Time-frequency calibration method for visible light sensing integrated system

Abstract

The invention provides a time-frequency calibration method for a visible light sensing integrated system, and relates to the technical field of time-frequency calibration. The method comprises the following steps: constructing a visible light sensing integrated system comprising a plurality of LED emitters and a user equipment receiver equipped with a photodiode, and calculating actual transmission time delay, signal gain and channel fading of communication between the LED emitters and the user equipment receiver; a sending signal sent by an LED emitter is obtained, a receiving signal obtained by a user equipment receiver is calculated based on the waveform, the signal gain and the channel fading of the sending signal, and a receiving signal estimation model is constructed, so that a clock synchronization and frequency calibration function containing an unknown clock parameter and an unknown frequency deviation parameter is constructed. According to the function, a time-frequency calibration technology is introduced into visible light communication, timestamp information is replaced by a received signal waveform, the calculation complexity is reduced, the universality is improved, a clock offset parameter and a frequency offset parameter are finally obtained, and clock synchronization and frequency calibration are completed.

Description

Technical Field

[0001] The present invention relates to the technical field of time-frequency calibration, and more particularly to a time-frequency calibration method for a visible light synaesthesia integrated system. Background Art

[0002] In distributed systems, due to differences in factors such as the aging of the crystal oscillators of various devices, frequency characteristics, and temperature, local time deviations may occur between different devices, thereby disrupting the consistency of data transmission and system stability, seriously affecting system performance.

[0003] To address this issue, the concept of clock synchronization and related research emerged. Clock synchronization includes phase synchronization and frequency synchronization. Phase synchronization refers to the synchronization of the clock signal with the active edge (typically the rising or falling edge) of the ideal signal. Frequency synchronization refers to the fact that the changing frequencies of the two signals are the same or maintain a fixed ratio. Clock synchronization aims to align the local time of different terminals. In traditional digital communication systems, clock synchronization is generally achieved through symbol timing synchronization. At the transmitter end of the system, bits of information are first mapped into a baseband digital signal according to a rule, then modulated onto a carrier and transmitted into a free channel. At the receiver end, after low-pass filtering, the receiver samples and makes decisions on the digital signal at symbol intervals. To accurately identify the boundaries of each symbol and determine the optimal sampling instant, symbol synchronization is required between the transmitter and receiver. Accurate symbol timing synchronization reduces inter-symbol interference and errors, thereby ensuring consistent and reliable data transmission, improving spectrum efficiency, and enhancing system performance.

[0004] With the future convergence of 6G mobile communication networks, perception networks, and computing networks, various new positioning and perception applications are placing even higher precision requirements on clock synchronization. On the one hand, scenarios such as autonomous driving, intelligent logistics, and drone operations require positioning accuracy at the meter or even decimeter level. Clock synchronization, as a key technology for achieving high-precision positioning, directly impacts the accuracy of positioning services. Therefore, further optimization of clock synchronization errors is necessary, keeping them within the nanosecond level. On the other hand, fields such as telemedicine, power systems, and military communications require extremely low latency and stable connections, placing an increasing demand on clock synchronization accuracy. Real-time services such as stock trading also place extremely high demands on the accuracy of time information. Therefore, network-based high-precision clock synchronization has become a core technology for distributed measurement and control systems.

[0005] Furthermore, in multi-access communication systems, communication no longer occurs point-to-point. Instead, multiple transmitters simultaneously transmit signals to a single receiver. To split and combine signals, each node must maintain the same rate and phase of the signals received in each direction, placing higher demands on synchronization accuracy and mechanisms. However, symbol synchronization cannot effectively support the simultaneous access and data transmission of a large number of devices, presenting significant limitations.

[0006] Currently, existing technologies mostly use timestamps for clock synchronization. Specifically, the transmitted signal is shifted on the time axis, and the cross-correlation function between it and the received signal is calculated. The phase of the transmitted signal shift when the cross-correlation function is maximum is obtained to obtain the timestamp; then, by constructing the relationship between the standard clock and the local clock, the least squares method is used to directly solve the unknown clock parameters of the target node. The specific steps of the timestamp-based clock synchronization algorithm are relatively simple and easy to implement. It has good applicability in simple scenarios with low synchronization accuracy requirements. However, this method also has obvious limitations: (1) The computational complexity is high. In the process of obtaining the timestamp, the correlation between the transmitted and received signals needs to be measured. For high-resolution signals, calculating the cross-correlation function of the transmitting and receiving signals requires a lot of time and memory resources. This limits the application of the algorithm in large-scale device access scenarios. When a large number of devices are connected and transmitting data at the same time, the demand for computing resources will increase exponentially, resulting in a decrease in system performance. (2) The accuracy of clock synchronization is low. The timestamp is estimated using the waveform of the transmitted and received signals. Its own characteristics determine the upper limit of clock synchronization accuracy. Limited by the minimum time slot problem of the timestamp itself, as well as the timestamp jitter caused by protocol stack processing jitter and data stream buffering, the estimation accuracy of clock synchronization cannot reach sub-microsecond accuracy, which cannot meet the high-speed, high-capacity and low-latency requirements of future communication systems. In high-tech fields such as industrial automation and aerospace, the requirements for time synchronization accuracy are extremely high, usually requiring nanosecond accuracy or even higher. (3) Lack of versatility. The construction of the signal cross-correlation function is based on the assumption of a linear system and is difficult to apply to complex nonlinear systems. In actual scenarios, signal propagation and data processing will introduce various nonlinear effects, resulting in problems such as signal distortion and frequency offset, affecting the accuracy of the cross-correlation function and thus reducing the accuracy of clock synchronization.

[0007] Furthermore, most existing clock synchronization research has overlooked the issue of carrier frequency inaccuracy. However, the received signal waveform depends on both clock and frequency parameters. Therefore, in VLC systems, clock calibration and carrier frequency calibration are mutually coupled issues. Due to unstable crystal oscillations in optical devices, the carrier frequency between transmitter and receiver is often inaccurate. In VLC systems, even small frequency errors can lead to significant clock performance degradation, and vice versa. Summary of the Invention

[0008] In order to solve the problems of high computational complexity, low clock synchronization accuracy, insufficient versatility and neglect of carrier frequency in existing clock synchronization technologies, the present invention proposes a time-frequency calibration method for a visible light telepathy integrated system, creatively introducing time-frequency calibration technology into visible light communication, reducing computational complexity while improving clock synchronization accuracy and versatility, thus meeting the needs of future high-speed communication and high-precision perception.

[0009] In order to achieve the above technical effects, the technical solutions of the present invention are as follows: This application proposes a time-frequency calibration method for a visible light synaesthesia integrated system, comprising the following steps: S1. Constructing an integrated visible light synaesthesia system, the system comprising: a plurality of LED emitters and a user device receiver equipped with a photodiode, the plurality of LED emitters communicating with the user device receiver, the user device receiver receiving visible light signals emitted by the LED emitters; S2. Using the LED clock as the standard clock, calculate the actual transmission delay based on the standard transmission delay when the LED transmitter communicates with the user device receiver; S3. Calculate the signal gain when the LED transmitter communicates with the user device receiver, and calculate the channel fading caused by the frequency offset based on the actual transmission delay when the LED transmitter communicates with the user device receiver and the frequency offset of the visible light signal subcarrier emitted by the LED transmitter; S4 obtains the transmission signal emitted by the LED transmitter, calculates the received signal obtained by the user equipment receiver based on the waveform of the transmitted signal, signal gain and channel fading, and constructs a received signal estimation model; S5. Based on the received signal estimation model, construct a clock synchronization and frequency calibration function, wherein the clock synchronization and frequency calibration function is a function containing unknown clock parameters and unknown frequency offset parameters; S6. Solve the clock synchronization and frequency calibration function to obtain the clock offset parameter and the frequency offset parameter, and complete the clock synchronization and frequency calibration.

[0010] In this technical solution, a visible light interawareness integrated system is first constructed, including multiple LED transmitters and a user equipment receiver equipped with a photodiode. The actual transmission delay, signal gain and channel fading of the communication between the LED transmitter and the user equipment receiver are calculated. The transmission signal emitted by the LED transmitter is obtained, and based on the waveform, signal gain and channel fading of the transmission signal, the received signal obtained by the user equipment receiver is calculated, and a received signal estimation model is constructed, thereby constructing a clock synchronization and frequency calibration function containing unknown clock parameters and unknown frequency offset parameters. This function introduces time-frequency calibration technology into visible light communication. Based on replacing timestamp information with the received signal waveform, it reduces the computational complexity while improving versatility and the accuracy of clock synchronization. Finally, the clock offset parameters and frequency offset parameters are obtained to complete clock synchronization and frequency calibration.

[0011] Preferably, the visible light synaesthesia integrated system in step S1 includes: An LED transmitter and a user equipment receiver equipped with a photodiode, wherein the photodiode is used to receive the visible light signal after O-OFDM modulation emitted by the LED transmitter and convert it into an electrical signal; wherein the first The known position vector of the LED emitter is , the direction vector is ; The known position vector of the user equipment receiver is , the direction vector is ;in, and are all unit vectors, and the expressions are:

[0012] .

[0013] Preferably, the process of calculating the actual transmission delay in step S2 is: Defines the time when the user equipment is receiving the standard time. The standard time delay for each LED emitter is , the expression is:

[0014] in, is the known position vector of the user equipment receiver, For the The known position vectors of the LED emitters, is the speed of light; Defines the clock offset parameters of the user equipment receiver The expression is:

[0015] in, represents the clock speed offset, Indicates that the clock is often offset; Using clock parameters Synchronize the clock of the user equipment receiver and set the user equipment receiver to the first Standard time delay for each LED emitter Mapped to the actual time delay when the user equipment receiver has clock deviation , the expression is: .

[0016] Preferably, the process of calculating the signal gain when the LED transmitter communicates with the user equipment receiver in step S3 is as follows: Calculate the The LED transmitter points to the transmission angle of the user device receiver , the user equipment receiver receives the The receiving angle of the LED transmitter , the calculation expression is:

[0017]

[0018] in, is the user equipment receiver position vector, For the The coordinate parameters of each LED emitter, For the Directional parameters of each LED emitter, is the user equipment receiver direction vector, Represents a transpose operation; Based on emission angle and receiving angle , building signal gain for visible light communication , the expression is:

[0019] in, The optical aperture of the photodiode, the optical filter gain, the concentrator gain and the first The joint band estimation parameters of the LED emitter power, is the Lambertian radiation order of the LED emitter, is the path loss exponent.

[0020] Preferably, in step S3, the channel fading caused by the frequency offset is calculated based on the actual transmission delay when the LED transmitter communicates with the user equipment receiver and the frequency offset of the visible light signal subcarrier emitted by the LED transmitter, and the expression is:

[0021] in, For the The first LED emitter emits Channel fading caused by frequency offset of subcarriers, For the The first LED emitter subcarrier frequencies, is the frequency offset caused by the local crystal oscillator, is the actual time delay when the user equipment receiver has clock deviation, is the number of LEDs.

[0022] Preferably, before constructing the received signal estimation model, the method further includes constructing an estimated waveform of a single received signal. , the expression is:

[0023] in, For the The first LED emitter The signal waveform sent by the subcarriers satisfies , For the The channel gain of LED optical signal transmission, For the The first LED emitter emits Channel fading caused by frequency offset of subcarriers; Integrate the estimated model of all individual received signals , build the final received signal estimation model , the expression is:

[0024] Where h is the channel gain coefficient, is the clock offset parameter of the user equipment, is the frequency offset parameter of the user equipment, vec[] represents the operation of integrating the time synchronization model of all signals into a column vector, is the number of OFDM subcarriers.

[0025] Preferably, the expression of the clock synchronization and frequency calibration function is:

[0026] in, is the waveform model of the transmitted signal actually received by the user equipment, is the optimal channel gain coefficient, is the clock offset parameter of the user equipment receiver, is the frequency offset parameter of the user equipment receiver; The clock synchronization and frequency calibration function is solved to obtain the clock offset parameter and the frequency offset parameter, and the channel gain coefficient is obtained. When solving the clock synchronization and frequency calibration function, let 、 and The parameters are 、 and In the The state at the iteration At the iteration, the parameter 、 and The channel gain estimation algorithm, clock calibration algorithm and frequency calibration algorithm are used to update in sequence respectively.

[0027] Preferably, the iterative update alternately optimizes and solves the objective function to obtain the optimal channel gain coefficient, and the process is: Update the channel gain coefficient using the channel gain estimation algorithm , the update process satisfies:

[0028] in, is the channel gain coefficient In the The state at the iteration, for and function, The clock offset parameter of the user equipment receiver In the The state at the iteration, Frequency offset parameter for the user equipment receiver In the The state at the iteration, and Already in Obtained in iterations; Based on the channel gain coefficient In the The optimal estimate at the iteration, The optimal estimate of the channel gain coefficient at the iteration , the expression is:

[0029] in, Represents the pseudo-inverse matrix operation.

[0030] Preferably, the iterative update alternately optimizes and solves the objective function to obtain the optimal clock offset parameter of the user equipment receiver, and the process is: Update the clock offset parameters of the user equipment using the clock calibration algorithm , the update process satisfies:

[0031] in, The clock offset parameter of the user equipment receiver In the The state at the iteration, Frequency offset parameter for the user equipment receiver In the The state at the iteration, is the channel gain coefficient In the The state at the iteration, , The clock offset parameter of the user equipment receiver Cost function of Based on the continuous linear least squares method, the iterative solution is obtained. The clock offset parameter of the user equipment receiver at the iteration The best estimate of .

[0032] Preferably, the iterative update alternately optimizes and solves the objective function to obtain the optimal user equipment receiver frequency offset parameter, and the process is: Update the user equipment receiver frequency offset parameters using the frequency calibration algorithm , the update process satisfies:

[0033] in, Frequency offset parameter for the user equipment receiver In the The state at the iteration, The clock offset parameter of the user equipment receiver In the The state at the iteration, is the channel gain coefficient In the The state at the iteration, , Frequency offset parameter for the user equipment receiver Cost function of Based on the continuous linear least squares method, the iterative solution is obtained. The user equipment receiver frequency offset parameter at the iteration The best estimate of .

[0034] Compared with the prior art, the present invention has the following beneficial effects: This invention proposes a time-frequency calibration method for an integrated visible light interoception system. First, for a constructed integrated visible light interoception system consisting of an LED transmitter and a user equipment receiver, the actual transmission delay, signal gain, and channel fading of the communication between the LED transmitter and the user equipment receiver are calculated. The transmitted signal emitted by the LED transmitter is obtained, and based on the waveform, signal gain, and channel fading of the transmitted signal, the received signal acquired by the user equipment receiver is calculated. A received signal estimation model is then constructed, thereby constructing a clock synchronization and frequency calibration function containing unknown clock parameters and unknown frequency offset parameters. This function introduces time-frequency calibration technology into visible light communication. By replacing timestamp information with the received signal waveform, it reduces computational complexity while improving versatility and clock synchronization accuracy. Finally, the clock synchronization and frequency calibration function is solved to obtain clock offset and frequency offset parameters, completing clock synchronization and frequency calibration. This invention creatively introduces time-frequency calibration technology into visible light communication, not only addressing the shortage of traditional radio frequency spectrum resources but also providing technical support for the future development of visible light ISACs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram showing a flow chart of a time-frequency calibration method for a visible light synaesthesia integrated system proposed in Example 1 of the present invention; Figure 2 A schematic diagram showing the structure of the visible light synaesthesia integrated system proposed in Example 2 of the present invention; Figure 3 A schematic diagram showing a comparison curve of clock speed offset estimation errors obtained by iteratively using the method proposed in the present invention and a clock calibration algorithm based on a signal waveform without frequency calibration, as proposed in Example 3 of the present invention; Figure 4 A schematic diagram showing a comparison curve of clock bias estimation errors obtained by iteratively performing a clock calibration algorithm based on a signal waveform without frequency calibration and using the method proposed in Example 3 of the present invention; Figure 5 A schematic diagram showing a comparison curve of frequency offset parameter estimation errors obtained by iteratively performing a frequency calibration algorithm based on a signal waveform without clock calibration and using the method proposed in Example 3 of the present invention; Figure 6A schematic diagram showing comparison curves of clock speed offset estimation errors obtained by iteratively using the method proposed in the present invention and a clock calibration algorithm based on timestamps and signal waveforms without frequency calibration under different signal-to-noise ratio conditions proposed in Example 3 of the present invention; Figure 7 A schematic diagram showing comparison curves of clock bias estimation errors obtained by iteratively using the method proposed in the present invention and a clock calibration algorithm based on timestamps and signal waveforms without frequency calibration under different signal-to-noise ratio conditions proposed in Example 3 of the present invention; Figure 8 A schematic diagram showing comparison curves of frequency offset parameter estimation errors obtained by iteratively using the method proposed in the present invention and a frequency calibration algorithm based on a signal waveform without clock calibration under different signal-to-noise ratio conditions proposed in Example 3 of the present invention; Figure 9 A schematic diagram showing a comparison curve of clock speed offset estimation errors obtained by iteratively using the method proposed in the present invention and a clock calibration algorithm based on timestamps and signal waveforms without frequency calibration under different subcarrier frequencies proposed in Example 3 of the present invention; Figure 10 A schematic diagram showing comparison curves of clock bias estimation errors obtained by iteratively using the method proposed in the present invention and a clock calibration algorithm based on timestamps and signal waveforms without frequency calibration under different subcarrier frequencies proposed in Example 3 of the present invention; Figure 11 A schematic diagram showing a comparison curve of clock speed offset estimation errors using the method proposed in the present invention and a frequency calibration algorithm based on a signal waveform without clock calibration under different frequency offset parameters proposed in Example 3 of the present invention; Figure 12 A schematic diagram showing a comparison curve of clock constant offset estimation errors using the method proposed in the present invention and a frequency calibration algorithm based on a signal waveform without clock calibration under different frequency offset parameters proposed in Example 3 of the present invention. DETAILED DESCRIPTION

[0036] The accompanying drawings are for illustrative purposes only and are not to be construed as limiting this patent; In order to better illustrate this embodiment, some parts of the drawings may be omitted, enlarged, or reduced, and do not represent the actual size; It is understandable to those skilled in the art that descriptions of certain well-known contents may be omitted in the drawings.

[0037] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0038] The positional relationships described in the drawings are for illustrative purposes only and should not be construed as limiting this patent; Example 1 This embodiment proposes a time-frequency calibration method for a visible light interoception integrated system. The flowchart of this method is shown in Figure 1 , including the following steps: S1. Constructing an integrated visible light synaesthesia system, the system comprising: a plurality of LED emitters and a user device receiver equipped with a photodiode, the plurality of LED emitters communicating with the user device receiver, the user device receiver receiving visible light signals emitted by the LED emitters; S2. Using the LED clock as the standard clock, calculate the actual transmission delay based on the standard transmission delay when the LED transmitter communicates with the user device receiver; S3. Calculate the signal gain when the LED transmitter communicates with the user device receiver, and calculate the channel fading caused by the frequency offset based on the actual transmission delay when the LED transmitter communicates with the user device receiver and the frequency offset of the visible light signal subcarrier emitted by the LED transmitter; S4 obtains the transmission signal emitted by the LED transmitter, calculates the received signal obtained by the user equipment receiver based on the waveform of the transmitted signal, signal gain and channel fading, and constructs a received signal estimation model; S5. Based on the received signal estimation model, construct a clock synchronization and frequency calibration function, wherein the clock synchronization and frequency calibration function is a function containing unknown clock parameters and unknown frequency offset parameters; S6. Solve the clock synchronization and frequency calibration function to obtain the clock offset parameter and the frequency offset parameter, and complete the clock synchronization and frequency calibration.

[0039] In this embodiment, a visible light interawareness integrated system is first constructed, including multiple LED transmitters and a user equipment receiver equipped with a photodiode. The actual transmission delay, signal gain, and channel fading of the communication between the LED transmitter and the user equipment receiver are calculated. The transmission signal emitted by the LED transmitter is obtained, and based on the waveform, signal gain, and channel fading of the transmission signal, the received signal obtained by the user equipment receiver is calculated. A received signal estimation model is constructed, thereby constructing a clock synchronization and frequency calibration function containing unknown clock parameters and unknown frequency offset parameters. This function introduces time-frequency calibration technology into visible light communication. Based on replacing timestamp information with the received signal waveform, it reduces computational complexity while improving versatility and the accuracy of clock synchronization. Finally, the clock offset parameter and frequency offset parameter are obtained, completing clock synchronization and frequency calibration.

[0040] Example 2 In this embodiment, the structure diagram of the visible light interoception integrated system in step S1 is as follows: Figure 2 As shown, the visible light synaesthesia integrated system includes: An LED transmitter and a user equipment receiver equipped with a photodiode, wherein the photodiode is used to receive the visible light signal after O-OFDM modulation emitted by the LED transmitter and convert it into an electrical signal; wherein the first The known position vector of the LED emitter is , the direction vector is ; The known position vector of the user equipment receiver is , the direction vector is ;in, and are all unit vectors, and the expressions are:

[0041]

[0042] Specifically, the integrated visible light communication system uses orthogonal frequency division multiplexing (OFDM) modulation technology. The design of the LED transmitter meets international lighting standards for various occasions, that is, the illuminance reaches 300lx to 1500lx, and the light radiation areas overlap and cover the entire area, ensuring that all receivers in the space can receive the light signal from any LED transmitter and realize visible light communication. The multiple LED transmitters in the visible light interoception integrated system communicate with the user equipment receiver, and each LED transmitter performs orthogonal modulation to generate The interval is These subcarriers are orthogonal to each other, and the symbol interval of the subband is , any two subcarriers and satisfy: .

[0043] In this embodiment, the process of calculating the actual transmission delay in step S2 is as follows: Defines the time when the user equipment is receiving the standard time. The standard time delay for each LED emitter is , the expression is:

[0044] in, is the known position vector of the user equipment receiver, For the The known position vectors of the LED emitters, is the speed of light; Defines the clock offset parameters of the user equipment receiver The expression is:

[0045] in, represents the clock speed offset, Indicates that the clock is often offset; Using clock parameters Synchronize the clock of the user equipment receiver and set the user equipment receiver to the first Standard time delay for each LED emitter Mapped to the actual time delay when the user equipment receiver has clock deviation , the expression is: .

[0046] In this embodiment, the process of calculating the signal gain when the LED transmitter communicates with the user equipment receiver in step S3 is as follows: Calculate the The LED transmitter points to the transmission angle of the user device receiver , the user equipment receiver receives the The receiving angle of the LED transmitter , the calculation expression is:

[0047]

[0048] in, is the user equipment receiver position vector, For the The coordinate parameters of each LED emitter, For the Directional parameters of each LED emitter, is the user equipment receiver direction vector, Represents a transpose operation; Based on emission angle and receiving angle , building signal gain for visible light communication , the expression is:

[0049] in, The optical aperture of the photodiode, the optical filter gain, the concentrator gain and the first The joint band estimation parameters of the LED emitter power, is the Lambertian radiation order of the LED emitter, is the path loss exponent.

[0050] Specifically, the signal gain It is the core parameter of the channel model and reflects the attenuation characteristics of the optical signal after propagation. In the integrated visible light communication system, the transmission channel between the LED transmitter and the user equipment receiver is usually considered to be a free space channel, relying on the Lambertian radiation model. In this application, it is assumed that the radiation intensity of the LED transmitter is cosine distributed with angle, which is suitable for describing the radiation characteristics of non-directional light sources; in addition, the signal gain of visible light communication is The expression reflects the modulation effect of spatial geometry on signal intensity, where represents the directional radiation of the light source, Indicates that the effective receiving area of ​​the receiving end changes with angle.

[0051] In this embodiment, step S3 calculates the channel fading caused by the frequency offset based on the actual transmission delay when the LED transmitter communicates with the user equipment receiver and the frequency offset of the visible light signal subcarrier emitted by the LED transmitter. The expression is:

[0052] in, For the The first LED emitter emits Channel fading caused by frequency offset of subcarriers, For the The first LED emitter subcarrier frequencies, is the frequency offset caused by the local crystal oscillator, is the actual time delay when there is clock deviation in the user equipment receiver.

[0053] In this embodiment, before constructing the received signal estimation model, it also includes constructing an estimated waveform of a single received signal. , the expression is:

[0054] in, For the The first LED emitter The signal waveform sent by the subcarriers satisfies , For the The channel gain of LED optical signal transmission, For the The first LED emitter emits Channel fading caused by frequency offset of subcarriers; Integrate the estimated model of all individual received signals , build the final received signal estimation model , the expression is:

[0055] Where h is the channel gain coefficient, is the clock offset parameter of the user equipment, is the frequency offset parameter of the user equipment, and vec[] represents the operation of integrating the time synchronization models of all signals into a column vector.

[0056] In this embodiment, the expression of the clock synchronization and frequency calibration function is:

[0057] in, is the waveform model of the transmitted signal actually received by the user equipment, is the optimal channel gain coefficient, is the clock offset parameter of the user equipment receiver, is the frequency offset parameter of the user equipment receiver; The clock synchronization and frequency calibration function is solved to obtain the clock offset parameter and the frequency offset parameter, and the channel gain coefficient is obtained. When solving the clock synchronization and frequency calibration function, let 、 and The parameters are 、 and In the The state at the iteration At the iteration, the parameter 、 and The channel gain estimation algorithm, clock calibration algorithm and frequency calibration algorithm are used to update in sequence respectively; Specifically, right and Due to the nonlinear dependency, the optimization problem is non-convex and there may be countless local optimal points in the feasible domain. To solve this problem, it is necessary to find a convex approximation function of the cost function and then continuously minimize the convex approximation function to obtain the optimal clock offset and frequency offset parameters. Therefore, the received signal estimation model can be optimized as:

[0058] in, , for and The function expression is:

[0059]

[0060] in, Indicates that the elements are stacked into a matrix by column, and diag indicates that the elements are stacked into a matrix by diagonal; Specifically, the clock synchronization and frequency calibration function is optimized as follows:

[0061] In this embodiment, the iterative update alternate optimization solves the objective function to obtain the optimal channel gain coefficient, and the process is: Update the channel gain coefficient using the channel gain estimation algorithm , the update process satisfies:

[0062] in, is the channel gain coefficient In the The state at the iteration, for and function, The clock offset parameter of the user equipment receiver In the The state at the iteration, Frequency offset parameter for the user equipment receiver In the The state at the iteration, and Already in Obtained in iterations; Based on the channel gain coefficient In the The optimal estimate at the iteration, The optimal estimate of the channel gain coefficient at the iteration , the expression is:

[0063] in, Represents the pseudo-inverse matrix operation.

[0064] By mining the optimized signal estimation model The linear structure of h in the given time-frequency parameters is obtained and The optimal estimate of the lower channel gain coefficient h.

[0065] In this embodiment, the iterative update alternate optimization solves the objective function to obtain the optimal clock offset parameter of the user equipment receiver. The process is as follows: Update the clock offset parameters of the user equipment using the clock calibration algorithm , the update process satisfies:

[0066] in, The clock offset parameter of the user equipment receiver In the The state at the iteration, Frequency offset parameter for the user equipment receiver In the The state at the iteration, is the channel gain coefficient In the The state at the iteration, , The clock offset parameter of the user equipment receiver Cost function of Based on the continuous linear least squares method, the iterative solution is obtained. The clock offset parameter of the user equipment receiver at the iteration The best estimate of .

[0067] Specifically, the update process satisfies the expression Still about To solve the non-convex problem, we need to fully explore the expression About The implicit convex substructure of , the process is: Will exist Substitute the first-order Taylor expansion at into the expression In, get about Non-convex problem , the expression is:

[0068] in, for exist The derivative of the attachment is expressed as:

[0069] in, and , and The expressions are:

[0070]

[0071] in, , , and The expressions are:

[0072]

[0073]

[0074]

[0075] Using the least squares solution, the clock offset parameters are calculated The expression is:

[0076] Based on this expression, At the time of the iteration, the expressions for the estimated values ​​of clock speed offset and clock constant offset are:

[0077]

[0078] in, {} means taking the real part of the complex vector, Represents the vector l elements.

[0079] In this embodiment, the iterative update alternate optimization solves the objective function to obtain the optimal user equipment receiver frequency offset parameter. The process is as follows: Update the user equipment receiver frequency offset parameters using the frequency calibration algorithm , the update process satisfies:

[0080] in, Frequency offset parameter for the user equipment receiver In the The state at the iteration, The clock offset parameter of the user equipment receiver In the The state at the iteration, is the channel gain coefficient In the The state at the iteration, , Frequency offset parameter for the user equipment receiver Cost function of Based on the continuous linear least squares method, the iterative solution is obtained. The user equipment receiver frequency offset parameter at the iteration The best estimate of .

[0081] Specifically, the update process satisfies the expression Still about To solve the non-convex problem, we need to fully explore the expression About The implicit convex substructure of , the process is: Will exist Substitute the first-order Taylor expansion at into the expression In, get about Non-convex problem , the expression is:

[0082] in, for exist The derivative near is expressed as:

[0083] in, , the expression is:

[0084] in, , the expression is:

[0085]

[0086] Using the least squares solution, the frequency offset parameters are calculated The expression is:

[0087] Specifically, after the alternating iteration of the above clock offset parameters and frequency offset parameters, the first The estimated error value after iterations is expressed as:

[0088] The sum of squared errors of the estimated error values The expression is:

[0089] Jordi The sum of squares of the estimated error values ​​before and after iterations Less than threshold , or the number of iterations Greater than or equal to the cutoff number , the iteration is stopped, thereby obtaining the optimal channel gain coefficient, clock offset parameter and frequency offset parameter of the user equipment receiver.

[0090] Specifically, the method for solving the clock synchronization and frequency calibration function to obtain the optimal channel gain coefficient, clock offset parameter, and frequency offset parameter of the user equipment receiver is a time-frequency calibration algorithm based on the signal waveform. The pseudo code of the algorithm is shown in Table 1: Table 1

[0091] Example 3 In this embodiment, a MATLAB platform is used for simulation to construct a visible light synaesthesia integrated system; Specifically, set the number of LED emitter light sources , these LED emitters are evenly arranged in a side length The LED light source is irradiated vertically downwards, i.e. ; Set the number of subcarriers , carrier frequency Approximately ,bandwidth , sampling period , the speed of light The path loss exponent and the Lambertian radiation order are set as and , response coefficient ; True value of the user equipment receiver clock speed offset , the clock is always biased to the true value , the true value of the frequency offset parameter ; In addition, the signal-to-noise ratio (SNR) of the user equipment receiver is set to 20 dB, and the expression is:

[0092] In this embodiment, based on a visible light synaesthesia integrated system constructed by simulation, the performance of different time-frequency calibration methods is compared with the time-frequency calibration method proposed in the present invention; Specifically, in order to better illustrate the performance of the calibration algorithm proposed in the present invention, the following three algorithms are used as comparison benchmarks: a clock calibration algorithm based on timestamp without frequency calibration, a clock calibration algorithm based on signal waveform without frequency calibration, and a frequency calibration algorithm based on signal waveform without clock calibration; Specifically, a comparison curve diagram of the clock speed offset obtained by iteratively obtaining the method proposed by the present invention and the clock calibration algorithm based on the signal waveform without frequency calibration is shown in FIG. Figure 3 As shown; the comparison curve diagram of the clock deviation obtained by iteratively obtaining the clock calibration algorithm based on the method proposed by the present invention and the clock calibration algorithm without frequency calibration based on the signal waveform is shown as follows Figure 4 As shown; the horizontal axis represents the number of iterations, and the vertical axis represents the estimated error of the clock speed offset and the estimated error of the clock bias .

[0093] Specifically, a comparison curve diagram of the frequency offset parameters obtained by iteratively obtaining the method proposed by the present invention and the frequency calibration algorithm based on the signal waveform without clock calibration is shown in FIG. Figure 5 As shown, the horizontal axis represents the number of iterations and the vertical axis represents the estimated error of the frequency offset .

[0094] Observing the iterative results, it can be seen that the joint calibration algorithm proposed in the present invention quickly converges to a stable error level within 20 iterations. Compared with the clock calibration algorithm without frequency calibration and the frequency calibration algorithm without clock calibration, the algorithm proposed in the present invention achieves lower clock and frequency calibration errors, where the estimated errors of clock speed offset, clock constant offset and frequency offset are lower than , 0.01ps and 1Hz.

[0095] In this embodiment, the clock offset parameter errors and frequency offset parameter errors of the method proposed in the present invention and three reference methods are compared under different signal-to-noise ratio conditions. The comparison curve of the clock speed offset obtained by iteratively using the method proposed in the present invention and the clock calibration algorithm based on timestamp and signal waveform without frequency calibration is shown in FIG. Figure 6 As shown; the comparison curve of the clock deviation obtained by iteratively performing the method proposed by the present invention and the clock calibration algorithm based on the timestamp and signal waveform without frequency calibration is shown as follows Figure 7 As shown; the horizontal axis represents the signal-to-noise ratio, and the vertical axis represents the estimated error of the clock speed offset and the estimated error of the clock bias .

[0096] Specifically, a comparison curve diagram of the frequency offset parameters obtained by iteratively obtaining the frequency calibration algorithm based on the signal waveform without clock calibration under different signal-to-noise ratio conditions is shown in FIG. Figure 8 As shown, the horizontal axis represents the number of iterations and the vertical axis represents the estimated error of the frequency offset .

[0097] As the signal-to-noise ratio increases, the clock calibration algorithm based on timestamps and signal waveforms without frequency calibration is affected by frequency offset due to the lack of frequency calibration, and its clock parameter estimation error will tend to saturate and form an error lower limit; in addition, the clock parameter estimation error accuracy of the clock calibration algorithm based on timestamps without frequency calibration will also be limited by the timestamp.

[0098] In contrast, the algorithm proposed in this paper shows that the estimated errors of velocity offset and clock constant bias gradually decrease as the signal-to-noise ratio increases. This is because the associated frequency errors are reduced through the joint calibration process, thus breaking the lower limit of the clock parameter errors. Furthermore, due to unavoidable clock errors, frequency calibration algorithms based on signal waveforms without clock calibration will reach the lower limit of the frequency offset estimation error. The algorithm proposed in this paper effectively solves this problem.

[0099] In this embodiment, the clock offset parameter errors of the method proposed in the present invention and the reference method are compared at different subcarrier frequencies. The comparison curves of the clock speed offsets obtained by iteratively using the method proposed in the present invention and the clock calibration algorithm based on timestamps and signal waveforms without frequency calibration at different subcarrier frequencies are shown in FIG. Figure 9 As shown; under different subcarrier frequencies, the comparison curve of the clock deviation obtained by iteratively using the method proposed by the present invention and the clock calibration algorithm based on timestamp and signal waveform without frequency calibration is shown as follows Figure 10 As shown; the horizontal axis represents the subcarrier frequency , the vertical axis represents the estimated error of clock speed offset and the estimated error of the clock bias .

[0100] The results show that as the baseband subcarrier frequency increases, the estimation performance gain of the method proposed in the present invention is significantly expanded compared with the clock calibration algorithm based on timestamp without frequency calibration and the clock calibration algorithm based on signal waveform without frequency calibration.

[0101] This is because compared with the clock calibration algorithm based on timestamp without frequency calibration, the algorithm proposed in this paper utilizes the phase information of the received visible light signal waveform, so a larger subcarrier frequency will bring higher spatial resolution; in addition, compared with the clock calibration algorithm based on signal waveform without frequency calibration, the algorithm proposed in this paper can effectively reduce the impact of frequency error.

[0102] In this embodiment, the relationship between the clock offset parameter estimation error and the frequency offset parameter of the method proposed in the present invention and the frequency calibration algorithm based on the signal waveform without clock calibration is compared. The schematic diagram of the comparison curve of the clock speed offset parameter estimation error using the method proposed in the present invention and the frequency calibration algorithm based on the signal waveform without clock calibration is shown as follows: Figure 11 As shown; the comparison curve diagram of the clock bias parameter estimation error using the method proposed by the present invention and the frequency calibration algorithm based on the signal waveform without clock calibration is shown as follows Figure 12 shown.

[0103] The horizontal axis represents the frequency offset, and the vertical axis represents the estimated error of the clock speed offset. and the estimated error of the clock bias .

[0104] Results show that the clock parameter error of a clock calibration algorithm based on signal waveforms without frequency calibration increases with increasing frequency offset error. However, the performance of the proposed method remains unaffected due to the use of a joint time-frequency calibration scheme. This demonstrates the contribution of joint calibration in suppressing frequency offset error.

[0105] Obviously, the above embodiments of the present invention are merely examples for the purpose of clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the claims of the present invention.

Claims

1. A time-frequency calibration method for a visible light synaesthesia integrated system, characterized in that: The following steps are involved: S1. Constructing an integrated visible light synaesthesia system, the system comprising: a plurality of LED emitters and a user device receiver equipped with a photodiode, the plurality of LED emitters communicating with the user device receiver, the user device receiver receiving visible light signals emitted by the LED emitters; S2. Using the LED clock as the standard clock, calculate the actual transmission delay based on the standard transmission delay when the LED transmitter communicates with the user device receiver; S3. Calculate the signal gain when the LED transmitter communicates with the user device receiver, and calculate the channel fading caused by the frequency offset based on the actual transmission delay when the LED transmitter communicates with the user device receiver and the frequency offset of the visible light signal subcarrier emitted by the LED transmitter; S4 obtains the transmission signal emitted by the LED transmitter, calculates the received signal obtained by the user equipment receiver based on the waveform of the transmitted signal, signal gain and channel fading, and constructs a received signal estimation model; S5. Based on the received signal estimation model, construct a clock synchronization and frequency calibration function, wherein the clock synchronization and frequency calibration function is a function containing unknown clock parameters and unknown frequency offset parameters; S6. Solve the clock synchronization and frequency calibration function to obtain the clock offset parameter and the frequency offset parameter, and complete the clock synchronization and frequency calibration.

2. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 1, characterized in that: The visible light synaesthesia integrated system in step S1 includes: An LED transmitter and a user equipment receiver equipped with a photodiode, wherein the photodiode is used to receive the visible light signal after O-OFDM modulation emitted by the LED transmitter and convert it into an electrical signal; wherein the first The known position vector of the LED emitter is , the direction vector is ; The known position vector of the user equipment receiver is , the direction vector is ;in, and are all unit vectors, and the expressions are: 。 3. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 2, characterized in that: The process of calculating the actual transmission delay in step S2 is as follows: Calculate the time at which the user equipment receives the standard time The standard time delay for each LED emitter is , the expression is: in, is the known position vector of the user equipment receiver, For the The known position vectors of the LED emitters, is the speed of light; Calculate the clock offset parameters of the user equipment receiver , the expression is: in, represents the clock speed offset, Indicates that the clock is often offset; Using clock parameters Synchronize the clock of the user equipment receiver and set the user equipment receiver to the first Standard time delay for each LED emitter Mapped to the actual time delay when the user equipment receiver has clock deviation , the expression is: 。 4. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 2, characterized in that: The process of calculating the signal gain when the LED transmitter communicates with the user equipment receiver in step S3 is as follows: Calculate the The LED transmitter points to the transmission angle of the user device receiver , the user equipment receiver receives the The receiving angle of the LED transmitter , the calculation expression is: in, is the user equipment receiver position vector, For the The coordinate parameters of each LED emitter, For the Directional parameters of each LED emitter, is the user equipment receiver direction vector, Represents a transpose operation; Based on emission angle and receiving angle , building signal gain for visible light communication , the expression is: in, The optical aperture of the photodiode, the optical filter gain, the concentrator gain and the first The joint band estimation parameters of the LED emitter power, is the Lambertian radiation order of the LED emitter, is the path loss exponent.

5. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 3, characterized in that: In step S3, the channel fading caused by the frequency offset is calculated based on the actual transmission delay when the LED transmitter communicates with the user equipment receiver and the frequency offset of the visible light signal subcarrier emitted by the LED transmitter. The expression is: in, For the The first LED emitter emits Channel fading caused by frequency offset of subcarriers, For the The first LED emitter subcarrier frequencies, is the frequency offset caused by the local crystal oscillator, is the actual time delay when the user equipment receiver has clock deviation, is the number of LEDs.

6. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 5, characterized in that: Before constructing the received signal estimation model, it also includes constructing an estimated waveform of a single received signal , the expression is: in, For the The first LED emitter The signal waveform sent by the subcarriers satisfies , For the The channel gain of LED optical signal transmission, For the The first LED emitter emits Channel fading caused by frequency offset of subcarriers; Integrate the estimated model of all individual received signals , build the final received signal estimation model , the expression is: in, is the channel gain coefficient, is the clock offset parameter of the user equipment, is the frequency offset parameter of the user equipment, vec[] represents the operation of integrating the time synchronization model of all signals into a column vector, is the number of OFDM subcarriers.

7. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 6, characterized in that: The expression of the clock synchronization and frequency calibration function is: in, is the waveform model of the transmitted signal actually received by the user equipment, is the optimal channel gain coefficient, is the clock offset parameter of the user equipment receiver, is the frequency offset parameter of the user equipment receiver; The clock synchronization and frequency calibration function is solved to obtain the clock offset parameter and the frequency offset parameter, and the channel gain coefficient is obtained. When solving the clock synchronization and frequency calibration function, let 、 and The parameters are 、 and In the The state at the iteration At the iteration, the parameter 、 and The channel gain estimation algorithm, clock calibration algorithm and frequency calibration algorithm are used to update in sequence respectively.

8. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 7, characterized in that: The iterative update alternately optimizes and solves the objective function to obtain the optimal channel gain coefficient. The process is: Update the channel gain coefficient using the channel gain estimation algorithm , the update process satisfies: in, is the channel gain coefficient In the The state at the iteration, for and function, The clock offset parameter of the user equipment receiver In the The state at the iteration, Frequency offset parameter for the user equipment receiver In the The state at the iteration, and Already in Obtained in iterations; Based on the channel gain coefficient In the The optimal estimate at the iteration, The optimal estimate of the channel gain coefficient at the iteration , the expression is: in, Represents the pseudo-inverse matrix operation.

9. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 7, characterized in that: The iterative update alternately optimizes and solves the objective function to obtain the optimal clock offset parameter of the user equipment receiver. The process is: Update the clock offset parameters of the user equipment using the clock calibration algorithm , the update process satisfies: in, The clock offset parameter of the user equipment receiver In the The state at the iteration, Frequency offset parameter for the user equipment receiver In the The state at the iteration, is the channel gain coefficient In the The state at the iteration, , The clock offset parameter of the user equipment receiver Cost function of Based on the continuous linear least squares method, the iterative solution is obtained. The clock offset parameter of the user equipment receiver at the iteration The best estimate of .

10. The time-frequency calibration method for a visible light synaesthesia integrated system according to claim 7, characterized in that: The iterative update alternately optimizes and solves the objective function to obtain the optimal user equipment receiver frequency offset parameter. The process is: Update the user equipment receiver frequency offset parameters using the frequency calibration algorithm , the update process satisfies: in, Frequency offset parameter for the user equipment receiver In the The state at the iteration, The clock offset parameter of the user equipment receiver In the The state at the iteration, is the channel gain coefficient In the The state at the iteration, , Frequency offset parameter for the user equipment receiver Cost function of Based on the continuous linear least squares method, the iterative solution is obtained. The user equipment receiver frequency offset parameter at the iteration The best estimate of .

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