Underwater wireless optical communication adaptive modulation method based on weighted fisher information

Abstract

The application discloses an underwater wireless optical communication adaptive modulation method based on weighted Fisher information quantity. In an offline calibration stage, Fisher information quantity of a subsequence is calculated, and then Fisher information quantity thresholds of modulation orders corresponding to each subsequence are obtained. In an online communication stage, Fisher information quantity of the subsequence is calculated, and then training sequence Fisher information quantity is obtained. The training sequence Fisher information quantity is compared with the Fisher information quantity thresholds of the modulation orders corresponding to each subsequence, and a PPM modulation order meeting a link reliability requirement is selected. The method does not need to statistically count error code events in real time, can explicitly reflect multiplicative fluctuation caused by underwater turbulence, and takes into account sensitive differences of different PPM modulation orders on scattering broadening, and can improve channel quality sensing capability, feedback real-time performance and link stability of an underwater wireless optical communication adaptive modulation system.

Description

Technical Field

[0001] This invention relates to the field of underwater wireless optical communication technology, and specifically to an adaptive modulation method for underwater wireless optical communication based on weighted Fisher information. Background Technology

[0002] Underwater Wireless Optical Communication (UWOC) utilizes the relatively low attenuation characteristics of blue-green light bands in water to achieve high-speed, low-latency, and electromagnetic interference-resistant data transmission over short-to-medium distance underwater links. It is suitable for underwater exploration, marine environmental monitoring, seabed equipment maintenance, submersible communication, and integrated air-space-ground-sea communication scenarios. However, optical signals propagating in water are affected by absorption, scattering, turbulence, and additive noise at the receiver. Absorption causes the received light intensity or equivalent driving current to attenuate with propagation distance; scattering causes multipath spread and inter-symbol interference; turbulence causes random fluctuations in the received light intensity, exhibiting non-stationary multiplicative ripples; and additive noise further reduces the reliability of the received signal. These factors are coupled, causing the quality of the underwater optical channel to continuously change with time and water conditions, resulting in significant composite degradation characteristics.

[0003] Existing UWOC adaptive modulation systems typically use the bit error rate (BER) or a metric derived from the BER as feedback. This type of method requires a sufficient number of bit error events to be counted at the receiver before feeding back to the transmitter, resulting in feedback lag and significant sample overhead. Furthermore, the BER tends to approach 0.5 in the low signal-to-noise ratio (SNR) region and close to 0 in the high SNR region, making it prone to low-end passivation and high-end saturation, and difficult to promptly distinguish between worse and better channel conditions. Summary of the Invention

[0004] The present invention addresses the problems of limited dynamic range and large statistical delay in traditional BER feedback methods by providing an adaptive modulation method for underwater wireless optical communication based on weighted Fisher information.

[0005] To solve the above problems, the present invention is achieved through the following technical solution:

[0006] An adaptive modulation method for underwater wireless optical communication based on weighted Fisher information includes an offline calibration stage and an online communication stage. In the offline calibration stage, a training sequence is transmitted between the transmitter and receiver of a simulated underwater wireless optical communication system. This training sequence includes multiple sub-sequences with different pulse widths. The Fisher information of each sub-sequence of the training sequence is calculated. This process is repeated to obtain the Fisher information of each sub-sequence of multiple training sequences. The weighted average and median values ​​of the Fisher information of the same sub-sequence from different training sequences are then calculated. If the difference between the weighted average and the median does not exceed a set proportion, the weighted average is used as the Fisher information threshold for the modulation order corresponding to that sub-sequence. Otherwise, the larger of the weighted average and the median is used as the Fisher information threshold for the modulation order corresponding to that sub-sequence. In the online communication phase, a training sequence is transmitted between the transmitter and receiver of the actual underwater wireless optical communication system. This training sequence includes multiple sub-sequences with different pulse widths. The Fisher information content of the training sequence is calculated. Then, the Fisher information content of the training sequence is compared with the Fisher information content threshold of the modulation order corresponding to each sub-sequence. The modulation order of the sub-sequence corresponding to the Fisher information content threshold that is closest to the Fisher information content of the training sequence is selected as the optimal modulation order for the transmitter and receiver of the underwater wireless optical communication system.

[0007] In the above scheme, the pulse interval between every two subsequences of the training sequence is greater than the duration of the impulse response of the underwater scattering channel.

[0008] The specific process for calculating the Fisher information content of each subsequence during the offline calibration stage described above is as follows:

[0009] The transmitting end sends training sequences through an underwater wireless optical communication link; the receiving end collects the training sequences transmitted through the underwater wireless optical communication link, and obtains the average pulse waveform, pulse amplitude sequence and pulse noise-free sampling segment after aligning each sub-sequence with a fixed time shift.

[0010] The total energy of the received pulse is estimated based on the average pulse waveform, the turbulence scintillation index is estimated based on the pulse amplitude sequence, the additive noise variance is estimated based on the pulse-free noise sampling segment, and the Fisher information content of each subsequence is calculated accordingly.

[0011] ,

[0012] In the formula, Let the Fisher information content of the k-th subsequence be . Let be the total energy of the received pulses in the k-th subsequence. Let be the turbulent scintillation index of the k-th subsequence. Let be the additive noise variance of the k-th subsequence.

[0013] During the online communication phase described above, the specific process for calculating the Fisher information content of the training sequence is as follows:

[0014] The transmitting end sends training sequences through an underwater wireless optical communication link; the receiving end collects the training sequences transmitted through the underwater wireless optical communication link, and obtains the average pulse waveform, pulse amplitude sequence and pulse noise-free sampling segment after aligning each sub-sequence with a fixed time shift.

[0015] The total energy of the received pulse is estimated based on the average pulse waveform, the turbulence scintillation index is estimated based on the pulse amplitude sequence, the additive noise variance is estimated based on the pulse-free noise sampling segment, and the Fisher information content of each subsequence is calculated accordingly.

[0016] ,

[0017] In the formula, Let the Fisher information content of the k-th subsequence be . Let be the total energy of the received pulses in the k-th subsequence. Let be the turbulent scintillation index of the k-th subsequence. Let V be the additive noise variance of the k-th subsequence;

[0018] Normalized weights are constructed based on the pulse widths corresponding to the subsequences, and the Fisher information is weighted and summed based on the normalized weights of the subsequences to obtain the Fisher information of the training sequence.

[0019] Compared with the prior art, the present invention has the following characteristics:

[0020] 1. No need to wait for error event statistics in real time: The receiver can obtain channel quality estimation through short pulse training sequences, which reduces the sample overhead and feedback delay of the BER feedback mechanism under high signal-to-noise ratio conditions.

[0021] 2. It can explicitly reflect the effects of underwater turbulence: The turbulence scintillation index is introduced into Fisher information, so that the channel quality scale is not only affected by received energy and noise variance, but also reflects the light intensity fluctuations caused by multiplicative turbulence.

[0022] 3. Wider effective dynamic range: Fisher information is not limited by the upper and lower bounds of 0 and 0.5 of BER, and can maintain continuous response at both high and low signal-to-noise ratios, which is beneficial for adaptive modulation systems to distinguish more channel states.

[0023] 4. Consideration of different PPM modulation orders: Through multi-pulse width training and weighted summation, the comprehensive index achieves a compromise between optimistic estimation of wide pulses and pessimistic estimation of narrow pulses, reducing the risk of incorrectly selecting too high or too low modulation orders.

[0024] 5. Facilitates engineering deployment: The required parameters can be directly estimated from the training sequence at the receiver. The method can be embedded into existing underwater wireless optical communication adaptive modulation links as a unified channel quality benchmark and a basis for selecting modulation order. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of an adaptive modulation method for underwater wireless optical communication based on weighted Fisher information.

[0026] Figure 2 This is a graph showing the mapping relationship between Fisher information content and the bit error rate of each modulation order in PPM.

[0027] Figure 3 This is a graph showing the relationship between Fisher information threshold and each modulation order of PPM. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific examples.

[0029] This invention proposes an adaptive modulation method for underwater wireless optical communication based on weighted Fisher information, such as... Figure 1 As shown, it includes an offline calibration phase and an online communication phase.

[0030] (1) Offline calibration stage:

[0031] First, by transmitting training sequences between the transmitter and receiver of a simulated underwater wireless optical communication system, the Fisher information of each subsequence of the training sequence is calculated. This simulated underwater wireless optical communication system can be an actual, offline-calibrated simulation built using simulation software, or an offline-calibrated simulation built using simulation software.

[0032] Then, the above process is repeated to obtain the Fisher information of each subsequence of multiple training sequences. For example, in this case, by sending 50 training sequences, the Fisher information of each subsequence under the 50 training sequences is obtained.

[0033] Finally, calculate the weighted average (e.g., the weighted average calculated by the Gaussian kernel weighted average method) and the median of the Fisher information of the same subsequence in different training sequences: if the difference between the weighted average and the median does not exceed a set proportion (e.g., 10%), then the weighted average is used as the Fisher information threshold for the modulation order corresponding to the subsequence; otherwise, the larger of the weighted average and the median is used as the Fisher information threshold for the modulation order corresponding to the subsequence.

[0034] Let the set of PPM modulation orders supported by the system be { ,…, }, the Fisher threshold for each modulation order under the target reliability constraint is obtained through offline calibration as { ,…, Specifically, for each PPM order M, the points selected from all samples are used to calculate the weighted average of their Fisher information content using the Gaussian kernel weighted average method, and the median is calculated simultaneously. If the difference between the two is no more than 10%, the weighted average is taken as the Fisher information content threshold for that order; if the difference is significant, the higher of the weighted average and the median is taken as the Fisher information content threshold for that order to ensure reliability. In actual communication, the receiver calculates the Fisher information content under the current channel state... And select the highest modulation order that satisfies the threshold constraint:

[0035] ,

[0036] in, This is the recommended PPM modulation order for the current channel conditions. If... If the value is below the lowest modulation threshold, the system can reduce the coding rate, extend the training cycle, increase the transmit drive current, or enter link hold mode; if If the modulation order is higher than the higher-order modulation threshold, the system can increase the modulation order to improve spectral efficiency.

[0037] During the offline calibration phase of the system, a mapping relationship between Fisher information content and the bit error rate of each modulation order of PPM is established, and the Fisher information content threshold required for each modulation order of PPM to meet the preset reliability requirements is obtained according to the above threshold algorithm. Taking moderate underwater channel conditions as an example: the near-end detector distance is 2m, the receiver distance is 15m (medium to long distance), and the chlorophyll concentration... The turbulence intensity is moderate. The symbol period is fixed in the simulation. Received signal-to-noise ratio Step from arrive At each SNR point, the Fisher information threshold for each subsequence (e.g., 2-PPM, 4-PPM, 8-PPM, 16-PPM, and 32-PPM) is calculated using the method described above. Fifty Monte Carlo experiments are performed on each set of parameters, and the average is taken to ensure statistical accuracy. Figure 2 This diagram illustrates the mapping relationship between Fisher information content and the bit error rate of each modulation order in the PPM. Figure 3 The graph shows the relationship between Fisher information threshold and each modulation order of PPM.

[0038] (2) Online communication stage:

[0039] First, the Fisher information content of the training sequence is calculated by sending training sequences between the transmitter and receiver of an actual underwater wireless optical communication system.

[0040] Then, the Fisher information content of the training sequence is compared with the Fisher information content threshold of the modulation order corresponding to each subsequence, and the modulation order of the subsequence corresponding to the Fisher information content threshold that is closest to the Fisher information content of the training sequence is selected as the optimal modulation order of the transmitter and receiver of the underwater wireless optical communication, which is used to adjust the modulation parameters of subsequent data transmission.

[0041] In the specific communication process, the receiving end will Alternatively, the corresponding modulation parameters can be sent to the transmitter via a feedback link, and the transmitter can adjust the PPM modulation order based on the feedback results. Since this method is based on training sequences and Fisher information and does not rely on real-time BER statistics, it has a shorter feedback link and better dynamic channel tracking capabilities.

[0042] Considering that Fisher information can characterize the amount of information contained in the observed signal regarding the transmitted symbol to be estimated, it can theoretically reflect the influence of factors such as signal energy, noise intensity, and turbulence flicker on the decision capability. This invention aims to introduce Fisher information into UWOC channel quality assessment to reduce reliance on bit error statistics and improve the sensitivity of channel state feedback. The calculation process of Fisher information is as follows:

[0043] 1) Send the training sequence.

[0044] Because the Fisher information obtained from a single pulse width training sequence is difficult to adapt to different PPM modulation orders simultaneously. For higher-order PPMs, the pulses are narrower and more susceptible to scattering broadening, while for lower-order PPMs, the pulses are wider and more resistant to distortion. If only a certain pulse width is used to estimate channel quality, it is easy to produce overly optimistic or overly conservative modulation order selections. Therefore, this invention uses multi-pulse width short pulse training sequences to achieve a unified channel quality scale and adaptive modulation method that takes into account the differences in modulation orders of different PPMs.

[0045] Before or during normal data communication, the transmitter periodically inserts training sequences into the underwater wireless optical communication link, sending multi-pulse-width short pulse training sequences. The training sequences consist of... It consists of several subsequences, each subsequence corresponding to a pulse width (modulation order), the first... Each subsequence uses pulse width , To avoid interference between scattering wakes of adjacent training pulses, the pulse interval between every two subsequences is... satisfy: > ;in, This indicates the duration of the impulse response of the underwater scattering channel.

[0046] In practical communication systems, pulse widths vary significantly depending on the PPM modulation order: higher order modulation results in narrower time slots and smaller pulse widths. Narrow pulses are more sensitive to inter-symbol interference caused by scattering. Therefore, in this embodiment, each subsequence uses a pulse width... It covers the equivalent time slot width corresponding to 2-PPM, 4-PPM, 8-PPM, 16-PPM, 32-PPM or other target modulation orders.

[0047] 2) Establish a composite underwater wireless optical channel model.

[0048] The receiver acquires the training sequence transmitted via the underwater wireless optical communication link, and after aligning each subsequence with a fixed time shift, obtains the average pulse waveform, pulse amplitude sequence, and pulse-free sampling segment.

[0049] Let the first The nth subsequence has a total of N pulses. For the nth... Each subsequence, after being aligned with a fixed time shift according to the launch start time:

[0050] Each pulse extracts L sampling points, and the m-th sampling value of the i-th pulse is... The average pulse waveform is then:

[0051] ,

[0052] In the formula, Number the subsequences. The number of subsequences in the training sequence; For the first Pulse numbering in each subsequence The number of pulses for each subsequence; The sampling point number within a single pulse sampling window. The number of sampling points in the sampling window.

[0053] Within the same sampling window of each pulse, the peak value representing the pulse amplitude is extracted to obtain the pulse amplitude sequence. ,in .

[0054] A pulse-free region containing no valid pulses and scattering wakes is selected between adjacent training pulses, and noise sampling points are extracted from the pulse-free region. , , The number of sampling points forms the first... Each subsequence corresponds to a pulse-free noise sampling segment, which can be used to estimate the variance of additive noise at the receiver.

[0055] 3) Calculate the Fisher information content of each subsequence.

[0056] First, estimate the total energy of the received pulse, the turbulent scintillation index, and the variance of the additive noise.

[0057] The total energy of the received pulses is estimated based on the average pulse waveform. Therefore, the total energy of the received pulses corresponding to the k-th subsequence is... :

[0058] ,

[0059] To estimate the turbulent scintillation index based on the pulse amplitude sequence, let the amplitude of the i-th pulse in the k-th subsequence be... Its mean is The turbulent scintillation index It can be estimated as follows:

[0060] ,

[0061] Based on the estimation of the additive noise variance from the pulse-free noise sampling segment, noise sampling points are extracted using the pulse-free region within the pulse interval. Let the noise sampling points be... The noise is The mean is Then the additive noise variance The estimate is:

[0062] ,

[0063] Therefore, the receiver does not need to know the complete underwater channel model in advance; it can obtain the three core parameters required for Fisher information calculation simply by using the training sequence.

[0064] Then, the total energy of the received pulse, the turbulent scintillation index, and the additive noise variance are substituted into the Fisher information estimation formula to obtain the Fisher information of each subsequence.

[0065] Fisher information content measures the amount of information contained in observed data X about the unknown parameter θ. Its basic definition is:

[0066] ,

[0067] The variance of the unbiased estimator satisfies the Cramer-Rao lower bound:

[0068] ,

[0069] In the UWOC system, the transmitted symbol or transmitted pulse amplitude is regarded as the parameter to be estimated, and the received pulse waveform is regarded as the observation data.

[0070] For the k-th subsequence, considering the equivalent pulse energy after scattering, the multiplicative fluctuations of turbulence, and the variance of additive noise, its Fisher information content can be estimated as follows:

[0071] ,

[0072] This expression shows that Fisher information is affected by the received pulse energy, noise intensity, and turbulence flicker, and can be used as a comprehensive quality benchmark for underwater composite channels.

[0073] 4) Calculate the Fisher information content of the training sequence.

[0074] Since different PPM modulation orders correspond to different pulse widths, the Fisher information obtained from a single pulse width cannot fully represent the actual link availability under all modulation orders. In order to ensure that the comprehensive Fisher information can reasonably reflect the actual availability of each modulation order, this invention constructs normalized weights based on the pulse widths corresponding to the subsequences, so that the contribution of low-order modulation corresponding to wide pulses is larger, and the contribution of high-order modulation corresponding to narrow pulses is smaller.

[0075] Let normalized weights With equivalent PPM modulation order If they are inversely proportional, then the normalized weight of the k-th subsequence is... Defined as:

[0076] ,

[0077] In the formula, This represents the pulse width corresponding to the k-th subsequence.

[0078] Weight design makes A conservative compromise is formed between wide-pulse optimistic estimation and narrow-pulse pessimistic estimation, suitable for underwater wireless optical channels with strong scattering and significant differences in the degree of inter-symbol interference affecting different PPM orders. The weighting relationships for different PPM modulation orders are shown in Table 1 below:

[0079]

[0080] Table 1

[0081] Ultimately, the Fisher information content of the training sequence Represented as:

[0082] .

[0083] This invention enables rapid estimation of channel quality in complex underwater wireless optical channels, explicitly reflects the effects of turbulence, and provides a unified channel quality scale and adaptive modulation method that takes into account differences in PPM modulation orders. The method is applied to an underwater wireless optical communication experimental link with both static water and artificial turbulence disturbances. Experiments show that the Fisher information maintains good linearity across the entire driving current range; the BER approaches 0.5 in the low SNR region and approaches 0 in the high SNR region, exhibiting effective interval compression. With the introduction of turbulence, the scintillation exponent in the Fisher information reflects physical channel fluctuations, while the sensitivity and sample stability of the BER decrease significantly. The comprehensive Fisher information obtained from multi-pulse width training monotonically increases with improving channel quality and can serve as a shared channel quality scale for different PPM orders. Underwater channel states are obtained through short-pulse training sequences, a unified channel quality scale is constructed using the Fisher information, and the PPM modulation order is selected accordingly.

[0084] In summary, this invention discloses an adaptive modulation method for underwater wireless optical communication based on weighted Fisher information. In the offline calibration phase, the transmitter periodically sends multiple sets of short pulse training sequences with different pulse widths. The receiver processes the training sequences and calculates the Fisher information of each sub-sequence, thereby obtaining the Fisher information threshold for the modulation order corresponding to each sub-sequence. In the online communication phase, the transmitter periodically sends multiple sets of short pulse training sequences with different pulse widths. The receiver processes the training sequences and calculates the Fisher information of each sub-sequence, thereby obtaining the Fisher information of the training sequence. The Fisher information of the training sequence is then compared with the Fisher information threshold for the modulation order corresponding to each sub-sequence, and the PPM modulation order that meets the link reliability requirements is selected and fed back to the transmitter. This method does not require real-time statistics of bit error events, can explicitly reflect the multiplicative fluctuations caused by underwater turbulence, and takes into account the sensitivity differences of different PPM modulation orders to scattering broadening. It can improve the channel quality perception capability, real-time feedback, and link stability of the underwater wireless optical communication adaptive modulation system.

[0085] It should be noted that although the embodiments described above are illustrative, they are not intended to limit the invention. Therefore, the invention is not limited to the specific embodiments described above. Any other embodiments obtained by those skilled in the art under the guidance of this invention without departing from its principles are considered to be within the protection scope of this invention.

Claims

1. An adaptive modulation method for underwater wireless optical communication based on weighted Fisher information, characterized in that... It includes an offline calibration phase and an online communication phase; In the offline calibration phase, a training sequence is sent between the transmitter and receiver of a simulated underwater wireless optical communication system. This training sequence includes multiple sub-sequences with different pulse widths, and the Fisher information content of each sub-sequence of the training sequence is calculated. Repeat the above process to obtain the Fisher information of each subsequence of multiple training sequences, and calculate the weighted average and median value of the Fisher information of the same subsequence of different training sequences: if the difference between the weighted average and the median value does not exceed a set ratio, the weighted average value is used as the Fisher information threshold of the modulation order corresponding to the subsequence; otherwise, the larger value between the weighted average and the median value is used as the Fisher information threshold of the modulation order corresponding to the subsequence. In the online communication phase, a training sequence is transmitted between the transmitter and receiver of the actual underwater wireless optical communication system. This training sequence includes multiple sub-sequences with different pulse widths. The Fisher information content of the training sequence is calculated. Then, the Fisher information content of the training sequence is compared with the Fisher information content threshold of the modulation order corresponding to each sub-sequence. The modulation order of the sub-sequence corresponding to the Fisher information content threshold that is closest to the Fisher information content of the training sequence is selected as the optimal modulation order for the transmitter and receiver of the underwater wireless optical communication system.

2. The underwater wireless optical communication adaptive modulation method based on weighted Fisher information as described in claim 1, characterized in that, The pulse interval between any two subsequences of the training sequence is greater than the duration of the impulse response of the underwater scattering channel.

3. The underwater wireless optical communication adaptive modulation method based on weighted Fisher information according to claim 1, characterized in that, The specific process for calculating the Fisher information content of each subsequence during the offline calibration stage is as follows: The transmitting end sends training sequences through an underwater wireless optical communication link; the receiving end collects the training sequences transmitted through the underwater wireless optical communication link, and obtains the average pulse waveform, pulse amplitude sequence and pulse noise-free sampling segment after aligning each sub-sequence with a fixed time shift. The total energy of the received pulse is estimated based on the average pulse waveform, the turbulence scintillation index is estimated based on the pulse amplitude sequence, the additive noise variance is estimated based on the pulse-free noise sampling segment, and the Fisher information content of each subsequence is calculated accordingly. ， In the formula, Let the Fisher information content of the k-th subsequence be . Let be the total energy of the received pulses in the k-th subsequence. Let be the turbulent scintillation index of the k-th subsequence. Let be the additive noise variance of the k-th subsequence.

4. The underwater wireless optical communication adaptive modulation method based on weighted Fisher information according to claim 1, characterized in that, During the online communication phase, the specific process for calculating the Fisher information content of the training sequence is as follows: The transmitting end sends training sequences through an underwater wireless optical communication link; the receiving end collects the training sequences transmitted through the underwater wireless optical communication link, and obtains the average pulse waveform, pulse amplitude sequence and pulse noise-free sampling segment after aligning each sub-sequence with a fixed time shift. The total energy of the received pulse is estimated based on the average pulse waveform, the turbulence scintillation index is estimated based on the pulse amplitude sequence, the additive noise variance is estimated based on the pulse-free noise sampling segment, and the Fisher information content of each subsequence is calculated accordingly. ， In the formula, Let the Fisher information content of the k-th subsequence be . Let be the total energy of the received pulses in the k-th subsequence. Let be the turbulent scintillation index of the k-th subsequence. Let V be the additive noise variance of the k-th subsequence; Normalized weights are constructed based on the pulse widths corresponding to the subsequences, and the Fisher information is weighted and summed based on the normalized weights of the subsequences to obtain the Fisher information of the training sequence.

5. The underwater wireless optical communication adaptive modulation method based on weighted Fisher information according to claim 3 or 4, characterized in that, Total energy of received pulses in the k-th subsequence for: ， The turbulent scintillation index of the k-th subsequence for: ， The additive noise variance of the k-th subsequence for: ， In the formula, The average pulse waveform of the k-th subsequence. This represents the number of pulse sampling points; Let be the amplitude of the i-th pulse in the k-th subsequence. Let N be the mean amplitude of the k-th subsequence, and N be the number of pulses in the subsequence. For the k-th subsequence Noise at each sampling point Let be the noise mean of the k-th subsequence. This represents the number of noise sampling points.

6. The underwater wireless optical communication adaptive modulation method based on weighted Fisher information according to claim 4, characterized in that, Normalized weights of the k-th subsequence for: ， In the formula, The first The pulse width corresponding to each subsequence This represents the number of subsequences in the training sequence.

7. In the underwater wireless optical communication adaptive modulation method based on weighted Fisher information as described in claim 1, the weighted average value of Fisher information of the same subsequence of different training sequences is calculated using the Gaussian kernel weighted average method.

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