A method and system for monitoring communication signals of an intelligent repeater

Abstract

This invention relates to the field of communication signal monitoring, specifically to a communication signal monitoring method and system for an intelligent repeater. The method includes: acquiring a signal time series of a wireless communication signal within a preset sampling period; using any signal in the signal time series as a target signal, calculating an adjustment step size for the target signal, updating the weights of filter modules in the repeater according to the adjustment step size, and constructing an error sequence by outputting an error signal from the filter modules with updated weights, wherein one signal in the signal time series corresponds to one error signal; and outputting a signal monitoring result based on the error sequence. This invention can improve the accuracy of signal monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication signal monitoring. More particularly, the present application relates to a communication signal monitoring method and system of an intelligent repeater. BACKGROUND

[0002] The purpose of repeater signal monitoring is to identify interference and then make a decision to suspend or forward the signal according to the monitoring result. The current 5G / 6G communication protocol sets a strict time limit for the signal monitoring of the repeater: the repeater must complete interference identification and make a decision within a very short time. However, the traditional LMS (Least Mean Square) algorithm updates the filter weight with a fixed step, which leads to a convergence process, i.e. the time required for the algorithm to make a stable judgment from the received signal exceeds the maximum response time allowed by the protocol. As a result, in a critical interference scenario, the algorithm needs a longer time to make a reliable judgment. Due to the time limit, the probability of misjudging instantaneous interference as real attenuation significantly increases during the critical response period. Therefore, the signal monitoring of the traditional repeater is not accurate enough. SUMMARY

[0003] The main purpose of the embodiments of the present application is to propose a communication signal monitoring method and system of an intelligent repeater, aiming to improve the accuracy of signal monitoring.

[0004] To achieve the above-mentioned purpose, the embodiments of the first aspect of the present application propose a communication signal monitoring method of an intelligent repeater, which comprises: collecting signal time sequences of wireless communication signals in a preset sampling period, taking any signal in the signal time sequences as a target signal, calculating an adjustment step of the target signal, updating the weight of a filter module in the repeater according to the adjustment step, and outputting an error signal to construct an error sequence according to the filter module after updating the weight, wherein one signal in the signal time sequence corresponds to one error signal; outputting a signal monitoring result according to the error sequence; wherein the calculation method of the adjustment step is: generating a window in the signal time sequence with the target signal as the right boundary, taking all signals in the window as a sub-sequence, calculating a noise influence coefficient of the sub-sequence, calculating the relative mutation intensity of the target signal, taking the sum of the reciprocal of the relative mutation intensity and the noise influence coefficient as the reciprocal of the step scaling coefficient, obtaining the reference step of the target signal, and taking the product of the reference step and the step scaling coefficient as the adjustment step.

[0005] In some embodiments, calculating the noise influence coefficient of the sub-sequence inside the window comprises: calculating the average noise power and the average signal power of the sub-sequence; and taking the ratio of the average noise power and the average signal power as the noise influence coefficient.

[0006] In some embodiments, the acquiring the relative mutation intensity of the target signal comprises: calculating a disturbance change rate of the target signal; acquiring a smoothing factor, based on which a history reference of the disturbance change rate is calculated using an exponential weighted moving average algorithm; and taking a ratio of the disturbance change rate and the history reference as the relative mutation intensity.

[0007] In some embodiments, the calculating the disturbance change rate of the target signal comprises: calculating a Doppler shift; taking a signal at a previous sampling time adjacent to a sampling time of the target signal as a reference signal, calculating an instantaneous amplitude of the target signal and an instantaneous amplitude of the reference signal, calculating an absolute difference value of the instantaneous amplitude of the target signal and the instantaneous amplitude of the reference signal, taking a ratio of the absolute difference value and the preset sampling period as an instantaneous change rate, and taking a ratio of the instantaneous change rate and the Doppler shift as the disturbance change rate of the target signal.

[0008] In some embodiments, the acquiring the smoothing factor comprises: calculating a Doppler shift, taking an inverse of the Doppler shift as a channel coherence time; and performing a negative correlation mapping on a ratio of the preset sampling period and the channel coherence time by an exponential function to obtain the smoothing factor.

[0009] In some embodiments, the acquiring the reference step length of the target signal comprises: calculating an average signal power of the sub-sequence; and taking a ratio of 2 and the average signal power as the reference step length.

[0010] In some embodiments, the outputting the monitoring result according to the error sequence comprises: counting a continuous number of errors greater than a first preset threshold in the error sequence; in response to the continuous number being greater than a second preset threshold, taking a real attenuation existing in the wireless communication signal as the monitoring result; and in response to the continuous number not being greater than the second preset threshold, taking an instantaneous disturbance existing in the wireless communication signal as the monitoring result.

[0011] Embodiments of the second aspect of the present application propose a communication signal monitoring system of an intelligent repeater, the system comprising: a processor and a memory, the memory storing computer program instructions, when the computer program instructions are executed by the processor, a communication signal monitoring method of an intelligent repeater is realized.

[0012] Advantages of the present application:

[0013] The traditional relay uses a fixed step in the implementation of the LMS algorithm, while the application is a dynamic step, and the dynamic step is positively correlated with the step scaling factor, which is related to the relative mutation intensity of the current signal and the noise influence coefficient: the greater the relative mutation intensity, the greater the interference of the previous signal, and the greater the step scaling factor, and the greater the step, the greater the step, which can accelerate the convergence of the iteration, that is, it can faster realize interference suppression and pure signal generation, and can complete interference identification and decision-making within the time specified by the 5G / 6G communication protocol as soon as possible, reduce the probability of misjudging instantaneous interference as real attenuation, and improve the accuracy of relay monitoring, and because of the existence of the noise influence coefficient, the step scaling factor will not increase unlimitedly, that is, the step will not increase unlimitedly, so that the algorithm converges faster without breaking the stability boundary. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 It is a flowchart of steps S1-S2 in a communication signal monitoring method of an intelligent relay according to an embodiment of the application. DETAILED DESCRIPTION

[0015] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments.

[0016] The specific embodiments of the application will be described in detail below with reference to the drawings.

[0017] REFERENCE Figure 1 A communication signal monitoring method of an intelligent relay includes steps S1-S2, which are as follows:

[0018] Step S1: Collecting signal time sequences of wireless communication signals in a preset sampling period, taking any signal in the signal time sequences as a target signal, calculating an adjustment step of the target signal, updating the weight of the filter module in the relay according to the adjustment step, and outputting an error signal to construct an error sequence according to the updated filter module.

[0019] Wherein, one signal in the signal time sequence corresponds to one error signal; wherein, the calculation method of the adjustment step is: generating a window in the signal time sequence with the target signal as the right boundary, taking all signals in the window as a subsequence, calculating the noise influence coefficient of the subsequence, calculating the relative mutation intensity of the target signal, taking the sum of the inverse of the relative mutation intensity and the noise influence coefficient as the inverse of the step scaling factor, obtaining the reference step of the target signal, and taking the product of the reference step and the step scaling factor as the adjustment step.

[0020] It should be noted that the wireless communication signal is essentially an analog voltage signal generated by the radio frequency front end processing of the electromagnetic wave received by the antenna, and the repeater continuously samples the received wireless communication signal at a preset sampling period to form a signal time sequence , The input signal of the filter module in the repeater is also .

[0021] It should be noted that the windowed subsequence (a signal sequence before the target signal) is intercepted and the noise influence coefficient of the subsequence is calculated to reflect the stable noise level of the current (the time when the target signal is located) communication environment. The noise influence coefficients of other signals in the signal time sequence are calculated in the same way as the target signal. The specific value of the window length can be adjusted according to the actual application scenario. Specifically, the window length is 10.

[0022] It can be understood that calculating the noise influence coefficient of the subsequence in the window includes calculating the average noise power and the average signal power of the subsequence, and taking the ratio of the average noise power and the average signal power as the noise influence coefficient.

[0023] Exemplarily, the calculation formula of the noise influence coefficient is as follows:

[0024]

[0025] In the formula , n is the noise influence coefficient at the time t, T is the window length, s(t) is the sampling signal at the time t, d(t) is the expected signal at the time t, n(t) is the noise signal at the time t, P(t) is the noise power at the time t, Pn is the average noise power of the subsequence, Ps is the average signal power of the subsequence.

[0026] For the formula , it should be noted that the expected signal is locally generated by the repeater according to the network configuration parameters and standard rules. Specifically, the repeater obtains network identification information in the communication establishment stage, and calculates the sequence in real time according to the protocol specification, without additional signal collection. This signal serves as a benchmark for evaluating the quality of the received signal. Through the analysis of the difference between the sampling signal and the expected signal, the degree of noise influence in the channel can be quantified.​​​​​​​​​​​​​​​

[0027] For the formula It should be added that, Used to measure the degree of threat that noise poses to the stability of the LMS algorithm. The closer to 0, the lower the degree of influence of noise in the channel at the current sampling time, and the lower the threat level. Otherwise, it means that the degree of influence of noise in the channel at the current sampling time is higher, and the noise may seriously interfere with the signal at the current sampling time.

[0028] Understandably, calculating the rate of change of interference in the target signal includes calculating the Doppler frequency shift;

[0029] Using the signal from the previous sampling time adjacent to the sampling time of the target signal as the reference signal, calculate the instantaneous amplitude of the target signal and the instantaneous amplitude of the reference signal, calculate the absolute difference between the instantaneous amplitude of the target signal and the instantaneous amplitude of the reference signal, use the ratio of the absolute difference to the preset sampling period as the instantaneous change rate, and use the ratio of the instantaneous change rate to the Doppler frequency shift as the interference change rate of the target signal.

[0030] For example, the formula for calculating the rate of change of disturbance is as follows:

[0031]

[0032] In the formula middle, for The rate of change of interference in the signal at any given time. for The instantaneous amplitude of the signal at a given moment. for The instantaneous amplitude of the signal at a given moment. For the preset sampling period, At the speed of light, The communication carrier frequency of the repeater (obtained from the network configuration parameters pre-stored in the repeater). The scene characteristic speed (the relative speed between the user and the repeater). It is the reciprocal of the Doppler frequency shift.

[0033] For the formula It should be noted that the calculation of each time step is performed using the Hilbert transform. The instantaneous amplitude refers to the signal's instantaneous amplitude at which the signal... The real-time intensity value at any given moment can intuitively reflect the dynamic changes in signal strength.

[0034] For the formula It should be noted that the characteristic speed varies depending on the scenario. For example, when a user is on a high-speed train, the speed limit is 300 km / h. The corresponding scene characteristic speed is For example, a user drives a car in the city, and the city speed limit is 50 The corresponding scene characteristic speed is .

[0035] For formula It should be noted that the Doppler shift represents the maximum change rate in the environment theory, that is, the limit value determined by physical laws; represents The instantaneous change rate of signal strength at the moment, when the interference suddenly occurs (such as a vehicle passing quickly), the value will increase sharply; and the real attenuation (building shielding) usually shows a gentle change. By dividing by , that is, comparing the actual observation value with the environmental theoretical limit, the purpose of eliminating scene differences is achieved. Greater than 1 indicates that the interference changes too fast, such as the interference caused by the high-speed driving of a high-speed rail; Less than 1 indicates that the interference changes slowly, which belongs to the normal attenuation phenomenon of the signal, Equal to 1 indicates that the interference change rate has reached the maximum change rate in the environment theory.

[0036] It should be noted that by formula The present application makes the interference intensity in different scenes have a unified measurement standard, provides a physical meaning clear basic feature for subsequent interference identification, and effectively solves the misjudgment problem caused by scene differences in traditional methods.

[0037] It can be understood that obtaining the smoothing factor includes: calculating the Doppler shift, taking the reciprocal of the Doppler shift as the channel coherence time; and performing negative correlation mapping on the ratio of the preset sampling period to the channel coherence time through an exponential function to obtain the smoothing factor.

[0038] Exemplarily, the calculation formula of the smoothing factor is as follows:

[0039]

[0040] In formula , is the smoothing factor in the current communication scene, is the preset sampling period, is the channel coherence time.

[0041] For formula It should be noted that the channel coherence time is the reciprocal of the Doppler shift, and the reciprocal of the Doppler shift is , which represents the maximum time window in which the signal characteristics remain stable.

[0042] It can be understood that the relative mutation intensity of the target signal is obtained by calculating the interference change rate of the target signal, obtaining a smoothing factor, calculating a historical reference of the interference change rate based on the smoothing factor using an exponentially weighted moving average algorithm, and taking the ratio of the interference change rate and the historical reference as the relative mutation intensity.

[0043] It should be noted that the EWMA (Exponentially Weighted Moving Average) is a commonly used time series smoothing technique, which is particularly suitable for giving different weights to past data. It can better capture the latest trend of data.

[0044] Exemplarily, the calculation formula of the historical reference is as follows:

[0045]

[0046] In the formula , is the historical reference of the interference change rate at the moment, is the smoothing factor under the current communication scenario, is the historical reference of the interference change rate at the moment, is the interference change rate of the signal at the moment.

[0047] For the formula , it should be noted that = , is constructed based on the physical law that the correlation of the wireless channel naturally decays over time, and quantifies the correlation strength between the channel state after a period of time and the history, which is dynamically determined by the deployment environment. When tends to 1 ( tends to 0, that is, the collection time interval is much smaller than the time for which the channel remains stable), the environment changes slowly, and at this time the historical reference of the interference change rate at the moment depends on the historical data to a large extent, and the current data is reflected slowly, and the curve is smooth); when tends to 0, ( tends to infinity, and the collection time interval is much larger than the time for which the channel remains stable), the environment changes dramatically, and at this time the dependence on historical data is small, and the recent data is reflected sensitively, and the curve fluctuates. This construction enables the algorithm to have an environment-adaptive memory capability: The greater the value, the higher the credibility of the historical data, and the algorithm pays more attention to filtering short-term fluctuations; ​​​The smaller the value, the stronger the environmental dynamics, and the algorithm needs to respond quickly to the latest changes.

[0048] For the formula , it needs to be noted that the size of the reference value directly reflects the typical fluctuation intensity of the current scene.

[0049] Exemplarily, the calculation formula of the relative mutation intensity is as follows:

[0050]

[0051] In the formula , the relative mutation intensity of the signal at the moment is , the interference change rate of the signal at the moment is , and the historical reference of the interference change rate at the moment is .

[0052] For the formula , it needs to be noted that the relative mutation intensity is constructed by the ratio of the current interference change rate and the environmental historical reference value . This design is based on the physical characteristics of signal fluctuation: the signal change amplitude caused by background noise is always within the typical fluctuation range of the current environment, while real interference will cause the signal change amplitude to significantly exceed the typical fluctuation range of the environment. When tends to 0, it means that the current signal change rate is much lower than the environmental typical fluctuation level , and the signal is in a highly stable state; when tends to 1, it represents that the current signal change rate is basically consistent with the environmental typical fluctuation level, indicating that the signal is in the normal fluctuation range under the influence of background noise. This state conforms to the natural propagation characteristics of electromagnetic waves in the current environment and belongs to the harmless fluctuation category; when is greater than 1, it means that the current change exceeds the environmental normal range, which can be determined as a real interference event. The present application converts the absolute change amount into an environmental relative index, enabling the interference identification to have environmental adaptive ability, without the need to set different thresholds for different scenes, so as to accurately distinguish between transient interference and signal attenuation under various deployment conditions, solving the misjudgment problem caused by environmental differences in traditional methods.

[0053] Exemplarily, the calculation formula of the step scaling coefficient is as follows:

[0054]

[0055] In the formula , the step scaling coefficient For the step size scaling coefficient of the time signal, For the noise influence coefficient of the time, For the relative mutation intensity of the time signal.

[0056] For the formula , it needs to be supplemented that the step size scaling coefficient The formula for calculating represents the significant degree of the current signal fluctuation relative to the environmental norm, which is essentially to normalize the absolute change to the relative intensity under the environment, so that the interference of different scenes is comparable; and quantifies the threat degree of the current noise to stability, when increases, the formula makes initially approximate linear growth to accelerate response, but as continues to increase, has inherent stability guaranteeing characteristics, its value is always less than , so that the algorithm accelerates convergence while never breaking the stability boundary, ensuring that it can speed up sufficiently in the presence of severe interference, and automatically compressing the adjustment range when the noise is severe, solving the dilemma between speed and stability of the fixed step size scheme.

[0057] For the formula , it needs to be supplemented that the step size scaling coefficient is negatively correlated with , The smaller, the lower the degree of influence of the current sampling time by the noise in the channel, and the lower the threat degree, at which time the step size scaling coefficient can be larger, The larger, the higher the degree of influence of the current sampling time by the noise in the channel, and the noise may seriously interfere with the signal at the current sampling time, at which time the step size scaling coefficient can be smaller to more carefully achieve interference suppression and pure signal generation.

[0058] It can be understood that the reference step size for obtaining the target signal includes: calculating the average signal power of the subsequence; and taking the ratio of 2 to the average signal power as the reference step size.

[0059] Exemplarily, the calculation formula of the adjustment step size is as follows:

[0060]

[0061] In the formula , is the adjustment step size of the time signal, is the noise influence coefficient of the time, is the step size scaling coefficient of the time signal, reference step size of the time signal, for step size scaling factor of the time signal.

[0062] For the formula , it needs to be noted that, , is the average signal power of the subsequence. The reference step size is the maximum safety value allowed by the current signal strength, and the scaling factor indicates the step size requirement of the interference response, and the multiplication of the two makes the step size not only increase with the increase of the interference, but also always be constrained by the noise, ensuring that it is both sufficient to speed up and never exceeds the boundary in the key response window, achieving the balance between speed and stability.

[0063] Step S2: output signal monitoring result according to error sequence.

[0064] It can be understood that the output signal monitoring result according to the error sequence includes: counting the number of consecutive errors greater than the first preset threshold in the error sequence; in response to the number of consecutive errors being greater than the second preset threshold, taking the real attenuation of the wireless communication signal as the monitoring result; in response to the number of consecutive errors being not greater than the second preset threshold, taking the instantaneous interference of the wireless communication signal as the monitoring result.

[0065] It needs to be noted that the first preset threshold and the second preset threshold are set according to the scene.

[0066] It needs to be noted that the signal at the current time in the signal time sequence corresponds to the error signal at the next time.

[0067] It needs to be noted that the number of consecutive errors not greater than the second preset threshold indicates that the error mutates for a short time and then stabilizes, at this time, there is instantaneous interference, and the repeater keeps the signal path unblocked, ensuring the continuity of communication; the number of consecutive errors greater than the second preset threshold indicates that the error persists, and at this time, there is real attenuation, and the repeater safely releases network resources. Compared with the traditional repeater, which misjudges the instantaneous interference as real attenuation and thus stops forwarding, resulting in problems such as video lag, connection interruption and other problems perceived by users, the present application reduces the misjudgment probability of the repeater through dynamic step size, thereby improving the user experience.

[0068] It needs to be noted that the instantaneous interference is, for example, multi-base station co-frequency interference, mobile object shielding, etc., and the real attenuation is, for example, path loss, building obstruction, etc.

[0069] It should be noted that the repeater applies the LMS algorithm to the filter module to enable the filter module to output a pure signal after interference cancellation, and the application process can be summarized as follows: receiving an input signal at the current time, calculating an output signal according to the current weight of the filter module, calculating an error signal of the output signal and the expected signal, updating the current weight according to the error signal, the input signal and the step, receiving the signal at the next time, and iterating the above process of obtaining the output signal according to the updated weight.

[0070] The application further provides a communication signal monitoring system of an intelligent repeater. The system comprises a processor and a memory, and the memory stores computer program instructions. When the computer program instructions are executed by the processor, the communication signal monitoring method of the intelligent repeater according to the first aspect of the application is implemented. The system further comprises a communication bus and a communication interface and other components familiar to those skilled in the art, and the settings and functions of the components are known in the art, so they will not be described here.

[0071] It should be noted that the above describes the preferred embodiments of the embodiments of the application with reference to the drawings, and does not limit the scope of the embodiments of the application. For those skilled in the art, without departing from the concept of the application, a number of modifications and improvements can be made, which are all within the scope of the application. Therefore, the protection scope of the patent of the application should be subject to the appended claims.

Claims

1. A method for monitoring communication signals of an intelligent repeater, characterized in that, The method comprises the following steps: Collecting a signal time sequence of a wireless communication signal in a preset sampling period, taking any signal in the signal time sequence as a target signal, calculating an adjustment step of the target signal, updating the weight of a filter module in a repeater according to the adjustment step, and outputting an error signal according to the updated filter module to construct an error sequence, wherein one signal in the signal time sequence corresponds to one error signal; Outputting a monitoring result according to the error sequence; The calculation method of the adjustment step is as follows: Generating a window in the signal time sequence with the target signal as the right boundary, taking all signals in the window as a sub-sequence, calculating a noise influence coefficient of the sub-sequence, calculating a relative mutation intensity of the target signal, taking the sum of the reciprocal of the relative mutation intensity and the noise influence coefficient as the reciprocal of a step scaling coefficient, obtaining a reference step of the target signal, and taking the product of the reference step and the step scaling coefficient as the adjustment step.

2. The communication signal monitoring method of an intelligent repeater according to claim 1, wherein, The calculation of the noise influence coefficient of the sub-sequence in the window comprises: Calculating the average noise power and the average signal power of the sub-sequence; Taking the ratio of the average noise power and the average signal power as the noise influence coefficient.

3. The method of claim 1, wherein the method further comprises: The calculation of the relative mutation intensity of the target signal comprises: Calculating the interference change rate of the target signal; Obtaining a smoothing factor, calculating a historical reference of the interference change rate based on the smoothing factor by using an exponential weighted moving average algorithm; Taking the ratio of the interference change rate and the historical reference as the relative mutation intensity.

4. The communication signal monitoring method of an intelligent repeater according to claim 3, wherein, The calculation of the interference change rate of the target signal comprises: Calculating the Doppler shift; Taking the signal at a previous sampling time adjacent to the sampling time of the target signal as a reference signal, calculating the instantaneous amplitude of the target signal and the instantaneous amplitude of the reference signal, calculating the absolute difference value of the instantaneous amplitude of the target signal and the instantaneous amplitude of the reference signal, taking the ratio of the absolute difference value and the preset sampling period as the instantaneous change rate, and taking the ratio of the instantaneous change rate and the Doppler shift as the interference change rate of the target signal.

5. The method of claim 3, wherein the method further comprises: The calculation of the smoothing factor comprises: Calculating the Doppler shift, and taking the reciprocal of the Doppler shift as the channel coherence time; Mapping the ratio of the preset sampling period and the channel coherence time to a negative correlation by using an exponential function to obtain the smoothing factor.

6. The method of claim 1, wherein the method further comprises: The calculation of the reference step of the target signal comprises: Calculating the average signal power of the sub-sequence; Taking the ratio of 2 and the average signal power as the reference step.

7. The method of claim 1, wherein the method further comprises: The output of the monitoring result according to the error sequence comprises: Counting the number of consecutive errors greater than a first preset threshold in the error sequence; In response to the number of consecutive errors being greater than a second preset threshold, taking the existence of real attenuation of the wireless communication signal as the monitoring result; In response to the number of consecutive errors being not greater than the second preset threshold, taking the existence of instantaneous interference of the wireless communication signal as the monitoring result.

8. A communication signal monitoring system for a smart repeater, characterized by, The device comprises: A processor and a memory, the memory storing computer program instructions, when the computer program instructions are executed by the processor, a communication signal monitoring method of an intelligent repeater according to any one of claims 1-7 is realized.

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