Optical communication receiving and data recovery method for space division multiple access many-to-many communication

Abstract

The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical communication receiving and data recovery methods for space division multiple access multi-to-multi communication, it is related to optical communication receiving technical field.The application discloses a kind of optical

Description

Technical Field

[0001] This invention relates to the field of optical communication receiving technology, and more specifically to an optical communication receiving and data recovery method for space division multiple access many-to-many communication. Background Technology

[0002] In high-density network scenarios such as vehicle-to-everything (V2X) communication and indoor visible light communication, spatial division multiple access (SDMA) technology is widely used to achieve many-to-many concurrent communication. In many-to-many communication systems, a transmitter (such as a Micro-LED array vehicle light) needs to send independent data streams to multiple receivers in different spatial locations simultaneously, or a receiver needs to receive optical signals from multiple transmitters simultaneously.

[0003] However, due to ambient light interference, overlapping and crosstalk between light spots in different spatial channels, and the dynamic relative motion between the receiver and transmitter, it is extremely challenging for the receiver to accurately separate and extract information from the respective target channels in a complex mixed optical field. Existing technologies lack a complete mechanism for parallel extraction, synchronization, and decision-making of multiple channels in multi-to-multi spatial division multiple access scenarios, making it difficult to guarantee the stability and low bit error rate of data recovery when multiple nodes communicate concurrently. Summary of the Invention

[0004] The purpose of this invention is to provide an optical communication reception and data recovery method for space-division multiple access (SDMA) multi-to-multiple communication. Addressing the multi-channel reception requirements of SDMA parallel optical communication systems, a complete signal extraction, synchronization decision, and verification recovery process is designed. This method first extracts the signal of the corresponding physical channel from the optical signal according to the target reception direction, avoiding crosstalk interference from adjacent channels. Using a preset synchronization sequence for sliding correlation detection, the frame start position can be accurately determined, achieving reliable synchronization even in low signal-to-noise ratio environments. By combining integral averaging within the symbol period with an adaptive decision threshold, the impact of noise and baseline drift on the decision is effectively suppressed. Finally, frame parsing and a check field verify data integrity, ensuring the correctness of the output data. Compared with general optical reception methods, this invention fully considers the characteristics of SDMA multi-to-multiple concurrent transmission. By selecting and processing multiple regions of interest (ROIs) in parallel in the image acquired by the imaging sensor, this invention can simultaneously separate and receive independent data streams from different spatial directions, perfectly supporting 'one-to-many' or 'many-to-many' multi-to-multiple communication architectures. This solution boasts strong anti-crosstalk capabilities, strong synchronization, and low error rate, making it particularly suitable for high-reliability concurrent communication needs such as dynamically changing vehicle-road cooperative multi-vehicle platoons or dense intersections.

[0005] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides an optical communication receiving and data recovery method for space division multiple access many-to-many communication, the method comprising: The system receives optical signals and extracts the corresponding physical channel signal from the optical signals according to the target receiving direction. The corresponding physical channel is the optical signal emitted by the pixel area in the Micro-LED array of the transmitter that corresponds to the target receiving direction. The extracted signal is sampled at a sampling frequency higher than the symbol rate to obtain a discrete time series; Sliding correlation calculation is performed on discrete time series based on a preset synchronization sequence, and the starting position of the data frame is determined when the correlation value exceeds a preset threshold. The discrete-time series is integrated or averaged according to the symbol period to obtain the decision value of each symbol, and the decision value is binarized based on the decision threshold to recover the bit sequence. The bit sequence is parsed according to the preset frame structure to extract the version field, data stream identifier field, sequence field, length field, payload field and check field; The load field is validated based on the validation field, and the recovery data is output when the validation passes.

[0006] In some embodiments, extracting the signal corresponding to the physical channel based on the target receiving direction includes: When an imaging sensor is used as the receiving device, a spatial region of interest corresponding to the target receiving direction is selected in the continuous image frames acquired by the imaging sensor. The pixel grayscale values ​​within the spatial region of interest are summed or weighted to obtain a single received value for each image frame. The received values ​​of consecutive image frames are arranged in chronological order to form the received signal sequence of the corresponding physical channel.

[0007] In some embodiments, sampling the extracted signal at a sampling frequency higher than the symbol rate includes: Each symbol period contains M sampling points, where M is an integer greater than or equal to 4; When an imaging sensor is used for reception, the sampling frequency is determined by the frame rate of the image sensor, and the number of image frames corresponding to each symbol period is M.

[0008] In some embodiments, performing sliding correlation calculations based on a preset synchronization sequence includes: The preset synchronization sequence and the discrete time sequence are subjected to a sliding inner product operation point by point starting from the starting point to obtain the correlation value sequence. Record the maximum value in the relevant value sequence and its corresponding sliding position; When the maximum value exceeds the preset threshold, the sliding position corresponding to the maximum value is taken as the starting position of the data frame; otherwise, the sliding search continues.

[0009] In some embodiments, obtaining the decision value for each symbol and binarizing it based on a decision threshold includes: For each symbol period, calculate the arithmetic mean or geometric mean of the M sample points, and use it as the decision value for that symbol. The decision threshold is either a fixed threshold or adaptively calculated based on the median of the average of the sign decision values ​​corresponding to logic "1" and the average of the sign decision values ​​corresponding to logic "0" in the synchronization sequence. When the number of judgments is greater than the judgment threshold, it is judged as logical "1"; otherwise, it is judged as logical "0".

[0010] In some embodiments, preprocessing and postprocessing steps are also included: Before calculating the decision value, the discrete time series is sequentially subjected to moving average filtering and finite impulse response low-pass filtering to suppress high-frequency noise and crosstalk components from adjacent physical channels. After parsing the bit sequence, a cyclic redundancy check is performed on the check field. If the check passes, the payload field is reassembled based on the sequence field. If the check fails, the current frame is discarded, and a retransmission request is triggered or the system waits for the next frame.

[0011] Secondly, the present invention also provides an optical communication receiving and data recovery apparatus for space division multiple access many-to-many communication, the apparatus comprising: The signal extraction module is used to receive optical signals and extract the corresponding physical channel signals from the optical signals according to the target receiving direction. The corresponding physical channel is the optical signal emitted by the pixel area in the Micro-LED array of the transmitter that corresponds to the target receiving direction. The signal sampling module is used to sample the extracted signal at a sampling frequency higher than the symbol rate to obtain a discrete time series. The correlation calculation module is used to perform sliding correlation calculation on discrete time series based on a preset synchronization sequence, and to determine the starting position of the data frame when the correlation value exceeds a preset threshold. The sequence processing module is used to integrate or average the discrete time sequence according to the symbol period to obtain the decision value of each symbol, and to binarize the decision value based on the decision threshold to recover the bit sequence. The structure parsing module is used to parse the bit sequence according to the preset frame structure and extract the version field, data stream identifier field, sequence field, length field, payload field and check field; The field validation module is used to validate the payload field according to the validation field, and output the recovery data when the validation passes.

[0012] Thirdly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the optical communication receiving and data recovery method for space division multiple access many-to-many communication provided in the first aspect.

[0013] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the optical communication reception and data recovery method for space-division multiple access many-to-many communication provided in the first aspect.

[0014] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the optical communication reception and data recovery method for space division multiple access many-to-many communication provided in the first aspect.

[0015] The beneficial effects of this invention are as follows: This invention provides an optical communication reception and data recovery method for space-division multiple access (SDMA) many-to-many communication. Addressing the multi-channel reception requirements of parallel optical communication systems with SDMA, it designs a complete signal extraction, synchronization decision, and verification recovery process. This method first extracts the signal of the corresponding physical channel from the optical signal according to the target reception direction, avoiding crosstalk interference from adjacent channels. Using a preset synchronization sequence for sliding correlation detection, the frame start position can be accurately determined, achieving reliable synchronization even in low signal-to-noise ratio environments. By combining integral averaging within the symbol period with an adaptive decision threshold, the influence of noise and baseline drift on the decision is effectively suppressed. Finally, frame parsing and a check field verify data integrity, ensuring the correctness of the output data. Compared with general optical reception methods, this invention fully considers the characteristics of concurrent transmission across multiple physical channels, possessing advantages such as anti-crosstalk, strong synchronization, and low bit error rate, making it particularly suitable for the high-reliability communication requirements in dynamically changing vehicle-to-infrastructure (V2I) scenarios.

[0016] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an optical communication receiving and data recovery method for space division multiple access many-to-many communication according to an embodiment of the present invention; Figure 2 This is a schematic diagram comparing waveforms before and after noise reduction according to an embodiment of the present invention; Figure 3 This is a schematic diagram comparing the waveforms before and after filtering according to an embodiment of the present invention; Figure 4This is a schematic diagram of the structure of an optical communication receiving and data recovery device for space division multiple access many-to-many communication according to an embodiment of the present invention; Figure 5 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. 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.

[0019] It should be noted that references to "an embodiment," "embodiment," "example embodiment," etc., in this specification refer to the described embodiment including specific features, structures, or characteristics; however, not every embodiment must include these specific features, structures, or characteristics. Furthermore, such expressions do not refer to the same embodiment. Moreover, when describing specific features, structures, or characteristics in conjunction with embodiments, whether or not explicitly described, it is indicated that incorporating such features, structures, or characteristics into other embodiments is within the knowledge of those skilled in the art.

[0020] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0021] In some embodiments, such as Figure 1 As shown, an optical communication receiving and data recovery method for space division multiple access many-to-many communication is provided. The specific method includes: S101 receives the optical signal and extracts the signal of the corresponding physical channel from the optical signal according to the target receiving direction.

[0022] The corresponding physical channel is the light signal emitted by the pixel region in the Micro-LED array of the transmitter that corresponds to the receiving direction of the target.

[0023] Specifically, the corresponding physical channel here refers to the optical signal channel emitted by the pixel area in the Micro-LED array of the transmitting end that corresponds to the receiving direction of the target. For example, a car (the receiving end) needs to receive the optical signal from the physical channel of the Micro-LED headlight of the car in front, pointing towards the car. Assume the car is located about 30 degrees to the left front of the car, and the car in front has already used the pixel area corresponding to that direction (denoted as channel 1) to send data to the car. The car is equipped with a CMOS imaging sensor as the light receiving end. The imaging sensor continuously captures images of the headlight area of ​​the car in front, obtaining a series of image frames. In each image frame, since the car knows its own direction relative to the car in front, the system can pre-calibrate or determine the spatial region of interest (ROI) in the image corresponding to channel 1 in the headlight of the car in front through image processing algorithms (such as finding bright areas). For example, in a 640×480 image, the ROI is located in a rectangular area from (100,80) to (150,130) in the upper left corner. Then, the gray values ​​of all pixels within the ROI are summed to obtain a single value representing the light intensity received at the current moment. Arranging the summation values ​​of consecutive image frames in chronological order forms the received signal sequence corresponding to the physical channel (channel 1). If the receiver uses a photodiode (PD) instead of an imaging sensor, optical collimating lenses and narrowband filters allow the PD to receive light only from a specific direction (i.e., the target receiving direction), directly outputting an analog electrical signal sequence. Through this step, the receiver successfully extracts its own signal from the complex composite optical field, avoiding interference from other directional channels. By utilizing spatial region of interest selection or optical filtering, signal separation in spatial division multiple access is achieved, enabling multiple receivers to simultaneously receive different data without crosstalk, greatly improving the system's concurrency capability.

[0024] Optionally, extracting the signal of the corresponding physical channel according to the target receiving direction includes: when an imaging sensor is used as the receiving device, selecting a spatial region of interest corresponding to the target receiving direction in the continuous image frames acquired by the imaging sensor; summing or weighted averaging the pixel gray values ​​in the spatial region of interest to obtain a single received value corresponding to each image frame; and arranging the received values ​​of the continuous image frames in chronological order to form a received signal sequence of the corresponding physical channel.

[0025] Specifically, firstly, the imaging sensor continuously captures images of the area of ​​the transmitter (such as the Micro-LED headlights of a vehicle), obtaining a series of image frames. Since the receiver knows its target reception direction relative to the transmitter (e.g., a horizontal angle of 22.5° and a pitch angle of 3.2° calculated through prior calibration or real-time positioning), the system can select a region of interest (ROI) corresponding to that direction in each frame. The selection method for the ROI can be as follows: Firstly, a mapping relationship between image pixel coordinates and actual spatial angles is established beforehand through calibration. Then, the corresponding image coordinates are found based on the target angle, and a rectangular or circular window is drawn centered on these coordinates. For example, in a 640×480 image, the target direction corresponds to image coordinates (320, 240), and a 40×40 pixel rectangular window is selected as the ROI centered on this coordinate. Another method is to utilize the transmitter sending a specific pattern (such as a flashing synchronization sequence) in each frame, and dynamically lock the ROI using image processing algorithms (such as finding the area with the most drastic brightness changes). After selecting the ROI, the system sums or performs a weighted average of the grayscale values ​​of all pixels within that area. For example, an ROI contains 1600 pixels, each with a grayscale value between 0 and 255. The system sums these grayscale values ​​to obtain a total, then divides by the number of pixels to obtain the average value. This single value represents the total light intensity received by the physical channel at the current moment. The reason for using summation or averaging is that multiple pixels within the same physical channel at the transmitting end emit the same data at the same time, forming a light spot on the image. The receiving end only needs to capture the total energy of this light spot, without needing to distinguish individual pixels. Arranging the summation (or average value) of consecutive image frames in chronological order forms the received signal sequence y[n] for the corresponding physical channel. For example, if the frame rate is 1000 frames per second, and each frame yields a value, then the sampling rate of y[n] is 1000Hz. If the symbol rate at the transmitting end is also 1000bps, then each symbol period corresponds to one frame. If the symbol rate is higher, a faster imaging sensor or other receiving devices (such as a PD) are required. By utilizing the spatial resolution capability of the imaging sensor, signal separation of specific physical channels in spatial division multiple access is achieved through ROI selection, avoiding crosstalk from other directional channels. Summing or averaging pixels within the ROI enhances signal energy and suppresses spatial noise, providing a high-quality input sequence for subsequent synchronization and decision-making.

[0026] S102, the extracted signal is sampled at a sampling frequency higher than the symbol rate to obtain a discrete time series.

[0027] Specifically, let the symbol rate (i.e., bit rate) at the transmitting end be 1 Mbps, meaning each symbol period is 1 microsecond. To satisfy the Nyquist sampling theorem and ensure the accuracy of subsequent decisions, the receiving end samples at a frequency at least four times the symbol rate, i.e., a sampling frequency of 4 MHz, containing M=4 sampling points per symbol period. For imaging sensor receivers, the sampling frequency is limited by the frame rate of the image sensor. If the sensor frame rate is 1000 fps, then each symbol period corresponds to 1 frame (i.e., M=1), but at this time the sampling rate equals the symbol rate, which easily leads to aliasing. Therefore, in practical systems, high-speed PDs combined with analog-to-digital converters (ADCs) are more commonly used to achieve oversampling. For example, the ADC samples the voltage signal output by the PD at a frequency of 20 MHz, obtaining 20 sampling points per symbol period. The sampled discrete-time sequence is represented as y[n], n=0,1,2,..., where each value represents the light intensity (including noise and possible crosstalk) at that sampling moment. Oversampling preserves the detailed information of the signal, provides redundancy for subsequent synchronization and decision-making, and helps to recover data in low signal-to-noise ratio environments.

[0028] Optionally, sampling the extracted signal at a sampling frequency higher than the symbol rate includes: each symbol period contains M sampling points, where M is an integer greater than or equal to 4; when an imaging sensor is used for reception, the sampling frequency is determined by the frame rate of the image sensor, and the number of image frames corresponding to each symbol period is M.

[0029] Specifically, firstly, we define each symbol period as containing M sampling points, where M is an integer greater than or equal to 4. Here, the symbol period refers to the duration of one bit modulated by the transmitter, for example, 1 microsecond (corresponding to 1 Mbps). If M=4, the sampling frequency is 4MHz, meaning sampling once every 0.25 microseconds. The value of M determines the oversampling factor; the larger M is, the stronger the noise suppression capability, but the greater the computational load. M must be at least 4 to meet the reliable decision requirements in general engineering. For receivers using photodiodes (PDs) with analog-to-digital converters, M=8, 16, or even higher can be easily achieved. For example, sampling a 1Mbps signal at a 20MHz sampling rate results in M=20. When the receiver uses an imaging sensor, the sampling frequency is limited by the frame rate of the image sensor. For example, common automotive cameras have frame rates of 30fps, 60fps, or 100fps, while the communication symbol rate may be as high as thousands or even tens of thousands of bps. In this case, one frame corresponds to multiple symbols, which cannot meet the requirement of multiple sampling points within each symbol period. Therefore, in scenarios using imaging sensors, it is usually necessary to reduce the symbol rate to adapt to the frame rate, or use a rolling shutter sensor to obtain higher temporal resolution. As explicitly stated earlier, when using an imaging sensor for reception, the sampling frequency is determined by the image sensor's frame rate, and the number of image frames corresponding to each symbol period is M. This means that the transmitter and receiver need to negotiate a symbol rate such that the symbol period is equal to M times the frame period. For example, if the imaging sensor's frame rate is 1000fps (i.e., one frame per millisecond), and M=4 is set, then the symbol period is 4 milliseconds, and the symbol rate is 250bps. The receiver acquires one sampling point per frame, and four consecutive frames correspond to one symbol period. In the specific implementation, the receiver first acquires the imaging sensor's frame rate F_fps, then sets the value of M (e.g., 4), so the symbol period T_symbol=M / F_fps, and the transmitter adjusts the modulation rate accordingly. The receiver extracts the ROI signal value in each frame, forming a discrete time sequence y[n], where n is the frame number. By specifying that the oversampling factor M≥4, sufficient redundancy is ensured during digital signal processing to suppress noise and accurately determine the synchronization position. For the imaging sensor receiving scheme, the relationship between frame rate and symbol rate is given, enabling system designers to reasonably configure the communication rate according to the sensor parameters and achieve reliable communication of the imaging sensor as an optical receiver.

[0030] S103, perform sliding correlation calculation on the discrete time series based on the preset synchronization sequence, and determine the starting position of the data frame when the correlation value exceeds the preset threshold.

[0031] Specifically, after obtaining the discrete-time series, a sliding correlation calculation is performed on the discrete-time series based on a preset synchronization sequence. When the correlation value exceeds a preset threshold, the starting position of the data frame is determined, and the symbol sequence to be decided is truncated based on this starting position. The preset synchronization sequence is a known pseudo-random bit sequence, such as a 32-bit Barker code, which is sent by the transmitter at the beginning of each data frame. The receiver performs a sliding correlation calculation between the locally stored synchronization sequence s[m] (m=0,...,L_s-1, L_s=32) and the discrete-time series y[n], with the formula C[t]=Σ_{m=0}^{L_s-1}y[t+m]·s[m]. Since s[m] is represented by ±1 or 0 / 1, in actual calculations, the bits are usually mapped to ±1 to enhance the correlation peak. Starting from the beginning of the sequence, the correlation value is calculated once for each sliding sampling point, resulting in the correlation value sequence C[t]. The maximum value C_max in C[t] and its corresponding sliding position t_peak are then identified. If C_max is greater than a preset threshold γ (e.g., γ = 0.8 × L_s), synchronization is considered successful, and t_peak is the starting position of the data frame. For example, assuming the synchronization sequence is [1, -1, 1, 1, -1, ...], if the correlation value reaches 28 at t_peak, which is greater than the threshold 25, the start of the frame is confirmed. Then, based on this starting position, a segment of sampling points is extracted every symbol period (M = 4) as the symbol sequence to be decided. For example, sampling points 0-3 after the start of the frame belong to the first symbol, sampling points 4-7 belong to the second symbol, and so on. If synchronization fails (i.e., the maximum correlation value does not exceed the threshold), the receiver continues the sliding search until a timeout occurs and an error is reported. Sliding correlation detection can accurately lock the frame boundary in strong noise and interference environments, overcoming the unreliability of simple threshold detection, and providing a time reference for subsequent correct demodulation and decoding.

[0032] Optionally, the sliding correlation calculation based on the preset synchronization sequence includes: performing a sliding inner product operation on the preset synchronization sequence and the discrete time sequence point by point from the starting point to obtain a correlation value sequence; recording the maximum value in the correlation value sequence and its corresponding sliding position; when the maximum value exceeds a preset threshold, using the sliding position corresponding to the maximum value as the starting position of the data frame; otherwise, continuing the sliding search.

[0033] Specifically, firstly, the preset synchronization sequence is a known bit sequence, such as a 32-bit Barker code, denoted as s[m], where m = 0, ..., 31. In actual calculations, bit 0 is usually mapped to -1, and bit 1 to +1 to enhance the correlation peak. The receiving end performs a sliding inner product operation on the local synchronization sequence and the discrete-time sequence y[n] point by point, starting from the starting point. That is, for each sliding position t, C[t] = Σ_{m=0}^{31}y[t+m] is calculated. s[m]. The multiplication and addition operations here can be quickly implemented in hardware. Since y[t+m] is an analog sampled value (which may contain noise), and s[m] is ±1, the magnitude of C[t] reflects the degree of matching between that position and the synchronization sequence. The sliding range starts from t=0 and goes up to a maximum search length (e.g., the maximum possible length of a frame). Each time C[t] is calculated, the system records the current value and the corresponding position t. After traversing the search range, the maximum value C_max among all C[t] and its corresponding sliding position t_peak are found. Then, C_max is compared with a preset threshold γ. The setting of the threshold γ is usually related to the length of the synchronization sequence and the desired signal-to-noise ratio, for example, γ=0.8. 32 = 25.6. If C_max > γ, synchronization is considered successful, and t_peak is used as the starting position of the data frame. If C_max ≤ γ, it means that no reliable synchronization sequence was found within the current search range, and synchronization is considered to have failed. At this time, the receiver can continue to slide the search until the preset maximum search length is reached (e.g., searching for 10 frames of data). If the threshold is still not exceeded, synchronization is declared to have failed, an error indication is output, and the receiver waits for the next round of reception. In practical systems, to improve robustness, multi-peak detection can also be used: if there are multiple peaks exceeding the threshold, the first one is selected or additional information (such as frame interval) is used for decision-making. Sliding correlation detection utilizes the good autocorrelation characteristics of the synchronization sequence, which can accurately lock the frame boundary under low signal-to-noise ratio and crosstalk conditions, and is superior to simple energy detection or edge triggering; setting the threshold and maximum search length avoids false synchronization or infinite loops, ensuring the reliability of the synchronization process.

[0034] S104 performs integration or averaging on the discrete-time sequence according to the symbol period to obtain the decision value of each symbol, and binarizes the decision value based on the decision threshold to recover the bit sequence.

[0035] Specifically, for the nth symbol, its corresponding set of sampling points is y[nM], y[nM+1], ..., y[nM+M-1] (M=4). The receiver calculates the arithmetic mean of these sampling points to obtain the decision value z[n]=(1 / M). Σ_{i=0}^{M-1}y[nM+i]. For example, if the four sampled values ​​within one symbol period are [0.8, 0.9, 0.85, 0.95] (unit: voltage volts), then the average value is 0.875. The decision threshold τ can be fixed in advance, for example, set to 0.5V, or an adaptive method can be used: using the known bit values ​​in the synchronization sequence, the average decision value μ_H corresponding to logic 1 and the average decision value μ_L corresponding to logic 0 are calculated respectively, and then τ=(μ_H+μ_L) / 2. Assuming that μ_H=0.9V and μ_L=0.2V are obtained after calculating the synchronization sequence, then τ=0.55V. Then, for z[n]=0.875>0.55, it is judged as logic 1; if z[n]=0.3<0.55, it is judged as logic 0. In this way, the decision is made symbol by symbol to obtain the recovered bit sequence. By effectively suppressing noise and random spikes through integral averaging, the adaptive threshold can track channel changes, making the decision more reliable and thus reducing the bit error rate. It is especially suitable for dynamic scenarios where the background light intensity changes continuously in vehicle headlight communication.

[0036] Optionally, obtaining the decision value of each symbol and binarizing it based on the decision threshold includes: for M sampling points within each symbol period, calculating their arithmetic mean or geometric mean as the decision value of that symbol; the decision threshold is a fixed threshold, or adaptively calculated based on the median of the average decision values ​​of the symbols corresponding to logic "1" and the average decision values ​​of the symbols corresponding to logic "0" in the synchronization sequence; when the decision value is greater than the decision threshold, it is judged as logic "1"; otherwise, it is judged as logic "0".

[0037] Specifically, firstly, for M sampling points (M≥4) within each symbol period, the system calculates their arithmetic or geometric mean as the decision value for that symbol. The formula for calculating the arithmetic mean is z[n]=(1 / M). Σ_{i=0}^{M-1}y[nM+i], where n is the symbol index. For example, if M=4, and the sampled values ​​within one symbol period are [0.85, 0.90, 0.88, 0.93] (unit: volts), then the arithmetic mean z=0.89V. The geometric mean is suitable for scenarios with a large signal dynamic range and is calculated as the Mth root of the Mth product, but the arithmetic mean is usually sufficient. Next, the decision threshold τ needs to be determined. The threshold can be a fixed threshold, for example, an optimal value determined experimentally beforehand, such as 0.5V, which is directly used for all decisions. A better approach is an adaptive threshold: using the known bit values ​​in the synchronization sequence to estimate the mean of the decision values ​​corresponding to logic 1 and logic 0 in the current channel. Specifically, within the symbol period corresponding to the synchronization sequence, since the receiver knows the original bits of the sequence, the decision values ​​of all symbols with original bits of 1 are collected, and their mean μ_H is calculated; the decision values ​​of all symbols with original bits of 0 are collected, and their mean μ_L is calculated. Then, the decision threshold τ = (μ_H + μ_L) / 2 is taken. For example, if there are 16 ones and 16 zeros in the synchronization sequence, μ_H = 0.92V and μ_L = 0.28V are calculated, then τ = 0.60V. This adaptive threshold can track channel attenuation and background light changes. After obtaining the decision threshold, the decision value z[n] of each symbol is compared: if z[n] > τ, it is judged as logic 1; if z[n] ≤ τ, it is judged as logic 0. For example, z = 0.89 > 0.60 is judged as 1, z = 0.30 is judged as 0. And so on, the entire bit sequence is recovered. The integral averaging after oversampling effectively suppresses random noise and sampling jitter; the adaptive threshold utilizes the prior information in the synchronization sequence to estimate the optimal decision threshold in real time, overcoming the performance degradation problem of fixed threshold when the channel changes, thus achieving a low bit error rate under various environmental conditions.

[0038] Optionally, before calculating the decision value, the discrete time series is sequentially subjected to moving average filtering and finite impulse response low-pass filtering to suppress high-frequency noise and crosstalk components from adjacent physical channels.

[0039] Specifically, preprocessing is performed before moving correlation detection and sign decision to suppress noise and crosstalk. First, the discrete-time series y[n] is subjected to moving average filtering. Moving average filtering is a simple time-domain filtering method: for each sampling point, the average of the L points before and after it is taken as the output, i.e., y_ma[n]=(1 / (2L+1)). Σ_{k=-L}^{L}y[n+k]. For example, taking L=2 and the window length of 5 can effectively smooth high-frequency random noise. Then, the sequence after moving average is further subjected to finite impulse response (FIR) low-pass filtering. The coefficients of the FIR filter are designed according to the signal bandwidth. For example, a low-pass filter with a cutoff frequency of 1.2 times the symbol frequency and an order of 10 can be designed using the window function method. After filtering, the sequence y_f[n] is obtained. The waveform of the preprocessed sequence y_f[n] is smoother, and the rapid fluctuations caused by spikes and crosstalk are greatly suppressed. Then, the aforementioned integral averaging process (i.e., averaging within each symbol period) is performed on y_f[n] to obtain the decision quantity z[n]. Figure 2 and Figure 3 The waveforms before and after noise reduction and filtering are shown, demonstrating that preprocessing significantly improves signal quality.

[0040] S105, the bit sequence is parsed according to the preset frame structure to extract the version field, data stream identifier field, sequence field, length field, payload field and check field.

[0041] Specifically, after recovering the bit sequence, the bit sequence is parsed according to a preset frame structure to extract the version field, data stream identifier field, sequence field, length field, payload field, and check field. The preset frame structure is a format agreed upon in advance by the transmitter and receiver. For example, a complete frame consists of the following fields in sequence: synchronization field (32 bits), version field (4 bits), data stream identifier field (8 bits), sequence field (8 bits), length field (16 bits), payload field (variable length, specified by the length field), and check field (16 bits). The receiving end begins parsing after the synchronization field: it reads the next 4 bits as the version number, for example, binary 0001 represents version 1; then it reads 8 bits as the data stream identifier, for example, 00000001 indicates that the frame belongs to the text stream of vehicle B; next, it reads 8 bits as the sequence number, for example, 00000000 indicates the first frame; then it reads 16 bits as the length, for example, 0000000000001100 (decimal 12) indicates that the payload is 12 bytes; then it reads 12 bytes as the payload data; finally, it reads 16 bits as the CRC checksum. In this way, the receiving end extracts each field from the raw bit stream in a structured manner. The standardized frame structure enables the receiving end to correctly distinguish different service streams, detect frame loss and out-of-order delivery, and provides the necessary information for subsequent verification and reassembly.

[0042] Optionally, after parsing the bit sequence, a cyclic redundancy check is performed on the check field. If the check passes, the payload field is reassembled based on the sequence field; if the check fails, the current frame is discarded, and a retransmission request is triggered or the system waits for the next frame.

[0043] Specifically, post-processing is performed after the bit sequence has been recovered and the frame structure parsed. The receiving end has already extracted the version field, data stream identifier field, sequence field, length field, payload field, and check field through frame parsing. Then, a Cyclic Redundancy Check (CRC) is performed on the check field. Specifically, using the same CRC-16-CCITT polynomial as the transmitting end, the CRC value for all data from the version field to the payload field is recalculated and compared with the received check field. If the two match (i.e., the check passes), it means that no errors occurred during the transmission of the frame data. The receiving end reassembles the payload field according to the sequence field: the payloads of multiple frames with the same data stream identifier and consecutive sequence numbers are sequentially concatenated to recover the complete service message. If the check fails, it means that there is an error in the frame. The receiving end discards the current frame and triggers a retransmission request to the upper layer (e.g., sending a NACK signal), or waits for the next frame to arrive (if a redundant transmission strategy is used). In addition, if the sequence field detects a skip number (e.g., receiving sequence number 7 directly after receiving sequence number 5), a retransmission request can also be triggered. The combination of moving average and FIR filtering in preprocessing effectively suppresses high-frequency noise and crosstalk between adjacent channels, improves the signal-to-noise ratio of symbol decision, and thus reduces the bit error rate. CRC check in postprocessing ensures data integrity, and the mechanism of discarding erroneous frames and triggering retransmission enables the system to cope with adverse channel conditions. The reassembly function of the sequence field ensures the correct order of multi-frame service data, ultimately providing a reliable and orderly data stream for upper-layer applications.

[0044] S106, validate the load field based on the validation field, and output the recovery data when the validation passes.

[0045] Specifically, the receiving end uses the same CRC-16-CCITT algorithm (generator polynomial x^16 + x^12 + x^5 + 1) as the transmitting end to recalculate the checksum for all data from the version field to the payload field, and compares it with the received checksum field. If they match, the checksum passes, indicating that no errors occurred in the payload data during transmission, and the receiving end outputs the payload field to the upper-layer application. For example, for the text stream of vehicle B, the 12 bytes of data in the payload field [0xE7, 0xB4, 0xA7, 0xE6, 0x80, 0xA5, 0xE5, 0x88, 0xB6, 0xE5, 0x8A, 0xA8] are decoded into the string "emergency braking" according to UTF-8, and the warning information can be displayed on the display screen of vehicle B. If the checksum does not match, it indicates that the frame may have bit errors due to noise or interference. The receiving end discards the frame and outputs an error indication to the upper layer (e.g., returning a specific error code), and the upper layer can initiate a retransmission request or wait for the next frame as needed. Furthermore, the receiver can also check for frame loss or out-of-order delivery in the sequence field, and request retransmission if any are found. CRC check provides robust error detection capabilities, ensuring communication reliability; the mechanism of discarding erroneous frames and outputting an indication avoids passing erroneous data to upper-layer applications, which is crucial for safety-critical vehicle-to-everything (V2X) scenarios; at the same time, combined with the retransmission mechanism of the sequence field, the integrity and robustness of data transmission are further improved.

[0046] Based on the same inventive concept, this application also provides an optical communication receiving and data recovery device for implementing the aforementioned optical communication receiving and data recovery method for space division multiple access (SDMA) multiple-to-many communication. The solution provided by this device is similar to the implementation described in the above-described method. Therefore, the specific limitations of one or more embodiments of the optical communication receiving and data recovery device for SDMA multiple-to-many communication provided below can be found in the limitations of the optical communication receiving and data recovery method for SDMA multiple-to-many communication described above, and will not be repeated here.

[0047] In one embodiment, such as Figure 4 As shown, an optical communication receiving and data recovery device for space division multiple access many-to-many communication is provided. The device includes: The signal extraction module 30 is used to receive optical signals and extract signals of corresponding physical channels from the optical signals according to the target receiving direction, wherein the corresponding physical channel is the optical signal emitted by the pixel area in the Micro-LED array of the transmitter that corresponds to the target receiving direction; The signal sampling module 31 is used to sample the extracted signal at a sampling frequency higher than the symbol rate to obtain a discrete time series; The correlation calculation module 32 is used to perform sliding correlation calculation on discrete time series based on a preset synchronization sequence, and to determine the starting position of the data frame when the correlation value exceeds a preset threshold. The sequence processing module 33 is used to integrate or average the discrete time sequence according to the symbol period to obtain the decision value of each symbol, and to binarize the decision value based on the decision threshold to recover the bit sequence. The structure parsing module 34 is used to parse the bit sequence according to the preset frame structure and extract the version field, data stream identifier field, sequence field, length field, payload field and check field; The field validation module 35 is used to validate the payload field according to the validation field, and output the recovery data when the validation passes.

[0048] This application also provides an electronic device, in some embodiments, referring to... Figure 5 As shown, the electronic device 700 includes an input unit 710, a memory 720, a processor 730, and an output unit 740. The memory 720 stores program instructions that can be executed on the processor 730. The processor 730 can execute the optical communication reception and data recovery method and / or technical solution based on the space division multiple access many-to-many communication method described in the foregoing embodiments by calling the program instructions. This electronic device 700 can be a mobile terminal device such as a mobile phone or computer.

[0049] Furthermore, embodiments of this application also provide a computer-readable storage medium for storing a computer program that executes a method for receiving and recovering data in optical communication for space-division multiple access many-to-many communication. For example, computer program instructions, when executed by a computer, can invoke or provide the methods and / or technical solutions according to this application through the operation of the computer. The program instructions that invoke the methods of this application may be stored in a fixed or removable storage medium, and / or transmitted via data streams in broadcast or other signal carrying media, and / or stored in a storage medium that operates according to the program instructions.

[0050] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0051] The technical features of the above embodiments can be arbitrarily integrated. For the sake of brevity, not all possible integrations of the technical features in the above embodiments are described. However, as long as the integration of these technical features does not contradict each other, they should be considered to be within the scope of this specification.

[0052] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for optical communication reception and data recovery for space division multiple access many-to-many communication, characterized in that, The method includes: The system receives an optical signal and extracts the signal of the corresponding physical channel from the optical signal according to the target receiving direction, wherein the corresponding physical channel is the optical signal emitted by the pixel area in the Micro-LED array of the transmitter that corresponds to the target receiving direction. The extracted signal is sampled at a sampling frequency higher than the symbol rate to obtain a discrete time series; The discrete time series is subjected to sliding correlation calculation based on a preset synchronization sequence, and the starting position of the data frame is determined when the correlation value exceeds a preset threshold. The discrete-time sequence is integrated or averaged according to the symbol period to obtain the decision value of each symbol, and the decision value is binarized based on the decision threshold to recover the bit sequence. The bit sequence is parsed according to a preset frame structure to extract the version field, data stream identifier field, sequence field, length field, payload field, and check field; The load field is validated based on the validation field, and the recovery data is output when the validation passes.

2. The optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in claim 1, characterized in that, The step of extracting the signal corresponding to the physical channel based on the target receiving direction includes: When an imaging sensor is used as a receiving device, a spatial region of interest corresponding to the target receiving direction is selected in the continuous image frames acquired by the imaging sensor. The pixel grayscale values ​​within the spatial region of interest are summed or weighted to obtain a single received value for each image frame. The received values ​​of consecutive image frames are arranged in chronological order to form the received signal sequence of the corresponding physical channel.

3. The optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in claim 2, characterized in that, The sampling of the extracted signal at a sampling frequency higher than the symbol rate includes: Each symbol period contains M sampling points, where M is an integer greater than or equal to 4; When an imaging sensor is used for reception, the sampling frequency is determined by the frame rate of the image sensor, and the number of image frames corresponding to each symbol period is M.

4. The optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in claim 1, characterized in that, The sliding correlation calculation based on the preset synchronization sequence includes: The preset synchronization sequence and the discrete time sequence are subjected to a sliding inner product operation point by point starting from the starting point to obtain the correlation value sequence. Record the maximum value in the relevant value sequence and its corresponding sliding position; When the maximum value exceeds the preset threshold, the sliding position corresponding to the maximum value is taken as the starting position of the data frame; otherwise, the sliding search continues.

5. The optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in claim 4, characterized in that, The process of obtaining the decision value for each symbol and binarizing it based on the decision threshold includes: For each symbol period, calculate the arithmetic mean or geometric mean of the M sampling points, and use it as the decision value for that symbol. The decision threshold is a fixed threshold, or it is adaptively calculated based on the median of the average value of the symbol decision quantity corresponding to logic "1" and the average value of the symbol decision quantity corresponding to logic "0" in the synchronization sequence. When the decision value is greater than the decision threshold, it is judged as logical "1"; otherwise, it is judged as logical "0".

6. The optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in claim 5, characterized in that, It also includes preprocessing and postprocessing steps: Before calculating the decision value, the discrete time series is sequentially subjected to moving average filtering and finite impulse response low-pass filtering to suppress high-frequency noise and crosstalk components from adjacent physical channels. After parsing the bit sequence, a cyclic redundancy check is performed on the check field. If the check passes, the payload field is reassembled based on the sequence field. If the verification fails, the current frame is discarded, and a retransmission request is triggered or the system waits for the next frame.

7. An optical communication receiving and data recovery device for space division multiple access many-to-many communication, characterized in that, The device includes: The signal extraction module is used to receive optical signals and extract signals of corresponding physical channels from the optical signals according to the target receiving direction, wherein the corresponding physical channel is the optical signal emitted by the pixel area in the Micro-LED array of the transmitter that corresponds to the target receiving direction; The signal sampling module is used to sample the extracted signal at a sampling frequency higher than the symbol rate to obtain a discrete time series. The correlation calculation module is used to perform sliding correlation calculation on the discrete time series based on a preset synchronization sequence, and determine the starting position of the data frame when the correlation value exceeds a preset threshold. The sequence processing module is used to integrate or average the discrete time sequence according to the symbol period to obtain the decision value of each symbol, and to binarize the decision value based on the decision threshold to recover the bit sequence. The structure parsing module is used to parse the bit sequence according to a preset frame structure and extract the version field, data stream identifier field, sequence field, length field, payload field and check field; The field validation module is used to validate the payload field according to the validation field, and output the recovery data when the validation passes.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the optical communication receiving and data recovery method for space division multiple access many-to-many communication as described in any one of claims 1 to 6.

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