50 results about "Nonlinear equalization" patented technology

The invention discloses a nonlinear equalization method, device and equipment and a storage medium, and relates to the technical field of communication, and the method comprises the steps: obtaining a floating point tap coefficient of an original equalizer, and carrying out the low-order quantization of the floating point tap coefficient, and obtaining an integer tap coefficient; constructing a target equalizer based on the integer tap coefficient; and compensating nonlinear distortion of a to-be-processed signal based on the target equalizer to obtain a recovered signal. Through the mode, the low-order quantization is performed on the tap coefficient of the equalizer, and the traditional floating-point number is converted into the low-order integer for representation, so that the storage space and the calculation complexity are remarkably reduced, the hardware implementation efficiency can be optimized and the power consumption can be reduced while the transmission performance is ensured.

A data channel on an integrated circuit device includes a non-linear equalizer having as inputs digitized samples of signals on the data channel, decoding circuitry configured to determine from outputs of the non-linear equalizer a respective value of each of the signals, and adaptation circuitry configured to adapt parameters of the non-linear equalizer based on respective ones of the value. The non-linear equalizer includes a non-linear filter portion, and a front-end filter portion configured to reduce numbers of the inputs from the digitized samples. The non-linear equalizer may be a neural network equalizer, such as a multi-layer perceptron neural network equalizer, a reduced complexity multi-layer perceptron neural network equalizer, or a radial-basis function neural network equalizer. Alternatively, the non-linear equalizer may include a linear filter and a non-linear activation function, which may be a hyperbolic tangent function.

The invention relates to the technical field of signal balanced transmission, and discloses a high-speed photoelectric interconnection signal balanced transmission method and device, and the method comprises the steps: carrying out the bandwidth characteristic and nonlinear characteristic collection of an on-chip photoelectric interconnection channel, and obtaining a channel characteristic data set; scattering parameters of the on-chip photoelectric interconnection channel are measured according to the channel characteristic data set, S21 pre-compensation processing is carried out, and a pre-compensation signal is obtained; on-chip multi-channel parallel transmission is carried out on the pre-compensation signal, and multi-channel transmission state information is collected; inputting the pre-compensation signal and the multi-channel transmission state information into a double-level signal equalization model for linear and nonlinear equalization processing to obtain a first equalization signal; and carrying out mixed compensation operation of time domain equalization and frequency domain equalization on the first equalization signal to obtain a second equalization signal. According to the invention, through real-time monitoring and dynamic compensation, the influence of channel crosstalk and dispersion distortion is effectively inhibited, and the stability of signal transmission is ensured.

The invention provides a short-distance high-speed optical fiber communication equalization method and system, and the method comprises the steps: building a Gaussian mixture model for an optical signal subjected to the quadrature amplitude modulation of a set order, and completing the parameter initialization of the Gaussian mixture model through a particle swarm optimization algorithm of which the inertia weight is firstly increased and then decreased; the method comprises the following steps: inputting data features of two dimensions of an in-phase component and an orthogonal component of data into a Gaussian mixture model, then solving parameters of the Gaussian mixture model by using an expectation maximization algorithm, and determining the membership degree of each data point and a clustering label corresponding to each unary Gaussian distribution through the parameters; and through the maximum posterior probability, the data are distributed to the corresponding clustering labels, and nonlinear equalization is completed. According to the method, the memory property of signal nonlinear impairment can be accurately captured, the nonlinear clustering precision is improved, and the calculation complexity of a nonlinear clustering model is reduced under the same clustering effect.

The invention relates to the technical field of coherent light transmission, and discloses a nonlinear equalization method of an ultra-high-order QAM coherent light transmission system, which comprises the following steps: acquiring a damaged digital signal after a signal to be transmitted is transmitted; iQ orthogonalization is carried out on the X polarization state and the Y polarization state of the damaged digital signal, in-phase components and orthogonal components of the X polarization state and the Y polarization state are obtained and expressed as XI, XQ, YI and YQ, and optimized in-phase components and optimized orthogonal components of the X polarization state and the Y polarization state are obtained through dispersion compensation, clock recovery, multimode operation, frequency offset estimation and carrier phase recovery in sequence; for the X polarization state and the Y polarization state, the optimized in-phase component and the optimized orthogonal component are used as input, an improved Wollaston polynomial equalizer is input, combined equalization is carried out through Wollaston series, corresponding X polarization state estimation digital signals and Y polarization state estimation digital signals are output, and equalization digital signals are obtained through fusion. And completing nonlinear equalization of the damaged digital signal.

The invention discloses an optical transmission system based on an FEC extended perturbation optical fiber nonlinear compensation technology, and relates to the technical field of optical fiber communication. A receiving end comprises an adaptive perturbation equalization module, a soft decision demodulation module, a de-interleaving module, an FEC decoding module, an interleaving module and a symbol reconstruction module based on soft information which are connected in sequence. The self-adaptive perturbation nonlinear equalization module is of a double-input structure and is connected with the output end of the symbol reconstruction module based on soft information besides receiving signals. The output data of the interleaving module and the output data of the soft decision demodulation module are added and then input to the second input end of the soft decision demodulation module; and the output end and the sending end of the FEC decoding module adopt a decoding mode with the same code pattern, and a received bit result is output. According to the invention, the receiver sensitivity and the optical fiber nonlinear effect tolerance in the optical system can be improved.

The nonlinearity of power amplifiers (PAs) has been a severe constraint in performance of modern wireless transceivers. This problem is even more challenging for the fifth generation (5G) cellular system since 5G signals have extremely high peak to average power ratio. Nonlinear equalizers that exploit both deep neural networks (DNNs) and Volterra series models are provided to mitigate PA nonlinear distortions. The DNN equalizer architecture consists of multiple convolutional layers. The input features are designed according to the Volterra series model of nonlinear PAs. This enables the DNN equalizer to effectively mitigate nonlinear PA distortions while avoiding over-fitting under limited training data. The non-linear equalizers demonstrate superior performance over conventional nonlinear equalization approaches.

Methods, systems, and devices for wireless communications are described. Generally, a base station may indicate, to a user equipment (UE), when it changes a power amplifier (PA) non-linearity model. The base station may transmit a set of parameters for the PA model, and a set of parameters for a non-linear equalizer function for the UE to use during a digital post-processing procedure (DPoD). The base station may indicate, to the UE, a lookup table, a vector of lookup tales, a set of kernels (e.g., from which the UE may estimate the coefficients of the PA model), or a set of both the kernels and the coefficients for the PA model. Similarly, for the non-linear equalizer function, the base station may indicate an explicit indication of the function, or may indicate a lookup table, or a kernels series (e.g., with or without corresponding coefficients).

This invention discloses a fiber optic nonlinear equalization method based on perturbation theory using a complex-valued convolutional neural network, comprising the following steps: S1, constructing a complex-valued channel feature map from symbol samples using perturbation theory to form an original training set, and inputting it into the neural network; S2, training the complex-valued convolutional neural network using the original training dataset, fitting the training data, and finally obtaining the most suitable nonlinear equalizer model; S3, constructing a complex-valued channel input feature map for the test signal, and inputting it as the test set into the fitted nonlinear equalizer model for equalization, obtaining the output result. The fiber optic nonlinear equalization method based on perturbation theory proposed in this invention utilizes perturbation theory combined with a complex-valued convolutional neural network to extract more useful feature information, solving the problems of high bit error rate and poor compensation effect during nonlinear equalization, improving the nonlinear compensation effect, and greatly enhancing system performance.

The invention discloses a nonlinear equalization method and device for digital subcarrier multiplexing signals and an optical fiber communication system. The method comprises the following steps: caching an original symbol of a transmitting end, and preprocessing a received signal to obtain a signal to be equalized; constructing a power model according to the link parameters and deducing a back propagation power model; inputting the data into an improved digital back transmission algorithm, and calculating a nonlinear accumulation amount in each equalization step length; determining an initial splitting ratio parameter by using a nonlinear symmetry principle, and embedding the initial splitting ratio parameter into the neural network as a trainable variable; inputting a received signal and an original symbol into a network, and optimizing a splitting ratio through gradient descent to obtain an optimal value; therefore, the position of a nonlinear operator in the improved digital back transmission algorithm is adjusted, linear and nonlinear combined compensation of the signal is realized, and a high-precision equalization result is output. According to the method, extra communication overhead is not needed, and the link power non-uniformity characteristic can be effectively adapted.

The invention relates to the field of optical fiber communication, in particular to a four-dimensional modulation signal recovery method and device, equipment, a medium and a product, and the method comprises the steps: dynamically obtaining a corresponding filter tap coefficient and phase information needed by phase compensation for each piece of target point information, the filter tap coefficient is updated based on the filter tap coefficient of the previous target point information and the original sending signal sequence, and the phase information corresponding to the target point information is updated based on the phase information of the previous target point information and the original sending signal sequence; low-complexity and robust phase estimation for four-dimensional modulation irregular constellation points is realized; performing nonlinear signal equalization by using an MIMO nonlinear equalizer in combination with target point information and a filter tap coefficient; phase compensation is carried out according to the balanced output signal and the phase information, and phase recovery is carried out while multi-dimensional balancing is carried out, so that the phase noise influence of balancing enhancement is reduced, and the transmission reliability of the four-dimensional modulation signal is improved.

The application discloses an optical fiber nonlinear equalization method, system, electronic equipment and medium, and relates to the technical field of optical fiber communication, and the method comprises the following steps: acquiring a target symbol sequence; the target symbol sequence is a symbol sequence of a received optical signal to be tested received by a receiving end; a perturbation triple product eigenvalue of each symbol in the target symbol sequence is constructed by using a perturbation theory to obtain a target eigenvalue set; the target eigenvalue set is input into an equalizer model to obtain a data category of the target symbol sequence after equalization; wherein the equalizer model is obtained by training a complex full-connection neural network by using training data. The application can obtain an equalizer model closer to a real value, and improve the performance of optical fiber signal nonlinear equalization.

The invention discloses a nonlinear equalizer for terahertz communication and a nonlinear equalization method of CNN-RES-LSTM combination, and belongs to the technical field of terahertz communication. The invention designs a nonlinear equalizer applied between a signal generator and a signal modulator of a terahertz communication system, which is used for carrying out nonlinear equalization processing on the terahertz communication system. The nonlinear equalizer refers to a neural network model based on CNN-RES-LSTM combination, and the processing steps of the CNN-RES-LSTM combination method are as follows: (1) improved CNN output retention: after spatial features are extracted from an improved CNN layer, the output is retained; (2) feature transformation and alignment: adjusting the feature dimension output by the CNN, and enabling the feature dimension to be matched with the dimension input by the LSTM; and (3) jump connection: directly splicing the adjusted CNN output with the LSTM. According to the invention, the problem of loss in a terahertz communication system is overcome, the performance and efficiency of balanced electric signals are calculated on demand, and the stability of signal transmission is improved.

A power amplifier nonlinear correction algorithm suitable for a broadband high-order modulation signal relates to the technical field of channel nonlinear equalization, and comprises the following steps: acquiring a baseband signal and carrying out synchronous preprocessing to generate a time sequence signal and a timing synchronization signal; generating a balanced input vector according to the time sequence signal and the timing synchronization signal; constructing an OS-ELM balancing unit for processing the balancing input vector and generating a balancing output result; after an equalization output result is processed by a buffer, an equalization output vector is extracted; a symbol decision unit is constructed and used for generating a symbol decision soft value according to the time sequence signal and the balanced output vector; constructing an online training unit, which is used for generating an online label vector according to the time sequence signal and the symbol decision soft value, and generating a hidden layer output matrix according to the time sequence signal and the balanced input vector; finally, combining the online label vector, the hidden layer output matrix and the hidden layer output matrix of the historical sample to generate a weight matrix; using the weight matrix to update an equalization output result; and the calculation complexity is low.

The present invention discloses a fiber optic nonlinear equalization method, system, device and storage medium, belonging to the field of optical transmission technology. The method includes: obtaining the M-QAM signal sequence received at the receiving end; inputting the M-QAM signal sequence into a trained bidirectional long short-term memory neural network based on a memristor array to output a score matrix; using the Viterbi algorithm to obtain the optimal label sequence corresponding to each input feature sequence according to the score matrix and the training score matrix obtained during the training process. The intermediate label values of all the optimal label sequences form the label values of the M-QAM signal sequence, and the data categories corresponding to the label values are subjected to constellation mapping to obtain the original signal sequence transmitted by the transmitting end, thus completing the nonlinear equalization. The present invention uses a memristor array to implement synaptic weights, greatly reducing the complexity of the network, and uses the bidirectional feature to process the current input information by combining the information of the previous and subsequent sequences, improving the signal quality and transmission performance.

The invention discloses a high-precision communication sensing integration method, belongs to the technical field of communication sensing integration, and aims to solve the problems of complicated steps and low accuracy of traditional microalgae density detection. The method comprises the following steps: preparing a microalgae sample and obtaining a density reference value, deducing a communication bit error rate mathematical expression related to multiple parameters, designing an OOK / PAM4 modulation and low-complexity nonlinear equalization algorithm, obtaining a bit error rate data set by taking a microalgae solution as a transmission medium, and constructing and verifying a microalgae density-bit error rate correlation model. Reversely deducing a density value, optimizing a test interval, repeatedly verifying the accuracy rate, outputting multiple parameters, and analyzing an association relationship; communication and sensing collaboration is achieved, the average accuracy rate of microalgae density monitoring exceeds 95%, the adaptation rate range is wide, chip integration of an equalizer is easy, no contact is achieved, environmental protection is achieved, and the system is suitable for microalgae cultivation, marine environment monitoring and other scenes.

The invention provides a non-linear optical channel equalization method and system and a medium, and relates to the technical field of optical fiber communication, and the method comprises the steps: carrying out the signal element definition of an optical signal, receiving the optical signal transmitted by an optical channel, executing the signal element verification, and if there is non-linear disturbance, carrying out the signal element verification; the method comprises the following steps of: performing probability density distribution reconstruction based on amplitude on an optical signal, performing optical signal equalization processing under entropy maximization by measuring distribution entropy and triggering a probability distribution equalizer aiming at the probability density distribution, outputting a target optical signal after nonlinear equalization of the optical signal, and importing the target optical signal into an optical channel, and the probability distribution equalizer is arranged at a peripheral interface of the optical channel in an embedded manner. The technical problems that in the prior art, non-linear optical channel equalization calculation is poor in real-time performance, compensation precision is insufficient, and consequently optical communication performance and efficiency are low are solved. The technical effects that the optical signal transmission quality is efficiently and accurately improved, and thus the performance and efficiency of the whole optical communication are improved are achieved.

The invention relates to a digital signal processing system for a signal receiving end, which comprises a first 4 * 4 MIMO (Multiple Input Multiple Output) equalizer, a carrier phase recovery module, a Wollaston nonlinear equalizer, a second 4 * 4 MIMO equalizer, a third 4 * 4 MIMO equalizer and an error rate calculation module which are connected in sequence, and the first, second and third 4 * 4 MIMO equalizers all meet the following conditions: in polarization demultiplexing, each of the first, second and third 4 * 4 MIMO equalizers meets the following conditions: 1, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8, 9, 10, 11, 12, 13 X polarization of an input signal is split into an I component and a Q component, Y polarization of the input signal is split into the I component and the Q component, four independent real-value filters are arranged for the I component and the Q component corresponding to the X polarization and the I component and the Q component corresponding to the Y polarization respectively, 16 real-value filters are deployed in total, and the MIMO equalizer is obtained. The digital signal processing system for the signal receiving end constructed by the invention can effectively and reliably restore the received signal.

A system and method for equalization of a linear or non-linear system. The system includes an adder configured to add an analog reference signal and an input signal, a processing system configured to process a sum of the analog reference signal and the input signal, a non-linear equalizer (NLEQ) configured to process an output of the processing system to remove a distortion incurred by the processing system, a calibration circuitry configured to generate a reconstructed reference signal in digital domain based on measurement of the analog reference signal, and generate coefficients for the NLEQ based on the reconstructed reference signal and the output of the processing system, and a subtractor configured to subtract the reconstructed reference signal from an output of the NLEQ. The analog reference signal may be a sinusoid including single or multiple tones of sinusoids. The non-linear system may be an analog-to-digital converter (ADC).

This invention discloses an optical transmission system based on FEC (Fiber Optic Expansion Coefficient) extended perturbation fiber nonlinearity compensation technology, belonging to the field of optical fiber communication technology. Its receiver includes, in sequence, an adaptive perturbation equalization module, a soft-decision demodulation module, a deinterleaving module, an FEC decoding module, an interleaving module, and a soft-information-based symbol reconstruction module. The adaptive perturbation nonlinear equalization module has a dual-input structure, connected to the output of the soft-information-based symbol reconstruction module in addition to the received signal. The output data of the interleaving module is added to the output data of the soft-decision demodulation module and then input to the second input of the soft-decision demodulation module. The output of the FEC decoding module uses the same decoding method as the transmitter to output the received bit result. This invention can improve the receiver sensitivity and fiber nonlinearity tolerance in optical systems.

The present application relates to the technical field of signal balanced transmission, and discloses a signal balanced transmission method and device for high-speed optoelectronic interconnection, the method comprising: collecting bandwidth characteristics and nonlinear characteristics of an on-chip optoelectronic interconnection channel to obtain a channel characteristic data set; measuring the scattering parameters of the on-chip optoelectronic interconnection channel according to the channel characteristic data set, and performing S21 pre-compensation processing to obtain a pre-compensated signal; performing on-chip multi-channel parallel transmission of the pre-compensated signal, and collecting multi-channel transmission state information; inputting the pre-compensated signal and the multi-channel transmission state information into a two-level signal equalization model for linear and nonlinear equalization processing to obtain a first equalized signal; performing a mixed compensation operation of time domain equalization and frequency domain equalization on the first equalized signal to obtain a second equalized signal. The present application effectively suppresses the influence of channel crosstalk and dispersion distortion through real-time monitoring and dynamic compensation, and ensures the stability of signal transmission.

The present invention discloses an MZM non - linear equalization compensation method based on the LM - BP neural network algorithm, belonging to the field of communication. First, at the transmitting end of the system, the generation of random signals and the modulation of PAM4 signals are implemented in Matlab. A PAM4 signal IM / DD back - to - back transmission system is built using the VPI simulation platform to simulate the non - linear damage caused by MZM and transmit the signals. The signal data after transmission is collected, and digital signal processing is performed through Matlab after going offline. The compensation algorithm of the present invention is to put the offline data into the neural network model, generate a large amount of empirical data through learning and exploration of the data to train the model, and finally extract the trained neural network model to verify the data signal. This method has an extremely fast operation speed, high accuracy after training, low scheme cost, good effect, can ensure the stability of the IM / DD system transmission, achieve precise compensation for MZM; and while not increasing the algorithm complexity, reduce the transmission error rate and improve the transmission efficiency of the system.

This invention proposes a field recovery-assisted iterative nonlinear channel equalization method for use in intensity modulation direct detection (IM / DD) fiber optic transmission systems. The method cascades the Gerchberg-Saxton (GS) iterative algorithm with a Volterra decision feedback equalizer (VDFE) in a digital receiver, forming a GS-VDFE equalizer. The GS iterative module proceeds first, iteratively updating the optical field by inferring the phase from the optical intensity signal, initially compensating for fiber dispersion and increasing the power at fading frequencies. The VDFE module follows, employing a simplified structure of a second-order feedforward Volterra and a first-order feedback DFE, to perform nonlinear equalization on the GS output signal to eliminate residual distortion. GS preprocessing eliminates the need for high-order nonlinear compensation in the VDFE, reducing equalizer complexity and noise sensitivity. The VDFE handles residual compensation, reducing the number of GS iterations to below 20, thus lowering processing latency. This invention effectively recovers high-speed digital signals in high-dispersion channels and mitigates spectral fading and self-reflection interference without altering the existing system structure.

The invention belongs to the technical field of communication, and particularly relates to a simplified second-order Volterra nonlinear equalization algorithm and device for digital signal processing of a receiving end in a communication system. The algorithm comprises the following steps: training: based on a second-order Volterra algorithm, balancing received data according to two groups of first-order weight coefficients and second-order weight coefficients, and calculating errors by taking sent data as reference; updating and optimizing each weight coefficient; simplification is carried out, the finally optimized second-order nonlinear weight coefficients are arranged from large to small according to absolute values of amplitudes, 70% of smaller parts are deleted, and values of the remaining parts are used as simplified second-order nonlinear weight coefficients; and balancing: successively balancing the effective data except the training sequence by using the obtained first-order weight coefficient and the simplified second-order weight coefficient. The method solves the problem that a traditional nonlinear equalizer is high in calculation complexity, has good universality, and is suitable for digital signal processing of receiving ends of various communication systems.

The invention relates to a nonlinear system correction method based on a nonlinear equalization filter. The method comprises the following steps: constructing a dual-tone sinusoidal baseband signal based on an FPGA, transmitting the dual-tone sinusoidal baseband signal as a training signal through an antenna after passing through a nonlinear transmission system; receiving the transmitted signal through an antenna, and transforming it into a baseband signal with nonlinear characteristics through a nonlinear receiving system; performing single-point FFT transformation on both the baseband signal with nonlinear characteristics and the dual-tone sinusoidal baseband signal constructed by the FPGA, and inputting the transformed signal into an ARM end, and obtaining an optimal filter coefficient vector and a corresponding combination of multiple delay items through calculation by the ARM; constructing a nonlinear signal by using a nonlinear equalization filter according to the optimal filter coefficient vector and the corresponding combination of multiple delay items of the dual-tone sinusoidal baseband signal constructed by the FPGA, and obtaining a signal after the nonlinear characteristics are corrected by subtracting the constructed nonlinear signal from the baseband signal with nonlinear characteristics.

The application relates to the technical field of optical fiber communication, and particularly discloses an optical fiber nonlinear equalization method and system based on a bit-by-bit estimation neural network. The method comprises the following steps: acquiring M-QAM data of a coherent optical communication system sender, converting the M-QAM data into bits corresponding to a modulation format of the M-QAM data, and taking the bits as neural network labels; performing linear equalization on a signal transmitted through the coherent optical communication system to obtain data only retaining a nonlinear effect, and taking the data as neural network data; processing the data, constructing a feature sequence corresponding to the data, and constructing a training set and a test set based on the feature sequence and the labels; constructing a CNN-BiGRU neural network based on bit-by-bit estimation, training and optimizing the neural network by using the training set; and predicting corresponding sender data based on the test set by using the trained neural network. The method improves the optical fiber nonlinear equalization performance and reduces the complexity, and can be applied to a long-distance, high-order modulation format and a multi-channel system.

The invention discloses a simplified super-Nyquist transmission method for optical interconnection in a high-speed data center, and relates to the technical field of optical communication. Comprising the following steps that: a transmitting end pre-codes a transmitting signal by using a simplified pre-coding technology to obtain a pre-coded signal; the pre-coded signal is transmitted to a receiving end through an optical fiber, and the receiving end receives the pre-coded signal sent by the transmitting end; and finally, decoding the pre-coded signal to obtain a transmission signal. According to the method, the processing of the signal is split to the transmitting end and the receiving end, and the transmitting signal is pre-coded before the signal is transmitted, namely the transmitting end, so that the inter-symbol interference possibly generated in the subsequent process of the transmitting signal is eliminated in advance, and error propagation is suppressed; and residual damage is eliminated by using simplified nonlinear equalization at a receiving end. According to the method, the system complexity is greatly reduced while the performance is maintained.

Disclosed are a nonlinear equalization method and apparatus for an optical transmission system, relating to the technical field of optical communications. The method comprises: on the basis of a specifically structured frame received, training a noise-filtering network and a main network, wherein the noise-filtering network is configured for tracking and filtering out time-varying noise, and the main network is configured for static nonlinear equalization; the specifically structured frame comprises a reference frame, an interference frame, and a test frame, wherein the reference frame is configured for training the main network so as to achieve convergence of a weight coefficient of the main network, the interference frame and the reference frame are configured for training the noise-filtering network so as to achieve real-time convergence of the noise-filtering network, and the test frame is configured for carrying a random service signal and testing system performance; performing nonlinear equalization on the test frame using the trained noise-filtering network and the trained main network, and outputting an equalized test frame. The present invention solves the problems of large nonlinear equalization convergence errors and poor generalization performance caused by the introduction of time-varying noise, has good anti-noise performance and low algorithmic complexity, and meets practical application requirements.

The invention relates to the technical field of underwater communication, in particular to an underwater AUV (Autonomous Underwater Vehicle) blue laser-SiPM detection equalization communication system and method, and particularly relates to a signal processing method applying a linear and nonlinear equalization technology. The underwater AUV blue light laser communication system integrates four modules of optical communication transmitting and receiving, signal processing and balancing, and underwater positioning and tracking. The transmitting module generates a blue laser signal, the receiving module converts the blue laser signal into an electric signal, the signal processing module suppresses distortion, and the positioning and tracking module adjusts the transmitting direction in real time to ensure signal alignment. According to the system, the underwater optical communication transmission distance is remarkably increased, and the underwater optical communication transmission distance can reach 250 meters under the standard seawater condition and is far beyond that of a traditional system. And meanwhile, the data transmission rate is greatly improved, and the high-bandwidth application requirement is met. The underwater communication performance is optimized through the overall design, and an efficient and stable communication solution is provided for deep sea detection, underwater robots and other high-requirement applications.

The invention provides a construction method of a communication perception integrated model and the communication perception integrated model, and relates to the field of communication, and the method comprises the steps: employing a set modulation mode to transmit a plurality of OFDM frames between a transmitter and a receiver, and obtaining a frequency domain OFDM signal segment corresponding to each OFDM frame through the receiver, and each OFDM frame comprises a data subcarrier and a pilot frequency subcarrier; each sample instance comprises a frequency domain OFDM signal segment, and a real symbol and a real distance corresponding to the frequency domain OFDM signal segment; the communication and perception integrated model comprises a communication network architecture and a perception network architecture which share the same complex value residual time sequence convolutional network; the communication network architecture carries out equalization processing based on the frequency domain OFDM signal segment of the input communication and perception integrated model so as to output a prediction symbol, and the perception network architecture carries out distance estimation based on the frequency domain OFDM signal segment of the input communication and perception integrated model so as to output a prediction distance between the transmitter and the receiver. Therefore, joint nonlinear equalization and transmitting-receiving end distance estimation are realized.