Signal collision detection method and device, storage medium and program product

Abstract

The invention relates to the technical field of Internet of Things, and particularly provides a signal collision detection method and device, a storage medium and a program product. The method comprises the steps that configuration information of wireless equipment is acquired based on received service signaling from an application platform, and the configuration information comprises configuration parameters of frame length control parameters; under the condition that the configuration parameter of the frame length control parameter represents that collision detection needs to be carried out on the signal of the wireless equipment, according to a preset symbol length, carrying out sliding window processing on an inventory signal from the wireless equipment to obtain a plurality of in-window signals; in-window signal collision characteristics of the in-window signals are extracted, wherein the in-window signal collision characteristics are used for representing the waveform abnormal fluctuation condition of the window sliding signals; and performing collision detection on the inventory signal based on the in-window signal collision characteristics of each in-window signal. Collision detection is realized by extracting the signal collision characteristics in the window, and the accuracy of collision detection is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of Internet of Things, and in particular to a signal collision detection method, device, storage medium and program product. Background Art

[0002] Radio Frequency Identification (RFID) technology uses electromagnetic waves for short-range wireless communication to achieve contactless information acquisition from the reader to the tag. The reader consists of a transceiver link. The reader is generally a single-antenna transceiver shared structure, and the transceiver path is isolated by a circulator. The tag is a passive tag that uses an ultra-low power chip design method. Its energy source is the reader's electromagnetic wave feeding the tag chip's external antenna.

[0003] When batch reading of tags is performed, the system issues tasks, the device receives the tasks and sends read signals to the tags. In the process of the device reading tags, there are situations where multiple tags respond at the same time, and the tag signals collide, resulting in unresolvable signals. Therefore, a collision detection solution is required to detect whether the tag signals collide. Summary of the invention

[0004] The present disclosure is proposed in view of the above problems. The present disclosure provides a signal collision detection method, device, storage medium and program product.

[0005] According to a first aspect of the present disclosure, a signal collision detection method is provided, which is applied to a passive radio frequency device, comprising:

[0006] Based on the service signaling received from the application platform, obtaining configuration information of the wireless device, wherein the configuration information includes configuration parameters of the frame length control parameter;

[0007] In the case where the configuration parameter of the frame length control parameter indicates that collision detection needs to be performed on the signal of the wireless device, sliding window processing is performed on the inventory signal from the wireless device according to a preset symbol length to obtain a plurality of signals within the window;

[0008] Extracting the intra-window signal collision feature of each of the intra-window signals, wherein the intra-window signal collision feature is used to characterize the abnormal fluctuation of the waveform of the windowed signal;

[0009] The inventory signals are subjected to collision detection based on the in-window signal collision characteristics of each of the in-window signals.

[0010] In addition, according to the signal collision detection method of the first aspect of the present disclosure, the configuration parameters of the frame length control parameter include at least one of the following:

[0011] Business scenario identification;

[0012] Frame length control parameters;

[0013] A flag used to indicate whether collision detection is required;

[0014] Frame length control parameter adjustment strategy.

[0015] In addition, according to the signal collision detection method of the first aspect of the present disclosure, extracting the intra-window signal collision feature of each of the intra-window signals includes:

[0016] Calculating the mean value of the signal power within the window of each signal within the window; and calculating the number of abnormal fluctuations within the window of each signal within the window based on the peak value of the fluctuation point within each signal within the window;

[0017] Calculating the signal variance within the window of each windowed signal based on the signal power mean within the window;

[0018] The number of abnormal fluctuations in the window and the variance of the signal in the window are used as collision features of the signal in the window.

[0019] In addition, according to the signal collision detection method of the first aspect of the present disclosure, collision detection is performed on the inventory signal based on the in-window signal collision characteristics of each in-window signal, including:

[0020] Taking the average of the signal variances in each of the windows to obtain the total signal variance; and obtaining the total abnormal fluctuation number based on the maximum value of the abnormal fluctuation number in each of the windows;

[0021] Comparing the total signal variance with a maximum variance threshold and a minimum variance threshold;

[0022] When the total signal variance is greater than the maximum variance threshold, confirming that the inventory signal has collided;

[0023] When the total signal variance is less than or equal to the maximum variance threshold value and greater than the minimum variance threshold value, and the total abnormal fluctuation number is greater than the fluctuation number threshold value, it is confirmed that the inventory signal has collided.

[0024] In addition, the signal collision detection method according to the first aspect of the present disclosure further includes:

[0025] Calculating a total signal power average of the stored signals based on the in-window signal power averages of the in-window signals;

[0026] Calculating a signal-to-noise ratio of the inventory signal based on the total signal power mean;

[0027] When it is confirmed that the signal-to-noise ratio is greater than the signal-to-noise ratio threshold, a step of comparing the total signal variance with a maximum variance threshold and a minimum variance threshold is performed.

[0028] In addition, the signal collision detection method according to the first aspect of the present disclosure further includes:

[0029] When it is confirmed that the inventory signal collides, and the configuration parameters of the frame length control parameter include that the frame length control parameter adjustment strategy is a target strategy and the frame length control parameter is a preset frame length control parameter, adjusting the preset frame length control parameter according to the target strategy to obtain an adjusted frame length control parameter;

[0030] The adjusted frame length control parameter is sent to the wireless device.

[0031] According to a second aspect of the present disclosure, a signal collision detection system is provided, comprising:

[0032] Passive RF devices and wireless devices;

[0033] The passive radio frequency device is used to obtain configuration information of the wireless device based on service signaling received from an application platform, wherein the configuration information includes configuration parameters of a frame length control parameter; when the configuration parameters of the frame length control parameter indicate that collision detection needs to be performed on the signal of the wireless device, sliding window processing is performed on the stored signals from the wireless device according to a preset symbol length to obtain multiple in-window signals; a collision feature of the in-window signal of each in-window signal is extracted, wherein the collision feature of the in-window signal is used to characterize abnormal fluctuations in the waveform of the windowed signal; and collision detection is performed on the stored signals based on the collision feature of the in-window signal of each in-window signal.

[0034] According to a third aspect of the present disclosure, a communication device is provided, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first aspect.

[0035] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program / instruction is stored, and when the computer program / instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0036] According to a fifth aspect of the present disclosure, there is provided a computer program product, comprising a computer program / instruction, which implements the steps of the method described in the first aspect when executed by a processor.

[0037] As described in detail below, according to the signal collision detection method of the embodiment of the present disclosure, the configuration information of the wireless device is obtained, and based on the configuration parameters of the frame length control parameter included in the configuration information, the feature extraction is performed on the window signal of the stored signal of the wireless device, the collision feature of the signal in the window is obtained, and the collision detection is performed on the stored signal based on the collision feature of the signal in the window. The collision detection based on the extracted collision feature of the signal in the window can improve the accuracy of the collision detection.

[0038] It is to be understood that both the foregoing general description and the following detailed description are exemplary, and are intended to provide further explanation of the technology as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and other purposes, features and advantages of the present disclosure will become more apparent by describing the embodiments of the present disclosure in more detail in conjunction with the accompanying drawings. The accompanying drawings are used to provide a further understanding of the embodiments of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the present disclosure and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0040] Figure 1 is a flowchart illustrating a method for detecting a signal collision according to an embodiment of the present disclosure.

[0041] Figure 2 is a schematic diagram illustrating a radio frequency application system according to an embodiment of the present disclosure.

[0042] Figure 3 is a schematic diagram illustrating a signal collision detection system implemented in combination with a cellular network according to an embodiment of the present disclosure;

[0043] Figure 4 It is a schematic diagram illustrating the comparison of detection accuracy between the traditional collision detection method according to the embodiment of the present disclosure and the optimization method in the proposal.

[0044] Figure 5 2 is a schematic diagram illustrating a comparison of tag reading rates between a conventional RFID system according to an embodiment of the present disclosure and a system using the proposed improved solution.

[0045] Figure 6 is a schematic diagram illustrating a signal collision detection system to which an embodiment of the present disclosure is applied.

[0046] Figure 7 is a schematic diagram illustrating a signal collision detection device according to an embodiment of the present disclosure.

[0047] Figure 8 is a hardware block diagram illustrating a communication device according to an embodiment of the present disclosure.

[0048] Fig. 9 is a schematic diagram illustrating a computer-readable storage medium according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical scheme and advantages of the embodiments of the present disclosure clearer, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the present disclosure for protection, but merely represents the selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present disclosure.

[0050] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0051] The term "and / or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

[0052] Tag reading in related technologies is mainly based on the following process:

[0053] The scheduling platform sends a read command to the reading device. In the existing mode, this command mainly starts the device reading, including the following general information: read start command, task information, device configuration parameters (coding, BLF, antenna ID, etc.), reading mode (timing, cycle, single, etc.);

[0054] The reading device receives the command and issues business instructions for reading according to the set device configuration and inventory mode, and reads multiple tags based on the existing collision detection and anti-collision algorithms. The existing typical collision detection is detected in the following two ways:

[0055] Whether a collision occurs is determined by whether the reading device can correctly decode the RN16 or data signal of the tag signal. The basic principle is that the tag echo signal is affected by the frequency of the oscillator inside the chip. Each tag return signal has a different time delay, causing multiple tag echo signals to collide with each other and produce a messy waveform. At this time, the receiver cannot correctly decode the signal data, and the time slot is determined to be a collision time slot.

[0056] The collision is determined by the number of violations of the coding rules after the data is decoded. Since the tag signal is encoded in FM0 or Miller coding, it will follow the rules of the coding method. The waveform without collision will not violate the coding method after decoding, and the collision superposition of tag signals will cause the waveform to violate the coding method. By using the number of violations of the coding rules by the waveform as the judgment standard, it can be determined whether a collision occurs in the time slot.

[0057] When it is determined that the tag signals do not collide, the tags interact according to the device commands as specified in the standard and return tag information;

[0058] The device reports the received tag information to the platform.

[0059] The above two collision detection solutions have the following problems:

[0060] The commands issued by the platform do not include the settings for the anti-collision module. The same anti-collision strategy is basically adopted for each tag reading scenario. Due to errors in collision detection and the need for the anti-collision algorithm to frequently adjust the Q value and send it to the tag through signaling, in specific reading scenarios, the number of tags is relatively fixed. The default opening of collision detection and anti-collision will increase the number and time of signaling interactions between the device and the tag, limiting the system's tag reading efficiency.

[0061] The collision detection algorithm only judges the signal waveform at the decoding level, and does not fully utilize the characteristics of the waveform, which is prone to misjudgment. In the following situations, the accuracy of existing methods in detecting collisions is low: when the distance between the two colliding tags and the receiver is one closer and the other farther, the signal strengths of the two are very different, and the signal waveform will be dominated by the high-intensity tag signal. The signal data can still be correctly decoded, and the number of violations of the coding rules is 0; the physical positions of the colliding tags are close, the time delay between the signals is extremely small, and the waveforms are not messy after superposition. At this time, the probability of correctly decoding the signal data is high, and the probability of violating the coding rules is low.

[0062] In order to alleviate the technical problems existing in the related art, the embodiments of the present disclosure provide a signal collision detection method, device, storage medium and program product. The method obtains the configuration information of the wireless device, and based on the configuration parameters of the frame length control parameter included in the configuration information, extracts the features of the window signal of the stored signal of the wireless device, obtains the collision features of the signal in the window, and performs collision detection on the stored signal based on the collision features of the signal in the window. Performing collision detection based on the extracted collision features of the signal in the window can improve the accuracy of collision detection.

[0063] To facilitate understanding of this embodiment, a signal collision detection method disclosed in the embodiment of the present disclosure is first introduced in detail. The execution subject of the signal collision detection method provided in the embodiment of the present disclosure is generally a passive radio frequency device.

[0064] See also Figure 1 FIG. 1 is a flow chart of a signal collision detection method provided by an embodiment of the present disclosure, and the method comprises the following steps:

[0065] Step 101: Based on the service signaling received from the application platform, obtain configuration information of the wireless device, wherein the configuration information includes configuration parameters of the frame length control parameter.

[0066] In this embodiment, the configuration parameters of the frame length control parameter include at least one of the following:

[0067] Business scenario identification;

[0068] Frame length control parameters;

[0069] A flag used to indicate whether collision detection is required;

[0070] Frame length control parameter adjustment strategy.

[0071] The business scenario identifier is used to indicate the business scenario used by the wireless device. In the application, the business scenario identified by the business scenario identifier includes but is not limited to a warehouse inventory scenario, a circulation area inventory scenario, or an in-and-out warehouse identification scenario.

[0072] Taking wireless devices as tags as an example, combined with warehouse inventory counting scenarios, circulation area inventory counting scenarios, and inbound and outbound identification scenarios, a tag quantity feature table as shown in Table 1 is given:

[0073] Table 1

[0074]

[0075] As shown in Table 1, in the warehouse inventory scenario and the in-and-out inventory identification scenario, the number of tags fluctuates slightly and the tag scale is also small. Therefore, in these two scenarios, there is no need to frequently adjust the frame length control parameter (Q). In the circulation area inventory scenario, the number of tags fluctuates greatly and the tag scale is also large. Therefore, in this scenario, the frame length control parameter needs to be frequently adjusted.

[0076] The frame length control parameter is used to determine the number of time slots for the passive RF device to communicate with the wireless device. According to the standard, the number of time slots for the passive RF device to communicate with the wireless device is 2. Q -1. Generally, when the flag for indicating whether collision detection is required indicates that collision detection is required, the frame length control parameter is a preset Q value, and when the flag for indicating whether collision detection is required indicates that collision detection is not required, the frame length control parameter is a default value. The preset Q value is a Q value set by the user as needed.

[0077] The frame length control parameter adjustment strategy is to adjust the value of the frame length control parameter.

[0078] In this embodiment, configuration information is pre-configured for wireless devices in different business scenarios, and the configuration information of wireless devices belonging to the same business scenario is the same. Therefore, when obtaining the configuration information of the wireless device, the application platform can obtain the business scenario identifier of the business scenario applied by the wireless device, and use the business scenario identifier to query the configuration information pre-configured in the application platform, so as to obtain the configuration information corresponding to a certain wireless device.

[0079] Step 102: When the configuration parameter of the frame length control parameter indicates that collision detection needs to be performed on the signal of the wireless device, a sliding window process is performed on the stored signal from the wireless device according to a preset symbol length to obtain a plurality of signals within the window.

[0080] It should be understood that when the configuration parameters of the frame length control parameters include a business scenario identifier, if the business scenario corresponding to the business scenario identifier is a business scenario in which the number of tags fluctuates greatly and the tag scale is also large, it can be determined that collision detection is required for the signal of the wireless device. On the contrary, if the business scenario identifier corresponds to a business scenario in which the number of tags fluctuates slightly and the tag scale is also small, it can be determined that collision detection is not required for the signal of the wireless device.

[0081] When the configuration parameters of the frame length control parameters include an identifier for indicating whether collision detection is required, if the identifier indicates that collision detection is required, it can be determined that collision detection is required for the signal of the wireless device. On the contrary, if the identifier indicates that collision detection is not required, it can be determined that collision detection is not required for the signal of the wireless device.

[0082] In the case where the configuration parameters of the frame length control parameter include the frame length control parameter, if the frame length control parameter is a preset Q value, it can be determined that collision detection is required for the signal of the wireless device. If the frame length control parameter is a default value, it can be determined that collision detection is not required for the signal of the wireless device.

[0083] When the configuration parameters of the frame length control parameter include a frame length control parameter adjustment strategy, if the frame length control parameter adjustment strategy is not empty, it can be determined that collision detection needs to be performed on the signal of the wireless device. On the contrary, if the frame length control parameter adjustment strategy is empty, it can be determined that collision detection does not need to be performed on the signal of the wireless device. It should be understood that the frame length control parameter adjustment strategy being empty means that no specific Q-switching strategy is configured, and the frame length control parameter adjustment strategy being not empty means that a specific Q-switching strategy is configured.

[0084] As an example, a wireless device load service and a corresponding control field table shown in Table 2 are given.

[0085] Table 2

[0086]

[0087] Among them, the business scenario [1] in Table 2 can be a warehouse inventory scenario, the business scenario [2] can be a circulation area inventory scenario, and the business scenario [3] can be an inbound and outbound warehouse identification scenario.

[0088] The Q-switching switch in Table 2 is an identifier used to indicate whether collision detection is required in this embodiment.

[0089] Combined with Table 2, in the configuration parameters corresponding to wireless device B, the business scenario corresponding to the business scenario identifier is business scenario [2]. In business scenario [2], the number of tags fluctuates greatly and the tag scale is also large. Therefore, based on this business scenario [2], it can be determined that the signal of wireless device B needs to be collided. The frame length control parameter (i.e., Q value) is the default value, so based on this Q value, it can also be determined that the signal of wireless device B needs to be collided. The Q switch is 1. When the Q switch is 1, the Q switch is turned on, that is, the user indicates whether a collision detection is required. The identifier indicates that a collision detection is required. Therefore, based on the Q switch with a value of 1, it can also be determined that the signal of wireless device B needs to be collided. The frame length control parameter adjustment strategy (i.e., Q strategy) is configured with a fast Q strategy, so based on the frame length control parameter adjustment strategy, it can also be determined that the signal of wireless device B needs to be collided.

[0090] Wireless device A and wireless device C are completely opposite to wireless device B. To avoid redundancy, wireless device A and wireless device C are not described one by one here.

[0091] In this embodiment, the inventory signal subjected to sliding window processing includes but is not limited to the RN16 signal. After receiving the inventory signal from the wireless device, the passive radio frequency device can complete synchronization of the inventory signal through the preamble of the signal to determine the initial position of the inventory signal. Then, starting from the initial position, the inventory signal is subjected to sliding window processing with a preset symbol length as a window, thereby obtaining multiple signals in the window.

[0092] Step 103: extracting the collision features of the signals in each window. The collision features of the signals in each window are used to characterize the abnormal fluctuation of the waveform of the windowed signal.

[0093] The signal collision characteristics within the window include variance and / or abnormal fluctuation number within the window. The abnormal fluctuation number within the window is determined based on the peak value of each fluctuation point within the window. When the peak value of the fluctuation point exceeds the interval range formed by the maximum peak value and the minimum peak value, the abnormal fluctuation number within the window is increased by 1.

[0094] In one or more embodiments, step 103 may include the following steps:

[0095] Calculating the mean power of the signal in each window; and calculating the number of abnormal fluctuations in the window of the signal in each window based on the peak value of the fluctuation point in the signal in each window;

[0096] Based on the mean power of the signal in the window, the signal variance in the window of each windowed signal is calculated;

[0097] The number of abnormal fluctuations within the window and the signal variance within the window are used as the collision features of the signal within the window.

[0098] The mean power of the signal in the window is obtained by taking the absolute value of each sampling point of the signal in the window and then taking the mean value. For specific expression in formula, please refer to formula (1):

[0099]

[0100] Where Pwindow is the mean power of the signal in the window, x(n) is the value of the signal sampling point in the window, and N is the number of sampling points in the window.

[0101] To count the variance of the windowed signal, first average the windowed signal:

[0102]

[0103] Where xmean(n) is the averaged signal sampling point value. Based on the averaged sampling value, the variance of the windowed signal is:

[0104]

[0105] The superposition of different tag signals will cause abnormal fluctuations in the received waveform, which is mainly reflected in the fluctuations in the middle area between the peaks and valleys of the received waveform. By recording the number of peaks in this range, the number of abnormal fluctuations in the window can be counted, and the collision waveform can be identified.

[0106] The scope is set as follows:

[0107]

[0108] Where peak(i) is the peak value of each fluctuation point in the entire window, s(i) is used to mark whether each peak is an abnormal fluctuation, min(x(n)) is the preset maximum peak value, and max(x(n)) is the preset minimum peak value. The number of abnormal fluctuations within the window of the signal within the window is:

[0109] S window =sum(s(i))(5)

[0110] Step 104: perform collision detection on the inventory signals based on the collision characteristics of the signals in each window.

[0111] When performing collision detection on the inventory signal, firstly, the total signal feature of the inventory signal is obtained based on the collision feature of the signal in each window, and then the collision detection is performed based on the total signal feature.

[0112] In specific implementation, in one or more embodiments, step 104 may include the following steps:

[0113] Taking the average of the signal variances in each window to obtain the total signal variance; and obtaining the total abnormal fluctuation number based on the maximum value of the abnormal fluctuation number in each window;

[0114] Compare the total signal variance with the maximum variance threshold and the minimum variance threshold;

[0115] When the total signal variance is greater than the maximum variance threshold, it is confirmed that the inventory signal has collided;

[0116] When the total signal variance is less than or equal to the maximum variance threshold and greater than the minimum variance threshold, and the total abnormal fluctuation number is greater than the fluctuation number threshold, it is confirmed that the inventory signal has collided.

[0117] Among them, the calculation formulas for the total signal variance and the total abnormal fluctuation number are as follows:

[0118]

[0119] S=max(S window )(7)

[0120] Among them, Var is the total signal variance, S is the total number of abnormal fluctuations, and W is the number of sliding windows on the signal waveform.

[0121] Var window is the mean of the signal variance within the window, the S window is the number of abnormal fluctuations in the window.

[0122] The maximum variance threshold value, the minimum variance threshold value, and the fluctuation number threshold value may be preset artificially based on experience, and this embodiment does not specifically limit this.

[0123] The total signal variance being greater than the maximum variance threshold value indicates that the signal quality of the inventory signal is unstable and is most likely a collision signal. Therefore, in this case, it is directly considered that the inventory signal has collided.

[0124] When the total signal variance is less than or equal to the maximum variance threshold and greater than the minimum variance threshold, it indicates that the signal quality of the inventory signal is stable. However, this can only indicate to a certain extent that the inventory signal has not collided. Further judgment is needed based on the total abnormal fluctuation number. If the total abnormal fluctuation number is greater than the fluctuation number threshold, the inventory signal can still be determined to be a collision signal.

[0125] It should be understood that when the total signal variance is less than or equal to the minimum variance threshold, or when the total signal variance is less than or equal to the maximum variance threshold and greater than the minimum variance threshold and the total abnormal fluctuation number is less than or equal to the fluctuation number threshold, the inventory signal is determined to be a signal without collision.

[0126] In one or more embodiments, since the signal quality of the inventory signal is also affected by the noise of the environment, in order to improve the detection accuracy, the signal-to-noise ratio of the inventory signal may be determined before comparing the total signal variance with the maximum variance threshold and the minimum variance threshold.

[0127] In a specific implementation, based on the window signal power average of the signal in each window, the total signal power average of the stored signal is calculated;

[0128] Calculate the signal-to-noise ratio of the inventory signal based on the total signal power average;

[0129] When it is confirmed that the signal-to-noise ratio is greater than the signal-to-noise ratio threshold, a step of comparing the total signal variance with a maximum variance threshold and a minimum variance threshold is performed.

[0130] The calculation formula of signal-to-noise ratio is as follows:

[0131]

[0132] Where P is the mean value of the total signal power, W is the number of sliding windows on the signal waveform, Y is the number of sliding windows for noise signal statistics, and x noise (n) refers to the value of the noise signal sampling point, and SNR is the signal-to-noise ratio.

[0133] In one or more embodiments, when confirming the disk storage signal, the configuration parameters of the frame length control parameter can also be adjusted. Specifically, when it is confirmed that a collision occurs in the disk storage signal and the configuration parameters of the frame length control parameter include that the frame length control parameter adjustment strategy is the target strategy and the frame length control parameter is the preset frame length control parameter, the preset frame length control parameter is adjusted according to the target strategy to obtain the adjusted frame length control parameter; the adjusted frame length control parameter is sent to the wireless device.

[0134] In the solution provided in this embodiment, the configuration information of the wireless device is obtained, and when it is based on the configuration parameters of the frame length control parameter included in the configuration information, the in-window signals of the inventory signal of the wireless device are feature-extracted to obtain the in-window signal collision feature, and the inventory signal is collision-detected based on the in-window signal collision feature. Collision detection based on the extracted in-window signal collision feature can improve the accuracy of collision detection.

[0135] The following takes the tag reading scenario as an example to describe the signal collision detection method of this application.

[0136] Please refer to Figure 2 , Figure 2 which is a schematic diagram of the radio frequency application system shown in the embodiment of this application. As Figure 2 shown, the radio frequency application system includes an application platform, RFID devices, and an RFID tag group.

[0137] Configuration information (such as anti-collision algorithm switch, preset Q value, and / or Q adjustment algorithm) is sent to the RFID device through the command of the application platform.

[0138] When the user issues a service through the application platform, the application platform queries the relationship table and then issues an execution signaling including the configuration information system to the RFID device. The target features of the tag signal are extracted and calculated, the variance and abnormal fluctuation values, and the signal-to-noise ratio of the signal are calculated according to the collision detection method in the foregoing embodiment. Assume that the feature statistics are: variance 11.23, abnormal fluctuation times 10, and signal-to-noise ratio 20.

[0139] Using the typical threshold settings in the collision detection process (signal-to-noise ratio threshold N = 12, minimum variance threshold var_L1 = 1, maximum variance threshold var_H1 = 15, fluctuation number threshold S1 = 5), it is judged according to the collected signal feature data that the time slot is a collision time slot. The specific judgment process is as follows:

[0140] The first step: Signal-to-noise ratio of the signal: 20 > N, enter the corresponding judgment interval;

[0141] The second step: Signal variance: var_L1 < 11.23 < var_H1, enter the next judgment;

[0142] Step 3: Abnormal signal fluctuation number: 10>S1, it is judged that the tag signal is a collision signal;

[0143] Subsequently, RFID technology will be combined with the cellular network, and the core network in the cellular network will replace the application platform in the above embodiment to send configuration information. Figure 3 The signal collision detection system shown is implemented in combination with a cellular network.

[0144] The above is an introduction to the proposed method. To verify its effect, a variety of typical tag reading scenarios were set up, and the traditional method and the improved optimization method were used to read the tags. The optimization effect of the method was verified through simulation.

[0145] First, we use the actual captured signal waveform to verify the improvement in collision detection accuracy:

[0146] Figure 4 The detection accuracy of the two methods is shown. It can be seen from the figure that for the same group of label signal samples, the detection accuracy of the method of the present application is higher than that of the traditional method.

[0147] Then verify the improvement of reading efficiency of the traditional method and the improved efficient method:

[0148] Figure 5 The reading efficiency comparison of the two methods in different numbers of tags and application scenarios is shown. From the figure, it can be seen that according to the characteristics of different scenarios, appropriate adjustment of the collision detection and Q-switching module switches can improve the system's efficiency in reading tags.

[0149] Based on the same inventive concept, the embodiment of the present application also provides a signal collision detection system, such as Figure 6 As shown, the system may include:

[0150] Application platform 61, passive radio frequency device 62 and wireless device 63;

[0151] The passive radio frequency device 62 is used to obtain configuration information of the wireless device 63 based on the service signaling received from the application platform 61, and the configuration information includes configuration parameters of the frame length control parameter; when the configuration parameters of the frame length control parameter indicate the need to perform collision detection on the signal of the wireless device 63, sliding window processing is performed on the inventory signal from the wireless device 63 according to the preset symbol length to obtain multiple in-window signals; the in-window signal collision characteristics of the signals in each window are extracted, and the in-window signal collision characteristics are used to characterize the abnormal fluctuation of the waveform of the windowed signal; and collision detection is performed on the inventory signal based on the in-window signal collision characteristics of the signals in each window.

[0152] The present disclosure also provides a signal collision detection device, which is used to perform the signal collision detection method provided in any of the above embodiments. Figure 7 As shown, the device comprises:

[0153] An acquisition module 71, configured to acquire configuration information of a wireless device based on service signaling received from an application platform, wherein the configuration information includes configuration parameters of a frame length control parameter;

[0154] A sliding window module 72, configured to perform sliding window processing on the stored signals from the wireless device according to a preset symbol length to obtain a plurality of signals within the window when the configuration parameter of the frame length control parameter indicates that collision detection needs to be performed on the signal of the wireless device;

[0155] An extraction module 73, used for extracting the collision feature of the signal in the window of each signal in the window, wherein the collision feature of the signal in the window is used for characterizing the abnormal fluctuation of the waveform of the windowed signal;

[0156] The detection module 74 is configured to perform collision detection on the inventory signal based on the collision characteristics of the signals within the windows.

[0157] In one or more embodiments, the configuration parameters of the frame length control parameter include at least one of the following:

[0158] Business scenario identification;

[0159] Frame length control parameters;

[0160] A flag used to indicate whether collision detection is required;

[0161] Frame length control parameter adjustment strategy.

[0162] In one or more embodiments, extracting the intra-window signal collision feature of each of the intra-window signals includes:

[0163] Calculating the mean value of the signal power within the window of each signal within the window; and calculating the number of abnormal fluctuations within the window of each signal within the window based on the peak value of the fluctuation point within each signal within the window;

[0164] Calculating the signal variance within the window of each windowed signal based on the signal power mean within the window;

[0165] The number of abnormal fluctuations in the window and the variance of the signal in the window are used as collision features of the signal in the window.

[0166] In one or more embodiments, performing collision detection on the inventory signal based on the intra-window signal collision characteristics of each of the intra-window signals includes:

[0167] Taking the average of the signal variances in each of the windows to obtain the total signal variance; and obtaining the total abnormal fluctuation number based on the maximum value of the abnormal fluctuation number in each of the windows;

[0168] Comparing the total signal variance with a maximum variance threshold and a minimum variance threshold;

[0169] When the total signal variance is greater than the maximum variance threshold, confirming that the inventory signal has collided;

[0170] When the total signal variance is less than or equal to the maximum variance threshold value and greater than the minimum variance threshold value, and the total abnormal fluctuation number is greater than the fluctuation number threshold value, it is confirmed that the inventory signal has collided.

[0171] In one or more embodiments, further comprising:

[0172] Calculating a total signal power average of the stored signals based on the in-window signal power averages of the in-window signals;

[0173] Calculating a signal-to-noise ratio of the inventory signal based on the total signal power mean;

[0174] When it is confirmed that the signal-to-noise ratio is greater than the signal-to-noise ratio threshold, a step of comparing the total signal variance with a maximum variance threshold and a minimum variance threshold is performed.

[0175] In one or more embodiments, further comprising:

[0176] When it is confirmed that the inventory signal collides, and the configuration parameters of the frame length control parameter include that the frame length control parameter adjustment strategy is a target strategy and the frame length control parameter is a preset frame length control parameter, adjusting the preset frame length control parameter according to the target strategy to obtain an adjusted frame length control parameter;

[0177] The adjusted frame length control parameter is sent to the wireless device.

[0178] The signal collision detection device provided in the embodiment of the present disclosure and the signal collision detection method provided in the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented therein.

[0179] The present disclosure also provides a communication device to perform the above signal collision detection method. Figure 8 It shows a schematic diagram of a communication device provided by some embodiments of the present disclosure. Figure 8As shown, the communication device 8 includes: a processor 800, a memory 801, a bus 802 and a communication interface 803, wherein the processor 800, the communication interface 803 and the memory 801 are connected via the bus 802; the memory 801 stores a computer program that can be run on the processor 800, and when the processor 800 runs the computer program, the signal collision detection method provided in any of the aforementioned embodiments of the present disclosure is executed.

[0180] The memory 801 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the device network element and at least one other network element is realized through at least one communication interface 803 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0181] The bus 802 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory 801 is used to store a program, and the processor 800 executes the program after receiving an execution instruction. The signal collision detection method disclosed in any implementation of the aforementioned embodiment of the present disclosure may be applied to the processor 800, or implemented by the processor 800.

[0182] The processor 800 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 800 or the instruction in the form of software. The above processor 800 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present disclosure can be directly embodied as a hardware decoding processor to be executed, or the hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 801, and the processor 800 reads the information in the memory 801 and completes the steps of the above method in combination with its hardware.

[0183] The communication device provided by the embodiment of the present disclosure and the signal collision detection method provided by the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented therein.

[0184] The present disclosure also provides a computer-readable storage medium corresponding to the signal collision detection method provided in the above embodiment. Fig. 9 The computer-readable storage medium shown is a CD 30 on which a computer program (ie, a program product) is stored. When the computer program is run by a processor, the signal collision detection method provided by any of the aforementioned embodiments will be executed.

[0185] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0186] The computer-readable storage medium provided by the above-mentioned embodiment of the present disclosure and the signal collision detection method provided by the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the method adopted, run or implemented by the application program stored therein.

[0187] It should be noted that:

[0188] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present disclosure can be practiced without these specific details. In some instances, well-known structures and technologies are not shown in detail so as not to obscure the understanding of this description.

[0189] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present disclosure, the various features of the present disclosure are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be interpreted as reflecting the following schematic diagram: the claimed disclosure requires more features than the features explicitly recited in each claim. More specifically, as reflected in the claims below, the inventive aspects lie in less than all the features of the single embodiment disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present disclosure.

[0190] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of this disclosure and form different embodiments. For example, in the claims below, any one of the claimed embodiments may be used in any combination.

[0191] The above is only a preferred specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for detecting signal collision, characterized in that: Applications in passive RF devices, including: Based on the service signaling received from the application platform, obtaining configuration information of the wireless device, wherein the configuration information includes configuration parameters of the frame length control parameter; In the case where the configuration parameter of the frame length control parameter indicates that collision detection needs to be performed on the signal of the wireless device, sliding window processing is performed on the inventory signal from the wireless device according to a preset symbol length to obtain a plurality of signals within the window; Extracting the intra-window signal collision feature of each of the intra-window signals, wherein the intra-window signal collision feature is used to characterize the abnormal fluctuation of the waveform of the windowed signal; The inventory signals are subjected to collision detection based on the in-window signal collision characteristics of each of the in-window signals.

2. The method according to claim 1, characterized in that The configuration parameters of the frame length control parameter include at least one of the following: Business scenario identification; Frame length control parameters; A flag used to indicate whether collision detection is required; Frame length control parameter adjustment strategy.

3. The method according to claim 1, characterized in that Extracting the intra-window signal collision feature of each of the intra-window signals includes: Calculating the mean value of the signal power within the window of each signal within the window; and calculating the number of abnormal fluctuations within the window of each signal within the window based on the peak value of the fluctuation point within each signal within the window; Calculating the signal variance within the window of each windowed signal based on the signal power mean within the window; The number of abnormal fluctuations in the window and the variance of the signal in the window are used as collision features of the signal in the window.

4. The method according to claim 3, characterized in that The method further comprises: performing collision detection on the inventory signal based on the collision characteristics of the signals in the windows, comprising: Taking the average of the signal variances in each of the windows to obtain the total signal variance; and obtaining the total abnormal fluctuation number based on the maximum value of the abnormal fluctuation number in each of the windows; Comparing the total signal variance with a maximum variance threshold and a minimum variance threshold; When the total signal variance is greater than the maximum variance threshold, confirming that the inventory signal has collided; When the total signal variance is less than or equal to the maximum variance threshold value and greater than the minimum variance threshold value, and the total abnormal fluctuation number is greater than the fluctuation number threshold value, it is confirmed that the inventory signal has collided.

5. The method according to claim 4, characterized in that Also includes: Calculating a total signal power average of the stored signals based on the in-window signal power averages of the in-window signals; Calculating a signal-to-noise ratio of the inventory signal based on the total signal power mean; When it is confirmed that the signal-to-noise ratio is greater than the signal-to-noise ratio threshold, a step of comparing the total signal variance with a maximum variance threshold and a minimum variance threshold is performed.

6. The method according to any one of claims 1 to 5, characterized in that: Also includes: When it is confirmed that the inventory signal collides, and the configuration parameters of the frame length control parameter include that the frame length control parameter adjustment strategy is a target strategy and the frame length control parameter is a preset frame length control parameter, adjusting the preset frame length control parameter according to the target strategy to obtain an adjusted frame length control parameter; The adjusted frame length control parameter is sent to the wireless device.

7. A signal collision detection system, characterized in that: include: Application platforms, passive RF devices and wireless devices; The passive radio frequency device is used to obtain configuration information of the wireless device based on the service signaling received from the application platform, wherein the configuration information includes configuration parameters of frame length control parameters; when the configuration parameters of the frame length control parameters indicate that collision detection needs to be performed on the signal of the wireless device, sliding window processing is performed on the stored signals from the wireless device according to a preset symbol length to obtain multiple in-window signals; a collision feature of the in-window signal of each in-window signal is extracted, wherein the collision feature of the in-window signal is used to characterize the abnormal fluctuation of the waveform of the windowed signal; and collision detection is performed on the stored signals based on the collision feature of the in-window signal of each in-window signal.

8. A communication device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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