Signal-to-noise ratio estimation method and device suitable for PSK (Phase Shift Keying) modulation

Abstract

The invention provides a signal-to-noise ratio estimation method and device suitable for PSK (Phase Shift Keying) modulation. The method comprises the following steps: calculating the average power of an input signal sequence; estimating the average power of the pilot frequency sequence; and calculating a signal-to-noise ratio. According to the method, the influence degree of noise on the distance between the PSK modulation signal and the original point in the constellation diagram is estimated, a traditional method for calculating the signal-to-noise ratio by estimating the deviation degree of the actual signal from the ideal signal due to the influence of noise is replaced, high accuracy can still be kept when the signal is influenced by Doppler frequency deviation and sampling deviation, the method is more suitable for an actual communication system, and compared with the prior art, the method has the advantages of simple operation and low cost. In an actual communication system, signal-to-noise ratio estimation is usually carried out after signal timing synchronization and carrier synchronization processing, however, the signal-to-noise ratio calculation method provided by the invention can be used for estimating the signal-to-noise ratio after synchronization before synchronization according to PSK modulation characteristics, and has certain application advantages in scenes such as switching modulation waveforms according to the signal-to-noise ratio.

Description

Technical Field

[0001] This application relates to the field of broadband signal technology, and in particular to a signal-to-noise ratio prediction method and apparatus suitable for PSK modulation. Background Technology

[0002] Currently, common signal-to-noise ratio (SNR) estimation algorithms measure additive white noise in the channel by constructing specially structured pilot sequences and applying the SNR calculation formula. However, traditional SNR estimation methods are susceptible to significant errors due to factors such as Doppler frequency offset and sampling deviation, requiring compensation of the pilot sequence and payload data before SNR estimation. Therefore, especially in broadband signal transmission, SNR estimation algorithms rely heavily on the performance of synchronization algorithms and cannot be estimated before synchronization.

[0003] Specifically, traditional signal-to-noise ratio (SNR) estimation methods based on special pilot sequences (such as Gray codes) subtract the sampled signal sequence from the local sequence to obtain an error sequence, and then calculate the SNR using the following formula: in, It is an error sequence, and the signal power of the pilot sequence is... 2 The signal-to-noise ratio (SNR) is the ratio of noise power to ideal signal power.

[0004] In traditional signal-to-noise ratio (SNR) calculations, the pilot sequence signal is considered to be affected only by Gaussian white noise. When the signal is affected by factors such as Doppler frequency offset and sampling deviation, the part of the signal that has not been synchronized is regarded as noise, which results in a large error between the SNR estimation and the result calculated after synchronization. Summary of the Invention

[0005] The technical solution adopted in this invention is to address the drawback of large errors in estimating the signal-to-noise ratio (SNR) using special pilot sequences when broadband signals are affected by factors such as Doppler frequency offset. Therefore, this invention provides a SNR prediction method and apparatus suitable for PSK modulation.

[0006] The present invention proposes a signal-to-noise ratio prediction method suitable for PSK modulation, comprising: Step S1: Calculate the average power of the input signal sequence; Step S2: Estimate the average power of the pilot sequence; Step S3: Calculate the signal-to-noise ratio.

[0007] In one embodiment, step S1 includes: Assume the Gaussian white noise sequence in the system is The noise-free original PSK modulated signal sequence is The real part is The noise is The imaginary part is Noise is The sequence length is n ; In the formula , ; Based on the property of uniform power spectral density distribution of Gaussian white noise, When the power spectral density of the constructed input pilot sequence is uniformly distributed, we get From formulas 1, 2, and 3, we get In one embodiment, step S2 includes: Based on the consistent power of each symbol in the original PSK modulated signal sequence, Based on the property of uniform power spectral density distribution of Gaussian white noise, In one embodiment, step S3 includes: The average noise power is obtained from formulas 1, 4, and 6. In the formula , That is, the actual input signal I and Q sequence values; According to the definition of signal-to-noise ratio (SNR), the SNR is calculated by the following formula: Another aspect of the present invention provides a signal-to-noise ratio prediction device suitable for PSK modulation, comprising: The input signal calculation unit is configured to calculate the average power of the input signal sequence. Pilot sequence calculation unit, configured to estimate the average power of pilot sequences; The signal-to-noise ratio calculation unit is configured to calculate the signal-to-noise ratio.

[0008] Another aspect of the present invention provides an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to execute the computer program to implement the signal-to-noise ratio prediction method for PSK modulation as described in any of the preceding claims.

[0009] Another aspect of the present invention provides a computer-readable storage medium storing a computer program that is executed to implement the signal-to-noise ratio prediction method for PSK modulation as described in any of the preceding claims.

[0010] By adopting the above technical solution, the present invention has at least the following advantages: The method provided by this invention is represented on a constellation diagram as the ratio of the average distance from the constellation points to the origin to the average noise power. When the signal is affected by Doppler frequency shift or sampling deviation, the constellation points move and rotate around the origin. In this case, traditional signal-to-noise ratio estimation methods will have large errors due to the constellation point shift, while the method of this invention is more accurate in calculating the signal-to-noise ratio of PSK modulated signals. Attached Figure Description

[0011] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a schematic flowchart of a signal-to-noise ratio prediction method for PSK modulation according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of another signal-to-noise ratio prediction method applicable to PSK modulation according to an embodiment of the present invention. Detailed Implementation

[0012] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments.

[0013] While exemplary embodiments of the invention are shown in the accompanying drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey its scope to those skilled in the art. The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0014] In the first embodiment of the present invention, a signal-to-noise ratio prediction method suitable for PSK modulation is provided, such as... Figure 1 As shown, it includes the following steps: Step S1: Calculate the average power of the input signal sequence; Step S2: Estimate the average power of the pilot sequence; Step S3: Calculate the signal-to-noise ratio.

[0015] The following will further combine Figure 2The method provided in this embodiment will be described in detail.

[0016] In one specific implementation, the overall flow of the signal-to-noise ratio prediction method applicable to PSK modulation is as follows: Figure 2 As shown, the system input is a PSK modulated signal sequence containing Gaussian white noise, affected by Doppler frequency offset and sampling deviation. After timing synchronization and carrier synchronization to compensate for phase and frequency offset, the system obtains a PSK modulated signal containing only Gaussian white noise. At this point, the signal-to-noise ratio (SNR) can be obtained using traditional SNR estimation methods. In this embodiment, the SNR is calculated by estimating the average power of the pilot sequence and the average power of the input signal sequence, allowing for a prediction of the SNR before synchronization. The predicted SNR result, SNR0, is approximately the same as that calculated using traditional methods.

[0017] Assume the Gaussian white noise sequence in the system is The noise-free original PSK modulated signal sequence is The real part is The noise is The imaginary part is Noise is The sequence length is n The signal-to-noise ratio prediction method applicable to PSK modulation is as follows: Calculate the average power of the input signal sequence In the formula , .

[0018] Based on the uniform distribution property of the power spectral density of Gaussian white noise, we can obtain... When the power spectral density of the constructed input pilot sequence is uniformly distributed, we can obtain... From equations (2), (3), and (4), we can obtain Estimating the average power of the pilot sequence Based on the fact that the power of each symbol in the original PSK modulated signal sequence is consistent, we can obtain... Based on the uniform distribution property of the power spectral density of Gaussian white noise, we can obtain... Calculate the signal-to-noise ratio The average noise power can be obtained from equations (2), (5), and (7). In the formula , This refers to the actual input signal I and Q sequence values.

[0019] According to the definition of signal-to-noise ratio (SNR), the SNR can be calculated using the following formula. This signal-to-noise ratio (SNR) estimation method is represented on a constellation diagram as the ratio of the average distance from the constellation points to the origin to the average noise power. When the signal is affected by Doppler frequency shift or sampling deviation, the constellation points move and rotate around the origin. In this case, traditional SNR estimation methods will have a large error due to the constellation point shift, while the method of this invention is more accurate in calculating the SNR of PSK modulated signals.

[0020] Compared with the prior art, this embodiment has at least the following advantages: 1) This invention uses the method of estimating the degree of noise influence on the distance between the PSK modulated signal and the origin in the constellation diagram, instead of the traditional method of estimating the degree of noise influence on the actual signal to deviate from the ideal signal to calculate the signal-to-noise ratio. It can still maintain high accuracy when the signal is affected by Doppler frequency offset and sampling deviation, and is more suitable for actual communication systems. 2) In contrast, in practical communication systems, signal timing synchronization and carrier synchronization are usually required before signal-to-noise ratio (SNR) estimation. The SNR calculation method proposed in this invention, tailored to PSK modulation characteristics, can predict the post-synchronization SNR before synchronization. This offers advantages in scenarios such as switching modulation waveforms based on SNR.

[0021] In a second embodiment of the present invention, a signal-to-noise ratio prediction device suitable for PSK modulation is disclosed. This device can be understood as a physical apparatus for implementing the method provided in the first embodiment. The apparatus includes: The input signal calculation unit is configured to calculate the average power of the input signal sequence. Pilot sequence calculation unit, configured to estimate the average power of pilot sequences; The signal-to-noise ratio calculation unit is configured to calculate the signal-to-noise ratio.

[0022] A third embodiment of the present invention provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the signal-to-noise ratio prediction method for PSK modulation as described in the first embodiment.

[0023] A fourth embodiment of the present invention provides a computer-readable storage medium storing a computer program that is executed to implement the signal-to-noise ratio prediction method for PSK modulation as described in the first embodiment.

[0024] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims. All of these forms are within the protection scope of this application.

Claims

1. A signal-to-noise ratio prediction method suitable for PSK modulation, characterized in that, include: Step S1: Calculate the average power of the input signal sequence; Step S2: Estimate the average power of the pilot sequence; Step S3: Calculate the signal-to-noise ratio.

2. The signal-to-noise ratio prediction method for PSK modulation according to claim 1, characterized in that, Step S1 includes: Assume the Gaussian white noise sequence in the system is The noise-free original PSK modulated signal sequence is The real part is The noise is The imaginary part is Noise is The sequence length is n ; Official 1 In the formula , ; Based on the property of uniform power spectral density distribution of Gaussian white noise, Official 2 When the power spectral density of the constructed input pilot sequence is uniformly distributed, we get Official 3 From formulas 1, 2, and 3, we get Official 4.

3. The signal-to-noise ratio prediction method for PSK modulation according to claim 2, characterized in that, Step S2 includes: Based on the consistent power of each symbol in the original PSK modulated signal sequence, Official 5 Based on the property of uniform power spectral density distribution of Gaussian white noise, Formula 6.

4. The signal-to-noise ratio prediction method for PSK modulation according to claim 3, characterized in that, Step S3 includes: The average noise power is obtained from formulas 1, 4, and 6. Formula 7 In the formula , That is, the actual input signal I and Q sequence values; According to the definition of signal-to-noise ratio (SNR), the SNR is calculated by the following formula: Formula 8.

5. A signal-to-noise ratio prediction device suitable for PSK modulation, characterized in that, include: The input signal calculation unit is configured to calculate the average power of the input signal sequence. Pilot sequence calculation unit, configured to estimate the average power of pilot sequences; The signal-to-noise ratio calculation unit is configured to calculate the signal-to-noise ratio.

6. An electronic device, characterized in that, The system includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the signal-to-noise ratio prediction method for PSK modulation as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The medium stores a computer program that is executed to implement the signal-to-noise ratio prediction method for PSK modulation as described in any one of claims 1 to 4.

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