Communication method and related device

Abstract

The invention provides a communication method and a related device, which can realize protection of user privacy in a perception scene. The method comprises the steps that a first device and a second device determine the type of a target scrambling function corresponding to a first sensing scene and parameters included in the target scrambling function; 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, and the target scrambling function is determined based on the type of the target scrambling function and the parameter; the first device outputs a first signal and a second signal, sends first information through a first antenna corresponding to the first device, and sends the second signal through a second antenna corresponding to the first device; correspondingly, the second device receives the signal from the first device, and obtains a sensing result based on the received signal and the target scrambling function.

Description

Technical Field

[0001] This application relates to the field of communication technologies, and in particular, to a communication method and related devices. Background Art

[0002] Sensing refers to using wireless signals to measure a channel and inferring information related to the environment or objects existing in the environment based on the measurement results (for example, channel state information (CSI) or channel impulse response (CIR)). In a wireless system, the measurement signals generally used for sensing have a publicly known signal structure, so it is possible to cause privacy exposure. For example, unauthorized users can achieve sensing of the physical environment by eavesdropping on and measuring the above-mentioned measurement signals, and thus infer user location, behavior characteristics, etc.

[0003] Therefore, there is an urgent need for a sensing protection technology to protect user privacy. Summary of the Invention

[0004] This application provides a communication method and related devices, which can achieve the protection of user privacy in a sensing scenario.

[0005] In a first aspect, this application provides a communication method, which can be applied to a first device. For example, the first device can be a terminal or a network device, or it can also be a component (such as a chip, a chip system, or a circuit, etc.) configured in a terminal or a network device, or it can also be a logic module or software capable of implementing all or part of the functions of a terminal or a network device. This application does not make any limitations in this regard.

[0006] The method includes: determining the type of a target scrambling function corresponding to a first sensing scenario and the parameters included in the target scrambling function; generating a first signal and a second signal, where the second signal is obtained by performing phase adjustment on 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, where 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.

[0007] In a possible implementation manner, the above-mentioned first sensing scenario is one of the following multiple sensing scenarios: a physiological feature detection scenario, a biological presence detection scenario, and an activity recognition scenario; where the physiological feature detection scenario is a scenario for detecting physiological feature parameters, the biological presence detection scenario is a scenario for detecting whether there is a biological in the environment, and the activity recognition scenario is a scenario for detecting biological activities.

[0008] In a possible implementation, the type of the above-mentioned target scrambling function is one of multiple random functions: sine function, linear combination of sine functions, double sine function, 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.

[0009] Exemplarily, the ratio of the first signal to the second signal is proportional to e jθ(t) or the ratio of the first signal to the second signal is inversely proportional to e jθ(t) , where θ(t) is the target scrambling function.

[0010] Based on the above technical content, the first device determines in advance the target scrambling function corresponding to the to-be-sensed scenario through the type of the scrambling function corresponding to the to-be-sensed scenario 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 can obtain the sensing result according to the received signals and the determined target scrambling function. Since the type of the scrambling function and the parameters included in the scrambling function are only shared between the authorized transceiver parties (for example, the first device and the second device in this application), only the authorized transceiver parties can obtain accurate sensing results, while the unauthorized devices cannot make accurate estimates because they do not know the scrambling function, so they cannot obtain the relevant information of the user, thus realizing the protection of user privacy.

[0011] In a second aspect, the present application provides a communication method, which can be applied to the second device. For example, the second device can be a terminal or a network device, or can also be a component (such as a chip, a chip system, or a circuit, etc.) configured in the terminal or the network device, or can also be a logical module or software capable of implementing all or part of the functions of the terminal or the network device. The present application does not make any limitations in this regard.

[0012] The method includes: determining the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function; and obtaining a sensing result based on the target scrambling function and the signals received from the first device, where the target scrambling function is determined based on the type of the target scrambling function and the parameters.

[0013] Based on the above technical content, the second device pre-determines the target scrambling function corresponding to the to-be-perceived scenario according to the type of the scrambling function corresponding to the to-be-perceived scenario and the parameters included in the scrambling function. Thus, after receiving multiple signals processed by the target scrambling function from the first device, the second device can obtain a perception result according to the received signals and the pre-determined target scrambling function. Since the type of the scrambling function and the parameters included in the scrambling function are only shared by the authorized transceiver parties (for example, the first device and the second device in this application), only the authorized transceiver parties can obtain an accurate perception result. Unauthorized devices cannot make accurate estimates because they do not know the scrambling function, and thus cannot obtain relevant information of the user, achieving the protection of user privacy.

[0014] For the description of the first perception scenario and the type of the target scrambling function, reference can be made to the description in the first aspect, which will not be elaborated here.

[0015] Exemplarily, obtaining the perception result based on the target scrambling function and the signals received from the first device includes: performing channel estimation based on the target scrambling function and the signals received from the first device to obtain channel state information; and obtaining the perception result based on the channel state information.

[0016] For example, if the first perception scenario is a physiological feature detection scenario, the above perception result can be physiological feature parameters such as heart rate or breathing rate; if the first perception scenario is a biological presence detection scenario, the above perception result can be that there is a biological in the environment or there is no biological in the environment; if the first perception scenario is an activity recognition scenario, the above perception result can be the activity type of the biological in the environment.

[0017] Combined with the first aspect (or the second aspect), in some possible implementation manners, after determining the type of the target scrambling function corresponding to the first perception scenario and the parameters included in the target scrambling function, the method further includes: sending a first message, where the first message indicates the type of the target scrambling function.

[0018] Correspondingly, combined with the second aspect (or the first aspect), in some possible implementation manners, the method further includes: receiving a first message, where the first message indicates the type of the target scrambling function.

[0019] For the description of the target scrambling function, reference can be made to the description in the first aspect above, which will not be elaborated here.

[0020] Combined with the first aspect (or the second aspect), in some possible implementation manners, before determining the type of the target scrambling function corresponding to the first perception scenario and the parameters included in the target scrambling function, the method further includes: receiving a first message, where the first message indicates the type of the target scrambling function.

[0021] Correspondingly, in combination with the second aspect (or the first aspect), in some possible implementation manners, the method further includes: sending first information, where the first information indicates the type of the target scrambling function.

[0022] Based on this method, the first device and the second device can obtain the type of the target scrambling function corresponding to the first sensing 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, so as to implement channel estimation and sensing.

[0023] In combination with the first aspect (or the second aspect), in some possible implementation manners, after determining the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function, the method further includes: sending second information, where the second information indicates the parameters included in the target scrambling function.

[0024] Correspondingly, in combination with the second aspect (or the first aspect), in some possible implementation manners, the method further includes: receiving second information, where the second information indicates the parameters included in the target scrambling function.

[0025] In combination with the first aspect (or the second aspect), in some possible implementation manners, before determining the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function, the method further includes: receiving second information, where the second information indicates the parameters included in the target scrambling function.

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

[0027] 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 sensing 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, so as to implement channel estimation and sensing.

[0028] In combination with the first aspect (or the second aspect), in some possible implementation manners, after determining the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function, the method further includes: sending third information, where the third information indicates the generation algorithm of the parameters.

[0029] Correspondingly, in combination with the second aspect (or the first aspect), in some possible implementation manners, the method further includes: receiving third information, where the third information indicates the generation algorithm of the parameters.

[0030] In combination with the first aspect (or the second aspect), in some possible implementation manners, before determining the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function, the method further includes: receiving third information, where the third information indicates the generation algorithm of the parameters.

[0031] Correspondingly, in combination with the second aspect (or the first aspect), in some possible implementation manners, the method further includes: sending third information, where the third information indicates the generation algorithm of the parameters.

[0032] 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 sensing scenario, so as to determine the parameters included in the target scrambling function based on the obtained generation algorithm of the parameters, and further determine the target scrambling function based on the type of the target scrambling function and the parameters included in the target scrambling function, so as to implement channel estimation and sensing.

[0033] Optionally, before determining the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function, the method further includes: determining the scenario to be sensed as the first sensing scenario.

[0034] In combination with the first aspect (or the second aspect), in some possible implementation manners, after determining the scenario to be sensed as the first sensing scenario, the method further includes: sending fourth information, where the fourth information indicates that the scenario to be sensed is the first sensing scenario.

[0035] Correspondingly, in combination with the second aspect (or the first aspect), in some possible implementation manners, the method further includes: receiving fourth information, where the fourth information indicates that the scenario to be sensed is the first sensing scenario.

[0036] In combination with the first aspect (or the second aspect), in some possible implementation manners, before determining the scenario to be sensed as the first sensing scenario, the method further includes: receiving fourth information, where the fourth information indicates that the scenario to be sensed is the first sensing scenario.

[0037] Correspondingly, in combination with the second aspect (or the first aspect), in some possible implementation manners, the method further includes: sending fourth information, where the fourth information indicates that the scenario to be sensed is the first sensing scenario.

[0038] Based on this method, the first device and the second device interact with the fourth information, which can enable the device for providing sensing services to determine the current sensing scenario, and further can determine the corresponding sensing algorithm based on the obtained sensing scenario, so as to implement sensing.

[0039] The methods described in the first aspect and the second aspect include one or more of the following possible implementation manners:

[0040] In some possible implementation manners, the first sensing scenario is the physiological feature detection scenario, the function type of the target scrambling function is the sine function, the parameter includes the frequency of the sine function, and the frequency of the sine function is within the frequency range corresponding to the physiological activity.

[0041] Optionally, the parameter further includes the amplitude and / or phase of the sine function.

[0042] Exemplarily, the frequency range corresponding to the physiological activity may include the frequency range corresponding to breathing, the frequency range corresponding to heartbeat, or the frequency range corresponding to other physiological activities.

[0043] Exemplarily, when the type of the target scrambling function is the sine function, the target scrambling function θ(t) satisfies:

[0044]

[0045] where F q ∈[F l1 , F l2 , [F l1 , F l2 represents the frequency range corresponding to the physiological activity, F q is a frequency value randomly selected within the frequency range of [F l1 , F l2 , and is a real number.

[0046] Optionally, the amplitude A may be equal to π.

[0047] Optionally, the initial phase may be equal to 0.

[0048] When A = π, , the target scrambling function θ(t) satisfies: θ(t) = πcos(2πF q t).

[0049] In some possible implementation manners, the first sensing scenario is the physiological feature detection scenario, the type of the target scrambling function is the 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, and the frequency of each sine function is within the frequency range corresponding to the physiological activity.

[0050] Optionally, the parameter further includes the amplitude and / or phase of at least one sine function in the linear combination of sine functions.

[0051] 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.

[0052] For the description of the frequency range corresponding to the physiological activity, reference can be made to the previous description, which will not be elaborated here.

[0053] Exemplarily, when the type of the target scrambling function is a linear combination of sine functions, the target scrambling function θ(t) satisfies:

[0054]

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

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

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

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

[0059] In some possible implementation manners, the first sensing 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 above double sine function is a linear combination of two sine functions with different frequencies, and the frequencies of the two sine functions respectively belong to the frequency ranges corresponding to different physiological characteristics.

[0061] Optionally, the parameter further includes 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 can be understood that if the biological presence detection scenario also includes the detection of other physiological characteristics, the double sine function can be replaced by a triple sine function, which includes the first sine function, the second sine function, and a third sine function, and the frequency of the third sine function is the frequency range corresponding to the other physiological characteristics. Among them, the third sine function can include at least one sine function, and the frequencies of at least one sine function are respectively within the frequency ranges corresponding to different physiological characteristics.

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

[0064]

[0065] where F a1 ∈[F m1 , F m2 , [F m1 , F m2 represents the frequency range corresponding to breathing, F a1 is a frequency value randomly selected within the frequency range of [F m1 , F m2 , F b1 ∈[F n1 , F n2 , [F n1 , F n2 represents the frequency range corresponding to heartbeat, F b1 is a frequency value randomly selected within the frequency range of [F n1 , F n2 , q Fa1 and q Fb1 are both non-zero real numbers, and are both real numbers.

[0066] It can be understood that in this double sine function, the initial phases of the two sine functions can be the same or different.

[0067] 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:

[0068] It can also be understood that in this double sine function, the amplitudes of the two sine functions can be the same or different.

[0069] In some possible implementations, the first sensing scenario is the biological presence detection scenario, the type of the target scrambling function is a linear combination of two sets of sine functions, and the parameters include the frequency of each sine function in the linear combination of the two sets of sine functions, and the number of sine functions included in each set of sine functions; the linear combination of the two sets of sine functions includes a first set of sine functions and a second set of sine functions, the frequency of each sine function in the first set of sine functions is within the frequency range corresponding to breathing, and the frequency of each sine function in the second set of sine functions is within the frequency range corresponding to heartbeat.

[0070] Optionally, the parameters further include the amplitude and / or phase of each sine function.

[0071] Similar to the double sine function mentioned above, the linear combination of the two sets of sine functions is a linear combination of sine functions in two different frequency ranges. Similarly, if the biological presence detection scenario also includes the detection of other physiological characteristics, the two sets of sine functions can be further extended to a linear combination of more sets of sine functions, and the frequencies of different sets of sine functions in the linear combination of the more sets of sine functions belong to the frequency ranges corresponding to different physiological characteristics respectively.

[0072] Exemplarily, when the target scrambling function is a linear combination of the two sets of sine functions, the target scrambling function θ(t) satisfies:

[0073]

[0074] where, F ai ∈[F m1 ,F m2 , [F m1 ,F m2 represents the frequency range corresponding to breathing, F ai is a frequency value randomly selected within [F m1 ,F m2 , F bi ∈[F n1 ,F n2 , [F n1 ,F n2 represents the frequency range corresponding to heartbeat, F bi is a frequency value randomly selected within the frequency range of [F n1 ,F n2 , and are both non-zero real numbers, n a and n b are both integers greater than 1, and are both real numbers.

[0075] It can be understood that among the (n a +n b ) sine functions included in the linear combination of the above two groups of sine functions, the initial phases of any two sine functions can be the same or different.

[0076] Exemplarily, when the initial phases of the (n a +n b ) sine functions are all 0, the target scrambling function θ(t) satisfies:

[0077] It can also be understood that among the (n a +n b ) sine functions included in the linear combination of the above two groups of sine functions, the amplitudes of any two sine functions can be the same or different.

[0078] In some possible implementation manners, the first sensing 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 parameter is the S random numbers, and S is an integer greater than 1.

[0079] Among them, the interpolation algorithm includes a cubic Hermite interpolation algorithm, or other types of interpolation algorithms, which are not limited in this application.

[0080] Exemplarily, S satisfies:

[0081]

[0082] Among them, F max is the maximum value of the maximum Doppler frequency shift caused by various actions to be recognized, the value of F max is determined by the sensing scenario and the 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 Μ is an integer greater than 1.

[0083] In some possible implementation manners, the method further includes: obtaining the target scrambling function based on the type of the target scrambling function and the parameter.

[0084] Exemplarily, the function form of the target scrambling function can be obtained based on the type of the target scrambling function; other parameters in the function form except the independent variable and the dependent variable can be determined based on the parameter, so that the target scrambling function can be obtained.

[0085] In a third aspect, the present application provides a communication device. This communication device can be used in the first device of the first aspect, or this communication device can be used in the second device of the second aspect. The communication device includes modules or units for implementing the methods in any of the above aspects and any possible implementation manners in any of the above aspects. The module or unit can be a hardware circuit, software, or a combination of a hardware circuit and software. Exemplarily, each module or unit can implement the corresponding function by executing a computer program.

[0086] In a fourth aspect, the present application provides a communication device, including a processor, where the processor is configured to execute the methods described in any of the above aspects and any possible implementation manners in any of the above aspects.

[0087] The device 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 methods described in the above aspects can be implemented.

[0088] The device may further include a communication interface for communicating the device with other devices. Exemplarily, the communication interface can be a transceiver, a circuit, a bus, a module, or other types of communication interfaces.

[0089] In a fifth aspect, the present application provides a chip system, which includes at least one processor for supporting the implementation of the functions involved in any of the above aspects and any possible implementation manners in any of the above aspects. For example, for receiving or processing the data and / or information involved in the above methods.

[0090] In a possible design, the chip system further includes a memory for storing program instructions and data, and the memory is located inside or outside the processor.

[0091] The chip system can be composed of chips or can include chips and other discrete devices.

[0092] In a sixth aspect, the present application provides a computer-readable storage medium, including a computer program, which when running on a computer, enables the computer to implement the methods in any of the above aspects and any possible implementation manners in any of the above aspects.

[0093] In a seventh aspect, the present application provides a computer program product, where the computer program product includes: a computer program (which can also be referred to as code or instructions), and when the computer program is run, it enables the computer to execute the methods in any of the above aspects and any possible implementation manners in any of the above aspects.

[0094] In an eighth aspect, the present application provides a communication system, including the aforementioned first device and second device. Among them, the first device is used to implement the method in the first aspect and any possible implementation manner in the first aspect, and the second device is used to implement the method in the second aspect and any possible implementation manner in the second aspect.

[0095] It should be understood that the third aspect to the eighth aspect of the present application correspond to the technical solutions of the first aspect or the second aspect of the present application, and the beneficial effects obtained by each aspect and the corresponding feasible implementation manners are similar, and will not be elaborated here. Description of the Drawings

[0096] Figure 1 is a schematic architecture diagram of a communication system applicable to the method provided in the embodiment of the present application;

[0097] Figure 2 is a schematic diagram of an application scenario applicable to the method provided in the embodiment of the present application;

[0098] Figure 3 and Figure 4 is a schematic flowchart of the communication method provided in the embodiment of the present application;

[0099] Figure 5 is a schematic diagram of the influence of the scrambling function designed for the physiological feature detection scenario provided in the present application on the perception result;

[0100] Figure 6 and Figure 7 is a schematic diagram of the influence of the scrambling function designed for the human presence scenario provided in the present application on the perception result;

[0101] Figure 8 is a schematic diagram of the dispersion of a relatively large impact provided in the embodiment of the present application into a frequency range;

[0102] Figure 9 is a schematic diagram of the influence of the scrambling function designed for the activity recognition scenario provided in the embodiment of the present application on the perception result;

[0103] Figure 10 and Figure 11 is a schematic block diagram of the device provided in the embodiment of the present application. Detailed Embodiments

[0104] Next, the technical solutions in the present application will be described with reference to the drawings.

[0105] To facilitate the understanding of the embodiments of the present application, the following points are first explained:

[0106] First, in the embodiments of the present application, the use of prefix words such as "first" and "second" is only for facilitating the differential description of different things belonging to the same name category, and does not restrict the order, size, or quantity of things. For example, "the first device" and "the second device" are merely different devices, and do not limit the quantity or the high-low relationship of priorities of the devices; for another example, "the first signal" and "the second signal" are merely different signals, and there is no relationship of time sequence, size, or high-low relationship of priorities between the two.

[0107] Second, "send" and "receive" in the embodiments of the present application represent the direction of signal transmission. For example, "sending the first information to the second device" can be understood as the destination of the information being the second device, which may include directly sending through the air interface, and also includes indirectly sending through the air interface by other units or modules. "Receiving the third information from the second device" can be understood as the source of the configuration information being the second device, which may include directly receiving from the second device through the air interface, and may also include indirectly receiving from the second device through the air interface from other units or modules. "Send" can also be understood as "output" of the chip interface, and "receive" can also be understood as "input" of the chip interface.

[0108] In other words, sending and receiving can be carried out between devices. For example, between the first device and the second device; it can also be carried out within a device. For example, sending or receiving between components within a device, between modules, between chips, between software modules, or between hardware modules through a bus, a trace, or an interface.

[0109] It can be understood that before the information is sent from the source to the destination, necessary processing may be performed, such as encoding, modulation, etc. After the destination receives the information from the source, corresponding processing may also be performed, such as decoding, demodulation, etc., so as to interpret the valid information from the source. Similar expressions in the present application can be understood similarly and will not be elaborated here.

[0110] Third, in the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects and indicates that there can be three relationships. For example, A and / or B can indicate: A exists alone, A and B exist simultaneously, or B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship, but it does not exclude the case where the associated objects before and after are in an "and" relationship. The specific meaning can be understood in combination with the context. "At least one (item)" or its similar expressions refer to any combination of these items, including any combination of single item(s) or plural item(s). For example, at least one (item) of a, b, or c can indicate: a, b, c; a and b; a and c; b and c; or a, b, and c. Where a, b, and c can be single or multiple.

[0111] Fourth, in the embodiments of the present application, "indicate" can include direct indication and indirect indication, and can also include explicit indication and implicit indication. If the information indicated by a certain piece of information (such as the indication information described below) is called the information to be indicated, then in the specific implementation process, there are many ways to indicate the information to be indicated. For example, but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated, etc. The information to be indicated can also be indirectly indicated by indicating other information, where there is an association relationship between the other information and the information to be indicated; it is also possible to only indicate a part of the information to be indicated, while the other parts of the information to be indicated are known or pre-agreed. For example, the arrangement order of each piece of information pre-agreed (such as protocol pre-definition) can be used to indicate specific information, thereby reducing the indication overhead to a certain extent. The present application does not limit the specific manner of indication.

[0112] 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.

[0113] Fifth, the tables in the embodiments of the present application are only examples. The values of the information in each table are only for illustration and can be configured as other values, which are not limited by the present application. Each table does not limit the protection scope 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 each table can also use other names understandable by the communication device, and the value or representation method of its parameters can also use other values or representation methods understandable 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 maps, etc.

[0114] Sixth, in the embodiments of the present application, descriptions such as "when...", "in the case of...", "if", and "when" all refer to the situation where the device (e.g., the first device or the second device) will perform corresponding processing under a certain objective situation, which does not limit the time, and it is not required that the device must have a judgment action when implemented, nor does it mean the existence of other limitations.

[0115] Seventh, the predefined in the present application can be understood as: define, pre-define, store, pre-store, pre-negotiate, pre-configure, solidify, or pre-burn.

[0116] The technical solution provided by the present 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), Sidelink (SL) communication system, 5th 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).

[0117] The technical solution provided by the present application can also be applied to communication systems evolved after 5G, such as the 6th generation (6G) mobile communication system, etc. The present application does not limit this.

[0118] The Radio Access Network (RAN) device in the present application is a device with wireless transceiver functions. The RAN device can provide wireless communication function services and can connect the terminal to the wireless network. The RAN device can be a node in the radio access network, abbreviated as RAN node.

[0119] In a possible scenario, the RAN node can be a base station (BS), evolved NodeB (eNodeB), transmission reception point (TRP), home evolved NodeB (or home Node B, HNB), access point (AP) of wireless fidelity (Wi-Fi), mobile switching center, next-generation NodeB (gNB) in a 5G mobile communication system, next-generation NodeB in a 6G mobile communication system, or a base station in a future mobile communication system, etc. The RAN node can also be a device that undertakes the function of a base station in a device-to-device (D2D) communication system, vehicle-to-everything (V2X) communication system, machine-to-machine (M2M) communication system, and Internet of Things (IoT) communication system, etc. The RAN node can also be an RAN node in a non-terrestrial network (NTN), that is, the RAN node can be deployed on a high-altitude platform or a satellite. The RAN node can be a macro base station, a micro base station or an indoor station, or a relay node or a donor node, etc., or a radio controller in a cloud radio access network (CRAN) scenario, a node in an open radio access network (O-RAN or ORAN) scenario, etc. Optionally, the RAN node can also be a server, a wearable device, a vehicle or an in-vehicle device, etc. For example, the RAN node in V2X technology can be a road side unit (RSU). Of course, the RAN node can also be a node in the core network.

[0120] In another possible scenario, multiple RAN nodes cooperate to assist a terminal in achieving wireless access, and different RAN nodes respectively implement partial functions of a base station. For example, the RAN node can be a central unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU), etc. The CU and the DU can be set separately, or can also be included in the same network element, such as a baseband unit (BBU). The RU can be included in a radio frequency device or a radio frequency unit, such as included in a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH).

[0121] In different systems, the CU (or CU-CP and CU-UP), DU, or RU may also have different names, but those skilled in the art can understand their meanings. For example, in the ORAN system, the CU can also be called an open CU (O-CU), the DU can also be called an open DU (O-DU), the CU-CP can also be called an open CU-CP (O-CU-CP), the CU-UP can also be called an open CU-UP (O-CU-UP), and the RU can also be called an open RU (O-RU).

[0122] Among them, any one of the 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 to say, the radio access network device in this application can be a virtualized device. For example, it can be implemented through general hardware and instantiated virtualization functions, or through dedicated hardware and instantiated virtualization functions. Among them, the general hardware can be a server, such as a cloud server.

[0123] The terminal in this application can also be called a user equipment (UE), an access terminal, a user unit, a user station, a mobile station, a mobile platform, a remote station, a remote terminal, a mobile device, a user terminal, a terminal device, a wireless communication device, a user agent, or a user device.

[0124] A terminal can be a device that provides voice / data connectivity to users. For example, it can be a handheld device, a vehicle-mounted device, etc. with wireless connection capabilities. Currently, some examples of terminal devices can be: mobile phone, pad, computer with wireless transceiver function (such as laptop, palmtop computer, etc.), mobile internet device (MID), virtual reality (VR) device, augmented reality (AR) device, intelligent point of sale (POS) machine, customer-premises equipment (CPE), wireless terminal in industrial control, wireless terminal in self-driving, drone, terminal device in IoT system, wireless terminal in remote medical, wireless terminal in smart grid, wireless terminal in transportation safety, wireless terminal in smart city, wireless terminal in smart home, cellular phone, cordless phone, session initiation protocol (SIP) phone, wireless local loop (WLL) station, personal digital assistant (PDA), handheld device with wireless communication function, computing device or other processing device connected to a wireless modem, vehicle-mounted device, wearable device, terminal device in 5G network or terminal device in a future evolved public land mobile network (PLMN), etc.

[0125] Among them, wearable devices can also be called wearable intelligent devices, which is the general term for devices developed by applying wearable technology to the intelligent design of daily wear, such as glasses, gloves, watches, clothing, shoes, etc. Wearable devices are portable devices that are either directly worn on the body or integrated into the user's clothes or accessories. Wearable devices are not only a kind of hardware device, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable intelligent devices include those with complete functions and large sizes that can achieve complete or partial functions without relying on a smartphone, such as smart watches or smart glasses, etc., and those that only focus on a certain type of application function and need to cooperate with other devices such as smartphones, such as various smart bracelets and smart jewelry for physical sign monitoring.

[0126] In addition, the terminal device may further include sensors such as intelligent printers, train detectors, and gas stations. The main functions include collecting data (for some terminal devices), receiving control information and downlink data from the network device, and transmitting electromagnetic waves to transmit uplink data to the network device.

[0127] The terminal in this application can be a virtualized device. For example, it can be implemented through general-purpose hardware and instantiated virtualization functions, or through dedicated hardware and instantiated virtualization functions. Among them, the general-purpose hardware can be a server, such as a cloud server.

[0128] It should be understood that this application does not limit the specific forms of the radio access network device and the terminal device.

[0129] Figure 1 It is a schematic diagram of the architecture of the communication system 100 applicable to the method provided in the embodiments of this application. As Figure 1 shown, the communication system 100 includes a radio access network 10 and a core network 20. Optionally, the communication system 100 may further include the Internet 30. Among them, the radio access network 10 may include at least one radio access network device (such as Figure 1 110a and 110b in Figure 1 ), and may also include at least one terminal (such as

[0130] 120a - 120j in

[0131] The terminal can be connected to the radio access network device wirelessly. The radio access network device can be connected to the core network wirelessly or wiredly. The core network device and the radio access network device can be independent and different physical devices, or the functions of the core network device and the logical functions of the radio access network device can be integrated on the same physical device, or the functions of part of the core network device and part of the radio access network device can be integrated on a physical device. Terminals and terminals, as well as radio access network devices and radio access network devices, can be connected to each other wiredly or wirelessly.

[0132] Among them, the radio access network device can be a base station deployed in the air, such as a satellite base station 110a; or it can be a base station deployed indoors, such as a micro base station or an indoor station 110b.

[0133] The terminal can be a terminal deployed in the air, such as Figure 1 the helicopter or drone 120i in Figure 1 ; or it can be a terminal deployed on the ground, such as

[0134] the mobile phones 120a, 120e, 120f, and 120j, the vehicle 120b, the computer 120g, the printer 120h, etc. in

[0135] The roles of the radio access network device and the terminal can be relative. For example, Figure 1 the helicopter or drone 120i in Figure 1 can be configured as a mobile base station. For 120j that accesses the radio access network 10 through 120i, 120i is a base station; but for 110a, 120i is a terminal, that is, the communication between 110a and 120i is through the radio air interface protocol. Of course, the communication between 110a and 120i can also be through the interface protocol between radio access network devices. At this time, relative to 110a, 120i is also a base station. Therefore, the radio access network device and the terminal can both be uniformly referred to as communication devices,

[0136] It should be understood that Figure 1 this is only a schematic diagram, and other devices can also be included in this communication system, such as wireless relay devices and wireless backhaul devices, which are not drawn in Figure 1 ;

[0137] Figure 2 This is a schematic diagram of a sensing scenario applicable to the method provided in the embodiments of the present application. As Figure 2As shown, in the communication environment between a transmitter and a receiver, there is a stationary human, walls, floors, etc. The transmitter sends a signal to the receiver. This signal can be transmitted through the line of sight (LOS) path, the non-line of sight (NLOS) path, or reach the receiver through reflection from walls and floors. When the receiver accesses the signal from the transmitter and performs channel estimation based on the received signal, it can then analyze the user-related information or environmental information existing in this communication environment based on the measured channel state information.

[0138] Among them, Figure 2 the receiver and transmitter shown can be Figure 1 the terminals or access network devices shown. For example, the transmitter is an access network device and the receiver is a terminal; or, the transmitter is a terminal and the receiver is an access network device.

[0139] For ease of understanding, first, a brief introduction to the relevant concepts involved in this application is given.

[0140] 1. Sensing: It refers to using the changes in wireless signals during propagation to obtain the characteristics of the signal propagation space and thereby infer information related to the environment or users (such as people and objects existing in the environment). For example, by measuring the channel to obtain CSI or CIR, sensing is achieved based on this.

[0141] 2. Physiological feature detection: It is the monitoring of, for example, the breathing rate or heart rate of an organism.

[0142] 3. Biological presence detection: It detects whether there are organisms in the environment, mainly divided into moving presence detection and stationary presence detection.

[0143] Among them, stationary presence detection mainly uses the detection of physiological feature information such as the breathing and heart rate of organisms to determine whether there are organisms in the environment. Moving presence detection determines whether there is a moving target based on the difference in the spectrum between motion and rest, and its essence is the same as activity detection. The biological presence detection in this application refers to stationary presence detection.

[0144] 4. Activity detection: It detects the different activity behaviors of organisms existing in the environment.

[0145] In wireless systems, some special "measurement" signals (e.g., reference signals) are commonly used for sensing, and such signals have a publicly known signal structure. When a transmitter performs sensing measurements by sending such signals, it may cause all receivers in the communication system that can receive such signals to be able to obtain sensing results based on the measurements of such signals. However, in some sensing scenarios, users only want the authorized transceiver pair (i.e., the transceiver ends authorized to perform sensing measurements) to obtain accurate sensing results, and unauthorized users cannot obtain correct sensing results. Therefore, if sensing measurements are still based on the current "measurement" signals, it may cause unauthorized users to obtain accurate sensing results, thereby leading to the leakage of user privacy.

[0146] In view of this, embodiments of the present application provide a communication method and related devices. In this method, the sending end scrambles a plurality of sensing signals to be sent through a scrambling function, and shares the scrambling function at the authorized transceiver ends. In this way, after receiving the signals, the authorized receiving end can perform channel estimation based on the pre-shared scrambling function and the received signals, and then obtain relevant information of the user. However, the scrambling function is unknown to unauthorized devices. Therefore, unauthorized devices can only perform channel estimation based on the received signals and cannot obtain relevant information of the user, thus realizing the protection of user privacy.

[0147] The following combines Figure 3 and Figure 4 , and details the communication method provided by the embodiments of the present application. The method provided by the present application can be applied to the network architecture shown in Figure 1 , but the embodiments of the present application are not limited thereto.

[0148] In Figure 3 and Figure 4 shown in the flowchart, the method is shown from the perspective of the interaction of communication devices, but the present application does not limit the execution entity of the method. For example, Figure 3 and Figure 4 The first device in can be a terminal device or an access network device, or the first device is a component (such as a chip, a chip system, or a processor) configured in a terminal device or an access network device, and can also be a logic module or software that can implement all or part of the functions of the first device; Figure 3 and Figure 4 The second device in can be a terminal device or an access network device, or the second device is a component (such as a chip, a chip system, or a processor) configured in a terminal device or an access network device, and can also be a logic module or software that can implement all or part of the functions of the second device.

[0149] Figure 3 is a schematic flowchart of the communication method 300 provided by the embodiments of the present application. As shown in Figure 3As shown, the method 300 may include S301 to S303. Each step in the method 300 will be introduced in detail below.

[0150] S301, a first device generates a first signal and a second signal. Among them, 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.

[0151] Among them, the predefined scrambling function is a time-varying function with a low-pass characteristic. This scrambling function can be used as an encryption parameter and shared by the authorized transceiver parties. For example, an encryption algorithm can be used to encrypt the information field indicating the type and generation method of the scrambling function, the parameters of the scrambling function, or the sampled values of the scrambling function, so that both the transceiver parties can obtain the scrambling function.

[0152] It can be understood that the first device can also generate M (M is an integer greater than or equal to 2) signals, and at least two signals among the M signals satisfy the relationship between the above-mentioned first signal and the second signal.

[0153] S302, the first device outputs the first signal and the second signal. Among them, the first signal is sent through the first antenna corresponding to the first device, and the second signal is sent through the second antenna corresponding to the first device.

[0154] Among them, the first antenna and the second antenna can be antennas deployed on the first device (that is, the first device includes a radio frequency unit); or, the first antenna and the second antenna are antennas corresponding to the first device (that is, the first device does not include a radio frequency unit).

[0155] Exemplarily, when the radio frequency unit is not deployed in the first device (for example, the first device is a baseband unit), S403 can be replaced with: the first device outputs the first signal and the 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.

[0156] Exemplarily, when the radio frequency unit is deployed in the first device (for example, the first device includes a baseband unit and a radio frequency unit), S403 can be replaced with: the first device sends the first signal through the first antenna included in the first device, and sends the second signal through the second antenna included in the first device.

[0157] S303, a second device obtains a sensing result based on the predefined scrambling function and the received signal.

[0158] In an embodiment of the present application, the first device sends multiple sensed signals scrambled by a predefined scrambling function to the second device, so that the second device performs channel measurement based on the received signals and the predefined target scrambling function to obtain a sensing result. Since the scrambling function is shared only by the authorized transceiver parties (which can be understood as the devices providing sensing services), only the authorized transceiver parties can obtain accurate sensing results and acquire user information. For unauthorized devices, the scrambling function is unknown, so they cannot obtain accurate channel state information and thus cannot acquire relevant user information, achieving the protection of user privacy.

[0159] Figure 4 It is a schematic flowchart of a communication method 400 provided by an embodiment of the present application. As Figure 4 shown, the method 400 may include S401 to S404. The following details each step in the method 400.

[0160] S401, the first device and the second device determine the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function.

[0161] Wherein, the first sensing scenario is the scenario to be sensed. When the to-be-sensed scenarios are different, the type and parameters of the target scrambling function determined by the first device and the second device are also different. That is, different sensing scenarios correspond to different types and parameters of scrambling functions.

[0162] The first sensing scenario may be one of the following multiple sensing scenarios: a physiological feature detection scenario, a biological presence detection scenario, or an activity recognition scenario; wherein, the physiological feature detection scenario is a scenario for detecting physiological feature parameters, the biological presence detection scenario is a scenario for detecting whether there is a biological in the environment, the activity recognition scenario is a scenario for detecting biological activities, etc. It should be understood that the first sensing scenario may also be other scenarios that need to be sensed.

[0163] The type of the target scrambling function may be one of the following multiple 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.

[0164] It can be 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 elaborated here for the time being.

[0165] S402, the first device generates a first signal and a second signal. The second signal is obtained by phase-adjusting the first signal based on a target scrambling function, and the target scrambling function is determined based on the type and parameters of the target scrambling function.

[0166] It can be understood that the first device can also generate M (M is an integer greater than or equal to 2) signals, and at least two signals satisfying the relationship between the first signal and the second signal are included among the M signals.

[0167] S403, the first device outputs the first signal and the second signal. Among them, the first signal is sent through the first antenna corresponding to the first device, and the second signal is sent through the second antenna corresponding to the first device.

[0168] This process can refer to the description in S302 above and will not be elaborated here.

[0169] S404, the second device obtains a sensing result based on the target scrambling function and the received signal.

[0170] Similarly, the second device includes a radio frequency unit or does not include a radio frequency unit.

[0171] Exemplarily, the second device obtains a sensing 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 sensing result based on the measurement result.

[0172] Exemplarily, when the second device corresponds to N antennas (or corresponds to N antennas, N is an integer greater than 0), the signal received by the second device refers to the signals received through the N antennas respectively. It can be understood that the signal received by the i-th (i takes values of 1, 2, 3,..., N) antenna among the N antennas refers to: the first signal sent by the first device through the first antenna after passing through the first channel and the second signal sent by the first device through the second antenna after passing through the second channel.

[0173] Among them, the first channel is the channel between the first antenna and the i-th antenna, and the second channel is the channel between the second antenna and the i-th antenna.

[0174] Optionally, after S404, the method 400 further includes: the second device sends the sensing result to the first device. Correspondingly, the first device receives the sensing result.

[0175] In the embodiments of the present application, the first device and the second device pre-determine the target scrambling function corresponding to the to-be-sensed scenario through the type of the scrambling function corresponding to the to-be-sensed scenario 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 based on the received signals and the determined target scrambling function to obtain the sensing result. Since the type of the scrambling function and the parameters included in the scrambling function are only shared between the first device and the second device, only the authorized transceiver parties can obtain the correct channel state information, and thus obtain an accurate sensing result. However, unauthorized devices cannot obtain the correct channel state information because they do not know the scrambling function, and thus cannot obtain the relevant information of the user, realizing the protection of user privacy.

[0176] In a possible implementation, the ratio of the first signal to the second signal is proportional to e jθ(t) or the ratio of the first signal to the second signal is inversely proportional to e jθ(t) , where θ(t) is the target scrambling function.

[0177] Exemplarily, the following relationship is satisfied between the first signal and the second signal:

[0178]

[0179] where Q 1 (t) is the first signal, Q 2 (t) is the second signal, and k is a non-zero real number. For example, k = 1 or -1.

[0180] In a possible implementation, when the first sensing 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 sensing 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 sets of sine functions; when the first sensing 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.

[0181] In a possible implementation, the same sensing scenario can correspond to multiple types of scrambling functions, and the first device and the second device can determine the type of the target scrambling function corresponding to the first sensing scenario through mutual negotiation.

[0182] In a possible implementation, the first device can determine the type of the target scrambling function corresponding to the first sensing scenario based on the first mapping relationship; and send the first information to the second device, where the first information indicates the type of the target scrambling function. Correspondingly, the second device receives the first information and determines the type of the target scrambling function corresponding to the first sensing scenario based on the first information.

[0183] Optionally, after the second device receives the first information, based on the first mapping relationship, it re-determines the type of the target scrambling function corresponding to the first sensing scenario; and according to the re-determined type of the target scrambling function corresponding to the first sensing scenario, it updates the first information 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 sensing scenario based on this information.

[0184] In a possible implementation, the second device can determine the type of the target scrambling function corresponding to the first sensing scenario based on the first mapping relationship; and send the 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 sensing scenario based on this information.

[0185] Optionally, after the first device receives the first information, based on the first mapping relationship, it re-determines the type of the target scrambling function corresponding to the first sensing scenario; and according to the re-determined type of the target scrambling function corresponding to the first sensing scenario, it updates the first information and sends the updated first information to the second device. Correspondingly, the second device receives the updated first information and re-determines the type of the target scrambling function corresponding to the first sensing scenario based on this information.

[0186] Wherein, the above first mapping relationship indicates the type of at least one scrambling function corresponding to each sensing scenario in multiple sensing scenarios.

[0187] Exemplarily, the type of the target scrambling function can be indicated by an index corresponding to the type of the target scrambling function. For example, the first information includes the index corresponding to the type of the target scrambling function.

[0188] The first information in this application is transmitted in an encrypted manner, and the encryption key is only shared between authorized transceiver devices.

[0189] 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 sets of sine functions, the parameter includes the frequency of each sine function in the linear combination of the two sets of sine functions and the number of sine functions included in each set 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.

[0190] In a possible implementation, after determining the type of the target scrambling function, the first device and the second device may determine the parameters included in the target scrambling function corresponding to the first sensing scenario based on the second mapping relationship, where the second mapping relationship indicates a set of parameters corresponding to each type of scrambling function among multiple types of scrambling functions.

[0191] In another possible implementation, after determining the type of the target scrambling function, the first device determines the parameters included in the target scrambling function based on the type of the target scrambling function; and sends second information to the second device, where the second information indicates the parameters included in the target scrambling function. Correspondingly, the second device receives the second information or the third information, and determines the parameters included in the target scrambling function based on the second information or the third information.

[0192] Optionally, after determining the type of the target scrambling function, the second device determines the parameters included in the target scrambling function based on the type of the target scrambling function; and sends second information to the first device, where the second information indicates the parameters included in the target scrambling function. Correspondingly, the first device receives the second information or the third information, and determines the parameters included in the target scrambling function based on the second information or the third information.

[0193] In another possible implementation, after determining the type of the target scrambling function, the first device determines the parameters included in the target scrambling function based on the type of the target scrambling function; and sends third information to the second device, where the third information indicates the generation algorithm (e.g., linear congruential algorithm, Mersenne Twister algorithm) of the parameters included in the target scrambling function. Correspondingly, the second device receives the third information, and determines the parameters included in the target scrambling function based on the third information.

[0194] Optionally, after determining the type of the target scrambling function, the second device determines the 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 the generation algorithm of 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.

[0195] Similar to the foregoing, since the same sensing scenario may 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 the target scrambling function corresponding to the first sensing scenario, the two parties may determine the parameters included in the target scrambling function through negotiation.

[0196] In a possible implementation, the first device may determine the parameters included in the target scrambling function corresponding to the first sensing scenario based on the third mapping relationship; and send the second information to the second device. Correspondingly, the second device receives the second information and determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the second information.

[0197] Optionally, after receiving the second information, the second device re-determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the third mapping relationship; and updates the second information according to the re-determined parameters included in the target scrambling function corresponding to the first sensing scenario, and sends the updated second information to the first device. Correspondingly, the first device receives the updated second information and re-determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the information.

[0198] In a possible implementation, the second device may determine the parameters included in the target scrambling function corresponding to the first sensing scenario based on the third mapping relationship; and send the second information to the first device. Correspondingly, the first device receives the second information and determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the second information.

[0199] Optionally, after receiving the second information, the first device re-determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the third mapping relationship; and updates the second information according to the re-determined parameters included in the target scrambling function corresponding to the first sensing scenario, and sends the updated second information to the second device. Correspondingly, the second device receives the updated second information and re-determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the information.

[0200] Wherein, the above-mentioned third mapping relationship indicates at least one set of parameters corresponding to each sensing scenario in multiple sensing scenarios.

[0201] In a possible implementation, the first device may determine the generation algorithm of the parameters included in the target scrambling function corresponding to the first sensing scenario based on the fourth mapping relationship; and send the third information to the second device. Correspondingly, the second device receives the third information and determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the third information.

[0202] Optionally, after receiving the second information, the second device re-determines the generation algorithm of the parameters included in the target scrambling function corresponding to the first sensing scenario based on the fourth mapping relationship; and updates the second information according to the re-determined parameters included in the target scrambling function corresponding to the first sensing scenario, and sends the updated second information to the first device. Correspondingly, the first device receives the updated third information and re-determines the parameters included in the target scrambling function corresponding to the first sensing scenario based on the information.

[0203] In a possible implementation, the second device may determine, based on the fourth mapping relationship, a generation algorithm for parameters included in the target scrambling function corresponding to the first sensing scenario; and send third information to the first device. Correspondingly, the first device receives the third information and determines, based on the third information, parameters included in the target scrambling function corresponding to the first sensing scenario.

[0204] Optionally, after receiving the second information, the first device re-determines, based on the fourth mapping relationship, a generation algorithm for parameters included in the target scrambling function corresponding to the first sensing scenario; and updates the second information according to the re-determined parameters included in the target scrambling function corresponding to the first sensing scenario, and sends the updated second information to the second device. Correspondingly, the second device receives the updated third information and re-determines, based on the information, parameters included in the target scrambling function corresponding to the first sensing scenario.

[0205] Wherein, the fourth mapping relationship indicates at least one set of generation algorithms corresponding to each sensing scenario among multiple sensing scenarios, and each generation algorithm in the at least one set of generation algorithms is used to generate a parameter.

[0206] In this application, the second information and the third information are transmitted in an encrypted manner, and the encryption key is shared only between authorized transceiver devices.

[0207] It can be understood that the first information and the second information may be sent simultaneously, for example, carried on the same signaling. Or the first information and the second information are sent separately, for example, carried on different signaling. This application does not make any limitations in this regard.

[0208] Similarly, the third information and the first information may be sent simultaneously, or the third information and the first information are sent separately.

[0209] Optionally, before S401, the method 400 further includes: the first device and the second device determine that the scene to be sensed is the first sensing scene.

[0210] The first device and the second device may determine the specific sensing scene through negotiation.

[0211] In a possible implementation manner, the first device determines that it is necessary to sense physiological characteristics; and sends fourth information to the second device, where the fourth information indicates that the scene to be sensed is a physiological characteristic detection scene. Correspondingly, the second device determines whether it can sense physiological characteristics based on the fourth information.

[0212] If the second device can sense physiological characteristics, it determines that the scene to be sensed is a physiological characteristic detection scene.

[0213] If the second device is unable to 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.

[0214] In another possible implementation, the second device determines that it is necessary to sense the physiological feature; and sends the fourth information to the first device, where the fourth information indicates that the scene to be sensed is the physiological feature detection scene. Correspondingly, the first device determines whether it is able to sense the physiological feature based on the fourth information.

[0215] If the first device is able to sense the physiological feature, it determines that the scene to be sensed is the physiological feature detection scene.

[0216] If the first device is unable to 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.

[0217] 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.

[0218] Exemplarily, the function form of the target scrambling function can be obtained based on the type of the target scrambling function; other parameters in the function form except the independent variable and the dependent variable can be determined based on the parameters included in the target scrambling function, so that the target scrambling function can be obtained.

[0219] For example, when the type of the target scrambling function is a sine function, the function form of the target scrambling function can be determined as: Except for the independent variable x and the dependent variable y, after knowing the amplitude A, the frequency f, and the phase the target scrambling function can be determined.

[0220] Next, the value range of the parameters included in the target scrambling function corresponding to the first sensing scene, and the corresponding target scrambling function are introduced.

[0221] In a possible implementation, when the first sensing scene is the physiological feature detection scene and 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.

[0222] Wherein, the frequency range corresponding to the physiological activity can be expressed as [F l1 , F l2 .

[0223] Exemplarily, the frequency range corresponding to the physiological activity may be the frequency range corresponding to breathing: 0.1 hertz (Hz) to 0.67 Hz (6 to 40 times per minute), or the frequency range corresponding to the heartbeat: 0.83 Hz to 2.5 Hz (50 to 150 times per minute).

[0224] When the frequency range corresponding to the physiological activity is the breathing frequency range, F l1 may be equal to 0.1 (Hz), and F l2 may be equal to 0.67 (Hz); when the frequency range corresponding to the physiological activity is the heart rate range, F l1 may be equal to 0.83 (Hz), and F l2 may be equal to 2.5 (Hz).

[0225] Exemplarily, the type of the target scrambling function is a sine function, and the target scrambling function θ(t) satisfies:

[0226]

[0227] wherein, F q ∈[F l1 , F l2 , F q is a frequency value randomly selected within the frequency range of [F l1 , F l2 , and A is a non-zero real number.

[0228] Exemplarily, when, the target scrambling function θ(t) satisfies: θ(t) = Acos2πF q t.

[0229] Optionally, A = π. At this time, the obtained scrambling function is θ(t) = πcos2πF q t, which can make the intensity of the false spectral peak at Fq much greater than the intensity of the true spectral peak, that is: the characteristics introduced by the true actions (such as breathing and heartbeat) of the perceived object in the spectrum will be masked by the spectral characteristics introduced by the scrambling function, and privacy is protected.

[0230] 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 may also be a function obtained by changing at least one of the following in formula (2): amplitude, phase, or frequency.

[0231] In a possible implementation, the first sensing scenario is a physiological feature detection scenario. 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.

[0232] It can be understood that the frequencies of any two sine functions in the linear combination of sine functions can be the same or different.

[0233] Regarding the description of the frequency range corresponding to the physiological activity, reference can be made to the previous description, which will not be elaborated here.

[0234] Exemplarily, the type of the target scrambling function is a linear combination of sine functions, and the target scrambling function θ(t) satisfies:

[0235]

[0236] where F qi ∈[F l1 , F l2 , F qi can be a frequency value randomly selected within the frequency range of [F l1 , F l2 , qFqi is a non-zero real number, n a is an integer greater than 1, is a real number.

[0237] It can be understood that among the above n a sine functions, the initial phases of any two sine functions can be the same or different. Among the above n a sine functions, the amplitudes of any two sine functions can be the same or different.

[0238] Exemplarily, when the initial phases of the n a sine functions are all 0, the target scrambling function θ(t) satisfies:

[0239] 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 in formula (3): the amplitude of at least one sine function among the n a sine functions, the phase of at least one sine function among the n a sine functions, or the frequency of at least one sine function among the n a sine functions.

[0240] In a possible implementation, the first sensing scenario is a biological presence detection scenario. When the function type of the target scrambling function is a double sine function, the double sine function includes a first sine function and a second sine function. Among them, 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.

[0241] 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 .

[0242] Regarding the frequency range corresponding to breathing and the frequency range corresponding to the heartbeat, reference can be made to the description above, and details are not repeated here. For example, F m1 can be equal to 0.1 (Hz), and F m2 can be equal to 0.67 (Hz); F n1 can be equal to 0.83 (Hz), and F n2 can be equal to 2.5 (Hz).

[0243] Exemplarily, the function type of the target scrambling function is a double-sine function, and the target scrambling function θ(t) satisfies:

[0244]

[0245] wherein, F a1 ∈[F m1 , F m2 , F a1 can be a frequency value randomly selected within the frequency range of [F m1 , F m2 , F b1 ∈[F n1 , F n2 , F b1 can be a frequency value randomly selected within the frequency range of [F n1 , F n2 , q Fa1 and q Fb1 are both non-zero real numbers, and are both real numbers.

[0246] It can be understood that in this double-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.

[0247] 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:

[0248] It can be understood that when the type of the target scrambling function is a double-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 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.

[0249] In a possible implementation, the first sensing scenario is a biological presence detection scenario, and the type of the target scrambling function is a linear combination of two sets of sine functions. The linear combination of the two sets of sine functions is a linear combination of A first sine functions (the A first sine functions can be referred to as the first set of sine functions) and B second sine functions (the B second sine functions can be referred to as the second set 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. Both A and B are integers greater than 0, but A and B cannot both be equal to 1. When A and B are not both 1, the determined target scrambling function can introduce multiple false spectral peaks, thereby increasing the difficulty for eavesdroppers to guess and achieving better privacy protection effect.

[0250] Among them, the frequency range corresponding to breathing can be expressed as: [F m1 , F m2 , and the frequency range corresponding to heartbeat can be expressed as: [F n1 , F n2 . For example, F m1 can be equal to 0.1 (Hz), and F m2 can be equal to 0.67 (Hz); F n1 can be equal to 0.83 (Hz), and F n2 can be equal to 2.5 (Hz).

[0251] It can be understood that when A is greater than 1, the frequencies of any two of the A first sine functions can be the same or different; when B is greater than 1, the frequencies of any two of the B second sine functions can be the same or different.

[0252] 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:

[0253]

[0254] Among them, F ai ∈ [Fm1, Fm2], F ai is a frequency value randomly selected within [Fm1, Fm2], F bi ∈ [Fn1, Fn2], F bi is a frequency value randomly selected within the frequency range of [Fn1, Fn2], and are both non-zero real numbers, n a and n b are both integers greater than 1, and are both real numbers.

[0255] It can be understood that among the (n a + n b ) sine functions included in the linear combination of the above two sets of 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.

[0256] Exemplarily, when the initial phases of the (n a + n b ) sine functions are all 0, the target scrambling function θ(t) satisfies:

[0257] 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 in formula (5): n a the amplitude of at least one sine function among the n a first sine functions, the frequency of at least one sine function among the n a first sine functions, the phase of at least one sine function among the n b first sine functions, the amplitude of at least one sine function among the n b second sine functions, the phase of at least one sine function among the n b second sine functions, or the frequency of at least one sine function among the n

[0258] In a possible implementation, when the first sensing scenario is an activity recognition scenario, the target scrambling function is obtained by interpolating S random numbers based on an interpolation algorithm. Exemplarily, the number S of the S random numbers used to determine the target scrambling function satisfies:

[0259]

[0260] where F max is the maximum value of the maximum Doppler frequency shift caused by various actions to be recognized, Fmax is determined by the sensing scenario and the carrier frequency, (for example, F max does not exceed a few hundred Hertz), 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 Μ is an integer greater than 1.

[0261] It should be understood that the functions obtained by interpolating the S random numbers based on different interpolation algorithms may be different.

[0262] Since the value of S is related to F max , therefore F maxIt can also be referred to as the parameters included in the target scrambling function corresponding to the activity recognition scenario. Additionally, since the target scrambling functions obtained under different interpolation algorithms may be different, the interpolation algorithm can also be referred to as the parameters included in the target scrambling function corresponding to the activity recognition scenario.

[0263] Exemplarily, based on the above-mentioned perception scenarios, the types of scrambling functions, and the corresponding relationships of the parameters, the corresponding relationship shown in Table 1 can be obtained.

[0264] Table 1

[0265]

[0266] 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.

[0267] The foregoing Method 400 detailed the corresponding relationships among the to-be-perceived scenarios, the types of scrambling functions, and the parameters included in the scrambling functions. Below, taking the example where the first device is equipped with two antennas, the second device is configured with a single antenna, and there is an unauthorized device in the environment, and the unauthorized device is equipped with two antennas, the design methods of the scrambling functions corresponding to the above three perception scenarios will be introduced in detail.

[0268] This application assumes that the signals transmitted by the two antennas of the first device are Q1(t) and Q2(t) respectively, and the unauthorized device performs perception by receiving Q1(t) and Q2(t) transmitted by the first device. Among them, the signals received on the two antennas of the unauthorized device are R1(t) and R2(t) respectively, and R 1 (t) and R 2 (t) satisfy:

[0269]

[0270] Among them, H tiej represents the frequency-domain channel coefficient from the i-th antenna of the first device to the j-th antenna of the unauthorized user. The value of i is 1 and 2, the value of j is 1 and 2, and Q 1 (t) and Q 2 (t) satisfy: That is, in the above formula (1), the value of k is 1.

[0271] Since the unauthorized device does not know Q 1 (t) and Q 2(t), so it is impossible to achieve channel estimation and sensing by using the received signals on each antenna alone. However, an unauthorized device may divide the signals received on the two antennas to eliminate the influence of the encrypted signal.

[0272] Exemplarily, the unauthorized device divides R 1 (t) by R 2 (t) to obtain S(t) satisfies:

[0273]

[0274] If we let in formula (8), we can obtain:

[0275]

[0276] I. The scenario to be sensed is a physiological feature detection scenario.

[0277] In an actual physiological feature detection scenario, Ra i (t) in formula (9) usually consists of a relatively strong DC component (corresponding to a relatively static environment) and a relatively weak time-varying component (corresponding to the minute 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 above-mentioned DC component, and g i ·ω i (t) represents the above-mentioned time-varying component, and the value of i is 1, 2, 3.

[0278] If we substitute Ra i (t) into formula (9), we can obtain:

[0279]

[0280] Since |c i | >> |g i , so

[0281] If we let A1(t) = c1 + g1·ω 1 (t) in formula (11), we can obtain:

[0282] S(t) ≈ A 1 (t)·A 2 (t). Formula (12)

[0283] Continuing the Fourier transform of formula (12), we can obtain:

[0284]

[0285] Since the result of the Fourier transform of A 1 (t) = c 1 + g 1 ·ω 1 (t) is Therefore, the above formula (13) can be equivalently replaced by:

[0286]

[0287] where p 0 refers to the DC component in A 1 (t), refers to the component in A 1 (t) with a frequency of , and F p is the true frequency corresponding to the physiological activity to be detected (e.g., the frequency corresponding to breathing or heartbeat).

[0288] From formula (14), the spectral peak corresponding to the function is F p . Therefore, in order to protect the user's physiological characteristics, the selection of the scrambling function θ(t) should be able to introduce false spectral peaks, that is, the selected θ(t) can make the F corresponding to the maximum value of the function not equal to F p , which means that the selected θ(t) can make hold.

[0289] To introduce false spectral peaks, θ(t) can be determined as a single-frequency function with a frequency of F q (e.g., θ(t) = πcos2πF q t). Let θ(t) = πcos2πF q t, it can be proved that: A 2 (t) ≈ z 0 + Re jθ(t) . At this time, A 2 (t) is a periodic function, and the spectrum of A 2 (t) can be approximated as:

[0290]

[0291] Substituting formula (15) into the above formula (14), we can obtain:

[0292]

[0293] According to the Fourier series formula of the periodic function, q can be calculated. 0 and

[0294]

[0295] where J 0 (x) and J 1 (x) are the Bessel functions of the first kind of order zero and order one respectively. According to the results of mathematical analysis and combined with the fact that in practice |c 2 |≈1, |c 3 |≈1, and |c 3 |≠|c 2 |, it can be obtained that |q 0 | and are roughly equivalent. Also, because so the intensity of the spurious spectral peak at F a is greater than the intensity of the true spectral peak at F p . That is to say, the features introduced by the user's true physiological characteristics (such as breathing and heartbeat) in the frequency spectrum will be masked by the frequency spectrum features introduced by the scrambling function, and the user's physiological characteristics are protected.

[0296] In summary, the scrambling function in this physiological characteristic detection scenario can be: θ(t) = πcos2πF q t.

[0297] To further enhance the protection effect of the user's physiological characteristics, multiple spurious spectral peaks can be introduced within [F l1 , F l2 . For example, the scrambling function can be selected as a linear combination of several single-frequency functions, such as:

[0298] Figure 5 shows a schematic diagram of the influence of the scrambling function designed for the physiological characteristic detection scenario on the perception result. Figure 5 In (a) and (d) of , the modulus of the time-domain waveform of S(t) when θ(t) = 0 and the modulus of the frequency spectrum corresponding to this S(t) are shown respectively. θ(t) = 0 means that the first device does not use the scrambling function to process the sensing signal. When θ(t) = 0, from the characteristics of the modulus of the frequency spectrum shown in (d) of Figure 5 , an unauthorized device can accurately estimate that the breathing frequency is 0.25 Hz.

[0299] Figure 5 In (b) and (e) of , 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 this S(t) are shown respectively. When θ(t) is a random number uniformly distributed within (0, 2π), fromFigure 5 From the characteristics of the modulus of the time-domain waveform shown in (b) in, it can be seen that the time-domain waveform of S(t) is chaotic, but from Figure 5 From the characteristics of the modulus of the spectrum shown in (e) in, it can be seen that the unauthorized device can still accurately estimate the breathing frequency as 0.25 Hz through the analysis of the frequency domain.

[0300] Figure 5 In (c) and (f) in, the scrambling function designed in this application is shown respectively: The modulus of the time-domain waveform of S(t) and the modulus of the spectrum corresponding to this S(t) when When, from Figure 5 From the characteristics of the modulus of the time-domain waveform shown in (c) in, it can be seen that the time-domain waveform of S(t) is chaotic, and from Figure 5 From the characteristics of the modulus of the spectrum shown in (f) in, it can be seen that when introducing the scrambling function (n a = 3) designed in this application in this scenario, three false spectral peaks are introduced, covering up the true breathing frequency, and the unauthorized device cannot estimate the true breathing frequency through the analysis of the frequency domain.

[0301] In summary, the scrambling function designed in this application in the physiological characteristic detection scenario can realize the protection of user information.

[0302] Second, the scenario to be sensed is the biological presence detection scenario. The following mainly takes human presence detection as an example for introduction.

[0303] In the human presence detection scenario, Ra in formula (9) i (t) needs to be replaced with:

[0304] Ra i (t)= c i + 1 {presense} (g i1 ·ω i1 (t)+ g i2 ·ω i2 (t));

[0305] Among them, c i represents the above-mentioned DC component, g i1 ·ω i1 (t) represents the first time-varying component (corresponding to the slight change of the channel caused by breathing), g i ·ω i (t) represents the second time-varying component (corresponding to the slight change of the channel caused by 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. In the context of detecting the presence of humans, when there are humans, the function value is 1; when there are no humans, the function value is 0; ω i1 ω(t) and ω i2 ω(t) are the channel fluctuation parameter terms caused by breathing and heartbeat respectively.

[0306] If Ra i ω(t) = c i +1 {presense} (g i1 ·ω i1 (t) + g i2 ·ω i2 (t)) is substituted into formula (9), the updated S(t) can be obtained:

[0307]

[0308] Since |c i | >> |g ij |, so

[0309] If A 1 (t) in formula (18) is set to c 1 +1 {presense} (g 11 ·ω 11 (t) + g 12 ·ω 12 (t)), the above formula (12) can be obtained.

[0310] The process of obtaining from formula (12) can refer to the analysis processes of formula (13) and formula (14) above. It will not be elaborated here.

[0311] Similarly, the corresponding spectral peak is F b . To ensure that unauthorized devices cannot infer whether there is someone, the scrambling function θ(t) should be selected such that the same false spectral peak can be introduced whether there is someone or no one in the environment, that is, the selected θ(t) can make the function when it reaches the maximum value, the corresponding F is equal to F a1 and F b1 , that is, the selected θ(t) can make: and both hold whether there is someone or no one in the environment.

[0312] Similar to the analysis in the physiological feature detection scenario, the scrambling function in this biological presence detection scenario can be designed as follows:

[0313] Similar to the previous text, to further enhance the effect of user information protection, the scrambling function can be selected as a combination of two sine functions, for example:

[0314] In the human presence detection scenario, after processing the sensing signal with the scrambling function designed in this application, the channel measurement results obtained by the authorized user are as Figure 6 shown. Among them, Figure 6 in (a) is the modulus of the time-domain waveform of S(t), Figure 6 in (b) is the modulus of the spectrum corresponding to this S(t). As can be seen from Figure 6 , in the scenarios of presence and absence of people, the change rules of the modulus of the time-domain waveform of the measured S(t) and the modulus of the spectrum corresponding to this S(t) are completely different. Therefore, the authorized user can determine whether there is anyone in the current environment based on the differences between the channel measurement results obtained in the scenarios of presence and absence of people.

[0315] In the human presence detection scenario, after processing the sensing signal with the scrambling function designed in this application, the channel measurement results obtained by the unauthorized device are as Figure 7 shown. Among them, Figure 7 in (a) is the modulus of the time-domain waveform of S(t), Figure 7 in (b) is the modulus of the spectrum corresponding to this S(t). As can be seen from Figure 7 , in the scenarios of presence and absence of people, the change rules of the modulus of the time-domain waveform of the measured S(t) and the modulus of the spectrum corresponding to this 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 scenarios of presence and absence of people.

[0316] Combining Figure 6 and Figure 7 it can be seen that the scrambling function designed by this application for the human presence detection scenario can achieve the protection of user information without affecting the sensing performance of the authorized user.

[0317] III. The scenario to be sensed is the activity recognition scenario.

[0318] Let in the above formula (9), we can get: S(t) = Ra1(t)·A(t). Formula (19)

[0319] In the activity recognition scenario, in order to achieve the protection of user privacy, the spectrum of A(t) in the above formula (19) needs to be able to scramble Ra 1(t) spectrum, that is: the spectrum of A(t) and Ra 1 After convolving the spectrum of (t) with the spectrum of Ra 1 The impacts with larger energy in (t) should be dispersed over a frequency range (such as Figure 8 shown).

[0320] Since the above A(t) is a composite function, the bandwidth of A(t) is determined by the function that changes fastest among them. In order for the spectral characteristics of A(t) to meet the above conditions (that is, after convolving the spectrum of A(t) with the spectrum of Ra 1 (t), the impacts with larger energy in Ra 1 (t) should be dispersed over a frequency range), θ(t) should be the function that changes fastest among the functions constituting A(t). Otherwise, the bandwidth of A(t) will be determined by the function Ra 2 (t) or the function Ra 3 (t), and Ra 2 (t) or Ra 3 (t) is caused by the movement of objects in the environment, and it may have a very narrow bandwidth and cannot achieve the effect of dispersing the spectrum of Ra 1 (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 various actions to be recognized max .

[0321] Based on the above requirements for the bandwidth of the scrambling function θ(t), a method for determining the scrambling function is introduced below. This method may include the following steps 1 to 4:

[0322] Step 1, assume that the entire sensing process includes M sensing rounds, and the duration interval of each sensing round is Δt. Then the total duration of the entire sensing process is (M * Δt), that is, the time duration of the scrambling function θ(t) is (M * Δt).

[0323] Step 2, randomly generate S uniformly distributed random numbers in the range of 0 to 2π, and the time interval corresponding to adjacent random numbers is

[0324] where S satisfies: (α is a number greater than 0 and less than 1), F max represents the maximum value of the maximum Doppler shift caused by various actions to be recognized, and the specific value is determined by the application scenario and the carrier frequency, generally not exceeding a few hundred Hertz. Since the time interval between every two adjacent random numbers among the S random numbers is Therefore, it can be considered that the S random numbers are the samples of the scrambling function θ(t) at times 0, (M - 1)Δt, etc.

[0325] Step 3: For the above S random numbers, the function obtained by using the piecewise interpolation algorithm for interpolation is determined as the scrambling function θ(t). If θ(t) is greater than 2π, then let θ(t) be equal to 2π; if θ(t) is less than 0, then let θ(t) be equal to 0.

[0326] Step 4: Sample θ(t) obtained in Step 3 at intervals of Δt, and a set of samples θ(mΔt) can be obtained. θ(mΔt) is the scrambling function used in the m-th sensing round.

[0327] Figure 9 The schematic diagram showing the influence of the scrambling function designed for the activity recognition scenario on the sensing result is shown. Figure 9 (a) and (d) in [reference] respectively show the modulus of the time-domain waveform of S(t) when θ(t) = 0 and the modulus of the spectrum corresponding to this S(t). θ(t) = 0 means that the first device does not process the sensing signal using the scrambling function. When θ(t) = 0, from Figure 9 the characteristics of the modulus of the spectrum shown in (d) in [reference], it can be seen that unauthorized devices can accurately distinguish between the two actions of stationary and walking.

[0328] Figure 9 (b) and (e) in [reference] respectively show the modulus of the time-domain waveform of S(t) and the modulus of the spectrum corresponding to this 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), from Figure 9 the modulus of the time-domain waveform shown in (b) in [reference] and Figure 9 the characteristics of the modulus of the spectrum shown in (e) in [reference], it can be seen that under the two actions of stationary and walking, there are still obvious differences in the time-domain waveform and time-frequency spectrum of S(t). Unauthorized devices can distinguish between the two actions of stationary and walking, and the protection of user privacy cannot be achieved.

[0329] Figure 9 (c) and (f) in [reference] respectively show the modulus of the time-domain waveform of S(t) and the modulus of the spectrum corresponding to this S(t) when the permutation function is the scrambling function designed in this application. From Figure 9 the modulus of the time-domain waveform shown in (c) in [reference] and Figure 9 the modulus of the spectrum shown in (f) in [reference], it can be seen that under the two actions of stationary and walking, neither the time-domain waveform nor the time-frequency spectrum of S(t) can be distinguished. Since unauthorized devices do not know the scrambling function, they cannot distinguish between the two actions of stationary and walking, and the protection of user privacy is achieved.

[0330] In summary, the scrambling function designed in this application for the activity recognition scenario can achieve the protection of user privacy.

[0331] As described above in combination withFigure 1 To 9 describe in detail the method provided by this application, the following combines Figure 10 and Figure 11 to introduce the device provided by this application.

[0332] Figure 10 and Figure 11 are schematic diagrams of possible devices provided by the embodiments of this 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 possessed by the above method embodiments.

[0333] Figure 10 is a schematic block diagram of the device provided by the embodiment of this application. As Figure 10 shown, the device 1000 includes a transceiver module 1010 and a processing module 1020.

[0334] A possible design is that the device 1000 is used to implement the above Figure 3 and Figure 4 functions of the first device in the method embodiments shown.

[0335] Exemplarily, the processing module 1020 is used to: determine the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function; generate a first signal and a second signal, where 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; and output the first signal and the second signal, where the first signal is sent through the first antenna corresponding to the first device, and the second signal is sent through the second antenna corresponding to the first device.

[0336] Another possible design is that the device 1000 is used to implement the above Figure 3 and Figure 4 functions of the second device in the method embodiments shown.

[0337] Exemplarily, the processing module 1020 is used to: determine the type of the target scrambling function corresponding to the first sensing scenario and the parameters included in the target scrambling function; and obtain a sensing result based on the target scrambling function and the signal received from the first device, where the target scrambling function is determined based on the type of the target scrambling function and the parameters.

[0338] Optionally, the transceiver module 1010 is used to: send or receive first information indicating the type of the target scrambling function.

[0339] Optionally, the transceiver module 1010 is further used to: send or receive second information indicating the parameters.

[0340] Optionally, the transceiver module 1010 is further configured to: send or receive third information, where the third information indicates the generation algorithm of the parameter.

[0341] Optionally, the transceiver module 1010 is further configured to: send or receive fourth information, where the fourth information indicates that the scene to be sensed is the first sensing scene.

[0342] 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 parameter.

[0343] For a more detailed description of the above transceiver module 1010 and processing module 1020, reference can be directly made to the relevant descriptions in Figure 3 and Figure 4 the embodiments shown, which will not be elaborated here.

[0344] It should be noted that the apparatus 1000 may include a sending module but not a receiving module. Alternatively, the apparatus 1000 may include a receiving module but not a sending module. Specifically, it depends on whether the above solutions executed by the apparatus 1000 include sending actions and receiving actions. It can be understood that since the apparatus 1000 has a communication function, it can also be referred to as a communication apparatus.

[0345] Figure 11 is another schematic block diagram of the apparatus provided in the embodiments of the present application. As Figure 11 shown, the apparatus 1100 includes one or more processors 1110. The processor 1110 may be a general-purpose processor or a dedicated processor, etc. 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 (such as the first apparatus, the second apparatus, or a chip, etc.), execute software programs, and process data of the software programs.

[0346] Optionally, in one design, the processor 1110 may include a program (which may also be referred to as code or instructions), and the program may be run on the processor 1110, so that the apparatus 1100 executes the methods performed by the first apparatus or the second apparatus in the above method embodiments. In another possible design, the apparatus 1100 includes a circuit ( Figure 11 not shown), and the circuit is used to implement the functions of the first apparatus or the second apparatus in the above method embodiments.

[0347] Exemplarily, the processor 1110 may be used to execute computer programs or instructions in a memory to implement Figure 3 and Figure 4 the steps performed by the first apparatus or the second apparatus in any one of the method embodiments shown in the embodiments shown.

[0348] Optionally, one or more memories 1120 may be included in the device 1100, on which there is a program (sometimes also referred to as code or instructions), and the program can be run on the processor 1110, so that the device 1100 executes the methods performed by the first device or the second device in the above embodiments.

[0349] Optionally, an artificial intelligence (AI) module may be included in the processor 1110 and / or the memory 1120, and the AI module is used to implement AI-related functions. The AI module can be implemented in a software, hardware, or a combination of software and hardware manner. For example, the AI module may include a radio intelligent controller (RIC) module. For example, the AI module may be a near real-time RIC or a non-real-time RIC.

[0350] Optionally, data may also be stored in the processor 1110 and / or the memory 1120. The processor and the memory may be provided separately or integrated together.

[0351] Optionally, the device 1100 may further include a communication interface 1130. The processor 1110 is sometimes also referred to as a processing unit and controls the device (such as the first device or the second device). The communication interface 1130 is sometimes also referred to as a transceiver unit, a transceiver, a transceiver circuit, or a transceiver, etc., and is used to implement the transceiver function of the device through the antenna 1140.

[0352] Optionally, the device 1100 further includes a communication interface 1130. The processor 1110 and the communication interface 1130 are coupled to each other. It can be understood that the communication interface 1130 can be a transceiver or an input / output interface.

[0353] It can be understood that since the device 1100 has a communication function, it can also be referred to as a communication device.

[0354] When the device 1100 is used to implement Figure 3 the method, the processor 1110 is used to execute the functions of the above-mentioned processing unit, and the communication interface 1130 is used to execute the functions of the above-mentioned transceiver module. Whether the communication interface 1130 is used for sending or receiving specifically depends on whether the device 1100 performs a sending action or a receiving action in the solution it executes.

[0355] It can be understood that when the device 1100 is the first device or the second device, the communication interface 1130 can be a transceiver, specifically including a transmitter and a receiver. The transmitter is used to send signals, and the receiver is used to receive signals. When the device 1100 is a chip applied to the first device or the second device, the communication interface 1130 can be an input / output circuit, where the input circuit can be used for receiving, and the output interface can be used for sending.

[0356] It should be noted that the above method embodiments can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiments can be completed by the integrated logic circuit in the hardware of the processor or the instructions in software form.

[0357] The above-mentioned processor can 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 devices, discrete gate or transistor logic devices, discrete hardware components or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0358] The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0359] 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 ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (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 but 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), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include but not be limited to these and any other suitable types of memory.

[0360] The present application also provides a computer-readable medium, on which a computer program is stored, and when the computer program is executed by a computer, the functions of the above method embodiments are implemented.

[0361] The present application also provides a computer program product containing instructions, and when the computer program product is executed by a computer, the functions of the above method embodiments are implemented.

[0362] The method provided by the above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it 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 processes or functions described in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. 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 wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium may be a magnetic medium (such as a floppy disk, a hard disk, a magnetic disk), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0363] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0364] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0365] In several embodiments provided in the present 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 illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other may be through some interfaces, and the indirect couplings or communication connections of the devices or units may be in electrical, mechanical, or other forms.

[0366] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0367] In addition, each functional unit in various embodiments of the present application may be integrated in a processing unit, may exist separately as individual physical units, or two or more units may be integrated in one unit.

[0368] If the above 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, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories, random access memories, magnetic disks, or optical discs that can store program codes.

[0369] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A communication method, characterized in that, applied to a first device, the method comprising: determining a type of a target scrambling function corresponding to a first sensing scenario and parameters included in the target scrambling function; generating a first signal and a second signal, the second signal being obtained by performing phase adjustment on 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; outputting the first signal and the second signal, the first signal being transmitted through a first antenna corresponding to the first device, and the second signal being transmitted 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 proportional to e jθ(t) is directly proportional, or the ratio of the first signal to the second signal is inversely proportional to e jθ(t) is inversely proportional, and θ(t) is the target scrambling function.

3. The method according to claim 1 or 2, characterized in that, the method further comprises: transmitting or receiving first information indicating the type of the target scrambling function.

4. The method according to any one of claims 1 to 3, characterized in that, the method further comprises: transmitting or receiving second information indicating the parameters.

5. The method according to any one of claims 1 to 3, characterized in that, the method further comprises: transmitting or receiving third information indicating a generation algorithm of the parameters.

6. The method according to any one of claims 1 to 5, characterized in that, the method further comprises: transmitting or receiving fourth information indicating that the scenario to be sensed is the first sensing scenario.

7. A communication method, characterized in that, applied to a second device, the method comprising: determining a type of a target scrambling function corresponding to a first sensing scenario and parameters included in the target scrambling function; obtaining a sensing result based on the target scrambling function and a signal received from the first device, the target scrambling function being determined based on the type of the target scrambling function and the parameters.

8. The method according to claim 7, characterized in that, the method further comprises: receiving or transmitting first information indicating the type of the target scrambling function.

9. The method according to claim 7 or 8, characterized in that, the method further comprises: receiving or transmitting second information indicating the parameters.

10. The method according to claim 7 or 8, characterized in that, the method further comprises: receiving or transmitting third information indicating a generation algorithm of the parameters.

11. The method according to any one of claims 7 to 10, characterized in that, the method further comprises: receiving or transmitting fourth information indicating that the scenario to be sensed is the first sensing scenario.

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

13. According to the method described in claim 12, characterized in that, the type of the target scrambling function is one of multiple 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.

14. According to the method described in claim 13, characterized in that, the first sensing scenario is the physiological feature detection scenario, the function type of the target scrambling function is the sine function, the parameter includes the frequency of the sine function, and the frequency of the sine function is within the frequency range corresponding to physiological activities.

15. According to the method described in claim 14, characterized in that, the target scrambling function θ(t) satisfies: θ(t) = π cos(2πF q t), Among them, F q ∈ [F l1 , F l2 , [F l1 , F l2 represents the frequency range corresponding to the physiological activity, and F q is a frequency value randomly selected within [F l1 , F l2 .

16. According to the method described in claim 13, characterized in that, the first sensing scenario is the physiological feature detection scenario, the type of the target scrambling function is the linear combination of sine functions, the parameters include 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, and the frequency of each sine function is within the frequency range corresponding to physiological activities.

17. According to the method described in 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 is a frequency value randomly selected within the frequency range of [F l1 , F l2 , is a non-zero real number, n a is an integer greater than 1.

18. According to the method described in claim 13, characterized in that, the first sensing scenario is the biological presence detection scenario, 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. According to the method described in 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 said breath, F a1 is a frequency value randomly selected within the frequency range of [F m1 , F m2 , F b1 ∈ [F n1 , F n2 , [F n1 , F n2 represents the frequency range corresponding to the said heartbeat, F b1 is a frequency value randomly selected within the frequency range of [F n1 , F n2 , and are both non-zero real numbers.

20. According to the method described in claim 13, characterized in that, the first sensing scenario is the biological presence detection scenario, the type of the target scrambling function is the linear combination of two sets of sine functions, the parameters include the frequency of each sine function in the linear combination of two sets of sine functions, and the number of sine functions included in each set of sine functions; the linear combination of two sets of sine functions includes a first set of sine functions and a second set of sine functions, the frequency of each sine function in the first set of sine functions is within the frequency range corresponding to breathing, and the frequency of each sine function in the second set of sine functions is within the frequency range corresponding to heartbeat.

21. According to the method described in claim 20, characterized in that, The target scrambling function θ(t) satisfies: In it, F ai ∈ [F m1 , F m2 , [F m1 , F m2 represents the frequency range corresponding to breathing, and F ai is a frequency value randomly selected within [F m1 , F m2 . [F bi ∈ [F n1 , F n2 , [F n1 , F n2 represents the frequency range corresponding to the heartbeat, and F bi is a frequency value randomly selected within the frequency range of [F n1 , F n2 . and are both non-zero real numbers, and n a and n b are both integers greater than 1. and are both real numbers.

22. The method according to claim 13, wherein, the first sensing 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 parameter is the S random numbers, and S is an integer greater than 1.

23. The method according to claim 22, wherein, S satisfies: Among them, F max is the maximum value of the maximum Doppler frequency shift caused by various actions to be recognized, M is the number of sensing wheels, Δt is the duration of each sensing wheel, α is a number greater than 0 and less than 1, and Μ is an integer greater than 1.

24. A communication device, wherein, it includes a module for implementing the method according to any one of claims 1 to 6 and 12 to 23; or, it includes a module for implementing the method according to any one of claims 7 to 23.

25. A communication device, wherein, it includes a processor for causing the communication device to implement the method according to any one of claims 1 to 6 and 12 to 23 by executing a computer program and / or by means of a logic circuit, or for causing the communication device to implement the method according to any one of claims 7 to 23.

26. The device according to claim 25, wherein, it further 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, wherein, it further includes a communication interface for inputting and / or outputting signals.

28. A computer-readable storage medium having a computer program stored thereon, wherein, when the computer program is executed by a processor, the method according to any one of claims 1 to 6 and 12 to 23 is executed, or the method according to any one of claims 7 to 23 is executed.

29. A computer program product, wherein, it includes a computer program, and when the computer program is run, the method according to any one of claims 1 to 6 and 12 to 23 is executed, or the method according to any one of claims 7 to 23 is executed.

30. A communication system, wherein, it includes 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 6 and 12 to 23, and the second device is used to implement the method according to any one of claims 7 to 23.

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