阅读说明：本技术 一种误码率检测方法及系统 (Method and system for detecting error rate ) 是由 韩宁 宋祥君 马飒飒 杨毅 樊浩 方东兴 郭晓冉 高润冬 康科 孙晶 于 2020-03-16 设计创作，主要内容包括：本发明涉及一种误码率检测方法及系统,所述方法包括：通过对待测系统进行建模,获得误码率检测模型；根据所述误码率检测模型和虚拟伪随机序列码进行计算,得到待测系统的理论误码率；根据所述误码率检测模型和实测伪随机序列码进行计算,得到待测系统的实测误码率；根据所述理论误码率和所述实测误码率,得到待测系统的真实误码率。本发明将理论的简洁性与实测的真实可靠性相结合,具有高可信度、高时效性以及误码率测试准确度高的优点。(The invention relates to a method and a system for detecting a bit error rate, wherein the method comprises the following steps: modeling a system to be tested to obtain an error rate detection model; calculating according to the error rate detection model and the virtual pseudorandom sequence code to obtain the theoretical error rate of the system to be detected; calculating according to the error rate detection model and the actually measured pseudorandom sequence code to obtain the actually measured error rate of the system to be measured; and obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate. The invention combines the theoretical simplicity and the actual reliability of actual measurement, and has the advantages of high reliability, high timeliness and high error rate test accuracy.)

1. A method for bit error rate detection, comprising:

modeling a system to be tested to obtain an error rate detection model;

calculating according to the error rate detection model and the virtual pseudorandom sequence code to obtain the theoretical error rate of the system to be detected;

calculating according to the error rate detection model and the actually measured pseudorandom sequence code to obtain the actually measured error rate of the system to be measured;

and obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate.

2. The method according to claim 1, wherein said obtaining the theoretical bit error rate of the system under test comprises:

acquiring the virtual pseudo-random sequence code by using a software simulation method, wherein the virtual pseudo-random sequence code is used as a theoretical pseudo-code input signal;

inputting the theoretical pseudo code input signal into a system to be tested to obtain a theoretical pseudo code output signal;

obtaining a theoretical noise signal according to the theoretical pseudo code output signal and the theoretical pseudo code input signal;

and obtaining the theoretical bit error rate according to the theoretical noise signal and the theoretical pseudo code output signal.

3. The method according to claim 1, wherein said obtaining the measured bit error rate of the system under test comprises:

obtaining the actual measurement pseudorandom sequence code by utilizing a pseudorandom code sequence generator, wherein the actual measurement pseudorandom sequence code is used as an actual measurement pseudorandom code input signal;

inputting the actual measurement pseudo code input signal into a system to be tested to obtain an actual measurement pseudo code output signal;

obtaining an actual measurement noise signal according to the actual measurement pseudo code output signal and the actual measurement pseudo code input signal;

and obtaining the actually measured error rate according to the actually measured noise signal and the actually measured pseudo code output signal.

4. The method according to claim 1, wherein said obtaining the true bit error rate of the system under test comprises:

obtaining a weight coefficient of the theoretical bit error rate and a weight coefficient of the actually measured bit error rate through a test data experience value assignment method;

obtaining a theoretical error rate component according to the theoretical error rate and the weight coefficient of the theoretical error rate;

obtaining an actually measured error rate component according to the actually measured error rate and the weight coefficient of the actually measured error rate;

and obtaining the real bit error rate according to the theoretical bit error rate component and the measured bit error rate component.

5. The bit error rate detection method according to claim 1, wherein the actual bit error rate of the system under test is obtained by the following specific formula:

P＝AP_s′+BP_r′；

in the formula: p is the true error rate, A is the weight coefficient of the theoretical error rate, P_s' is theoretical error rate, B is weight coefficient of measured error rate, P_r' is the measured error rate.

6. The method according to claim 2, wherein the theoretical bit error rate is obtained by the following formula:

in the formula: p_s' theoretical bit error rate, N_in' is a theoretical noise signal, S_out' is the theoretical pseudo-code output signal.

7. A bit error rate detection system, comprising:

the modeling module is used for modeling a system to be tested to obtain an error rate detection model;

the theoretical error rate calculation module is used for calculating according to the error rate detection model and the virtual pseudo-random sequence code to obtain the theoretical error rate of the system to be detected;

the actual measurement error rate calculation module is used for calculating according to the error rate detection model and the actual measurement pseudo-random sequence code to obtain the actual measurement error rate of the system to be measured;

and the real error rate calculation module is used for obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate.

8. The ber detection system of claim 7, wherein the theoretical ber calculation module comprises:

the theoretical pseudo code input signal determining unit is used for obtaining the virtual pseudo random sequence code by using a software simulation method, and the virtual pseudo random sequence code is used as a theoretical pseudo code input signal;

the theoretical pseudo code output signal determining unit is used for inputting the theoretical pseudo code input signal into a system to be tested to obtain a theoretical pseudo code output signal;

the theoretical noise signal determining unit is used for obtaining a theoretical noise signal according to the theoretical pseudo code output signal and the theoretical pseudo code input signal;

and the theoretical error rate determining unit is used for obtaining the theoretical error rate according to the theoretical noise signal and the theoretical pseudo code output signal.

9. A bit error rate detection system according to claim 7, wherein said measured bit error rate calculation module comprises:

the device comprises an actual measurement pseudo code input signal determining unit, a pseudo random code sequence generator and a pseudo random code sequence generator, wherein the actual measurement pseudo random sequence code is used as an actual measurement pseudo code input signal;

the actual measurement pseudo code output signal determining unit is used for inputting the actual measurement pseudo code input signal into a system to be tested to obtain an actual measurement pseudo code output signal;

the actual measurement noise signal determining unit is used for obtaining an actual measurement noise signal according to the actual measurement pseudo code output signal and the actual measurement pseudo code input signal;

and the actually measured error rate determining unit is used for obtaining the actually measured error rate according to the actually measured noise signal and the actually measured pseudo code output signal.

10. The ber detection system of claim 7, wherein the true ber calculation module comprises:

the weight determining unit is used for obtaining a weight coefficient of the theoretical bit error rate and a weight coefficient of the actually measured bit error rate through a test data experience value assignment method;

a theoretical error rate component determining unit, configured to obtain a theoretical error rate component according to the theoretical error rate and a weight coefficient of the theoretical error rate;

the actually measured error rate component determining unit is used for obtaining an actually measured error rate component according to the actually measured error rate and the weight coefficient of the actually measured error rate;

and the real bit error rate determining unit is used for obtaining the real bit error rate according to the theoretical bit error rate component and the measured bit error rate component.

Technical Field

The present invention relates to the field of error rate detection, and in particular, to an error rate detection method and system.

Background

The existing error rate detection is only carried out in a theoretical model simulation mode, the error rate detection accuracy of an actual system is evaluated based on data simulated by a theoretical model, and the problems that the detection result is greatly influenced by subjective factors and the detection accuracy is not high exist.

Disclosure of Invention

The present invention provides a method and a system for detecting a bit error rate, so as to solve the above problems.

In order to achieve the purpose, the invention provides the following scheme:

a method of bit error rate detection, comprising:

modeling a system to be tested to obtain an error rate detection model;

calculating according to the error rate detection model and the virtual pseudorandom sequence code to obtain the theoretical error rate of the system to be detected;

calculating according to the error rate detection model and the actually measured pseudorandom sequence code to obtain the actually measured error rate of the system to be measured;

and obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate.

Preferably, the obtaining the theoretical bit error rate of the system under test includes:

acquiring the virtual pseudo-random sequence code by using a software simulation method, wherein the virtual pseudo-random sequence code is used as a theoretical pseudo-code input signal;

inputting the theoretical pseudo code input signal into a system to be tested to obtain a theoretical pseudo code output signal;

obtaining a theoretical noise signal according to the theoretical pseudo code output signal and the theoretical pseudo code input signal;

and obtaining the theoretical bit error rate according to the theoretical noise signal and the theoretical pseudo code output signal.

Preferably, the obtaining the measured bit error rate of the system under test includes:

obtaining the actual measurement pseudorandom sequence code by utilizing a pseudorandom code sequence generator, wherein the actual measurement pseudorandom sequence code is used as an actual measurement pseudorandom code input signal;

inputting the actual measurement pseudo code input signal into a system to be tested to obtain an actual measurement pseudo code output signal;

obtaining an actual measurement noise signal according to the actual measurement pseudo code output signal and the actual measurement pseudo code input signal;

and obtaining the actually measured error rate according to the actually measured noise signal and the actually measured pseudo code output signal.

Preferably, the obtaining the true bit error rate of the system under test includes:

obtaining a weight coefficient of the theoretical bit error rate and a weight coefficient of the actually measured bit error rate through a test data experience value assignment method;

obtaining a theoretical error rate component according to the theoretical error rate and the weight coefficient of the theoretical error rate;

obtaining an actually measured error rate component according to the actually measured error rate and the weight coefficient of the actually measured error rate;

and obtaining the real bit error rate according to the theoretical bit error rate component and the measured bit error rate component.

Preferably, the obtaining of the true error rate of the system to be measured has a specific formula as follows:

P＝AP_s′+BP_r′；

in the formula: p is the true error rate, A is the weight coefficient of the theoretical error rate, P_s' is theoretical error rate, B is weight coefficient of measured error rate, P_r' is the measured error rate.

Preferably, the specific formula for obtaining the theoretical bit error rate is as follows:

in the formula: p_s' theoretical bit error rate, N_in' is a theoretical noise signal, S_out' is the theoretical pseudo-code output signal.

A bit error rate detection system comprising:

the modeling module is used for modeling a system to be tested to obtain an error rate detection model;

the theoretical error rate calculation module is used for calculating according to the error rate detection model and the virtual pseudo-random sequence code to obtain the theoretical error rate of the system to be detected;

the actual measurement error rate calculation module is used for calculating according to the error rate detection model and the actual measurement pseudo-random sequence code to obtain the actual measurement error rate of the system to be measured;

and the real error rate calculation module is used for obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate.

Preferably, the theoretical bit error rate calculation module includes:

the theoretical pseudo code input signal determining unit is used for obtaining the virtual pseudo random sequence code by using a software simulation method, and the virtual pseudo random sequence code is used as a theoretical pseudo code input signal;

the theoretical pseudo code output signal determining unit is used for inputting the theoretical pseudo code input signal into a system to be tested to obtain a theoretical pseudo code output signal;

the theoretical noise signal determining unit is used for obtaining a theoretical noise signal according to the theoretical pseudo code output signal and the theoretical pseudo code input signal;

and the theoretical error rate determining unit is used for obtaining the theoretical error rate according to the theoretical noise signal and the theoretical pseudo code output signal.

Preferably, the measured bit error rate calculation module includes:

the device comprises an actual measurement pseudo code input signal determining unit, a pseudo random code sequence generator and a pseudo random code sequence generator, wherein the actual measurement pseudo random sequence code is used as an actual measurement pseudo code input signal;

the actual measurement pseudo code output signal determining unit is used for inputting the actual measurement pseudo code input signal into a system to be tested to obtain an actual measurement pseudo code output signal;

the actual measurement noise signal determining unit is used for obtaining an actual measurement noise signal according to the actual measurement pseudo code output signal and the actual measurement pseudo code input signal;

and the actually measured error rate determining unit is used for obtaining the actually measured error rate according to the actually measured noise signal and the actually measured pseudo code output signal.

Preferably, the true bit error rate calculation module includes:

the weight determining unit is used for obtaining a weight coefficient of the theoretical bit error rate and a weight coefficient of the actually measured bit error rate through a test data experience value assignment method;

a theoretical error rate component determining unit, configured to obtain a theoretical error rate component according to the theoretical error rate and a weight coefficient of the theoretical error rate;

the actually measured error rate component determining unit is used for obtaining an actually measured error rate component according to the actually measured error rate and the weight coefficient of the actually measured error rate;

and the real bit error rate determining unit is used for obtaining the real bit error rate according to the theoretical bit error rate component and the measured bit error rate component.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects:

modeling a system to be tested to obtain an error rate detection model; calculating according to the error rate detection model and the virtual pseudorandom sequence code to obtain the theoretical error rate of the system to be detected; calculating according to the error rate detection model and the actually measured pseudorandom sequence code to obtain the actually measured error rate of the system to be measured; and obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate. The invention combines the theoretical simplicity and the actual reliability of actual measurement, and has the advantages of high reliability, high timeliness and high error rate test accuracy.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.

Fig. 1 is a flow chart of the bit error rate detection method of the present invention.

Detailed Description

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

The invention aims to provide a bit error rate detection method and system with high reliability, high timeliness and high accuracy.

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.

As shown in fig. 1, the bit error rate detection method of the present invention includes:

and modeling the system to be tested to obtain an error rate detection model.

And calculating according to the error rate detection model and the virtual pseudorandom sequence code to obtain the theoretical error rate of the system to be detected.

And calculating according to the error rate detection model and the actually measured pseudorandom sequence code to obtain the actually measured error rate of the system to be measured.

And obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate.

Specifically, the formula of the bit error rate detection model is as follows:

S_out＝S_in+N_in；

in the formula: s_outOutputting signals, S, for pseudo-codes_inFor pseudo-code input signals, N_inIs a noise signal.

As an optional implementation manner, the obtaining of the theoretical bit error rate of the system under test according to the present invention includes:

and acquiring the virtual pseudo-random sequence code by using a software simulation method, wherein the virtual pseudo-random sequence code is used as a theoretical pseudo-code input signal.

And inputting the theoretical pseudo code input signal into a system to be tested to obtain a theoretical pseudo code output signal.

And subtracting the theoretical pseudo code output signal and the theoretical pseudo code input signal to obtain a theoretical noise signal.

And obtaining the theoretical bit error rate according to the theoretical noise signal and the theoretical pseudo code output signal.

The concrete formula is as follows:

in the formula: p_s' theoretical bit error rate, N_in' is a theoretical noise signal, S_out' is the theoretical pseudo-code output signal.

As an optional implementation manner, the obtaining of the measured bit error rate of the system under test according to the present invention includes:

and acquiring the actually measured pseudo-random sequence code by using a pseudo-random code sequence generator, wherein the actually measured pseudo-random sequence code is used as an actually measured pseudo-code input signal.

Inputting the actual measurement pseudo code input signal into a system to be tested to obtain an actual measurement pseudo code output signal;

and subtracting the actual measurement pseudo code output signal and the actual measurement pseudo code input signal to obtain an actual measurement noise signal.

And obtaining the actually measured error rate according to the actually measured noise signal and the actually measured pseudo code output signal.

The concrete formula is as follows:

in the formula: p_r' measured bit error rate, N_in"is the measured noise signal, S_out"outputs a signal for the measured pseudo code.

As an optional implementation manner, the obtaining of the true bit error rate of the system under test according to the present invention includes:

and obtaining the weight coefficient of the theoretical bit error rate and the weight coefficient of the actually measured bit error rate by a test data experience value assignment method.

And multiplying the theoretical bit error rate by the weight coefficient of the theoretical bit error rate to obtain a theoretical bit error rate component.

And multiplying the weight coefficient of the actually measured error rate and the actually measured error rate to obtain an actually measured error rate component.

And obtaining the real bit error rate according to the theoretical bit error rate component and the measured bit error rate component.

The concrete formula is as follows:

P＝AP_s′+BP_r′；

in the formula: p is the true error rate, A is the weight coefficient of the theoretical error rate, P_s' is theoretical error rate, B is weight coefficient of measured error rate, P_r' is the measured error rate.

In this embodiment, the weight coefficient of the theoretical bit error rate is 0.6, and the weight coefficient of the measured bit error rate is 0.4.

The invention also provides a system for detecting the bit error rate, which comprises:

and the modeling module is used for modeling the system to be tested to obtain an error rate detection model.

And the theoretical error rate calculation module is used for calculating according to the error rate detection model and the virtual pseudo-random sequence code to obtain the theoretical error rate of the system to be detected.

And the actual measurement error rate calculation module is used for calculating according to the error rate detection model and the actual measurement pseudo-random sequence code to obtain the actual measurement error rate of the system to be measured.

And the real error rate calculation module is used for obtaining the real error rate of the system to be tested according to the theoretical error rate and the actual measurement error rate.

As an optional implementation manner, the theoretical bit error rate calculation module of the present invention includes:

and the theoretical pseudo code input signal determining unit is used for obtaining the virtual pseudo random sequence code by using a software simulation method, and the virtual pseudo random sequence code is used as a theoretical pseudo code input signal.

And the theoretical pseudo code output signal determining unit is used for inputting the theoretical pseudo code input signal into a system to be tested to obtain a theoretical pseudo code output signal.

And the theoretical noise signal determining unit is used for subtracting the theoretical pseudo code output signal and the theoretical pseudo code input signal to obtain a theoretical noise signal.

And the theoretical error rate determining unit is used for performing division on the theoretical noise signal and the theoretical pseudo code output signal to obtain the theoretical error rate.

As an optional implementation manner, the measured bit error rate calculation module of the present invention includes:

and the actual measurement pseudo code input signal determining unit is used for obtaining the actual measurement pseudo random sequence code by utilizing a pseudo random code sequence generator, and the actual measurement pseudo random sequence code is used as an actual measurement pseudo code input signal.

And the actual measurement pseudo code output signal determining unit is used for inputting the actual measurement pseudo code input signal into a system to be tested to obtain an actual measurement pseudo code output signal.

And the actually measured noise signal determining unit is used for subtracting the actually measured pseudo code output signal and the actually measured pseudo code input signal to obtain an actually measured noise signal.

And the actually measured error rate determining unit is used for performing division on the actually measured noise signal and the actually measured pseudo code output signal to obtain the actually measured error rate.

As an optional implementation manner, the true bit error rate calculation module of the present invention includes:

and the weight determining unit is used for obtaining the weight coefficient of the theoretical bit error rate and the weight coefficient of the actually measured bit error rate through a test data experience value assignment method.

And the theoretical error rate component determining unit is used for multiplying the theoretical error rate and the weight coefficient of the theoretical error rate to obtain the theoretical error rate component.

And the actually measured error rate component determining unit is used for multiplying the actually measured error rate and the weight coefficient of the actually measured error rate to obtain the actually measured error rate component.

And the real bit error rate determining unit is used for adding the theoretical bit error rate component and the measured bit error rate component to obtain the real bit error rate.

The method combines the simplicity of a theoretical simulation model and the real reliability of measured data, and obtains a bit error rate test result which is closer to that of an actual system to be tested in a weighted average mode. The method has the advantages of high reliability, high timeliness and high error rate test accuracy.

The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.

The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.