An in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition

Abstract

The present invention relates to the field of underwater acoustic communication technology, and particularly to an in-band full-duplex spread-spectrum underwater acoustic communication method based on the acquisition of residual self-interference. The method includes using the transmitted signal in the digital domain and the output signal of the power amplifier collected through the auxiliary link as the input reference signal of the adaptive filter in the digital-aided analog interference cancellation process. The adaptive filter based on the recursive least squares algorithm realizes self-interference reconstruction in the digital domain, and performs analog interference cancellation by outputting to the acquisition end in the analog domain. The signal without analog interference cancellation is collected through the auxiliary link, and the residual self-interference is cancelled by the adaptive filter based on the recursive least squares algorithm. The weight coefficient is iteratively updated using the error to complete the cancellation of the residual self-interference in the digital domain, so as to obtain the desired signal at the far end with noise interference. The present invention effectively overcomes the influence of the nonlinearity of the power amplifier while reducing the complexity of the interference cancellation system structure in the analog domain and the digital domain.

Description

Technical Field

[0001] The present invention relates to the field of underwater acoustic communication technology, and particularly to an in-band full-duplex spread-spectrum underwater acoustic communication method based on the acquisition of residual self-interference. Background Art

[0002] In-band full-duplex underwater acoustic communication technology can simultaneously transmit and receive communication signals within the same frequency band, which can significantly improve the frequency utilization efficiency and has important research significance and application value under the background of severely limited available spectrum resources in the underwater acoustic channel. In the process of realizing in-band full-duplex underwater acoustic communication technology, it is necessary to cancel the strong self-interference emitted by the local proximal transmitter, so that the proximal receiver can successfully receive and demodulate the weak desired signal from the far end. Therefore, how to suppress and cancel the local strong self-interference signal is a key problem to be solved.

[0003] Currently, the process of self-interference cancellation in the implementation of in-band full-duplex communication can be mainly summarized into the following steps: (1) spatial-domain self-interference suppression; (2) modeling of the complex self-interference propagation channel; (3) analog-domain self-interference cancellation; (4) digital-domain self-interference cancellation. Among them, spatial-domain self-interference suppression can significantly reduce the self-interference cancellation pressure in the subsequent analog domain and digital domain. However, at the same time, some research results show that active and passive self-interference suppression in the spatial domain will affect the self-interference propagation channel, further exacerbating the frequency-selective fading effect.

[0004] The composition of the self-interference signal can be mainly divided into three categories, namely, linear components, nonlinear components, and transmitter noise. Among them, the linear component is the part with the largest energy proportion in the self-interference signal, and the nonlinear component is mainly introduced by the power amplifier in the in-band full-duplex communication system. If this component is not canceled, it will affect the overall self-interference cancellation effect of the system. There have been some research results on the cancellation of the nonlinear distortion component introduced by the power amplifier, which are mainly realized by nonlinear reconstruction, auxiliary link, pre-distortion compensation, etc. However, the performance of the self-interference cancellation scheme in the independent analog domain or digital domain is limited. Moreover, if the analog interference cancellation effect is too good, it will lead to a decrease in the digital interference cancellation performance. This result is mainly caused by two reasons. First, the energy of the residual signal is already too low, resulting in inaccurate channel estimation results of the residual self-interference. Second, there is already a large difference between the residual signal and the reference signal, and accurate channel estimation results cannot be obtained by modeling the residual interference signal channel with the reference signal. Summary of the Invention

[0005] In view of the above-mentioned disadvantages of the prior art, the purpose of the present invention is to provide an in-band full-duplex spread-spectrum underwater acoustic communication method based on the acquisition of residual self-interference, which can obtain accurate residual interference signals through a residual self-interference acquisition structure, thereby solving the problem that there is a large difference between the residual signal and the reference signal.

[0006] To achieve the above and other related objectives, the present invention provides an in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition, including:

[0007] S1. The receiving end uses a receiving transducer to receive the mixed signal of the local self-interference signal and the desired signal, and respectively uses the transmitted signal in the digital domain and the output signal of the power amplifier collected through the auxiliary link as the input reference signal of the adaptive filter in the digital-aided analog interference cancellation process;

[0008] S2. The adaptive filter based on the recursive least squares algorithm realizes self-interference reconstruction in the digital domain, and performs analog interference cancellation through the acquisition end output to the analog domain. The weight coefficient ω asic (n) is iteratively updated using the error ε asic (n). Through continuous iteration, preliminary self-interference cancellation in the analog domain is completed to obtain the remote desired signal s f (t) and the residual interference signal e asic (t);

[0009] S3. The signal without analog interference cancellation is collected through the auxiliary link, and the digital domain is combined with the reconstructed interference signal to obtain the residual self-interference signal y rsi [n]. The residual self-interference signal y rsi [n] is used as the input reference signal of the linear adaptive filter in the digital interference cancellation process;

[0010] S4. The adaptive filter based on the recursive least squares algorithm cancels the residual self-interference. The weight coefficient ω dsic (n) is iteratively updated using the error ε dsic (n). The residual self-interference cancellation in the digital domain is completed to obtain the remote desired signal with noise interference.

[0011] In an embodiment of the present invention, the transmitted signal in the digital domain in step S1 is the local reference signal before digital-to-analog conversion.

[0012] In an embodiment of the present invention, the output signal of the power amplifier in step S1 is the signal output by the power amplifier after digital-to-analog conversion, that is, the transmitted signal in the analog domain.

[0013] In an embodiment of the present invention, the interference signal y pa (t) of the transmitted signal in the digital domain in step S1 reaches the receiving end after propagation, that is, the channel with the channel impulse response h SI (t). Then the signal received by the receiving end is: Among them, S f (t) is the remote desired signal, and n s (t) is the noise.

[0014] In an embodiment of the present invention, the implementation of self-interference reconstruction by the adaptive filter based on the recursive least squares algorithm in the digital domain in step S2 includes:

[0015] Initialize the parameters of the adaptive filter. The forgetting factor λ is a positive value close to 1. Let ε asic (n)=0, and define P(n)=λ -1 E, where E is an N-order identity matrix, the received signal is S s (n), and the input reference signal is S i (n). The iterative process includes:

[0016] Update the intermediate variables:

[0017] Update the estimated error variance matrix:

[0018] Update the error coefficient:

[0019] Update the iterative weight: ω asic (n)=ω asic (n - 1)+L(n)ε asic (n),

[0020] Repeat the iterative process,

[0021] After completing the iterative process, ε asic (n) is the cancellation result including the remote desired signal s f (n) and the residual interference signal e asic (n), which is the reconstructed self-interference signal.

[0022] In an embodiment of the present invention, in step S3, the signal that has not been subjected to analog interference cancellation is collected through the auxiliary link, and the digital domain is combined with the reconstructed interference signal to obtain the residual self-interference signal y rsi [n]. Using the residual self-interference signal y rsi [n] as the input reference signal of the linear adaptive filter in the digital interference cancellation process includes:

[0023] By controlling the effective quantization bit number of the first AD analog-to-digital conversion module and the amplification factor of the programmable amplifier, the remote desired signal s f (t) is made to fall outside the dynamic quantization range of the first AD analog-to-digital conversion module to obtain the self-interference signal. After entering the digital domain, the digital domain and the reconstructed interference signal are subjected to inverse cancellation to obtain the residual self-interference signal y rsi [n]. Using the residual self-interference signal y rsi[n] As the input reference signal of the linear adaptive filter in the digital interference cancellation process to achieve the cancellation of the residual self-interference signal.

[0024] In an embodiment of the present invention, the cancellation of the residual self-interference by the adaptive filter based on the recursive least squares algorithm in step S4 includes:

[0025] Initialize the parameters of the adaptive filter, where the forgetting factor λ is a positive value close to 1, and let ε dsic (n)=0, define P(n)=λ -1 E, where E is the N-order identity matrix, the received signal is ε asic (n), and the input reference signal is y ric (n). The iterative process includes:

[0026] Update the intermediate variables:

[0027] Update the estimated error variance matrix:

[0028] Update the error coefficient:

[0029] Update the iterative weight: ω dsic (n)=ω dsic (n - 1)+L(n)ε dsic (n),

[0030] Repeat the iterative process,

[0031] After completing the iterative process, ε dsic (n) is the desired signal at the far end with noise interference after analog and digital interference cancellation.

[0032] As described above, a method for in-band full-duplex spread-spectrum underwater acoustic communication based on residual self-interference of the present invention has the following beneficial effects:

[0033] The method for in-band full-duplex spread-spectrum underwater acoustic communication based on residual self-interference of the present invention effectively overcomes the influence of the power amplifier's nonlinearity while reducing the complexity of the analog domain and digital domain interference cancellation system structure.

[0034] The method for in-band full-duplex spread-spectrum underwater acoustic communication based on residual self-interference of the present invention uses the local transmitted signal as the input reference signal of the linear filter for preliminary analog interference cancellation, reducing the system complexity of the analog interference cancellation process.

[0035] The in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition of the present invention obtains a "pure" interference signal through an auxiliary acquisition link and introduces it into the digital domain to obtain an approximate sample of the residual, which can reduce the length of the linear filter in the digital interference cancellation process and improve the convergence speed of the filter in the digital domain interference cancellation process.

[0036] The in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition of the present invention does not require prior non-linear model estimation and measurement of the power amplifier, and has a wide range of applicability.

[0037] The two linear filters adopted by the in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition of the present invention can be implemented by an improved recursive least squares filter, which can further improve the convergence speed and steady-state performance of each iteration process.

[0038] The residual interference acquisition structure adopted by the in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition of the present invention can also suppress the influence of transmitter noise on the interference cancellation performance and improve the robustness of the system. Description of the Drawings

[0039] Figure 1 It is a schematic structural diagram of a system related to the in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition provided by an embodiment of the present application.

[0040] Figure 2 It is a flowchart of the operation of the in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition provided by an embodiment of the present application.

[0041] Figure 3 It is a comparison result of the normalized mean square error performance after simulated interference cancellation of the in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition provided by an embodiment of the present application under different parameters.

[0042] Figure 4 It is a comparison result of the normalized mean square error performance after simulated and digital interference cancellation of the in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition provided by an embodiment of the present application under different conditions. Detailed Embodiments

[0043] The following uses specific specific examples to illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0044] It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Therefore, only the components related to the present invention are shown in the diagrams, rather than being drawn according to the number, shape, and size of the components in actual implementation. The types, quantities, and proportions of the components in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0045] Please refer to Figure 1 、 Figure 2 , Figure 1 FIG. is a schematic structural diagram of a system related to an in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition provided by an embodiment of the present application. Figure 2 FIG. is a flowchart of the operation of an in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition provided by an embodiment of the present application. The known digital domain transmitted signal is used as the input reference signal of the adaptive filter in the digital-aided analog interference cancellation process; combined with the received signal at the receiving end, a recursive least squares adaptive filter is used for preliminary analog domain self-interference cancellation to obtain a desired signal at the far end containing residual interference; the signal without analog interference cancellation is collected through an auxiliary acquisition link and merged with the reconstructed interference signal in the digital domain to obtain a residual self-interference signal, which is used as the input of the linear adaptive filter in the digital interference cancellation process; a recursive least squares adaptive filter is used for canceling the residual self-interference to obtain a desired signal at the far end with a certain amount of noise interference.

[0046] The present invention provides an in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition, including:

[0047] S1. The receiving end uses a receiving transducer to receive a mixed signal of a local self-interference signal and a desired signal, and respectively uses the transmitted signal in the digital domain and the output signal of the power amplifier collected through an auxiliary link as the input reference signal of the adaptive filter in the digital-aided analog interference cancellation process. Specifically, the mixed signal of the local self-interference signal and the desired signal is a mixed signal of a local strong self-interference and a desired signal at the far end.

[0048] Since the communication system used in this method is a spread-spectrum communication system, both reference signals need to undergo a spread-spectrum signal modulation operation. The transmitted signal s(t) can be expressed as:

[0049] where A is the amplitude of the transmitted signal, c i (t) is a sequence with a code length of N, and the chip duration is T c of the spreading code, is the initial phase, f c is the carrier frequency, and then s[n] is the local reference signal input to the first linear adaptive filter, that is, linear adaptive filter ①.

[0050] The transmitted interference signal y output by the power amplifier in the in-band full-duplex underwater acoustic communication system pa (t), after short-distance propagation, reaches the proximal receiving end, and can be regarded as passing through a channel with an impulse response of h SI (t). Then the signal received at the receiving end is: where S f (t) is the desired signal from the far end, and n s (t) is the noise.

[0051] S2. The adaptive filter based on the recursive least squares algorithm realizes self-interference reconstruction in the digital domain, and performs analog interference cancellation through the acquisition end output to the analog domain. Using the error ε asic (n) to iteratively update the weight coefficient ω asic (n), and complete the preliminary self-interference cancellation in the analog domain through continuous iteration to obtain the desired signal s from the far end f (t) and the residual interference signal e asic (t).

[0052] Initialize the filter parameters. The forgetting factor λ is a positive value close to 1. Let ε asic (n) = 0, and define P(n) = λ -1 E, where E is the N-order identity matrix, the received signal is S s (n), and the input reference signal is S i (n). The specific iterative process is as follows:

[0053] Update the intermediate variable:

[0054] Update the estimated error variance matrix:

[0055] Update the error coefficient:

[0056] Update the iterative weight: ω asic (n) = ω asic (n - 1) + L(n)ε asic (n),

[0057] Repeat the above process to complete the iteration,

[0058] After completing the iteration, ε asic (n) is the cancellation result containing the desired signal s from the far end f (n) and the residual interference signal e asic (n), is the reconstructed self-interference signal.

[0059] S3. Collect the signal without analog interference cancellation through the auxiliary link, and combine the digital domain with the reconstructed interference signal to obtain the residual self-interference signal y rsi [n]. Use the residual self-interference signal y rsi [n] as the input reference signal of the second linear adaptive filter in the digital interference cancellation process, that is, the linear adaptive filter ②.

[0060] First, by controlling the effective quantization bit number of the first AD analog-to-digital conversion module, that is, the A / D analog-to-digital conversion module ①, and the amplification factor of the programmable amplifier, make the remote desired signal fall outside the dynamic quantization range to obtain an approximate "pure" self-interference signal. After entering the digital domain, perform in-phase cancellation with the reconstructed interference signal obtained in step S2 to obtain the residual self-interference signal, and use this as the input of the second linear adaptive filter to achieve the cancellation of the residual self-interference signal.

[0061] S4. Cancel the residual self-interference using the adaptive filter based on the recursive least squares algorithm, and use the error ε dsic (n) to iteratively update the weight coefficient ω dsic (n), complete the cancellation of the residual self-interference in the digital domain to obtain the remote desired signal with noise interference.

[0062] Initialize the filter parameters. The forgetting factor λ is a positive value close to 1. Let ε dsic (n) = 0, define P(n) = λ -1 E, where E is the N-order identity matrix, the received signal is ε asic (n), and the input reference signal is y ric (n). The specific iterative process is as follows:

[0063] Update the intermediate variable:

[0064] Update the estimated error variance matrix:

[0065] Update the error coefficient:

[0066] Update the iterative weight: ω dsic (n) = ω dsic (n - 1) + L(n)ε dsic (n),

[0067] Repeat the above process to complete the iteration. ε dsic (n) is the remote desired signal with a certain amount of noise interference after analog and digital interference cancellation.

[0068] Please refer to Figure 3 、 Figure 4 , Figure 3This is the comparison result of the normalized mean square error performance after simulated interference cancellation for an in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition under different parameters provided by the embodiments of this application. Figure 4 This is the comparison result of the normalized mean square error performance after simulated and digital interference cancellation for an in-band full-duplex spread-spectrum underwater acoustic communication method based on residual self-interference acquisition under different conditions. To demonstrate the performance of the present invention, a comparison group is used for illustration. In the comparison group, the input reference signal of the first linear adaptive filter is sourced from the signal collected into the digital domain through an auxiliary link with an attenuator from the output of the power amplifier. Theoretical simulations were conducted on the two schemes corresponding to the two different input reference signals and the influence of different parameters on the interference cancellation result. In the theoretical simulations, auxiliary link circuit noise was added respectively. This part of the noise was equivalent to additive white Gaussian noise, and the signal-to-noise ratios were set to 30, 40, and 50 dB respectively. At the same time, a non-linear model was used to describe the influence of the non-linear effect of the power amplifier. The transmitter noise was taken as 65 dB, and the complex self-interference propagation channel was a real collected self-interference propagation channel. The initial interference-to-signal power ratio was set to 78 dB.

[0069] The interference cancellation result is filtered in-band, and the normalized mean square error (NMSE) curve is smoothed through moving average and displayed by equally spaced sampling. The comparison results of the NMSE performance after self-interference cancellation under each parameter configuration are as Figure 3 shown. Since the auxiliary link noise interference will affect the performance of analog-domain interference cancellation, the steady-state performance of analog-domain self-interference cancellation is approximately 33.8 dB, 44.6 dB, and 55.1 dB respectively. After combining digital-domain self-interference cancellation, the steady-state performance can be improved to approximately 56.6 dB, 70.6 dB, and 66.3 dB respectively. It can be seen that when the performance of analog-domain interference cancellation exceeds 50 dB, the gain effect brought by digital-domain self-interference cancellation will decrease. When the local transmitted signal is used as the input reference of the linear filter in the process of analog-domain self-interference cancellation, the steady-state performance of self-interference cancellation can only reach approximately 26.9 dB, because the non-linear distortion components are not considered in this process. After combining digital-domain self-interference cancellation, the steady-state performance can be improved to approximately 74.8 dB.

[0070] It can be seen from this that when the analog-domain self-interference cancellation process uses the power amplifier reference signal as the input reference of the linear filter, under the influence of link noise interference, due to the large residual self-interference energy, it is impossible to achieve in-band full-duplex underwater acoustic communication through independent analog-domain self-interference cancellation. After combining digital-domain self-interference cancellation, the steady-state performance of self-interference cancellation under various parameter settings has been enhanced, but the interference-to-signal power ratio is still at a level where the communication system cannot robustly demodulate (>7 dB). However, when in the analog-domain self-interference cancellation process, if the local reference signal is used as the input reference signal of the first linear adaptive filter, and the non-linear distortion component is obtained through the auxiliary acquisition link as the input reference signal of the second linear adaptive filter, and cancellation is performed in the digital-domain self-interference cancellation stage, the overall self-interference cancellation performance of the system can be made close to the steady-state level of self-interference cancellation without noise interference in the auxiliary link, further reducing the interference-to-signal power ratio, and thus supporting the smooth demodulation of the in-band full-duplex spread-spectrum underwater acoustic communication system.

[0071] In summary, the present invention provides an in-band full-duplex spread-spectrum underwater acoustic communication method based on the acquisition of residual self-interference. The simulation results show that this method can effectively overcome the influence of the non-linearity of the power amplifier, obtain a "pure" interference signal through the auxiliary acquisition link, introduce it into the digital domain to obtain an approximate sample of the residual self-interference, and complete the cancellation of the residual self-interference through further digital-domain self-interference cancellation, improving the signal-to-interference-plus-noise power ratio to the demodulable level of the spread-spectrum communication system. It should be noted, however, that this structure will cause a certain loss of the desired signal at the far end. Therefore, at present, this structure can only be implemented using a communication system with strong anti-interference ability.

[0072] The above embodiments are only illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. An in-band full-duplex spread-spectrum underwater acoustic communication method based on the acquisition of residual self-interference, characterized in that, Including: S1. The receiving end uses a receiving transducer to receive the mixed signal of the local self-interference signal and the desired signal, and respectively uses the transmitted signal in the digital domain and the output signal of the power amplifier collected through the auxiliary link as the input reference signal of the adaptive filter in the digital-aided analog interference cancellation process; S2. The adaptive filter based on the recursive least squares algorithm realizes self-interference reconstruction in the digital domain, and performs analog interference cancellation by outputting to the acquisition end of the analog domain, and uses the error ε asic (n) to iteratively update the weight coefficient ω asic (n), and completes the preliminary self-interference cancellation in the analog domain through continuous iteration to obtain the desired signal s f (t) and the residual interference signal e asic (t); S3. Collect the signal without analog interference cancellation through the auxiliary link, and merge the digital domain with the reconstructed interference signal to obtain the residual self-interference signal y rsi [n], and use the residual self-interference signal y rsi [n] as the input reference signal of the linear adaptive filter in the digital interference cancellation process; S4. Use an adaptive filter based on the recursive least squares algorithm to cancel the residual self-interference, and utilize the error ε dsic (n) to iteratively update the weight coefficient ω dsic (n), complete the cancellation of the residual self-interference in the digital domain to obtain the desired signal of the remote end with noise interference; The implementation of self-interference reconstruction by the adaptive filter based on the recursive least squares algorithm in step S2 includes: Initialize the parameters of the adaptive filter. The forgetting factor λ is a positive value close to 1. Let ε asic (n) = 0, and define P(n) = λ -1 E, where E is an N - order identity matrix. The received signal is S s (n), and the input reference signal is S i (n). The iterative process includes: Update intermediate variable: Update the estimated error variance matrix: Update error coefficient: Update and iterate the weight: ω asic (n) = ω asic (n - 1)+L(n)ε asic (n), Repeating the iterative process, After completing the iteration process, ε asic (n) includes the desired signal s at the far end f (n) and the cancellation result of the residual interference signal e asic (n); is the reconstructed self-interference signal; The cancellation of the residual self-interference by the adaptive filter based on the recursive least squares algorithm in step S4 includes: Initialize the parameters of the adaptive filter. The forgetting factor λ is a positive value close to 1. Let ε dsic (n)=0, and define P(n)=λ -1 E, where E is an N-order identity matrix. The received signal is ε asic (n), and the input reference signal is y ric (n). The iterative process includes: Update intermediate variable: Update the estimated error variance matrix: Update error coefficient: Updated and iterated weight: ω dsic (n) = ω dsic (n - 1) + L(n)ε dsic (n), Repeating the iterative process, After completing the iterative process, ε dsic (n) is the desired signal at the far end with noise interference after analog and digital interference cancellation.

2. The in-band full-duplex spread-spectrum underwater acoustic communication method according to claim 1, characterized in that, The transmitted signal in the digital domain in step S1 is the local reference signal before digital-to-analog conversion.

3. The in-band full-duplex spread-spectrum underwater acoustic communication method according to claim 1, characterized in that, The output signal of the power amplifier in step S1 is the signal output by the power amplifier after digital-to-analog conversion, that is, the transmitted signal in the analog domain.

4. The in-band full-duplex spread-spectrum underwater acoustic communication method according to claim 1, characterized in that, The interference signal y of the transmitted signal in the digital domain in step S1 pa (t), after propagation, reaches the receiving end, that is, the channel with the channel impulse response h SI (t), then the signal received at the receiving end is: where S f (t) is the desired signal from the far end, and n s (t) is the noise.

5. The in-band full-duplex spread-spectrum underwater acoustic communication method according to claim 1, characterized in that, In step S3, collecting the signal without analog interference cancellation through the auxiliary link, and combining the digital domain with the reconstructed interference signal to obtain the residual self-interference signal y rsi [n], using the residual self-interference signal y rsi [n] as the input reference signal of the linear adaptive filter in the digital interference cancellation process includes: By controlling the effective quantization bit number of the first AD analog-to-digital conversion module and the amplification factor of the programmable amplifier, the desired signal s at the remote end is made to fall outside the dynamic quantization range of the first AD analog-to-digital conversion module to obtain a self-interference signal. After entering the digital domain, the digital domain and the reconstructed interference signal are subjected to inverse cancellation to obtain a residual self-interference signal y f (t). After entering the digital domain, the digital domain and the reconstructed interference signal are subjected to inverse cancellation to obtain a residual self-interference signal y rsi [n]. Using the residual self-interference signal y rsi [n] as the input reference signal of the linear adaptive filter in the digital interference cancellation process to achieve the cancellation of the residual self-interference signal.

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