A signal-to-interference ratio prediction method for CP-OFDM passband underwater acoustic communication system

Abstract

The present application discloses a method for predicting the signal-to-interference ratio of a CP-OFDM passband underwater acoustic communication system, which relates to the field of passband underwater acoustic communication systems. The method uses an impulse response function to model an underwater acoustic channel, thereby determining a time-domain passband received signal after a time-domain passband transmitted signal passes through an underwater acoustic channel. The time-domain passband received signal is then subjected to receiving-end preprocessing, discrete Fourier transform discrete sampling, and zero-forcing equalization to obtain a post-equalization discrete frequency domain measurement value on the current subcarrier. The signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system can be predicted based on the useful signal term and the interference signal term in the post-equalization discrete frequency domain measurement value. The method can predict the signal-to-interference ratio directly based on the structure and communication principle of the CP-OFDM passband underwater acoustic communication system without the need for Monte Carlo simulation, and is easy to implement with high accuracy.

Description

Technical Field

[0001] The present application relates to the field of passband underwater acoustic communication systems, and in particular to a signal-to-interference ratio prediction method for a CP-OFDM passband underwater acoustic communication system. Background Art

[0002] Shallow sea is an important part of my country's territorial waters. High-speed, stable and reliable communication is of great significance for maintaining marine rights and interests, ensuring the economic development of territorial waters, and protecting the underwater safety of territorial waters. CP-OFDM (Cyclic Prefix Orthogonal Frequency Division Multiplexing) is a commonly used modulation method for realizing high-speed underwater acoustic communication. The system structure diagram of a typical passband underwater acoustic communication system based on CP-OFDM waveform is shown in the figure below. Figure 1 As shown in the figure, after the binary input bit stream is modulated by PSK, it is subjected to IDFT (inverse discrete Fourier transform) operation after serial-to-parallel conversion, and then a cyclic prefix is ​​added after parallel-to-serial conversion. After that, the passband transmission signal is obtained through upsampling and digital up-conversion. The passband transmission signal is passed through the underwater acoustic channel to obtain the received signal. Since the Doppler effect seriously interferes with the underwater acoustic communication signal, the received signal is firstly subjected to time domain resampling Doppler coarse compensation at the receiving end. After that, the received signal after coarse compensation can generate a baseband reception signal through the corresponding inverse process of the transmitting end (including removal of cyclic prefix, serial-to-parallel conversion, DFT operation and parallel-to-serial conversion), and finally the binary output bit stream is obtained through PSK demodulation.

[0003] The use of cyclic prefixes enables CP-OFDM to simply and effectively suppress channel multipath effects and avoid inter-code interference caused by underwater acoustic multipath effects, and is therefore widely used in underwater acoustic communication scenarios with high-speed requirements. However, underwater acoustic channels not only include channel multipath effects, but also the effects caused by underwater acoustic Doppler effects. Due to the multi-carrier modulation nature of CP-OFDM and the higher sidelobe energy brought by the rectangular window, CP-OFDM is sensitive to Doppler frequency shift and is prone to performance degradation. In order to accurately analyze the signal-to-interference ratio of CP-OFDM under the influence of Doppler frequency shift, the current mainstream approach is to use Monte Carlo simulation to achieve this, but its implementation complexity is high and the accuracy is not ideal. Summary of the invention

[0004] In view of the above problems and technical requirements, this application proposes a signal-to-interference ratio prediction method for a CP-OFDM passband underwater acoustic communication system. The technical solution of this application is as follows:

[0005] A signal-to-interference ratio prediction method for a CP-OFDM passband underwater acoustic communication system, the signal-to-interference ratio prediction method comprising:

[0006] The underwater acoustic channel model containing multiple tap paths in the CP-OFDM passband underwater acoustic communication system is obtained by using impulse response function.

[0007] Determine the time domain passband transmission signal s of the CP-OFDM passband underwater acoustic communication system based on the underwater acoustic channel model p (t) Time domain passband received signal after passing through the underwater acoustic channel For time domain passband receiving signal Perform receiving end preprocessing to obtain the time domain baseband received signal y after Doppler coarse compensation and carrier removal b (t);

[0008] For the time domain baseband received signal y b (t) After performing discrete Fourier transform, discrete sampling and zero-forcing equalization, a post-equalization discrete frequency domain measurement value Y[l] on the current l-th subcarrier is obtained, where the post-equalization discrete frequency domain measurement value Y[l] includes a useful signal term Y1[l] where n=l and an interference signal term Y2[l] where n≠l;

[0009] according to The signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system is predicted based on the useful signal term Y1[l] and the interference signal term Y2[l], and E() represents the average value.

[0010] A further technical solution is to decompose the discrete frequency domain measurement value Y[l] after equalization to obtain the useful signal term Y1[l]=s[l]D l ; The interference signal term obtained by decomposing the discrete frequency domain measurement value Y[l] after equalization Where s[l] is the frequency domain transmission symbol on the current l-th subcarrier, D l is the channel distortion coefficient of the current l-th subcarrier, s[n] is the frequency domain transmission symbol on any n-th subcarrier, I l,n is the inter-carrier interference coefficient between any nth subcarrier and the current lth subcarrier, N is the total number of subcarriers, γ E (f n )=Υ(f l ) / γ(f n ) represents the ratio of the channel frequency response of the current l-th subcarrier to that of any n-th subcarrier.

[0011] A further technical solution is that the channel distortion coefficient D of the current lth subcarrier l and the inter-carrier interference coefficient I between the nth subcarrier and the current lth subcarrier l,n for:

[0012]

[0013] Among them, γ RD is the residual Doppler factor and j is an imaginary number.

[0014] Its further technical solution is to predict the signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system including:

[0015] Based on the fact that the CP-OFDM passband underwater acoustic communication system adopts PSK modulation and the energy of the frequency domain transmission symbol s[l] on the current l-th subcarrier is equal to the energy of the frequency domain transmission symbol s[n] on any n-th subcarrier, the signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system is predicted according to the following formula:

[0016]

[0017] A further technical solution is that obtaining the post-equalization discrete frequency domain measurement value Y[l] on the current l-th subcarrier includes:

[0018] according to The formula for the time domain baseband received signal y b (t) Perform discrete Fourier transform to obtain the frequency domain measurement value Y′[l] on the current l-th subcarrier, where Δf is the subcarrier spacing and T is the symbol duration of a single OFDM waveform;

[0019] The frequency domain measurement value Y′[l] on the current l-th subcarrier is calculated according to T s =T / N sampling period to perform discrete sampling, and obtain the discrete frequency domain measurement value Y″[l] on the current l-th subcarrier;

[0020] Zero-forcing equalization is performed on the discrete frequency domain measurement value Y″[l] on the current l-th subcarrier to obtain the equalized discrete frequency domain measurement value Y[l] on the current l-th subcarrier.

[0021] Its further technical solution is that the underwater acoustic channel model obtained by modeling includes:

[0022] Based on the characteristics of underwater acoustic channels that meet the fully saturated channel conditions in shallow sea horizontal long-distance communication scenarios, the Doppler factors of all tap paths in the underwater acoustic channel are determined to be equal and equal to ε, and the impulse response function is used to calculate the Doppler factor of the N-channel. P The underwater acoustic channel with multipath taps is represented by the following model:

[0023]

[0024] Among them, δ() represents the impulse response function, A p is the amplitude of the pth tap path, τ p is the tap delay of the pth tap path, N pis the total number of tap paths of the underwater acoustic channel.

[0025] A further technical solution is to determine the time domain passband received signal include:

[0026] Determine the time domain passband transmission signal s of the CP-OFDM passband underwater acoustic communication system p (t) is written as for t∈[0,T+T CP ]:

[0027]

[0028] Combined with the underwater acoustic channel model, the passband received signal after the passband transmitted signal passes through the underwater acoustic channel is determined It is expressed as:

[0029]

[0030] Among them, f n =f c +nΔf is the subcarrier frequency of any nth subcarrier, f c is the center frequency of the passband signal, g(t) is the expression for the pulse shaping filter and T CP is the cyclic prefix duration of a single OFDM waveform, is the ocean ambient noise within the passband.

[0031] A further technical solution is to obtain a time domain baseband received signal y after Doppler coarse compensation and carrier removal. b (t) include:

[0032] Using the Doppler factor estimate For passband receiving signal Resample to obtain the signal y after Doppler coarse compensation and carrier removal b ′(t) is:

[0033]

[0034] After Doppler coarse compensation and carrier removal, the signal y b ′(t) is simplified to obtain the time domain baseband received signal:

[0035]

[0036] Among them, the residual Doppler factor ω(t) is the baseband ocean ambient noise.

[0037] A further technical solution is to obtain the frequency domain measurement value Y′[l] and the discrete frequency domain measurement value Y″[l] on the current l-th subcarrier as follows:

[0038]

[0039]

[0040] Among them, the channel frequency response of any nth subcarrier is ω[l] is the ambient noise term on the lth subcarrier obtained by discrete Fourier transform.

[0041] A further technical solution is to perform Doppler coarse compensation and carrier removal on the signal y b ′(t) simplification includes:

[0042] Within the error range Equivalent to 1, based on the cyclic prefix duration T of a single OFDM waveform CP The characteristic of the maximum multipath delay greater than the underwater acoustic channel is g(t-τ p ) = g(t) = 1, based on the residual Doppler shift With subcarrier frequency f n The irrelevant features consider the residual Doppler shift suffered by the CP-OFDM passband underwater acoustic communication system as consistent and After Doppler coarse compensation and carrier removal, the signal y b ′(t) is simplified to obtain the time domain baseband received signal y b (t).

[0043] The beneficial technical effects of this application are:

[0044] The present application discloses a method for predicting the signal-to-interference ratio of a CP-OFDM passband underwater acoustic communication system. The method can fit and determine a time domain baseband receiving signal according to the structure and communication principle of the CP-OFDM passband underwater acoustic communication system, and then obtain a discrete frequency domain measurement value after equalization after processing the time domain baseband receiving signal. Then, the useful signal item and the interference signal item can be extracted respectively, and the signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system can be predicted. The method can directly fit and predict the signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system without using Monte Carlo simulation, and is easy to implement. It provides a feasible method for analyzing the signal-to-interference ratio performance of the CP-OFDM passband underwater acoustic communication system in different sea areas. In addition, in the prediction process, no conditional approximation processing is performed except for parameter equivalence within an error range, so the predicted signal-to-interference ratio has a high accuracy.

[0045] This method analyzes the resampled underwater acoustic CP-OFDM received signal and finds that the residual Doppler shift is independent of each subcarrier frequency and can be regarded as a consistent Doppler shift, thereby simplifying the prediction process. The prediction process is further simplified based on the characteristics of the PSK digital modulation method. The prediction process intuitively establishes the correlation between the signal-to-interference ratio and the interference subcarrier energy. The method is not limited by the PSK digital modulation method and has strong versatility. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a structural diagram of the CP-OFDM passband underwater acoustic communication system.

[0047] Figure 2 This is a method flow chart of a signal-to-interference ratio prediction method according to an embodiment of the present application.

[0048] Figure 3 It is a schematic diagram of the frequency offset suffered by the subcarrier in the CP-OFDM passband underwater acoustic communication system. DETAILED DESCRIPTION

[0049] The specific implementation of the present application is further described below in conjunction with the accompanying drawings.

[0050] This application discloses a method for predicting the signal-to-interference ratio of a CP-OFDM passband underwater acoustic communication system. Figure 2 The signal-to-interference ratio prediction method comprises the following steps:

[0051] Step 1: Use impulse response function to model the underwater acoustic channel containing multiple tap paths in the CP-OFDM passband underwater acoustic communication system to obtain an underwater acoustic channel model.

[0052] According to the transmission characteristics of underwater acoustic channels, the impulse response function can be used to p The underwater acoustic channel with 1 tap path is expressed as:

[0053]

[0054] Where t represents time. p is the initial delay of the pth tap path. ε p is the Doppler factor of the pth tap path. p is the path amplitude of the pth tap path, and generally the path amplitude A of all tap paths can be set p are the same. δ() represents the impulse response function. A p and τ p The total number of tap paths N of the underwater acoustic channel can be obtained through BELLHOP software. p ≥2 and the value is determined according to the structure of the actual underwater acoustic channel.

[0055] In the shallow sea horizontal long-distance communication scenario, the horizontal transmission distance is much greater than the vertical depth. The underwater acoustic channel can be regarded as satisfying the fully saturated channel condition in the shallow sea horizontal long-distance communication scenario. At this time, it can be determined that the Doppler factors of all tap paths in the underwater acoustic channel are equal and recorded as ε. Then, substituting into formula (1), the underwater acoustic channel model can be obtained as follows:

[0056]

[0057] Step 2: Determine the time domain passband transmission signal s of the CP-OFDM passband underwater acoustic communication system according to the underwater acoustic channel model. p (t) Time domain passband received signal after passing through the underwater acoustic channel

[0058] Based on the signal characteristics of the CP-OFDM passband underwater acoustic communication system, the time domain passband transmission signal s of the CP-OFDM passband underwater acoustic communication system p (t) can be expressed as:

[0059]

[0060] Formula (3) is CP ], T is the symbol duration of a single OFDM waveform, T CP is the cyclic prefix duration of a single OFDM waveform.

[0061] s[n] is the frequency domain transmission symbol on any nth subcarrier, parameter 0≤n≤N-1, N is the total number of subcarriers. Δf is the subcarrier spacing, f c is the center frequency of the passband signal. g(t) is the expression for the pulse shaping filter and j is an imaginary number.

[0062] Combined with the underwater acoustic channel model, the passband transmission signal s can be determined p (t) Passband received signal after passing through the underwater acoustic channel It is expressed as:

[0063]

[0064] Among them, f n =f c +nΔf is the subcarrier frequency of any nth subcarrier. is the ocean ambient noise within the passband.

[0065] Step 3: Receive the signal in the time domain passband Perform receiving end preprocessing to obtain the time domain baseband received signal y after Doppler coarse compensation and carrier removal b (t).

[0066] The underwater acoustic Doppler scale factor is large due to the slow underwater propagation speed. Although it can be considered that each tap path has a consistent Doppler factor ε, the broadband underwater acoustic communication system will still suffer from severe non-uniform Doppler frequency shift, such as Figure 3 As shown, the subcarrier frequency f of any nth subcarrier n The frequency will shift to (1+ε)f n ,Therefore, in a mobile broadband underwater acoustic communication system, each frequency component suffers from a different degree of frequency offset.

[0067] In order to offset part of the influence of the non-uniform Doppler effect, the passband received signal is first Resampled non-uniform Doppler coarse compensation is performed. In practical applications, linear frequency modulation signals are generally inserted before and after the signal frame, and then the Doppler factor estimate is determined based on the linear frequency modulation signal. This part is a commonly used operation step at present, and this embodiment will not be repeated. Then use the Doppler factor estimation value For passband receiving signal The signal yb′(t) obtained by resampling after Doppler coarse compensation and carrier removal is:

[0068]

[0069] where ω(t) is the baseband ocean ambient noise.

[0070] Then, the signal y after Doppler coarse compensation and carrier removal is b ′(t) is simplified, including the following simplifications:

[0071] (a) Due to the Doppler factors ε of all tap paths and the Doppler factor estimates are much smaller than 1, so they will be within the error range. Equivalent to 1.

[0072] (b) Since the cyclic prefix duration T of a single OFDM waveform CP If g(t-τ) is greater than the maximum multipath delay of the underwater acoustic channel, then the OFDM symbol will not be affected by the channel multipath. p )=g(t)=1.

[0073] (c) In addition, the first term on the right side of equation (5) shows that the residual Doppler frequency shift The value of the subcarrier frequency f n The residual Doppler frequency shift suffered by the CP-OFDM passband underwater acoustic communication system can be regarded as consistent, so we can make Introducing the residual Doppler factor

[0074] Combining the above three aspects of simplification, equation (5) can be simplified to obtain the time domain baseband received signal y after Doppler coarse compensation and carrier removal: b (t) is:

[0075]

[0076] Step 4: Receive the time domain baseband signal y b (t) After performing discrete Fourier transform, discrete sampling and zero-forcing equalization, the equalized discrete frequency domain measurement value Y[l] on the current l-th subcarrier is obtained, including:

[0077] (1) First, follow The formula for the time domain baseband received signal y b (t) Perform discrete Fourier transform to obtain the frequency domain measurement value Y′[l] on the current l-th subcarrier.

[0078] Combined with the time domain baseband received signal y of formula (6) b (t), the frequency domain measurement value Y′[l] on the current l-th subcarrier can be obtained as:

[0079]

[0080] Among them, the channel frequency response of any nth subcarrier is ω[l] is the ambient noise term on the lth subcarrier obtained by discrete Fourier transform.

[0081] (2) The frequency domain measurement value Y′[l] on the current l-th subcarrier is calculated according to T s =T / N sampling period, at the sampling time Discrete sampling is performed to obtain the discrete frequency domain measurement value Y″[l] on the current l-th subcarrier. The discrete frequency domain measurement value Y″[l] after discrete sampling in formula (7) is:

[0082]

[0083] Since the environmental noise term ω[l] is Gaussian white noise, the power spectrum at each frequency point is consistent, so no distinction is made in practice. In addition, the focus of this application is to predict the signal-to-interference ratio, so the environmental noise term ω[l] can be ignored within the error range, so formula (8) can actually be considered to have only the first term.

[0084] In order to distinguish useful signals from interference signals, the first term of equation (8) is decomposed into useful signal terms with n=1 and interference signal terms with n≠1. Equation (8) can be rewritten as:

[0085]

[0086] Where s[l] is the frequency domain transmission symbol on the current l-th subcarrier, D l is the channel distortion coefficient of the current l-th subcarrier, and the channel frequency response γ(f l ) can be calculated according to γ(f n ) is determined in the form of . s[n] is the frequency domain transmission symbol on any nth subcarrier, I l,n is the inter-carrier interference coefficient between any n-th subcarrier and the current l-th subcarrier.

[0087] According to the form of formula (8), the channel distortion coefficient D of the current l-th subcarrier can be obtained: l and the inter-carrier interference coefficient I between the nth subcarrier and the current lth subcarrier l,n for:

[0088]

[0089] (3) Based on the characteristics of the known perfect channel state information at the receiving end of the CP-OFDM passband underwater acoustic communication system, the discrete frequency domain measurement value Y″[l] on the current l-th subcarrier is subjected to zero-forcing equalization, and the channel frequency domain response estimate at the l-th subcarrier is set to Zero-forcing equalization is performed on equation (8) to obtain the post-equalization discrete frequency domain measurement value Y[l] on the current l-th subcarrier. The post-equalization discrete frequency domain measurement value Y[l] is similar to equation (9), and also includes the useful signal term Y1[l] when n=l and the interference signal term Y2[l] when n≠l, which can be expressed as:

[0090]

[0091] Among them, the useful signal term Y1[l]=s[l]D obtained by decomposing the discrete frequency domain measurement value Y[l] after equalization l .

[0092] The interference signal term obtained by decomposing the discrete frequency domain measurement value Y[l] after equalization γ E (f n )=γ(f l ) / γ(f n ) represents the ratio of the channel frequency response on the current l-th subcarrier to that on any n-th subcarrier.

[0093] Step 5, follow The signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system is predicted based on the useful signal term Y1[l] and the interference signal term Y2[l].

[0094] In the above formula, E() represents the average value. Substituting the useful signal term Y1[l] and the interference signal term Y2[l] into the signal-to-interference ratio calculation formula, the signal-to-interference ratio can be obtained as follows:

[0095]

[0096] In one embodiment, when the CP-OFDM passband underwater acoustic communication system adopts the PSK modulation mode, the energy of the frequency domain transmission symbol s[l] on the current l-th subcarrier is equal to the energy of the frequency domain transmission symbol s[n] on any n-th subcarrier. Based on this feature, equation (12) can be further simplified and the signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system can be predicted according to the following formula:

[0097]

[0098] The above is only a preferred embodiment of the present application, and the present application is not limited to the above embodiments. It is understood that other improvements and changes directly derived or associated by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included in the protection scope of the present application.

Claims

1. A method for predicting signal-to-interference ratio of a CP-OFDM passband underwater acoustic communication system, characterized in that: The signal-to-interference ratio prediction method comprises: The underwater acoustic channel model containing multiple tap paths in the CP-OFDM passband underwater acoustic communication system is obtained by using impulse response function. Determine the time domain passband transmission signal s of the CP-OFDM passband underwater acoustic communication system according to the underwater acoustic channel model p (t) Time domain passband received signal after passing through the underwater acoustic channel For time domain passband receiving signal Perform receiving end preprocessing to obtain the time domain baseband received signal y after Doppler coarse compensation and carrier removal b (t); The time domain baseband received signal y after Doppler coarse compensation and carrier removal is obtained b (t) include: Using the Doppler factor estimate For passband receiving signal Resample to obtain the signal y after Doppler coarse compensation and carrier removal b ′(t) is: After Doppler coarse compensation and carrier removal, the signal y b ′(t) is simplified to obtain the time domain baseband received signal: Among them, the residual Doppler factor ω(t) is the baseband ocean ambient noise. The Doppler factors of all tap paths in the underwater acoustic channel are equal and equal to ε. The Doppler factor estimate is f n =f c +nΔf is the subcarrier frequency of any nth subcarrier, f c is the center frequency of the passband signal, Δf is the subcarrier spacing, N is the total number of subcarriers, A p is the amplitude of the pth tap path, τ p is the tap delay of the pth tap path, N p is the total number of tap paths of the underwater acoustic channel, s[n] is the frequency domain transmission symbol on any nth subcarrier; After Doppler coarse compensation and carrier removal, the signal y b ′(t) simplification includes: Within the error range Equivalent to 1, based on the cyclic prefix duration T of a single OFDM waveform CP The characteristic of the maximum multipath delay greater than the underwater acoustic channel is g(t-τ p )=g(t)=1, g(t) is the expression of the pulse shaping filter and T is the symbol duration of a single OFDM waveform, based on the residual Doppler shift With subcarrier frequency f n The irrelevant features consider the residual Doppler shift suffered by the CP-OFDM passband underwater acoustic communication system as consistent and After Doppler coarse compensation and carrier removal, the signal y b ′(t) is simplified to obtain the time domain baseband received signal y b (t); For the time domain baseband received signal y b (t) After performing discrete Fourier transform, discrete sampling and zero-forcing equalization, a post-equalization discrete frequency domain measurement value Y[l] on the current l-th subcarrier is obtained, and the post-equalization discrete frequency domain measurement value Y[l] includes a useful signal item Y1[l] of any n-th subcarrier n=l and an interference signal item Y2[l] of n≠l; according to The signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system is predicted based on the useful signal term Y1[l] and the interference signal term Y2[l], and E() represents the average value.

2. The signal-to-interference ratio prediction method according to claim 1, characterized in that: The useful signal term Y1[l]=s[l]D obtained by decomposing the discrete frequency domain measurement value Y[l] after equalization l ; The interference signal term obtained by decomposing the discrete frequency domain measurement value Y[l] after equalization Where s[l] is the frequency domain transmission symbol on the current l-th subcarrier, D l is the channel distortion coefficient of the current l-th subcarrier, s[n] is the frequency domain transmission symbol on any n-th subcarrier, I l,n is the inter-carrier interference coefficient between any nth subcarrier and the current lth subcarrier, N is the total number of subcarriers, γ E (f n )=γ(f l )γ(f n ) represents the ratio of the channel frequency response of the current l-th subcarrier to that of any n-th subcarrier.

3. The signal-to-interference ratio prediction method according to claim 2, characterized in that: The channel distortion coefficient D of the current lth subcarrier l and the inter-carrier interference coefficient I between the nth subcarrier and the current lth subcarrier l,n for: Among them, γ RD is the residual Doppler factor and j is an imaginary number.

4. The signal-to-interference ratio prediction method according to claim 3, characterized in that: The predicted signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system includes: Based on the fact that the CP-OFDM passband underwater acoustic communication system adopts PSK modulation and the energy of the frequency domain transmission symbol s[l] on the current l-th subcarrier is equal to the energy of the frequency domain transmission symbol s[n] on any n-th subcarrier, the signal-to-interference ratio of the CP-OFDM passband underwater acoustic communication system is predicted according to the following formula:

5. The signal-to-interference ratio prediction method according to claim 1, characterized in that: Obtaining the post-equalization discrete frequency domain measurement value Y[l] on the current l-th subcarrier includes: according to The formula for the time domain baseband received signal y b (t) Perform discrete Fourier transform to obtain the frequency domain measurement value Y′[l] on the current l-th subcarrier, where Δf is the subcarrier spacing and T is the symbol duration of a single OFDM waveform; The frequency domain measurement value Y′[l] on the current l-th subcarrier is calculated according to T s = TN sampling period to perform discrete sampling, and obtain the discrete frequency domain measurement value Y″[l] on the current l-th subcarrier; Zero-forcing equalization is performed on the discrete frequency domain measurement value Y″[l] on the current l-th subcarrier to obtain the equalized discrete frequency domain measurement value Y[l] on the current l-th subcarrier.

6. The signal-to-interference ratio prediction method according to claim 5, characterized in that: The underwater acoustic channel model obtained by modeling includes: Based on the characteristics of underwater acoustic channels that meet the fully saturated channel conditions in shallow sea horizontal long-distance communication scenarios, the Doppler factors of all tap paths in the underwater acoustic channel are determined to be equal and equal to ε, and the impulse response function is used to calculate the Doppler factor of the N-channel. P The underwater acoustic channel with multipath taps is represented by the following model: Among them, δ() represents the impulse response function, A p is the amplitude of the pth tap path, τ p is the tap delay of the pth tap path, N p is the total number of tap paths of the underwater acoustic channel.

7. The signal-to-interference ratio prediction method according to claim 6, characterized in that: Determine the passband of the received signal in the time domain include: Determine the time domain passband transmission signal s of the CP-OFDM passband underwater acoustic communication system p (t) is written as for t∈[0,T+T CP ]: Combined with the underwater acoustic channel model, determine the passband received signal after the passband transmission signal passes through the underwater acoustic channel It is expressed as: Among them, f n =f c +nΔf is the subcarrier frequency of any nth subcarrier, f c is the center frequency of the passband signal, g(t) is the expression for the pulse shaping filter and T CP is the cyclic prefix duration of a single OFDM waveform, is the ocean ambient noise within the passband.

8. The signal-to-interference ratio prediction method according to claim 7, characterized in that: The frequency domain measurement value Y′[l] and discrete frequency domain measurement value Y″[l] on the current l-th subcarrier are obtained as follows: Among them, the channel frequency response of any nth subcarrier is ω[l] is the ambient noise term on the lth subcarrier obtained by discrete Fourier transform.

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