Underwater sound generalized frequency division multiplexing communication subcarrier subsymbol adaptive configuration method based on interference minimization

Abstract

The invention relates to the field of wireless communication, in particular to an underwater sound generalized frequency division multiplexing communication subcarrier subsymbol self-adaptive configuration method based on interference minimization, and discloses an underwater sound generalized frequency division multiplexing communication subcarrier subsymbol self-adaptive configuration method based on interference minimization. The objective of the invention is to solve the problems of low accuracy of channel estimation and low communication quality caused by too high inter-carrier interference and inter-symbol interference due to the fact that a GFDM system is affected by a multipath effect in underwater acoustic communication. According to the method provided by the invention, after the optimal configuration is selected, the performance of the GFDM communication system in the underwater acoustic channel can be greatly improved. By accurately analyzing and calculating the energy of interference between subcarriers and interference between sub-symbols, an optimal configuration scheme based on interference energy minimization is selected, and the scheme not only fully utilizes a flexible data block structure of GFDM, but also combines an interference elimination technology, so that the system shows better performance in an underwater acoustic multipath channel; and the channel estimation accuracy and the communication quality are improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a method for adaptively configuring sub-carrier sub-symbols in underwater acoustic generalized frequency division multiplexing communications. Background Art

[0002] As a key technical means, underwater acoustic communication is widely used in military, environmental monitoring, marine science research and other fields. However, since the complexity of underwater acoustic channels is much higher than that of wireless channels on the ground, underwater acoustic communication faces many challenges in practical applications. The multipath effect, time-varying characteristics, noise background and limited bandwidth of underwater acoustic channels make the reliability and transmission rate of high-speed underwater acoustic communication relatively lagging behind that of terrestrial wireless communications. In recent years, with the rapid development of 5G communication technology, how to apply it to the field of underwater acoustic communication has become a hot topic of concern to international scholars and researchers.

[0003] In traditional underwater acoustic communication systems, Orthogonal Frequency Division Multiplexing (OFDM) technology has been widely used. This technology effectively solves the problem of multipath interference by dividing data into multiple subcarriers for transmission. However, the OFDM system also has its inherent defects. First, the OFDM system is not flexible enough and it is difficult to adapt to the complex underwater acoustic channel environment. Secondly, since the subcarriers in the OFDM system are orthogonal, it is difficult to completely maintain the orthogonality in practical applications, resulting in serious out-of-band leakage problems in the system. In addition, the spectrum utilization rate of the OFDM system is low, especially in underwater acoustic communications, where spectrum resources are already scarce, this problem is even more prominent.

[0004] In order to overcome these problems, Generalized Frequency Division Multiplexing (GFDM), as an emerging waveform technology, has gradually attracted the attention of the academic community. Compared with OFDM, GFDM has been improved and optimized in many aspects. First, GFDM retains the cyclic prefix (CP) structure in OFDM, which makes it easier to achieve channel equalization at the receiving end, thereby simplifying the design of the system. At the same time, GFDM improves the spectrum efficiency by reducing the number of CPs, which is particularly important for underwater acoustic communication, because the improvement of spectrum efficiency means that more information can be transmitted under limited bandwidth. In addition, as a non-orthogonal multi-carrier transmission scheme, GFDM has flexible data block structure adjustment capabilities and can dynamically adjust transmission parameters according to changes in the underwater acoustic channel, so as to better adapt to complex underwater environments. GFDM also has a lower peak-to-average power ratio, which not only helps to reduce the nonlinear distortion of the power amplifier, but also reduces the power consumption of the system, which is also an important advantage in underwater acoustic communication.

[0005] Although GFDM has many advantages in theory, in practical applications, the complexity of underwater acoustic channels puts higher requirements on the performance of GFDM systems. Previous studies have mainly focused on the improvement of GFDM channel estimation algorithms. For underwater acoustic channels, due to their special physical characteristics, channel estimation often requires the help of pilots. However, since the subcarriers of the GFDM system are non-orthogonal, this will introduce additional interference in actual transmission, resulting in the accuracy of channel estimation being affected. Therefore, how to effectively eliminate these interferences has become a key issue in the application of GFDM in underwater acoustic communications. In existing research, scholars have proposed a variety of methods to eliminate interference. Among them, the commonly used methods include pilot interference elimination and transmitter interference elimination. These methods improve the channel estimation accuracy of the system by reducing the self-interference between subcarriers during pilot design and transmission. However, the effects of these methods are limited, and there is still room for improvement when facing complex underwater acoustic channels. In recent years, some new technologies have been proposed, such as interference-free pilot insertion technology, GFDM dual filter transmission, joint iterative channel estimation and symbol detection. These methods further improve the performance of the system by introducing new signal processing technologies, but at the same time increase the implementation complexity of the system. Summary of the invention

[0006] The purpose of the present invention is to solve the problem that the inter-carrier interference and inter-symbol interference of the GFDM system in underwater acoustic communication are too high due to the multipath effect, resulting in low accuracy of channel estimation and low communication quality, and to propose an adaptive configuration method of sub-carriers and sub-symbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization.

[0007] The specific process of the adaptive configuration method of subcarrier subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization is as follows:

[0008] Step 1: Determine a binary input data consisting of 0 and 1

[0009] Step 2: Set the initial iteration count n=0, and set the number of subcarriers and subsymbols to K respectively. (n) and M (n) ;

[0010] Binary input data The length is K (n) ×M (n) ;

[0011] Based on binary input data Calculate the subcarrier interference energy at iteration count n Sum sub-symbol interference energy Save the optimal number of subcarriers as K′=K (n) , the optimal number of sub-symbols is M′=M (n) ;

[0012] Step 3: Set the iteration count n=n+1, and set the new number of subcarriers and subsymbols to K respectively. (n) and M (n) ;

[0013] Binary input data The length is K (n) ×M (n) ;

[0014] Based on binary input data Calculate the new subcarrier interference energy Sum sub-symbol interference energy

[0015] Compare the new subcarrier interference energy and the original subcarrier interference energy

[0016] Comparison of new sub-symbol interference energy and the original sub-symbol interference energy

[0017] If the new subcarrier interference energy Less than the original retained subcarrier interference energy And the new sub-symbol interference energy Less than the original retained sub-symbol interference energy Then the optimal number of subcarriers is updated to the new number of subcarriers, and the optimal number of subsymbols is updated to the new number of subsymbols;

[0018] If the new subcarrier interference energy Less than the original retained subcarrier interference energy And the new sub-symbol interference energy Greater than or equal to the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols;

[0019] If the new subcarrier interference energy Greater than or equal to the original reserved subcarrier interference energy And the new sub-symbol interference energy Less than the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols;

[0020] If the new subcarrier interference energy Greater than or equal to the original reserved subcarrier interference energy And the new sub-symbol interference energy Greater than or equal to the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols;

[0021] Step 4: Repeat step 3 until the maximum number of iterations is reached or the number of subcarriers and the number of subsymbols do not change in N consecutive iterations, stop iteration, and save the optimal number of subcarriers and the optimal number of subsymbols.

[0022] The beneficial effects of the present invention are:

[0023] The present invention enables the GFDM communication system to exhibit higher reliability and adaptability in a complex underwater acoustic channel by adaptively optimizing the configuration of subcarriers and subsymbols and combining interference elimination technology.

[0024] The present invention optimizes the configuration of subcarriers and subsymbols by analyzing the performance of the GFDM system itself and combining different multipath underwater acoustic channel models. At the same time, the present invention combines pilot technology and a relatively simple interference elimination method to propose an effective solution that can reduce the inter-carrier interference (Inter-Carrier Interference) and inter-symbol interference (Inter-Symbol Interference) of the GFDM system, thereby improving the performance of the GFDM system while maintaining a low implementation complexity, providing a new idea for the application of GFDM in underwater acoustic communications.

[0025] The subcarrier-subsymbol adaptive configuration method based on interference minimization proposed in the present invention can significantly improve the performance of the GFDM communication system in the underwater acoustic channel after selecting the optimal configuration. By accurately analyzing and calculating the energy of the interference between subcarriers and the interference between subsymbols, the optimal configuration scheme based on minimizing the interference energy is selected. This scheme not only makes full use of the flexible data block structure of GFDM, but also combines the interference elimination technology, so that the system can show better performance in the underwater acoustic multipath channel; it improves the accuracy of channel estimation and the communication quality.

[0026] Experimental results show that compared with the fixed configuration method, the present invention can improve the reliability and adaptability of the GFDM system in practical applications with less complexity by iteratively selecting the number of subcarriers and subsymbols with the minimum ISI and ICI under the current channel. This achievement is of great significance to the development of underwater communication, especially in complex marine environments, where the present invention can achieve more efficient and stable communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the present invention;

[0028] Figure 2 It is the GFDM symbol block diagram;

[0029] Figure 3 Implement a block diagram for the GFDM communication system;

[0030] Figure 4 The channel impulse response diagrams used in the simulation are (a) underwater acoustic multipath channel 1, (b) underwater acoustic multipath channel 2;

[0031] Figure 5BER comparison diagram of GFDM communication system with different subcarrier and subsymbol configurations under three channels: (a) BER comparison diagram of GFDM communication system with different subcarrier and subsymbol configurations under Gaussian white noise channel, (b) BER comparison diagram of GFDM communication system with different subcarrier and subsymbol configurations under underwater acoustic multipath channel 1, (c) BER comparison diagram of GFDM communication system with different subcarrier and subsymbol configurations under underwater acoustic multipath channel 2. DETAILED DESCRIPTION

[0032] Specific implementation method 1: The specific process of the method for adaptively configuring subcarrier subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization is as follows:

[0033] Step 1: Determine a binary input data consisting of 0 and 1

[0034] Step 2: Set the initial iteration count n=0, and set the number of subcarriers and subsymbols to K respectively. (n) and M (n) ;

[0035] Binary input data The length is K (n) ×M (n) (For example, the sequence Length 1024, K is 2, M is 512; k is 4, M is 256; K is 256, M is 4; and so on);

[0036] Based on binary input data Calculate the subcarrier interference energy at iteration count n Sum sub-symbol interference energy Save the optimal number of subcarriers as K′=K (n) , the optimal number of sub-symbols is M′=M (n) ;

[0037] Step 3: Set the iteration count n=n+1, and set the new number of subcarriers and subsymbols to K respectively. (n) and M (n) ;

[0038] Binary input data The length is K (n) ×M (n) ;

[0039] Based on binary input data Calculate the new subcarrier interference energy Sum sub-symbol interference energy

[0040] Compare the new subcarrier interference energy and the original subcarrier interference energy

[0041] Comparison of new sub-symbol interference energy and the original sub-symbol interference energy

[0042] If the new subcarrier interference energy Less than the original retained subcarrier interference energy And the new sub-symbol interference energy Less than the original retained sub-symbol interference energy Then the optimal number of subcarriers is updated to the new number of subcarriers, and the optimal number of subsymbols is updated to the new number of subsymbols;

[0043] If the new subcarrier interference energy Less than the original retained subcarrier interference energy And the new sub-symbol interference energy Greater than or equal to the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols;

[0044] If the new subcarrier interference energy Greater than or equal to the original reserved subcarrier interference energy And the new sub-symbol interference energy Less than the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols;

[0045] If the new subcarrier interference energy Greater than or equal to the original reserved subcarrier interference energy And the new sub-symbol interference energy Greater than or equal to the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols;

[0046] Step 4: Repeat step 3 until the maximum number of iterations is reached or the number of subcarriers and the number of subsymbols do not change in N consecutive iterations, stop iteration, and save the optimal number of subcarriers and the optimal number of subsymbols.

[0047] Specific implementation method 2: This implementation method is different from the specific implementation method 1 in that the step 2 is based on the binary input data Calculate the subcarrier interference energy at iteration count n Sum sub-symbol interference energy The specific process is:

[0048] Step 21: Input binary data one by one Perform encoding, mapping, precoding, and GFDM modulation to obtain modulated signal data;

[0049] Add a cyclic prefix (CP) to the modulated signal data to obtain the transmitted signal x(t);

[0050] Step 22: Construct a multipath channel model h(t);

[0051] Step 2: The transmitted signal x(t) passes through the multipath channel h(t) to obtain the received signal r(t);

[0052] Step 24: Based on the received signal r(t), obtain the kth subcarrier r in the received signal r(t) k Inter-carrier interference (ICI) k (t);

[0053] Step 25: Based on the received signal r(t), obtain the mth sub-symbol r in the received signal r(t) m Inter-symbol interference ISIm(t) of (t);

[0054] Step 26: Based on the mth sub-symbol r in the received signal r(t) m ISI of inter-symbol interference (t) m (t), calculate the sub-symbol interference energy E ISI ;

[0055] Step 27: Based on the kth subcarrier r in the received signal r(t) k Inter-carrier interference (ICI) k (t), calculate the subcarrier interference energy E ICI .

[0056] The other steps and parameters are the same as those in the first or second embodiment.

[0057] Specific implementation method three: This implementation method is different from specific implementation methods one or two in that the binary input data is sequentially processed in step 21. Perform encoding, mapping, precoding, and GFDM modulation to obtain modulated signal data;

[0058] Add a cyclic prefix (CP) to the modulated signal data to obtain the transmitted signal x(t);

[0059] The signal x(t) is expressed as

[0060]

[0061] The GFDM signal is generalized frequency division multiplexing;

[0062] Among them, d k,m represents the data at the kth subcarrier and the mth subsymbol position, g(t) represents the filter, T represents the duration of the subsymbol, f represents the frequency interval between subcarriers, K and M represent the number of subcarriers and subsymbols respectively; t represents time; j represents the imaginary unit, j 2 =-1.

[0063] The other steps and parameters are the same as those in the first or second embodiment.

[0064] Specific implementation method 4: This implementation method is different from the specific implementation methods 1 to 3 in that the multipath channel model h(t) is constructed in step 22, which is expressed as

[0065]

[0066] Where L represents the number of multipaths, h l represents the amplitude of the lth multipath, τ l represents the time delay; δ(t) represents the impulse function, and h(t) represents the multipath channel.

[0067] The other steps and parameters are the same as those in Specific Embodiments 1 to 3.

[0068] Specific implementation mode 5: This implementation mode is different from the specific implementation modes 1 to 4 in that in the steps 2 and 3, the transmitted signal x(t) passes through the multipath channel h(t) to obtain the received signal r(t); the specific process is as follows:

[0069] The received signal r(t) is expressed as

[0070] r(t)=x(t)*h(t)+n(t) (3)

[0071] Among them, * represents convolution, n(t) represents additive noise;

[0072] Expanding the convolution operation of equation (3), the received signal r(t) can also be expressed as

[0073]

[0074] Due to the influence of multipath effect, the received signal of GFDM communication system will have subcarrier interference and subsymbol interference.

[0075] The other steps and parameters are the same as those in Specific Embodiments 1 to 4.

[0076] Specific implementation method 6: This implementation method is different from any one of specific implementation methods 1 to 5 in that in step 24, based on the received signal r(t), the kth subcarrier r in the received signal r(t) is obtained. k Inter-carrier interference (ICI) k (t); The specific process is:

[0077] The kth subcarrier in the received signal r(t) is expressed as

[0078]

[0079] Among them, r k (t) represents the kth subcarrier in the received signal r(t);

[0080] ICI k (t) represents the inter-carrier interference of the kth subcarrier;

[0081] Inter-carrier interference (ICI) of the kth subcarrier k (t) is expressed as:

[0082]

[0083] in, Indicates subcarrier and data at the mth subsymbol position.

[0084] The other steps and parameters are the same as those in Specific Implementation Methods 1 to 5.

[0085] Specific implementation method 7: This implementation method is different from any one of specific implementation methods 1 to 6 in that in step 25, based on the received signal r(t), the mth sub-symbol r in the received signal r(t) is obtained. m ISI of inter-symbol interference (t) m (t); The specific process is:

[0086] The mth sub-symbol in the received signal r(t) is expressed as

[0087]

[0088] Among them, r m (t) represents the mth sub-symbol in the received signal r(t);

[0089] ISI m (t) represents the inter-symbol interference of the m-th sub-symbol;

[0090] The inter-symbol interference ISI of the m-th sub-symbol m (t) is expressed as:

[0091]

[0092] in, represents the kth subcarrier and the The data at the sub-symbol position.

[0093] In order to compare the numerical values ​​of ICI and ISI, we consider obtaining the energy of the two.

[0094] The other steps and parameters are the same as those in Specific Embodiments 1 to 6.

[0095] Specific implementation example 8: This implementation example is different from any one of specific implementation examples 1 to 7 in that in step 26, based on the mth sub-symbol r in the received signal r(t), m ISI of inter-symbol interference (t) m (t), calculate the sub-symbol interference energy E ISI ; The expression is:

[0096]

[0097] The other steps and parameters are the same as those in Specific Embodiments 1 to 7.

[0098] Specific implementation method 9: This implementation method is different from any one of specific implementation methods 1 to 8 in that in step 27, based on the kth subcarrier r in the received signal r(t), k Inter-carrier interference (ICI) k (t), calculate the subcarrier interference energy E ICI ; The expression is:

[0099] Considering that ICI is caused by interference between subcarrier frequencies, its energy is calculated in the frequency domain;

[0100]

[0101] Among them, f k represents the center frequency of the kth subcarrier; B represents the bandwidth range of the subcarrier frequency; △f represents a continuous frequency variable; G() represents the frequency domain expression of the filter; f c Indicates the carrier frequency of the subcarrier.

[0102] The other steps and parameters are the same as those in Specific Embodiments 1 to 8.

[0103] Specific implementation method ten: This implementation method is different from any one of specific implementation methods one to nine in that, in step four, 2≤N≤6.

[0104] The other steps and parameters are the same as those in Specific Embodiments 1 to 9.

[0105] The received signal r(t) corresponding to the optimal number of subcarriers and the optimal number of subsymbols is sequentially subjected to GFDM demodulation, deprecoding, demapping, and decoding to obtain binary output data, and the binary output data and the binary input data are calculated. The bit error rate is calculated and the bit error rate curve is obtained under different signal-to-noise ratio conditions.

[0106] The present invention may also have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization, characterized by: The specific process of the method is: Step 1: Determine a binary input data consisting of 0 and 1 Step 2: Set the initial iteration count n=0, and set the number of subcarriers and subsymbols to K respectively. (n) and M (n) ; Binary input data The length is K (n) ×M (n) ; Based on binary input data Calculate the subcarrier interference energy at iteration count n Sum sub-symbol interference energy Save the optimal number of subcarriers as K′=K (n) , the optimal number of sub-symbols is M′=M (n) ; Step 3: Set the iteration count n=n+1, and set the new number of subcarriers and subsymbols to K respectively. (n) and M (n) ; Binary input data The length is K (n) ×M (n) ; Based on binary input data Calculate the new subcarrier interference energy Sum sub-symbol interference energy Compare the interference energy of new subcarriers and the original subcarrier interference energy Comparison of new sub-symbol interference energy and the original sub-symbol interference energy If the new subcarrier interference energy Less than the original retained subcarrier interference energy And the new sub-symbol interference energy Less than the original retained sub-symbol interference energy Then the optimal number of subcarriers is updated to the new number of subcarriers, and the optimal number of subsymbols is updated to the new number of subsymbols; If the new subcarrier interference energy Less than the original retained subcarrier interference energy And the new sub-symbol interference energy Greater than or equal to the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols; If the new subcarrier interference energy Greater than or equal to the original reserved subcarrier interference energy And the new sub-symbol interference energy Less than the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols; If the new subcarrier interference energy Greater than or equal to the original reserved subcarrier interference energy And the new sub-symbol interference energy Greater than or equal to the original retained sub-symbol interference energy The original subcarrier interference energy is retained and the original retained sub-symbol interference energy The corresponding number of subcarriers and subsymbols; Step 4: Repeat step 3 until the maximum number of iterations is reached or the number of subcarriers and the number of subsymbols do not change in N consecutive iterations, stop iteration, and save the optimal number of subcarriers and the optimal number of subsymbols.

2. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 1 is characterized in that: In step 2, based on binary input data Calculate the subcarrier interference energy at iteration count n Sum sub-symbol interference energy The specific process is: Step 21: Input binary data one by one Perform encoding, mapping, precoding, and GFDM modulation to obtain modulated signal data; Add a cyclic prefix to the modulated signal data to obtain a transmitted signal x(t); Step 22: Construct a multipath channel model h(t); Step 2: The transmitted signal x(t) passes through the multipath channel h(t) to obtain the received signal r(t); Step 24: Based on the received signal r(t), obtain the kth subcarrier r in the received signal r(t) k Inter-carrier interference (ICI) k (t); Step 25: Based on the received signal r(t), obtain the mth sub-symbol r in the received signal r(t) m ISI of inter-symbol interference (t) m (t); Step 26: Based on the mth sub-symbol r in the received signal r(t) m ISI of inter-symbol interference (t) m (t), calculate the sub-symbol interference energy E ISI ; Step 27: Based on the kth subcarrier r in the received signal r(t) k Inter-carrier interference (ICI) k (t), calculate the subcarrier interference energy E ICI .

3. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 2 is characterized in that: In the step 21, the binary input data is sequentially Perform encoding, mapping, precoding, and GFDM modulation to obtain modulated signal data; Add a cyclic prefix to the modulated signal data to obtain a transmitted signal x(t); The signal x(t) is expressed as The GFDM signal is generalized frequency division multiplexing; Among them, d k,m represents the data at the kth subcarrier and the mth subsymbol position, g(t) represents the filter, T represents the duration of the subsymbol, f represents the frequency interval between subcarriers, K and M represent the number of subcarriers and subsymbols respectively; t represents time; j represents the imaginary unit, j 2 =-1.

4. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 3 is characterized in that: In step 22, a multipath channel model h(t) is constructed, which is expressed as Where L represents the number of multipaths, h l represents the amplitude of the lth multipath, τ l represents the time delay; δ(t) represents the impulse function, and h(t) represents the multipath channel.

5. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 4 is characterized in that: In the steps 2 and 3, the transmitted signal x(t) passes through the multipath channel h(t) to obtain the received signal r(t); the specific process is as follows: The received signal r(t) is expressed as r(t)=x(t)*h(t)+n(t) (3) Among them, * represents convolution, n(t) represents additive noise; Expanding the convolution operation of equation (3), the received signal r(t) can also be expressed as 6. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 5 is characterized by: In the step 24, based on the received signal r(t), the kth subcarrier r in the received signal r(t) is obtained. k Inter-carrier interference (ICI) k (t); The specific process is: The kth subcarrier in the received signal r(t) is expressed as Among them, r k (t) represents the kth subcarrier in the received signal r(t); ICI k (t) represents the inter-carrier interference of the kth subcarrier; Inter-carrier interference (ICI) of the kth subcarrier k (t) is expressed as: in, Indicates subcarrier and data at the mth subsymbol position.

7. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 6 is characterized by: In the step 25, based on the received signal r(t), the mth sub-symbol r in the received signal r(t) is obtained. m ISI of inter-symbol interference (t) m (t); The specific process is: The mth sub-symbol in the received signal r(t) is expressed as Among them, r m (t) represents the mth sub-symbol in the received signal r(t); ISI m (t) represents the inter-symbol interference of the m-th sub-symbol; The inter-symbol interference ISI of the m-th sub-symbol m (t) is expressed as: in, represents the kth subcarrier and the The data at the sub-symbol position.

8. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 7 is characterized by: In step 26, based on the mth sub-symbol r in the received signal r(t), m ISI of inter-symbol interference (t) m (t), calculate the sub-symbol interference energy E ISI ; The expression is:

9. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 8, characterized in that: In the step 27, based on the kth subcarrier r in the received signal r(t), k Inter-carrier interference (ICI) k (t), calculate the subcarrier interference energy E ICI ; The expression is: Among them, f k represents the center frequency of the kth subcarrier; B represents the bandwidth range of the subcarrier frequency; △f represents a continuous frequency variable; G() represents the frequency domain expression of the filter; f c Indicates the carrier frequency of the subcarrier.

10. The method for adaptively configuring subcarriers and subsymbols in underwater acoustic generalized frequency division multiplexing communication based on interference minimization according to claim 9, characterized in that: In the step 4, 2≤N≤6.

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