CN115987425A

CN115987425A - Signal transmission environment identification method and related device

Info

Publication number: CN115987425A
Application number: CN202211659973.7A
Authority: CN
Inventors: 汤渊
Original assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Current assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Priority date: 2022-12-22
Filing date: 2022-12-22
Publication date: 2023-04-18

Abstract

The application provides a signal transmission environment identification method and a related device, firstly, according to signal round-trip time data between target equipment and access equipment, estimated distance data between the target equipment and the access equipment is determined; meanwhile, obtaining received signal strength data between the target equipment and the access equipment; then, counting the estimated distance data to obtain an estimated distance characteristic, and counting the received signal strength data to obtain a received signal strength characteristic; and finally, inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment. The accuracy and the efficiency of signal transmission environment recognition can be improved, and the operation cost is saved.

Description

Signal transmission environment identification method and related device

Technical Field

The present application relates to the field of channel identification technologies, and in particular, to a method and a related apparatus for identifying a signal transmission environment.

Background

Wireless communication technology has been integrated into people's life and work, and both traditional WiFi technology and advanced 5G technology utilize electromagnetic wave propagation in space to transmit information, and the complexity of the actual propagation environment requires fine analysis and modeling of wireless signals. The existing signal transmission environment identification scheme generally extracts the characteristics of Channel State Information (CSI) in the Channel transmission process, such as signal arrival angle, signal impulse response, and the like, to identify the signal transmission environment, and because the signal is interfered by various barriers and noises in the environment in the actual transmission process, the acquired CSI data often contains many noises, and meanwhile, the CSI data is the representation of the Channel change condition within a certain time, contains Information of multiple dimensions such as time domain, space domain, frequency domain, and the like, and has huge data volume. Extracting useful features from the channel state information usually needs a complex calculation process and relies on a large amount of prior statistical information. Therefore, the process of extracting useful features from the channel state information often requires a lot of time and computational resources.

Disclosure of Invention

In view of this, the present application provides a signal transmission environment recognition method and a related apparatus, which can use signal round trip time as input, and use an environment recognition model for automatic recognition, so as to improve accuracy of signal transmission environment recognition and reduce computation cost.

In a first aspect, an embodiment of the present application provides a method for identifying a signal transmission environment, where the method includes:

determining estimated distance data between target equipment and access equipment according to signal round-trip time data between the target equipment and the access equipment;

acquiring received signal strength data between the target device and the access device;

counting the estimated distance data to obtain estimated distance characteristics, and counting the received signal strength data to obtain received signal strength characteristics;

inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment.

In a second aspect, an embodiment of the present application provides an apparatus for identifying a signal transmission environment, where the apparatus includes:

a distance determining unit, configured to determine estimated distance data between a target device and an access device according to signal round trip time data between the target device and the access device;

a signal strength determining unit, configured to obtain received signal strength data between the target device and the access device;

a characteristic determining unit, configured to count the estimated distance data to obtain an estimated distance characteristic, and count the received signal strength data to obtain a received signal strength characteristic;

and the environment identification unit is used for inputting the estimated distance characteristic and the received signal strength characteristic into an environment identification model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing steps in any method of the first aspect of the embodiment of the present application.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program causes a computer to perform some or all of the steps described in any one of the methods in the first aspect of the embodiment of the present application.

In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps as described in any one of the methods of the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

Firstly, determining estimated distance data between target equipment and access equipment according to signal round-trip time data between the target equipment and the access equipment; meanwhile, obtaining received signal strength data between the target equipment and the access equipment; then, counting the estimated distance data to obtain estimated distance characteristics, and counting the received signal strength data to obtain received signal strength characteristics; and finally, inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment. The accuracy and the efficiency of signal transmission environment recognition can be improved, and the operation cost is saved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic diagram illustrating a type of signal transmission environment according to an embodiment of the present application;

fig. 2 is a system architecture diagram of a signal transmission environment identification method according to an embodiment of the present application;

fig. 3 is a schematic flowchart of a signal transmission environment identification method according to an embodiment of the present application;

fig. 4 is a schematic flowchart of another signal transmission environment identification method according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

fig. 6 is a block diagram illustrating functional units of a signal transmission environment recognition apparatus according to an embodiment of the present disclosure;

fig. 7 is a block diagram illustrating functional units of another signal transmission environment recognition apparatus according to an embodiment of the present disclosure.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

It should be understood that the term "and/or" herein is merely one type of association relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in this document indicates that the former and latter related objects are in an "or" relationship. The "plurality" appearing in the embodiments of the present application means two or more.

In the embodiments of the present application, "at least one item" or the like means any combination of these items, including a single item(s) or any combination of plural items(s), means one or more, and means two or more. For example, at least one (one) of a, b, or c, may represent seven cases as follows: a, b, c, a and b, a and c, b and c, a, b and c. Each of a, b, and c may be an element or a set including one or more elements.

The term "connect" in the embodiments of the present application refers to various connection manners, such as direct connection or indirect connection, to implement communication between devices, which is not limited in this embodiment of the present application.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein may be combined with other embodiments.

The following description will be given of terms related to the present application.

The existing signal transmission environment is generally divided into a Line of Sight (LOS) transmission environment and a Non-Line of Sight (NLOS) transmission environment, wherein the Line of Sight transmission environment indicates that there is no obstacle between a sender and a receiver of a signal, the signal can directly reach the receiver along a straight Line, the Non-Line of Sight transmission environment indicates that there is an obstacle between the sender and the receiver of the signal, the signal cannot directly reach the receiver along the straight Line, but the actual application situation is often more complicated, and misjudgment is easy to occur.

In order to solve the above problems, the signal transmission environment in the embodiment of the present application includes four types, that is, a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment, and weak non-line-of-sight transmission, which are not described any more, the weak line-of-sight transmission environment indicates that a sender and a receiver of a signal are in the same complete spatial area, but a partial obstruction exists between the sender and the receiver of the signal, and the weak non-line-of-sight transmission environment indicates that the sender and the receiver of the signal are in different spatial areas, but only an obstruction with a poor signal obstruction effect exists between different spatial areas.

For convenience of understanding, referring to fig. 1 for description, fig. 1 is a schematic diagram of a type of signal transmission environment provided in an embodiment of the present application, and it can be seen that a signal straight line transmission path between a transmitting device 1 and a receiving device 1 has no obstruction, and a signal transmission environment between the transmitting device 1 and the receiving device 1 is a line-of-sight transmission environment; the transmitting device 2 and the receiving device 1 are located in a complete space region, and a wall exists on a signal linear transmission path between the transmitting device 2 and the receiving device 1, that is, a signal transmission environment between the transmitting device 2 and the receiving device 1 is a weak-sight transmission environment; the transmitting device 3 and the receiving device 2 are located in two space areas, and media with strong signal blocking effect, such as cement solid walls, metal and the like, exist in a signal linear transmission path between the transmitting device 3 and the receiving device 2, namely, a signal transmission environment between the transmitting device 3 and the receiving device 2 is a non-line-of-sight transmission environment; the transmitting device 4 and the receiving device 2 are located in two spatial regions, and a medium with a weak signal blocking effect, such as a thin wooden board, a hollow keel wall or a cardboard, exists in a signal linear transmission path between the transmitting device 4 and the receiving device 2, that is, a signal transmission environment between the transmitting device 4 and the receiving device 2 is a weak non-line-of-sight transmission environment. Therefore, more actual scenes can be covered, and more accurate signal transmission environments can be identified conveniently.

A system architecture of a signal transmission environment identification method in the embodiment of the present application is described below with reference to fig. 2, where fig. 2 is a system architecture diagram of a signal transmission environment identification method provided in the embodiment of the present application, and the system architecture includes a target device 210 and an access device 220.

The target device 210 in this embodiment may be a device with a transceiving function, which may also be referred to as a terminal, a User Equipment (UE), a remote terminal device (remote UE), a relay device (relay UE), an access terminal device, a subscriber unit, a subscriber station, a mobile station, a remote station, a mobile device, a user terminal device, an intelligent terminal device, a wireless communication device, a user agent, or a user equipment. It should be noted that the relay device is a terminal device capable of providing a relay forwarding service for other terminal devices (including a remote terminal device).

For example, the target device 210 may be a mobile phone (mobile phone), a tablet computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) terminal device, an Augmented Reality (AR) terminal device, a wireless terminal device in industrial control (industrial control), a wireless terminal device in unmanned autonomous driving, a wireless terminal device in remote medical treatment (remote medical), a wireless terminal device in smart grid (smart grid), a wireless terminal device in transportation safety (transportation safety), a wireless terminal device in smart city (smart city), a wireless terminal device in smart home (smart home), or the like.

For another example, the target device 210 may also be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA), a handheld device with a wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a next generation communication system (e.g., NR communication system, 6G communication system) or a terminal device in a Public Land Mobile Network (PLMN) for future evolution, and the like, which are not limited in particular.

In some possible implementations, the target device 210 may be deployed on land, including indoors or outdoors, hand-held, worn, or vehicle-mounted; can be deployed on the water surface (such as a ship and the like); may be deployed in the air (e.g., aircraft, balloons, satellites, etc.).

In some possible implementations, the target device 210 may include means for wireless communication functionality, such as a system-on-chip, a chip module. Illustratively, the chip system may include a chip and may also include other discrete devices.

The access device 220 in the embodiment of the present application may be a device with a transceiving function, and is used for communicating with a terminal device.

In some possible implementations, the access device 220 may be responsible for Radio Resource Management (RRM), quality of service (QoS) management, data compression and encryption, data transceiving, and the like on the air interface side.

In some possible implementations, the access device 220 may be a Base Station (BS) in a communication system or a device deployed in a Radio Access Network (RAN) for providing wireless communication functions.

For example, the access device 220 may be an evolved node B (eNB or eNodeB) in an LTE communication system, a next generation evolved node B (ng-eNB) in an NR communication system, a next generation node B (gNB) in an NR communication system, a Master Node (MN) in a dual connectivity architecture, a second node or a Secondary Node (SN) in the dual connectivity architecture, and the like, which are not particularly limited.

In some possible implementations, the access device 220 may also be a device in a Core Network (CN), such as an access and mobility management function (AMF), a User Plane Function (UPF), and the like; but also Access Points (APs) in WLANs, relay stations, communication devices in PLMN networks for future evolution, communication devices in NTN networks, etc.

In some possible implementations, the access device 220 may include an apparatus, such as a system-on-chip, a chip, or a chip module, that provides wireless communication functionality for the terminal device. The system of chips may include a chip, or may include other discrete devices, as examples.

In some possible implementations, the access device 220 may communicate with an Internet Protocol (IP) network. Such as the internet, a private IP network or other data network, etc.

In some possible implementations, the access device 220 may be a separate node to implement the functionality of the base station or the access device 220 may include two or more separate nodes to implement the functionality of the base station. For example, access device 220 includes a Centralized Unit (CU) and a Distributed Unit (DU), such as a gNB-CU and a gNB-DU. Further, in other embodiments of the present application, the access device 220 may further include an Active Antenna Unit (AAU). The CU implements a part of the functions of the access device 220, and the DU implements another part of the functions of the access device 220. For example, the CU is responsible for processing non-real-time protocols and services, and implements functions of a Radio Resource Control (RRC) layer, a Service Data Adaptation (SDAP) layer, and a Packet Data Convergence (PDCP) layer. The DU is responsible for processing a physical layer protocol and a real-time service, and implements functions of a Radio Link Control (RLC) layer, a Medium Access Control (MAC) layer, and a Physical (PHY) layer. In addition, the AAU may implement portions of physical layer processing functions, radio frequency processing, and active antenna related functions. Since the information of the RRC layer eventually becomes or is converted from the information of the PHY layer, in the network deployment, the higher layer signaling (e.g., RRC signaling) may be considered to be sent by the DU or jointly sent by the DU and the AAU. It is understood that the access device 220 may include at least one of a CU, a DU, and an AAU. In addition, the CU may be divided into network devices in the RAN, or the CU may also be divided into access devices 220 in the core network, which is not specifically limited.

The System architecture can be applied to a communication System, and the communication System in the embodiment of the present application may include a General Packet Radio Service (GPRS), a Long Term Evolution (Long Term Evolution, LTE) System, an Advanced Long Term Evolution (LTE-a) System, a New Radio (NR) System, an Evolution System of an NR System, an LTE (LTE-based Access to Unlicensed Spectrum) on an Unlicensed Spectrum, LTE-U) System, NR-based Access to Unlicensed Spectrum (NR-U) System, non-Terrestrial communication network (NTN) System, universal Mobile Telecommunications System (UMTS), wireless Local Area Network (WLAN), wireless Fidelity (Wi-Fi), 6th-Generation (6 th-Generation, 6G) communication System, or other communication systems.

It should be noted that the conventional communication system has a limited number of connections and is easy to implement. However, with the development of communication technology, the communication system in the embodiment of the present application may support not only a conventional communication system, but also a device to device (D2D) communication, a machine to machine (M2M) communication, a Machine Type Communication (MTC), a vehicle to vehicle (V2V) communication, a vehicle to internet (V2X) communication, a narrow band internet of things (NB-IoT) communication, and the like.

It is to be understood that the target device 210 in this embodiment of the present application may perform Fine Timing Measurement with the access device 220 through an 802.11mc Fine Timing Measurement (FTM) protocol to obtain round trip time data and perform signal transmission environment identification, that is, the target device 210 may serve as an execution subject of the signal transmission environment identification method.

With the system architecture in the embodiment of the present application understood, a method for identifying a signal transmission environment in the embodiment of the present application is described below with reference to fig. 3, where fig. 3 is a schematic flow chart of the method for identifying a signal transmission environment provided in the embodiment of the present application, and the method specifically includes the following steps:

step 301, determining estimated distance data between a target device and an access device according to signal round trip time data between the target device and the access device.

The target device and the access device can perform fine timing sequence measurement in a preset time period through the fine timing sequence measurement protocol, and each fine timing sequence measurement process comprises the following steps:

s1, target equipment sends a fine timing sequence measurement request to access equipment, and the fine timing sequence measurement starts when receiving a response of the access equipment to the fine timing sequence measurement request.

And S2, the target equipment receives a first message from the access equipment, wherein the first message can comprise a Ping message.

And S3, the target equipment sends a second message responding to the first message to the access equipment, wherein the second message can comprise a Pong message.

And S4, acquiring a t1 timestamp, a t2 timestamp, a t3 timestamp and a t4 timestamp.

The time stamp of t1 is the time stamp of the first message sent by the access device, the time stamp of t2 is the time stamp of the first message received by the target device, the time stamp of t3 is the time stamp of the second message sent by the target device, and the time stamp of t4 is the time stamp of the second message received by the access device.

And S5, determining the estimated distance between the target equipment and the access equipment according to the t1 timestamp, the t2 timestamp, the t3 timestamp and the t4 timestamp.

Specifically, the estimated distance may be determined by the following formula:

estimated distance = ((t 4-t 1) - (t 3-t 2)) light speed ÷ 2.

It will be appreciated that the t1, t2, t3 and t4 timestamps described above are the signal round trip time for each fine timing measurement. The signal round trip time data may include signal round trip time more than a preset number of times, and the estimated distance data may include an estimated distance more than the preset number of times, where the preset number of times may be 10 times, and the like, and is not particularly limited herein.

The signal round trip time of each fine timing measurement when a preset number of fine timing measurements are performed between the target device and the access device may be obtained, and then the estimated distance corresponding to each fine timing measurement may be determined according to the signal round trip time of each fine timing measurement. It is understood that the time interval between each fine timing measurement is negligible, the positions of the target device and the access device may be considered to be unchanged within the preset time period, and the preset time period may be set to a time period capable of performing the fine timing measurement more than the preset number of times.

Therefore, the estimated distance data between the target device and the access device is determined according to the signal round-trip time data between the target device and the access device, a method for measuring the signal round-trip time in real time is adopted, the data volume is small, the real-time performance is high, the subsequent operation cost can be reduced, and the subsequent algorithm time delay is improved.

Step 302, obtaining received signal strength data between the target device and the access device.

The received signal strength corresponding to each fine timing measurement performed between the target device and the access device within a preset time period can be obtained. It is understood that step 302 and step 301 may be performed simultaneously. The received signal strength data includes received signal strength for more than a preset number of times.

Therefore, accurate data support can be provided for subsequent signal environment identification by acquiring the received signal strength data between the target device and the access device, and the identification accuracy is improved.

Step 303, counting the estimated distance data to obtain an estimated distance characteristic, and counting the received signal strength data to obtain a received signal strength characteristic.

The distance average, the distance variance, the distance quartile range, the distance skewness, the distance kurtosis, the distance value range and the number of distance abnormal values of the estimated distance corresponding to each fine timing measurement can be counted, and then the distance average, the distance variance, the distance quartile range, the distance skewness, the distance kurtosis, the distance value range and the number of distance abnormal values are combined into the estimated distance feature.

The signal strength average value, the signal strength variance, the signal strength quartering distance, the signal strength skewness, the signal strength kurtosis, the signal strength range and the number of signal strength abnormal values of the received signal strength corresponding to each fine timing measurement can be counted, and then the signal strength average value, the signal strength variance, the signal strength quartering distance, the signal strength skewness, the signal strength kurtosis, the signal strength range and the number of signal strength abnormal values are combined into the received signal strength characteristic.

Specifically, the estimated distances in the estimated distance data and the received signal strengths in the received signal strength data may be sorted according to the determined time, for example, the estimated distance data includes l estimated distances, the received signal strength data includes l received signal strengths, and the estimated distance characteristic and the received signal strength characteristic may be determined by an average value formula, a variance formula, a quartering distance formula, a skewness formula, a kurtosis formula, a value range formula, and an outlier number formula. The specific formula is as follows:

quartering pitch = Q3-Q1; q3 represents the third quartile, and Q1 represents the first quartile.

Data range = max-min.

μ ³ Represents the 3 rd order central moment, and σ represents the standard deviation.

The number of abnormal values is the number of values which are more than Q3 or less than Q1 in the group data.

It will be appreciated that the estimated distance characteristic and the received signal strength characteristic may be presented in tabular form, as shown in table one below:

watch 1

And is not particularly limited herein.

Therefore, the estimated distance data is counted to obtain the estimated distance characteristic, and the received signal strength data is counted to obtain the received signal strength characteristic, so that the estimated distance and the received signal strength can be accurately represented, and support is provided for the accuracy of subsequent signal transmission environment identification.

Step 304, inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model, so as to obtain a signal transmission environment between the target device and the access device.

Wherein the signal transmission environment includes any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak-line-of-sight transmission environment, and a weak non-line-of-sight transmission environment.

The environment recognition model may be a trained random forest model or other trained neural network models that can support multi-classification tasks, and is not specifically limited herein.

The estimated distance feature and the received signal strength feature may be input into the environment recognition model to obtain an environment tag confidence level, where the environment tag confidence level includes a line-of-sight transmission confidence level, a non-line-of-sight transmission confidence level, a weak-line-of-sight transmission confidence level, and a weak non-line-of-sight transmission confidence level, and then the signal transmission environment is determined according to the environment tag confidence level. Namely, the signal transmission environment between the target device and the access device with the highest confidence is determined.

It can be seen that, with the above method, first, estimated distance data between a target device and an access device is determined according to signal round trip time data between the target device and the access device; meanwhile, obtaining received signal strength data between the target equipment and the access equipment; then, counting the estimated distance data to obtain an estimated distance characteristic, and counting the received signal strength data to obtain a received signal strength characteristic; and finally, inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment. The accuracy and the efficiency of signal transmission environment recognition can be improved, and the operation cost is saved.

Next, another signal transmission environment identification method in the embodiment of the present application is described with reference to fig. 4, where fig. 4 is a schematic flow chart of another signal transmission environment identification method provided in the embodiment of the present application, and specifically includes the following steps:

step 401, training data is obtained.

The training data includes training signal round-trip time data, training estimated distance data, and training received signal strength data between different devices in a line-of-sight transmission environment, training signal round-trip time data, training estimated distance data, and training received signal strength data between different devices in a non-line-of-sight transmission environment, training signal round-trip time data, training estimated distance data, and training received signal strength data between different devices in a weak non-line-of-sight transmission environment.

Specifically, the two devices can perform multiple times of fine timing sequence measurement at the same position under the line-of-sight transmission environment, the non-line-of-sight transmission environment, the weak-line-of-sight transmission environment and the weak-non-line-of-sight transmission environment respectively, the signal round-trip time of each fine timing sequence measurement is obtained, the estimated distance corresponding to each fine timing sequence measurement is calculated, the received signal strength corresponding to each fine timing sequence measurement is obtained at the same time, and the corresponding signal transmission environment can be marked at the same time.

The training data may be as shown in table two below:

watch two

It can be seen that, the device 1 and the access device 1 perform multiple measurements at the same position in the line-of-sight transmission environment, and the device 2 and the access device 2 perform multiple measurements at the same position in the non-line-of-sight transmission environment, which is not described herein again.

Therefore, by acquiring the data for training, an accurate environment recognition model can be trained.

Step 402, counting the training data to obtain training features.

The training features may include a training estimated distance feature and a training received signal strength feature. The method for determining the characteristics may refer to the description in step 303, which is not described herein.

And 403, inputting the training features into a preset model until the output of the preset model is converged to obtain the environment recognition model.

The preset model may be a preset random forest model or other neural network models that can be used for multi-classification tasks, and is not specifically limited herein.

Step 404, determining estimated distance data between a target device and an access device according to signal round trip time data between the target device and the access device, and obtaining received signal strength data between the target device and the access device.

Step 405, counting the estimated distance data to obtain an estimated distance characteristic, and counting the received signal strength data to obtain a received signal strength characteristic.

Step 406, inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model, so as to obtain a signal transmission environment between the target device and the access device.

Next, a terminal device in the embodiment of the present application is described with reference to fig. 5, and fig. 5 is a schematic structural diagram of an electronic device in the embodiment of the present application. The electronic device 500 comprises, among other things, a processor 510, a memory 520, and a communication bus for connecting the processor 510 and the memory 520.

In some possible implementations, the memory 520 includes, but is not limited to, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a portable read-only memory (CD-ROM), and the memory 520 is used for storing program codes executed by the electronic device 500 and transmitted data.

In some possible implementations, the electronic device 500 also includes a communication interface for receiving and transmitting data.

In some possible implementations, processor 510 may be one or more Central Processing Units (CPUs), which in the case of processor 510 being a single-core CPU, may be a multi-core CPU.

In some possible implementations, the processor 510 may be a baseband chip, a Central Processing Unit (CPU), a general purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof.

In particular implementations, the processor 510 in the electronic device 500 is configured to execute the computer program or instructions 521 stored in the memory 520 to perform the following operations:

determining estimated distance data between a target device and an access device according to signal round-trip time data between the target device and the access device;

It can be seen that, with the above signal transmission environment identification method and related apparatus, first, estimated distance data between a target device and an access device is determined according to signal round-trip time data between the target device and the access device; meanwhile, obtaining the received signal strength data between the target device and the access device; then, counting the estimated distance data to obtain an estimated distance characteristic, and counting the received signal strength data to obtain a received signal strength characteristic; and finally, inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment. The accuracy and the efficiency of signal transmission environment recognition can be improved, and the operation cost is saved.

The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that, in the embodiment of the present application, the division of the unit is schematic, and is only one logic function division, and when the actual implementation is realized, another division manner may be provided.

In the case of dividing each function module according to each function, a detailed description is given below with reference to fig. 6 for a signal transmission environment recognition apparatus in the embodiment of the present application, where fig. 6 is a block diagram of functional units of a signal transmission environment recognition apparatus provided in the embodiment of the present application, and the signal transmission environment recognition apparatus 600 includes:

a distance determining unit 610, configured to determine estimated distance data between a target device and an access device according to signal round trip time data between the target device and the access device;

a signal strength determining unit 620, configured to obtain received signal strength data between the target device and the access device;

a characteristic determining unit 630, configured to count the estimated distance data to obtain an estimated distance characteristic, and count the received signal strength data to obtain a received signal strength characteristic;

an environment recognition unit 640, configured to input the estimated distance feature and the received signal strength feature into an environment recognition model, so as to obtain a signal transmission environment between the target device and the access device, where the signal transmission environment includes any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak-line-of-sight transmission environment, and a weak non-line-of-sight transmission environment.

It can be seen that, with the above signal transmission environment identification method and related apparatus, first, estimated distance data between a target device and an access device is determined according to signal round trip time data between the target device and the access device; meanwhile, obtaining the received signal strength data between the target device and the access device; then, counting the estimated distance data to obtain an estimated distance characteristic, and counting the received signal strength data to obtain a received signal strength characteristic; and finally, inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment. The accuracy and the efficiency of signal transmission environment recognition can be improved, and the operation cost is saved.

It should be noted that the specific implementation of each operation may adopt the corresponding description of the above-mentioned method embodiment, and the signal transmission environment recognition apparatus 600 may be configured to execute the above-mentioned method embodiment of the present application, which is not described again.

In the case of using an integrated unit, the following describes in detail another signal transmission environment recognition apparatus 700 in the embodiment of the present application with reference to fig. 7, where the signal transmission environment recognition apparatus 700 includes a processing unit 701 and a communication unit 702, where the processing unit 701 is configured to execute any step in the above method embodiments, and when data transmission such as sending is performed, the communication unit 702 is optionally invoked to complete the corresponding operation.

The signal transmission environment recognition apparatus 700 may further include a storage unit 703 for storing program codes and data. The processing unit 701 may be a processor, the communication unit 702 may be a wireless communication module, and the storage unit 703 may be a memory.

The processing unit 701 is specifically configured to:

It should be noted that the specific implementation of each operation may adopt the corresponding description of the above-mentioned method embodiment, and the signal transmission environment recognition apparatus 700 may be configured to execute the above-mentioned method embodiment of the present application, which is not described again.

Embodiments of the present application further provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, and the computer program makes a computer execute part or all of the steps of any one of the methods as described in the above method embodiments.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.

It should be noted that for simplicity of description, the above-mentioned embodiments of the method are described as a series of acts, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the above-described units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some interfaces, indirect coupling or communication connection between devices or units, and may be in an electrical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, the technical solutions of the present application, which are essential or part of the technical solutions contributing to the prior art, or all or part of the technical solutions, may be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the above methods of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, read-Only memories (ROMs), random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A signal transmission environment recognition method, the method comprising:

and inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment.

2. The method of claim 1, wherein determining estimated distance data between a target device and an access device from signal round trip time data between the target device and the access device comprises:

acquiring the round trip time of a signal for performing each fine timing measurement between the target equipment and the access equipment within a preset time period;

and determining the estimated distance corresponding to each fine timing measurement according to the round trip time of the signal of each fine timing measurement.

3. The method of claim 1, wherein the obtaining received signal strength data between the target device and the access device comprises:

and acquiring the received signal strength corresponding to each fine timing measurement executed between the target equipment and the access equipment in a preset time period.

4. The method of claim 2, wherein said statistically analyzing the estimated distance data to obtain an estimated distance feature comprises:

counting the distance average value, the distance variance, the distance quartile range, the distance skewness, the distance kurtosis, the distance value range and the distance abnormal value number of the estimated distance corresponding to each fine time sequence measurement;

merging the distance mean, the distance variance, the distance quartile, the distance skewness, the distance kurtosis, the distance value range, and the number of distance outliers into the estimated distance feature.

5. The method of claim 3, wherein the counting the received signal strength data to obtain a received signal strength characteristic comprises:

counting the average signal strength value, the variance of the signal strength, the four-bit distance of the signal strength, the deviation of the signal strength, the kurtosis of the signal strength, the range of the signal strength value and the number of abnormal signal strength values of the received signal strength corresponding to each fine time sequence measurement;

and combining the signal strength average value, the signal strength variance, the signal strength quartering distance, the signal strength skewness, the signal strength kurtosis, the signal strength range and the number of signal strength abnormal values into the received signal strength characteristic.

6. The method of claim 1, wherein inputting the estimated distance characteristic and the received signal strength characteristic into an environment recognition model to obtain a signal transmission environment between the target device and the access device comprises:

inputting the estimated distance features and the received signal strength features into the environment recognition model to obtain environment tag confidence levels, wherein the environment tag confidence levels comprise a line-of-sight transmission confidence level, a non-line-of-sight transmission confidence level, a weak line-of-sight transmission confidence level and a weak non-line-of-sight transmission confidence level;

determining the signal transmission environment according to the environment tag confidence.

7. The method of any of claims 1-6, wherein prior to determining the estimated distance data between the target device and the access device based on signal round trip time data between the target device and the access device, the method further comprises:

acquiring training data including training signal round-trip time data, training estimated distance data, and training received signal strength data between different devices to which the line-of-sight transmission environment is labeled, training signal round-trip time data, training estimated distance data, and training received signal strength data between different devices to which the non-line-of-sight transmission environment is labeled, training signal round-trip time data, training estimated distance data, and training received signal strength data between different devices to which the line-of-sight transmission environment is labeled;

counting the training data to obtain training characteristics;

and inputting the training features into a preset model until the output of the preset model is converged to obtain the environment recognition model.

8. A signal transmission environment recognition apparatus, characterized in that the apparatus comprises:

and the environment identification unit is used for inputting the estimated distance characteristic and the received signal strength characteristic into an environment identification model to obtain a signal transmission environment between the target equipment and the access equipment, wherein the signal transmission environment comprises any one of a line-of-sight transmission environment, a non-line-of-sight transmission environment, a weak line-of-sight transmission environment and a weak non-line-of-sight transmission environment.

9. An electronic device, comprising: a processor, memory, and one or more programs; the one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-7.

10. A computer storage medium, characterized in that it stores a computer program comprising program instructions which, when executed by a processor, cause the processor to carry out the method according to any one of claims 1-7.