splitting, merging, etc. For another example, the parameter names shown in the titles of the tables can also use other names that can be understood by the communication device, and the values ​​or representations of the parameters can also use other values ​​or representations that can be understood by the communication device. For another example, when implementing the above tables, other data structures can also be used, such as arrays, queues, containers, stacks, linear lists, pointers, linked lists, trees, graphs, structures, classes, heaps, hash tables or hash tables.

[0111] Sixth, in the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device (such as the first device or the second device) will perform corresponding processing under certain objective circumstances. It does not limit the time, nor does it require the device to perform a judgment action when implemented, nor does it mean that there are other limitations.

[0112] Seventh, the predefined in this application can be understood as: define, predefine, store, pre-store, pre-negotiate, pre-configure, solidify, or pre-burn.

[0113] The technical solutions provided in this application can be applied to various communication systems, such as: long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD) system, sidelink (SL) communication system, fifth generation (5G) mobile communication system or new radio access technology (NR), satellite communication system, etc. Among them, the 5G mobile communication system can include non-standalone (NSA) and / or standalone (SA) networking.

[0114] The technical solution provided in this application can also be applied to communication systems that evolve after 5G, such as the sixth generation (6G) mobile communication system, etc. This application does not limit this.

[0115] In this application, a radio access network (RAN) device is a device with wireless transceiver capabilities. It can provide wireless communication services and connect terminals to a wireless network. It can be a node in a radio access network, referred to as a RAN node.

[0116] In one possible scenario, a RAN node can be a base station (BS), an evolved NodeB (eNodeB), a transmission reception point (TRP), a home evolved NodeB (HNB), a wireless fidelity (Wi-Fi) access point (AP), a mobile switching center, a next-generation NodeB (gNB) in a 5G mobile communication system, a next-generation NodeB in a 6G mobile communication system, or a base station in a future mobile communication system. A RAN node can also be a device that performs base station functions in device-to-device (D2D) communication systems, vehicle-to-everything (V2X) communication systems, machine-to-machine (M2M) communication systems, and Internet of Things (IoT) communication systems. A RAN node can also be a RAN node in a non-terrestrial network (NTN), meaning that the RAN node can be deployed on a high-altitude platform or satellite. A RAN node can be a macro base station, a micro base station, an indoor base station, a relay node, a donor node, or a radio controller in a cloud radio access network (CRAN) scenario, or a node in an open radio access network (O-RAN or ORAN) scenario. Alternatively, a RAN node can be a server, a wearable device, a vehicle, or an onboard device. For example, a RAN node in V2X technology can be a roadside unit (RSU). Of course, a RAN node can also be a node in the core network.

[0117] In another possible scenario, multiple RAN nodes collaborate to assist the terminal in achieving wireless access, and different RAN nodes respectively implement part of the functions of the base station. For example, the RAN node can be a centralized unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU). The CU and DU can be set separately, or they can be included in the same network element, such as a baseband unit (BBU). The RU can be included in a radio frequency device or radio frequency unit, such as a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH).

[0118] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meanings. For example, in the ORAN system, CU may be referred to as Open CU (O-CU), DU may be referred to as Open DU (O-DU), CU-CP may be referred to as Open CU-CP (O-CU-CP), CU-UP may be referred to as Open CU-UP (O-CU-UP), and RU may be referred to as Open RU (O-RU).

[0119] Among them, any unit among CU (or CU-CP, CU-UP), DU and RU can be implemented by a software module, a hardware module, or a combination of a software module and a hardware module. That is, the wireless access network device in this application can be a virtualized device, for example, implemented by general hardware and instantiated virtualization functions, or by dedicated hardware and instantiated virtualization functions. Among them, the general hardware can be a server, such as a cloud server.

[0120] The terminal in this application may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal equipment, wireless communication equipment, user agent or user device.

[0121] A terminal can be a device that provides voice / data connectivity to a user, such as a handheld device or vehicle-mounted device with wireless connection function. At present, some examples of terminal devices can be: mobile phones, tablet computers, computers with wireless transceiver functions (such as laptops, PDAs, etc.), mobile internet devices (MIDs), virtual reality (VR) devices, augmented reality (AR) devices, smart point of sale (POS) machines, customer-premises equipment (CPE), wireless terminals in industrial control, wireless terminals in self-driving cars, drones, terminal devices in IoT systems, wireless terminals in remote medical care, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), etc. assistant, PDA), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to a wireless modem, vehicle-mounted devices, wearable devices, terminal devices in 5G networks or terminal devices in future evolved public land mobile communication networks (PLMN), etc.

[0122] Wearable devices, also known as wearable smart devices, are a general term for wearable devices that use wearable technology to intelligently design and develop wearable devices for daily wear, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not just hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. In a broad sense, wearable smart devices include those that are fully functional, large in size, and can achieve full or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0123] In addition, terminal devices can also include sensors such as smart printers, train detectors, and gas stations. Their main functions include collecting data (part of the terminal devices), receiving control information and downlink data from network devices, and sending electromagnetic waves to transmit uplink data to network devices.

[0124] The terminal in this application may be a virtualized device, for example, implemented by general-purpose hardware and instantiated virtualization functions, or by dedicated hardware and instantiated virtualization functions. The general-purpose hardware may be a server, for example, a cloud server.

[0125] It should be understood that the present application does not limit the specific forms of the wireless access network device and the terminal device.

[0126] Figure 1 is a schematic diagram of the architecture of a communication system 100 applicable to the method provided in an embodiment of the present application. As shown in Figure 1 , the communication system 100 includes a radio access network 10 and a core network 20. Optionally, the communication system 100 may also include the Internet 30. The radio access network 10 may include at least one radio access network device (such as 110a and 110b in Figure 1 ) and at least one terminal (such as 120a-120j in Figure 1 ).

[0127] Terminals can connect to radio access network equipment wirelessly, and radio access network equipment can connect to the core network wirelessly or via wired connections. Core network equipment and radio access network equipment can be independent, distinct physical devices, or they can integrate the core network equipment's functions and the radio access network equipment's logical functions into the same physical device. Alternatively, a single physical device can integrate some core network equipment functions and some radio access network equipment functions. Terminals and radio access network equipment can connect to each other via wired or wireless connections.

[0128] Wireless access network devices and terminals, wireless access network devices, and terminals can communicate through authorized spectrum, unauthorized spectrum, or both. They can communicate through spectrum below 6 gigahertz (GHz), spectrum above 6 GHz, or both. The embodiments of this application do not limit the spectrum resources used for wireless communications.

[0129] The wireless access network device may be a base station deployed in the air, such as a satellite base station 110a; or a base station deployed indoors, such as a micro base station or an indoor station 110b.

[0130] The terminal can be a terminal deployed in the air, such as the helicopter or drone 120i in Figure 1; it can also be a terminal deployed on the ground, such as the mobile phones 120a, 120e, 120f and 120j, vehicle 120b, computer 120g, printer 120h, etc. in Figure 1.

[0131] Wireless access network equipment and terminals can be fixed or mobile. For example, they can be deployed on land, indoors or outdoors, handheld or vehicle-mounted; on water; or in the air on aircraft, balloons, and satellites.

[0132] The roles of radio access network devices and terminals can be relative. For example, the helicopter or drone 120i in Figure 1 can be configured as a mobile base station. For devices 120j accessing the radio access network 10 via 120i, 120i is a base station; however, for 110a, 120i is a terminal. That is, communication between 110a and 120i occurs via a wireless air interface protocol. Of course, communication between 110a and 120i can also occur via an interface protocol between radio access network devices. In this case, 120i is also a base station relative to 110a. Therefore, radio access network devices and terminals can be collectively referred to as communication devices. 110a, 110b, and 120a-120j in Figure 1 can be referred to as communication devices having their respective corresponding functions, such as communication devices having base station functions or communication devices having terminal functions.

[0133] It should be understood that FIG1 is only a schematic diagram, and the communication system may further include other devices, such as wireless relay devices and wireless backhaul devices, which are not shown in FIG1 .

[0134] FIG2 is a schematic diagram of a perception scenario applicable to the method provided in an embodiment of the present application. As shown in FIG2 , there is a stationary human, a wall, a ground, etc. in the communication environment between the transmitter and the receiver. The transmitter transmits a signal to the receiver, which can be transmitted through a line of sight (LOS) path, a non-line of sight (NLOS) path, or reflected by a wall or the ground to reach the receiver; when the receiver receives the signal from the transmitter and performs channel estimation based on the received signal, it can analyze the user-related information or environmental information in the communication environment based on the measured channel state information.

[0135] The receiver and transmitter shown in Figure 2 may be the terminal or access network device shown in Figure 1. For example, the transmitter is the access network device and the receiver is the terminal; or the transmitter is the terminal and the receiver is the access network device.

[0136] To facilitate understanding, we first briefly introduce the relevant concepts involved in this application.

[0137] 1. Perception: This refers to using changes in wireless signals during propagation to obtain the characteristics of the signal propagation space and infer information related to the environment or users (such as people and objects in the environment). For example, channel measurements are performed to obtain CSI or CIR, which is used to achieve perception.

[0138] 2. Physiological characteristic detection: monitoring of, for example, the breathing rate or heart rate of an organism.

[0139] 3. Biological presence detection: Detects whether there are biological organisms in the environment, which is mainly divided into motion presence detection and stationary presence detection.

[0140] Static presence detection primarily uses physiological characteristics like breathing and heart rate to determine the presence of living things in an environment. Motion presence detection, similar to activity detection, determines the presence of a moving target based on the differences in the frequency spectrum between motion and rest. In this application, organism presence detection refers to static presence detection.

[0141] 4. Activity detection: Detect different activity behaviors of organisms in the environment.

[0142] In wireless systems, some special "measurement" signals (for example, reference signals) are often used for perception, and these signals have a public signal structure. If a transmitter performs perception measurement by sending such signals, it may cause all receivers in the communication system that can receive such signals to obtain perception results based on the measurement of such signals. However, in some perception scenarios, users only hope that the authorized sender and receiver (that is, the sender and receiver authorized to perform perception measurements) can obtain accurate perception results, and unauthorized users cannot obtain correct perception results. Therefore, if perception measurements are still performed based on the current "measurement" signals, unauthorized users may obtain accurate perception results, which may lead to the leakage of user privacy.

[0143] In view of this, an embodiment of the present application provides a communication method and related apparatus. In this method, a transmitting end scrambles multiple sensing signals to be sent using a scrambling function and shares the scrambling function with authorized transmitting and receiving ends. In this way, after receiving the signal, the authorized receiving end can perform channel estimation based on the pre-shared scrambling function and the received signal, and thus obtain user-related information. The scrambling function is unknown to unauthorized devices, so unauthorized devices can only perform channel estimation based on the received signal and cannot obtain user-related information, thereby protecting user privacy.

[0144] The communication method provided in the embodiment of the present application is described in detail below in conjunction with Figures 3 and 4. The method provided in the present application can be applied to the network architecture shown in Figure 1, but the embodiment of the present application is not limited thereto.

[0145] In the flowcharts shown in Figures 3 and 4, the method is illustrated from the perspective of communication device interaction, but the present application does not limit the execution subject of the method. For example, the first device in Figures 3 and 4 can be a terminal device or an access network device, or the first device can be a component configured in the terminal device or access network device (such as a chip, a chip system, or a processor), or it can be a logic module or software that can realize all or part of the functions of the first device; the second device in Figures 3 and 4 can be a terminal device or an access network device, or the second device can be a component configured in the terminal device or access network device (such as a chip, a chip system, or a processor), or it can be a logic module or software that can realize all or part of the functions of the second device.

[0146] FIG3 is a schematic flow chart of a communication method 300 provided in an embodiment of the present application. As shown in FIG3 , the method 300 may include steps S301 to S303. Each step in the method 300 is described in detail below.

[0147] S301: A first device generates a first signal and a second signal, wherein the second signal is obtained by performing phase adjustment on the first signal based on a predefined scrambling function, and the scrambling function is predefined.

[0148] The preset scrambling function is a time-varying function with a low-pass characteristic. This scrambling function can be used as an encryption parameter and shared between authorized senders and receivers. For example, an encryption algorithm can be used to encrypt the information field indicating the scrambling function type and generation method, the scrambling function parameters, or the sampled values ​​of the scrambling function, so that both the sender and the receiver can obtain the scrambling function.

[0149] It can be understood that the first device can also generate M (M is an integer greater than or equal to 2) signals, and the M signals include at least two signals that satisfy the relationship between the above-mentioned first signal and the second signal.

[0150] S302: The first device outputs a first signal and a second signal, wherein the first signal is sent via a first antenna corresponding to the first device, and the second signal is sent via a second antenna corresponding to the first device.

[0151] The first antenna and the second antenna may be antennas deployed on the first device (ie, the first device includes a radio frequency unit); or, the first antenna and the second antenna may be antennas corresponding to the first device (ie, the first device does not include a radio frequency unit).

[0152] Exemplarily, when a radio frequency unit is not deployed in the first device (for example, the first device is a baseband unit), S302 can be replaced by: the first device outputs a first signal and a second signal; and sends the first signal through the first antenna corresponding to the first device, and sends the second signal through the second antenna corresponding to the first device.

[0153] Exemplarily, when a radio frequency unit is deployed in the first device (for example, the first device includes a baseband unit and a radio frequency unit), S302 can be replaced by: the first device sends a first signal through a first antenna included in the first device, and sends a second signal through a second antenna included in the first device.

[0154] S303: The second device obtains a perception result based on a predefined scrambling function and the received signal.

[0155] In an embodiment of the present application, the first device sends multiple sensing signals scrambled by a predefined scrambling function to the second device, so that the second device performs channel measurement and obtains sensing results based on the received signals and the predefined target scrambling function. Since the scrambling function is only shared by authorized senders and receivers (which can be understood as devices used to provide sensing services), only authorized senders and receivers can obtain accurate sensing results and obtain user information. The scrambling function is unknown to unauthorized devices, so unauthorized devices cannot obtain accurate channel state information, and thus cannot obtain relevant information about the user, thereby protecting user privacy.

[0156] Figure 4 is a schematic flow chart of a communication method 400 provided in an embodiment of the present application. As shown in Figure 4, the method 400 may include steps S401 to S404. Each step in the method 400 is described in detail below.

[0157] S401: The first device and the second device determine a type of a target scrambling function corresponding to a first perception scenario and parameters included in the target scrambling function.

[0158] The first perception scene is the scene to be perceived. When the scenes to be perceived are different, the types and parameters of the target scrambling functions determined by the first device and the second device are also different. That is, different perception scenes correspond to different types and parameters of the scrambling functions.

[0159] The first perception scenario can be one of the following perception scenarios: a physiological characteristic detection scenario, a biological presence detection scenario, or an activity recognition scenario. The physiological characteristic detection scenario is a scenario for detecting physiological characteristic parameters, the biological presence detection scenario is a scenario for detecting the presence of biological organisms in an environment, and the activity recognition scenario is a scenario for detecting biological activities. It should be understood that the first perception scenario can also be other scenarios requiring perception.

[0160] The type of the target scrambling function can be one of the following random functions: a sine function, a linear combination of sine functions, a double sine function, a linear combination of two groups of sine functions, or a function obtained by interpolating S random numbers based on an interpolation algorithm, etc., where S is an integer greater than 1.

[0161] It is understood that the parameters included in the target scrambling function are related to the type of the target scrambling function, that is, different types of target scrambling functions may include different parameters. Since the parameters included in different types of scrambling functions are described in detail below, they will not be described in detail here.

[0162] S402: The first device generates a first signal and a second signal. The second signal is obtained by performing phase adjustment on the first signal based on a target scrambling function, where the target scrambling function is determined based on a type and parameters of the target scrambling function.

[0163] It can be understood that the first device can also generate M signals, including at least two signals that satisfy the relationship between the first signal and the second signal; where M is an integer greater than or equal to 2.

[0164] S403: The first device outputs a first signal and a second signal, wherein the first signal is sent via a first antenna corresponding to the first device, and the second signal is sent via a second antenna corresponding to the first device.

[0165] This process can be referred to the description of S302 above and will not be repeated here.

[0166] S404: The second device obtains a perception result based on the target scrambling function and the received signal.

[0167] Similarly, the second device includes a radio frequency unit or does not include a radio frequency unit.

[0168] Exemplarily, the second device obtains a perception result based on the target scrambling function and the received signal, including: the second device determines the first signal and the second signal based on the target scrambling function; performs channel measurement based on the first signal, the second signal and the received signal to obtain a measurement result; and obtains a perception result based on the measurement result.

[0169] Exemplarily, when the second device corresponds to N antennas (or corresponds to N antennas, where N is an integer greater than 0), the signal received by the second device refers to the signal received by each of the N antennas. It will be understood that the signal received by the i-th antenna (i is 1, 2, 3, ..., N) of the N antennas refers to: the signal received by the first signal sent by the first device via the first antenna after passing through the first channel, and the signal received by the second signal sent by the first device via the second antenna after passing through the second channel.

[0170] The first channel is a channel between the first antenna and the i-th antenna, and the second channel is a channel between the second antenna and the i-th antenna.

[0171] Optionally, after S404, the method 400 further includes: the second device sending the perception result to the first device. Correspondingly, the first device receives the perception result.

[0172] In an embodiment of the present application, the first device and the second device predetermine the target scrambling function corresponding to the scene to be perceived by the type of scrambling function corresponding to the scene to be perceived and the parameters included in the scrambling function. Then, the first device sends multiple signals processed by the target scrambling function to the second device, so that the receiving end performs channel measurement and obtains the perception result based on the received signal and the determined target scrambling function. Since the type of scrambling function and the parameters included in the scrambling function are only shared between the first device and the second device, only the authorized sender and receiver can obtain the correct channel state information and thus obtain accurate perception results. Unauthorized devices cannot obtain the correct channel state information due to the unknown scrambling function, and thus cannot obtain relevant information about the user, thereby protecting the user's privacy.

[0173] In one possible implementation, the ratio of the first signal to the second signal is equal to e jθ(t) is proportional to, or the ratio of the first signal to the second signal is proportional to e jθ(t) Inversely proportional to θ(t), θ(t) is the target scrambling function.

[0174] Exemplarily, the first signal and the second signal satisfy the following relationship:

[0175] Wherein, Q1(t) is the first signal, Q2(t) is the second signal, and k is a non-zero real number, for example, k=1 or -1.

[0176] In one possible implementation, when the first perception scenario is a physiological feature detection scenario, the type of the target scrambling function can be a sine function or a linear combination of sine functions; when the first perception scenario is a biological presence detection scenario, the type of the target scrambling function is a double sine function or a linear combination of two groups of sine functions; when the first perception scenario is an activity recognition scenario, the type of the target scrambling function is a function obtained by interpolating S random numbers based on an interpolation algorithm.

[0177] In one possible implementation, the same perception scenario may correspond to multiple types of scrambling functions, and the first device and the second device may determine the type of target scrambling function corresponding to the first perception scenario through mutual negotiation.

[0178] In one possible implementation, the first device may determine the type of the target scrambling function corresponding to the first perceived scenario based on the first mapping relationship, and send first information indicating the type of the target scrambling function to the second device. Correspondingly, the second device receives the first information and determines the type of the target scrambling function corresponding to the first perceived scenario based on the first information.

[0179] Optionally, after receiving the first information, the second device re-determines the type of the target scrambling function corresponding to the first perception scenario based on the first mapping relationship; updates the first information based on the re-determined type of the target scrambling function corresponding to the first perception scenario, and sends the updated first information to the first device. Correspondingly, the first device receives the updated first information and re-determines the type of the target scrambling function corresponding to the first perception scenario based on the updated first information.

[0180] In one possible implementation, the second device may determine the type of the target scrambling function corresponding to the first perceived scenario based on the first mapping relationship, and send first information indicating the type of the target scrambling function to the first device. Correspondingly, the first device receives the first information and determines the type of the target scrambling function corresponding to the first perceived scenario based on the first information.

[0181] Optionally, after receiving the first information, the first device re-determines the type of the target scrambling function corresponding to the first perception scenario based on the first mapping relationship; updates the first information based on the re-determined type of the target scrambling function corresponding to the first perception scenario, and transmits the updated first information to the second device. Correspondingly, the second device receives the updated first information and, based on the updated information, re-determines the type of the target scrambling function corresponding to the first perception scenario.

[0182] The first mapping relationship indicates the type of at least one scrambling function corresponding to each of the multiple perception scenarios.

[0183] Exemplarily, the type of the target scrambling function may be indicated by an index corresponding to the type of the target scrambling function. For example, the first information includes an index corresponding to the type of the target scrambling function.

[0184] The first information in this application is transmitted in an encrypted manner, and the encryption key is only shared between authorized sending and receiving devices.

[0185] It can be understood that the parameters included in the target scrambling function are related to the type of the target scrambling function. For example, when the type of the target scrambling function is a sine function, the parameter includes the frequency of the sine function; when the function type of the target scrambling function is a linear combination of sine functions, the parameter includes the frequency of each sine function in the linear combination of sine functions, and the number of sine functions included in the linear combination of sine functions; when the function type of the target scrambling function is a double sine function, the parameter includes the frequency of each sine function in the double sine function; when the type of the target scrambling function is a linear combination of two groups of sine functions, the parameter includes the frequency of each sine function in the linear combination of the two groups of sine functions, and the number of sine functions included in each group of sine functions; when the type of the target scrambling function is a function obtained by interpolating S random numbers based on an interpolation algorithm, the parameter is S random numbers.

[0186] In one possible implementation, the first device and the second device may determine the parameters included in the target scrambling function corresponding to the first perception scene based on a second mapping relationship after determining the type of the target scrambling function, where the second mapping relationship indicates a set of parameters corresponding to each type of scrambling function among multiple types of scrambling functions.

[0187] In another possible implementation, after determining the type of the target scrambling function, the first device determines parameters included in the target scrambling function based on the type of the target scrambling function. The first device then sends second information indicating the parameters included in the target scrambling function to the second device. Correspondingly, the second device receives the second information or third information and determines the parameters included in the target scrambling function based on the second information or third information.

[0188] Optionally, after determining the type of the target scrambling function, the second device determines parameters included in the target scrambling function based on the type of the target scrambling function, and sends second information indicating the parameters included in the target scrambling function to the first device. Correspondingly, the first device receives the second information or third information and determines the parameters included in the target scrambling function based on the second information or third information.

[0189] In another possible implementation, after determining the type of the target scrambling function, the first device determines parameters included in the target scrambling function based on the type of the target scrambling function. The first device then sends third information to the second device, where the third information indicates an algorithm for generating the parameters included in the target scrambling function (e.g., a linear congruential algorithm or a Mersenne twister algorithm). Correspondingly, the second device receives the third information and, based on the third information, determines the parameters included in the target scrambling function.

[0190] Optionally, after determining the type of the target scrambling function, the second device determines parameters included in the target scrambling function based on the type of the target scrambling function, and sends third information to the first device, where the third information indicates an algorithm for generating the parameters included in the target scrambling function. Correspondingly, the first device receives the third information and determines the parameters included in the target scrambling function based on the third information.

[0191] Similar to the previous article, since the same perception scenario can correspond to multiple types of scrambling functions, and each type of scrambling function corresponds to a set of parameters, when the first device and the second device have not determined the type of target scrambling function corresponding to the first perception scenario, the two parties can determine the parameters included in the target scrambling function through negotiation.

[0192] In one possible implementation, the first device may determine parameters of a target scrambling function corresponding to the first perceived scenario based on the third mapping relationship, and send second information to the second device. Correspondingly, the second device receives the second information and, based on the second information, determines parameters of the target scrambling function corresponding to the first perceived scenario.

[0193] Optionally, after receiving the second information, the second device re-determines the parameters of the target scrambling function corresponding to the first perceived scenario based on the third mapping relationship; updates the second information based on the re-determined parameters of the target scrambling function corresponding to the first perceived scenario, and transmits the updated second information to the first device. Correspondingly, the first device receives the updated second information and, based on the updated second information, re-determines the parameters of the target scrambling function corresponding to the first perceived scenario.

[0194] In one possible implementation, the second device may determine, based on the third mapping relationship, parameters included in the target scrambling function corresponding to the first perceived scenario, and send the second information to the first device. Correspondingly, the first device receives the second information and, based on the second information, determines the parameters included in the target scrambling function corresponding to the first perceived scenario.

[0195] Optionally, after receiving the second information, the first device re-determines the parameters of the target scrambling function corresponding to the first perceived scenario based on the third mapping relationship; updates the second information based on the re-determined parameters of the target scrambling function corresponding to the first perceived scenario, and transmits the updated second information to the second device. Correspondingly, the second device receives the updated second information and, based on the updated second information, re-determines the parameters of the target scrambling function corresponding to the first perceived scenario.

[0196] Among them, the above-mentioned third mapping relationship indicates at least one set of parameters corresponding to each perception scene in multiple perception scenes.

[0197] In one possible implementation, the first device may determine, based on the fourth mapping relationship, an algorithm for generating parameters included in a target scrambling function corresponding to the first perceived scenario, and send third information to the second device. Correspondingly, the second device receives the third information and, based on the third information, determines the parameters included in the target scrambling function corresponding to the first perceived scenario.

[0198] Optionally, after receiving the second information, the second device re-determines an algorithm for generating parameters included in the target scrambling function corresponding to the first perceived scenario based on the fourth mapping relationship. The second device updates the second information based on the re-determined parameters included in the target scrambling function corresponding to the first perceived scenario, and transmits the updated second information to the first device. Correspondingly, the first device receives the updated third information and, based on the updated third information, re-determines the parameters included in the target scrambling function corresponding to the first perceived scenario.

[0199] In one possible implementation, the second device may determine, based on the fourth mapping relationship, an algorithm for generating parameters included in a target scrambling function corresponding to the first perceived scenario, and send third information to the first device. Correspondingly, the first device receives the third information and, based on the third information, determines the parameters included in the target scrambling function corresponding to the first perceived scenario.

[0200] Optionally, after receiving the second information, the first device re-determines an algorithm for generating parameters included in the target scrambling function corresponding to the first perceived scenario based on the fourth mapping relationship; updates the second information based on the re-determined parameters included in the target scrambling function corresponding to the first perceived scenario, and transmits the updated second information to the second device. Correspondingly, the second device receives the updated third information and, based on the updated third information, re-determines the parameters included in the target scrambling function corresponding to the first perceived scenario.

[0201] The fourth mapping relationship indicates that each of the multiple perception scenarios corresponds to at least one group of generation algorithms, and each generation algorithm in the at least one group of generation algorithms is used to generate a parameter.

[0202] The second information and the third information in this application are transmitted in an encrypted manner, and the encryption key is only shared between authorized sending and receiving devices.

[0203] It is understood that the first information and the second information can be sent simultaneously, for example, carried in the same signaling. Alternatively, the first information and the second information can be sent separately, for example, carried in different signaling. This application does not limit this.

[0204] Similarly, the third information and the first information can be sent at the same time, or the third information and the first information can be sent separately.

[0205] Optionally, before S401, the method 400 further includes: the first device and the second device determine that the scene to be perceived is a first perception scene.

[0206] The first device and the second device may determine a specific perception scenario through negotiation.

[0207] In one possible implementation, a first device determines that a physiological feature needs to be sensed and sends fourth information to a second device, the fourth information indicating that the scene to be sensed is a physiological feature detection scene. Correspondingly, the second device determines whether the physiological feature can be sensed based on the fourth information.

[0208] If the second device is capable of sensing the physiological characteristics, the scene to be sensed is determined to be a physiological characteristics detection scene.

[0209] If the second device cannot sense the physiological feature, the first device may send the fourth information to other devices or continue to send the fourth information to the second device after a period of time.

[0210] In another possible implementation, the second device determines that the physiological feature needs to be sensed and sends fourth information to the first device, where the fourth information indicates that the scene to be sensed is a physiological feature detection scene. Correspondingly, the first device determines whether the physiological feature can be sensed based on the fourth information.

[0211] If the first device is capable of sensing the physiological characteristics, the scene to be sensed is determined to be a physiological characteristics detection scene.

[0212] If the first device cannot sense the physiological feature, the second device may send the fourth information to other devices or continue to send the fourth information to the first device after a period of time.

[0213] Optionally, before S402, the method 400 further includes: the first device and the second device obtain the target scrambling function based on the type of the target scrambling function and the parameters included in the target scrambling function.

[0214] Exemplarily, the function form of the target scrambling function can be obtained based on the type of the target scrambling function; based on the parameters included in the target scrambling function, other parameters in the function form except the independent variable and the dependent variable can be determined, thereby obtaining the target scrambling function.

[0215] For example, if the type of the target scrambling function is a sine function, the function form of the target scrambling function can be determined as: In addition to the independent variable x and the dependent variable y, when the amplitude A, frequency f and phase are known After that, the target scrambling function can be determined.

[0216] The following introduces the value range of the parameters included in the target scrambling function corresponding to the first perception scenario, as well as the corresponding target scrambling function.

[0217] In a possible implementation, the first perception scenario is a physiological feature detection scenario, and when the type of the target scrambling function is a sine function, the frequency of the sine function is within the frequency range corresponding to the physiological activity.

[0218] Among them, the frequency range corresponding to physiological activities can be expressed as [F l1 ,F l2 ].

[0219] For example, the frequency range corresponding to physiological activities may be the frequency range corresponding to breathing: 0.1 Hz to 0.67 Hz (6 to 40 times / minute), or the frequency range corresponding to heartbeat: 0.83 Hz to 2.5 Hz (50 to 150 times / minute).

[0220] When the frequency range corresponding to physiological activities is the range of respiratory frequency, F l1 Can be equal to 0.1(Hz), F l2 It can be equal to 0.67 (Hz); when the frequency range corresponding to physiological activities is the range of heart rate, F l1 Can be equal to 0.83 (Hz), F l2 It can be equal to 2.5 (Hz).

[0221] Exemplarily, the type of the target scrambling function is a sine function, and the target scrambling function θ(t) satisfies:

[0222] Among them, F q ∈[F l1 ,F l2 ], F q It is in [F l1 ,F l2 ] is a frequency value randomly selected within the frequency range, where A is a non-zero real number.

[0223] For example, When the target scrambling function θ(t) satisfies: θ(t)=Acos2πF q t.

[0224] Optionally, A = π. In this case, the obtained scrambling function is θ(t) = πcos2πF q t, which can make F q The intensity of the false spectrum peak at is much greater than the intensity of the real spectrum peak, that is, the characteristics introduced by the real action of the perceived object (such as breathing, heartbeat) on the spectrum will be masked by the spectrum characteristics introduced by the scrambling function, and privacy is protected.

[0225] It can be understood that when the type of the target scrambling function is a sine function, the target scrambling function determined by the first device and the second device can also be a function obtained by changing at least one of the following items in formula (2): amplitude, phase, or frequency.

[0226] In one possible implementation, the first perception scenario is a physiological feature detection scenario, and when the function type of the target scrambling function is a linear combination of sine functions, the frequency of each sine function in the linear combination of sine functions is within the frequency range corresponding to the physiological activity.

[0227] It can be understood that the frequencies of any two sine functions in the linear combination of sine functions may be the same or different.

[0228] For the description of the frequency range corresponding to physiological activities, please refer to the previous description and will not be repeated here.

[0229] Exemplarily, the type of the target scrambling function is a linear combination of sine functions, and the target scrambling function θ(t) satisfies:

[0230] Among them, F qi ∈[F l1 ,F l2 ], F qi It can be in [F l1 ,F l2 ] frequency value randomly selected within the frequency range, is a non-zero real number, n a is an integer greater than 1, is a real number.

[0231] It is understandable that the above n a The initial phases of any two sine functions in the sine functions can be the same or different. a The amplitudes of any two of the sine functions can be the same or different.

[0232] For example, n a When the initial phases of all sine functions are 0, the target scrambling function θ(t) satisfies:

[0233] It can be understood that when the type of the target scrambling function is a linear combination of sine functions, the target scrambling function determined by the first device and the second device can also be a function obtained by changing at least one of the following items in formula (3): n a The amplitude of at least one of the sine functions, n a The phase of at least one of the sine functions, or n a The frequency of at least one of the sine functions.

[0234] In one possible implementation, when the first sensing scenario is a biological presence detection scenario and the target scrambling function is a dual-sine function, the dual-sine function includes a first sine function and a second sine function. The frequency of the first sine function is within the frequency range corresponding to breathing, and the frequency of the second sine function is within the frequency range corresponding to heartbeat.

[0235] Among them, the frequency range corresponding to breathing can be expressed as: [F m1 ,F m2 ], the frequency range corresponding to the heartbeat can be expressed as: [F n1 ,F n2 ].

[0236] Regarding the frequency range corresponding to breathing and the frequency range corresponding to heartbeat, please refer to the previous description and will not be repeated here. m1 Can be equal to 0.1(Hz), F m2 Can be equal to 0.67 (Hz); F n1 Can be equal to 0.83 (Hz), F n2 It can be equal to 2.5 (Hz).

[0237] Exemplarily, the function type of the target scrambling function is a double sine function, and the target scrambling function θ(t) satisfies:

[0238] Among them, F a1 ∈[F m1 ,F m2 ], F a1 It can be in [F m1 ,F m2 ] is a frequency value randomly selected within the frequency range, F b1 ∈[F n1 ,F n2 ], F b1 It can be in [F n1 ,F n2 ] frequency value randomly selected within the frequency range, and are all non-zero real numbers, and All are real numbers.

[0239] It can be understood that in the dual sine function, the initial phases of the two sine functions can be the same or different, and the amplitudes of the two sine functions can be the same or different.

[0240] Exemplarily, when the initial phases of the two sine functions in the above double sine function are both 0, the target scrambling function θ(t) satisfies:

[0241] It can be understood that when the type of the target scrambling function is a dual sine function, the target scrambling function determined by the first device and the second device can also be a function obtained by changing at least one of the following items in formula (4): the amplitude of the first sine function, the frequency of the first sine function, the phase of the first sine function, the amplitude of the second sine function, the phase of the second sine function, or the frequency of the second sine function.

[0242] In one possible implementation, the first perception scenario is a biological presence detection scenario, and the type of the target scrambling function is a linear combination of two groups of sine functions. The linear combination of the two groups of sine functions is a linear combination of A first sine functions (A first sine functions can be called a first group of sine functions) and B second sine functions (B second sine functions can be called a second group of sine functions). The frequencies of the A first sine functions are all within the frequency range corresponding to breathing, and the frequencies of the B second sine functions are all within the frequency range corresponding to heartbeat. A and B are both integers greater than 0, but A and B cannot be equal to 1 at the same time. When A and B are not 1 at the same time, the determined target scrambling function can introduce multiple false spectral peaks, thereby increasing the difficulty for eavesdroppers to guess and achieving better privacy protection.

[0243] Among them, the frequency range corresponding to breathing can be expressed as: [F m1 ,F m2 ], the frequency range corresponding to the heartbeat can be expressed as: [F n1 ,F n2 ]. For example, F m1 Can be equal to 0.1(Hz), F m2 Can be equal to 0.67 (Hz); F n1 Can be equal to 0.83 (Hz), F n2 It can be equal to 2.5 (Hz).

[0244] It can be understood that when A is greater than 1, the frequencies of any two sine functions in the A first sine functions can be the same or different; when B is greater than 1, the frequencies of any two sine functions in the B second sine functions can be the same or different.

[0245] Exemplarily, the type of the target scrambling function is a linear combination of two sets of sine functions, and the target scrambling function θ(t) satisfies:

[0246] Among them, F ai ∈[F m1 ,F m2 ], F ai For [F m1 ,F m2 ] is a frequency value randomly selected from the bi ∈[F n1,F n2 ], F bi For [F n1 ,F n2 ] frequency value randomly selected within the frequency range, and are all non-zero real numbers, n a and n b are all integers greater than 1, and All are real numbers.

[0247] It can be understood that the linear combination of the above two groups of sine functions includes (n a +n b ) sine functions, the initial phases of any two sine functions can be the same or different, and the amplitudes of any two sine functions can be the same or different.

[0248] For example, in (n a +n b ) When the initial phases of the sine functions are all 0, the target scrambling function θ(t) satisfies:

[0249] Similar to formula (4), when the type of the target scrambling function is a linear combination of two sets of sine functions, the target scrambling function determined by the first device and the second device can also be a function obtained by changing at least one of the following items in formula (5): n a The amplitude of at least one of the first sine functions, n a The frequency of at least one of the first sine functions, n a The phase of at least one of the first sine functions, n b The amplitude of at least one of the second sine functions, n b The phase of at least one of the second sine functions, or n b The frequency of at least one of the two second sine functions.

[0250] In one possible implementation, when the first perception scenario is an activity recognition scenario, the target scrambling function is obtained by interpolating S random numbers based on an interpolation algorithm. For example, the number S of S random numbers used to determine the target scrambling function satisfies:

[0251] Among them, F max is the maximum value of the maximum Doppler frequency shift caused by various actions to be identified, F max Determined by the perceived scene and carrier frequency, (e.g., F maxNo more than a few hundred Hz), M is the number of perception wheels, Δt is the duration of each perception wheel, α is a number greater than 0 and less than 1, and M is an integer greater than 1.

[0252] It should be understood that the functions obtained by interpolating the S random numbers based on different interpolation algorithms may be different.

[0253] Since the value of S is related to F max related, so F max It can also be called the parameters included in the target scrambling function corresponding to the activity recognition scenario. In addition, since the target scrambling functions obtained under different interpolation algorithms may be different, the interpolation algorithm can also be called the parameters included in the target scrambling function corresponding to the activity recognition scenario.

[0254] For example, by combining the above-mentioned perception scenarios, types of scrambling functions, and correspondences of parameters, a correspondence as shown in Table 1 can be obtained.

[0255] Table 1

[0256] As shown in Table 1, the bits shown in the "Type Indication" column in Table 1 can be used to indicate the types of different scrambling functions corresponding to different perception scenarios. For example, "000" indicates that the type of the target scrambling function corresponding to the first perception scenario is a sine function, and "001" indicates that the type of the target scrambling function corresponding to the first perception scenario is a linear combination of sine functions.

[0257] Method 400 above describes in detail the correspondence between the scenario to be sensed, the type of scrambling function, and the parameters included in the scrambling function. The following describes in detail the design methods for the scrambling functions corresponding to the three sensing scenarios, using the example of a first device equipped with two antennas, a second device equipped with a single antenna, and an unauthorized device present in the environment, where the unauthorized device is equipped with two antennas.

[0258] This application assumes that the signals transmitted by the two antennas of the first device are Q1(t) and Q2(t), and the unauthorized device perceives the signal by receiving Q1(t) and Q2(t) transmitted by the first device. The signals received by the two antennas of the unauthorized device are R1(t) and R2(t), and R1(t) and R2(t) satisfy the following conditions:

[0259] Among them, H tiej represents the frequency domain channel coefficient between the i-th antenna of the first device and the j-th antenna of the unauthorized user, where i is 1 and 2, j is 1 and 2, and Q1(t) and Q2(t) satisfy: That is, in the above formula (1), the value of k is 1.

[0260] Unauthorized devices cannot use the received signals from each antenna to perform channel estimation and perception because they do not know the relationship between Q1(t) and Q2(t). However, they can divide the signals received from the two antennas to eliminate the influence of the encrypted signal.

[0261] For example, the unauthorized device divides R1(t) and R2(t) to obtain S(t) satisfies:

[0262] If the formula (8) You can get:

[0263] 1. The scene to be perceived is a physiological feature detection scene.

[0264] In the actual physiological feature detection scenario, Ra in formula (9) i (t) is usually composed of a strong DC component (corresponding to a relatively static environment) and a weak time-varying component (corresponding to the slight changes in the channel caused by breathing or heartbeat), that is: Ra i (t) = c i +g i ·ω i (t), and |c i |>>|g i |,c i represents the DC component mentioned above, g i ·ω i (t) represents the time-varying component mentioned above, and the value of i is 1, 2, or 3.

[0265] If Ra i Substituting (t) into formula (9), we can obtain:

[0266] Because |c i |>>|g i |, so

[0267] If A1(t)=c1+g1·ω1(t) in formula (11), We can get: S(t)≈A1(t)·A2(t). Formula (12)

[0268] Continuing to perform Fourier transform on formula (12), we can obtain:

[0269] Since the result of Fourier transform of A1(t)=c1+g1·ω1(t) is Therefore, the above formula (13) can be equivalently replaced by:

[0270] Where p0 refers to the DC component in A1(t), It means that the frequency in A1(t) is The weight, F p It is the actual frequency corresponding to the physiological activity to be detected (for example, the frequency corresponding to breathing or heartbeat).

[0271] From formula (14), we can get the function The corresponding peak is F p Therefore, in order to protect the user's physiological characteristics, the scrambling function θ(t) should be selected so that it can introduce a false spectral peak, that is, the selected θ(t) can make the function When the maximum value is taken, the corresponding F is not equal to F p , that is, the selected θ(t) can make Established.

[0272] In order to introduce a false peak, θ(t) can be determined as the frequency F q A single-frequency function (e.g., θ(t) = πcos2πF q t). Let θ(t)=πcos2πF q At t, it can be proved that: A2(t)≈z0+Re jθ(t) , in this case A2(t) is a periodic function, and the spectrum of A2(t) can be approximated as:

[0273] Substituting formula (15) into the above formula (14), we can obtain:

[0274] According to the Fourier series formula of periodic function, q0 and

[0275] q0≈z0+RJ0(π)≈z0-0.304R,

[0276] Where J0(x) and J1(x) are zero-order and first-order Belle functions of the first kind, respectively. According to the results of mathematical analysis and combined with the fact that |c2|≈1, |c3|≈1, and |c3|≠|c2|, we can get |q0| and Roughly equivalent, and because So F a The false peak intensity at F pThat is to say, the features introduced by the spectrum of the user's real physiological characteristics (such as breathing and heartbeat) will be masked by the spectrum features introduced by the scrambling function, and the user's physiological characteristics will be protected.

[0277] In summary, the scrambling function in the physiological feature detection scenario can be: θ(t) = πcos2πF q t.

[0278] In order to further enhance the protection effect of the user's physiological characteristics, it can be considered to [F l1 ,F l2 ] introduce multiple false peaks into the spectrum. For example, the scrambling function can be selected as a linear combination of several single-frequency functions, such as:

[0279] Figure 5 shows a schematic diagram of the effect of a scrambling function designed for a physiological feature detection scenario on the perception results. Figure 5 (a) and (d) respectively show the modulus of the time domain waveform of S(t) when θ(t) = 0 and the modulus of the spectrum corresponding to S(t). θ(t) = 0 means that the first device does not use a scrambling function to process the perception signal. When θ(t) = 0, the modulus of the spectrum shown in Figure 5 (d) shows that the unauthorized device can accurately estimate the respiratory rate to be 0.25 Hz.

[0280] (b) and (e) in Figure 5 respectively show the modulus of the time domain waveform of S(t) when θ(t) is a random number uniformly distributed within (0, 2π) and the modulus of the frequency spectrum corresponding to S(t). When θ(t) is a random number uniformly distributed within (0, 2π), it can be seen from the characteristics of the modulus of the time domain waveform shown in Figure 5 (b) that the time domain waveform of S(t) is disordered, but it can be seen from the characteristics of the modulus of the frequency spectrum shown in Figure 5 (e) that the unauthorized device can still accurately estimate the breathing frequency to be 0.25 Hz through frequency domain analysis.

[0281] (c) and (f) in FIG5 respectively show that the permutation function is the scrambling function designed by this application: The modulus of the time domain waveform of S(t) and the modulus of the spectrum corresponding to S(t) are When the time domain waveform of S(t) is chaotic, it can be seen from the characteristics of the mode of the time domain waveform shown in (c) of Figure 5, and it can be seen from the characteristics of the mode of the spectrum shown in (f) of Figure 5 that after introducing the scrambling function (n a =3), three false spectrum peaks are introduced, which mask the true respiratory frequency, and unauthorized devices cannot estimate the true respiratory frequency through frequency domain analysis.

[0282] In summary, the scrambling function designed in this application in the physiological feature detection scenario can protect the user's information.

[0283] 2. The scenario to be sensed is a biological presence detection scenario. The following mainly uses human presence detection as an example to introduce.

[0284] In the human presence detection scenario, Ra in formula (9) i (t) needs to be replaced by: Ra i (t) = c i +1{presense}(g i1 ·ω i1 (t)+g i2 ·ω i2 (t));

[0285] Among them, c i represents the DC component mentioned above, g i1 ·ω i1 (t) represents the first time-varying component (corresponding to the small changes in the channel caused by breathing), g i ·ω i (t) represents the second time-varying component (corresponding to the small changes in the channel caused by the heartbeat), 1 {X} is an indicator function. When the event described by X is true, the function value is 1, otherwise the function value is 0. Combined with the perception scenario of detecting whether humans exist, when humans exist, the function value is 1, and when humans do not exist, the function value is 0; ω i1 (t) and ω i2 (t) are the channel fluctuation parameters caused by breathing and heartbeat respectively.

[0286] If Ra i (t) = c i +1{presense}(g i1 ·ω i1 (t)+g i2 ·ω i2 Substituting S(t) into formula (9), we can get the updated S(t):

[0287] Because |c i |>>|g ij |, so

[0288] If A1(t)=c1+1{presense}(g 11 ·ω 11 (t)+g 12 ·ω 12 (t)), The above formula (12) can be obtained.

[0289] According to formula (12), we can get The process of can refer to the analysis process of formula (13) and formula (14) above. No further details will be given here.

[0290] Similarly, The corresponding peak is F b In order to ensure that unauthorized devices cannot infer whether there is someone, the selection of the scrambling function θ(t) should be able to introduce the same false spectrum peak whether there is someone or not in the environment, that is, the selected θ(t) can make the function The corresponding F at the maximum value is equal to F a1 and F b1 , that is, the selected θ(t) can make: and This holds true whether there are people in the environment or not.

[0291] Similar to the analysis in the physiological feature detection scenario, it can be concluded that the scrambling function in the biological presence detection scenario can be designed as:

[0292] Similar to the previous article, to further enhance the protection of user information, the scrambling function can be selected as a combination of two sets of sine functions, for example:

[0293] In the human presence detection scenario, after processing the perception signal using the scrambling function designed in this application, the channel measurement results obtained by the authorized user are shown in Figure 6. Among them, (a) in Figure 6 is the modulus of the time domain waveform of S(t), and (b) in Figure 6 is the modulus of the spectrum corresponding to S(t). As can be seen from Figure 6, in the two scenarios with and without people, the modulus of the measured time domain waveform of S(t) and the modulus of the spectrum corresponding to S(t) have completely different change patterns. Therefore, the authorized user can determine whether there is a human in the current environment based on the difference between the channel measurement results obtained in the scenarios with and without people.

[0294] In the human presence detection scenario, after the perception signal is processed using the scrambling function designed in this application, the channel measurement results obtained by the unauthorized device are shown in Figure 7. Among them, (a) in Figure 7 is the modulus of the time domain waveform of S(t), and (b) in Figure 7 is the modulus of the spectrum corresponding to S(t). As can be seen from Figure 7, in both the manned and unmanned scenarios, the change patterns of the modulus of the measured S(t) time domain waveform and the modulus of the spectrum corresponding to S(t) are difficult to distinguish. Therefore, the unauthorized device cannot determine whether there is anyone in the current environment based on the channel measurement results obtained in the manned and unmanned scenarios.

[0295] 6 and 7 , it can be seen that the scrambling function designed in the present application for the human presence detection scenario can protect the user's information without affecting the perception performance of the authorized user.

[0296] 3. The scene to be perceived is an activity recognition scene.

[0297] Let the above formula (9) We can get: S(t) = Ra1(t)·A(t). Formula (19)

[0298] In the activity recognition scenario, in order to protect user privacy, the spectrum of A(t) in the above formula (19) needs to be able to confuse the spectrum of Ra1(t). That is, after the spectrum of A(t) is convolved with the spectrum of Ra1(t), it must be able to diffuse the high-energy impact in Ra1(t) into a frequency range (as shown in Figure 8).

[0299] The above-mentioned A(t) is a composite function, so the bandwidth of A(t) is determined by the function that changes the fastest among them. In order to make the spectral characteristics of A(t) meet the above conditions (that is, after the spectrum of A(t) is convolved with the spectrum of Ra1(t), the impact with larger energy in Ra1(t) should be able to be diffused within a frequency range), this application should make θ(t) the fastest changing function among the various functions that constitute A(t). Otherwise, the bandwidth of A(t) will be determined by the function Ra2(t) or the function Ra3(t), and Ra2(t) or Ra3(t) is caused by the movement of objects in the environment, and it is possible that the bandwidth is very narrow and cannot achieve the effect of dispersing the spectrum of Ra1(t). Therefore, the bandwidth of the selected scrambling function θ(t) should be greater than the maximum value F of the maximum Doppler shift caused by the various actions to be identified. max .

[0300] Based on the above requirements for the bandwidth of the scrambling function θ(t), a method for determining the scrambling function is introduced below. The method may include the following steps 1 to 4:

[0301] Step 1: Assume that the entire perception process includes M perception rounds, and the duration of each perception round is Δt. Then the total duration of the total perception process is (M*Δt), that is, the time duration of the scrambling function θ(t) is (M*Δt).

[0302] Step 2: Randomly generate S uniformly distributed random numbers ranging from 0 to 2π, and the time interval corresponding to adjacent random numbers is

[0303] Among them, S satisfies: (α is a number greater than 0 and less than 1), F maxThe maximum value of the maximum Doppler shift caused by various actions to be identified is determined by the application scenario and carrier frequency, and is generally not more than a few hundred Hz. So we can think that S random numbers are the scrambling function θ(t) at 0, Sampling at time (M-1)Δt etc.

[0304] Step 3: For the above S random numbers, use the piecewise interpolation algorithm to interpolate the function obtained as the scrambling function θ(t). If θ(t) is greater than 2π, then set θ(t) equal to 2π; if θ(t) is less than 0, then set θ(t) equal to 0.

[0305] Step 4: Sample θ(t) obtained in step 3 at intervals of Δt to obtain a set of samples θ(mΔt). θ(mΔt) is the scrambling function used in the mth perception round.

[0306] Figure 9 shows a schematic diagram of the effect of a scrambling function designed for an activity recognition scenario on perception results. Figures 9 (a) and (d) respectively show the modulus of the time domain waveform of S(t) and the modulus of the spectrum corresponding to S(t) when θ(t) = 0. θ(t) = 0 means that the first device does not use a scrambling function to process the perception signal. When θ(t) = 0, the modulus of the spectrum shown in Figure 9 (d) indicates that the unauthorized device can accurately distinguish between standing still and walking.

[0307] (b) and (e) in Figure 9 respectively show the modulus of the time domain waveform of S(t) and the modulus of the spectrum corresponding to S(t) when θ(t) is a random number uniformly distributed on (0, 2π). When θ(t) is a random number uniformly distributed on (0, 2π), it can be seen from the characteristics of the modulus of the time domain waveform shown in (b) in Figure 9 and the modulus of the spectrum shown in (e) in Figure 9 that there are still obvious differences between the time domain waveform and the time spectrum of S(t) under the two actions of stillness and walking. Unauthorized devices can distinguish between the two actions of stillness and walking, and user privacy cannot be protected.

[0308] Figures 9(c) and (f) respectively show the modulus of the time-domain waveform of S(t) and the modulus of the spectrum corresponding to S(t) when the permutation function is the scrambling function designed in this application. The modulus of the time-domain waveform shown in Figure 9(c) and the modulus of the spectrum shown in Figure 9(f) show that the time-domain waveform and the time-domain spectrum of S(t) are indistinguishable under both stationary and walking actions. Since unauthorized devices are unaware of the scrambling function, they are unable to distinguish between stationary and walking actions, thus protecting user privacy.

[0309] In summary, the scrambling function designed in this application in the activity recognition scenario can protect user privacy.

[0310] The method provided by the present application is described in detail above with reference to Figures 1 to 9 , and the device provided by the present application is introduced below with reference to Figures 10 and 11 .

[0311] Figures 10 and 11 are schematic diagrams of possible devices provided by embodiments of the present application. These devices can be used to implement the functions of the first device or the second device in the above method embodiments, and thus can also achieve the beneficial effects of the above method embodiments.

[0312] FIG10 is a schematic block diagram of an apparatus according to an embodiment of the present application. As shown in FIG10 , the apparatus 1000 includes a transceiver module 1010 and a processing module 1020 .

[0313] One possible design is that the device 1000 is used to implement the function of the first device in the method embodiments shown in FIG. 3 and FIG. 4 .

[0314] Exemplarily, the processing module 1020 is used to: determine the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function; generate a first signal and a second signal, the second signal being obtained by phase adjusting the first signal based on the target scrambling function, the target scrambling function being determined based on the type of the target scrambling function and the parameters; and outputting the first signal and the second signal, the first signal being sent through the first antenna corresponding to the first device, and the second signal being sent through the second antenna corresponding to the first device.

[0315] Another possible design is that the device 1000 is used to implement the function of the second device in the method embodiments shown in FIG. 3 and FIG. 4 .

[0316] Exemplarily, the processing module 1020 is used to: determine the type of the target scrambling function corresponding to the first perception scene and the parameters included in the target scrambling function; and obtain a perception result based on the target scrambling function and the signal received from the first device, wherein the target scrambling function is determined based on the type of the target scrambling function and the parameters.

[0317] Optionally, the transceiver module 1010 is configured to send or receive first information, where the first information indicates a type of the target scrambling function.

[0318] Optionally, the transceiver module 1010 is further used to: send or receive second information, where the second information indicates the parameter.

[0319] Optionally, the transceiver module 1010 is further configured to send or receive third information, where the third information indicates an algorithm for generating the parameters.

[0320] Optionally, the transceiver module 1010 is further used to: send or receive fourth information, where the fourth information indicates that the scene to be perceived is the first perception scene.

[0321] Optionally, the processing module 1020 is further configured to obtain the target scrambling function based on the type of the target scrambling function and the parameters.

[0322] A more detailed description of the transceiver module 1010 and the processing module 1020 can be directly obtained by referring to the relevant descriptions in the embodiments shown in FIG. 3 and FIG. 4 , and is not repeated here.

[0323] It should be noted that device 1000 may include a sending module but not a receiving module. Alternatively, device 1000 may include a receiving module but not a sending module. This may depend on whether the above-mentioned solution executed by device 1000 includes both sending and receiving actions. It is understood that since device 1000 has communication functionality, it can also be referred to as a communication device.

[0324] Figure 11 is another schematic block diagram of an apparatus provided in an embodiment of the present application. As shown in Figure 11, apparatus 1100 includes one or more processors 1110. The processor 1110 may be a general-purpose processor or a dedicated processor. For example, it may be a baseband processor or a central processing unit. The baseband processor may be used to process communication protocols and communication data, and the central processing unit may be used to control the apparatus (e.g., the first apparatus, the second apparatus, or the chip), execute software programs, and process data of the software programs.

[0325] Optionally, in one design, the processor 1110 may include a program (also referred to as code or instructions), which may be executed on the processor 1110 to cause the apparatus 1100 to perform the method performed by the first apparatus or the second apparatus in the above method embodiments. In another possible design, the apparatus 1100 includes a circuit (not shown in FIG. 11 ) configured to implement the functions of the first apparatus or the second apparatus in the above method embodiments.

[0326] Exemplarily, the processor 1110 may be configured to execute a computer program or instruction in a memory to implement the steps performed by the first device or the second device in the method embodiment shown in any one of the embodiments shown in FIG. 3 and FIG. 4 .

[0327] Optionally, the device 1100 may include one or more memories 1120 on which programs (sometimes also referred to as codes or instructions) are stored. The programs can be run on the processor 1110 so that the device 1100 executes the method executed by the first device or the second device in the above embodiment.

[0328] Optionally, the processor 1110 and / or the memory 1120 may include an artificial intelligence (AI) module, which is used to implement AI-related functions. The AI ​​module may be implemented through software, hardware, or a combination of software and hardware. For example, the AI ​​module may include a wireless intelligent controller (RIC) module. For example, the AI ​​module may be a near real-time RIC or a non-real-time RIC.

[0329] Optionally, data may be stored in the processor 1110 and / or the memory 1120. The processor and the memory may be provided separately or integrated together.

[0330] Optionally, the device 1100 may further include a communication interface 1130. The processor 1110 may also be referred to as a processing unit, and controls the device (e.g., the first device or the second device). The communication interface 1130 may also be referred to as a transceiver unit, a transceiver, a transceiver circuit, or a transceiver, and is configured to implement the transceiver function of the device via the antenna 1140.

[0331] Optionally, the apparatus 1100 further includes a communication interface 1130. The processor 1110 and the communication interface 1130 are coupled to each other. It is understood that the communication interface 1130 may be a transceiver or an input / output interface.

[0332] It is understandable that, since the device 1100 has a communication function, it can also be called a communication device.

[0333] When the apparatus 1100 is used to implement the method of FIG3 , the processor 1110 is used to perform the functions of the processing unit described above, and the communication interface 1130 is used to perform the functions of the transceiver module described above. Whether the communication interface 1130 is used for sending or receiving can be determined by whether the method implemented by the apparatus 1100 is used for sending or receiving.

[0334] It is understood that when the device 1100 is the first device or the second device, the communication interface 1130 may be a transceiver, specifically including a transmitter and a receiver, where the transmitter is used to transmit signals and the receiver is used to receive signals. When the device 1100 is a chip used in the first device or the second device, the communication interface 1130 may be an input / output circuit, where the input circuit can be used for receiving and the output interface can be used for transmitting.

[0335] It should be noted that the above method embodiments can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by hardware integrated logic circuits in the processor or by software instructions.

[0336] The processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0337] The steps of the method disclosed in the embodiments of this application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0338] The memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0339] The present application also provides a computer-readable medium having a computer program stored thereon, which implements the functions of the above-mentioned method embodiment when executed by a computer.

[0340] The present application also provides a computer program product comprising instructions, which implements the functions of the above method embodiments when executed by a computer.

[0341] The methods provided in the above embodiments can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, they can be implemented in whole or in part in the form of a computer program product. The computer program product may include one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic disk), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0342] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0343] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0344] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0345] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0346] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0347] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk, or an optical disk.

[0348] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A communication method, characterized in that: Applied to a first device, the method comprises: Determining a type of a target scrambling function corresponding to a first perception scene and parameters included in the target scrambling function; generating a first signal and a second signal, wherein the second signal is obtained by phase-adjusting the first signal based on the target scrambling function, wherein the target scrambling function is determined based on a type of the target scrambling function and the parameter; The first signal and the second signal are output, wherein the first signal is sent through a first antenna corresponding to the first device, and the second signal is sent through a second antenna corresponding to the first device.

2. The method according to claim 1, characterized in that The ratio of the first signal to the second signal is equal to e jθ(t) is proportional to, or the ratio of the first signal to the second signal is proportional to e jθ(t) Inversely proportional to θ(t), θ(t) is the target scrambling function.

3. The method according to claim 1 or 2, characterized in that: Also includes: First information is sent or received, where the first information indicates a type of the target scrambling function.

4. The method according to any one of claims 1 to 3, characterized in that Also includes: Second information is sent or received, where the second information indicates the parameter.

5. The method according to any one of claims 1 to 3, characterized in that Also includes: Send or receive third information, where the third information indicates an algorithm for generating the parameters.

6. The method according to any one of claims 1 to 5, characterized in that Also includes: Send or receive fourth information, where the fourth information indicates that the scene to be perceived is the first perceived scene.

7. A communication method, characterized in that: Applied to a second device, comprising: Determining a type of a target scrambling function corresponding to a first perception scene and parameters included in the target scrambling function; A perception result is obtained based on the target scrambling function and the signal received from the first device, wherein the target scrambling function is determined based on the type of the target scrambling function and the parameter.

8. The method according to claim 7, characterized in that Also includes: First information is received or sent, where the first information indicates a type of the target scrambling function.

9. The method according to claim 7 or 8, characterized in that: Also includes: Second information is received or sent, where the second information indicates the parameter.

10. The method according to claim 7 or 8, characterized in that: Also includes: Receive or send third information, where the third information indicates an algorithm for generating the parameters.

11. The method according to any one of claims 7 to 10, characterized in that Also includes: Receive or send fourth information, where the fourth information indicates that the scene to be perceived is the first perceived scene.

12. The method according to any one of claims 1 to 11, characterized in that The first perception scene is one of the following multiple perception scenes: a physiological characteristic detection scene, a biological presence detection scene and an activity recognition scene; wherein the physiological characteristic detection scene is a scene for detecting physiological characteristic parameters, the biological presence detection scene is a scene for detecting whether there are biological organisms in the environment, and the activity recognition scene is a scene for detecting biological activities.

13. The method according to claim 12, characterized in that The type of the target scrambling function is one of a variety of random functions: a sine function, a linear combination of sine functions, a double sine function, a linear combination of two groups of sine functions, or a function obtained by interpolating S random numbers based on an interpolation algorithm, where S is an integer greater than 1.

14. The method according to claim 13, characterized in that The first perception scene is the physiological feature detection scene, the function type of the target scrambling function is the sine function, the parameters include the frequency of the sine function, and the frequency of the sine function is within the frequency range corresponding to the physiological activity.

15. The method according to claim 14, characterized in that The target scrambling function θ(t) satisfies: θ(t) = πcos 2πF q t, Among them, F q ∈[F l1 ,F l2 ],[F l1 ,F l2 ] represents the frequency range corresponding to the physiological activity, F q For in [F l1 ,F l2 ] is a frequency value randomly selected from .

16. The method according to claim 13, characterized in that The first perception scenario is the physiological feature detection scenario, the type of the target scrambling function is the linear combination of sinusoidal functions, the parameters include the frequency of each sinusoidal function in the linear combination of sinusoidal functions and the number of sinusoidal functions included in the linear combination of sinusoidal functions, and the frequency of each sinusoidal function is within the frequency range corresponding to the physiological activity.

17. The method according to claim 16, characterized in that The target scrambling function θ(t) satisfies: Among them, F qi ∈[F l1 ,F l2 ],[F l1 ,F l2 ] represents the frequency range corresponding to the physiological activity, F qi For in [F l1 ,F l2 ] frequency range randomly selected, is a non-zero real number, n a is an integer greater than 1.

18. The method according to claim 13, characterized in that The first perception scene is the biological presence detection scene, the type of the target scrambling function is the double sine function, the double sine function includes a first sine function and a second sine function, the parameters include the frequency of the first sine function and the frequency of the second sine function, the frequency of the first sine function is within the frequency range corresponding to breathing, and the frequency of the second sine function is within the frequency range corresponding to heartbeat.

19. The method according to claim 18, characterized in that The target scrambling function θ(t) satisfies: Among them, F a1 ∈[F m1 ,F m2 ],[F m1 ,F m2 ] represents the frequency range corresponding to the breathing, F a1 For in [F m1 ,F m2 ] is a frequency value randomly selected within the frequency range of b1 ∈[F n1 ,F n2 ],[F n1 ,F n2 ] represents the frequency range corresponding to the heartbeat, F b1 For in [F n1 ,F n2 ] frequency range randomly selected, and All are non-0 real numbers.

20. The method according to claim 13, characterized in that The first perception scene is the biological presence detection scene, the type of the target scrambling function is a linear combination of the two groups of sine functions, and the parameters include the frequency of each sine function in the linear combination of the two groups of sine functions, and the number of sine functions included in each group of sine functions; The linear combination of the two groups of sine functions includes a first group of sine functions and a second group of sine functions, the frequency of each sine function in the first group of sine functions is within the frequency range corresponding to breathing, and the frequency of each sine function in the second group of sine functions is within the frequency range corresponding to heartbeat.

21. The method according to claim 20, characterized in that The target scrambling function θ(t) satisfies: Among them, F ai ∈[F m1 ,F m2 ],[F m1 ,F m2 ] represents the frequency range corresponding to breathing, F ai For in [F m1 ,F m2 ] is a frequency value randomly selected from bi ∈[F n1 ,F n2 ],[F n1 ,F n2 ] indicates the frequency range corresponding to the heartbeat, F bi For in [F n1 ,F n2 ] frequency range randomly selected, and are all non-zero real numbers, n a and n b are all integers greater than 1, and All are real numbers.

22. The method according to claim 13, characterized in that The first perception scene is the activity recognition scene, the type of the target scrambling function is a function obtained by interpolating S random numbers based on an interpolation algorithm, the parameters are the S random numbers, and S is an integer greater than 1.

23. The method according to claim 22, characterized in that S satisfies: Among them, F max is the maximum value of the maximum Doppler frequency shift caused by various actions to be identified, M is the number of perception rounds, Δt is the duration of each perception round, α is a number greater than 0 and less than 1, and M is an integer greater than 1.

24. A communication device, characterized in that: Comprising means for implementing the method as claimed in any one of claims 1 to 23.

25. A communication device, characterized in that: The device comprises a processor configured to enable the communication device to implement the method according to any one of claims 1 to 23 by executing a computer program and / or a logic circuit.

26. The device according to claim 25, characterized in that The system also includes a memory for storing a computer program and / or a configuration file of the logic circuit.

27. The device according to claim 25 or 26, characterized in that A communication interface is also included for inputting and / or outputting signals.

28. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 23 is performed.

29. A computer program product, characterized in that The invention comprises a computer program, and when the computer program is run, the method according to any one of claims 1 to 23 is performed.

30. A communication system, characterized in that: The method comprises a first device and a second device, wherein the first device is used to implement the method according to any one of claims 1 to 23.

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