A method for OFDM signal demodulation for wireless optical communication systems

Abstract

The application relates to the field of communication and signal processing, in particular to an OFDM signal demodulation method for a wireless optical communication system; the method is completed under the cooperation of a transmitting end and a receiving end; the transmitting end models the probability distribution of a scaled signal by using a Gaussian mixture model; based on the model, the nonlinear distortion is expressed as the weighted sum of the distortions of each Gaussian component, and the corresponding clipping coefficients are calculated for each Gaussian component; finally, the scaled signal and the clipping coefficients are sent to the receiving end; the receiving end uses the received clipping coefficients to perform inverse weighting processing on the received signal to compensate for the nonlinear distortion, and then performs equalization, deprecoding and demodulation to recover the original bit stream; by accurately modeling the non-Gaussian signal characteristics and precomputing the clipping coefficients, the application can effectively suppress the deep clipping distortion of the transmitting signal and significantly reduce the system error rate.

Description

Technical Field

[0001] This invention relates to the field of communication and signal processing, and in particular to an OFDM (Orthogonal Frequency Division Multiplexing) signal demodulation method for wireless optical communication systems. Background Technology

[0002] With the rapid development of emerging applications such as smart manufacturing, autonomous driving, and the Internet of Things, higher demands are being placed on the transmission rate, latency, and sensing capabilities of wireless communication systems. Traditional radio frequency communication systems, in complex electromagnetic environments, suffer from limited bandwidth resources and susceptibility to electromagnetic interference, making it difficult for their transmission performance to meet the needs of these application scenarios.

[0003] In contrast, wireless optical communication technology, with its advantages of abundant bandwidth resources, high transmission rates, and strong resistance to electromagnetic interference, has become an important supplementary means for short-range, high-speed data transmission. Meanwhile, optical sensing technology, based on the reflection and propagation characteristics of optical signals, is gradually being applied to scenarios such as indoor positioning and intelligent driving assistance, demonstrating broad application prospects. However, currently, most wireless optical communication systems and optical sensing systems are still deployed independently, leading to redundant equipment configuration, increased costs, and difficulty in flexible deployment in space-constrained environments.

[0004] Furthermore, OFDM technology is widely used in wireless optical communication systems due to its high spectral efficiency. However, OFDM signals have an inherent drawback of high PAPR (Peak-to-Average Power Ratio), which can easily cause signal clipping distortion in practical light sources due to limited peak power, seriously affecting communication quality and sensing accuracy.

[0005] To suppress PAPR, various technical solutions have been proposed in the prior art. For example, SLM (Selected Mapping) technology reduces the peak power of the signal through phase rotation optimization, but this technology requires the transmission of additional sideband information, increasing system overhead; companding transformation technology, although simple to implement, introduces non-negligible signal distortion, affecting system performance; DFT (Discrete Fourier Transform) precoding technology performs DFT matrix operations on the frequency domain symbols at the transmitter, and then feeds them into the IFFT (Inverse Fast Fourier Transform) module, utilizing its unitary transform characteristics to make the amplitude distribution of the serial signal more uniform, thereby effectively suppressing PAPR and reducing the system bit error rate without sacrificing spectral efficiency.

[0006] However, under extreme conditions such as severe nonlinearity of the light source and deep clipping of the signal, although the above-mentioned PAPR suppression methods can reduce the PAPR value of the signal to a certain extent, the compensation capability of existing methods is limited for the severe signal distortion caused by deep clipping, and it is difficult to effectively solve the problem of high bit error rate.

[0007] Therefore, there is an urgent need for a demodulation method that can effectively recover signals and reduce bit error rate under deep clipping conditions, so as to improve the reliability and practicality of wireless optical communication systems in complex environments. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention proposes an OFDM signal demodulation method for wireless optical communication systems. Based on the Gaussian mixture model and the weighted Bussgang theorem, the method performs signal recovery processing at the receiving end to solve the problem of deep clipping distortion caused by the limited peak power of the light source and the resulting increase in the system bit error rate.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] This invention proposes an OFDM signal demodulation method for wireless optical communication systems, including a transmitting end step and a receiving end step;

[0011] The transmitting end steps include:

[0012] S1. Generate a binary bit stream, and convert the binary bit stream into a complex symbol vector through constellation mapping;

[0013] S2. Perform Hermitian symmetric processing on the complex-valued symbol vector to obtain a Hermitian symmetric signal; perform DFT precoding on the Hermitian symmetric signal to generate a precoded signal; and perform IFFT and parallel-to-serial conversion on the precoded signal in sequence to obtain a serial signal.

[0014] S3. A power factor is introduced to scale the serial signal to obtain a scaled signal;

[0015] S4. The probability distribution of the scaled signal is modeled using a Gaussian mixture model to obtain a probability distribution model. Based on the probability distribution model, the nonlinear distortion of the scaled signal during the clipping process is expressed as a weighted sum of the distortions of each Gaussian component, and a corresponding clipping coefficient is calculated for each Gaussian component in the probability distribution model.

[0016] S5. Send the scaled signal and clipping coefficient to the receiving end;

[0017] The receiving end steps include:

[0018] S6. Receive the optical signal transmitted via the wireless optical channel and obtain the clipping coefficient transmitted by the transmitter. The optical signal is generated by the light source driven by the scaled signal.

[0019] S7. First, convert the optical signal into an electrical signal, then convert the electrical signal into a digital signal, and use the clipping coefficient to perform inverse weighting compensation on the digital signal to obtain the compensated signal.

[0020] S8. Demodulate the compensated signal to recover the binary bit stream.

[0021] Furthermore, in S4, the probability density function of the probability distribution model is:

[0022]

[0023] In the formula, for The probability density function, This is the scaled signal. This represents the total number of Gaussian components in the probability distribution model. Let i be the weight of the i-th Gaussian component. Let be the mean of the i-th Gaussian component. Let be the standard deviation of the i-th Gaussian component.

[0024] Furthermore, the characteristic is that, in S4, the formula for calculating the clipping coefficient is:

[0025]

[0026] In the formula, Let be the clipping coefficient corresponding to the i-th Gaussian component. for and Cross-correlation expectation, This is the signal corresponding to the i-th Gaussian component in the scaled signal. Let be the signal output by the clipping system under the i-th Gaussian component.

[0027] Furthermore, the transmitting end step further includes: adding a cyclic prefix to the scaled signal before driving the light source to emit; the receiving end step further includes: removing the cyclic prefix from the digital signal before inverse weighting compensation.

[0028] Further, the method for demodulating the compensated signal in S8 includes: sequentially performing serial-to-parallel conversion and FFT on the compensated signal to obtain a frequency domain signal; performing first-order equalization on the frequency domain signal to obtain an equalized signal; performing de-DFT precoding on the equalized signal to obtain a de-precoded signal; and demodulating the de-precoded signal.

[0029] Furthermore, the feature is that, in S5, the clipping coefficient is transmitted as sideband information along with the scaled signal.

[0030] Furthermore, the method for performing inverse weighted compensation of the digital signal using the clipping coefficient in S7 is as follows: divide the signal corresponding to each Gaussian component in the digital signal by its corresponding clipping coefficient.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0032] (1) This invention analyzes the non-Gaussian nature of the signal after DFT precoding and uses a Gaussian mixture model to accurately model its distribution, overcoming the inherent limitations of traditional methods in processing such signals. Furthermore, based on the weighted Bussgang theorem, the overall nonlinear distortion is decomposed into a weighted sum of the distortions of each Gaussian component, providing a reliable path for signal recovery under deep clipping conditions. Therefore, the scheme proposed in this invention can significantly reduce the bit error rate of the system even under extreme clipping conditions.

[0033] (2) This invention achieves refined modeling of the clipping process of serial signals by calculating independent clipping coefficients for each Gaussian component. This enables the receiver to efficiently compensate for distortion through simple inverse weighting operations without complex algebra selection, thereby reducing complexity while ensuring performance. This also enables the transmitter to transmit the clipping coefficients as sideband information after using DFT precoding to suppress PAPR, maintaining the high spectral efficiency of the system without sacrificing additional spectrum resources.

[0034] (3) The probability distribution modeling of the present invention based on the Gaussian mixture model can flexibly adapt to different channel environments and signal characteristics, making the scheme widely applicable. In addition, the efficient signal processing framework constructed by the present invention not only ensures reliable communication performance, but also provides technical support for the accurate extraction of optical sensing parameters such as distance and speed through its accurate signal recovery capability. Attached Figure Description

[0035] Figure 1 This is a flowchart of the OFDM signal demodulation method in an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the probability distribution model in an embodiment of the present invention;

[0037] Figure 3 This is a comparison chart showing the impact of the normalized power factor on the bit error rate of the deprecated signal and the compensated signal in an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Example

[0040] refer to Figure 1 This embodiment proposes an OFDM signal demodulation method for a DCO-OFDM (Direct Current-biased Optical Orthogonal Frequency Division Multiplexing) wireless optical communication system. The system includes a transmitter and a receiver. The transmitter includes a source module, a DFT precoding module, an IFFT module, a clipping coefficient calculation module, and a light source driving circuit. The receiver includes a photodetector, a signal processor, and a clipping compensation module.

[0041] The OFDM signal demodulation method proposed in this embodiment includes a transmitting end step and a receiving end step.

[0042] The transmitting end steps are as follows:

[0043] S1. The source module generates a binary bit stream to be transmitted, and converts the binary bit stream into a complex symbol vector through M-QAM (M-ary Quadrature Amplitude Modulation) constellation mapping. , Where N is the number of subcarriers, For complex-valued symbol vectors The Nth subcarrier in this example uses 16-QAM (16-ary Quadrature Amplitude Modulation) for constellation mapping.

[0044] S2. To ensure that the output is a real-valued time-domain signal after IFFT processing, the complex-valued sign vector is subjected to Hermitian symmetry processing to obtain a Hermitian symmetric signal. .

[0045] To reduce the PAPR of the signal, Hermitian symmetric signals... Input to the DFT precoding module for Hermitian symmetric signals Perform DFT precoding to generate a precoded signal. :

[0046]

[0047] In the formula, The DFT precoding matrix satisfies , for The conjugate transpose of the matrix. Let L×L be the identity matrix. , To introduce the number of redundant information, 1 ≤ N p ≤N.

[0048] It is composed of a diagonal matrix G and a matrix T, that is:

[0049]

[0050] In the formula, the diagonal matrix G is composed of a set of orthogonal bases, with the following specific form:

[0051]

[0052]

[0053] In the formula, The element in row (l+1) and column (l+1) of G.

[0054] Matrix T is an L×N rotation factor matrix, whose elements are determined by the rotation factor. constitute, The expression is:

[0055]

[0056]

[0057] In the formula, j is the imaginary unit, and m is the exponent of the rotation factor. Let t be the relative row number of the row index within the block; matrix T contains two blocks, the first block has N rows, and the row numbers within the block are sequentially numbered from 0 to N-1; the second block has N rows. The line numbers within the blocks range from 0 to... -1 is the sequential number; s is the column index, 0≤s≤N-1.

[0058] The specific form of matrix T is:

[0059]

[0060] The precoded signal The input is fed into the N-point IFFT module to process the precoded signal. Perform IFFT to obtain the time-domain signal. Subsequently, the time-domain signal is converted using a parallel-to-serial conversion module. Perform parallel-to-serial conversion to obtain a serial signal. ; Serial signal The nth sample in the series is denoted as .

[0061] S3. To control the signal transmission power and clipping distortion, this embodiment introduces a power factor β to scale the serial signal, resulting in a scaled signal. , , scaled signal The nth sample in the series is denoted as .

[0062] S4. Regarding the non-Gaussian nature of the signal after DFT precoding, in this embodiment, the clipping coefficient calculation module uses a Gaussian mixture model to calculate the scaling of the signal. We model the probability distribution to obtain a probability distribution model, and the probability density function of the probability distribution model is:

[0063]

[0064] In the formula, for The probability density function, This represents the total number of Gaussian components in the probability distribution model. Let i be the weight of the i-th Gaussian component. Let be the mean of the i-th Gaussian component. Let be the standard deviation of the i-th Gaussian component.

[0065] Using the weighted Bussgang theorem, the nonlinear distortion of the scaled signal during clipping is expressed as a weighted sum of the distortions of each Gaussian component. This model is used to model the clipping process for each Gaussian component in the probability distribution model, and a corresponding clipping coefficient is calculated for each Gaussian component. For the i-th Gaussian component, the clipping process can be modeled as follows:

[0066]

[0067] In the formula, For the i-th Gaussian component, the signal output by the clipping system is... This is the signal corresponding to the i-th Gaussian component in the scaled signal. Let be the clipping coefficient corresponding to the i-th Gaussian component. Let n be the clipped noise corresponding to the i-th Gaussian component, and n be the additive noise.

[0068] The clipping coefficient corresponding to the i-th Gaussian component The calculation formula is:

[0069]

[0070]

[0071]

[0072]

[0073] In the formula, for and Cross-correlation expectation, The cumulative distribution function of the standard normal distribution. Let be the probability density function of the standard normal distribution. This is the normalized clipping lower bound for the i-th Gaussian component. Let the normalized clipping upper bound be the value for the i-th Gaussian component. Due to optical power limitations.

[0074] Clipping noise power The calculation formula is:

[0075]

[0076]

[0077] In the formula, for average power, for The average power.

[0078] S5, Copy the N at the end of the scaled signal. cp N samples will be copied cp N samples are added to the beginning of the scaled signal as a cyclic prefix to form the transmitted signal. In this embodiment, N cp =32; The transmitted signal is sent to the light source driving circuit. After D / A conversion, the transmitted signal drives the laser to transmit optical signals. At the same time, the clipping coefficient corresponding to each sample in the transmitted signal is sent to the receiving end as sideband information.

[0079] The receiving end steps are as follows:

[0080] S6. The photodetector receives the optical signal generated by the laser at the transmitting end and converts the optical signal into an electrical signal. The electrical signal is then converted into a digital signal by an A / D converter.

[0081] S7. The signal processor receives the digital signal and the clipping coefficient sent by the transmitter, removes the cyclic prefix before the digital signal, and obtains the deprecated signal. Based on the linear relationship revealed by the clipping process of the scaled signal, the clipping compensation module uses the clipping coefficient to adjust the deprecated signal. Perform inverse weighted compensation to obtain the compensated signal. The specific compensation method is as follows:

[0082]

[0083] In the formula, For the compensated signal The signal corresponding to the i-th Gaussian component in the signal, For deprecation signal The signal corresponding to the i-th Gaussian component.

[0084] S8. Perform serial-to-parallel conversion and FFT sequentially on the compensated signal to obtain the frequency domain signal; then, in order to compensate for the linear distortion caused by channel multipath effects, perform first-order equalization on the frequency domain signal to obtain the equalized signal; perform de-DFT precoding operation on the equalized signal, i.e., multiply by... The de-precoded signal is obtained; the de-precoded signal is demodulated using 16-QAM to recover the binary bit stream.

[0085] To better illustrate the beneficial effects of the present invention, numerical simulations were performed on the OFDM signal demodulation method proposed in this embodiment. The simulation parameters were set as follows:

[0086] Optical power limit C is 10mW, number of subcarriers N is 256, and noise power density is... The modulation scheme is 16-QAM, and the length of the cyclic prefix is ​​N. cp It is 32.

[0087] Taking the probability distribution model with a total number of Gaussian components K of 5 as an example, the schematic diagram of the resulting probability distribution model is shown in the reference. Figure 2 ,from Figure 2 It can be seen that the transmitted signal no longer follows a standard Gaussian distribution.

[0088] When the total number of Gaussian components K in the probability distribution model is 50, the simulation results are referenced. Figure 3 It should be noted that, Figure 3 The normalized power factor, shown on the horizontal axis, is the ratio of the power factor to the optical power limitation, used to characterize the relative clipping degree of the signal; from Figure 3 As can be seen, in the deep clipping region, the OFDM signal demodulation method proposed in this invention can effectively reduce the bit error rate, enabling the receiver to accurately recover the bit stream information sent by the transmitter and achieve effective communication.

[0089] The specific embodiments of the present invention are provided to enable those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention.

[0090] It should be understood that the present invention is not limited to the content already described above, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for demodulating OFDM signals in a wireless optical communication system, characterized in that, Includes both transmitting and receiving steps; The transmitting end steps include: S1. Generate a binary bit stream, and convert the binary bit stream into a complex symbol vector through constellation mapping; S2. Perform Hermitian symmetric processing on the complex-valued symbol vector to obtain a Hermitian symmetric signal; perform DFT precoding on the Hermitian symmetric signal to generate a precoded signal; and perform IFFT and parallel-to-serial conversion on the precoded signal in sequence to obtain a serial signal. S3. A power factor is introduced to scale the serial signal to obtain a scaled signal; S4. The probability distribution of the scaled signal is modeled using a Gaussian mixture model to obtain a probability distribution model. Based on the probability distribution model, the nonlinear distortion of the scaled signal during the clipping process is expressed as a weighted sum of the distortions of each Gaussian component, and a corresponding clipping coefficient is calculated for each Gaussian component in the probability distribution model. S5. Send the scaled signal and clipping coefficient to the receiving end; The receiving end steps include: S6. Receive the optical signal transmitted via the wireless optical channel and obtain the clipping coefficient transmitted by the transmitter. The optical signal is generated by the light source driven by the scaled signal. S7. First, convert the optical signal into an electrical signal, then convert the electrical signal into a digital signal, and use the clipping coefficient to perform inverse weighting compensation on the digital signal to obtain the compensated signal. S8. Demodulate the compensated signal to recover the binary bit stream.

2. The OFDM signal demodulation method for a wireless optical communication system according to claim 1, characterized in that, In S4, the probability density function of the probability distribution model is: In the formula, for The probability density function, This is the scaled signal. This represents the total number of Gaussian components in the probability distribution model. Let i be the weight of the i-th Gaussian component. Let be the mean of the i-th Gaussian component. Let be the standard deviation of the i-th Gaussian component.

3. The OFDM signal demodulation method for a wireless optical communication system according to claim 2, characterized in that, In S4, the formula for calculating the clipping coefficient is: In the formula, Let be the clipping coefficient corresponding to the i-th Gaussian component. for and Cross-correlation expectation, This is the signal corresponding to the i-th Gaussian component in the scaled signal. Let be the signal output by the clipping system under the i-th Gaussian component.

4. The OFDM signal demodulation method for a wireless optical communication system according to claim 1, characterized in that, The transmitting end step further includes: adding a cyclic prefix to the scaled signal before driving the light source to emit; the receiving end step further includes: removing the cyclic prefix from the digital signal before inverse weighting compensation.

5. The OFDM signal demodulation method for a wireless optical communication system according to claim 1, characterized in that, In S8, the method for demodulating the compensated signal includes: sequentially performing serial-to-parallel conversion and FFT on the compensated signal to obtain a frequency domain signal; performing first-order equalization on the frequency domain signal to obtain an equalized signal; performing a de-DFT precoding operation on the equalized signal to obtain a de-precoded signal; and demodulating the de-precoded signal.

6. The OFDM signal demodulation method for a wireless optical communication system according to claim 1, characterized in that, In S5, the clipping coefficient is transmitted as sideband information along with the scaled signal.

7. The OFDM signal demodulation method for a wireless optical communication system according to claim 1, characterized in that, In S7, the specific method for performing inverse weighted compensation of the digital signal using the clipping coefficient is as follows: divide the signal corresponding to each Gaussian component in the digital signal by its corresponding clipping coefficient.

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