Method for removing noise points of constellation diagram
By creating a constellation diagram using counting and binarization steps to remove noise points, the problem of noise interference during signal conversion is solved, the signal processing flow is simplified, and the burden on network and backend resources is reduced.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-04-07
AI Technical Summary
Existing technologies generate a large number of noise points when converting the I and Q components of radio signals into constellation diagrams, leading to difficulties in signal modulation identification and high pressure on network transmission and backend resources.
The method removes noise points from the constellation map by creating a counting constellation map, calculating a threshold, and binarizing the non-zero pixels in the counting constellation map. The specific steps include creating a counting constellation map, calculating the average value of non-zero pixels as a threshold, and binarizing the non-zero pixels in the counting constellation map.
It simplifies the process of removing noise points from constellation diagrams, making it suitable for processing in signal acquisition front-end equipment and reducing the burden on network transmission and back-end resources.
Smart Images
Figure CN121814221A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of wireless signal processing, and specifically relates to a method for removing noise points from constellation diagrams. Background Technology
[0002] In the field of radio spectrum regulation, it is often necessary to receive radio signals and identify their modulation methods. To facilitate human and machine identification of signal modulation methods, the I and Q components of a received radio signal are usually converted into a constellation diagram.
[0003] As signal acquisition speeds increase, the number of I and Q components in a radio signal grows dramatically. If all of these components were transmitted to the backend for modulation identification, it would place immense pressure on network transmission and backend resources. Therefore, identifying the modulation scheme simultaneously with the acquisition of the I and Q components has significant application value. However, converting the I and Q components into a constellation diagram generates numerous scattered points, introducing interference to the modulation identification process.
[0004] Therefore, there is an urgent need in practical applications for a simple and rapid method to eliminate noise points in constellation diagrams, meeting the requirements of low cost and real-time performance at the acquisition end. This invention is based on this practical need. Summary of the Invention (a) Technical problems to be solved The technical problem to be solved by the present invention is how to provide a method for removing noise points in constellation diagrams, so as to solve the problem of simple and fast elimination of noise points in constellation diagrams.
[0005] (II) Technical Solution To address the aforementioned technical problems, this invention proposes a method for removing noise points from constellation diagrams, comprising the following steps: S1. Steps for creating a counting constellation diagram: Based on the I and Q component pairs of the received signal, create a counting constellation diagram. In the constellation diagram, the value of a pixel is the number of times the I and Q component pairs appear. S2. Threshold Calculation Step: Calculate the average pixel value of non-zero pixels in the counting constellation map to determine the subsequent binarization threshold; S3. Binarization step of the counting constellation image: Based on the threshold, the non-zero pixels in the counting constellation image are binarized to obtain a binary constellation image that can be used for subsequent processing.
[0006] (III) Beneficial Effects This invention proposes a method for removing noise points from constellation diagrams. The method is simple to calculate and suitable for processing in front-end devices for signal acquisition. It has significant application value in fields such as wireless signal monitoring and management. Attached Figure Description
[0007] Figure 1This is a flowchart of the method for removing noise points from constellation diagrams according to the present invention. Detailed Implementation
[0008] To make the objectives, contents, and advantages of the present invention clearer, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.
[0009] This invention belongs to the field of wireless signal processing and relates to a method for removing noise points in a constellation diagram. More specifically, it relates to a method for eliminating noise points in a constellation diagram by utilizing the frequency of signal occurrences.
[0010] The purpose of this invention is to provide a method for removing noise points from constellation diagrams, which meets the requirement of front-end signal modulation mode identification in radio spectrum management.
[0011] To achieve the above objectives, this invention proposes a method for removing noise points from constellation diagrams, the method comprising: S1. Steps for creating a counting constellation diagram: Based on the I and Q component pairs of the received signal, create a counting constellation diagram. In the constellation diagram, the value of a pixel is not 0 or 1, but the number of times the I and Q component pairs appear.
[0012] S2. Threshold Calculation Step: Calculate the average pixel value of non-zero pixels in the counting constellation map to determine the subsequent binarization threshold.
[0013] S3. Binarization step of the counting constellation image: Based on the threshold, the non-zero pixels in the counting constellation image are binarized to obtain a binary constellation image that can be used for subsequent processing.
[0014] Example 1: Figure 1 This is a flowchart of a method for removing noise points from a constellation diagram according to the present invention. Figure 1 As shown, the method includes: (1) Steps for creating a counting constellation diagram. Based on the I and Q component pairs of the received signal, a counting constellation diagram is created. In the counting constellation diagram, the value of a pixel is not 0 or 1, but the number of times the I and Q component pairs appear.
[0015] In practical implementation, the m I and Q component pairs of a signal are: (I(1),Q(1)), (I(2),Q(2)),…, (I(m),Q(m)) The constellation diagram is N*N in size, and the initial value of each pixel in the constellation diagram is 0.
[0016] First, calculate the maximum value of the absolute values of the I and Q components: maxIQ=max{|I(1)|,|Q(1)|,|I(2)|,|Q(2)|, …, |I(m)|,|Q(m)|}.
[0017] Then calculate the coordinates (x(i), y(i)) of each I, Q component pair (I(i), Q(i)) in the constellation diagram: x(i)=[(I(i)+maxIQ) * N] / (2 * maxIQ), y(i)=[(Q(i)+maxIQ) * N] / (2 * maxIQ).
[0018] Finally, this I, Q component pair (I(i), Q(i)) is added to the constellation diagram: the pixel value at the position (x(i), y(i)) in the constellation diagram is incremented by 1.
[0019] After all m I and Q component pairs of a signal have been processed as described above, a counting constellation diagram is obtained.
[0020] (2) Threshold calculation step. Calculate the average value of non-zero pixels in the counting constellation map to determine the subsequent binarization threshold.
[0021] In practice, the sum of the pixel values of non-zero pixels in the counting constellation diagram is calculated as M; at the same time, the number of non-zero pixels in the counting constellation diagram, K, is calculated.
[0022] The average pixel value of non-zero pixels in the constellation count diagram is A = M / K.
[0023] The threshold th is usually: th = A * τ = (M * τ) / K. τ is a preset parameter, for example, 0.1, 0.2, or 0.3.
[0024] (3) Binarization step of the counting constellation map. Based on the threshold, the non-zero pixels in the counting constellation map are binarized to obtain a binary constellation map that can be used for subsequent processing.
[0025] In practice, if a threshold th is determined and the pixel value at (x,y) in the constellation map is f(x,y), then f(x,y) is binarized: if f(x,y) ≥ th, then f(x,y) = 1; otherwise, f(x,y) = 0. In this way, I and Q component pairs that occur less frequently are removed as noise.
[0026] Example 2: A method for removing noise points from a constellation diagram includes: (1) Steps for creating a counting constellation diagram.
[0027] (2) Calculate the threshold step.
[0028] (3) Binarization steps of the constellation counting diagram.
[0029] In the constellation diagram creation step, for a signal containing m I and Q component pairs: (I(1),Q(1)), (I(2),Q(2)), ..., (I(m),Q(m)), the constellation diagram size is N*N, and the initial value of each pixel in the constellation diagram is 0.
[0030] First, calculate the maximum value of the absolute values of the m I and Q components: maxIQ=max{|I(1)|,|Q(1)|,|I(2)|,|Q(2)|, …, |I(m)|,|Q(m)|}.
[0031] Then calculate the coordinates (x(i), y(i)) of this I, Q component pair (I(i), Q(i)) in the constellation diagram: x(i) = [(I(i) + maxIQ) * N] / (2 * maxIQ), y(i)=[(Q(i)+maxIQ) * N] / (2 * maxIQ).
[0032] Finally, this I, Q component pair (I(i), Q(i)) is added to the constellation diagram: the pixel value at the position (x(i), y(i)) in the constellation diagram is incremented by 1.
[0033] In the threshold calculation step, the sum of the pixel values of non-zero pixels in the constellation count is M; the number of non-zero pixels in the constellation count is K. The average pixel value of non-zero pixels in the constellation count is A = M / K. The threshold th is usually: th = A * 0.2 = (M * 0.2) / K.
[0034] In the binarization step of the counting constellation diagram, the pixel value at (x,y) in the counting constellation diagram is f(x,y). If f(x,y)≥th, then f(x,y)=1; otherwise, f(x,y)=0.
[0035] This invention discloses a method for removing noise points from a constellation diagram. The method includes: (1) a constellation diagram creation step. A constellation diagram is created based on the received I and Q component pairs of the signal. (2) a threshold calculation step. The average value of the non-zero pixels in the constellation diagram is calculated to determine the subsequent binarization threshold. (3) a constellation diagram binarization step. Based on the threshold, the non-zero pixels in the constellation diagram are binarized to obtain a constellation diagram that can be used for subsequent processing. The method for removing noise points from a constellation diagram proposed in this invention is simple to calculate and has important application value in fields such as wireless signal monitoring and management.
[0036] The method for removing noise points from constellation diagrams proposed in this invention is computationally simple, suitable for processing in front-end devices for signal acquisition, and has significant application value in fields such as wireless signal monitoring and management.
[0037] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. A method for removing noise points from a constellation diagram, characterized in that, The method includes the following steps: S1. Steps for creating a counting constellation diagram: Based on the I and Q component pairs of the received signal, create a counting constellation diagram. In the constellation diagram, the value of a pixel is the number of times the I and Q component pairs appear. S2. Threshold Calculation Step: Calculate the average pixel value of non-zero pixels in the counting constellation map to determine the subsequent binarization threshold; S3. Binarization step of the counting constellation image: Based on the threshold, the non-zero pixels in the counting constellation image are binarized to obtain a binary constellation image that can be used for subsequent processing.
2. The method for removing noise points from constellation diagrams as described in claim 1, characterized in that, The method includes the following steps: In S1, the m I, Q component pairs of a signal segment are: (I(1),Q(1)), (I(2),Q(2)),…, (I(m),Q(m)) The constellation diagram is N*N in size, and the initial value of each pixel in the constellation diagram is 0.
3. The method for removing noise points from constellation diagrams as described in claim 2, characterized in that, The method includes the following steps: In S1, First, calculate the maximum value of the absolute values of the I and Q components: maxIQ=max{|I(1)|,|Q(1)|,|I(2)|,|Q(2)|, …, |I(m)|,|Q(m)|}; Then calculate the coordinates (x(i), y(i)) of each I, Q component pair (I(i), Q(i)) in the constellation diagram: x(i)=[(I(i)+maxIQ) * N] / (2 * maxIQ), y(i)=[(Q(i)+maxIQ) * N] / (2 * maxIQ), Finally, this I, Q component pair (I(i), Q(i)) is added to the constellation diagram: the pixel value at position (x(i), y(i)) in the constellation diagram is incremented by 1; After all m I and Q component pairs of a signal have been processed as described above, a counting constellation diagram is obtained.
4. The method for removing noise points from constellation diagrams as described in claim 3, characterized in that, The method includes the following steps: In S2, calculating the average pixel value of non-zero pixels in the counting constellation diagram includes: Calculate the sum of the pixel values of non-zero pixels in the counting constellation diagram as M; and simultaneously calculate the number of non-zero pixels K in the counting constellation diagram. The average pixel value of non-zero pixels in the constellation count is A = M / K.
5. The method for removing noise points from constellation diagrams as described in claim 4, characterized in that, The method includes the following steps: In S2, the subsequent binarization threshold is determined as follows: The threshold th is: th=A*τ=(M*τ) / K, where τ is a preset parameter.
6. The method for removing noise points from constellation diagrams as described in claim 5, characterized in that, The method includes the following steps: τ is 0.
1.
7. The method for removing noise points from a constellation diagram as described in claim 5, characterized in that, The method includes the following steps: τ is 0.
2.
8. The method for removing noise points from constellation diagrams as described in claim 5, characterized in that, The method includes the following steps: τ is 0.
3.
9. The method for removing noise points from a constellation diagram as described in claim 5, characterized in that, The method includes the following steps: S3 includes: after determining the threshold th, the pixel value at (x,y) of the counting constellation map is f(x,y), then f(x,y) is binarized: if f(x,y)≥th, then f(x,y)=1, otherwise f(x,y)=0.
10. The method for removing noise points from a constellation diagram as described in claim 9, characterized in that, This method is used to determine the modulation scheme of radio signals.