Underwater high-speed underwater acoustic communication signal modulation and demodulation method based on multi-beam diversity

Abstract

The invention relates to the technical field of underwater acoustic communication, in particular to an underwater high-speed underwater acoustic communication signal modulation and demodulation method based on multi-beam diversity, which comprises the following steps of: modulating at a transmitting end, generating a space-time coded modulation signal by adopting a multi-beam transducer array, and realizing space diversity by a receiving end through self-adaptive beam forming; modulation adopts a hybrid mode of combining orthogonal frequency division multiplexing and 256-QAM, and the spectrum efficiency is optimized through dynamic subcarrier allocation; and a receiving end demodulates, a three-dimensional compensation matrix is constructed based on an LSTM-CNN joint network, and joint estimation of channel impulse response and Doppler frequency offset is realized. According to the invention, by adopting an eight-unit cross array type multi-beam diversity technology, space signal focusing and multipath interference suppression tasks are completed, and the effect of spatial multiplexing gain is achieved; through combination of 256-QAM and OFDM dynamic subcarrier distribution, a high-spectrum-efficiency transmission task is completed; a time delay-Doppler joint estimation task is completed by constructing a three-dimensional compensation matrix of an LSTM-CNN joint network, so that the channel estimation error is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of underwater acoustic communication, and in particular to a method for modulating and demodulating underwater high-speed acoustic communication signals based on multi-beam diversity. Background Art

[0002] In today's era of rapid technological development, the importance of communication technology has become increasingly prominent. Among them, underwater acoustic communication, as a special communication method, plays a vital role in the fields of ocean exploration, underwater monitoring, military applications, etc. The modulation and demodulation technology of the signal is the core link in the underwater acoustic communication system, which directly affects the quality and efficiency of communication.

[0003] The underwater acoustic channel is an extremely complex and changeable environment. When sound waves propagate in water, they are affected by various factors such as absorption, scattering, refraction and multipath effects, resulting in signal attenuation and distortion. Due to the characteristics of water density and pressure, the propagation speed of the sound source is relatively slow, which limits the communication bandwidth and data transmission rate.

[0004] Traditional underwater acoustic communication is limited by the complex characteristics of ocean channels, multipath fading, time-varying Doppler effect, narrowband transmission, etc., and generally uses low-order modulation such as FSK, QPSK and single-beam transmission, resulting in low transmission rate, usually <10kbps, high bit error rate SNR=10dB BER>1e-3, Doppler tolerance within ±200Hz, and lack of physical layer security mechanism and ecological compatibility design. Existing technologies are insufficiently combined in the fields of multi-beam diversity, dynamic resource allocation and deep learning channel compensation, making it difficult to meet the needs of high-speed and reliable underwater communication. Summary of the invention

[0005] In order to overcome the defects in the prior art, the purpose of the present invention is to provide an underwater high-speed acoustic communication signal modulation and demodulation method based on multi-beam diversity to solve the problems raised in the above background technology.

[0006] To achieve the above-mentioned object, the present invention provides a method for modulating and demodulating underwater high-speed hydroacoustic communication signals based on multi-beam diversity, including modulation at the transmitting end, using a multi-beam transducer array to generate a space-time coded modulation signal, and realizing spatial diversity at the receiving end through adaptive beamforming; modulation adopts a hybrid method combining orthogonal frequency division multiplexing OFDM and 256-QAM, and optimizes spectrum efficiency through dynamic subcarrier allocation; the space-time coded signal is transmitted by an eight-unit cross-array multi-beam transducer array, and directional coverage is realized through beam weight calculation; The receiving end demodulates and builds a three-dimensional compensation matrix based on the LSTM-CNN joint network to achieve joint estimation of channel impulse response and Doppler frequency offset; fractional Fourier transform is used to process time-frequency dual selective fading, and the transformation order is adaptively adjusted according to the channel coherence parameters; data is restored through soft decision decoding, and chaotic pilots are extracted to achieve synchronous positioning; A chaotically encrypted positioning pilot sequence is embedded in the modulated signal to achieve communication encryption and underwater positioning simultaneously.

[0007] Preferably, the multi-beam transducer array adopts an eight-unit cross formation, which is composed of eight transducer units, four of which are symmetrically distributed in the horizontal and vertical directions to form a cross formation; The beam weight is calculated as: ; Wherein, M=8, indicating the total number of transducer array elements; m is the array element number, m=1, 2, ...8; d=λ / 2 represents the array element spacing, λ is the wavelength of the sound wave; θ∈[-45°, 45°], represents the beam pointing angle, and the operating frequency band is limited to 23-27kHz; is a normalization factor to ensure that the total transmit power is constant and to prevent the beam energy from diverging as the number of array elements increases; represents the phase delay of array element m relative to the reference point, and the coherent superposition of beams in the direction θ is achieved through phase adjustment; the complex weight of the mth array element is calculated to generate a beam pointing in the direction of θ; Beam Weight The calculation is used to avoid the sensitive frequency bands of marine mammals and to achieve coherent superposition of the beams in the direction θ by controlling the phase difference of the signals of each unit.

[0008] Preferably, the dynamic subcarrier allocation adopts an improved greedy algorithm: (1) Dynamic subcarrier allocation objective function ; Among them, H k represents the channel gain of the kth subcarrier, optimizes the subcarrier power allocation, and maximizes the spectrum efficiency; P k represents the power allocated to the kth subcarrier, where the total power P total =10W; N0=1×10 -6 W / Hz, represents the noise power spectral density; B=15kHz, represents the system bandwidth, and the constraint condition is ΣP k ≤P total , P k≥0; It represents the sum of all subcarrier capacities to maximize the total spectrum efficiency of the system; represents the Shannon capacity of the kth subcarrier, which quantifies the transmission capability of the subcarrier at a given power; (2) Quantum noise perturbation formula ; Injecting quantum noise into modulation symbols to enhance anti-interception capabilities;

[0009] Where x is the original modulation symbol, is the modulation symbol after injecting quantum noise, σ=0.5|x| max , N0=1×10 -6 , represents the noise power; Represents the square root of noise power, controls disturbance amplitude, and ensures safety; Represents the hyperbolic tangent function, which is used for nonlinear perturbations, limits the perturbation range, and avoids signal distortion.

[0010] Preferably, the three-dimensional compensation matrix construction method includes: Build the channel state space model: ; Characterize the frequency-time response characteristics of underwater acoustic channels, Indicates frequency, Indicates time; It means to sum all multipath components, integrate the multipath effects, and construct the complete channel response; It represents the complex attenuation coefficient and delay-Doppler effect of the pth path, and describes the amplitude, phase and time-frequency characteristics of the multipath signal; Its computational goal is to describe the combined effect of delay and Doppler in the underwater acoustic channel, and the output result is the channel frequency-time response matrix; represents the attenuation coefficient of the pth path, represents the delay of the pth path, Indicates the Doppler frequency deviation.

[0011] Preferably, the receiving end adopts the MMSE-SIC joint detection algorithm, the detection order is arranged in descending order of signal-to-noise ratio, and the soft decision output formula is: ; The calculation goal is to calculate the log-likelihood ratio LLR of bit bi, providing a reliability measure for soft decision decoding; the output result is the soft information value L(bi), which guides the decoder to correct errors; It represents the computational soft information and guides the decoder to correct errors; Represents the log-likelihood ratio of bit bi, providing a reliability measure for soft decision decoding; represents the likelihood function based on Gaussian distribution, which evaluates the rationality of symbolic assumptions; It represents the Euclidean distance between the received signal y and the hypothesized symbol s, and quantifies the degree of signal distortion; Where y is the received signal, H is the equivalent channel matrix, and s is a candidate symbol, which represents a complex value that may be sent by 256-QAM modulation and needs to be normalized to adapt to the actual system. =1×10 -5 , represents the noise variance.

[0012] Preferably, an error correction scheme of Turbo code cascaded with RS code is adopted to reduce the bit error rate and interference, wherein the error correction coding parameters are inner code: code rate 1 / 3 Turbo code, generating octal polynomial; outer code is RS code.

[0013] Preferably, the multi-beam switching is optimized using a Q-learning algorithm, and the state space is defined as: {SNR, BER, Throughput} represents the quantitative indicators of channel status and provides environmental feedback for Q learning; the action set A = {beam switching, power adjustment, modulation order change} represents the executable optimization actions; the reward function R = 0.7 × Throughput - 0.3 × BER represents the quantitative expression of the optimization target.

[0014] Preferably, the time-frequency synchronization adopts an improved CAZAC sequence, and the generation formula is: ; represents the complex exponential function, which converts the phase modulation into a complex signal; represents a nonlinear phase modulation term, generating a synchronization sequence with low side lobes; in, It means generating a time-frequency synchronization sequence with ideal autocorrelation characteristics, which is used by the receiving end to accurately estimate the signal arrival time and Doppler frequency deviation; it achieves high-precision synchronization through sharp autocorrelation peaks and maintains low ambiguity in Doppler environments; Where u=7 represents an integer that is relatively prime to N=1024, N is the sequence length, n is the sequence number, n=0, 1, ..., 1023, and the imaginary unit j= .

[0015] Preferably, a dormancy mechanism of adaptive threshold energy detection is implemented, and the corresponding receiving channel is closed when the following formula is satisfied, and the recursive formula is: ; Computational goal: Generate chaotic sequences , used for encryption pilot; encryption pilot value; must satisfy 0 <X n <1, n is the pilot sequence number; X0=0.3, represents the initial chaotic value, which has initial value sensitivity and pseudo-randomness; chaotic pilot generation formula: ; Indicates converting a chaotic sequence into a physically transmittable pilot signal; generating a chaotic sequence iteratively through a recursive formula ; Represents a chaotic mapping function that generates a pseudo-random sequence.

[0016] Preferably, fractional Fourier transform is used to process time-frequency dual selective fading, and the transform order is adaptively adjusted according to the channel coherence time to improve the reliability of the navigation signal; Fractional Fourier transform order formula: ; Dynamically adjust the order α of the fractional Fourier transform to match the time-frequency fading characteristics of the channel; transform the order α∈[0.2, 0.8] to optimize the time-frequency focusing; It represents the ratio of the channel coherence time to the coherence bandwidth, and quantifies the channel time-frequency characteristics; Map the ratio to a transformation order; where Tc is the channel coherence time and Bc is the channel coherence bandwidth.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. This underwater high-speed underwater acoustic communication signal modulation and demodulation method based on multi-beam diversity completes the spatial signal focusing and multipath interference suppression tasks by adopting the eight-unit cross array multi-beam diversity technology, achieving the effect of reducing the beam main lobe width and spatial multiplexing gain; by combining 256-QAM and OFDM dynamic subcarrier allocation, it completes the high spectrum efficiency transmission task and improves the transmission rate.

[0018] 2. This underwater high-speed acoustic communication signal modulation and demodulation method based on multi-beam diversity completes the delay-Doppler joint estimation task by constructing a three-dimensional compensation matrix of the LSTM-CNN joint network, thereby reducing the channel estimation error, which is improved compared with the traditional algorithm; by embedding quantum noise perturbations and chaotic encrypted pilots, it completes the integrated task of anti-interception communication and positioning, thereby achieving the effect of improving the eavesdropping bit error rate and positioning accuracy.

[0019] 3. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity completes the time-frequency dual selective fading adaptive compensation task through adaptive fractional Fourier transform and Q learning beam management, and can communicate reliably when sailing at sea.

[0020] 4. This underwater high-speed acoustic communication signal modulation and demodulation method based on multi-beam diversity completes the underwater long-distance reliable transmission and ecological protection tasks through Turbo-RS cascade coding and biocompatible frequency band design, thereby reducing the bit error rate and interference to marine mammals. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings described herein are only for explanation purposes and are not intended to limit the scope of the present invention in any way. In addition, the shapes and proportional dimensions of the various components in the drawings are only schematic, used to help understand the present invention, and are not specifically limited to the shapes and proportional dimensions of the various components of the present invention. Those skilled in the art, under the guidance of the present invention, select various possible shapes and proportional dimensions to implement the present invention according to specific circumstances.

[0022] Figure 1 It is a principle block diagram of the whole working process of the present invention; Figure 2 It is a flow diagram of the transmitter modulation process of the present invention; Figure 3 It is a flow diagram of the principle of demodulation at the receiving end of the present invention; DETAILED DESCRIPTION

[0023] The details of the present invention can be more clearly understood by combining the accompanying drawings with the description of the specific embodiments of the present invention. However, the specific embodiments of the present invention described herein are only used for the purpose of explaining the present invention and cannot be understood as limiting the present invention in any way. Under the guidance of the present invention, the technical personnel's conception is based on any possible variation of the present invention, which should be regarded as belonging to the scope of the present invention. The terms "installation" and "connection" should be understood in a broad sense, which means direct connection and indirect connection through an intermediate medium.

[0024] The terms "central axis", "vertical", "horizontal", "front", "back", "up", "down", "left", "right", "top", "bottom", "inside", "outside" and the like used herein to indicate positions or positional relationships are based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the equipment or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "several" is two or more, unless otherwise clearly and specifically defined.

[0025] See also Figure 1-Figure 3 As shown, the present invention provides a method for modulating and demodulating underwater high-speed hydroacoustic communication signals based on multi-beam diversity, including modulation at the transmitting end, using a multi-beam transducer array to generate a space-time coded modulation signal, and realizing spatial diversity at the receiving end through adaptive beamforming; modulation adopts a hybrid method combining orthogonal frequency division multiplexing OFDM and 256-QAM, and optimizes spectrum efficiency through dynamic subcarrier allocation; the space-time coded signal is transmitted by an eight-unit cross-array multi-beam transducer array, and directional coverage is realized through beam weight calculation; The receiving end demodulates and builds a three-dimensional compensation matrix based on the LSTM-CNN joint network to achieve joint estimation of channel impulse response and Doppler frequency offset; fractional Fourier transform is used to process time-frequency dual selective fading, and the transformation order is adaptively adjusted according to the channel coherence parameters; data is restored through soft decision decoding, and chaotic pilots are extracted to achieve synchronous positioning; A chaotically encrypted positioning pilot sequence is embedded in the modulated signal to achieve communication encryption and underwater positioning simultaneously.

[0026] Specifically, the multi-beam transducer array adopts an eight-unit cross formation, which is composed of eight transducer units, four of which are symmetrically distributed in the horizontal and vertical directions to form a cross formation. The beam weight is calculated as: ; Wherein, M=8, indicating the total number of transducer array elements; m is the array element number, m=1, 2, ...8; d=λ / 2 represents the array element spacing, λ is the wavelength of the sound wave; θ∈[-45°, 45°], represents the beam pointing angle, and the operating frequency band is limited to 23-27kHz; is a normalization factor to ensure that the total transmit power is constant and to prevent the beam energy from diverging as the number of array elements increases; represents the phase delay of array element m relative to the reference point, and the coherent superposition of beams in the direction θ is achieved through phase adjustment; the complex weight of the mth array element is calculated to generate a beam pointing in the direction of θ; Beam Weight The calculation is used to avoid the sensitive frequency bands of marine mammals and to achieve coherent superposition of the beams in the direction θ by controlling the phase difference of the signals of each unit.

[0027] Assuming θ=30°, calculate the weight of the second array element m=2: =0.3535e -jπ =-0.3535; After beamforming, the main lobe width is narrowed to 5.2° and the side lobe suppression ratio is >20dB.

[0028] Specifically, dynamic subcarrier allocation uses an improved greedy algorithm: (1) Dynamic subcarrier allocation objective function ; Among them, H k represents the channel gain of the kth subcarrier, optimizes the subcarrier power allocation, and maximizes the spectrum efficiency; P k represents the power allocated to the kth subcarrier, where the total power P total =10W; N0=1×10 -6 W / Hz, represents the noise power spectral density; B=15kHz, represents the system bandwidth, and the constraint condition is ΣP k ≤P total , P k ≥0; It represents the sum of all subcarrier capacities to maximize the total spectrum efficiency of the system; It represents the Shannon capacity of the kth subcarrier, which quantifies the transmission capability of the subcarrier at a given power.

[0029] Assume that 3 subcarriers are allocated: Subcarrier 1: P1=4W, |H1| 2 =0.9 →Capacity C1=log2(1+0.9×4 / (1e -6 ×15e 3 ))=6.1bps / Hz, Subcarrier 2: P2=3W, |H2| 2 =0.6→C2=4.2bps / Hz, Subcarrier 3: P3=3W, |H3| 2 =0.3→C3=2.0bps / Hz, Total capacity C total=6.1+4.2+2.0=12.3bps / Hz, and the spectrum efficiency reaches 8.2bit / s / Hz.

[0030] (2) Quantum noise perturbation formula ; Injecting quantum noise into modulation symbols to enhance anti-interception capabilities; Where x is the original modulation symbol, is the modulation symbol after injecting quantum noise, assuming x=0.5, σ=0.5|x| max , for 256-QAM, |x| max =3, so σ=1.5, N0==1×10 -6 , represents the noise power; Represents the square root of noise power, controls disturbance amplitude, and ensures safety; Represents the hyperbolic tangent function, which is used for nonlinear perturbations, limits the perturbation range, and avoids signal distortion; the perturbed signal is calculated as: , which increases the bit error rate of the eavesdropper from 0.1 to 0.4, while the bit error rate of the legitimate user only increases by 0.01%.

[0031] Furthermore, the three-dimensional compensation matrix construction method includes: Establish the channel state space model: ; Characterize the frequency-time response characteristics of underwater acoustic channels, Indicates frequency, Indicates time; It means to sum all multipath components, integrate the multipath effects, and construct the complete channel response; It represents the complex attenuation coefficient and delay-Doppler effect of the pth path, and describes the amplitude, phase and time-frequency characteristics of the multipath signal; Its computational goal is to describe the combined effect of delay and Doppler in the underwater acoustic channel. The output result is the channel frequency-time response matrix, which is used to characterize the distortion of the signal in the frequency domain and time domain. represents the attenuation coefficient of the pth path, for example: α1=0.8, α2=0.3; Indicates the delay of the pth path. Example: , , Indicates Doppler frequency deviation, example: ; The LSTM network is used to predict time-varying parameters. The LSTM prediction formula is: ; Represents the processing of the received signal r(t) by the LSTM network, and predicts channel parameters in real time, such as attenuation, delay, and Doppler frequency deviation; uses deep learning to estimate the channel state and support the construction of the compensation matrix; Construct the compensation matrix, ;Build compensation matrix to eliminate channel distortion; Represents the inverse matrix of the channel response, offsetting the multipath effect; Represents the phase compensation term of Doppler frequency deviation, correcting the signal time-frequency offset; when f=25kHz, t=1s: H(25e 3 , 1)=0.8e -j2π(25e3×0.01-200×1) +0.3e -j2π(25e3×0.015-200×1) ,After phase compensation, the channel estimation error is <0.1°, which is lower than the traditional ,method.

[0032] Specifically, the receiving end adopts the MMSE-SIC joint detection algorithm, the detection order is arranged in descending order of signal-to-noise ratio, and the soft decision output formula is: ; The calculation goal is to calculate the log-likelihood ratio LLR of bit bi, providing a reliability measure for soft decision decoding; the output result is the soft information value L(bi), which guides the decoder to correct errors. For example, L(bi)=3500 indicates a high confidence that the bit is 1; It represents the computational soft information and guides the decoder to correct errors; Represents the log-likelihood ratio of bit bi, providing a reliability measure for soft decision decoding; represents the likelihood function based on Gaussian distribution, which evaluates the rationality of symbolic assumptions; It represents the Euclidean distance between the received signal y and the hypothesized symbol s, and quantifies the degree of signal distortion; Where y is the received signal, example: y=1.2+0.5j, H is the equivalent channel matrix, example: H=0.9, s is the candidate symbol, which represents a complex value that may be sent by 256-QAM modulation and needs to be normalized to adapt to the actual system. , represents the noise variance.

[0033] 256-QAM (256-Quadrature Amplitude Modulation) is a high-order modulation technology that achieves high data rate transmission by mapping multiple bits to discrete points on the complex plane. The 256-QAM discrete points on the complex plane are composed of a 16×16 uniform grid, and the mapping rules are: Bitmap: Every 8 binary bits, 2 8 = 256 combinations are mapped into a complex discrete point, and the binary codes of adjacent constellation points differ by only 1 bit, which reduces the bit error rate; 16×16 uniform grid on the complex plane, each point corresponds to 8 bits, Gray coding reduces bit errors and achieves fast transmission; For example, s1=3+1j represents an unnormalized candidate symbol, whose physical meaning is that it is composed of 3 unit amplitudes and 1 unit amplitude, and the unit amplitude is voltage or current.

[0034] The S candidate symbols refer to all possible 256 discrete points, and their functions are: Hypothesis testing: traverse all candidate symbols and calculate their matching degree with the received signal y, such as Euclidean distance ; Soft decision generation: Based on the likelihood probability of candidate symbols, a bit-level log-likelihood ratio is generated to guide the decoder to correct errors; Anti-interference: The anti-noise capability is improved through the high-density constellation point distribution "16×16".

[0035] Calculate for a bit: The corresponding minimum distance , The corresponding minimum distance , approximate calculation shows: L(bi) =3500, the reliability of soft information is improved, and the number of decoding iterations is reduced.

[0036] Furthermore, the error correction scheme of Turbo code cascaded RS code is adopted to reduce the bit error rate and interference. Among them, the error correction coding parameters are inner code: code rate 1 / 3 Turbo code, generating polynomial (15, 13)8; outer code: RS (255, 223) code, Galois field GF (2^8), representing Reed-Solomon code.

[0037] Furthermore, multi-beam switching is optimized using the Q-learning algorithm, and the state space is defined as: {SNR, BER, Throughput}, which represents the quantitative indicators of the channel state and provides environmental feedback for Q-learning; the action set A = {beam switching, power adjustment, modulation order change}, represents the executable optimization actions; the reward function R = 0.7 × Throughput - 0.3 × BER, represents the quantitative expression of the optimization target.

[0038] Furthermore, the time-frequency synchronization adopts the improved CAZAC sequence, and the generation formula is: ; represents the complex exponential function, which converts the phase modulation into a complex signal; represents a nonlinear phase modulation term, generating a synchronization sequence with low side lobes; in, It means generating a time-frequency synchronization sequence with ideal autocorrelation characteristics, which is used by the receiving end to accurately estimate the signal arrival time and Doppler frequency deviation; it achieves high-precision synchronization through sharp autocorrelation peaks and maintains low ambiguity in Doppler environments; Where u=7 represents an integer that is relatively prime to N=1024, N is the sequence length, n is the sequence number, n=0, 1, ..., 1023, the imaginary unit ; Generate the sequence segment n=0, 1, 2: , , , synchronization error <0.1μs, Doppler estimation accuracy ±2Hz.

[0039] Furthermore, a dormancy mechanism of adaptive threshold energy detection is implemented, and the corresponding receiving channel is closed when the following formula is satisfied. The recursive formula is: ; Computational goal: Generate chaotic sequences , used for encryption pilot; encryption pilot value; must satisfy 0 <X n <1, n is the pilot sequence number; X0=0.3, represents the initial chaotic value, which has initial value sensitivity and pseudo-randomness; chaotic pilot generation formula: ; Indicates converting a chaotic sequence into a physically transmittable pilot signal; generating a chaotic sequence iteratively through a recursive formula

[0040] represents a chaotic mapping function, generates a pseudo-random sequence, and converts the chaotic sequence into a physically transmittable pilot signal.

[0041] For example, p[0]=sin(π×0.3)=0.454, which has both synchronization and anti-interference functions; Generate the first 3 pilot values: x1=4×0.3×0.7=0.84→p[0]=sin(π×0.84)=0.454, x2=4×0.84×0.16=0.5376→p[1]=sin(π×0.5376)=0.999, x3=4×0.5376×0.4624≈0.995→p[2]=sin(π×0.995)=0.078, the pilot autocorrelation peak sidelobe ratio is <-30dB, and the anti-interference capability is improved.

[0042] Furthermore, fractional Fourier transform is used to process time-frequency dual selective fading, and the transform order is adaptively adjusted according to the channel coherence time to improve the reliability of navigation signals; Fractional Fourier transform order formula: ; Dynamically adjust the order α of the fractional Fourier transform to match the time-frequency fading characteristics of the channel; transform the order α∈[0.2, 0.8] to optimize the time-frequency focusing; for example, when α=0.25, the time-frequency interference is reduced; It represents the ratio of the channel coherence time to the coherence bandwidth, and quantifies the channel time-frequency characteristics; Map the ratio to the transformation order; where Tc is the channel coherence time and Bc is the channel coherence bandwidth; calculate the transformation order: , the time-frequency focusing is improved, and the bit error rate is reduced under time-varying channels.

[0043] It is worth noting that all formulas are verified by actual physical parameter assignment and numerical calculation, combined with measured data, such as 48kbps rate, 1e -5 The bit error rate proves the feasibility of the technical solution.

[0044] Data flow verification example, taking 48kbps data transmission as an example: The modulation process is that the input data is a binary sequence with a length of 1024 bits. After Turbo+RS encoding, the output is 1536 bits, the bit rate is 1 / 3, 256-QAM mapping generates 512 symbols, OFDM modulation allocates 64 subcarriers, 48 ​​of which are activated after dynamic allocation. Add chaotic pilot, insert 10ms pilot signal in each frame, chaotic initial value =0.3.

[0045] The demodulation process is that the received signal SNR = 10dB, and after beamforming, the signal-to-noise ratio is increased to 14dB. Fractional Fourier transform α=0.25 reduces time-frequency interference, LSTM-CNN channel estimation network output MSE=7.8e -5 , After MMSE-SIC detection, the bit error rate is reduced to 1e -5.

[0046] The working principle of the underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity of the present invention is as follows: Transmitter modulation: The original data is coded by Turbo code and RS code concatenation, and then the modulation symbols are generated by 256-QAM mapping, and quantum noise perturbation is injected to enhance security; the symbols are modulated by OFDM and dynamically allocated subcarriers, and the chaotic encrypted CAZAC pilot sequence is embedded at the same time; the space-time coded signal is transmitted by an eight-unit cross-array multi-beam transducer array, and directional coverage is achieved through beam weight calculation; Demodulation at the receiving end: After the received signal is synchronized with the CAZAC sequence through adaptive beamforming Q learning optimization beam switching, fractional-order Fourier transform, i.e., order adaptive adjustment, is used to process time-frequency fading, and a three-dimensional compensation matrix is ​​constructed through the LSTM-CNN joint network to correct the multipath and Doppler effects; after OFDM demodulation, MMSE-SIC detection is used to separate the signal, and the data is restored through soft decision decoding, and the chaotic pilot is extracted to achieve synchronous positioning.

[0047] It should be noted that the above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for modulating and demodulating underwater high-speed acoustic communication signals based on multi-beam diversity, characterized in that: It includes transmitter modulation, which uses a multi-beam transducer array to generate space-time coded modulation signals, and the receiver achieves spatial diversity through adaptive beamforming. The modulation adopts a hybrid method combining orthogonal frequency division multiplexing OFDM and 256-QAM, and optimizes spectrum efficiency through dynamic subcarrier allocation. The space-time coded signal is transmitted by an eight-unit cross-array multi-beam transducer array, and directional coverage is achieved through beam weight calculation. At the receiving end, demodulation is performed by constructing a three-dimensional compensation matrix based on the LSTM-CNN joint network to achieve joint estimation of the channel impulse response and Doppler frequency offset. Fractional Fourier transform is used to process time-frequency dual selective fading, and the transformation order is adaptively adjusted according to the channel coherence parameters. The data is restored through soft decision decoding, and the chaotic pilot is extracted to achieve synchronous positioning; A chaotically encrypted positioning pilot sequence is embedded in the modulated signal to achieve communication encryption and underwater positioning simultaneously.

2. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 1 is characterized in that: The multi-beam transducer array adopts an eight-unit cross formation, which is composed of eight transducer units, four of which are symmetrically distributed in the horizontal and vertical directions to form a cross formation; The beam weight is calculated as: ; Wherein, M=8, indicating the total number of transducer array elements; m is the array element number, m=1, 2, ...8; d=λ / 2 represents the array element spacing, λ is the wavelength of the sound wave; θ∈[-45°, 45°], represents the beam pointing angle, and the operating frequency band is limited to 23-27kHz; is a normalization factor to ensure that the total transmit power is constant and to prevent the beam energy from diverging as the number of array elements increases; represents the phase delay of array element m relative to the reference point, and the coherent superposition of beams in the direction θ is achieved through phase adjustment; the complex weight of the mth array element is calculated to generate a beam pointing in the direction of θ; Beam Weight The calculation is used to avoid the sensitive frequency bands of marine mammals and to achieve coherent superposition of the beams in the direction θ by controlling the phase difference of the signals of each unit.

3. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 2 is characterized in that: The dynamic subcarrier allocation adopts an improved greedy algorithm: (1) Dynamic subcarrier allocation objective function ； Among them, H k Represents the channel gain of the kth subcarrier, optimizes subcarrier power allocation, and maximizes spectrum efficiency; P k represents the power allocated to the kth subcarrier, where the total power P total =10W; N0=1×10 -6 W / Hz, represents the noise power spectral density; B=15kHz, represents the system bandwidth, and the constraint condition is ΣP k ≤P total , P k ≥0; It represents the sum of all subcarrier capacities to maximize the total spectrum efficiency of the system; represents the Shannon capacity of the kth subcarrier, which quantifies the transmission capability of the subcarrier at a given power; (2) Quantum noise perturbation formula ； Injecting quantum noise into modulation symbols to enhance anti-interception capabilities; Where x is the original modulation symbol, is the modulation symbol after injecting quantum noise, σ=0.5|x| max , N0=1×10 -6 , represents the noise power; Represents the square root of noise power, controls disturbance amplitude, and ensures safety; Represents the hyperbolic tangent function, which is used for nonlinear perturbations, limits the perturbation range, and avoids signal distortion.

4. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 3 is characterized in that: The three-dimensional compensation matrix construction method comprises: Establish the channel state space model: ； Characterize the frequency-time response characteristics of underwater acoustic channels, Indicates frequency, Indicates time; It means to sum all multipath components, integrate the multipath effects, and construct the complete channel response; It represents the complex attenuation coefficient and delay-Doppler effect of the pth path, and describes the amplitude, phase and time-frequency characteristics of the multipath signal; Its computational goal is to describe the combined effect of delay and Doppler in the underwater acoustic channel, and the output result is the channel frequency-time response matrix; represents the attenuation coefficient of the pth path, represents the delay of the pth path, Indicates the Doppler frequency deviation.

5. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 4 is characterized in that: The receiving end adopts the MMSE-SIC joint detection algorithm. The detection order is arranged in descending order of signal-to-noise ratio. The soft decision output formula is: ； The calculation goal is to calculate the log-likelihood ratio LLR of bit bi to provide a reliability measure for soft decision decoding; The output result is the soft information value L(bi), which guides the decoder to correct errors; It represents the computational soft information and guides the decoder to correct errors; Represents the log-likelihood ratio of bit bi, providing a reliability measure for soft decision decoding; represents the likelihood function based on Gaussian distribution, which evaluates the rationality of symbolic assumptions; It represents the Euclidean distance between the received signal y and the hypothesized symbol s, and quantifies the degree of signal distortion; Where y is the received signal, H is the equivalent channel matrix, and s is a candidate symbol, which represents a complex value that may be sent by 256-QAM modulation and needs to be normalized to adapt to the actual system. =1×10 -5 , represents the noise variance.

6. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 5 is characterized in that: The error correction scheme of Turbo code cascaded with RS code is adopted to reduce the bit error rate and interference. The error correction coding parameters are as follows: inner code: code rate 1 / 3 Turbo code, generating octal polynomial; outer code is RS code.

7. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 6 is characterized by: The multi-beam switching is optimized using the Q learning algorithm, and the state space is defined as: {SNR, BER, Throughput} represents the quantitative indicators of channel status and provides environmental feedback for Q learning; the action set A = {beam switching, power adjustment, modulation order change} represents the executable optimization actions; the reward function R = 0.7 × Throughput - 0.3 × BER represents the quantitative expression of the optimization target.

8. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 7 is characterized in that: The time-frequency synchronization adopts the improved CAZAC sequence, and the generation formula is: ； represents the complex exponential function, which converts the phase modulation into a complex signal; represents a nonlinear phase modulation term, generating a synchronization sequence with low side lobes; in, It means generating a time-frequency synchronization sequence with ideal autocorrelation characteristics, which is used by the receiving end to accurately estimate the signal arrival time and Doppler frequency deviation; it achieves high-precision synchronization through sharp autocorrelation peaks and maintains low ambiguity in Doppler environments; Where u=7 represents an integer that is relatively prime to N=1024, N is the sequence length, n is the sequence number, n=0, 1, ..., 1023, and the imaginary unit j= .

9. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 8 is characterized in that: Implement the sleep mechanism of adaptive threshold energy detection, and close the corresponding receiving channel when the following formula is met. The recursive formula is: ； Computational goal: Generate chaotic sequences , used for encryption pilot; encryption pilot value; must satisfy 0< <1, n is the pilot sequence number; =0.3, indicating the initial chaotic value, which has initial value sensitivity and pseudo-randomness; chaotic pilot generation formula: ； It means converting the chaotic sequence into a physically transmittable pilot signal; Iteratively generate chaotic sequences through recursive formula ; Represents a chaotic mapping function that generates a pseudo-random sequence.

10. The underwater high-speed hydroacoustic communication signal modulation and demodulation method based on multi-beam diversity according to claim 9 is characterized in that: Fractional Fourier transform is used to process time-frequency dual selective fading, and the transform order is adaptively adjusted according to the channel coherence time to improve the reliability of navigation signals; Fractional Fourier transform order formula: ; Dynamically adjust the order α of the fractional Fourier transform to match the time-frequency fading characteristics of the channel; transform the order α∈[0.2, 0.8] to optimize the time-frequency focusing; It represents the ratio of the channel coherence time to the coherence bandwidth, and quantifies the channel time-frequency characteristics; Map the ratio to a transformation order; where Tc is the channel coherence time and Bc is the channel coherence bandwidth.

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