Nonlinear DOA estimation method integrated with CE-OFDM

Abstract

The application discloses a CE-OFDM communication and sensing integrated anti-nonlinear DOA estimation method, belongs to the field of communication sensing, and comprises the following steps: generating a 0dB peak-to-average power ratio CE-OFDM signal at a transmitting end, so that the CE-OFDM signal can drive a power amplifier to work in a saturation region, thereby avoiding nonlinear distortion while ensuring high power amplifier efficiency. A uniform linear array is used to receive signals at a receiving end, the signals are decomposed into a frequency domain through discrete Fourier transform, narrowband MVDR spatial spectra are independently calculated for each subcarrier frequency point, wideband spatial spectra are obtained through non-coherent fusion, and finally high-precision DOA estimation is realized through peak value searching. The application fundamentally suppresses power amplifier nonlinear distortion by using the constant envelope characteristic of CE-OFDM, avoids eigenvalue decomposition and source number estimation by combining the IMVDR algorithm, supports frequency point level parallel calculation, and realizes high-precision and low-complexity DOA estimation while ensuring communication reliability.

Description

Technical Field

[0001] This invention belongs to the field of communication sensing, and particularly relates to a CE-OFDM integrated sensing and communication anti-nonlinear DOA estimation method. Background Technology

[0002] Integrated communication and sensing is one of the core technologies of sixth-generation mobile communication (6G) and future wireless systems. By deeply integrating radar sensing and wireless communication functions, it places high demands on the efficient coordination of physical layer waveform design. Orthogonal frequency division multiplexing (OFDM) has gained widespread attention in ISAC systems due to its strong anti-multipath interference capability and high spectral efficiency. However, the inherent peak-to-average power ratio (PAPR) characteristic of OFDM signals necessitates a significant backoff of the operating point of high-power RF amplifiers to avoid nonlinear distortion. This not only reduces power amplification efficiency but also increases the bit error rate due to nonlinear distortion, affecting communication quality. Constant envelope OFDM achieves constant envelope modulation by embedding information into the phase, exhibiting a 0dB PAPR characteristic. Theoretically, this allows the HPA to operate directly in the saturation region, significantly improving power amplifier efficiency while effectively suppressing nonlinear distortion, avoiding the performance degradation of traditional OFDM in high-power transmission scenarios. Although CE-OFDM has been extensively studied in the field of communication, its application in ISAC systems is extremely limited.

[0003] In ISAC systems, accurate angle-of-arrival (DOA) estimation is crucial for radar sensing and communication beamforming. Existing DOA estimation methods are mostly based on subspace decomposition algorithms, typically relying on eigenvalue decomposition and source number estimation, resulting in high computational complexity and difficulty meeting real-time processing requirements. More importantly, current research has not yet combined the constant envelope characteristics of CE-OFDM with low-complexity DOA estimation methods, failing to fully leverage the advantages of CE-OFDM in resisting power amplifier nonlinear distortion, and making it difficult to simultaneously ensure communication reliability and sensing accuracy under high-power transmission conditions. Therefore, how to utilize the unique advantages of CE-OFDM signals in ISAC systems to achieve DOA estimation that is resistant to power amplifier nonlinearity, has low latency, and high accuracy has become an urgent technical problem to be solved. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a CE-OFDM integrated inductive nonlinear DOA estimation method, comprising: A constant envelope orthogonal frequency division multiplexing (CE-OFDM) signal is generated, amplified by a power amplifier, and then transmitted. Signals are received using a uniform linear array, and frequency domain data is obtained from the received signals. Based on the frequency domain data, obtain the broadband spatial spectrum; Based on the broadband spatial spectrum, determine the estimated angle of arrival (DOA).

[0005] Optionally, generating the CE-OFDM signal includes: The initial frequency domain symbols are subjected to Hermitian symmetry processing by adding a 0 at the beginning and end of the initial frequency domain symbol sequence, and adding the reverse order of its complex conjugate after the original sequence; Performing an inverse discrete Fourier transform on the sequence yields a real-valued orthogonal frequency division multiplexing (OFDM) baseband signal. Phase modulation is performed on the OFDM baseband signal to embed the amplitude information of the OFDM baseband signal into the phase, thereby generating a CE-OFDM signal with a peak-to-average power ratio of 0dB.

[0006] Optionally, the phase modulation includes: The OFDM baseband signal is phase-modulated using a preset phase modulation index and a normalization factor; wherein the normalization factor is determined based on the number of discrete Fourier transform points and the modulation order of the initial frequency domain symbol.

[0007] Optionally, obtaining frequency domain data based on the received signal includes: The analog signal received by the uniform linear array is converted from analog to digital to obtain a digital time-domain signal; The digital time-domain signal is subjected to a discrete Fourier transform to decompose it into multiple frequency points, thereby obtaining the frequency domain signal corresponding to each array element at each frequency point.

[0008] Optionally, obtaining frequency domain data based on the received signal further includes: Based on the frequency domain signals of multiple snapshot data, the spatial covariance matrix of each frequency point is calculated; wherein, the spatial covariance matrix is ​​obtained by summing and averaging the product of the frequency domain signal vectors of all array elements at each frequency point and their conjugate transposes along the snapshot dimension.

[0009] Optionally, obtaining the broadband spatial spectrum based on the frequency domain data includes: For each frequency point, the narrowband minimum variance distortionless response (MVDR) spatial spectrum of that frequency point is calculated based on the inverse of the spatial covariance matrix of that frequency point and the array steering vector of that frequency point. The broadband spatial spectrum is obtained by incoherently fusing the narrowband MVDR spatial spectra of all frequency points.

[0010] Optionally, the narrowband MVDR spatial spectrum is obtained by calculating the product of the conjugate transpose of the array steering vector and the inverse of the spatial covariance matrix, then multiplying it by the array steering vector, and taking the reciprocal of the resulting scalar value.

[0011] Optionally, determining the DOA estimate includes: Within a preset angle scanning range, calculate the spectral values ​​of the broadband spatial spectrum and extract at least one peak spectral value; The angle corresponding to the at least one peak spectral value is determined as the DOA estimation result.

[0012] On the other hand, the present invention also provides an electronic device including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0013] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0014] Compared with the prior art, the present invention has the following advantages and technical effects: This invention employs CE-OFDM signals, whose 0dB constant envelope characteristic allows the power amplifier to operate directly in the saturation region, fundamentally avoiding nonlinear distortion caused by high-power amplification. This ensures the fidelity of the communication and sensing signals at the receiving end, providing a high-quality input signal for subsequent high-precision DOA estimation. Based on this, the invention transforms the received signal to the frequency domain, independently applies the narrowband MVDR method to each subcarrier frequency point, and performs incoherent fusion of the resulting spatial spectrum. This avoids the eigenvalue decomposition and source number estimation required by traditional subspace methods, significantly reducing computational complexity. The independent processing structure for each frequency point naturally supports parallel computing, greatly shortening processing latency and meeting the stringent real-time requirements of the ISAC system. Experimental results show that, compared to traditional OFDM schemes, this invention significantly improves DOA estimation accuracy when operating in the power amplifier saturation region, achieving synergistic optimization of communication reliability and sensing accuracy under high-power transmission conditions. Attached Figure Description

[0015] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the emission after amplification by HPA when the PAPR is 0dB, according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the IMVDR spatial spectrum according to an embodiment of the present invention; Figure 4 This is a schematic diagram comparing the DOA estimation accuracy of CE-OFDM and OFDM in an embodiment of the present invention. Detailed Implementation

[0016] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0017] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0018] Example 1 like Figure 1 As shown, this embodiment provides a CE-OFDM integrated inductive nonlinear DOA estimation method, including: A constant envelope orthogonal frequency division multiplexing (CE-OFDM) signal is generated, amplified by a power amplifier, and then transmitted. Signals are received using a uniform linear array, and frequency domain data is obtained from the received signals. Based on the frequency domain data, obtain the broadband spatial spectrum; Based on the broadband spatial spectrum, determine the estimated angle of arrival (DOA).

[0019] Specifically, it includes: S1. The OFDM baseband signal is embedded into the constant envelope signal through phase modulation to generate the CE-OFDM signal. The modulation method generated at the transmitting end is multi-level quadrature amplitude modulation. Frequency domain symbols And reconstruct it into an Hermitian symmetric sequence: ; in express The complex conjugate, , The number of FFT points. After performing the IDFT operation, a real-valued time-domain OFDM signal is obtained: ; in, For complex units, This is the index of the time-domain sampling point.

[0020] Phase modulation of the above OFDM signal yields a CE-OFDM signal: ; in, Let be the phase modulation index, and define a constant. As a normalization factor, the PAPR of this signal is 0dB. After being amplified by HPA, it is transmitted, effectively avoiding nonlinear distortion. Let be the QAM modulation order.

[0021] Step 2, using The ULA receives CE-OFDM signals and converts the received analog signals into digital time-domain signals using an analog-to-digital converter. ,in: ; in For the first Additive white Gaussian noise at each array element , To be from the direction The time delay corresponding to the incident event. , The total number of signal sources, The speed of electromagnetic wave transmission This indicates the element spacing of ULA. For the first The signal emitted by the source Indicates time.

[0022] Step 3: Process the received signal Point DFT yields the frequency domain signal and the corresponding frequency covariance matrix. conduct The point's DFT, decomposed into the frequency domain, yields: ; in, For the first The frequency of each point, This represents Gaussian noise at the corresponding frequency.

[0023] in Simplifying the above equation, we get: ; in Indicates frequency point Place The signal vector of each source signal For the corresponding noise vector, The corresponding array manifold vector is represented as follows: ; in Indicates the first Individual source signal direction exist The array guide vector at that location.

[0024] based on Calculate the spatial covariance matrix for each frequency point from the snapshot data: ; in, , for The conjugate transpose of .

[0025] Step 4: For each frequency component ,use and guide vector Calculate the narrowband MVDR spatial spectrum: ; in, for The inverse matrix, for The conjugate transpose of .

[0026] Step 5: Incoherently integrate the spatial spectra of all frequency points to obtain the final spatial spectrum. The angle corresponding to the maximum value of the spatial spectrum is the final DOA estimate. The spatial spectrum is as follows: ; Within the preset angle range Inside, extract of The angle corresponding to the maximum peak value is used to obtain the DOA estimation result: ; Repeat steps 1-5 above to conduct Monte Carlo experiments and plot a comparison of the DOA estimation accuracy between CE-OFDM and OFDM. Figure 4 As shown, CE-OFDM can resist the effects of power amplifier nonlinearity and improve the accuracy of DOA estimation.

[0027] Example 2 This embodiment provides a CE-OFDM integrated inductive nonlinear DOA estimation method, including: Consider a far-field single signal source A, transmitting a communication-sensing integrated signal to the receiver at a 1 GHz carrier frequency. The angle between its incident direction and the normal of the uniform linear array is... The receiver array consists of The array consists of several antenna elements, with the element spacing strictly set to half a wavelength. , (Carrier wavelength). The signal source can transmit both traditional OFDM and CE-OFDM signals, which are amplified by the same solid-state power amplifier in the saturation region and then received by the ULA. The specific implementation steps of the CE-OFDM integrated inductive nonlinear DOA estimation method disclosed in this embodiment are as follows: Step 1: The transmitting end generates frequency domain symbols with 16QAM modulation. And reconstruct it into an Hermitian symmetric sequence: ; in express The complex conjugate, , The number of FFT points. After performing the IDFT operation, a real-valued time-domain OFDM signal is obtained: ; Phase modulation of the above OFDM signal yields a CE-OFDM signal: ; in Let be the phase modulation index, and define a constant. As a normalization factor. For example... Figure 2 The signal has a PAPR of 0dB and is emitted after being amplified by HPA, effectively avoiding nonlinear distortion.

[0028] Step 2: Use a 16-element ULA to receive CE-OFDM signals, and convert the received analog signals into digital time-domain signals using an analog-to-digital converter. ,in: ; in, For the first Additive white Gaussian noise at each array element To be from the direction The time delay corresponding to the incident event. , The speed of electromagnetic wave transmission This indicates the element spacing of the ULA.

[0029] Step 3: Process the received signal Point DFT yields the frequency domain signal of each frequency component and the corresponding covariance matrix. conduct The point's DFT, decomposed into the frequency domain, yields: ; in Simplifying the above equation, we get: ; in Indicates frequency point Place The signal vector of each source signal This is the corresponding noise vector. The corresponding array manifold vector is: ; in Indicates the first Individual source signal direction exist The array steering vector at that location. Based on Calculate the spatial covariance matrix for each frequency point from the snapshot data: ; Step 4: For each frequency component ,use and guide vector Calculate the narrowband MVDR spatial spectrum: ; Step 5: Incoherently combine the spatial spectra of all frequency points to obtain the final spatial spectrum. The angle corresponding to the maximum value of the spatial spectrum is the final DOA estimate. The spatial spectrum is as follows: ; Within the preset angle range Inside, extract of The angle corresponding to the maximum peak value is used to obtain the DOA estimation result: .

[0030] In this embodiment, Plot the IMVDR spatial spectrum. For example... Figure 3 As shown in the figure, the estimated value can be obtained. .

[0031] Repeat steps 1-5 above to conduct Monte Carlo experiments and plot a comparison of the DOA estimation accuracy between CE-OFDM and OFDM. Figure 4 As shown, CE-OFDM can resist the effects of power amplifier nonlinearity and improve the accuracy of DOA estimation.

[0032] On the other hand, this embodiment also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0033] On the other hand, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0034] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A CE-OFDM integrated inductive method for nonlinear DOA estimation, characterized in that, include: A constant envelope orthogonal frequency division multiplexing (CE-OFDM) signal is generated, amplified by a power amplifier, and then transmitted. Signals are received using a uniform linear array, and frequency domain data is obtained from the received signals. Based on the frequency domain data, obtain the broadband spatial spectrum; Based on the broadband spatial spectrum, determine the estimated angle of arrival (DOA).

2. The method according to claim 1, characterized in that, Generating the CE-OFDM signal includes: The initial frequency domain symbols are subjected to Hermitian symmetry processing by adding a 0 at the beginning and end of the initial frequency domain symbol sequence, and adding the reverse order of its complex conjugate after the original sequence; Performing an inverse discrete Fourier transform on the sequence yields a real-valued orthogonal frequency division multiplexing (OFDM) baseband signal. Phase modulation is performed on the OFDM baseband signal to embed the information of the OFDM baseband signal into the phase, thereby generating a CE-OFDM signal with a peak-to-average power ratio of 0dB.

3. The method according to claim 2, characterized in that, The phase modulation includes: The OFDM baseband signal is phase-modulated using a preset phase modulation index and a normalization factor; wherein the normalization factor is determined based on the number of discrete Fourier transform points and the modulation order of the initial frequency domain symbol.

4. The method according to claim 1, characterized in that, The step of obtaining frequency domain data based on the received signal includes: The analog signal received by the uniform linear array is converted from analog to digital to obtain a digital time-domain signal; The digital time-domain signal is subjected to a discrete Fourier transform to decompose it into multiple frequency points, thereby obtaining the frequency domain signal corresponding to each array element at each frequency point.

5. The method according to claim 4, characterized in that, The step of obtaining frequency domain data based on the received signal further includes: Based on the frequency domain signals of multiple snapshot data, the spatial covariance matrix of each frequency point is calculated; wherein, the spatial covariance matrix is ​​obtained by summing and averaging the product of the frequency domain signal vectors of all array elements at each frequency point and their conjugate transposes along the snapshot dimension.

6. The method according to claim 1, characterized in that, The step of obtaining the broadband spatial spectrum based on the frequency domain data includes: For each frequency point, the narrowband minimum variance distortionless response (MVDR) spatial spectrum of that frequency point is calculated based on the inverse of the spatial covariance matrix of that frequency point and the array steering vector of that frequency point. The broadband spatial spectrum is obtained by incoherently fusing the narrowband MVDR spatial spectra of all frequency points.

7. The method according to claim 6, characterized in that, The narrowband MVDR spatial spectrum is obtained by multiplying the product of the conjugate transpose of the array steering vector and the inverse of the spatial covariance matrix, then multiplying it by the array steering vector, and taking the reciprocal of the resulting scalar value.

8. The method according to claim 1, characterized in that, Determining the DOA estimate includes: Within a preset angle scanning range, calculate the spectral values ​​of the broadband spatial spectrum and extract at least one peak spectral value; The angle corresponding to the at least one peak spectral value is determined as the DOA estimate.

9. An electronic device comprising a memory, a processor, and a computing program stored in the memory and executable on the processor, characterized in that, When the processor executes the computing program, it implements the method of any one of claims 1-8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-8.

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