A judgment method, terminal and data processing method

Abstract

The present invention discloses a judgment method, a terminal and a data processing method. The method is based on the judgment of constellation combination to reduce the judgment of bit error rate, and comprises the following steps: step one: after decoding the received data, normalization processing is performed to obtain constellation data of each frame of data; step two: judging the obtained constellation data, obtaining constellation data corresponding to the same judgment result, and constructing a constellation data matrix; step three: taking each column of the constructed constellation data matrix as a unit to perform unit mean, and forming a unit mean array; step four: judging the unit mean data to obtain the final judgment bit, and the judgment bit is used as the judgment result for subsequent processing. The present invention is based on the judgment of constellation combination, and the constellation sequence of the combined M frames is 1 / M times the noise power of the new sequence of a single frame, which effectively reduces the judgment error and the error-free rate of the judgment bit, so as to obtain the correct bit, which is beneficial to the later mapping analysis and coding analysis.

Description

Technical Field

[0001] The present invention belongs to the field of data processing, and in particular relates to a judgment method, a terminal and a data processing method. Background Art

[0002] In signal analysis, the signal-to-noise ratio of the received data may not meet the analysis conditions of error-free code. Error-free code brings great difficulties to coding analysis and mapping analysis. The constellation diagram and demodulated bit diagram are as follows: Figure 1 , 2 As shown. The constellation data is obtained through demodulation synchronization and normalization processing, and the bitmap is the hard decision data of the corresponding constellation data. By analyzing the frame structure with errors and the constellation data, it is found that the data filling frame data is the same; the corresponding constellation data with the same filling can be jointly judged to finally ensure that there is no error in the judgment. It is under this premise that the solution of this application is proposed. Summary of the invention

[0003] The object of the present invention is to provide a decision method, which can effectively reduce the error-free rate of decision bits to obtain correct bits, which is beneficial to subsequent processing.

[0004] To achieve the purpose of the present invention, a decision method is provided for reducing the bit error rate based on the decision of the constellation combination, comprising the following steps:

[0005] Step 1: Decode the received data and perform normalization processing to obtain the constellation diagram data of each frame of data;

[0006] Step 2: Judge the obtained constellation data, obtain the constellation data corresponding to the same judgment result, and construct a constellation data matrix;

[0007] Step 3: Take each column of the constructed constellation data matrix as a unit to perform unit mean to form a unit mean array;

[0008] Step 4: Determine the unit mean data to obtain a final decision bit, which is used as a decision result for subsequent processing.

[0009] In some implementations, the step 2 of making a decision on the acquired constellation data is to use the aligned constellation data to calculate the average and then make a hard decision, which has the advantage that the averaging operation reduces the noise of the constellation data and effectively reduces the bit error rate of the hard decision.

[0010] A second object of the present invention is to provide a decision terminal, the terminal at least comprising:

[0011] A receiving module, used for receiving data;

[0012] The processing module is interconnected with the receiving module and performs the following processing on the data received by the receiving module:

[0013] Step 1: Decode the received data and perform normalization processing to obtain the constellation diagram data of each frame of data;

[0014] Step 2: Judge the obtained constellation data, obtain the constellation data corresponding to the same judgment result, and construct a constellation data matrix;

[0015] Step 3: Take each column of the constructed constellation data matrix as a unit to perform unit mean to form a unit mean array;

[0016] Step 4: Determine the unit mean data to obtain a final decision bit, which is used as a decision result for subsequent processing.

[0017] The third object of the present invention is to provide a data processing method, which first uses the decision method provided by the present invention to obtain decision bits, and then encodes or decodes the decision bits.

[0018] The present invention is based on the decision of constellation union. The constellation sequence of the united M frames is 1 / M times of the noise power of the new sequence of a single frame, which effectively reduces the decision bit error and the error-free rate of the decision bit to obtain the correct bit, which is beneficial to the later mapping analysis and coding analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings herein are incorporated into and constitute a part of the specification, showing embodiments consistent with the present invention, and together with the specification, are used to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0020] Figure 1-2 The constellation diagram and the demodulated bit diagram recorded in the present invention;

[0021] Figure 3 The present invention is a flowchart of the decision method provided by the present invention. DETAILED DESCRIPTION

[0022] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the invention will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0023] Definitions of technical terms involved in this technical solution:

[0024] 1. Constellation map

[0025] The distribution diagram of the endpoints of the signal vector is called a constellation diagram. The distribution diagram of the endpoints of the signal vector is called a constellation diagram. The digital signal is represented on the complex plane to intuitively represent the signal and the relationship between the signals. This diagram is called a constellation diagram. The constellation diagram can be regarded as a "two-dimensional eye diagram" array of digital signals, and the position of the symbol in the diagram has reasonable restrictions or decision boundaries. The closer the receiving points are in the diagram, the higher the signal quality.

[0026] 2. Constellation Alliance

[0027] It refers to combining the constellation diagrams corresponding to the frame data having the same codeword signal contained in the frame constituting the target data.

[0028] 3. The verdict is the same

[0029] Including the judgment results are exactly the same, or eighty percent the same; for example, the judgment results 01110 and 11110 also belong to the same judgment results described in this solution.

[0030] 4. Alignment hard decision

[0031] It refers to adding the same data in the constellation diagram corresponding to each frame of data (adding real numbers) to align the data, and then making a hard decision; hard decision refers to the process of outputting 0 and 1 after judging the data according to the judgment threshold.

[0032] This scheme is based on the fact that the constellation sequence of the joint M frames is 1 / M times the noise power of the new sequence of a single frame, so it effectively reduces the decision error, which is beneficial to the later mapping analysis and coding analysis. By selecting a sufficiently large number of M frames with the same constellation data, an error-free decision constellation (decision bit) can be finally obtained. The principle that the constellation sequence of the joint M frames can effectively reduce the decision error is as follows:

[0033] The same constellation sequence of the combined M-frame transmission is A1A2…A n , with a length of n; the normalization process limits the data to a certain range, eliminating the adverse effects caused by singular data. The value range of the normalized constellation A is generally [-1,1]; the received constellation sequence after passing through the Gaussian white noise channel is B1B2…B n ;in, In the formula The mean is 0 and the variance is σ 2 The Gaussian distribution of random variables and the noise of each constellation between each frame is independent of each other, and its mathematical symbol expression is N~(0,σ 2 )

[0034] Arrange the constellation sequence received by M frames into a matrix form

[0035]

[0036] Note: The superscript represents the frame number, and the subscript represents the number of the constellation sequence within a frame.

[0037] First, the columns of the received matrix are averaged to obtain a one-dimensional joint constellation mean sequence C1C2…C n ,in:

[0038]

[0039] Then simplify it to get:

[0040]

[0041] Let the random variable C1=A1+Z,C2=A2+Z…C n =A n +Z.

[0042] According to the conclusion of probability theory, the linear combination of independent Gaussian random variables also conforms to the Gaussian distribution, and its mean Its variance Z Obey Gaussian distribution.

[0043] Therefore, the constellation sequence of the joint M frames is 1 / M times the noise power of the new sequence of a single frame, which effectively reduces the decision error and is beneficial to the later mapping analysis and coding analysis. By selecting a sufficiently large M frame with the same constellation data, a decision constellation without error can be finally obtained.

[0044] To this end, the present invention provides a decision method for reducing the bit error rate based on constellation joint decision, the method comprising the following steps:

[0045] Step 1: Decode the received data and then perform synchronous demodulation, which includes carrier synchronization, timing synchronization and frame synchronization. The demodulated data is normalized to obtain the constellation point data of each frame of data for constructing the constellation diagram corresponding to each frame of data.

[0046] Step 2: Make a judgement on the obtained constellation data, obtain the constellation data corresponding to the same judgement result, and construct a constellation data matrix; in this step, the constellation data can be judged by observation method, by observing the constellation corresponding to each frame of data; or it can be judged by alignment hard decision method; the constellation data matrix includes row items and column items, each row represents a constellation, and the constellation point data of a constellation constitutes a row; the number of constellation point data determines the number of columns of the constellation data array.

[0047] Step 3: Take each column of the constructed constellation data matrix as a unit to perform unit mean to form a unit mean array; the unit mean in this step is obtained by adding the values ​​of each column in the constellation data matrix and dividing by the number of values ​​in the column. Each column is subjected to unit mean processing to obtain a mean, which constitutes a unit mean array.

[0048] Step 4: Judge the mean in the unit mean array to obtain the final decision bit, which is used as the decision result for subsequent processing; the decision in this step is to set a threshold value, use the threshold and the mean value to make a decision, set the decision condition, and when the mean value meets the decision condition, it is output as the decision bit. The decision condition is set according to the situation, which can be greater than or equal to the threshold value, or less than or equal to the threshold value.

[0049] The decision bit in the present disclosure is the final bit.

[0050] The relationship between noise power and bit error rate is described by a standard mathematical relationship. In short, the greater the noise power, the higher the bit error rate. This judgment method is based on the constellation sequence of the joint M frame, which effectively reduces the judgment bit error and ultimately obtains the correct bit. The correct bit is conducive to subsequent encoding, decoding analysis, and processing.

[0051] The judgment method can be implemented by the following judgment terminals, including:

[0052] A receiving module, used for receiving data;

[0053] The processing module is interconnected with the receiving module, and processes the data received by the receiving module as described in the above steps 1 to 4 to obtain the correct bits of the sending end.

[0054] The present disclosure has been described by the above-mentioned relevant embodiments, but the above-mentioned embodiments are only examples for implementing the present disclosure. It must be pointed out that the disclosed embodiments do not limit the scope of the present disclosure. On the contrary, changes and modifications made without departing from the spirit and scope of the present disclosure are all within the scope of patent protection of the present disclosure.

Claims

1. A judgment method, characterized in that: The method is based on the decision of constellation joint to reduce the bit error rate decision, including the following steps: Step 1: Obtain M frames of data, perform decoding and normalization processing, and obtain constellation data of the M frames of data; the M frames of data transmit the same constellation sequence, and the constellation sequence is A1A2…A n , length is n; Step 2: judging the obtained constellation data, obtaining the judged constellation data, and constructing a constellation data matrix; Step 3: Take each column of the constructed constellation data matrix as a unit to perform unit mean to form a unit mean array; Step 4: Determine the unit mean in the unit mean array to obtain a final decision bit, and the decision bit is used as a decision result for subsequent processing.

2. The judgment method according to claim 1, characterized in that: The step 2 of making a decision on the obtained constellation data is to calculate the average of the aligned constellation data and then make a hard decision.

3. A decision terminal, characterized in that: The terminal comprises at least: A receiving module, used for receiving data; The processing module is interconnected with the receiving module and performs the following processing on the data received by the receiving module: Step 1: Obtain M frames of data, perform decoding and normalization processing, and obtain constellation data of the M frames of data; the M frames of data transmit the same constellation sequence, and the constellation sequence is A1A2…A n , length is n; Step 2: judging the obtained constellation data, obtaining the judged constellation data, and constructing a constellation data matrix; Step 3: Take each column of the constructed constellation data matrix as a unit to perform unit mean to form a unit mean array; Step 4: Determine the unit mean in the unit mean array to obtain a final decision bit, and the decision bit is used as a decision result for subsequent processing.

4. The decision terminal according to claim 3, characterized in that: The processing module uses aligned hard decision to make a decision on the acquired constellation diagram data.

5. A data processing method, characterized in that: The method first uses the decision method described in claims 1-2 to obtain decision bits, and then encodes or decodes the decision bits.

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