Test data management system and method based on millimeter wave communication equipment

Abstract

The invention discloses a test data management system and method based on millimeter wave communication equipment, and relates to the technical field of wireless communication, historical data is divided into a data set with signal loss and a data set without signal loss, data in the data sets are used for training a missing value filling model, and a missing value filling model is obtained; obtaining signal fragments with signal loss in the wireless signal, obtaining associated fragments of the target signal, screening out the repair fragment with the minimum difference from the plurality of repair fragments as a substitute fragment through a missing value filling model according to the association relationship, and replacing the target signal fragment with the substitute fragment, and inputting the wireless signal after replacing the target signal segment into a signal analysis end, obtaining the accuracy of the analysis result of the signal, and establishing a new association relationship between the other association segment in the two association segments and the target signal segment to replace the original association relationship.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a test data management system and method based on millimeter wave communication equipment. Background Art

[0002] Millimeter wave communication refers to communication that uses millimeter waves as a carrier for transmitting information. Due to its short wavelength and wide bandwidth, millimeter waves can be applied to the field of high-speed bandwidth wireless communications. In the field of traditional digital communication technology, it is necessary to sample the transmission waveform and then make a judgment based on the signal waveform. In order to improve the accuracy of signal decoding, it is necessary to add check bits and error correction bits to the transmission signal. However, as the information transmission rate increases, the information capacity of the communication system continues to increase. Adding additional check bits and error correction bits will cause the system to transmit too much redundant information. Traditional information error correction methods are difficult to apply to high-speed transmission communication systems. Summary of the invention

[0003] The purpose of the present invention is to provide a test data management system and method based on millimeter wave communication equipment to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solution: a test data management method based on millimeter wave communication equipment, the method comprising:

[0005] Step S100: collecting historical data of wireless communications, dividing the historical data into a data set with signal loss and a data set without signal loss, using the data in the data set to train a missing value filling model, and verifying the missing value filling model by simulating interference caused by signal loss;

[0006] Step S200: collecting the currently transmitted wireless signal, obtaining a signal segment with signal loss in the wireless signal, taking the signal segment as a target signal segment, and taking two signal segments adjacent to the target signal segment as associated segments of the target signal;

[0007] Step S300: using a missing value filling model, obtaining several repair segments of the target signal segment, establishing an association relationship between one of the two associated segments and the target signal segment, selecting a repair segment with the smallest difference from the several repair segments according to the association relationship as a substitute segment, and replacing the target signal segment with the substitute segment;

[0008] Step S400: inputting the wireless signal after replacing the target signal segment into the signal analysis terminal to obtain the accuracy of the signal analysis result;

[0009] Step S500: Obtain the average value of several unit detection cycles. When the accuracy of the analysis result of the replaced wireless signal is less than the average value, establish a new association relationship between the other associated fragment of the two associated fragments and the target signal fragment to replace the original association relationship, set a protection threshold, and when the replacement frequency of the association relationship is higher than the protection threshold, issue an alarm to the relevant management personnel.

[0010] Furthermore, step S100 includes:

[0011] Step S101: Collecting historical transmission records of wireless communications, and dividing the historical transmission records into a first category of historical records and a second category of historical records, wherein the first category of historical records includes historical transmission records in which signal loss occurs during wireless signal transmission, and the second category of historical records includes historical transmission records in which there is no signal loss during wireless signal transmission;

[0012] Step S102: marking the first type of historical records according to the cause of signal loss to obtain interference cause labels, and collecting the interference cause labels to obtain an interference feature library;

[0013] Step S103: obtaining an interference cause label or a combination of at least two interference cause labels from the interference feature library, generating an interference signal, simulating the wireless transmission signal in the second type of historical records to obtain a first simulation signal, interfering with the first simulation signal through the interference signal to obtain a second simulation signal, and collecting the second simulation signals to obtain a verification data set;

[0014] Step S104: training a random forest model through the second historical record to obtain a missing value filling model, and verifying the missing value filling model through a verification data set;

[0015] A random forest model is trained using the non-missing values ​​in the data set. This random forest model is used to generate replacement fragments for information fragments with interference. Through the pre-trained data model, the fragments are identified and adjusted to avoid judging the information content of each interfering fragment, thereby improving the efficiency of processing the interfered information.

[0016] Further, step S200 includes:

[0017] Step S201: taking the currently transmitted wireless signal as the current transmission signal, obtaining the transmitter and receiver of the current transmission signal, and recording the direction from the transmitter to the receiver as the signal transmission direction;

[0018] Step S202: Divide the current transmission signal into a plurality of signal segments, obtain a signal segment with signal loss in the current transmission signal, take the model segment as the target signal segment, obtain a signal segment adjacent to the target signal segment along the signal transmission direction, record the segment as the first associated segment, obtain a signal segment adjacent to the target signal segment along the opposite direction of the signal transmission direction, record the segment as the second associated segment,

[0019] Furthermore, step S300 includes:

[0020] Step S301: Obtain N repair segments of a target signal segment through the missing value filling model, and obtain the distance between the i-th repair segment and the associated segment among the N repair segments, denoted as d i , the associated fragment is the first associated fragment or the second associated fragment;

[0021] Step S302: Obtain reference samples of N repaired segments, where the reference sample is the average or median of the N repaired segments, and record the distance between the i-th repaired segment in the N repaired segments and the reference sample as r i ;

[0022] Step S303: Calculate the reference coefficient α of the i-th repair segment i ,

[0023] Firstly, a unilateral dependency relationship between the target information fragment and its unilateral neighbor is established. The computational complexity in the decision process is reduced through the unilateral dependency relationship, thus improving the processing and matching efficiency of the information fragment.

[0024] Step S304: traverse the N repair segments to obtain reference coefficients of the respective repair segments, use the repair segment with the smallest reference coefficient as a substitute segment, and replace a target signal segment with the substitute segment.

[0025] Furthermore, step S400 includes:

[0026] Step S401: setting a unit detection period with a time length of T0, obtaining and storing the average value of the signal transmission accuracy rate in each unit detection period;

[0027] Step S402: When the moment after the replacement of the substitute segment is completed is taken as the current moment, the unit detection cycle including the current moment is taken as the current cycle, the current cycle is recorded as the jth cycle, and the k unit detection cycles before the jth cycle are obtained, wherein the kth unit detection cycle before the jth cycle is recorded as cor j-k , respectively obtain the average value of the signal transmission accuracy of the first k unit detection cycles, and calculate the accuracy reference value β, Among them, cor mIt represents the average value of the signal transmission accuracy of the mth unit detection cycle in the first k unit detection cycles, satisfying the condition jk≥1;

[0028] After replacing the information fragments, the accuracy of information parsing is obtained. When the accuracy of information parsing is improved after replacement, it means that the dependency relationship selected can provide better communication quality.

[0029] Furthermore, step S500 includes:

[0030] Step S501: Obtain the average value of the signal transmission accuracy rate in the jth cycle, denoted as cor j , when cor j ≥β, the association relationship between the repaired segment and the corresponding associated segment in step S300 is maintained;

[0031] Step S502: When cor j <β, adjusting the association relationship between the repair segment and the corresponding associated segment in step S300, and re-executing step S300, wherein the adjustment method includes: if the first associated segment is adopted in step S300, adjusting to adopt the second associated segment when step S300 is executed next time; if the second associated segment is adopted in step S300, adjusting to adopt the first associated segment when step S300 is executed next time;

[0032] Step S503: adjusting the association relationship from the first association segment to the second association segment, or from the second association segment to the first association segment is recorded as one adjustment, and setting an alarm period of T1, where T1 satisfies the condition: T1>T0, and when the number of adjustments within the alarm period exceeds P times, an alarm prompt is issued to the relevant management personnel, where P is a positive integer;

[0033] When the system frequently changes dependencies, it indicates that the stability of the system has deteriorated. In order to avoid larger-scale communication system failures caused by deterioration of system stability, it is necessary to request inspection and maintenance in a timely manner.

[0034] In order to better implement the above method, a test data management system based on millimeter wave communication equipment is also proposed, the system includes: a model management module, a signal acquisition module, a signal replacement module, an evaluation module and an association adjustment module, wherein the model management module is used to train and manage the missing value filling model, the signal acquisition module is used to collect the currently transmitted wireless signal and perform fragment management on the wireless signal, the signal replacement module is used to obtain the repair fragment and replace the target signal fragment, the evaluation module is used to evaluate the accuracy of the signal analysis result, and the association adjustment module is used to adjust the association relationship of the target signal fragment;

[0035] The model management module includes: a historical record classification unit, an interference feature management unit and a missing value filling model management unit, wherein the historical record classification unit is used to collect historical transmission records of wireless communications and divide the historical transmission records into first-category historical records and second-category historical records, the interference feature management unit is used to manage an interference feature library, and the missing value filling model management unit is used to manage a missing value filling model;

[0036] The signal acquisition module includes: a transmission direction acquisition unit and a slice management unit, wherein the transmission direction acquisition unit is used to obtain the transmission direction of the wireless signal, and the slice management unit is used to perform slice management on the wireless signal;

[0037] The signal substitute module includes: a repair segment management unit, an associated slice management unit, a reference coefficient calculation unit and a traversal unit, wherein the repair segment management unit is used to obtain a repair segment through a missing value filling model, the associated slice management unit is used to obtain an associated slice of a target signal slice, the reference coefficient calculation unit is used to obtain an associated relationship between a repair segment and an associated slice, and calculate a reference coefficient, and the traversal unit is used to traverse the repair segment to obtain a substitute segment;

[0038] The evaluation module includes: an accuracy management unit and a replacement evaluation unit, wherein the accuracy management unit is used to obtain and store the signal transmission accuracy in each unit detection cycle, and the replacement evaluation unit is used to evaluate the signal transmission accuracy of the replaced wireless signal;

[0039] The association adjustment module includes: an association relationship judgment unit, an association relationship adjustment unit and an alarm prompt unit, wherein the association relationship judgment unit is used to judge whether the association relationship is maintained, the association relationship adjustment unit is used to adjust the association relationship of the target signal slice, and the alarm prompt unit is used to monitor the adjustment frequency.

[0040] Compared with the prior art, the beneficial effects of the present invention are: through the pre-trained recognition model, the received wireless signal is pre-processed at the wireless communication receiving end. In order to improve the processing efficiency, the wireless signal of the fragment is processed as a whole, which reduces the error correction pressure for the back-end information judgment and information decoding process. In the process of matching the information fragments, the form of unilateral matching is adopted to reduce the amount of matching operation in the matching process. In order to ensure the correctness of the unilateral matching, verification and protection related modules are also designed, so that the system can achieve self-checking and self-protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a structural schematic diagram of a test data management system based on millimeter wave communication equipment of the present invention;

[0042] Figure 2The figure is a flow chart of a test data management method based on millimeter wave communication equipment according to the present invention. DETAILED DESCRIPTION

[0043] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0044] Example: Figure 1 and Figure 2 As shown, the present invention provides a technical solution, a test data management method based on millimeter wave communication equipment:

[0045] Step S100: collecting historical data of wireless communications, dividing the historical data into a data set with signal loss and a data set without signal loss, using the data in the data set to train a missing value filling model, and verifying the missing value filling model by simulating interference caused by signal loss;

[0046] Wherein, step S100 includes:

[0047] Step S101: Collecting historical transmission records of wireless communications, and dividing the historical transmission records into a first category of historical records and a second category of historical records, wherein the first category of historical records includes historical transmission records in which signal loss occurs during wireless signal transmission, and the second category of historical records includes historical transmission records in which there is no signal loss during wireless signal transmission;

[0048] Step S102: marking the first type of historical records according to the cause of signal loss to obtain interference cause labels, and collecting the interference cause labels to obtain an interference feature library;

[0049] Step S103: obtaining an interference cause label or a combination of at least two interference cause labels from the interference feature library, generating an interference signal, simulating the wireless transmission signal in the second type of historical records to obtain a first simulation signal, interfering with the first simulation signal through the interference signal to obtain a second simulation signal, and collecting the second simulation signals to obtain a verification data set;

[0050] Step S104: training a random forest model through the second historical record to obtain a missing value filling model, and verifying the missing value filling model through a verification data set;

[0051] The random forest model is trained by using an error-free data set, and the error detection and correction capabilities of the random forest model are tested by introducing artificial interference data. The maximum depth, minimum number of sample splits, and minimum number of leaf node samples of the conditional random forest model are set to make the model adapt to the environmental characteristics of the receiver operation.

[0052] In an embodiment, the causes of signal loss are, for example, interference received during wireless transmission and background noise of the communication system itself.

[0053] Step S200: collecting the currently transmitted wireless signal, obtaining a signal segment with signal loss in the wireless signal, taking the signal segment as a target signal segment, and taking two signal segments adjacent to the target signal segment as associated segments of the target signal;

[0054] Wherein, step S200 includes:

[0055] Step S201: taking the currently transmitted wireless signal as the current transmission signal, obtaining the transmitter and receiver of the current transmission signal, and recording the direction from the transmitter to the receiver as the signal transmission direction;

[0056] Step S202: Divide the current transmission signal into several signal segments, obtain the signal segment with signal loss in the current transmission signal, take the model segment as the target signal segment, obtain the signal segment adjacent to the target signal segment along the signal transmission direction, record the segment as the first associated segment, obtain the signal segment adjacent to the target signal segment along the opposite direction of the signal transmission direction, and record the segment as the second associated segment.

[0057] Step S300: using a missing value filling model, obtaining several repair segments of the target signal segment, establishing an association relationship between one of the two associated segments and the target signal segment, selecting a repair segment with the smallest difference from the several repair segments according to the association relationship as a substitute segment, and replacing the target signal segment with the substitute segment;

[0058] Wherein, step S300 includes:

[0059] Step S301: Obtain N repair segments of a target signal segment through the missing value filling model, and obtain the distance between the i-th repair segment and the associated segment among the N repair segments, denoted as d i , the associated fragment is the first associated fragment or the second associated fragment;

[0060] Step S302: Obtain reference samples of N repaired segments, where the reference sample is the average or median of the N repaired segments, and record the distance between the i-th repaired segment in the N repaired segments and the reference sample as r i ;

[0061] Step S303: Calculate the reference coefficient α of the i-th repair segment i ,

[0062] Step S304: traverse the N repair segments to obtain reference coefficients of the respective repair segments, use the repair segment with the smallest reference coefficient as a substitute segment, and replace a target signal segment with the substitute segment.

[0063] Step S400: inputting the wireless signal after replacing the target signal segment into the signal analysis terminal to obtain the accuracy of the signal analysis result;

[0064] Wherein, step S400 includes:

[0065] Step S401: setting a unit detection period with a time length of T0, obtaining and storing the average value of the signal transmission accuracy rate in each unit detection period;

[0066] Step S402: When the moment after the replacement of the substitute segment is completed is taken as the current moment, the unit detection cycle including the current moment is taken as the current cycle, the current cycle is recorded as the jth cycle, and the k unit detection cycles before the jth cycle are obtained, wherein the kth unit detection cycle before the jth cycle is recorded as cor j-k , respectively obtain the average value of the signal transmission accuracy of the first k unit detection cycles, and calculate the accuracy reference value β, Among them, cor m It represents the average value of the signal transmission accuracy of the mth unit detection cycle in the first k unit detection cycles, satisfying the condition jk≥1;

[0067] For example, the current cycle is the jth cycle, the first cycle before the jth cycle is the j-1th cycle, the second cycle before the jth cycle is the j-2th cycle, and so on, the kth cycle before the jth cycle is the jkth cycle;

[0068] In an embodiment, the signal transmission accuracy rate may be expressed as 1-SER, where SER represents bit error rate.

[0069] Step S500: obtaining an average value of several unit detection cycles. When the accuracy of the analysis result of the replaced wireless signal is less than the average value, a new association relationship is established between the other associated segment of the two associated segments and the target signal segment to replace the original association relationship. A protection threshold is set. When the replacement frequency of the association relationship is higher than the protection threshold, an alarm is given to the relevant management personnel.

[0070] Wherein, step S500 includes:

[0071] Step S501: Obtain the average value of the signal transmission accuracy rate in the jth cycle, denoted as cor j , when cor j ≥β, the association relationship between the repaired segment and the corresponding associated segment in step S300 is maintained;

[0072] Step S502: When cor j <β, adjusting the association relationship between the repair segment and the corresponding associated segment in step S300, and re-executing step S300, wherein the adjustment method includes: if the first associated segment is adopted in step S300, adjusting to adopt the second associated segment when step S300 is executed next time; if the second associated segment is adopted in step S300, adjusting to adopt the first associated segment when step S300 is executed next time;

[0073] Step S503: Adjusting the association relationship from the first association segment to the second association segment, or from the second association segment to the first association segment is recorded as one adjustment, and an alarm period of T1 is set, where T1 satisfies the condition: T1>T0. When the number of adjustments within the alarm period exceeds P times, an alarm prompt is given to the relevant management personnel, where P is a positive integer.

[0074] A test data management system based on millimeter wave communication equipment, the system includes: a model management module, a signal acquisition module, a signal substitute module, an evaluation module and a correlation adjustment module;

[0075] The model management module is used to train and manage the missing value filling model, wherein the model management module includes: a historical record classification unit, an interference feature management unit and a missing value filling model management unit, wherein the historical record classification unit is used to collect historical transmission records of wireless communications and divide the historical transmission records into a first category of historical records and a second category of historical records, the interference feature management unit is used to manage an interference feature library, and the missing value filling model management unit is used to manage the missing value filling model;

[0076] The signal acquisition module is used to acquire the currently transmitted wireless signal and perform slice management on the wireless signal. The signal acquisition module includes: a transmission direction acquisition unit and a slice management unit. The transmission direction acquisition unit is used to acquire the transmission direction of the wireless signal, and the slice management unit is used to perform slice management on the wireless signal.

[0077] The signal replacement module is used to obtain a repair segment and replace the target signal segment. The signal replacement module includes: a repair segment management unit, an associated slice management unit, a reference coefficient calculation unit and a traversal unit. The repair segment management unit is used to obtain a repair segment through a missing value filling model, the associated slice management unit is used to obtain an associated slice of the target signal slice, the reference coefficient calculation unit is used to obtain an associated relationship between the repair slice and the associated slice, and calculate a reference coefficient. The traversal unit is used to traverse the repair segment to obtain a replacement segment.

[0078] The evaluation module is used to evaluate the accuracy of the analysis result of the signal, wherein the evaluation module includes: an accuracy management unit and a replacement evaluation unit, wherein the accuracy management unit is used to obtain and store the signal transmission accuracy in each unit detection cycle, and the replacement evaluation unit is used to evaluate the signal transmission accuracy of the replaced wireless signal;

[0079] Among them, the association adjustment module is used to adjust the association relationship of the target signal segments, wherein the association adjustment module includes: an association relationship judgment unit, an association relationship adjustment unit and an alarm prompt unit, wherein the association relationship judgment unit is used to judge whether the association relationship is maintained, the association relationship adjustment unit is used to adjust the association relationship of the target signal slices, and the alarm prompt unit is used to monitor the adjustment frequency.

[0080] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A test data management method based on millimeter wave communication equipment, characterized in that: Step S100: collecting historical data of wireless communications, dividing the historical data into a data set with signal loss and a data set without signal loss, using the data in the data set to train a missing value filling model, and verifying the missing value filling model by simulating interference caused by signal loss; Step S200: collecting the currently transmitted wireless signal, obtaining a signal segment with signal loss in the wireless signal, taking the signal segment as a target signal segment, and taking two signal segments adjacent to the target signal segment as associated segments of the target signal; Step S300: obtaining several repair segments of the target signal segment through a missing value filling model, establishing an association relationship between one of the two associated segments and the target signal segment, selecting a repair segment with the smallest difference from the several repair segments according to the association relationship as a substitute segment, and replacing the target signal segment with the substitute segment; Step S400: inputting the wireless signal after replacing the target signal segment into the signal analysis terminal to obtain the accuracy of the signal analysis result; Step S500: Obtain the average value of several unit detection cycles. When the accuracy of the analysis result of the replaced wireless signal is less than the average value, establish a new association relationship between the other associated fragment of the two associated fragments and the target signal fragment to replace the original association relationship, set a protection threshold, and when the replacement frequency of the association relationship is higher than the protection threshold, issue an alarm to the relevant management personnel.

2. The test data management method based on millimeter wave communication equipment according to claim 1, characterized in that: Step S100 includes: Step S101: Collecting historical transmission records of wireless communications, and dividing the historical transmission records into a first category of historical records and a second category of historical records, wherein the first category of historical records includes historical transmission records in which signal loss occurs during wireless signal transmission, and the second category of historical records includes historical transmission records in which there is no signal loss during wireless signal transmission; Step S102: marking the first type of historical records according to the cause of signal loss to obtain interference cause labels, and collecting the interference cause labels to obtain an interference feature library; Step S103: obtaining an interference cause label or a combination of at least two interference cause labels from the interference feature library, generating an interference signal, simulating the wireless transmission signal in the second type of historical records to obtain a first simulation signal, interfering with the first simulation signal through the interference signal to obtain a second simulation signal, and collecting the second simulation signals to obtain a verification data set; Step S104: training the random forest model through the second historical record to obtain a missing value filling model, and verifying the missing value filling model through the verification data set.

3. The test data management method based on millimeter wave communication equipment according to claim 2, characterized in that: Step S200 includes: Step S201: taking the currently transmitted wireless signal as the current transmission signal, obtaining the transmitter and receiver of the current transmission signal, and recording the direction from the transmitter to the receiver as the signal transmission direction; Step S202: Divide the current transmission signal into several signal segments, obtain the signal segment with signal loss in the current transmission signal, take the model segment as the target signal segment, obtain the signal segment adjacent to the target signal segment along the signal transmission direction, record the segment as the first associated segment, obtain the signal segment adjacent to the target signal segment along the opposite direction of the signal transmission direction, and record the segment as the second associated segment.

4. The test data management method based on millimeter wave communication equipment according to claim 3, characterized in that: Step S300 includes: Step S301: Obtain N repair segments of a target signal segment through the missing value filling model, and obtain the distance between the i-th repair segment and the associated segment in the N repair segments, which is recorded as d i , the associated fragment is the first associated fragment or the second associated fragment; Step S302: Obtain reference samples of the N repaired segments, where the reference samples are the average or median of the N repaired segments, and record the distance between the i-th repaired segment in the N repaired segments and the reference sample as r i ; Step S303: Calculate the reference coefficient α of the i-th repair segment i , Step S304: traverse the N repair segments to obtain reference coefficients of the respective repair segments, use the repair segment with the smallest reference coefficient as a substitute segment, and replace the target signal segment with the substitute segment.

5. The test data management method based on millimeter wave communication equipment according to claim 4, characterized in that: Step S400 includes: Step S401: setting a unit detection period with a time length of T0, obtaining and storing the average value of the signal transmission accuracy rate in each unit detection period; Step S402: When the moment after the replacement of the substitute segment is completed is taken as the current moment, the unit detection cycle including the current moment is taken as the current cycle, the current cycle is recorded as the jth cycle, and the k unit detection cycles before the jth cycle are obtained, wherein the kth unit detection cycle before the jth cycle is recorded as cor j-k , respectively obtain the average value of the signal transmission accuracy of the first k unit detection cycles, and calculate the accuracy reference value β, Among them, cor m It represents the average value of the signal transmission accuracy of the mth unit detection cycle in the first k unit detection cycles, satisfying the condition jk≥1.

6. The test data management method based on millimeter wave communication equipment according to claim 5, characterized in that: Step S500 includes: Step S501: Obtain the average value of the signal transmission accuracy rate in the jth cycle, denoted as cor j , when cor j ≥β, the association relationship between the repaired segment and the corresponding associated segment in step S300 is maintained; Step S502: When cor j <β, adjusting the association relationship between the repair segment and the corresponding associated segment in step S300, and re-executing step S300, wherein the adjustment method includes: if the first associated segment is adopted in step S300, adjusting to adopt the second associated segment when step S300 is executed next time; if the second associated segment is adopted in step S300, adjusting to adopt the first associated segment when step S300 is executed next time; Step S503: Adjusting the association relationship from the first association segment to the second association segment, or from the second association segment to the first association segment is recorded as one adjustment, and an alarm period of T1 is set, where T1 satisfies the condition: T1>T0. When the number of adjustments within the alarm period exceeds P times, an alarm prompt is given to the relevant management personnel, where P is a positive integer.

7. A test data management system based on millimeter wave communication equipment, used to execute the test data management method based on millimeter wave communication equipment according to any one of claims 1 to 6, characterized in that: The system includes: A model management module, a signal acquisition module, a signal replacement module, an evaluation module and an association adjustment module, wherein the model management module is used to train and manage the missing value filling model, the signal acquisition module is used to collect the currently transmitted wireless signal and perform fragment management on the wireless signal, the signal replacement module is used to obtain the repair fragment and replace the target signal fragment, the evaluation module is used to evaluate the accuracy of the signal analysis result, and the association adjustment module is used to adjust the association relationship of the target signal fragment.

8. The test data management system based on millimeter wave communication equipment according to claim 7, characterized in that: The model management module includes: a historical record classification unit, an interference feature management unit and a missing value filling model management unit, wherein the historical record classification unit is used to collect historical transmission records of wireless communications and divide the historical transmission records into first-category historical records and second-category historical records, the interference feature management unit is used to manage an interference feature library, and the missing value filling model management unit is used to manage a missing value filling model; The signal acquisition module includes: a transmission direction acquisition unit and a slice management unit, wherein the transmission direction acquisition unit is used to obtain the transmission direction of the wireless signal, and the slice management unit is used to perform slice management on the wireless signal.

9. The test data management system based on millimeter wave communication equipment according to claim 7, characterized in that: The signal replacement module includes: a repair fragment management unit, an associated slice management unit, a reference coefficient calculation unit and a traversal unit, wherein the repair fragment management unit is used to obtain the repair fragment through the missing value filling model, the associated slice management unit is used to obtain the associated slice of the target signal slice, the reference coefficient calculation unit is used to obtain the association relationship between the repair slice and the associated slice, calculate the reference coefficient, and the traversal unit is used to traverse the repair fragment to obtain the replacement fragment.

10. The test data management system based on millimeter wave communication equipment according to claim 7, characterized in that: The evaluation module includes: an accuracy management unit and a replacement evaluation unit, wherein the accuracy management unit is used to obtain and store the signal transmission accuracy in each unit detection cycle, and the replacement evaluation unit is used to evaluate the signal transmission accuracy of the replaced wireless signal; The association adjustment module includes: an association relationship judgment unit, an association relationship adjustment unit and an alarm prompt unit, wherein the association relationship judgment unit is used to judge whether the association relationship is maintained, the association relationship adjustment unit is used to adjust the association relationship of the target signal slice, and the alarm prompt unit is used to monitor the adjustment frequency.

Images