Electronic apparatus for identifying movement and method for performing same

Abstract

A disclosed operation method of an electronic apparatus comprises the operations of: on the basis of a wireless signal received by the electronic apparatus, acquiring channel state information (CSI) corresponding to a plurality of sub-carriers included in the wireless signal; acquiring channel state data by preprocessing the channel state information acquired by the electronic apparatus for a specified time; on the basis of the channel state data, acquiring a time delayed relationship indicating the similarity of the channel state data in each time period; on the basis of the channel state data, acquiring a sub-carrier relationship indicating the similarity between pieces of channel state data corresponding to respective sub-carriers; and on the basis of the time delayed relationship and the sub-carrier relationship, identifying whether there is movement in a space in which the electronic apparatus is installed, corresponding to a first time period.

Description

Electronic device for identifying movement and a method for performing the same

[0001] The present disclosure relates to an electronic device and a method of operating the same. Specifically, it relates to an electronic device for identifying movement in a space in which the electronic device is installed and a method of operating the same.

[0002] Electronic devices can operate through various network environments such as wired Ethernet, wireless LAN, and Bluetooth. Users can access the Internet through network functions or connect to peripheral devices to display their content. Wireless LAN can provide Wi-Fi functionality. Wi-Fi channel state information (CSI) represents the channel frequency response per subcarrier of orthogonal frequency division multiplexing (OFDM) and may include information regarding signal deformation between the transmitting and receiving sides, such as attenuation, diffraction, and reflection.

[0003] An electronic device according to one embodiment of the present disclosure may include a memory for storing at least one instruction. The electronic device may include at least one processor including a circuit device. The electronic device may include a communication interface.

[0004] By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire channel state information (CSI) corresponding to a plurality of subcarriers included in the wireless signal based on the wireless signal received by the electronic device. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire channel state data by preprocessing the channel state information acquired by the electronic device for a specified time period. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire a time delayed relationship indicating similarity between the channel state data corresponding to each time interval based on the channel state data. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire a subcarrier relationship indicating similarity between the channel state data corresponding to each subcarrier based on the channel state data. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can identify the movement of the space in which the electronic device is installed corresponding to the first time interval based on the time correlation and the subcarrier correlation.

[0005] A method of operation of an electronic device according to one embodiment of the present disclosure may include an operation of acquiring channel state information (CSI) corresponding to a plurality of subcarriers included in a wireless signal based on a wireless signal received by the electronic device. The method may include an operation of acquiring channel state data by preprocessing the channel state information acquired by the electronic device for a specified period of time. The method may include an operation of acquiring a time delayed relationship indicating similarity between the channel state data corresponding to each time interval based on the channel state data. The method may include an operation of acquiring a subcarrier relationship indicating similarity between the channel state data corresponding to each subcarrier based on the channel state data. The method may include an operation of identifying whether there is movement in the space where the electronic device is installed in a first time interval based on the time delayed relationship and the subcarrier relationship.

[0006] According to one embodiment of the present disclosure, a computer-readable recording medium having at least one instruction recorded thereon may be provided. By executing the at least one instruction individually or collectively by the at least one processor, the computer-readable recording medium may perform the method described above or below.

[0007] The present invention can be easily understood from the combination of the following detailed description and the accompanying drawings, where reference numerals denote structural elements.

[0008] FIG. 1 is a schematic diagram of a method of operation of an electronic device according to one embodiment of the present disclosure.

[0009] FIG. 2 shows an example of an electronic device according to one embodiment of the present disclosure.

[0010] FIG. 3 is a flowchart illustrating a method for an electronic device according to one embodiment of the present disclosure to identify whether there is movement in a space where the electronic device is installed.

[0011] FIGS. 4a and 4b are drawings for illustrating a method for an electronic device to acquire channel state information according to one embodiment of the present disclosure.

[0012] FIG. 5a is a diagram illustrating channel state data obtained by an electronic device according to one embodiment of the present disclosure by preprocessing channel state information.

[0013] FIG. 5b is a flowchart illustrating a method for an electronic device according to one embodiment of the present disclosure to obtain channel state data by preprocessing channel state information.

[0014] FIG. 6a is a flowchart for further explaining a method for an electronic device according to one embodiment of the present disclosure to obtain a time correlation.

[0015] FIG. 6b is a drawing for illustrating a time association diagram according to one embodiment of the present disclosure.

[0016] FIG. 6c is a drawing for illustrating a time association diagram according to one embodiment of the present disclosure.

[0017] FIG. 7a is a flowchart for further explaining a method for an electronic device according to one embodiment of the present disclosure to acquire a subcarrier association.

[0018] FIG. 7b is a diagram illustrating a subcarrier association diagram according to one embodiment of the present disclosure.

[0019] FIG. 7c is a drawing for illustrating a time association diagram according to one embodiment of the present disclosure.

[0020] FIG. 8a is a flowchart for explaining in detail how an electronic device included in operation 344 acquires a subcarrier association according to one embodiment of the present disclosure.

[0021] FIG. 8b is a diagram illustrating a subcarrier association diagram according to one embodiment of the present disclosure.

[0022] FIG. 9a is a flowchart for further explaining a method for an electronic device according to one embodiment of the present disclosure to acquire a channel state information pattern.

[0023] FIG. 9b is a drawing for illustrating a pattern recognition model according to one embodiment of the present disclosure.

[0024] FIG. 9c is a flowchart for further explaining a method for identifying whether there is movement in a space where an electronic device is installed based on a channel state information pattern according to one embodiment of the present disclosure.

[0025] FIG. 9d is a flowchart for further explaining a method for identifying whether there is movement in a space where an electronic device is installed based on a channel state information pattern according to one embodiment of the present disclosure.

[0026] FIG. 9e is a flowchart for further explaining a method for identifying whether there is movement in a space where an electronic device is installed based on a channel state information pattern according to one embodiment of the present disclosure.

[0027] FIG. 10a is a drawing for illustrating a channel state information pattern according to one embodiment of the present disclosure.

[0028] FIG. 10b is a drawing for illustrating a channel state information pattern according to one embodiment of the present disclosure.

[0029] FIG. 10c is a drawing for illustrating a channel state information pattern according to one embodiment of the present disclosure.

[0030] FIG. 11a is a flowchart illustrating a method for controlling the presence or absence of movement in a space where an electronic device is installed according to one embodiment of the present disclosure.

[0031] FIG. 11b is a flowchart illustrating a method for controlling the presence or absence of movement in a space where an electronic device is installed according to one embodiment of the present disclosure.

[0032] FIG. 12 is a block diagram illustrating the configuration of an electronic device according to one embodiment of the present disclosure.

[0033] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments.

[0034] In relation to the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of the noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise.

[0035] In this document, each of the phrases such as "A or B", "at least one of A and B", "at least one of A or B", "A, B or C", "at least one of A, B and C", and "at least one of A, B, or C" may include any one of the items listed together in the corresponding phrase, or all possible combinations thereof.

[0036] The term “and / or” includes a combination of multiple related described components or any of the multiple related described components.

[0037] Terms such as "first," "second," or "first" or "second" may be used simply to distinguish a component from another component and do not limit the components in other aspects (e.g., importance or order).

[0038] Where any (e.g., 1st) component is referred to as "coupled" or "connected" to another (e.g., 2nd) component, with or without the terms "functionally" or "communicationly," it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0039] Terms such as “include” or “have” are intended to specify the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in this document, and do not preclude the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0040] When it is said that one component is “connected,” “combined,” “supported,” or “in contact” with another component, this includes not only cases where the components are directly connected, combined, supported, or in contact, but also cases where they are indirectly connected, combined, supported, or in contact through a third component.

[0041] When it is said that a component is located “on” another component, this includes not only cases where one component is in contact with the other, but also cases where another component exists between the two components.

[0042] It should be understood that the blocks in each flowchart and combinations of flowcharts can be executed by one or more computer programs containing computer-executable instructions. One or more computer programs may be stored all in a single memory or may be partitioned and stored in multiple different memories.

[0043] One embodiment of the present disclosure may be represented by functional block configurations and various processing steps. Some or all of these functional blocks may be implemented by various numbers of hardware and / or software configurations that execute specific functions. For example, the functional blocks of the present disclosure may be implemented by one or more microprocessors or by circuit configurations for a specific function. Additionally, for example, the functional blocks of the present disclosure may be implemented in various programming or scripting languages. The functional blocks may be implemented as algorithms executed on one or more processors. Furthermore, the present disclosure may employ prior art for electronic configuration, signal processing, and / or data processing, etc.

[0044] All functions or operations, including functions related to artificial intelligence according to the present disclosure, are operated through a processor and memory. The processor may be composed of one or more processors. A single processor or a combination of processors may include circuitry that performs processing, such as an AP (Application Processor), CP (Communication Processor), GPU (Graphical Processing Unit), NPU (Neural Processing Unit), MPU (Microprocessor Unit), SoC (System on Chip), IC (Integrated Chip), etc.

[0045] The present disclosure will be described in detail below with reference to the attached drawings.

[0046] FIG. 1 is a schematic diagram of a method of operation of an electronic device according to one embodiment of the present disclosure.

[0047] Referring to FIG. 1, a wireless router (20) may be located around an electronic device (100). A wireless router (20) may be located in a space (10) where the electronic device is installed. In one embodiment, the wireless router (20) may be located in a space that is not separated from the space (10) where the electronic device is installed by a wall or a door.

[0048] The space (10) where the electronic device is installed may be of various sizes and shapes, depending on the environment or architectural structure in which the electronic device (100) is installed. For example, the space (10) where the electronic device is installed may be a single room. In this case, the room may represent a single space that is not separated from other spaces by walls, doors, or other physical boundary elements. In one embodiment, the space (10) where the electronic device is installed may be a larger space, such as an entire house. The interior of the house may consist of multiple rooms. The space where the electronic device (100) is installed corresponds to the space where the wireless router (20) is installed under the same network environment and can be considered as a single integrated space where wireless signals can be transmitted.

[0049] An electronic device (100) can perform wireless communication through a wireless router (20) and a wireless signal (30). The wireless router (20) may have a wired internet connection. The wireless router (20) may connect the electronic device (100) to the internet using the wired internet connection and the wireless communication connection. Wireless communication may include Wi-Fi, and the wireless signal (30) may correspond to a Wi-Fi signal, but the present disclosure is not limited to the examples described above.

[0050] The electronic device (100) can acquire (or retrieve) multipath channel characteristic data based on the wireless signal (30). The electronic device (100) can control the electronic device (100) using the multipath channel characteristic data. The multipath channel characteristic data may represent the channel status characteristics of the multipath. For example, the multipath channel characteristic data may include channel status information (CSI).

[0051] In one embodiment of the present disclosure, the electronic device (100) can identify movement around the electronic device (100) (e.g., a space where the electronic device (100) is installed) using channel state information. The electronic device (100) can obtain channel state data by preprocessing channel state information obtained during a specified time (e.g., 3 seconds, 5 seconds). The channel state data may be data representing changes in channel state information over time.

[0052] In one embodiment of the present disclosure, an electronic device (100) may obtain a time relationship indicating similarity between the channel state data corresponding to each time interval based on the channel state data. The electronic device (100) may obtain a sub-carrier relationship indicating similarity between the channel state data corresponding to each subcarrier based on the channel state data. The time relationship may be represented in the form of at least one of a vector or a matrix. The sub-carrier relationship may be represented in the form of at least one of a vector or a matrix.

[0053] In one embodiment of the present disclosure, the electronic device (100) can identify whether there is movement in the space where the electronic device is installed corresponding to a first time interval based on the time correlation and the subcarrier correlation. In one embodiment of the present disclosure, the electronic device (100) can obtain a channel state information pattern corresponding to a wireless signal based on the time correlation and the subcarrier correlation. For example, the electronic device (100) can obtain a channel state information pattern corresponding to a wireless signal by concatenating the time correlation and the subcarrier correlation. The electronic device (100) can identify whether there is movement in the space where the electronic device is installed corresponding to a first time interval based on the channel state information pattern using a pattern recognition model.

[0054] The pattern recognition model may be learned based on a first channel state information pattern in which movement exists in the space where the electronic device is installed and a second channel state information pattern in which movement does not exist in the space where the electronic device is installed. The electronic device (100) can use the pattern recognition model to identify the larger value between a first similarity between the acquired channel state information pattern and the first channel state information pattern and a second similarity between the acquired channel state information pattern and the second channel state information pattern. If the first similarity is greater than or equal to the second similarity, the electronic device (100) may determine that movement exists in the space where the electronic device is installed. If the first similarity is less than the second similarity, the electronic device (100) may determine that movement does not exist in the space where the electronic device is installed.

[0055] In one embodiment, the electronic device (100) can control the electronic device (100) based on identified movement. For example, if there is no movement around the electronic device (100), the electronic device (100) can set the power mode of the electronic device (100) to power saving mode.

[0056] In one embodiment of the present disclosure, if a user (102) is using the electronic device (100) (e.g., if the user (102) is watching video content through the electronic device (100)), the electronic device (100) can detect movement in the space where the electronic device (100) is installed. In one embodiment of the present disclosure, if the user (102) is not using the electronic device (100), the electronic device (100) may not detect movement in the space where the electronic device (100) is installed. In this case, the electronic device (100) can reduce unnecessary power consumption by operating in a power-saving mode or by turning off the power. For example, the power-saving mode may include at least one of lowering the screen brightness of the electronic device (100), lowering the sound of the electronic device (100), turning off the screen of the electronic device (100), turning off the sound of the display device (110), and turning off the power of the electronic device (100).

[0057] The electronic device (100) can accurately identify whether there is movement in the space where the electronic device (100) is installed by identifying whether there is movement in the space where the electronic device (100) is installed based on time correlation and subcarrier correlation. In one embodiment, the electronic device (100) can improve the user experience by accurately identifying the movement in the space where the electronic device (100) is installed and controlling the electronic device (100) to continue operating (e.g., playing content) when a user is present in the space where the electronic device (100) is installed. For example, it can prevent the electronic device (100) from switching to power-saving mode even when a user is present in the space where the electronic device (100) is installed. If there is no movement in the space where the electronic device (100) is installed, the electronic device (100) can save power consumption, such as by switching to power-saving mode.

[0058] In one embodiment of the present disclosure, the electronic device (100) can accurately identify whether there is movement in the space where the electronic device (100) is installed, regardless of the distance between the electronic device (100) and the wireless router (20). For example, the electronic device (100) can accurately identify whether there is movement in the space where the electronic device (100) is installed even when the distance from the wireless router (20) is 1m or less.

[0059] Hereinafter, we will examine in detail an electronic device (100) according to one embodiment of the present disclosure, a method for identifying whether there is movement in a space where the electronic device is installed, and an electronic device (100) that performs the same.

[0060] FIG. 2 is a block diagram illustrating the configuration of an electronic device according to one embodiment of the present disclosure.

[0061] According to one embodiment of the present disclosure, an electronic device (100) is a device capable of displaying an image or data upon a user's request and may include a memory (110), a processor (120), and a communication interface (130).

[0062] The electronic device (100) can be implemented in various forms. The electronic device (100) can be any type of device that performs functions including a processor and memory. The electronic device (100) can be a stationary or portable device. For example, the electronic device (100) can represent a device equipped with a display capable of displaying image content, video content, game content, graphic content, etc.

[0063] The electronic device (100) may include various types of electronic devices capable of receiving and outputting content, such as televisions like network TV, smart TV, internet TV, web TV, and IPTV; computers like desktops, laptops, and tablets; smart monitors, digital signage, large displays, 360-degree projectors, smartphones, cellular phones, game players, music players, video players, medical equipment, and home appliances. The electronic device (100) may include various types of home appliances, including air conditioners. The electronic device (100) may be referred to as a display device in terms of displaying content, and may also be referred to as a content providing device, a computing device, etc.

[0064] The electronic device (100) can output various forms of content provided by content providers. The content may include still images, video such as video, audio, subtitles, and other additional information. A content provider may refer to a content production company that provides various content to consumers, a terrestrial broadcasting station, a cable broadcasting station, a satellite broadcasting station, or an IPTV (Internet Protocol Television) service provider or an OTT (Over the Top) service provider. A content provider may produce various types of content, such as dramas, movies, entertainment programs, news, games, audio, etc.

[0065] In one embodiment, the electronic device (100) may be implemented without a display. The electronic device (100) may include, but is not limited to, a set-top box, a desktop PC, etc., that can be connected to a separate external display. In this case, the electronic device (100) may be configured to be connected to an external display device through an input / output section such as an HDMI port to transmit video / audio signals to the external display device. Alternatively, the electronic device (100) may be connected to the external display device through short-range wireless communication or long-range wireless communication such as wired communication, wireless LAN (W-LAN), Wi-Fi, or Bluetooth.

[0066] The memory (110) can store a program for processing and controlling the processor (120), and can store data that is input to or output from the electronic device (100). Additionally, the memory (110) can store data necessary for the operation of the electronic device (100).

[0067] The memory (110) may include at least one type of storage medium among flash memory type, hard disk type, multimedia card micro type, card type memory (e.g., SD or XD memory, etc.), RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk, and optical disk.

[0068] The memory (110) may not exist separately but may be configured to be included in the processor (120). The memory (110) may be composed of volatile memory, non-volatile memory, or a combination of volatile and non-volatile memory. The memory (110) may store a program or at least one instruction for performing operations according to the embodiments described below. The memory (110) may provide stored data to the processor (120) upon the request of the processor (120).

[0069] The memory (110) may include a pattern recognition model (112). The pattern recognition model (112) may represent an algorithm or a set of algorithms for identifying (or recognizing) channel state information patterns.

[0070] The pattern recognition model (112) can identify whether there is movement in a space where an electronic device corresponding to a specific time interval is installed, based on time correlation and subcarrier correlation. The pattern recognition model (112) can obtain time correlation and subcarrier correlation as input data. The pattern recognition model (112) can output whether there is movement in a space where an electronic device corresponding to a specific time interval is installed as result data.

[0071] In one embodiment of the present disclosure, in order for the pattern recognition model (112) to accurately output result data corresponding to the input data, it is necessary to train the pattern recognition model (112). Here, 'training' may include a process of inputting various data into the pattern recognition model (112) and training the pattern recognition model (112) so that the pattern recognition model (112) can discover or learn on its own methods for analyzing the input data, methods for classifying the input data, and / or methods for extracting features necessary for generating result data from the input data.

[0072] Specifically, through the learning process, the pattern recognition model (112) can train the training data (e.g., multiple different images) to optimize and set the weight values ​​within the neural network. Then, by learning the input data itself through the pattern recognition model (112) having the optimized weight values, it can output the desired result.

[0073] The pattern recognition model (112) may be learned (or trained) based on channel state information patterns. In one embodiment of the present disclosure, the pattern recognition model (112) may be learned (or trained) based on a first channel state information pattern in which movement of the space where the electronic device (100) is installed exists and a second channel state information pattern in which movement of the space where the electronic device (100) is installed does not exist.

[0074] The pattern recognition model (112) may represent a neural network model. For example, the pattern recognition model (112) may represent an algorithm or a set of algorithms for implementing artificial intelligence technology. Artificial intelligence technology (hereinafter referred to as 'AI technology') is a technology that obtains a desired result by performing operations through a neural network to process input data, such as analysis and / or classification. The neural network receives input data, performs the aforementioned analysis and / or classification operations, and outputs result data.

[0075] Examples of pattern recognition models (112) include, but are not limited to, CNN (Convolutional Neural Network), DNN (Deep Neural Network), RNN (Recurrent Neural Network), RBM (Restricted Boltzmann Machine), DBN (Deep Belief Network), BRDNN (Bidirectional Recurrent Deep Neural Network), and Deep Q-Networks. Additionally, neural networks can be subdivided. For example, a CNN neural network can be subdivided into a DCNN (Deep Convolutional Neural Network) or a Capsnet neural network.

[0076] The processor (120) controls the overall operation of the electronic device (100). The processor (120) is configured to control a series of processes to enable the electronic device (100) to operate according to the embodiments described below, and may be composed of one or more processors. One or more processors included in the processor (120) may be circuitry such as a System on Chip (SoC) or an Integrated Circuit (IC). One or more processors included in the processor (120) may be a general-purpose processor such as a CPU (Central Processing Unit), MPU (Micro Processor Unit), AP (Application Processor), or DSP (Digital Signal Processor); a graphics-dedicated processor such as a GPU (Graphic Processing Unit) or VPU (Vision Processing Unit); an artificial intelligence-dedicated processor such as an NPU (Neural Processing Unit); or a communication-dedicated processor such as a CP (Communication Processor). If one or more processors included in the processor (120) are artificial intelligence dedicated processors, the artificial intelligence dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0077] The processor (120) can write data to memory (110) or read data stored in memory (110), and in particular, can process data according to a predefined operation rule or artificial intelligence model by executing a program or at least one instruction stored in memory (110). Accordingly, the processor (120) can perform operations described in subsequent embodiments, and operations described as being performed by the electronic device (100) or detailed elements included in the electronic device (100) in subsequent embodiments can be seen as being performed by the processor (120) unless otherwise specified.

[0078] For example, the processor (120) can perform the function of the electronic device (100) described in the present disclosure by executing at least one instruction stored in the memory (110) individually or collectively. According to one embodiment of the present disclosure, the electronic device (100) can perform the function described in the present disclosure by executing at least one instruction stored in the memory (110) individually or collectively by the processor (120).

[0079] The processor (120) can process data according to a predefined operation rule or artificial intelligence model by executing a program or at least one instruction stored in memory (110). Accordingly, the processor (120) can perform operations described in subsequent embodiments, and operations described as being performed by the electronic device (100) or detailed components included in the electronic device (100) in subsequent embodiments can be seen as being performed by the processor (120) unless otherwise specified.

[0080] The communication interface (130) can communicate with at least one electronic device. Here, 'communication' may mean the operation of transmitting and / or receiving data, signals, requests, and / or commands, etc. The communication interface (130) can perform wired or wireless communication with at least one electronic device. The electronic device (100) can communicate with the wireless router (20) through the communication interface (130).

[0081] For example, the communication interface (130) may include at least one of a communication module, a communication circuit, a communication device, an input / output port, and an input / output plug for performing wired or wireless communication with at least one electronic device. For example, the communication interface (130) may include at least one wireless communication module, a wireless communication circuit, or a wireless communication device for performing wireless communication with at least one electronic device.

[0082] For example, the communication interface (130) may include a short-range communication module, such as an IR (infrared) communication module, capable of receiving control commands from a remote controller located at a short distance. In this case, the communication interface (130) may receive control signals from the remote controller.

[0083] For example, the communication interface (130) may include at least one communication module that performs communication according to wireless communication standards such as Bluetooth, Wi-Fi, BLE (Bluetooth Low Energy), NFC (Near Field Communication), RFID (Radio Frequency Identification), Wi-Fi Direct, UWB, or Zigbee. Alternatively, the communication interface (130) may further include a communication module that performs communication with a server to support long-distance communication according to long-distance communication standards. For example, the communication interface (130) may include a communication module that performs communication through a network for internet communication. Additionally, the communication interface (130) may include a communication module that performs communication through a communication network according to communication standards such as 3G, 4G, 5G and / or 6G.

[0084] Now, with reference to FIGS. 3 to 12, we will explain in detail how the electronic device (100) identifies whether there is movement in the space where the electronic device is installed.

[0085] FIG. 3 is a flowchart illustrating a method for an electronic device according to one embodiment of the present disclosure to identify whether there is movement in a space where the electronic device is installed.

[0086] Referring to FIG. 3, the method of operation of the electronic device (100) may include operations 310 to 350. In one embodiment of the present disclosure, operations 310 to 350 may be executed by at least one processor included in the electronic device (100). The method of operation of the electronic device (100) is not limited to that shown in FIG. 3, and in one or more embodiments, operations not shown in FIG. 3 may be further included, or some operations may be omitted. This also applies to the detailed flowchart of FIG. 3 described with reference to FIG. 4 to FIG. 12. Since the operations performed by the electronic device (100) have been previously described with reference to FIG. 1 to FIG. 2, redundant descriptions may be omitted.

[0087] In operation 310, the electronic device (100) can obtain channel state information (CSI).

[0088] In one embodiment of the present disclosure, an electronic device (100) may acquire (or receive) a wireless signal. For example, the electronic device (100) may acquire (or receive) a wireless signal for a specified period of time. For example, the electronic device (100) may acquire a wireless signal transmitted by a wireless router (e.g., a wireless router (20)). The wireless signal may be a Wi-Fi signal. In one embodiment, the electronic device (100) may acquire a wireless signal via a multipath (or multi-path). The wireless signal may include a plurality of sub-carriers.

[0089] In one embodiment of the present disclosure, an electronic device (100) can analyze the characteristics of each subcarrier based on a wireless signal comprising a plurality of subcarriers received through multiple paths. The electronic device (100) can determine the frequency and time domain characteristics of the signal by considering the transmission characteristics of the wireless signal and signal deformation in a multipath environment.

[0090] In one embodiment of the present disclosure, an electronic device (100) can obtain channel state information (CSI) included in a wireless signal based on a received wireless signal. The channel state information may correspond to a plurality of subcarriers. For example, the electronic device (100) can obtain channel state information based on orthogonal frequency division multiplexing (OFDM). The channel state information may represent a channel frequency response for each subcarrier. The electronic device (100) can obtain channel state information based on the channel characteristics of the response signal by identifying the response signal of the wireless router (20) to the response request signal of the electronic device (100).

[0091] Channel state information may be information obtained by an electronic device (100) by identifying (e.g., determining) the amplitude and phase difference between the signal of each subcarrier and the reference signal. In one embodiment, the amplitude and phase difference between the signal of each subcarrier and the reference signal may be caused by a multipath effect due to the difference in medium or spatial structure between the transmission space and the reception space of the wireless signal. In one embodiment, the amplitude and phase difference between the signal of each subcarrier and the reference signal may occur if there is movement in at least one of the transmission space or the reception space.

[0092] In operation 320, the electronic device (100) can obtain channel state data by preprocessing channel state information.

[0093] In one embodiment of the present disclosure, an electronic device (100) may acquire channel state data based on channel state information acquired during a specified time. The electronic device (100) may acquire channel state data by preprocessing channel state information acquired during a specified time. The channel state data may be a physical quantity capable of representing the data flow of channel state information.

[0094] In operation 330, the electronic device (100) can obtain a time delayed relationship indicating similarity between channel state data corresponding to each time interval based on channel state data.

[0095] In one embodiment of the present disclosure, an electronic device (100) can identify channel state data corresponding to individual subcarriers (or, each frequency). Based on the channel state data, the electronic device (100) can obtain (or calculate) a time correlation that indicates the similarity of the channel state data by time interval. The channel state data may be divided by time interval. The similarity between the channel state data corresponding to each time interval may indicate the similarity between the channel state data of adjacent time intervals. For example, the electronic device (100) may obtain the similarity between the channel state data corresponding to each time interval based on an autocorrelation function (ACF), but the present disclosure is not limited to the described embodiments.

[0096] The electronic device (100) can calculate the similarity between channel state data corresponding to a reference point in each time interval. The reference point may represent one of the sampling points of the channel state data (e.g., points when a response signal is received). For example, if the Wth point is the reference point of the first time interval, the electronic device (100) can determine the similarity between the channel state data corresponding to the first point in the first window through the Wth point and the channel state data corresponding to the second point in the second window through the W+1th point, thereby determining the time similarity value corresponding to the Wth point. The electronic device (100) can determine the time similarity values ​​of other points included in the specified time, including the W+1th point, in the same manner.

[0097] In one embodiment of the present disclosure, an electronic device (100) can obtain a temporal correlation based on the similarity between channel state data corresponding to a reference point in each time interval. The electronic device (100) can obtain a temporal correlation based on a temporal similarity value corresponding to at least one reference point included in a specified time.

[0098] The temporal correlation can indicate a pattern change in channel state data over time. Channel state data may change based on the movement of the space where the electronic device (100) is installed. The temporal correlation can indicate a pattern change in channel state data. The electronic device (100) can identify the movement of the space where the electronic device (100) is installed through the temporal correlation.

[0099] In operation 340, the electronic device (100) can obtain a sub-carrier relationship indicating similarity between channel state data corresponding to each subcarrier based on channel state data.

[0100] In one embodiment of the present disclosure, an electronic device (100) can identify channel state data corresponding to individual subcarriers (or, each frequency). Based on the channel state data corresponding to each subcarrier (or, each frequency), the electronic device (100) can obtain (or calculate) a subcarrier correlation that indicates the similarity between the channel state data corresponding to each subcarrier.

[0101] Channel state data can be distinguished for each subcarrier. In one embodiment, subcarrier association may indicate similarity between channel state data of subcarriers having different frequencies. For example, subcarrier association may indicate similarity between channel state data of subcarriers having different frequencies for each time interval included in a specified time. In one embodiment of the present disclosure, subcarrier association may indicate similarity between channel state data of subcarriers having adjacent frequencies. For example, subcarrier association may indicate similarity between channel state data of subcarriers having adjacent frequencies for each time interval included in a specified time.

[0102] For example, the electronic device (100) may obtain similarity between channel state data corresponding to each subcarrier based on an auto-correlation function (ACF), but the present disclosure is not limited to the described embodiments.

[0103] The subcarrier correlation can indicate a pattern change in channel state data corresponding to each subcarrier channel over time. The channel state data may change based on the movement of the space where the electronic device (100) is installed. The subcarrier correlation can indicate a pattern change in the channel state data. Based on the subcarrier correlation, the electronic device (100) can identify the movement of the space where the electronic device (100) is installed.

[0104] A method for an electronic device (100) to obtain a subcarrier correlation that indicates similarity between channel state data corresponding to each subcarrier is described in detail with reference to FIGS. 7a to 7c and FIGS. 8a to 8b, and redundant descriptions are omitted here.

[0105] In operation 350, the electronic device (100) can identify whether there is movement in the space where the electronic device corresponding to the first time interval is installed, based on the time correlation and the subcarrier correlation. In one embodiment, the first time interval may be any time interval included in a specified time.

[0106] In one embodiment of the present disclosure, an electronic device (100) can obtain a channel state information pattern corresponding to a wireless signal based on time association and subcarrier association. For example, the electronic device (100) can obtain a channel state information pattern by connecting (or grouping) the time association and the subcarrier association. The electronic device (100) can connect (or group) the time association and the subcarrier association by assigning weights to each of the time association and the subcarrier association.

[0107] In one embodiment of the present disclosure, the electronic device (100) can identify whether there is movement in the space where the electronic device is installed corresponding to the first time interval based on a channel state information pattern. The electronic device (100) can identify whether there is movement in the space where the electronic device is installed corresponding to the first time interval using a pattern recognition model.

[0108] In one embodiment of the present disclosure, the pattern recognition model may be learned based on a first channel state information pattern in which movement exists in the space where the electronic device is installed. In one embodiment, the pattern recognition model may be learned based on a second channel state information pattern in which movement does not exist in the space where the electronic device is installed. The pattern recognition model may be an artificial intelligence model configured to classify or predict patterns of new input data by extracting features from input data and learning the relationships between the extracted features. For example, such a model may be learned to analyze the statistical characteristics of input channel state information and identify whether movement exists based on machine learning or deep learning techniques.

[0109] The electronic device (100) can train the pattern recognition model itself. During the training process of the pattern recognition model, the electronic device (100) can optimize the model parameters using multiple channel state information samples. The trained pattern recognition model may include a neural network model, and may be implemented using, for example, a convolutional neural network (CNN), a recurrent neural network (RNN), or a modified structure thereof. Additionally, the electronic device (100) can store the previously trained pattern recognition model in memory. The electronic device (100) can determine the presence or absence of movement by analyzing channel state information input in real time using the pattern recognition model.

[0110] In one embodiment of the present disclosure, an electronic device (100) can use a pattern recognition model to identify the larger value between a first similarity between a channel state information pattern and a first channel state information pattern and a second similarity between a channel state information pattern and a first channel state information pattern. If the first similarity is greater than or equal to the second similarity, the electronic device (100) can determine that there is movement in the space where the electronic device is installed. If the first similarity is less than the second similarity, the electronic device (100) can determine that there is no movement in the space where the electronic device is installed.

[0111] FIGS. 4a and 4b are drawings for illustrating a method for an electronic device to acquire channel state information according to one embodiment of the present disclosure.

[0112] Referring to FIG. 4a, the electronic device (100) and the wireless router (20) can transmit and receive wireless signals through a direct signal path (Line of Sight, LoS) (31). The electronic device (100) and the wireless router (20) can transmit and receive wireless signals through paths other than the direct signal path (Non-Line-of-Sight, NLoS) paths (32, 34, 36). The NLoS paths (32, 34, 36) may include signal paths reflected by objects such as walls, ceilings, and furniture. In a multipath environment, signals from multiple paths overlap, and each path may have unique delay and attenuation characteristics. The electronic device (100) can analyze the overlapping signals to obtain channel state information, which is a channel characteristic aggregated for each subcarrier.

[0113] If there is movement in the space (10) where the electronic device is installed, the channel state information may change. For example, if there is movement in the space (10) where the electronic device is installed, there may be a change in the signal strength and phase received by the electronic device (100) through the Line-of-Sight (LoS) path (31) and the Non-LoS (NLoS) path (32, 34, 36). For example, if there is movement in the space (10) where the electronic device is installed, the amplitude and phase of the channel state information acquired by the electronic device (100) may change over time as the path where the wireless signal is reflected in a multipath environment changes. Based on the change in the channel state information, the electronic device (100) can identify whether there is movement in the space (10) where the electronic device is installed.

[0114] Referring to FIG. 4b, the electronic device (100) can transmit and receive to and from the wireless router (20) a response request and response signal, or convert it into a general data wireless signal. The electronic device (100) can transmit a pilot signal having a predetermined amplitude and phase change between the electronic device (100) and the router (20) as a reference value for converting the wireless signal transmitted and received between the electronic device (100) and the router (20) into data. The electronic device (100) can obtain (or calculate, determine) channel state information from the difference between the amplitude and phase change of the pilot signal received at the actual receiving device and the predetermined amplitude and phase change. The electronic device (100) can calculate channel state information for each subcarrier by frequency analyzing the channel state information obtained at specified intervals. In one embodiment, the channel state information may represent the characteristics of each subcarrier.

[0115] FIG. 5a is a diagram illustrating channel state data obtained by an electronic device according to one embodiment of the present disclosure by preprocessing channel state information.

[0116] FIG. 5b is a flowchart illustrating a method for an electronic device according to one embodiment of the present disclosure to obtain channel state data by preprocessing channel state information.

[0117] From now on, we will describe the channel status information and channel status data with reference to FIGS. 5a and FIGS. 5b together.

[0118] In operation 320, the electronic device (100) can obtain channel state data by preprocessing channel state information obtained for a specified time.

[0119] Referring to FIG. 5a, in operation 322, the electronic device (100) can identify the amplitude of the plurality of subcarriers and the phase of the plurality of subcarriers based on channel state information corresponding to the plurality of subcarriers.

[0120] The electronic device (100) can obtain channel state data by preprocessing channel state information at a reference point corresponding to each time interval. The electronic device (100) can obtain (or generate) channel state data by extracting the amplitude of each subcarrier and the phase of each subcarrier from the channel state information.

[0121] In one embodiment, the channel state information may be in the form of a complex number. For example, the channel state information may include the difference in amplitude and the difference in phase change of the response signal relative to the pilot signal in the frequency band of each subcarrier.

[0122] For example, channel state information can be represented as in Equation 1.

[0123]

[0124] In mathematical formula 1, is channel state information at subcarrier k, is the amplitude of the channel response, It can represent the phase of the channel response.

[0125] Referring to operation 324, the electronic device (100) can determine channel state data corresponding to each time interval of the plurality of subcarriers based on the amplitude of the plurality of subcarriers and the phase of the plurality of subcarriers.

[0126] In one embodiment of the present disclosure, the electronic device (100) can obtain a power value corresponding to a subcarrier by preprocessing channel state information. For example, the electronic device (100) can obtain a power value for each time interval by squaring the amplitude of each subcarrier. For example, the electronic device (100) can obtain a power value corresponding to at least one of the entire subcarrier or individual subcarriers by squaring the amplitude.

[0127] In one embodiment of the present disclosure, the electronic device (100) can preprocess channel state information to obtain a phase angle value corresponding to a subcarrier. For example, for each time interval, the electronic device (100) can obtain at least one of a phase angle value corresponding to the entire subcarrier or a phase angle value corresponding to an individual subcarrier.

[0128] Referring to FIG. 5b, the channel state data (510) for each time interval is each subcarrier Channel characteristics corresponding to can be represented. In one embodiment, in the channel state data (510) θ is the frequency of the subcarrier with index i, t is the reference point of each time interval, t=M is ​​the end point of the specified time, and a may represent power or phase angle. i has a value from 1 to N, and N may represent the total number of subcarriers. N may be determined according to the frequency band of the radio signal.

[0129] for example, is the frequency obtained at the reference time t=0 It can represent channel state data of a subcarrier having. For example, is the frequency obtained at the reference time t=k It can represent channel state data of a subcarrier having. For example, is the frequency obtained at the reference time t=0 It can represent channel state data of a subcarrier having.

[0130] FIG. 6a is a flowchart for further explaining a method for an electronic device included in operation 330 according to one embodiment of the present disclosure to obtain a time correlation.

[0131] In operation 332, the electronic device (100) can determine a time similarity value corresponding to a specific point in time (e.g., point W).

[0132] In one embodiment of the present disclosure, an electronic device (100) may determine a time similarity value at a specific point in time (e.g., a W-th point in time) based on a sliding window technique. The time similarity value may be at least one value. A sliding window technique may represent a method of processing data by moving a window (interval) of fixed size over the data. A W-th point in time may be a reference point in a first time interval. The window may represent a data set of channel state data acquired by the electronic device (100) at regular intervals.

[0133] In one embodiment of the present disclosure, an electronic device (100) can compare channel state data corresponding to a first time point to a W time point within a first window with channel state data corresponding to a second time point to a W+1 time point within a second window. The electronic device (100) can determine the similarity between the channel state data corresponding to a first time point to a W time point within the first window and the channel state data corresponding to a second time point to a W+1 time point within the second window, thereby determining the temporal similarity corresponding to the W time point. For example, the electronic device (100) can identify whether the amount of change in channel state data over time is correlated with each other. For example, the electronic device (100) can determine the temporal similarity value based on an auto-correlation function (ACF).

[0134] The electronic device (100) can finely identify changes in channel state data over time by comparing channel state data included in the first window and the second window. In one embodiment of the present disclosure, the electronic device (100) can identify that movement occurred within the space where the electronic device (100) is installed in the first time interval corresponding to the W time point when the similarity value between the first window and the second window decreases (e.g., approaches 0). In one embodiment, the electronic device (100) can identify that movement did not occur within the space where the electronic device (100) is installed at the W time point when the similarity value between the first window and the second window increases (e.g., approaches 1), but the present disclosure is not limited to the described embodiments.

[0135] In operation 334, the electronic device (100) can obtain a time correlation based on a similarity value corresponding to at least one reference point included in the specified time. The time correlation may be represented in the form of a vector or a matrix.

[0136] In one embodiment of the present disclosure, the electronic device (100) can obtain a time correlation for each individual subcarrier. The time correlation may be represented as a matrix indicating the similarity between channel state data for each subcarrier corresponding to each time interval. This is explained with reference to FIG. 6b, and redundant descriptions are omitted.

[0137] In one embodiment of the present disclosure, the electronic device (100) can obtain a time correlation for the entire subcarrier. The time correlation may be represented as a vector indicating the similarity between channel state data for the entire subcarrier corresponding to each time interval. This is explained with reference to FIG. 6c, and redundant descriptions are omitted.

[0138] FIG. 6b is a drawing for illustrating a time association diagram according to one embodiment of the present disclosure.

[0139] The electronic device (100) can obtain a temporal correlation by determining (or calculating) a temporal similarity value between channel state data corresponding to two different windows. The temporal similarity value may be at least one value. The electronic device (100) can obtain a temporal similarity value by identifying the similarity between channel state data (510) corresponding to adjacent windows.

[0140] In one embodiment of the present disclosure, the electronic device (100) may determine a time similarity value (640) corresponding to each subcarrier at time W based on channel state data (510) corresponding to each subcarrier at time W to time W within a first window (610) of channel state data and channel state data (510) corresponding to each subcarrier at time W to time W+1 within a second window (620). In one embodiment of the present disclosure, the electronic device (100) may determine a time similarity value corresponding to each subcarrier at time W+1 based on channel state data (510) corresponding to each subcarrier at time W to time W+1 within a second window (620) of channel state data and channel state data (510) corresponding to each subcarrier at time W to time W+2 within a third window (630).

[0141] The electronic device (100) can obtain a time correlation (650) based on a similarity value corresponding to each subcarrier of at least one reference time included in a specified time.

[0142] In one embodiment of the present disclosure, the electronic device (100) can obtain a time similarity value (640) of an individual subcarrier with respect to time W. In the channel state data (510), each subcarrier is It can be represented as follows. i can represent a value between 1 and N. N can represent the total number of subcarriers. N can be determined according to the frequency band of the radio signal.

[0143] Sub-carrier A first window (610) and a second window (620) may be defined regarding the i-th channel state data of. The electronic device (100) is a subcarrier The i-th similarity value at time W ( ) can be determined. The electronic device (100) can determine a time similarity value (640) for at least one subcarrier included in the frequency band of the wireless signal.

[0144] In one embodiment of the present disclosure, an electronic device (100) can identify a reference point corresponding to each (or individual) time interval included in a specified time. The electronic device (100) can obtain a time correlation (650) based on a time similarity value corresponding to at least one reference point included in the specified time. The electronic device (100) can obtain the time correlation (650) by integrating (e.g., connecting, combining) the time similarity values ​​corresponding to at least one reference point included in the specified time. The time correlation (650) may be represented as a matrix indicating the similarity between channel state data for each subcarrier corresponding to at least one reference point included in the specified time.

[0145] The electronic device (100) can identify the channel characteristics of individual subcarriers based on the time correlation of individual subcarriers. For example, the electronic device (100) can identify the stability or change of a specific frequency band included in a wireless signal based on the time correlation of individual subcarriers.

[0146] FIG. 6c is a drawing for illustrating a time association diagram according to one embodiment of the present disclosure.

[0147] Referring to FIG. 6c, the electronic device (100) can obtain a temporal similarity value between channel state data corresponding to two different windows, such that the temporal similarity value is at least one value. The electronic device (100) can obtain a temporal similarity value by identifying the similarity between channel state data (510) corresponding to adjacent windows.

[0148] In one embodiment of the present disclosure, an electronic device (100) can identify a similarity between channel state data (510) corresponding to a first window (610) including a first time point to a W-th time point and a second window (620) including a second time point to a W+1-th time point, and identify a time similarity value (642) corresponding to the W-th time point. For example, the electronic device (100) can identify a similarity between channel state data (510) corresponding to a second window (620) including a second time point to a W+2-th time point and a third window (630) including a third time point to a W+2-th time point, and identify a time similarity value corresponding to the W+1-th time point.

[0149] The electronic device (100) can obtain a time similarity value (642) of the entire subcarrier with respect to the W time point. In one embodiment, the electronic device (100) obtains a first similarity value ( ) to the Nth similarity value at time W ( Once ) is determined, the similarity values( inside The time similarity value (642) of the entire subcarrier can be determined based on the statistical value of )). For example, the electronic device (100) can determine the time similarity values ​​( at the W reference point ( inside The time similarity value (642) of the entire subcarrier at time W can be determined based on the average value of ).

[0150] The electronic device (100) can obtain a time correlation (652) based on a similarity value of at least one reference point included in the specified time. In one embodiment of the present disclosure, the electronic device (100) can identify a reference point corresponding to each time interval included in the specified time. The electronic device (100) can obtain a time correlation (652) based on a time similarity value corresponding to at least one reference point included in the specified time. The time correlation (662) may be represented as a vector indicating the similarity between channel state data of the entire subcarrier corresponding to at least one reference point included in the specified time.

[0151] The electronic device (100) can identify the temporal characteristics of the entire wireless communication environment or changes that occur in the space where the electronic device is installed (e.g., the occurrence of movement) based on the temporal correlation of the entire subcarrier.

[0152] FIG. 7a is a flowchart for further explaining a method in which an electronic device included in operation 340 according to one embodiment of the present disclosure obtains a subcarrier association.

[0153] In operation 342, the electronic device (100) can determine a subcarrier similarity value corresponding to a specific time point (e.g., a W-th time point). The W-th time point may be a reference time point of a first time interval. The subcarrier similarity value corresponding to a specific time point (e.g., a W-th time point) may include at least one of a matrix, a vector, or at least one of at least one value.

[0154] In one embodiment of the present disclosure, an electronic device (100) may determine a subcarrier similarity value corresponding to time W based on channel state data corresponding to two different subcarriers for time W. For example, the electronic device (100) may determine the subcarrier similarity value based on at least one of an auto-correlation function (ACF) or a cross-correlation function, but the present disclosure is not limited to the described embodiments.

[0155] In one embodiment of the present disclosure, the electronic device (100) can determine a subcarrier similarity value (e.g., a subcarrier similarity matrix) between channel state data corresponding to all subcarriers for a W time point. The electronic device (100) can obtain subcarrier similarity based on the subcarrier similarity value (e.g., a subcarrier similarity matrix) between channel state data corresponding to all subcarriers.

[0156] In one embodiment of the present disclosure, the electronic device (100) can determine a subcarrier similarity value between channel state data corresponding to adjacent subcarriers for a W time point. The electronic device (100) can determine a subcarrier similarity value based on the similarity between channel state data corresponding to adjacent subcarriers.

[0157] In operation 344, the electronic device (100) can obtain a subcarrier association based on a subcarrier similarity value corresponding to at least one reference point included in a specified time. The subcarrier association may be represented in the form of a vector or a matrix.

[0158] In one embodiment of the present disclosure, an electronic device (100) may obtain subcarrier similarity values ​​between all subcarriers corresponding to at least one reference time included in a specified time. Based on the subcarrier similarity values, the electronic device (100) may obtain subcarrier association. The subcarrier association may be represented as a matrix indicating the similarity between channel state data for each time interval corresponding to each subcarrier. This is explained with reference to FIG. 7b, and redundant descriptions are omitted.

[0159] In one embodiment of the present disclosure, an electronic device (100) may obtain a subcarrier correlation based on a similarity value between adjacent (or consecutive) subcarriers corresponding to at least one reference time included in a specified time. The subcarrier correlation may be represented as a matrix indicating the similarity between channel state data for each time interval corresponding to adjacent subcarriers. This is explained with reference to FIG. 7c, and redundant descriptions are omitted.

[0160] FIG. 7b is a diagram illustrating a subcarrier association diagram according to one embodiment of the present disclosure.

[0161] The electronic device (100) can obtain a subcarrier correlation by calculating a subcarrier similarity value between channel state data corresponding to subcarriers corresponding to different frequencies. In one embodiment of the present disclosure, the electronic device (100) can obtain a subcarrier similarity value between a first subcarrier and a second subcarrier based on channel state data (710) corresponding to a first subcarrier of channel state data (510) and channel state data (720) corresponding to a second subcarrier. In one embodiment of the present disclosure, the electronic device (100) can obtain a subcarrier similarity value between a first subcarrier and a third subcarrier based on channel state data (710) corresponding to a first subcarrier of channel state data (510) and channel state data (730) corresponding to a third subcarrier. In one embodiment of the present disclosure, the electronic device (100) can obtain a subcarrier similarity value between the second subcarrier and the third subcarrier based on channel state data (720) corresponding to the second subcarrier of the channel state data (510) and channel state data (730) corresponding to the third subcarrier.

[0162] In one embodiment of the present disclosure, if the reference time point of the first time interval is the W time point, the electronic device (100) has channel state data corresponding to the first subcarrier for the W time point ( ) and channel state data corresponding to the second subcarrier ( Based on ), a subcarrier similarity value (Subrlt12_tW) between the first subcarrier and the second subcarrier corresponding to the Wth time point can be obtained. The subcarrier similarity value (Subrlt_tW, 740) corresponding to the Wth time point can be represented as a matrix indicating the similarity between all subcarriers at a specific time point (e.g., the Wth time point).

[0163] For example, in the subcarrier similarity value (740) corresponding to the Wth time point, Subrlt13_tW may represent the subcarrier similarity value between the first subcarrier and the third subcarrier at the Wth time point. SubrltN1_tW may represent the subcarrier similarity value between the first subcarrier and the Nth subcarrier at the Wth time point. N may represent the number of subcarriers included in the frequency band of the wireless signal.

[0164] The electronic device (100) can obtain a subcarrier association (750) based on subcarrier similarity corresponding to at least one reference point included in the specified time. In one embodiment, the electronic device (100) can obtain a subcarrier similarity value Subrlt_tW+1 corresponding to the W+1 time point through an operation similar to the process of obtaining a subcarrier similarity value (740) corresponding to the W time point. The electronic device (100) can obtain a subcarrier similarity value Subrlt_tW+1 corresponding to the W+2 time point. The electronic device (100) can obtain a subcarrier association (750) by connecting (or combining) subcarrier similarity values ​​corresponding to at least one reference point included in the specified time (e.g., the W time point, the W+1 time point, the W+2 time point, etc.).

[0165] FIG. 7c is a drawing for illustrating a time association diagram according to one embodiment of the present disclosure.

[0166] The electronic device (100) can obtain a subcarrier correlation by calculating a subcarrier similarity value between channel state data corresponding to two adjacent subcarriers. Two adjacent subcarriers may represent two subcarriers corresponding to adjacent frequencies.

[0167] In one embodiment of the present disclosure, the electronic device (100) can obtain a subcarrier similarity value between the first subcarrier and the second subcarrier based on channel state data (710) corresponding to the first subcarrier of the channel state data (510) and channel state data (720) corresponding to the second subcarrier. In one embodiment of the present disclosure, the electronic device (100) can obtain a subcarrier similarity value between the second subcarrier and the third subcarrier based on channel state data (720) corresponding to the second subcarrier of the channel state data (510) and channel state data (730) corresponding to the third subcarrier. The electronic device (100) may not obtain a subcarrier similarity value between channel state data corresponding to two non-adjacent subcarriers (e.g., channel state data (710) corresponding to the first subcarrier and channel state data (730) corresponding to the third subcarrier).

[0168] In one embodiment of the present disclosure, if the reference time point of the first time interval is the W time point, the electronic device (100) has channel state data corresponding to the first subcarrier for the W time point ( ) and channel state data corresponding to the second subcarrier ( Based on ), a subcarrier similarity value (Subrlt12_tW) between the first subcarrier and the second subcarrier corresponding to time W can be obtained. The electronic device (100) obtains channel state data (N-1 subcarrier) corresponding to time W. ) and channel state data corresponding to the Nth subcarrier ( Based on ), a subcarrier similarity value (Subrlt(N-1)(N)_tW) between the N-1 subcarrier and the N subcarrier corresponding to the W time point can be obtained. The subcarrier similarity value (Subrlt12_tW to Subrlt(N-1)(N)_tW) corresponding to the W time point can be represented as a vector indicating the similarity between adjacent subcarriers at a specific time point (e.g., the W time point).

[0169] The electronic device (100) can obtain a subcarrier association (760) based on a subcarrier similarity value corresponding to at least one reference point included in the specified time. In one embodiment, the electronic device (100) can obtain a subcarrier similarity value Subrlt_tW+1 corresponding to the W+1 time point through an operation similar to the process of obtaining a subcarrier similarity value (740) corresponding to the W time point. The electronic device (100) can obtain subcarrier similarity values ​​(Subrlt12_tW+1 to Subrlt(N-1)(N)_tW+1) corresponding to the W+2 time point. The electronic device (100) can obtain a subcarrier association (760) by connecting (or combining) subcarrier similarity values ​​corresponding to at least one reference point included in the specified time (e.g., the W time point, the W+1 time point, the W+2 time point, etc.).

[0170] FIG. 8a is a flowchart for explaining in detail how an electronic device included in operation 344 acquires a subcarrier association according to one embodiment of the present disclosure.

[0171] In operation 345, the electronic device (100) can determine an average subcarrier similarity value for each subcarrier by dividing the sum of the subcarrier similarity values ​​corresponding to the Wth time point for each subcarrier by the number of subcarrier similarity values ​​corresponding to the Wth time point for each subcarrier. The average subcarrier similarity may be represented in at least one form of a vector, a matrix, or a value.

[0172] In operation 346, the electronic device (100) can obtain a subcarrier association based on an average subcarrier similarity value corresponding to at least one reference point included in a specified time. The subcarrier association may be represented in the form of a vector or a matrix.

[0173] Operations 345 and 346 will be described in detail below with reference to FIG. 8b.

[0174] FIG. 8b is a diagram illustrating a subcarrier association diagram according to one embodiment of the present disclosure.

[0175] The electronic device (100) can obtain a subcarrier similarity value (Subrlt_tW, 740) corresponding to time W. Since the subcarrier similarity value (Subrlt_tW, 740) was previously explained with reference to FIG. 7b, a redundant explanation is omitted here.

[0176] The electronic device (100) can identify a portion (742) indicating the association between the first subcarrier and other subcarriers (744, 746, ...) in the subcarrier similarity value (740) corresponding to the W time point. In one embodiment, the electronic device (100) can determine a value representing the portion (742) indicating the association between the first subcarrier and other subcarriers corresponding to the W time point. For example, the electronic device (100) can determine the average subcarrier similarity value (meanSubrlt1_tW) for the first subcarrier by dividing the sum of the subcarrier similarity values ​​corresponding to the W time point included in the portion (742) indicating the association between the first subcarrier and other subcarriers by the number of subcarrier similarity values ​​corresponding to the W time point for each subcarrier.

[0177] In one embodiment of the present disclosure, the electronic device (100) may determine a value representing a portion (744) that indicates the association between a second subcarrier and another subcarrier corresponding to time W. For example, the electronic device (100) may determine an average subcarrier similarity value (meanSubrlt2_tW) for the second subcarrier.

[0178] In one embodiment of the present disclosure, the electronic device (100) can obtain meanSubrlt_tW, which is a matrix (810) (i.e., mean subcarrier similarity matrix) representing the association between a specific subcarrier and another subcarrier corresponding to time W.

[0179] In one embodiment of the present disclosure, the electronic device (100) may obtain a subcarrier association (820) based on an average subcarrier similarity value corresponding to at least one reference time included in a specified time. The subcarrier association (820) may be represented as a matrix indicating the similarity between channel state data for each time interval corresponding to all subcarriers.

[0180] FIG. 9a is a flowchart for further explaining a method for an electronic device included in operation 350 according to one embodiment of the present disclosure to acquire a channel state information pattern.

[0181] In operation 352, the electronic device (100) can obtain a channel state information pattern corresponding to a wireless signal based on time association and subcarrier association. In one embodiment, the electronic device (100) can group the time association and subcarrier association into a channel state information pattern (e.g., integrating, concatenating). The electronic device (100) can obtain the channel state information pattern by combining (e.g., integrating or concatenating) the data of the time association and subcarrier association and presenting them in a single structured data format. The channel state information pattern may be in the form of at least one of a vector or a matrix.

[0182] In one embodiment of the present disclosure, the electronic device (100) may integrate the time correlation and the subcarrier correlation based on a time interval (or a reference point of the time interval). In one embodiment, the electronic device (100) may obtain a channel state information pattern by arranging the time correlation and the subcarrier correlation corresponding to the same time interval (or a reference point of the time interval) in at least one of the same row or the same column.

[0183] In one embodiment of the present disclosure, the electronic device (100) may arrange the time correlation and subcarrier correlation obtained in a specific time interval in a single column. For example, the electronic device (100) may obtain a channel state information pattern by arranging the time correlation and subcarrier correlation calculated in at least one time interval included in a specified time in a single column, such as arranging the time correlation and subcarrier correlation obtained in a first time interval in column 1 and the time correlation and subcarrier correlation obtained in a second time interval in column 2.

[0184] In one embodiment of the present disclosure, the electronic device (100) may determine a time similarity value corresponding to a W time point (e.g., a reference time point of a first time interval) included in the time association diagram as a first component of the channel state information pattern. The first component may represent a row, column, or row and column component of the channel state information pattern, but the present disclosure is not limited to the above-described embodiment.

[0185] The electronic device (100) may determine a time similarity value corresponding to the W+1 time point included in the time association diagram as a second component of the channel state information pattern. The second component may represent components of the next column or next row of the first component, but the present disclosure is not limited to the embodiments described above.

[0186] In one embodiment of the present disclosure, the electronic device (100) can identify a first subset, which is at least one subcarrier similarity value for a W time point included in the subcarrier association diagram. The first subset may be in the form of at least one of a matrix, a vector, or a value. In one embodiment, the electronic device (100) can identify a second subset, which is at least one subcarrier similarity value for a W+1 time point (e.g., a reference time point of a second time interval) included in the subcarrier association diagram. The second subset may be in the form of at least one of a matrix, a vector, or a value.

[0187] The electronic device (100) can obtain a channel state information pattern by connecting the time correlation and the subcarrier correlation so that the first component, the components of the first subset, the second component, and the components of the second subset are positioned in order. In one embodiment of the present disclosure, the electronic device (100) can arrange the time correlation and the subcarrier correlation calculated in a specific time interval side by side in a single row. For example, the electronic device (100) can obtain a channel state information pattern by continuously arranging the time correlation and the subcarrier correlation obtained in at least one time interval included in a specified time in a single row, such as arranging the time correlation and the subcarrier correlation obtained in the first time interval side by side in a single row, and then arranging the time correlation and the subcarrier correlation obtained in the second time interval side by side in the first row after the last component of the time correlation and the subcarrier correlation obtained in the first time interval.

[0188] In one embodiment of the present disclosure, the electronic device (100) may determine the time association as a reference row of the channel state information pattern. In one embodiment, the electronic device (100) may obtain the channel state information pattern by connecting the time association and the subcarrier association such that the subcarrier similarity value corresponding to the Wth time point of the subcarrier association is located in the same column as the time similarity value corresponding to the Wth time point of the time association.

[0189] In one embodiment of the present disclosure, an electronic device (100) can obtain a channel state information pattern by assigning mutual weights to time association and subcarrier association. For example, the electronic device (100) can obtain a channel state information pattern by setting the weight of the time association to 1 and the weight of the subcarrier association to 1. For example, the electronic device (100) can obtain a channel state information pattern by setting the weight of the time association to 1 and the weight of the subcarrier association to 2. The weights may be values ​​calculated by the electronic device (100). The weights may be values ​​obtained by the electronic device (100) by calculating them on another electronic device or server.

[0190] In operation 354, the electronic device (100) can identify whether there is movement in the space where the electronic device corresponding to the first time interval is installed, based on the channel state information pattern using a pattern recognition model.

[0191] FIG. 9b is a drawing for illustrating a pattern recognition model according to one embodiment of the present disclosure.

[0192] Referring to FIG. 9b, the pattern recognition model (950) may be learned based on a first channel state information pattern (910) and a second channel state information pattern (920). In one embodiment, the electronic device (100) may obtain first channel state information when there is movement between the electronic device and the wireless router. In one embodiment, the electronic device (100) may obtain a first time correlation and a first subcarrier correlation based on the first channel state information. The electronic device (100) may obtain a first channel state information pattern (910) based on the first time correlation and the first subcarrier correlation.

[0193] In one embodiment of the present disclosure, the electronic device (100) may obtain second channel state information when there is no movement between the electronic device and the wireless router. In one embodiment of the present disclosure, the electronic device (100) may obtain a second time correlation and a second subcarrier correlation based on the second channel state information. The electronic device (100) may obtain a second channel state information pattern (920) based on the second time correlation and the second subcarrier correlation.

[0194] The pattern recognition model (950) may be a model trained by a plurality of training data that takes the first channel state information pattern (910) and the second channel state information pattern (920) as inputs and outputs whether there is movement in the space where the electronic device is installed.

[0195] In one embodiment of the present disclosure, the pattern recognition model (950) can learn the characteristic difference between the first channel state information pattern (910) and the second channel state information pattern (920). The pattern recognition model (950) can identify changes or characteristics of the channel state information pattern caused by movement. In one embodiment of the present disclosure, the electronic device (100) can train the pattern recognition model in advance. In one embodiment of the present disclosure, the electronic device (100) may store a pattern recognition model that has been trained in advance.

[0196] In one embodiment of the present disclosure, the electronic device (100) can distinguish the movement of the space in which the electronic device is installed into two states (e.g., binary form): a 'state of no movement' and a 'state of movement'. The electronic device (100) may learn only one of the two state channel state information patterns. Even if the electronic device (100) learns only one of the two state channel state information patterns, it can identify both states. For example, the electronic device (100) may learn only the channel state information pattern of the state of no movement of the space in which the electronic device is installed. In one embodiment, the electronic device (100) can identify the learned state (i.e., the state of no movement) by identifying the channel state information pattern. For example, the electronic device (100) can identify the state of movement by identifying the channel state information pattern.

[0197] In one embodiment of the present disclosure, the electronic device (100) can determine that if it fails to identify a learned state (e.g., a state without movement), it is immediately a state not learned (e.g., a state with movement). Accordingly, the electronic device (100) can determine whether it is a state with movement or a state without movement by determining whether a channel state information pattern corresponds to a learned state or a state not learned.

[0198] In one embodiment of the present disclosure, the electronic device (100) can identify both a state without movement and a state with movement by learning a channel state information pattern corresponding to a state without movement. The electronic device (100) can identify both a state without movement and a state with movement by learning a channel state information pattern corresponding to a state with movement.

[0199] In one embodiment of the present disclosure, the electronic device (100) operates with a binary judgment structure, so that it can indirectly recognize another state (e.g., 'movement present') with only one learned state (e.g., 'no movement').

[0200] According to one embodiment of the present disclosure, a pattern recognition model (950) may operate in an electronic device (100). According to one embodiment of the present disclosure, the pattern recognition model (950) may take a channel state information pattern as input and output whether there is movement in the space where the electronic device is installed. The electronic device (100) may collect learning data during operation, and when a reference number or more of learning data is collected, the pattern recognition model (950) may be trained. Additionally, the electronic device (100) may collect additional learning data during operation to reinforce the pattern recognition model (950).

[0201] According to one embodiment of the present disclosure, the pattern recognition model (950) may represent a neural network model (e.g., CNN (Convolutional Neural Network), DNN (Deep Neural Network), RNN (Recurrent Neural Network), RBM (Restricted Boltzmann Machine), DBN (Deep Belief Network), BRDNN (Bidirectional Recurrent Deep Neural Network)). The pattern recognition model may be machine learned based on a first channel state information pattern and a second channel state information pattern. The pattern recognition model may be machine learned to determine whether there is movement in the space where the electronic device is installed based on the channel state information pattern.

[0202] According to one embodiment of the present disclosure, the pattern recognition model (950) may operate on a server. The electronic device (100) transmits collected training data to the server, and the server may train the pattern recognition model (950) using the collected training data. Additionally, if additional training data is collected, the server may perform reinforcement training on the pattern recognition model (950). When the pattern recognition model (950) operates on a server, the electronic device (100) transmits a channel state information pattern to the server, and the server may obtain whether there is movement in the space where the electronic device is installed using the pattern recognition model (950). The server may transmit whether there is movement in the space where the electronic device is installed to the electronic device (100).

[0203] According to one embodiment of the present disclosure, an electronic device (100) may input a channel state information pattern obtained based on channel state information (or preprocessed channel state information) into a pattern recognition model (950). For example, the electronic device (100) may, through a preprocessing process, obtain channel state data from channel state information, obtain time correlation and subcarrier correlation based on channel state data, obtain a channel state information pattern based on time correlation and subcarrier correlation, and input it into a pattern recognition model (950).

[0204] In one embodiment of the present disclosure, the electronic device (100) can identify in real time whether there is movement (940) in the space where the electronic device is installed, corresponding to a first time interval, based on a channel state information pattern (930), using a learned pattern recognition model (950).

[0205] FIG. 9c is a flowchart for further explaining a method for identifying whether there is movement in a space where an electronic device is installed based on a channel state information pattern included in operation 354 according to one embodiment of the present disclosure.

[0206] In operation 960, the electronic device (100) can obtain (or determine, calculate) a first similarity between a channel state information pattern and a first channel state information pattern. The electronic device (100) can obtain (or determine, calculate) a second similarity between a channel state information pattern and a second channel state information pattern.

[0207] In operation 970, the electronic device (100) can identify the larger value between the first similarity and the second similarity.

[0208] In operation 980, the electronic device (100) can determine (or, decide, identify) that there is movement in the space where the electronic device is installed based on the fact that the first similarity is greater than or equal to the second similarity.

[0209] In operation 990, the electronic device (100) may determine (or decide) that there is no movement in the space where the electronic device is installed, based on the fact that the first similarity is less than the second similarity.

[0210] FIG. 9d is a flowchart for further explaining a method for identifying whether there is movement in a space where an electronic device is installed based on a channel state information pattern included in operation 354 according to one embodiment of the present disclosure.

[0211] In operation 962, the electronic device (100) can obtain (or determine, calculate) a first similarity between a channel state information pattern and a first channel state information pattern.

[0212] In operation 972, the electronic device (100) can identify whether the first similarity is greater than or equal to a first threshold. The first threshold may be a fixed value. The first threshold may be a value obtained from a server or an external device.

[0213] In operation 982, if the first similarity is greater than or equal to the first threshold value, the electronic device (100) can determine (or, determine, identify) that there is movement in the space where the electronic device is installed.

[0214] In operation 992, if the first similarity is less than the first threshold value, the electronic device (100) may determine (or decide) that there is no movement in the space where the electronic device is installed.

[0215] FIG. 9e is a flowchart for further explaining a method for identifying whether there is movement in a space where an electronic device is installed based on a channel state information pattern included in operation 354 according to one embodiment of the present disclosure.

[0216] In operation 964, the electronic device (100) can obtain (or determine, calculate) a second similarity between a channel state information pattern and a second channel state information pattern.

[0217] In operation 974, the electronic device (100) can identify whether the second similarity is greater than or equal to a second threshold. The second threshold may be a fixed value. The second threshold may be a value obtained from a server or an external device.

[0218] In operation 984, if the second similarity is greater than or equal to the second threshold value, the electronic device (100) can determine (or, determine, identify) that there is no movement in the space where the electronic device is installed.

[0219] In operation 994, if the second similarity is less than the second threshold value, the electronic device (100) may determine (or decide) that there is no movement in the space where the electronic device is installed.

[0220] The electronic device (100) can smoothly identify whether there is movement in the space where the electronic device is installed, even when it has learned based on one of the first channel state information pattern or the second channel state information pattern through the operations described with reference to FIGS. 9d to 9e.

[0221] FIG. 10a is a drawing for illustrating a channel state information pattern according to one embodiment of the present disclosure.

[0222] In one embodiment of the present disclosure, an electronic device (100) can obtain a channel state information pattern (1010) by connecting the time association diagram (662) described with reference to FIG. 6c and the subcarrier association diagram (750) described with reference to FIG. 7b. In one embodiment, the electronic device (100) can obtain a channel state information pattern (1010) by connecting (or grouping, integrating) the time association diagram (662) and the subcarrier association diagram (750) so that parts corresponding to the same time interval in the time association diagram (662) and the subcarrier association diagram (750) are arranged side by side.

[0223] The electronic device can create a patterned data structure by connecting or integrating the time association (662) and the subcarrier association (750) so that parts corresponding to the same time interval are placed side by side. For example, in the channel state information pattern (1010), the first component represents the time association of the first time interval, and the next component (e.g., the next column components of the same row) may list the subcarrier association of the first time interval. The subcarrier association may consist of values ​​expressing the interrelationship between individual subcarriers. For example, in the channel state information pattern (1010), the time association corresponding to the second time interval may be placed after the subcarrier association corresponding to the first time interval (e.g., the next column components of the same row), and the subcarrier association of the second time interval may be listed in the same manner.

[0224] For example, the electronic device (100) has a time correlation in which the first component corresponds to a first time interval. And, A channel state information pattern (1010) can be obtained in which the components of Subrlt_tW, which is a subcarrier association corresponding to the first time interval (or the Wth time point, which is the reference point of the first time interval), are listed in order in the next component. In the channel state information pattern (1010), Subrlt12_tW may represent the subcarrier association between the first subcarrier and the second subcarrier in the first time interval (or the Wth time point, which is the reference point of the first time interval). In the channel state information pattern (1010), SubrltN(N-1)_tW may represent the subcarrier association between the Nth subcarrier and the N-1st subcarrier in the first time interval (or the Wth time point, which is the reference point of the first time interval). The channel state information pattern (1010) is the next component of SubrltN(N-1)_tW, which is a time association corresponding to the second time interval There exists, The next component (or next column component) of may be in the form where the components of Subrlt_tW+1, which are subcarrier associations corresponding to the second time interval (or the reference point of the second time interval, the W+1 time point), are listed in order.

[0225] FIG. 10b is a drawing for illustrating a channel state information pattern according to one embodiment of the present disclosure.

[0226] In one embodiment of the present disclosure, an electronic device (100) can obtain a channel state information pattern (1020) by connecting the time association diagram (662) described with reference to FIG. 6c and the subcarrier association diagram (820) described with reference to FIG. 8b. In one embodiment, the electronic device (100) can obtain a channel state information pattern (1020) by connecting (or grouping, integrating) the time association diagram (662) and the subcarrier association diagram (820) so that parts corresponding to the same time interval in the time association diagram (662) and the subcarrier association diagram (820) are arranged side by side.

[0227] The electronic device can create a patterned data structure by connecting or integrating the time association (662) and the subcarrier association (820) so that parts corresponding to the same time interval are placed side by side. For example, in the channel state information pattern (1020), the first component represents the time association of the first time interval, and the next component (e.g., the next column components of the same row) may list the subcarrier association of the first time interval. The subcarrier association may consist of average subcarrier similarities corresponding to the first time interval. For example, in the channel state information pattern (1020), the time association corresponding to the second time interval may be placed after the subcarrier association corresponding to the first time interval (e.g., the next column components of the same row), and the subcarrier association of the second time interval may be listed in the same manner.

[0228] For example, the electronic device (100) has a time correlation in which the first component corresponds to a first time interval. And, A channel state information pattern (1020) can be obtained in which components of meanSubrlt_tW, which is the average subcarrier similarity corresponding to the first time interval (or the Wth time point, which is the reference time point of the first time interval), are listed in order in the next component. In the channel state information pattern (1020), meanSubrlt1_tW may represent the average subcarrier similarity value for the first subcarrier. In the channel state information pattern (1020), meanSubrltN_tW may represent the average subcarrier similarity value for the Nth subcarrier. The channel state information pattern (1020) is the next component (or next column component) of meanSubrltN_tW, which is the time correlation corresponding to the second time interval There exists, The following components may be in the form of meanSubrlt_tW+1, which is the mean subcarrier similarity corresponding to the second time interval (or the reference time point of the second time interval, which is the W+1 time point), listed in order.

[0229] FIG. 10c is a drawing for illustrating a channel state information pattern according to one embodiment of the present disclosure.

[0230] In one embodiment of the present disclosure, the electronic device (100) can obtain a channel state information pattern (1030) by connecting the time association diagram (662) described with reference to FIG. 6c and the subcarrier association diagram (760) described with reference to FIG. 7c. In one embodiment, the electronic device (100) can obtain a channel state information pattern (1030) by connecting (or grouping, integrating) the time association diagram (662) and the subcarrier association diagram (760) so that parts corresponding to the same time interval in the time association diagram (662) and the subcarrier association diagram (760) are arranged side by side.

[0231] The electronic device can create a patterned data structure by connecting or integrating the time association (662) and the subcarrier association (760) such that parts corresponding to the same time interval are placed in the same column. For example, in the channel state information pattern (1020), the first component represents the time association of the first time interval, and the next component (e.g., the next row components in the same column) may list the subcarrier association of the first time interval. The subcarrier association may consist of similarity values ​​between adjacent subcarriers corresponding to the first time interval. For example, in the channel state information pattern (1020), the time association corresponding to the second time interval may be placed after the subcarrier association corresponding to the first time interval (e.g., the next column component in the same row), and the subcarrier association corresponding to the second time interval may be listed in the same manner as the next components of the time association corresponding to the second time interval (e.g., the next row components in the same column).

[0232] For example, the electronic device (100) has a time correlation in which the first component corresponds to a first time interval. And, A channel state information pattern (1030) can be obtained in which Subrlt12_tW, Subrlt23_tW, ..., Subrlt(N-1)(N)_tW, which are subcarrier similarities corresponding to the first time interval (or the reference time point W of the first time interval), are listed in order as the next row components. In the channel state information pattern (1030), Subrlt12_tW may represent the subcarrier similarity value between the first subcarrier and the second subcarrier in the first time interval. In the channel state information pattern (1030), Subrlt(N-1)(N)_tW may represent the subcarrier similarity value between the (N-1) subcarrier and the N subcarrier in the first time interval. The channel state information pattern (1030) As the next column component of, the time association corresponding to the second time interval There exists, The following row components may be in the form of average subcarrier similarities Subrlt12_tW+1, Subrlt23_tW+1 ... Subrlt(N-1)(N)_tW+1 corresponding to the second time interval (or the reference time point of the second time interval, which is time point W+1), listed in order.

[0233] The channel state information pattern (1010, 1020, 1030) described with reference to FIG. 10a, 10b, or 10c above may simultaneously include the relationship between the characteristics of a signal that changes over time and the subcarrier (or frequency). An electronic device can comprehensively analyze the interaction between the temporal change and the frequency based on the channel state information pattern (1010, 1020, 1030). The channel state information pattern (1010, 1020, 1030) can represent the characteristics of a wireless signal at multiple points in time by continuously combining the relationships between various time intervals and frequencies.

[0234] FIG. 11a is a flowchart illustrating a method for controlling the presence or absence of movement in a space where an electronic device is installed according to one embodiment of the present disclosure.

[0235] The electronic device (100) may perform the operation of operation 360 described below after performing operation 350. In one embodiment, the electronic device (100) may perform operation 360 after performing the operation of operation 370 described below with reference to FIG. 11b.

[0236] In operation 360, the electronic device (100) can control the movement of the space where the electronic device is installed, corresponding to the first time interval determined in operation 350 or operation 370.

[0237] In operation 362, the electronic device (100) can identify the movement of the space where the electronic device (100) is installed, corresponding to each of a specified number of time intervals prior to the first time interval, based on a channel state information pattern. For example, the electronic device (100) can identify the movement of the space where the electronic device (100) is installed, corresponding to each of three time intervals immediately preceding the first time interval. The electronic device (100) can identify the movement of the space where the electronic device (100) is installed, corresponding to each of a specified number of time intervals prior to the first time interval, through operations 310 to 350 described above with reference to FIGS. 1 to 10c.

[0238] In operation 364, the electronic device (100) can be controlled to change whether there is movement in the space where the electronic device (100) is installed, based on whether there is movement in each of the specified number of time intervals prior to the first time interval. For example, the electronic device (100) can identify that there is movement in the space where the electronic device (100) is installed if movement corresponding to the first time interval is identified and all movements corresponding to each of the specified number of time intervals prior to the first time interval are identified. For example, the electronic device (100) can identify that there is no movement in the space where the electronic device (100) is installed if movement corresponding to the first time interval is identified and movement corresponding to at least one of the specified number of time intervals prior to the first time interval is not identified.

[0239] The electronic device (100) can improve the accuracy of motion identification by controlling the change in the presence or absence of movement in the space where the electronic device is installed, taking into account the motion identification results of at least one previous analysis period. Through this, the electronic device (100) can determine whether there is movement by comprehensively analyzing temporally continuous data, rather than making a judgment based solely on the current channel state information pattern.

[0240] The electronic device (100) can correct the current motion identification result based on whether there is a motion identified in a specified number of previous time intervals, or evaluate the reliability of the current motion data to reduce unnecessary false positives or false negatives. For example, if it is determined that there is no motion in a specified number of previous time intervals, the electronic device (100) can change the motion status to "none" by considering the fine motion data detected in the result obtained based on the channel state information pattern of the first time interval as noise.

[0241] In one embodiment, if strong movement is continuously detected in the previous analysis result, the electronic device (100) can control the change of whether there is movement in the space where the electronic device is installed by supplementing the result determined based on the channel state information pattern of the first time interval with "movement present" even if the result indicates only slight movement.

[0242] The electronic device (100) can reliably track patterns of temporally continuous movement and reduce false detections caused by environmental noise or transient interference, thereby improving the accuracy of movement identification in the space where the electronic device is installed.

[0243] FIG. 11b is a flowchart illustrating a method for controlling the presence or absence of movement in a space where an electronic device is installed according to one embodiment of the present disclosure.

[0244] The electronic device (100) may perform the operation of operation 370 described below after performing operation 350. In one embodiment, the electronic device (100) may perform operation 370 after performing the operation of operation 360 described below with reference to FIG. 11a.

[0245] In operation 370, the electronic device (100) can control the movement of the space where the electronic device is installed, corresponding to the first time interval determined in operation 350 or operation 360.

[0246] In operation 372, the electronic device (100) can identify movement in the space where the electronic device is installed corresponding to a first time interval based on the time association. In one embodiment, the electronic device (100) can identify time similarity corresponding to each time interval in the time association. The electronic device (100) can identify (or measure) movement in the space where the electronic device is installed based on the result of a comparison between time similarity and a threshold. For example, the electronic device (100) can determine that there is movement in a time interval where the time similarity is greater than the threshold. For example, the electronic device (100) can determine that there is no movement in a time interval where the time similarity is less than the threshold. The electronic device (100) can adaptively adjust the threshold according to the distribution of time similarities.

[0247] In operation 374, the electronic device (100) may control the change of the existence of movement in the space where the electronic device (100) is installed corresponding to the first time interval based on the time correlation. In one embodiment, the electronic device (100) may determine that there is no movement in the space where the electronic device (100) is installed corresponding to the first time interval based on the time correlation is not identified, and in operation 350, the movement in the space where the electronic device (100) is installed corresponding to the first time interval is not identified. In one embodiment, the electronic device (100) may determine that there is no movement in the space where the electronic device is installed if at least one of the movement in the space where the electronic device (100) is installed corresponding to the first time interval based on the time correlation or the movement in the space where the electronic device (100) is installed corresponding to the first time interval in operation 350 is identified.

[0248] The electronic device (100) can increase the accuracy of motion identification by determining whether there is motion in the space where the electronic device (100) is installed by considering both the presence of motion in the space where the electronic device (100) is installed corresponding to a first time interval based on time correlation and the presence of motion in the space where the electronic device (100) is installed corresponding to a first time interval based on channel state information patterns. The electronic device (100) can effectively reduce false detection or non-detection of motion in the space where the electronic device is installed that may occur due to individual analysis methods. The electronic device (100) can identify the presence of motion in the installed space more precisely, thereby providing stable motion detection even when various environmental variables and signal interference occur.

[0249] FIG. 12 is a block diagram illustrating the configuration of an electronic device according to one embodiment of the present disclosure.

[0250] In one embodiment, the electronic device (100) may include a memory (110), a processor (120), a communication interface (130), a display (140), a microphone (150), an input / output interface (160), an audio output interface (170), a video processing interface (180), an audio processing interface (185), and a power module (190). The electronic device (100) may be composed of various combinations of the components shown in FIG. 12, and not all of the components shown in FIG. 12 are essential components.

[0251] The memory (110) can store a program related to the operation of the electronic device (100) and various data generated during the operation of the electronic device (100). The memory (110) can store at least one instruction. Additionally, the memory (110) may store at least one instruction executed by the processor (120). Additionally, the memory (110) may store at least one program executed by the processor (120). Additionally, the memory (110) may store an application for providing a specific service.

[0252] The memory (110) may include various types of memory. The memory (110) may include a main memory that stores data currently being processed in the electronic device (100). For example, the main memory may include non-volatile memory including at least one of ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), and PROM (Programmable Read-Only Memory), and volatile memory such as RAM (Random Access Memory) or SRAM (Static Random Access Memory).

[0253] The memory (110) may include a secondary memory that permanently stores a large amount of data (e.g., programs, system files, etc.). For example, the secondary memory may include a hard disk drive (HDD), a solid-state drive (SSD), an optical drive (e.g., a CD), a flash drive, etc., but is not limited thereto.

[0254] The processor (120) can control the overall operations of the electronic device (100). For example, the processor (120) can perform the functions of the electronic device (100) described in this disclosure by executing one or more instructions stored in memory (110) individually or collectively. The processor (120) may include a processing circuit. There may be one or more processors (120).

[0255] In an embodiment of the present disclosure, the processor (120) may store one or more instructions in an internally provided memory and control the operation of the electronic device (100) to be performed by executing one or more instructions stored in the internally provided memory. That is, the processor (120) may perform a predetermined operation by executing at least one instruction or program stored in an internal memory or memory (110) provided within the processor (120).

[0256] According to one embodiment, the processor (120) can perform the operation of the electronic device (100) described in the present disclosure by executing one or more instructions stored in memory (110).

[0257] The processor (120) may be composed of at least one of, for example, a Central Processing Unit (CPU), a Microprocessor, a Graphic Processing Unit (GPU), ASICs (Application Specific Integrated Circuits), DSPs (Digital Signal Processors), DSPDs (Digital Signal Processing Devices), PLDs (Programmable Logic Devices), FPGAs (Field Programmable Gate Arrays), an Application Processor (AP), a Neural Processing Unit (NPU), or an AI-dedicated processor designed with a hardware structure specialized for processing AI models, but is not limited thereto.

[0258] The communication interface (130) can perform data communication with other electronic devices (e.g., servers) under the control of the processor (120). Here, 'communication' may mean the operation of transmitting and / or receiving data, signals, requests, and / or commands, etc. The communication interface (130) may include a communication circuit.

[0259] The communication interface (130) can perform wired or wireless communication with at least one external device. The external device may be a server, etc. For example, the communication interface (130) may include at least one of a communication module, a communication circuit, a communication device, an input / output port, and an input / output plug for performing wired or wireless communication with at least one external device.

[0260] The communication interface (130) may include one or more modules that enable wired wireless communication between the electronic device (100) and a wireless communication system or between the electronic device (100) and a network where another electronic device is located. For example, the communication interface (130) may include a mobile communication module (132), a wireless internet module (134), a Wi-Fi communication module (136), and a Bluetooth communication module (138).

[0261] The mobile communication module (132) transmits and receives wireless signals with at least one of a base station, an external terminal, and a server on a mobile communication network. The wireless signals may include various forms of data such as voice call signals, video call call signals, or text / multimedia message transmission and reception.

[0262] The wireless internet module (134) refers to a module for wireless internet access, which may be built into or external to the device. Wireless internet technologies such as WLAN (Wireless LAN) (WiFi), Wibro (Wireless broadband), WiMAX (World Interoperability for Microwave Access), and HSDPA (High Speed ​​Downlink Packet Access) may be used. Through the wireless internet module (134), the electronic device (100) can establish a Wi-Fi P2P (Peer to Peer) connection with another electronic device.

[0263] The communication interface (130) may include a short-range communication module for short-range communication. Short-range communication technologies such as Bluetooth, BLE (Bluetooth Low Energy), RFID (Radio Frequency Identification), infrared communication (IrDA, infrared Data Association), UWB (Ultra-Wideband), and ZigBee may be used. The communication interface (130) may include a Wi-Fi communication module (136) and a Bluetooth communication module (138) as short-range communication modules.

[0264] The display (140) can output a video signal to the screen of the electronic device (100) under the control of the processor (120). For example, the electronic device (100) can output content through the display (140). The display (140) can generate a driving signal by converting a video signal, data signal, OSD signal, control signal, etc. processed by the processor (120), and can display an image according to the driving signal. The display (140) may include any one of a liquid crystal display, a plasma display, an organic light emitting diode display, or an inorganic light emitting diode display. However, the present disclosure is not limited thereto, and the display (140) may include other types of displays capable of displaying content.

[0265] The microphone (150) can acquire a voice signal. For example, the microphone (150) can receive the voice of a user's utterance. The microphone (150) can convert the received voice signal into an electrical signal and transmit it to the electronic device (100). The microphone (150) can detect the voice of a user in the space where the electronic device (100) is located. The microphone (150) may be placed at the bottom center or bottom right of the electronic device (100) to detect the voice of a user in the space where the electronic device (100) is located. The microphone (150) can transmit the acquired sensor value to the processor (120). The processor (120) can acquire ambient utterances of the electronic device by applying a predetermined processing to the acquired sensor value.

[0266] The input / output interface (160) processes input / output from outside the electronic device (100). The input / output interface (160) receives video (e.g., video, etc.), audio (e.g., voice, music, etc.), and additional information (e.g., EPG, etc.). The input / output interface (160) may include any one of an HDMI (High-Definition Multimedia Interface) port (162), a component jack (152), a PC port (153), a USB (Universal Serial Bus) port (154), an MHL (Mobile High-Definition Link), a DP (Display Port), a Thunderbolt, a VGA (Video Graphics Array) port, an RGB port, a D-SUB (D-subminiature), a DVI (Digital Visual Interface), and an audio jack. In one embodiment, the input / output interface (160) may be implemented to include a plurality of modules (e.g., USB port, HDMI port, etc.) for implementing the aforementioned input / output methods.

[0267] The electronic device (100) can be connected to external devices such as a display, camera, microphone, speaker, touchpad, and set-top box through an input / output interface (160). The input / output interface (160) may include a user input section. For example, the input / output interface (160) may include at least one of a key, a touch panel, and a pen recognition panel. The electronic device (100) may display various content or user interfaces according to user input received from at least one of the key, touch panel, and pen recognition panel. The key may include various types of keys, such as mechanical buttons or wheels, formed in various areas such as the front, side, or back of the main body exterior of the electronic device (100). The touch panel may detect the user's touch input and output a touch event value corresponding to the detected touch signal. When the touch panel is combined with a display panel to form a touch screen (not shown), the touch screen may be implemented with various types of touch sensors, such as capacitive, resistive, or piezoelectric.

[0268] The audio output interface (170) can output audio (e.g., voice, sound) input from the communication interface (130) or the input / output interface (160). Additionally, the audio output interface (170) can output audio stored in memory (110) under the control of the processor (120). The audio output interface (170) may include at least one of a speaker, a headphone output terminal, or an S / PDIF (Sony / Philips Digital Interface) output terminal, or a combination thereof.

[0269] The video processing interface (180) performs processing on video data played by the electronic device (100). The video processing interface (180) can perform various image / video processing on the video data, such as decoding, scaling, noise filtering, frame rate conversion, resolution conversion, rendering, etc.

[0270] The audio processing interface (185) performs processing on audio data played by the electronic device (100). Various processing such as decoding, amplification, and noise filtering can be performed on the audio data at the audio processing interface (185).

[0271] The power module (190) supplies power input from an external power source to the components inside the electronic device (100) that operate under the control of the processor (120). Additionally, the power module (190) can supply power output from one or more batteries located inside the electronic device (100) to the internal components under the control of the processor (120).

[0272] An electronic device according to one embodiment of the present disclosure may include a memory for storing at least one instruction. The electronic device may include at least one processor including a circuit device. The electronic device may include a communication interface.

[0273] By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire channel state information (CSI) corresponding to a plurality of subcarriers included in the wireless signal based on the wireless signal received by the electronic device. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire channel state data by preprocessing the channel state information acquired by the electronic device for a specified time period. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire a time delayed relationship indicating similarity between the channel state data corresponding to each time interval based on the channel state data. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can acquire a subcarrier relationship indicating similarity between the channel state data corresponding to each subcarrier based on the channel state data. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can identify the movement of the space in which the electronic device is installed corresponding to the first time interval based on the time correlation and the subcarrier correlation.

[0274] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can acquire a channel state information pattern corresponding to the wireless signal based on the time correlation and the subcarrier correlation. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can identify the movement of the space where the electronic device is installed corresponding to a first time interval based on the channel state information pattern using the pattern recognition model. The pattern recognition model may be learned based on at least one of a first channel state information pattern in which movement of the space where the electronic device is installed exists or a second channel state information pattern in which movement of the space where the electronic device is installed does not exist.

[0275] By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can identify a first similarity between the channel state information pattern and the first channel state information pattern using the pattern recognition model. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can determine that movement exists in the space where the electronic device is installed if the first similarity is greater than or equal to a first threshold value. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can determine that movement does not exist in the space where the electronic device is installed if the first similarity is less than the first threshold value.

[0276] By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can identify a second similarity between the channel state information pattern and the second channel state information pattern. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can determine that there is no movement in the space where the electronic device is installed if the second similarity is greater than or equal to a second threshold. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can determine that there is movement in the space where the electronic device is installed if the second similarity is less than the second threshold.

[0277] By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can use the pattern recognition model to identify the larger value between the first similarity between the channel state information pattern and the first channel state information pattern and the second similarity between the channel state information pattern and the second channel state information pattern. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can determine that movement exists in the space where the electronic device is installed if the first similarity is greater than or equal to the second similarity. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can determine that movement does not exist in the space where the electronic device is installed if the first similarity is less than the second similarity.

[0278] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can identify the movement of the space where the electronic device is installed corresponding to each of a specified number of time intervals prior to the first time interval by using the pattern recognition model and based on the channel state information pattern. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can control the change of the presence or absence of the movement of the space where the electronic device is installed corresponding to the first time interval based on the presence or absence of the movement of the space where the electronic device is installed corresponding to each of the specified number of time intervals prior to the first time interval.

[0279] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can identify the movement of the space where the electronic device is installed corresponding to the first time interval based on the time association. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can control the change of the presence or absence of the movement of the space where the electronic device is installed corresponding to the first time interval based on the time association.

[0280] According to one embodiment of the present disclosure, the reference point of the first time interval may be a W point. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device may determine the similarity between channel state data corresponding to a first point in time to the W point in a first window and channel state data corresponding to a second point in time to the W+1 point in a second window, thereby determining a time similarity value corresponding to the W point. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device may obtain the time correlation based on the time similarity value corresponding to at least one reference point included in the specified time.

[0281] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can determine a time similarity value corresponding to each subcarrier at the W time point based on channel state data corresponding to each subcarrier at the first to W time point within a first window of the channel state data and channel state data corresponding to each subcarrier at the second to W+1 time point within a second window. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can obtain the time correlation based on the time similarity value corresponding to each subcarrier at at least one reference time point included in the specified time.

[0282] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can determine a subcarrier similarity value corresponding to the W time point based on the channel state data corresponding to two different subcarriers for the W time point. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can obtain the subcarrier association based on the subcarrier similarity value corresponding to at least one reference time point included in the specified time.

[0283] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can determine the average subcarrier similarity for each subcarrier by dividing the sum of the subcarrier similarity values ​​corresponding to the Wth time point for each subcarrier by the number of the subcarrier similarity values ​​corresponding to the Wth time point for each subcarrier. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can obtain the subcarrier association based on the average subcarrier similarity value corresponding to at least one reference time point included in the specified time.

[0284] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can determine a time similarity value corresponding to the Wth time point included in the time association diagram as the first component of the channel state information pattern. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can identify a first subset which is at least one subcarrier similarity value for the Wth time point included in the subcarrier association diagram. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can determine a time similarity value corresponding to the W+1th time point included in the time association diagram as the second component of the channel state information pattern. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can identify a second subset, which is at least one subcarrier similarity value for the W+1 time point included in the subcarrier association diagram. By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can obtain the channel state information pattern by connecting the time association diagram and the subcarrier association diagram such that the first component, the components of the first subset, the second component, and the components of the second subset are positioned in order.

[0285] According to one embodiment of the present disclosure, the two different subcarriers may be two adjacent subcarriers.

[0286] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can determine the time association as a reference row of the channel state information pattern. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can obtain the channel state information pattern by connecting the time association and the subcarrier association such that the subcarrier similarity value corresponding to the Wth time point of the subcarrier association is located in the same column as the time similarity value corresponding to the Wth time point of the time association.

[0287] According to one embodiment of the present disclosure, by executing the at least one instruction individually or collectively by the at least one processor, the electronic device can identify the amplitude of the plurality of subcarriers and the phase of the plurality of subcarriers based on channel state information corresponding to the plurality of subcarriers. By executing the at least one instruction individually or collectively by the at least one processor, the electronic device can determine the channel state data corresponding to each time interval of the plurality of subcarriers based on the amplitude of the plurality of subcarriers and the phase of the plurality of subcarriers.

[0288] According to one embodiment of the present disclosure, the time similarity value may be determined based on an autocorrelation function (ACF). The subcarrier similarity value may be determined based on an autocorrelation function (ACF).

[0289] By executing the above at least one instruction individually or collectively by the above at least one processor, the electronic device can be controlled to operate in a power-saving mode based on the fact that movement in the space where the electronic device is installed corresponding to a specified number of time intervals is not identified.

[0290] A method of operation of an electronic device according to one embodiment of the present disclosure may include an operation of acquiring channel state information (CSI) corresponding to a plurality of subcarriers included in a wireless signal based on a wireless signal received by the electronic device. The method may include an operation of acquiring channel state data by preprocessing the channel state information acquired by the electronic device for a specified period of time. The method may include an operation of acquiring a time delayed relationship indicating similarity between the channel state data corresponding to each time interval based on the channel state data. The method may include an operation of acquiring a subcarrier relationship indicating similarity between the channel state data corresponding to each subcarrier based on the channel state data. The method may include an operation of identifying whether there is movement in a space where the electronic device is installed in a first time interval based on the time delayed relationship and the subcarrier relationship using a pattern recognition model.

[0291] According to one embodiment of the present disclosure, the method may include an operation of obtaining a channel state information pattern corresponding to the wireless signal based on the time correlation and the subcarrier correlation. The method may include an operation of identifying whether there is movement in the space where the electronic device is installed corresponding to the first time interval based on the channel state information pattern.

[0292] According to one embodiment of the present disclosure, the pattern recognition model may be trained based on at least one of a first channel state information pattern in which movement of the space where the electronic device is installed exists or a second channel state information pattern in which movement of the space where the electronic device is installed does not exist.

[0293] According to one embodiment of the present disclosure, the method may include an operation of identifying a first similarity between the channel state information pattern and the first channel state information pattern using the pattern recognition model. According to one embodiment of the present disclosure, the method may include an operation of determining that there is movement in the space where the electronic device is installed if the first similarity is greater than or equal to a first threshold value. According to one embodiment of the present disclosure, the method may include an operation of determining that there is no movement in the space where the electronic device is installed if the first similarity is less than the first threshold value.

[0294] According to one embodiment of the present disclosure, the method may include an operation of identifying a second similarity between the channel state information pattern and the second channel state information pattern using the pattern recognition model. According to one embodiment of the present disclosure, the method may include an operation of determining that there is no movement in the space where the electronic device is installed if the second similarity is greater than or equal to a second threshold value using the pattern recognition model. According to one embodiment of the present disclosure, the method may include an operation of determining that there is movement in the space where the electronic device is installed if the second similarity is less than the second threshold value using the pattern recognition model.

[0295] According to one embodiment of the present disclosure, the method may include an operation of identifying the larger value between a first similarity between the channel state information pattern and the first channel state information pattern and a second similarity between the channel state information pattern and the second channel state information pattern using the pattern recognition model. The method may include an operation of determining that there is movement in the space where the electronic device is installed if the first similarity is greater than or equal to the second similarity. The method may include an operation of determining that there is no movement in the space where the electronic device is installed if the first similarity is less than the second similarity.

[0296] According to one embodiment of the present disclosure, the method may include an operation of identifying whether there is movement in the space where the electronic device is installed, corresponding to each of a specified number of time intervals prior to the first time interval, based on the channel state information pattern using the pattern recognition model. The method may include an operation of controlling to change whether there is movement in the space where the electronic device is installed, corresponding to the first time interval, based on whether there is movement in the space where the electronic device is installed, corresponding to each of the specified number of time intervals prior to the first time interval.

[0297] According to one embodiment of the present disclosure, the method may include an operation of identifying movement of the space where the electronic device is installed corresponding to the first time interval based on the time correlation. The method may include an operation of controlling to change the existence of movement of the space where the electronic device is installed corresponding to the first time interval based on the existence of movement of the space where the electronic device is installed corresponding to the first time interval based on the time correlation.

[0298] According to one embodiment of the present disclosure, the reference point of the first time interval may be the Wth point. The method may include an operation of determining the similarity between channel state data corresponding to the first point to the Wth point within a first window and channel state data corresponding to the second point to the W+1th point within a second window, and determining a time similarity value corresponding to the Wth point. The method may include an operation of obtaining the time correlation based on the time similarity value corresponding to at least one reference point included in the specified time.

[0299] According to one embodiment of the present disclosure, the method may include an operation of determining a time similarity value corresponding to each subcarrier at the W-th time point based on channel state data corresponding to each subcarrier at the first to W-th time point within a first time window of the channel state data and channel state data corresponding to each subcarrier at the second to W+1-th time point within a second time window. The method may include an operation of obtaining the time correlation based on a similarity value corresponding to each subcarrier at at least one reference time point included in the specified time.

[0300] According to one embodiment of the present disclosure, the method may include an operation of determining a subcarrier similarity value corresponding to the W time point based on channel state data corresponding to two different subcarriers for the W time point. The method may include an operation of obtaining the subcarrier association based on the subcarrier similarity value corresponding to at least one reference time point included in the specified time.

[0301] According to one embodiment of the present disclosure, the method may include an operation of determining an average subcarrier similarity value for each subcarrier by dividing the sum of the subcarrier similarity values ​​corresponding to the Wth time point for each subcarrier by the number of the subcarrier similarity values ​​corresponding to the Wth time point for each subcarrier. The method may include an operation of obtaining the subcarrier association based on the average subcarrier similarity value corresponding to at least one reference time point included in the specified time.

[0302] According to one embodiment of the present disclosure, the method may include an operation of determining a time similarity value corresponding to the W-th time point included in the time association diagram as a first component of the channel state information pattern. The method may include an operation of identifying a first subset which is at least one subcarrier similarity value for the W-th time point included in the subcarrier association diagram. The method may include an operation of determining a time similarity value corresponding to the W+1-th time point included in the time association diagram as a second component of the channel state information pattern. The method may include an operation of identifying a second subset which is at least one subcarrier similarity value for the W+1-th time point included in the subcarrier association diagram. The method may include an operation of obtaining the channel state information pattern by connecting the time association diagram and the subcarrier association diagram such that the first component, the components of the first subset, the second component, and the components of the second subset are positioned in order.

[0303] According to one embodiment of the present disclosure, the two different subcarriers may be two adjacent subcarriers.

[0304] According to one embodiment of the present disclosure, the method may include an operation of determining the time association as a reference row of the channel state information pattern. The method may include an operation of obtaining the channel state information pattern by connecting the time association and the subcarrier association such that the subcarrier similarity value corresponding to the Wth time point of the subcarrier association is located in the same column as the time similarity value corresponding to the Wth time point of the time association.

[0305] According to one embodiment of the present disclosure, the method may include an operation of identifying the amplitude of the plurality of subcarriers and the phase of the plurality of subcarriers based on channel state information corresponding to the plurality of subcarriers. The method may include an operation of determining the channel state data corresponding to each time interval of the plurality of subcarriers based on the amplitude of the plurality of subcarriers and the phase of the plurality of subcarriers.

[0306] According to one embodiment of the present disclosure, the time similarity value may be determined based on an autocorrelation function (ACF). The subcarrier similarity value may be determined based on an autocorrelation function (ACF).

[0307] The above method may include an operation to control the electronic device to operate in a power-saving mode based on the fact that no movement of the space in which the electronic device is installed is identified for a specified number of time intervals.

[0308] According to one embodiment of the present disclosure, a computer-readable recording medium having at least one instruction recorded thereon may be provided. By executing the at least one instruction individually or collectively by the at least one processor, the computer-readable recording medium may perform the method described above or below.

[0309] Some embodiments may also be implemented in the form of a recording medium containing computer-executable instructions, such as program modules executed by a computer. A computer-readable medium may be any available medium accessible by a computer and includes both volatile and non-volatile media, and both removable and non-removable media. Additionally, a computer-readable medium may include a computer storage medium. A computer storage medium includes both volatile and non-volatile, removable and non-removable media implemented by any method or technique for storing information, such as computer-readable instructions, data structures, program modules, or other data.

[0310] The disclosed embodiments may be implemented as a software program comprising instructions stored on a computer-readable storage media.

[0311] A computer is a device capable of calling instructions stored from a storage medium and performing operations according to the disclosed embodiments according to the called instructions, and may include an electronic device according to the disclosed embodiments.

[0312] Computer-readable storage media may be provided in the form of non-transitory storage media. Here, 'non-transitory' means only that the storage medium does not contain a signal and is tangible, without distinguishing whether data is stored semi-permanently or temporarily on the storage medium. Device-readable storage media may be provided in the form of non-transitory storage media. For example, 'non-transitory storage media' may include a buffer in which data is temporarily stored.

[0313] In addition, the control method according to the disclosed embodiments may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product.

[0314] A computer program product may include a software program and a computer-readable storage medium on which the software program is stored. For example, a computer program product may include a product in the form of a software program (e.g., a downloadable app) that is electronically distributed through a device manufacturer or an electronic market (e.g., Google Play Store, App Store). For electronic distribution, at least a portion of the software program may be stored on a storage medium or temporarily created. In this case, the storage medium may be a server of the manufacturer, a server of the electronic market, or a storage medium of a relay server that temporarily stores the software program.

[0315] A computer program product may include a storage medium of a server or a storage medium of a device in a system composed of a server and a device. Alternatively, if a third device (e.g., a smartphone) is communicationally connected to the server or device, the computer program product may include a storage medium of the third device. Alternatively, the computer program product may include the S / W program itself that is transmitted from the server to the device or the third device, or transmitted from the third device to the device.

[0316] In this case, one of the server, the device, and the third device may execute the computer program product to perform the method according to the disclosed embodiments. Alternatively, two or more of the server, the device, and the third device may execute the computer program product to perform the method according to the disclosed embodiments in a distributed manner.

[0317] For example, a server (e.g., a cloud server or an artificial intelligence server, etc.) can execute a computer program product stored on the server to control a device connected to the server in communication to perform a method according to the disclosed embodiments.

[0318] As another example, the third device may execute a computer program product to control a device connected to the third device in communication to perform a method according to the disclosed embodiment. When the third device executes the computer program product, the third device may download the computer program product from a server and execute the downloaded computer program product. Alternatively, the third device may execute a computer program product provided in a preloaded state to perform a method according to the disclosed embodiments.

[0319] Additionally, in this specification, "interface" may be a hardware component, such as a processor or circuit, and / or a software component executed by a hardware component, such as a processor.

[0320] The foregoing description of the present disclosure is for illustrative purposes only, and those skilled in the art will understand that other specific forms can be easily modified without altering the technical spirit or essential features of the present disclosure. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. For example, each component described as a single unit may be implemented in a distributed manner, and components described as distributed may likewise be implemented in a combined form.

[0321] The scope of the present disclosure is defined by the claims set forth below rather than by the detailed description above, and all modifications or variations derived from the meaning and scope of the claims and equivalent concepts thereof should be interpreted as being included within the scope of the present disclosure.

Claims

1. In a method of operating an electronic device, An operation (310) of acquiring channel state information (CSI) corresponding to a plurality of sub-carriers included in the wireless signal based on a wireless signal received by the electronic device; The operation (320) of preprocessing the channel state information obtained by the electronic device for a specified period of time to obtain channel state data; Based on the above channel state data, an operation (330) to obtain a time delayed relationship indicating similarity between the channel state data corresponding to each time interval; Based on the above channel state data, an operation (340) of obtaining a sub-carrier relationship indicating similarity between the channel state data corresponding to each subcarrier; and A method comprising an operation (350) of identifying whether there is movement in the space where the electronic device is installed, corresponding to the first time interval, based on the above time correlation and the above subcarrier correlation.

2. In Paragraph 1, The operation of identifying whether there is movement in the space where the electronic device is installed, corresponding to the first time interval above, is, An operation to obtain a channel state information pattern corresponding to the wireless signal based on the above time correlation and the above subcarrier correlation; and The operation includes identifying whether there is movement in the space where the electronic device is installed, corresponding to the first time interval, based on the channel state information pattern using a pattern recognition model, A method in which the above pattern recognition model is learned based on at least one of a first channel state information pattern in which movement of the space where the electronic device is installed exists or a second channel state information pattern in which movement of the space where the electronic device is installed does not exist.

3. In Paragraph 2, The operation of identifying whether there is movement in the space where the electronic device is installed, corresponding to the first time interval, based on the channel state information pattern using the above pattern recognition model, is: An operation of identifying a first similarity between the channel state information pattern and the first channel state information pattern using the above pattern recognition model; An operation of determining that movement exists in the space where the electronic device is installed if the first similarity is greater than or equal to a first threshold value; and A method comprising determining that there is no movement in the space where the electronic device is installed if the first similarity is less than the first threshold value.

4. In Paragraph 2 or 3, The operation of identifying whether there is movement in the space where the electronic device is installed, corresponding to the first time interval, based on the channel state information pattern using the above pattern recognition model, is: An operation to identify a second similarity between the above channel state information pattern and the above second channel state information pattern; If the second similarity is greater than or equal to a second threshold value, the operation of determining that there is no movement in the space where the electronic device is installed; and A method comprising determining that there is movement in the space where the electronic device is installed if the second similarity is less than the second threshold value.

5. In any one of paragraphs 2 through 4, The operation of identifying whether there is movement in the space where the electronic device is installed, corresponding to the first time interval, based on the channel state information pattern using the above pattern recognition model, is: An operation of identifying the larger value between the first similarity between the channel state information pattern and the first channel state information pattern and the second similarity between the channel state information pattern and the second channel state information pattern using the above pattern recognition model; If the first similarity is greater than or equal to the second similarity, the operation of determining that there is movement in the space where the electronic device is installed; and A method comprising determining that there is no movement in the space where the electronic device is installed if the first similarity is less than the second similarity.

6. In any one of paragraphs 2 through 5, An operation of identifying whether there is movement in the space where the electronic device is installed, corresponding to each of a specified number of time intervals prior to the first time interval, based on the channel state information pattern using the above pattern recognition model; and A method further comprising an operation to control the existence of movement in the space where the electronic device is installed corresponding to the first time interval, based on whether there is movement in the space where the electronic device is installed corresponding to each of the specified number of time intervals prior to the first time interval.

7. In any one of paragraphs 1 through 6, An operation to identify the movement of the space in which the electronic device is installed, corresponding to the first time interval, based on the above time correlation diagram; and A method further comprising an operation to control the existence of movement in the space where the electronic device is installed, corresponding to the first time interval, based on the existence of movement in the space where the electronic device is installed, corresponding to the first time interval based on the time correlation diagram above.

8. In any one of paragraphs 1 through 7, The reference point of the above first time interval is the W point, and The operation of obtaining a temporal correlation diagram indicating similarity by time interval of the above-mentioned channel state data is, An operation to identify the similarity between channel state data corresponding to a first time point to the W time point within a first window and channel state data corresponding to a second time point to the W+1 time point within a second window, and to determine a time similarity value corresponding to the W time point; and A method comprising the operation of obtaining the time correlation based on a time similarity value corresponding to at least one reference point included in the specified time.

9. In Paragraph 8, The operation of obtaining a subcarrier correlation that indicates the similarity between the channel state data corresponding to each of the above subcarriers is, An operation to determine a subcarrier similarity value corresponding to the W time point based on the channel state data corresponding to two different subcarriers for the W time point; and A method comprising the operation of obtaining the subcarrier correlation based on the subcarrier similarity corresponding to at least one reference point included in the specified time.

10. In Paragraph 9, The operation of obtaining the above subcarrier correlation is, For each of the above subcarriers, an operation to determine an average subcarrier similarity value corresponding to the W time point by dividing the sum of the subcarrier similarity values ​​included in the subcarrier similarity corresponding to the W time point by the number of the subcarrier similarity values ​​included in the subcarrier similarity matrix corresponding to the W time point; and A method comprising the operation of obtaining the subcarrier association based on the average subcarrier similarity value corresponding to at least one reference point included in the specified time.

11. In any one of paragraphs 8 through 10, Based on the above time correlation and the above subcarrier correlation, the operation of obtaining a channel state information pattern corresponding to the wireless signal is, An operation to determine a time similarity value corresponding to the W time point included in the above time association diagram as the first component of the channel state information pattern; An operation to identify a first subset, which is at least one subcarrier similarity value for the W time point included in the above subcarrier association diagram; An operation to determine the time similarity value corresponding to the W+1 time point included in the above time association diagram as the second component of the channel state information pattern; An operation to identify a second subset, which is at least one subcarrier similarity value for the W+1 time point included in the above subcarrier association diagram; and A method comprising the operation of obtaining the channel state information pattern by connecting the time correlation and the subcarrier correlation so that the first component, the components of the first subset, the second component, and the components of the second subset are positioned in order.

12. In any one of paragraphs 8 through 11, Based on the above time correlation and the above subcarrier correlation, the operation of obtaining a channel state information pattern corresponding to the wireless signal is, The operation of determining the above time association as the reference row of the above channel state information pattern; and A method comprising the operation of obtaining a channel state information pattern by connecting the time association and the subcarrier association such that the subcarrier similarity value corresponding to the Wth time point of the subcarrier association is located in the same column as the time similarity value corresponding to the Wth time point of the time association.

13. In any one of paragraphs 1 through 12, A method comprising controlling the electronic device to operate in a power-saving mode based on the fact that no movement of the space in which the electronic device is installed is identified for a specified number of time intervals.

14. In an electronic device (100), Memory (110) for storing at least one instruction; At least one processor (120) including a circuit device; and It includes a communication interface (130), By having the above at least one instruction executed individually or collectively by the above at least one processor (120), the electronic device (100) Based on a wireless signal received by the electronic device, channel state information (CSI) corresponding to a plurality of sub-carriers included in the wireless signal is obtained, and The above electronic device preprocesses the channel state information acquired during a specified time period to obtain channel state data, and Based on the above channel state data, a time delayed relationship indicating similarity between the above channel state data corresponding to each time interval is obtained, and Based on the above channel state data, a sub-carrier relationship indicating the similarity between the channel state data corresponding to each subcarrier is obtained, and An electronic device (100) that identifies the movement of the space in which the electronic device is installed, corresponding to the first time interval, based on the above time correlation and the above subcarrier correlation.

15. A computer-readable recording medium having a program recorded thereon for performing the method of any one of paragraphs 1 through 13 on a computer.

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