A wireless optical communication and perception integrated system based on DCO-OTFS and an implementation method thereof

Abstract

The application discloses a wireless optical communication and sensing integrated system based on DCO-OTFS and an implementation method, relates to the technical field of wireless optical communication and sensing integration, and comprises the following steps: introducing orthogonal time-frequency-space OTFS modulation technology into the wireless optical communication and sensing integrated system, constructing a direct current bias light DCO-OTFS integrated sensing and communication system suitable for intensity modulation / direct detection by applying two-dimensional Hermite symmetry constraint in the delay-Doppler domain; designing the signal of the transmitting end of the direct current bias light DCO-OTFS integrated sensing and communication system, and generating a time-domain OTFS detection signal satisfying non-negative and real number constraints; processing the signal of the receiving end communication function, and deducing a theoretical bit error rate expression under a Málaga turbulence channel; processing the signal of the receiving end sensing function; by applying two-dimensional Hermite symmetry in the delay-Doppler domain, the application applies OTFS modulation to the wireless optical system of intensity modulation / direct detection, and solves the problem that the traditional complex baseband waveform cannot be directly applied.

Description

Technical Field

[0001] This invention relates to the field of wireless optical communication sensing integration technology, specifically to a wireless optical communication sensing integration system and implementation method based on DCO-OTFS. Background Technology

[0002] With the rapid development of 6G mobile communication and smart IoT technologies, future wireless systems not only need to support ultra-high-speed data transmission but also require real-time, high-precision perception capabilities of environmental targets. Integrated Communication-Sensing (ISAC) technology, by sharing hardware platforms, spectrum resources, and signal waveforms, achieves synergistic optimization of communication and sensing functions, and has become an important development direction for 6G networks. Compared to traditional discrete systems, ISAC can significantly improve spectrum utilization efficiency and system integration, and has broad application prospects in scenarios such as connected vehicles, unmanned systems, and smart cities.

[0003] In the field of wireless optical communication, intensity modulation / direct detection (IM / DD) systems have attracted widespread attention due to their advantages such as simple structure, low cost, and strong resistance to electromagnetic interference. However, IM / DD systems require the transmitted signal to be real and non-negative. This physical constraint makes it impossible to directly apply complex-valued modulation waveforms widely used in the radio frequency (RF) field to wireless optical scenarios. Currently, optical orthogonal frequency division multiplexing (OOFDM) and its improved forms are widely used in wireless optical communication and preliminary integrated sensing system design. Although OOFDM has good resistance to frequency-selective fading and high spectral efficiency, it requires the introduction of DC bias to meet the non-negative transmission condition, resulting in reduced power utilization. At the same time, in high-speed moving or strong turbulent environments, OOFDM is susceptible to time-varying multipath and Doppler spread, leading to a significant deterioration in system performance. Furthermore, when the system expands from a single communication function to a fusion of sensing and communication, traditional OFDM waveforms have inherent limitations in terms of delay and Doppler resolution, making it difficult to meet the requirements of high-precision sensing.

[0004] Orthogonal Time-Frequency Spatial Modulation (OTFS), a novel modulation technique defined in the delay-Doppler domain, maps information symbols to the delay-Doppler domain and generates time-frequency domain signals through a two-dimensional transformation. This enables more stable channel representation in highly dynamic channels, fully utilizing multipath diversity gain and exhibiting superior bit error rate performance and robustness compared to OFDM in time-varying channel environments. Therefore, OTFS is considered a potential key technology for highly mobile integrated communication and sensing systems. However, traditional OTFS signals are bipolar complex signals, which cannot directly satisfy the real-valued non-negativity constraint of IM / DD systems. While recent research has explored the construction of DCO-OTFS systems by introducing a two-dimensional Hermitian symmetric structure in the delay-Doppler domain and combining it with DC bias technology, making them suitable for optical communication scenarios, this work has primarily focused on communication performance analysis. Systematic research on deeply integrating OTFS modulation into integrated wireless optical communication and sensing systems to achieve unified modeling and optimization of communication and sensing performance remains lacking.

[0005] Therefore, how to effectively introduce OTFS modulation into wireless optical ISAC systems while meeting the physical constraints of IM / DD signals, and achieve a synergistic improvement in high-reliability communication and high-resolution sensing, has become a key technical problem that urgently needs to be solved. Summary of the Invention

[0006] To address the shortcomings of existing wireless optical communication and sensing integrated systems in terms of waveform design, power efficiency, and sensing resolution, this invention provides a wireless optical communication and sensing integrated system and its implementation method based on DCO-OTFS. The aim is to improve the communication reliability and sensing accuracy of the system in turbulent channels while meeting the non-negative and real number constraints of the transmitted signal in the optical intensity modulation / direct detection system, thereby achieving efficient integration of communication and sensing functions.

[0007] The technical solution adopted by this invention to solve its technical problem is:

[0008] A wireless optical communication and sensing integrated system based on DCO-OTFS includes a transmitter, a communication receiver, and a sensing receiver.

[0009] The transmitter includes:

[0010] The signal generation module is configured to apply a two-dimensional Hermitian symmetry constraint to the information symbols after quadrature amplitude modulation (QAM) in the delay-Doppler domain to generate a delay-Doppler domain symbol matrix that satisfies the symmetry.

[0011] The transformation module is configured to sequentially perform inverse symmetric finite Fourier transform and Heisenberg transform on the symmetric delay-Doppler domain symbol matrix to generate a time-domain bipolar signal.

[0012] A DC bias module is configured to add a DC bias to the time-domain bipolar signal to form a DCO-OTFS probe signal that satisfies the non-negative, real number constraints.

[0013] A light source is configured to transmit the DCO-OTFS detection signal to a wireless optical channel, wherein the DCO-OTFS detection signal simultaneously carries communication information and serves as a sensing and detection waveform.

[0014] The communication receiving end includes:

[0015] A first photodetector is configured to receive the DCO-OTFS detection signal and convert it into a first electrical signal;

[0016] The first processing module is configured to sequentially perform Wigner transform and symmetric finite Fourier transform on the first electrical signal to recover the delay-Doppler domain communication symbols, and to perform channel equalization and demapping on the delay-Doppler domain communication symbols to recover the original communication information.

[0017] The sensing receiver, either integrated into the transmitter or set up independently, includes:

[0018] A second photodetector is configured to receive the echo signal of the DCO-OTFS detection signal reflected by the target and convert it into a second electrical signal;

[0019] The perception processing module is configured to perform matched filtering with the second electrical signal using a copy of the DCO-OTFS detection signal, and to estimate the target's time delay and Doppler parameters by calculating a fuzzy function and performing peak detection on the fuzzy function.

[0020] The two-dimensional Hermitian symmetric constraint includes: for the independent information symbol positions in the delay-Doppler domain grid, satisfying... For the symmetrical position of independent information symbols, the following conditions are met: ,in, and These represent the discretization sizes for the delay domain and the Doppler domain, respectively. For symbolic coordinates, For modulo operation, This is a complex conjugate operation.

[0021] The implementation method of the DCO-OTFS-based wireless optical communication sensing integrated system includes the following steps:

[0022] Step S1: Introduce the orthogonal time-frequency space-time OTFS modulation technology into the wireless optical communication and sensing integrated system. By applying two-dimensional Hermitian symmetry constraints in the delay-Doppler domain, a DC biased optical DCO-OTFS integrated sensing and communication system suitable for intensity modulation / direct detection is constructed.

[0023] Step S2: Design the signal of the transmitter of the DC biased optical DCO-OTFS integrated sensing and communication system to generate a time-domain OTFS detection signal that satisfies the non-negative, real number constraints, which is used to simultaneously transmit communication data and sense target information;

[0024] Step S3: Process the signal of the receiver's communication function, derive the theoretical bit error rate expression under the Málaga turbulent channel, and recover the original bit information through receiver processing;

[0025] Step S4: Process the signal of the receiving end sensing function, derive the closed-form expression of the system ambiguity function, and extract the target's time delay and Doppler frequency shift parameters through matched filtering to achieve high-precision sensing.

[0026] Furthermore, in the DCO-OTFS integrated sensing and communication system of step S1, the signal generation process includes the following steps:

[0027] S11: Perform quadrature amplitude modulation (QAM) on the binary bit sequence to be transmitted, and map it into a two-dimensional information symbol in the delay-Doppler domain;

[0028] S12: To meet the requirements of non-negative and real signals in the optical intensity modulation / direct detection system, a two-dimensional Hermitian symmetry constraint is applied to the QAM symbols in the delay-Doppler domain to obtain a delay-Doppler domain symbol matrix with conjugate symmetry characteristics.

[0029] S13: Transform the delayed-Doppler domain symbols that satisfy symmetry constraints to the time-frequency domain using the inverse symmetric finite Fourier transform;

[0030] S14: By using the Heisenberg transform and employing a transmit pulse shaping filter, the time-frequency domain symbol is converted into a complex baseband time-domain continuous signal;

[0031] S15: Take the real part of the complex baseband time-domain signal and add a DC bias sufficient to ensure the non-negativity of the signal to generate a unipolar real signal suitable for laser intensity modulation, namely the DCO-OTFS signal, and emit it through the laser.

[0032] Furthermore, in step S2, after the DCO-OTFS transmitted signal is transmitted through the wireless optical channel, the processing at the receiving end includes the following steps:

[0033] S21: The DCO-OTFS transmitted signal is transmitted through a wireless optical channel containing the Málaga turbulence effect, then received by a photodetector and directly detected by the square law, and converted into an electrical signal.

[0034] S22: Perform a Wigner transform on the received electrical signal to convert it from the time domain back to the time-frequency domain;

[0035] S23: Apply the symplectic finite Fourier transform to the time-frequency domain signal to convert it back to the delay-Doppler domain, and obtain a two-dimensional symbol containing channel effects and noise;

[0036] S24: For the communication receiver (device B), channel equalization and QAM demapping are performed on the delay-Doppler domain symbols to recover the original binary bit stream;

[0037] S25: For the sensing receiver (device A), the stored copy of the transmitted signal is matched and filtered with the received reflected signal to calculate the ambiguity function. The distance and relative velocity of the target are estimated by analyzing the peak position of the ambiguity function.

[0038] Furthermore, in step S3, the theoretical analysis process of communication performance includes: deriving the instantaneous signal-to-noise ratio of the system in the delay-Doppler domain under ideal channel equalization conditions; combining the probability density function of the Málaga turbulent channel, obtaining the closed-form expression of the average bit error rate of the system under the turbulent channel by statistically averaging the instantaneous bit error rate, thus providing a theoretical basis for evaluating the system's communication performance.

[0039] Furthermore, in step S4, the theoretical analysis process of sensing performance includes: substituting the transmitted OTFS waveform into the definition of the ambiguity function, deriving that it can be expressed as a weighted superposition of the time-frequency domain symbol power and the transmitted pulse ambiguity function; this expression reveals that the OTFS waveform ambiguity function has high resolution characteristics in the delay-Doppler domain, theoretically proving its potential for high-precision sensing.

[0040] Furthermore, the method also includes: verifying the bit error rate performance of the system under different turbulence intensities (weak, medium, and strong) through simulation and comparing it with the traditional DCO-OFDM scheme, proving that the DCO-OTFS scheme proposed in this invention has a signal-to-noise ratio gain of about 3dB in communication performance; by comparing the zero-delay section and zero-Doppler section of the ambiguity function of DCO-OTFS and DCO-OFDM, proving that the scheme proposed in this invention has a lower sidelobe level and a sharper main lobe in the delay and Doppler domains, thereby having higher accuracy and stronger anti-interference capability in distance and velocity estimation.

[0041] Compared with existing technologies, the beneficial effects of this invention are as follows: First, by applying two-dimensional Hermitian symmetry in the delay-Doppler domain, this invention applies OTFS modulation to intensity modulation / direct detection wireless optical systems, solving the problem that traditional complex baseband waveforms cannot be directly applied. Second, through a comprehensive theoretical analysis of the system's communication and sensing performance, closed-form expressions for the bit error rate and ambiguity function are derived, providing a theoretical basis for system design. Finally, simulation results show that, compared with traditional OFDM schemes, the method proposed in this invention significantly improves the sensing resolution and parameter estimation accuracy in the delay-Doppler domain while ensuring reliable communication, providing a new and effective technical path for the design of wireless optical integrated sensing and communication systems. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a model diagram of the DCO-OTFS wireless optical communication and sensing integrated system described in this invention;

[0044] Figure 2 This is a comparison chart of the theoretical bit error rate and simulation results of the system described in this invention under weak, medium and strong Málaga turbulence conditions;

[0045] Figure 3 This is a comparison chart of the bit error rate performance of the DCO-OTFS system and the DCO-OFDM system described in this invention under weak turbulence conditions;

[0046] Figure 4 This is a comparison diagram of the zero-Doppler cross-sectional ambiguity function of the DCO-OTFS system and the DCO-OFDM system at the sensing receiver end of the present invention;

[0047] Figure 5 This is a comparison diagram of the zero-delay section ambiguity function of the DCO-OTFS system and the DCO-OFDM system at the sensing receiver end described in this invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0049] Example 1: This example provides a wireless optical communication and sensing integrated system based on DCO-OTFS, including a transmitter, a communication receiver, and a sensing receiver;

[0050] The transmitter includes:

[0051] The signal generation module is configured to apply a two-dimensional Hermitian symmetry constraint to the information symbols after quadrature amplitude modulation (QAM) in the delay-Doppler domain to generate a delay-Doppler domain symbol matrix that satisfies the symmetry.

[0052] The transformation module is configured to sequentially perform inverse symmetric finite Fourier transform and Heisenberg transform on the delay-Doppler domain symbol matrix that satisfies symmetry, generating a time-domain bipolar signal.

[0053] A DC bias module is configured to add a DC bias to the time-domain bipolar signal to form a DCO-OTFS probe signal that satisfies the non-negative, real number constraints.

[0054] A light source is configured to transmit the DCO-OTFS detection signal to a wireless optical channel, wherein the DCO-OTFS detection signal simultaneously carries communication information and serves as a sensing and detection waveform.

[0055] The communication receiving end includes:

[0056] A first photodetector is configured to receive the DCO-OTFS detection signal and convert it into a first electrical signal;

[0057] The first processing module is configured to sequentially perform Wigner transform and symmetric finite Fourier transform on the first electrical signal to recover the delay-Doppler domain communication symbols, and to perform channel equalization and demapping on the delay-Doppler domain communication symbols to recover the original communication information.

[0058] The sensing receiver, either integrated into the transmitter or set up independently, includes:

[0059] A second photodetector is configured to receive the echo signal of the DCO-OTFS detection signal reflected by the target and convert it into a second electrical signal;

[0060] The perception processing module is configured to perform matched filtering with the second electrical signal using a copy of the DCO-OTFS detection signal, and to estimate the target's time delay and Doppler parameters by calculating a fuzzy function and performing peak detection on the fuzzy function.

[0061] The two-dimensional Hermitian symmetric constraint includes: for the independent information symbol positions in the delay-Doppler domain grid, satisfying... For the symmetrical position of independent information symbols, the following conditions are met: ,in, and These represent the discretization sizes for the delay domain and the Doppler domain, respectively. For symbolic coordinates, For modulo operation, This is a complex conjugate operation.

[0062] Example 2: This example provides a method for implementing a wireless optical communication sensing integrated system based on DCO-OTFS. Its system model is as follows: Figure 1 As shown in the diagram, in a one-way ISAC scenario, device A acts as both a communication transmitter and a sensing transceiver, while device B acts only as a communication receiver. Device A transmits a DCO-OTFS signal via a laser diode, and device B's photodiode receives and demodulates this signal to recover the communication data. Simultaneously, a portion of the transmitted signal is reflected by device B and captured by device A's photodiode, thereby enabling the estimation of the distance and relative speed between devices A and B.

[0063] Step 1: Define system parameters and generate transmitted information: Consider a wireless optical communication and sensing integrated system using DCO-OTFS modulation. Its key parameters are set as follows: delay domain discretization size. Doppler domain discretization size OTFS subcarrier count QAM modulation order Subcarrier spacing Symbol duration The transmitting end (device A) randomly generates a binary bit sequence. , as the original communication data.

[0064] Step 2: Generation of DCO-OTFS signal at the transmitting end: The binary bit sequence is modulated with 4-QAM and mapped to two-dimensional information symbols in the delay-Doppler domain. ,in , , For QAM constellation point set.

[0065] To satisfy the constraints of non-negative, real-valued transmitted signals in intensity modulation / direct detection (IM / DD) systems, a two-dimensional Hermitian symmetry is applied to the delay-Doppler domain symbols. Specifically, this symmetry operation involves dividing the delay-Doppler domain mesh into regions carrying independent information and regions Hermitian symmetric to them. For independent information symbols, the following holds:

[0066] ;

[0067] For its corresponding symmetrical position, the sign value must satisfy:

[0068] ;

[0069] in, and These represent the discretization sizes for the delay domain and the Doppler domain, respectively. The coordinates of the symbol in the grid. For modulo operation, This is a complex conjugate operation. This constraint is crucial to ensuring that the subsequently generated time-domain signal is a real number.

[0070] Then, the symmetric delayed-Doppler domain symbol is obtained by inverse symmetric finite Fourier transform (ISFFT). Transform to the time-frequency domain:

[0071] ;

[0072] in, Time index (range of values) arrive ), Frequency index (range of values) arrive ), and These correspond to the number of time slots and the number of subcarriers, respectively, in this embodiment. , .

[0073] Next, the Heisenberg transform is used to map the time-frequency domain symbols into a continuous time-domain baseband signal:

[0074] ;

[0075] in For transmitting pulse shaping filters, rectangular pulses are typically used.

[0076] Next, the real part of the baseband signal is extracted and a DC bias is added. To ensure the signal is non-negative:

[0077] ;

[0078] in This indicates the real part operation, and the bias is applied. satisfy:

[0079] ;

[0080] The final result This is the DCO-OTFS signal, emitted via a laser. This signal simultaneously carries communication information and serves as a sensing and detection signal.

[0081] Step 3: Channel Transmission: The transmitted signal passes through an atmospheric turbulence channel, and the turbulence effect is modeled using the Málaga distribution. The optical signal received by the receiving end (the communication receiver of device B or the sensing receiver of device A) can be represented as:

[0082] ;

[0083] in This represents additive white Gaussian noise. The Málaga turbulent fading coefficient, whose probability density function (PDF) can be expressed as:

[0084] ;

[0085] in Indicates large-scale turbulence, This indicates small-scale turbulence. Corresponding to the light intensity scalar, It is a modified Bessel function, and These are parameters used for PDF normalization, and can be expressed as:

[0086] ,

[0087] ;

[0088] Step 4: Communication Receiver Processing: The photodetector of Device B performs direct square-law detection and outputs an electrical signal:

[0089] ;

[0090] in The responsivity of a photodetector is expressed in A / W. This represents thermal noise, which is usually modeled as additive white Gaussian noise.

[0091] right A Wigner transform is performed, which is achieved through a filter bank matched to the transmitted pulse, to obtain the time-frequency domain symbol:

[0092] ;

[0093] in, To emit shaped pulses The conjugate of , and the integration interval is the entire symbol period.

[0094] Next, the symplectic finite Fourier transform (SFFT) is applied to convert the time-frequency domain symbols back to the delay-Doppler domain:

[0095] ;

[0096] This transformation is the inverse process of the transmitter's ISFFT, aiming to map the received signal back to the original delay-Doppler domain grid points. superior.

[0097] Step 5: Sensing Receiver Processing: At the sensing receiver (device A), the stored copy of the transmitted signal is processed... With the received echo signal Matched filtering is performed by calculating a fuzzy function, which is defined as follows:

[0098] ;

[0099] in, This indicates the time delay of the echo signal relative to the transmitted signal, expressed through... Calculate the target distance ( (speed of light) This represents the Doppler frequency shift caused by the relative motion of the target, through... The relative velocity of the target can be calculated. ( (The wavelength is the laser wavelength). The sensing and processing module detects... To estimate the peak position and .

[0100] Step 6: Communication Performance Analysis: After performing Wigner distribution and SFFT at the receiver, the equivalent input-output relationship of the system in the delay-Doppler domain can be expressed as:

[0101] ;

[0102] in Represents a two-dimensional circular convolution. For the equivalent channel response, The noise is then converted to QAM demapping of the symbols after equalization to recover the transmitted binary bit sequence.

[0103] Under ideal channel estimation and equalization conditions (such as using a minimum mean square error MMSE equalizer), the delay-Doppler domain symbol can be approximated as being transmitted over an additive white Gaussian noise channel, and its instantaneous signal-to-noise ratio can be expressed as:

[0104] ;

[0105] in This represents the average transmitted symbol power, and its value is determined by the average energy of the modulation constellation diagram. The Málaga turbulence fading coefficient is a random variable; while This represents the equivalent noise power, including the contributions of thermal noise and shot noise.

[0106] For M-QAM modulation, given an instantaneous signal-to-noise ratio The corresponding bit error rate can be approximated as:

[0107] ;

[0108] in Represents the Q function, Indicates the modulation order.

[0109] Due to the random fading characteristics of the Málaga channel, the system's average bit error rate is obtained by averaging the channel's statistical characteristics, i.e.:

[0110] ;

[0111] in PDF representing the Málaga turbulence channel.

[0112] Step 7: Perception Performance Analysis: In perception mode, the system uses communication waveforms as detection signals and estimates target parameters through matched filtering. The corresponding fuzzy function is defined as:

[0113] ;

[0114] By using the Heisenberg expression of the DCO-OTFS waveform (i.e., in step 2) Substituting the expression into the above equation, and utilizing the orthogonality of pulse functions, the ambiguity function can be approximately represented as a weighted superposition of the time-frequency domain symbol power spectrum and the transmitted pulse ambiguity function:

[0115] ;

[0116] in Indicates the emission of a shaped pulse The self-fuzzy function is defined as:

[0117] ;

[0118] This expression shows that the overall blur function of the OTFS waveform is determined by the two-dimensional convolution of the symbol energy allocated on the time-frequency resource grid with the basic pulse blur function, thus achieving high resolution in both the delay domain and the Doppler domain.

[0119] Step 8: Simulation Verification and Result Analysis: To verify the effectiveness of the present invention, simulations were performed on the MATLAB platform. The simulation parameters are shown in Table 1, and the Málaga turbulence channel parameters are shown in Table 2.

[0120] Table 1 Summary of Simulation Parameters

[0121]

[0122] Table 2 Málaga Turbulence Channel Parameters

[0123]

[0124] Figure 2 The theoretical bit error rate (BER) and simulation performance under weak, medium, and strong Málaga turbulence conditions were compared. It can be observed that the theoretical analysis and simulation results are in high agreement in the low signal-to-noise ratio (SNR) region, while a slight deviation occurs at high SNR. Nevertheless, the overall trend remains consistent, verifying the effectiveness of the derived BER expression. Further comparison of different turbulence intensities shows that, at the same BER level, the system under weak turbulence achieves approximately 8.6 dB of SNR gain compared to strong turbulence, and approximately 3.8 dB of gain compared to medium turbulence. This indicates that turbulence intensity has a significant impact on BER performance.

[0125] Figure 3 This paper compares the bit error rate (BER) performance of OTFS and OFDM under weak turbulence conditions. It can be observed that OTFS consistently outperforms OFDM in BER performance for both DCO and ACO schemes. Specifically, at the same BER level, DCO-OTFS achieves approximately 3 dB of SNR gain compared to DCO-OFDM, while ACO-OTFS provides approximately 4 dB of SNR gain compared to ACO-OFDM. This demonstrates that OTFS exhibits superior robustness in weak turbulence channels.

[0126] Figure 4 The zero-Doppler cross-section of the ambiguity function at the sensing receiver is shown, reflecting the system's range estimation accuracy. It can be observed that the main lobe widths of DCO-OTFS and DCO-OFDM are approximately equal and relatively narrow, indicating that both possess high time-delay resolution and the ability to distinguish targets with small spacing. However, the sidelobe level of DCO-OTFS is significantly lower than that of DCO-OFDM, demonstrating that OTFS outperforms OFDM in interference suppression and weak target detection.

[0127] Figure 5 The zero-delay cross-section of the blurring function at the sensing receiver is shown, which directly reflects the waveform's resolution in the Doppler domain, i.e., the accuracy of velocity estimation. It can be clearly observed that the main lobe of DCO-OTFS is sharper than that of DCO-OFDM, and its sidelobe level is lower. This indicates that DCO-OTFS achieves better energy concentration in the Doppler domain, enabling more accurate estimation and differentiation of targets with different velocities, while significantly reducing the risk of weak targets being masked by the sidelobes of strong targets, thus improving detection reliability in multi-target scenarios. Therefore, compared to DCO-OFDM, DCO-OTFS offers superior performance in both velocity estimation accuracy and robustness.

[0128] Of course, the above description is not limited to the examples above. Technical features not described in this invention can be implemented by or using existing technology, and will not be repeated here. The above embodiments and drawings are only used to illustrate the technical solutions of this invention and are not intended to limit this invention. This invention has been described in detail with reference to preferred embodiments. Those skilled in the art should understand that any changes, modifications, additions or substitutions made by those skilled in the art within the scope of this invention do not depart from the spirit of this invention and should also fall within the scope of protection of the claims of this invention.

Claims

1. A wireless optical communication and sensing integrated system based on DCO-OTFS, characterized in that, This includes the transmitting end, the communication receiving end, and the sensing receiving end; The transmitter includes: The signal generation module is configured to apply a two-dimensional Hermitian symmetry constraint to the orthogonally amplitude-modulated information symbols in the delay-Doppler domain to generate a delay-Doppler domain symbol matrix that satisfies the symmetry. The transformation module is configured to sequentially perform inverse symmetric finite Fourier transform and Heisenberg transform on the symmetric delay-Doppler domain symbol matrix to generate a time-domain bipolar signal. A DC bias module is configured to add a DC bias to the time-domain bipolar signal to form a DCO-OTFS probe signal that satisfies the non-negative, real number constraints. A light source is configured to transmit the DCO-OTFS detection signal to a wireless optical channel, wherein the DCO-OTFS detection signal simultaneously carries communication information and serves as a sensing and detection waveform. The communication receiving end includes: A first photodetector is configured to receive the DCO-OTFS detection signal and convert it into a first electrical signal; The first processing module is configured to sequentially perform Wigner transform and symmetric finite Fourier transform on the first electrical signal to recover the delay-Doppler domain communication symbols, and to perform channel equalization and demapping on the delay-Doppler domain communication symbols to recover the original communication information. The sensing receiver, either integrated into the transmitter or set up independently, includes: A second photodetector is configured to receive the echo signal of the DCO-OTFS detection signal reflected by the target and convert it into a second electrical signal; The sensing processing module is configured to perform matched filtering with the second electrical signal using a copy of the DCO-OTFS detection signal, and to estimate the target's time delay and Doppler parameters by calculating an ambiguity function and performing peak detection on the ambiguity function.

2. The wireless optical communication and sensing integrated system based on DCO-OTFS according to claim 1, characterized in that, The two-dimensional Hermitian symmetry constraint includes: for the independent information symbol positions in the delay-Doppler domain grid, satisfying... For the symmetrical position of independent information symbols, the following conditions are met: ,in, and These represent the discretization sizes for the delay domain and the Doppler domain, respectively. For symbolic coordinates, For modulo operation, This is a complex conjugate operation.

3. A method for implementing a wireless optical communication and sensing integrated system based on DCO-OTFS, characterized in that, Includes the following steps: Step S1: Introduce the orthogonal time-frequency space-time OTFS modulation technology into the wireless optical communication and sensing integrated system. By applying two-dimensional Hermitian symmetry constraints in the delay-Doppler domain, a DC biased optical DCO-OTFS integrated sensing and communication system suitable for intensity modulation / direct detection is constructed. Step S2: Design the signal of the transmitter of the DC biased optical DCO-OTFS integrated sensing and communication system to generate a time-domain OTFS detection signal that satisfies the non-negative, real number constraints, which is used to simultaneously transmit communication data and sense target information; Step S3: Process the signal of the receiver's communication function, derive the theoretical bit error rate expression under the Málaga turbulent channel, and recover the original bit information through receiver processing; Step S4: Process the signal of the receiving end sensing function, derive the closed-form expression of the system ambiguity function, and extract the target's time delay and Doppler frequency shift parameters through matched filtering to achieve high-precision sensing.

4. The implementation method of the wireless optical communication sensing integrated system based on DCO-OTFS according to claim 3, characterized in that, In the DCO-OTFS integrated sensing and communication system in step S1, the signal generation process includes the following steps: S11: Perform quadrature amplitude modulation (QAM) on the binary bit sequence to be transmitted, and map it into a two-dimensional information symbol in the delay-Doppler domain; S12: To meet the requirements of non-negative and real signals in the optical intensity modulation / direct detection system, a two-dimensional Hermitian symmetry constraint is applied to the QAM symbols in the delay-Doppler domain to obtain a delay-Doppler domain symbol matrix with conjugate symmetry characteristics. S13: Transform the delayed-Doppler domain symbols that satisfy symmetry constraints to the time-frequency domain using the inverse symmetric finite Fourier transform; S14: By using the Heisenberg transform and employing a transmit pulse shaping filter, the time-frequency domain symbol is converted into a complex baseband time-domain continuous signal; S15: Take the real part of the complex baseband time-domain signal and add a DC bias sufficient to ensure the non-negativity of the signal to generate a unipolar real signal suitable for laser intensity modulation, namely the DCO-OTFS signal, and emit it through the laser.

5. The implementation method of the wireless optical communication sensing integrated system based on DCO-OTFS according to claim 3, characterized in that, In step S2, after the DCO-OTFS transmitted signal is transmitted through the wireless optical channel, the processing at the receiving end includes the following steps: S21: The DCO-OTFS transmitted signal is transmitted through a wireless optical channel containing the Málaga turbulence effect, then received by a photodetector and directly detected by the square law, and converted into an electrical signal. S22: Perform a Wigner transform on the received electrical signal to convert it from the time domain back to the time-frequency domain; S23: Apply the symplectic finite Fourier transform to the time-frequency domain signal to convert it back to the delay-Doppler domain, and obtain a two-dimensional symbol containing channel effects and noise; S24: For the communication receiver, channel equalization and QAM demapping are performed on the delay-Doppler domain symbols to recover the original binary bit stream; S25: For the sensing receiver, the stored copy of the transmitted signal is matched and filtered with the received reflected signal to calculate the ambiguity function. The distance and relative velocity of the target are estimated by analyzing the peak position of the ambiguity function.

6. The implementation method of the wireless optical communication sensing integrated system based on DCO-OTFS according to claim 3, characterized in that, In step S3, the theoretical analysis process of communication performance includes: deriving the instantaneous signal-to-noise ratio of the system in the delay-Doppler domain under ideal channel equalization conditions; and obtaining a closed-form expression for the average bit error rate of the system under turbulent channels by statistically averaging the instantaneous bit error rate, in combination with the probability density function of the Málaga turbulent channel.

7. The implementation method of the wireless optical communication sensing integrated system based on DCO-OTFS according to claim 3, characterized in that, In step S4, the theoretical analysis process of sensing performance includes: substituting the transmitted OTFS waveform into the definition of the ambiguity function, and deriving that it can be expressed as a weighted superposition of the time-frequency domain symbol power and the transmitted pulse ambiguity function.

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