WO2024067178A1 - 基于蒙特卡罗极化码的译码级联迭代的水声通信*** - Google Patents

基于蒙特卡罗极化码的译码级联迭代的水声通信*** Download PDF

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WO2024067178A1
WO2024067178A1 PCT/CN2023/119224 CN2023119224W WO2024067178A1 WO 2024067178 A1 WO2024067178 A1 WO 2024067178A1 CN 2023119224 W CN2023119224 W CN 2023119224W WO 2024067178 A1 WO2024067178 A1 WO 2024067178A1
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channel
monte carlo
signal
polarization code
channel estimation
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PCT/CN2023/119224
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French (fr)
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吴金秋
齐晓飞
陈柔池
左大鸿
张文博
周佳琼
赵庆超
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鹏城实验室
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0057—Block codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B13/00—Transmission systems characterised by the medium used for transmission, not provided for in groups H04B3/00 - H04B11/00
    • H04B13/02—Transmission systems in which the medium consists of the earth or a large mass of water thereon, e.g. earth telegraphy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector
    • H04L1/203—Details of error rate determination, e.g. BER, FER or WER
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/24—Testing correct operation
    • H04L1/245—Testing correct operation by using the properties of transmission codes
    • H04L1/246—Testing correct operation by using the properties of transmission codes two-level transmission codes, e.g. binary
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03878—Line equalisers; line build-out devices
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2626—Arrangements specific to the transmitter only
    • H04L27/2627—Modulators
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2689—Link with other circuits, i.e. special connections between synchronisation arrangements and other circuits for achieving synchronisation
    • H04L27/2695—Link with other circuits, i.e. special connections between synchronisation arrangements and other circuits for achieving synchronisation with channel estimation, e.g. determination of delay spread, derivative or peak tracking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/03433—Arrangements for removing intersymbol interference characterised by equaliser structure
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present application relates to the technical field of underwater acoustic communication, and in particular to an underwater acoustic communication system based on a decoding cascade iteration of Monte Carlo polarization codes.
  • Polar codes constructed by existing methods may not achieve sufficient performance in underwater acoustic communications due to the great differences between underwater acoustic channels and B-DMC channels, Gaussian channels, etc. Therefore, it is of great significance to construct Polar codes with excellent performance according to the characteristics of underwater acoustic channels and in combination with specific communication methods.
  • the technical problem to be solved by the present application is that, in view of the above-mentioned defects of the related art, an underwater acoustic communication system with decoding cascade iteration based on Monte Carlo polarization code is provided, aiming to solve the problem that the Polar code constructed by the existing method in the related art may not obtain sufficient performance in underwater acoustic communication.
  • an embodiment of the present application provides an underwater acoustic communication system based on a decoding cascade iteration of a Monte Carlo polarization code, wherein the system comprises:
  • a transmitting end device is used to perform Monte Carlo polarization code encoding and modulation processing on the initial sequence to obtain an OFDM signal, and transmit a sound wave containing the OFDM signal; wherein the Monte Carlo polarization code is constructed based on the Monte Carlo method and channel estimation;
  • a receiving end device is used to receive a sound wave containing noise in an underwater acoustic channel, and perform analog-to-digital conversion, hybrid channel estimation, equalization, demodulation and Monte Carlo polarization code decoding on the sound wave containing noise to obtain a decoding sequence; wherein the Monte Carlo polarization code decoder in the receiving end device is cascaded with the hybrid channel estimation module and the equalizer.
  • the transmitting end device includes:
  • a Monte Carlo polarization code encoder is used to encode an initial sequence using a polarization code constructed by a Monte Carlo method to obtain a coded signal;
  • a first channel modulator used for performing QPSK modulation on the coded signal
  • OFDM modulator used for performing OFDM modulation on the QPSK modulated signal
  • a digital-to-analog converter used to convert digital signals into analog signals
  • the transmitting transducer is used to transmit sound waves in the underwater acoustic channel.
  • the receiving end device includes:
  • a receiving transducer used for receiving sound waves in an underwater acoustic channel
  • Analog-to-digital converter used to convert analog signals into digital signals
  • a hybrid channel estimation module used to perform channel estimation by fusing a channel estimation method based on a pilot signal with a channel estimation method processed between blocks; wherein the channel estimation method processed between blocks is to perform decoding of a current OFDM block based on a channel estimation result of a previous OFDM block;
  • a channel equalizer used to compensate for the characteristics of the channel
  • An OFDM demodulator used for performing OFDM demodulation on the QPSK demodulated signal
  • a channel demodulator used for performing QPSK demodulation on the signal output by the channel equalizer
  • a Monte Carlo polarization code decoder is used to decode the signal output by the OFDM demodulator
  • a polar code encoder used for re-encoding the signal decoded by the Monte Carlo polar code decoder
  • a second channel modulator used for performing QPSK modulation on the signal encoded by the polar code encoder
  • the channel estimation module of the inter-block processing is used to decode the current OFDM block according to the channel estimation result of the previous OFDM block.
  • the Monte Carlo polar code decoder is cascaded with a hybrid channel estimation module and an equalizer to form a loop iteration.
  • an embodiment of the present application further provides a signal processing method for an underwater acoustic communication system based on a decoding cascade iteration of a Monte Carlo polarization code, wherein the polarization code constructed by the Monte Carlo method is used to encode the initial sequence, and the coded signal obtained includes:
  • the Monte Carlo polar code construction result is used to encode the initial sequence to obtain the encoded signal.
  • constructing a Monte Carlo polar code based on channel state information and the Monte Carlo method includes:
  • the binary random sequence is polarization-coded and channel-modulated, and then input into the underwater acoustic channel corresponding to the channel state information;
  • constructing a Monte Carlo polar code according to a bit error rate of each sub-channel includes:
  • the sub-channels corresponding to the top K bit error rates are used as information bit sets
  • the information bit set is taken as the construction result of Monte Carlo polar code.
  • the performing channel estimation after fusing the channel estimation method based on the pilot signal with the channel estimation method based on the inter-block processing includes:
  • a first channel transfer function corresponding to a current OFDM symbol and a second channel transfer function corresponding to a previous OFDM symbol are merged to obtain a mixed channel transfer function.
  • obtaining a second channel transfer function corresponding to a previous OFDM symbol according to a decoded signal corresponding to a previous OFDM symbol includes:
  • the decoded signal corresponding to the previous OFDM symbol is subjected to polarization code re-encoding and channel modulation to obtain a modulated signal;
  • the channel is estimated according to the modulated signal and the preprocessed signal to obtain a second channel transfer function.
  • the initial sequence is encoded and modulated using Monte Carlo polarization codes, and the following steps are performed:
  • the initial sequence after Monte Carlo polarization code encoding and modulation processing is subjected to symbol mapping, serial-to-parallel conversion, subcarrier allocation, pilot insertion, inverse fast Fourier transform, cyclic prefix addition processing and parallel-to-serial conversion.
  • performing analog-to-digital conversion, hybrid channel estimation, equalization, demodulation, and Monte Carlo polarization code decoding on a sound wave containing noise includes:
  • the sound wave containing noise is subjected to analog-to-digital conversion, serial-to-parallel conversion, cyclic prefix removal, fast Fourier transform, hybrid channel estimation, equalization, pilot removal, parallel-to-serial conversion, demodulation and Monte Carlo polarization code decoding to obtain a decoding sequence.
  • an embodiment of the present application also provides an intelligent terminal, comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, wherein the one or more programs include a signal processing method for an underwater acoustic communication system based on a decoding cascade iteration of a Monte Carlo polarization code as described in any one of the above.
  • the embodiments of the present application further provide a non-transitory computer-readable storage medium,
  • the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the signal processing method for an underwater acoustic communication system based on the Monte Carlo polarization code decoding cascade iteration as described in any one of the above.
  • the embodiment of the present application discloses an underwater acoustic communication system based on Monte Carlo polarization code decoding cascade iteration, the system comprising: a transmitting end device, used to perform Monte Carlo polarization code encoding and modulation processing on an initial sequence to obtain an OFDM signal, and transmit a sound wave containing the OFDM signal; wherein the Monte Carlo polarization code is constructed based on the Monte Carlo method and channel estimation; a receiving end device, used to receive a sound wave containing noise in an underwater acoustic channel, and perform analog-to-digital conversion, hybrid channel estimation, equalization, demodulation and Monte Carlo polarization code decoding on the sound wave containing noise to obtain a decoded sequence; wherein the Monte Carlo polarization code decoder in the receiving end device is cascaded with a hybrid channel estimation module and an equalizer.
  • the Monte Carlo method and channel estimation are used to construct the polarization code in the transmitting device, and the Monte Carlo polarization code decoding can be constructed in different shallow water acoustic channels.
  • the hybrid channel estimation is used in the receiving device to improve the accuracy of the channel estimation.
  • the hybrid channel estimation module, the equalizer and the Monte Carlo polarization code decoder are cascaded to form a cyclic iterative operation to improve the performance of the entire communication system.
  • FIG1 is a schematic diagram of an underwater acoustic communication system based on a Monte Carlo polarization code decoding cascade iteration according to an embodiment of the present application;
  • FIG2 is a block diagram of the principle of constructing Polar codes using the Monte Carlo method provided in an embodiment of the present application
  • FIG3 is a structural diagram of a transmission sequence provided in an embodiment of the present application.
  • FIG4 is a flowchart of processing an nth OFDM symbol by an inter-block iterative receiver provided in an embodiment of the present application
  • FIG5 is a graph showing the variation of the sub-channel BER with the number of cycles provided in an embodiment of the present application.
  • FIG6 is a diagram showing the transformation of the error bit d with the number of cycles provided in an embodiment of the present application.
  • FIG7 is a distribution diagram of normalized decision factors of the Monte Carlo construction method when the code length is 512 provided in an embodiment of the present application;
  • FIG8 is a normalized decision factor distribution diagram of the Monte Carlo construction method when the code length is 2048 provided in an embodiment of the present application;
  • FIG. 9 is a block diagram of the internal structure of the smart terminal provided in an embodiment of the present application.
  • the present application discloses an underwater acoustic communication system based on Monte Carlo polarization code decoding cascade iteration.
  • the present application is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
  • the constructed Polar code may not achieve sufficient performance in underwater acoustic communication.
  • the disadvantages of the related technology are: (1) The existing Polar code technology is not suitable for complex underwater acoustic channel conditions. (2) The existing Polar code technology does not improve the polarization code construction scheme for underwater acoustic channels at the system transmitter; (3) The existing Polar code technology is not well integrated with the channel at the system receiver.
  • this embodiment provides an underwater acoustic communication system based on the decoding cascade iteration of Monte Carlo polarization code.
  • the Monte Carlo polarization code decoding can be constructed in different shallow water acoustic channels.
  • the receiving end device adopts the hybrid channel estimation to improve the accuracy of the channel estimation.
  • the hybrid channel estimation module, the equalizer and the Monte Carlo polarization code decoder are cascaded to form a cyclic iterative operation, thereby improving the performance of the entire communication system and reducing the system bit error rate.
  • the specific system includes: a transmitting end device, which is used to perform Monte Carlo polarization code encoding and modulation processing on the initial sequence to obtain an OFDM signal, and transmit a sound wave containing the OFDM signal; wherein the Monte Carlo polarization code is constructed based on the Monte Carlo method and channel estimation; a receiving end device, which is used to receive a sound wave containing noise in the underwater acoustic channel, and perform analog-to-digital conversion, hybrid channel estimation, equalization, demodulation and Monte Carlo polarization code decoding on the sound wave containing noise to obtain a decoding sequence; wherein the Monte Carlo polarization code decoder in the receiving end device is cascaded with the hybrid channel estimation module and the equalizer.
  • an embodiment of the present application provides an underwater acoustic communication system based on a Monte Carlo polarization code decoding cascade iteration, the system comprising: a transmitting end device, for performing Monte Carlo polarization code encoding and modulation processing on an initial sequence to obtain an OFDM signal, and transmitting an acoustic signal containing the OFDM signal; wave; wherein the Monte Carlo polarization code is constructed based on the Monte Carlo method and channel estimation; a receiving end device is used to receive a sound wave containing noise in an underwater acoustic channel, and perform analog-to-digital conversion, hybrid channel estimation, equalization, demodulation and Monte Carlo polarization code decoding on the sound wave containing noise to obtain a decoding sequence; wherein the Monte Carlo polarization code decoder in the receiving end device is cascaded with the hybrid channel estimation module and the equalizer.
  • the system uses the Monte Carlo method and channel estimation to construct polarization codes (Polar codes) in the transmitting device.
  • polarization codes Polar codes
  • the method is applied to the screening of polarization channels, and the error probability of different polarization sub-channels can be obtained.
  • the specific characteristics of the underwater acoustic channel are fully utilized to improve the construction of polarization codes.
  • the initial sequence is encoded with Monte Carlo polarization codes and then channel modulated and OFDM modulated to obtain an OFDM signal.
  • the principle of OFDM is to convert binary data streams into serial-to-parallel and distribute them to several mutually orthogonal sub-channels for transmission. Since the communication is carried out underwater, the transmitting device transmits processed sound waves containing OFDM signals.
  • the traditional receiving device uses pilot-based channel estimation, and the channel estimation accuracy is low.
  • the system uses hybrid channel estimation in the receiving device, which is an improvement on the existing pilot-based channel estimation and can achieve more accurate channel estimation.
  • the Monte Carlo polarization code decoder is cascaded with the hybrid channel estimation module and the equalizer to iterate, and the sequence obtained by the receiving end after decoding is used for the channel estimation of the next OFDM symbol, which effectively realizes the application of polarization code in complex underwater acoustic channels and improves the performance of the entire communication system.
  • the analog-to-digital conversion, equalization, and demodulation in the receiving device all use related technologies.
  • Monte Carlo polarization code decoding is the inverse process of Monte Carlo polarization code encoding.
  • the transmitting end device includes: a Monte Carlo polarization code encoder, which is used to encode an initial sequence using a polarization code constructed by the Monte Carlo method to obtain a coded signal; a first channel modulator, which is used to perform QPSK modulation on the coded signal; an OFDM modulator, which is used to perform OFDM modulation on the QPSK modulated signal; a digital-to-analog converter, which is used to convert a digital signal into an analog signal; and a transmitting transducer, which is used to transmit sound waves in an underwater acoustic channel.
  • a Monte Carlo polarization code encoder which is used to encode an initial sequence using a polarization code constructed by the Monte Carlo method to obtain a coded signal
  • a first channel modulator which is used to perform QPSK modulation on the coded signal
  • an OFDM modulator which is used to perform OFDM modulation on the QPSK modulated signal
  • a digital-to-analog converter which is used to convert
  • the transmitting end device includes a Monte Carlo polarization code encoder, a first channel modulator, an OFDM modulator, a digital-to-analog converter, and a transmitting transducer.
  • the Monte Carlo polarization code encoder is constructed using a Monte Carlo polarization code.
  • the Monte Carlo polarization method is a method for calculating the probability of occurrence of corresponding events through experiments. After being applied to the screening of polarization channels, the error probability of different polarization sub-channels can be obtained, which makes full use of the characteristics of the underwater acoustic channel and improves the construction of the polarization code.
  • the modulation mode of the first channel modulator includes but is not limited to BPSK, QPSK, QAM, 16PSK and other modulation modes.
  • QPSK modulation is used.
  • the signal needs to be OFDM modulated.
  • the transmitting sequence is shown in FIG3.
  • the OFDM modulated signal is converted into an analog signal after digital-to-analog conversion and transmits sound waves through the transmitting transducer.
  • the receiving end device includes: a receiving transducer for receiving sound waves in an underwater acoustic channel; an analog-to-digital converter for converting analog signals into digital signals; a hybrid channel estimation module for combining a channel estimation method based on a pilot signal with a channel estimation method processed between blocks.
  • the channel estimation method of the inter-block processing is to decode the current OFDM block according to the channel estimation result of the previous OFDM block; a channel equalizer is used to compensate for the characteristics of the channel; an OFDM demodulator is used to perform OFDM demodulation on the signal output by the channel equalizer; a channel demodulator is used to perform QPSK demodulation on the signal after QPSK demodulation; a Monte Carlo polarization code decoder is used to decode the signal output by the OFDM demodulator; a polarization code encoder is used to re-encode the signal decoded by the Monte Carlo polarization code decoder; a second channel modulator is used to perform QPSK modulation on the signal encoded by the polarization code encoder; a channel estimation module for inter-block processing is used to decode the current OFDM block according to the channel estimation result of the previous OFDM block.
  • the receiving end device includes a receiving transducer, an analog-to-digital converter, a hybrid channel estimation module, a channel equalizer, a channel demodulator, an OFDM demodulator, a Monte Carlo polarization code decoder, a polarization code encoder, a second channel modulator and a channel estimation module for inter-block processing.
  • the receiving transducer receives the sound wave containing noise in the underwater acoustic channel, it converts it into a digital signal through analog-to-digital conversion.
  • a hybrid channel estimation module is used to merge the channel estimation method based on the pilot signal with the channel estimation method for inter-block processing.
  • the channel estimation method for inter-block processing is to decode the current OFDM block according to the channel estimation result of the previous OFDM block, this means that the Monte Carlo polarization code decoding of the current OFDM block and the Monte Carlo polarization code decoding of the previous OFDM block are cascaded and iterated, thereby improving the performance of the underwater acoustic OFDM communication system.
  • the channel characteristics will be compensated by the channel equalizer, and then the channel demodulation will be performed by the channel demodulator according to the reverse processing process of the transmitting end.
  • the demodulation method also includes but is not limited to BPSK, QPSK, QAM, 16PSK and other demodulation methods.
  • the system adds a polarization code encoder and a second channel modulator in the receiving end device.
  • the polarization code encoder can be the Monte Carlo polarization code encoder in the embodiment of the present application, or it can be the polarization code encoder in the related art.
  • the signal decoded by the Monte Carlo polar code decoder in the receiving end device is re-encoded by a polar code encoder, and then QPSK modulation is performed by a second channel modulator.
  • the QPSK modulated signal is input into a channel estimation module for inter-block processing.
  • the channel estimation module for inter-block processing performs channel estimation according to the QPSK modulated signal and the preprocessed signal to obtain a second channel transfer function. Assuming that the second channel transfer function is regarded as a channel estimation result of a previous OFDM block, the second channel transfer function can be used for decoding the current OFDM block.
  • the Monte Carlo polar code decoder is cascaded with a hybrid channel estimation module and an equalizer to form a loop iteration.
  • the Monte Carlo polarization code decoder is connected to the channel equalizer, and the channel equalizer is connected to the hybrid channel estimation module.
  • the Monte Carlo polarization code decoder, the channel equalizer, and the hybrid channel estimation module are regarded as a processing module.
  • the output of the processing module is input into the processing module again after passing through the polarization code re-encoding, QPSK modulation, and the channel estimation module for inter-block processing. Therefore, the above process is a one-cycle iterative process.
  • This application proposes a Monte Carlo method to construct polarization codes. Different from the previous polarization code encoding method, this scheme is a method to calculate the probability of occurrence of corresponding events through experiments. By applying it to the screening of polarization channels, the error probability of different polarization sub-channels can be obtained; secondly, this application makes full use of the characteristics of underwater acoustic channels and improves the construction scheme of polarization codes.
  • the channel estimation scheme is improved, and the improved channel estimation scheme facilitates further integration with the polar code decoder.
  • the improved channel estimation scheme is cascaded and iterated with the polarization code decoder to improve the performance of the underwater acoustic OFDM communication system.
  • This embodiment provides a signal processing method for an underwater acoustic communication system based on a decoding cascade iteration of a Monte Carlo polarization code.
  • the method can be applied to an intelligent terminal for underwater acoustic communication.
  • encoding an initial sequence using a polarization code constructed using a Monte Carlo method to obtain a coded signal includes: performing channel estimation based on a pilot signal to obtain channel state information; constructing a Monte Carlo polarization code based on the channel state information and the Monte Carlo method; and encoding the initial sequence using a Monte Carlo polarization code construction result to obtain a coded sequence.
  • the system transmitting end device inputs a training sequence, which is a random number consisting of 0 and 1.
  • the training sequence is modulated by QPSK and then OFDM, and a pilot LFM is added.
  • the pilot can also be in the form of HFM and CW signals and LFM, HFM and CW combinations.
  • digital-to-analog conversion it is transmitted to the underwater acoustic channel through the transmitting transducer, and received by the receiving end device through the receiving transducer.
  • the pilot LFM is removed, OFDM is demodulated, and the receiving sequence is obtained.
  • Channel estimation is performed based on the receiving sequence and the input training sequence to obtain channel state information, that is, the channel transfer function.
  • the Monte Carlo polarization code in the embodiment of the present application is constructed based on the Monte Carlo method of the channel state information.
  • the construction of the Monte Carlo polarization code based on the channel state information and the Monte Carlo method includes the following steps: generating a binary random sequence based on a preset code length and a preset code rate; performing polarization code encoding and channel modulation on the binary random sequence and then inputting the sequence into the underwater acoustic channel corresponding to the channel state information; performing channel demodulation and polarization code decoding on a signal output by the underwater acoustic channel corresponding to the channel state information; repeatedly executing the step of generating the binary random sequence based on the preset code length and the preset code rate M times, and counting the number of errors of each subchannel during the polarization code decoding process; obtaining the bit error rate of each subchannel based on a preset formula according to the number of repetitions M and the number of errors; and constructing the Monte Carlo polarization code
  • Monte Carlo is a method that calculates the probability of occurrence of corresponding events through experiments. By applying it to the screening of polarization channels, the error probability of different polarization sub-channels can be obtained. Assuming that the transmission of polarization code elements in the underwater acoustic channel is a random event ⁇ , then the event A is that the polarization code after SC decoding is different from the initial sequence of the transmitter. When A occurs, ⁇ takes the value of 1, and if A does not occur, ⁇ takes the value of 0. Assuming that the total number of Monte Carlo experiments is M, and the total number of times A occurs is v, the frequency v is a random variable, and the bit error rate (BER) of a single sub-channel can be expressed as:
  • the probability that the above formula is true is 1.
  • the probability obtained by the above model is It is approximately the bit error rate of a single polarization subchannel. Therefore, as long as the state information of the underwater acoustic channel is known, the statistical information of the subchannel bit error rate can be iteratively calculated by the Monte Carlo method.
  • the transmitted signal corresponding to the kth subcarrier of underwater acoustic OFDM is:
  • h i and ⁇ i represent the amplitude and delay corresponding to the i-th path of the underwater acoustic channel respectively.
  • the steps of generating a binary random sequence based on a preset code length and a preset code rate are repeated; polarization code encoding and channel modulation of the binary random sequence are input to the underwater acoustic channel corresponding to the channel state information; the signal output by the underwater acoustic channel corresponding to the channel state information is channel demodulated and polarization code decoded are repeated M times, and the number of errors V of each sub-channel in the polarization code decoding process is counted.
  • the bit error rate BER of each polarization sub-channel can be calculated, and the Monte Carlo polarization code is constructed according to the bit error rate of each sub-channel.
  • the Monte Carlo polar code is constructed according to the bit error rate of each sub-channel, including the following steps: sorting the bit error rates of each sub-channel from small to large; taking the sub-channels corresponding to the top K bit error rates as the information bit set; and taking the information bit set as the construction result of the Monte Carlo polar code.
  • the Monte Carlo method constructs Polar by iteratively accumulating the sub-channel BER values, and selecting the channel with a relatively small BER value as the information transmission channel.
  • the bit error rates of each subchannel are sorted from small to large, and the subchannels corresponding to the top K bit error rates are used as information bit sets, and the remaining subchannels are selected as transmission frozen bit sets.
  • the process of constructing Polar codes by the Monte Carlo method conforms to the law of large numbers, that is, the more operations are performed, the closer the BER estimation value of each subchannel is to the true value, and the performance of the constructed Polar code is also close to that of the ideal Polar code.
  • the information bit set of the ideal Polar code is Aref
  • the information bit set of the Polar code constructed after M cycles is A
  • d crad (Aref) - crad (Aref ⁇ A) represents the number of different elements between set A and set Aref
  • crad (X) represents the number of elements in set X.
  • the information bit set is taken as the construction result of the Monte Carlo polar code, that is, the information bit set is taken as the information transmission channel.
  • the channel estimation result of the LS method is affected by channel noise under low signal-to-noise ratio conditions, and the channel change information cannot be obtained in time by only using the training sequence estimation in the time-varying channel.
  • the received information on all subcarriers of the OFDM receiving end is used for channel estimation, and combined with the LS estimation result of the pilot sequence, the channel change information in the LS estimation result can be supplemented.
  • the present application combines the decoding of polarization codes with OFDM channel estimation and adopts the channel estimation method of inter-block processing, that is, the channel estimation result of the previous OFDM block is used for the decoding of the current OFDM block.
  • the channel estimation method of inter-block processing is combined with the channel estimation method based on pilot signals, and an iterative receiver is set up with the aid of channel decoding estimation values, thereby improving the accuracy of channel estimation and reducing the use of pilot subcarrier systems.
  • the channel estimation after fusing the channel estimation method based on the pilot signal with the channel estimation method of the inter-block processing comprises the following steps: converting the received signal from the time domain to the frequency domain to obtain a preprocessed signal; estimating the channel based on the pilot signal in the preprocessed signal to obtain a first channel transfer function corresponding to the current OFDM symbol; obtaining a decoded signal corresponding to the previous OFDM symbol; and obtaining the decoded signal corresponding to the previous OFDM symbol according to the decoded signal corresponding to the previous OFDM symbol.
  • the first channel transfer function corresponding to the current OFDM symbol and the second channel transfer function corresponding to the previous OFDM symbol are merged to obtain a mixed channel transfer function.
  • the received signal is converted from the time domain to the frequency domain by FFT to obtain a preprocessed signal, which includes a pilot signal.
  • channel estimation is performed based on the pilot signal to obtain a first channel transfer function
  • only Channel equalization and decoding are performed, assuming that the decoding output value of the first OFDM symbol of the group is accurate, and a decoded signal corresponding to the OFDM symbol is obtained;
  • the decoded signal corresponding to the OFDM symbol is subjected to polarization code recoding and channel modulation to obtain a modulated signal; then the channel is estimated according to the modulated signal and the preprocessed signal to obtain a second channel transfer function, that is, in combination with the corresponding sequence of the preprocessing output, the corresponding channel estimation value (second channel transfer function) can be obtained as follows:
  • y m (n-1) represents the n-1th group of OFDM sequences in the mth frame received signal, It represents the output sequence of its corresponding decoded output sequence after re-encoding and QPSK modulation.
  • the first channel transfer function corresponding to the current OFDM symbol and the second channel transfer function corresponding to the previous OFDM symbol are merged to obtain a mixed channel transfer function.
  • the iterative decoding estimate that is, the second channel transfer function
  • the input hybrid estimation module is used for channel estimation of the nth group of OFDM sequences. and the second channel transfer function Perform weighted averaging and define the weight coefficient ⁇ (0,1), then the output of the mixed channel estimation (i.e., the mixed channel transfer function) is:
  • the method includes the following steps after the Monte Carlo polarization code encoding and modulation processing is performed on the initial sequence: performing symbol mapping, serial-to-parallel conversion, subcarrier allocation, pilot insertion, inverse fast Fourier transform, cyclic prefix addition processing and parallel-to-serial conversion on the initial sequence after the Monte Carlo polarization code encoding and modulation processing.
  • symbol mapping serial-to-parallel conversion, subcarrier allocation, pilot insertion, inverse fast Fourier transform, cyclic prefix addition and parallel-to-serial conversion are conventional processing methods of the underwater acoustic OFDM communication system, which will not be repeated here.
  • performing analog-to-digital conversion, hybrid channel estimation, equalization, demodulation, and Monte Carlo polarization code decoding on a sound wave containing noise includes the following steps: performing analog-to-digital conversion, serial-to-parallel conversion, cyclic prefix removal processing, fast Fourier transform, hybrid channel estimation, equalization, pilot removal processing, parallel-to-serial conversion, demodulation, and Monte Carlo polarization code decoding on the sound wave containing noise, The above processing process is related technology and will not be described in detail here.
  • Figure 5 is a graph showing the change of subchannel BER with the number of cycles
  • Figure 6 is a schematic diagram showing the change of error bit d with the number of cycles
  • Figure 7 is a distribution graph of the normalized decision factor of the Monte Carlo construction method when the code length is 512
  • the points in the figure are the decision factors of the Monte Carlo construction method, that is, the distribution of BER. It can be seen from the figure that the decision factors of this construction method all show certain polarization characteristics, and the polarization characteristics of BER distribution are obvious.
  • Figure 8 is a distribution graph of the normalized decision factors of the Monte Carlo construction method when the code length is 2048.
  • the present application also provides an intelligent terminal, whose principle block diagram can be shown in Figure 9.
  • the intelligent terminal includes a processor, a memory, a network interface, a display screen, and a temperature sensor connected through a system bus.
  • the processor of the intelligent terminal is used to provide computing and control capabilities.
  • the memory of the intelligent terminal includes a non-volatile storage medium and an internal memory.
  • the non-volatile storage medium stores an operating system and a computer program.
  • the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium.
  • the network interface of the intelligent terminal is used to communicate with an external terminal through a network connection.
  • FIG. 9 is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the smart terminal to which the scheme of the present application is applied.
  • a specific smart terminal may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.
  • a smart terminal comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, wherein the one or more programs include instructions for performing the following operations:
  • the polar code constructed by Monte Carlo method is used to encode the initial sequence, and the coded signal obtained includes:
  • the initial sequence is encoded using Monte Carlo polarization code to obtain a coded sequence.
  • the constructing a Monte Carlo polarization code based on the channel state information and the Monte Carlo method includes:
  • the binary random sequence is polarization-coded and channel-modulated, and then input into the underwater acoustic channel corresponding to the channel state information;
  • the step of constructing a Monte Carlo polar code according to the bit error rate of each sub-channel includes:
  • the sub-channels corresponding to the top K bit error rates are used as information bit sets
  • the information bit set is taken as the construction result of Monte Carlo polar code.
  • the channel estimation is performed by fusing the channel estimation method based on the pilot signal with the channel estimation method of the inter-block processing, comprising:
  • a first channel transfer function corresponding to a current OFDM symbol and a second channel transfer function corresponding to a previous OFDM symbol are merged to obtain a mixed channel transfer function.
  • the obtaining, according to the decoded signal corresponding to the previous OFDM symbol, a second channel transfer function corresponding to the previous OFDM symbol comprises:
  • the decoded signal corresponding to the previous OFDM symbol is subjected to polarization code re-encoding and channel modulation to obtain a modulated signal;
  • the channel is estimated according to the modulated signal and the preprocessed signal to obtain a second channel transfer function.
  • the initial sequence is encoded and modulated by Monte Carlo polarization code, including:
  • the initial sequence after Monte Carlo polarization code encoding and modulation processing is subjected to symbol mapping, serial-to-parallel conversion, subcarrier allocation, pilot insertion, inverse fast Fourier transform, cyclic prefix addition processing and parallel-to-serial conversion.
  • Analog-to-digital conversion of noisy sound waves, hybrid channel estimation, equalization, demodulation, and Monte Carlo polarimetric decoding include:
  • the sound wave containing noise is subjected to analog-to-digital conversion, serial-to-parallel conversion, cyclic prefix removal, fast Fourier transform, hybrid channel estimation, equalization, pilot removal, parallel-to-serial conversion, demodulation and Monte Carlo polarization code decoding to obtain a decoding sequence.
  • Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory.
  • Volatile memory can include random access memory (RAM) or external cache memory.
  • RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
  • the present application discloses an underwater acoustic communication system based on Monte Carlo polarization code decoding cascade iteration, the system comprising: a transmitting end device, used to perform Monte Carlo polarization code encoding and modulation processing on an initial sequence to obtain an OFDM signal, and transmit a sound wave containing the OFDM signal; wherein the Monte Carlo polarization code is constructed based on the Monte Carlo method and channel state information; a receiving end device, used to receive a sound wave containing noise in an underwater acoustic channel, and perform analog-to-digital conversion, hybrid channel estimation, equalization, demodulation and Monte Carlo polarization code decoding on the sound wave containing noise to obtain a decoded sequence; wherein the Monte Carlo polarization code decoder in the receiving end device is cascaded with a hybrid channel estimation module and an equalizer.
  • the Monte Carlo method and channel estimation are used to construct polarization codes in the transmitting end device, and the Monte Carlo polarization code construction results can be used to construct polarization code decoding in different shallow water acoustic channels.
  • Hybrid channel estimation is used in the receiving end device to improve the accuracy of channel estimation.
  • the hybrid channel estimation module, the equalizer and the Monte Carlo polarization code decoder are cascaded to form a cyclic iterative operation, thereby improving the performance of the entire communication system.
  • the present application discloses a signal processing method for an underwater acoustic communication system based on a decoding cascade iteration of Monte Carlo polarization codes. It should be understood that the application of the present application is not limited to the above examples. For ordinary technicians in this field, it can be improved or transformed according to the above description, and all these improvements and transformations should fall within the scope of protection of the claims attached to the present application.

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Abstract

本申请公开了一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，***包括：发射端装置，用于将初始序列进行蒙特卡罗极化码编码和调制处理，得到OFDM信号并发射；接收端装置，用于在水声信道接收包含噪声的声波，并将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码，得到译码序列；蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联。

Description

基于蒙特卡罗极化码的译码级联迭代的水声通信***
相关申请
本申请要求于2022年9月28日申请的、申请号为202211186944.3的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及水声通信技术领域，尤其涉及的是基于蒙特卡罗极化码的译码级联迭代的水声通信***。
背景技术
虽然水声通信中Polar码的研究取得一定的研究进展，但由于水声信道与B-DMC信道，高斯信道等有很大差别，现有方法构造的Polar码在水声通信中可能无法获得足够的性能，因此，根据水声信道特点，结合具体的通信方式构造性能优异的Polar码有重要意义。
因此，相关技术还有待改进和发展。
发明内容
本申请要解决的技术问题在于，针对相关技术的上述缺陷，提供一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，旨在解决相关技术中现有方法构造的Polar码在水声通信中可能无法获得足够的性能的问题。
本申请解决问题所采用的技术方案如下：
第一方面，本申请实施例提供一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，其中，所述***包括：
发射端装置，用于将初始序列进行蒙特卡罗极化码编码和调制处理，得到OFDM信号，并发射包含OFDM信号的声波；其中，所述蒙特卡罗极化码基于蒙特卡罗法和信道估计构造；
接收端装置，用于在水声信道接收包含噪声的声波，并将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码，得到译码序列；其中，所述接收端装置中的蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联。
在一种实现方式中，所述发射端装置包括：
蒙特卡罗极化码编码器，用于采用蒙特卡罗法构造的极化码对初始序列进行编码，得到编码信号；
第一信道调制器，用于对所述编码信号进行QPSK调制；
OFDM调制器，用于对QPSK调制后的信号进行OFDM调制；
数模转换器，用于将数字信号转换成模拟信号；
发射换能器，用于在水声信道发射声波。
在一种实现方式中，所述接收端装置包括：
接收换能器，用于在水声信道接收声波；
模数转换器，用于将模拟信号转换成数字信号；
混合信道估计模块，用于将基于导频信号的信道估计方式与块间处理的信道估计方式融合后进行信道估计；其中，所述块间处理的信道估计方式为根据前一个OFDM块的信道估计结果来进行当前OFDM块的译码；
信道均衡器，用于对信道的特性进行补偿；
OFDM解调器，用于对QPSK解调后的信号进行OFDM解调；
信道解调器，用于对信道均衡器输出的信号进行QPSK解调；
蒙特卡罗极化码译码器，用于对OFDM解调器输出的信号进行译码；
极化码编码器，用于将所述蒙特卡罗极化码译码器译码后的信号进行重编码；
第二信道调制器，用于将所述极化码编码器编码后的信号进行QPSK调制；
块间处理的信道估计模块，用于根据前一个OFDM块的信道估计结果来进行当前OFDM块的译码。
在一种实现方式中，所述蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联，形成循环迭代。
第二方面，本申请实施例还提供一种基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，其中，采用蒙特卡罗法构造的极化码对初始序列进行编码，得到编码信号包括：
基于导频信号进行信道估计，得到信道状态信息；
基于所述信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码；
采用蒙特卡罗极化码构造结果对初始序列进行编码，得到编码信号。
在一种实现方式中，所述基于信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码包括：
基于预设的码长和预设的码率生成二进制随机序列；
将所述二进制随机序列进行极化码编码和信道调制后输入所述信道状态信息对应的水声信道；
将所述信道状态信息对应的水声信道输出的信号进行信道解调和极化码译码；
重复执行基于预设的码长和预设的码率生成二进制随机序列的步骤M次，统计极化码译码过程中各个子信道的出错个数；
基于预设的公式，根据重复执行次数M和所述出错个数，得到各个子信道的误码率；
根据各个子信道的误码率，构造蒙特卡罗极化码。
在一种实现方式中，所述根据各个子信道的误码率，构造蒙特卡罗极化码包括：
将各个子信道的误码率按照从小到大进行排序；
将排序靠前的K个误码率对应的子信道作为信息位集合；
将信息位集合作为蒙特卡罗极化码的构造结果。
在一种实现方式中，所述将基于导频信号的信道估计方式与块间处理的信道估计方式融合后进行信道估计包括：
将接收信号从时域转换到频域，得到预处理信号；
基于所述预处理信号中的导频信号对信道进行估计，得到当前OFDM符号对应的第一信道传递函数；
获取前一个OFDM符号对应的译码信号；
根据前一个OFDM符号对应的译码信号，得到前一个OFDM符号对应的第二信道传递函数；
将当前OFDM符号对应的第一信道传递函数和前一个OFDM符号对应的第二信道传递函数进行融合，得到混合信道传递函数。
在一种实现方式中，所述根据前一个OFDM符号对应的译码信号，得到前一个OFDM符号对应的第二信道传递函数包括：
将前一个OFDM符号对应的译码信号进行极化码重编码和信道调制，得到调制信号；
根据所述调制信号和所述预处理信号对信道进行估计，得到第二信道传递函数。
在一种实现方式中，将初始序列进行蒙特卡罗极化码编码和调制处理之后包括：
将进行蒙特卡罗极化码编码和调制处理后的初始序列进行符号映射、串并转换、子载波分配、导频***、快速傅里叶逆变换、循环前缀的添加处理和并串转换。
在一种实现方式中，将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码包括：
将包含噪声的声波进行模数转换、串并转换、循环前缀的移除处理、快速傅里叶变换、混合信道估计、均衡、导频的去除处理、并串转换、解调和蒙特卡罗极化码译码，得到译码序列。
第三方面，本申请实施例还提供一种智能终端，包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行所述一个或者一个以上程序包含用于执行如上述任意一项所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法。
第四方面，本申请实施例还提供一种非临时性计算机可读存储介质， 当所述存储介质中的指令由电子设备的处理器执行时，使得电子设备能够执行如上述中任意一项所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法。
本申请的有益效果：本申请实施例公开了一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，***包括：发射端装置，用于将初始序列进行蒙特卡罗极化码编码和调制处理，得到OFDM信号，并发射包含OFDM信号的声波；其中，所述蒙特卡罗极化码基于蒙特卡罗法和信道估计构造；接收端装置，用于在水声信道接收包含噪声的声波，并将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码，得到译码序列；其中，所述接收端装置中的蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联。可见，本申请实施例中在发射端装置采用蒙特卡罗法和信道估计构造极化码，可以在不同浅海水声信道中构造蒙特卡罗极化码译码，在接收端装置采用混合信道估计，提高信道估计准确性，将混合信道估计模块、均衡器与蒙特卡罗极化码译码器级联，构成循环迭代运算，提高整个通信***的性能。
附图说明
为了更清楚地说明本申请实施例或相关技术中的技术方案，下面将对实施例或相关技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例提供的一种基于蒙特卡罗极化码的译码级联迭代的水声通信***示意图；
图2为本申请实施例提供的蒙特卡罗法构造Polar码的原理框图；
图3为本申请实施例提供的发射序列结构图；
图4为本申请实施例提供的块间迭代接收机对第n个OFDM符号的处理流程图；
图5为本申请实施例提供的子信道BER随循环次数的变化图；
图6为本申请实施例提供的出错位d随循环次数的变换图；
图7为本申请实施例提供的码长512时，蒙特卡罗构造法的归一化判决因子分布图；
图8为本申请实施例提供的码长2048时，蒙特卡罗构造法的归一化判决因子分布图；
图9为本申请实施例提供的智能终端的内部结构原理框图。
具体实施方式
本申请公开了一种基于蒙特卡罗极化码的译码级联迭代的水声通信系 统，为使本申请的目的、技术方案及效果更加清楚、明确，以下参照附图并举实施例对本申请进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。
本技术领域技术人员可以理解，除非特意声明，这里使用的单数形式“一”、“一个”、“所述”和“该”也可包括复数形式。应该进一步理解的是，本申请的说明书中使用的措辞“包括”是指存在所述特征、整数、步骤、操作、元件和/或组件，但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、组件和/或它们的组。应该理解，当我们称元件被“连接”或“耦接”到另一元件时，它可以直接连接或耦接到其他元件，或者也可以存在中间元件。此外，这里使用的“连接”或“耦接”可以包括无线连接或无线耦接。这里使用的措辞“和/或”包括一个或更多个相关联的列出项的全部或任一单元和全部组合。
本技术领域技术人员可以理解，除非另外定义，这里使用的所有术语(包括技术术语和科学术语)，具有与本申请所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语，应该被理解为具有与相关技术的上下文中的意义一致的意义，并且除非像这里一样被特定定义，否则不会用理想化或过于正式的含义来解释。
由于相关技术中，构造的Polar码在水声通信中可能无法获得足够的性能，相关技术的缺点：(1)现有Polar码技术不适合于复杂的水声信道情况。(2)现有Polar码技术在***发射端未针对水声信道对极化码构造方案进行改进；(3)现有Polar码技术在***接收端未与信道进行良好的结合。
为了解决相关技术的问题，本实施例提供了一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，通过在发射端装置采用蒙特卡罗法和信道估计构造极化码，可以在不同浅海水声信道总构造蒙特卡罗极化码译码，在接收端装置采用混合信道估计，提高信道估计准确性，将混合信道估计模块、均衡器与蒙特卡罗极化码译码器级联，构成循环迭代运算，提高整个通信***的性能，降低***误比特率。具体***包括：发射端装置，用于将初始序列进行蒙特卡罗极化码编码和调制处理，得到OFDM信号，并发射包含OFDM信号的声波；其中，所述蒙特卡罗极化码基于蒙特卡罗法和信道估计构造；接收端装置，用于在水声信道接收包含噪声的声波，并将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码，得到译码序列；其中，所述接收端装置中的蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联。
示例性设备
如图1中所示，本申请实施例提供一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，该***包括：发射端装置，用于将初始序列进行蒙特卡罗极化码编码和调制处理，得到OFDM信号，并发射包含OFDM信号的声 波；其中，所述蒙特卡罗极化码基于蒙特卡罗法和信道估计构造；接收端装置，用于在水声信道接收包含噪声的声波，并将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码，得到译码序列；其中，所述接收端装置中的蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联。
具体地，本***在发射端装置中采用蒙特卡罗法和信道估计构造极化码(Polar码)，通过实验计算相应事件发生概率的方法，将其应用到极化信道的筛选中，可以获得不同极化子信道的出错概率，并且充分利用了水声信道的特定，对极化码的构造进行了改进。将初始序列进行蒙特卡罗极化码编码后进行信道调制和OFDM调制，得到OFDM信号，OFDM的原理是将二进制的数据流通过串并转换，分配到相互正交的若干个子信道中进行传输。由于在水下进行通信，故发射端装置发射的是经过处理的包含OFDM信号的声波。传统的接收端装置采用基于导频的信道估计，信道估计准确性低，本***在接收端装置采用混合信道估计，是对现有基于导频的信道估计进行改进，能够实现更为准确的信道估计。此外，在接收端装置中蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联迭代，将接收端通过译码后得到的序列用于下一个OFDM符号的信道估计，有效的实现了极化码在复杂水声信道中的应用，提升了整个通信***的性能。接收端装置中的模数转换、均衡、解调均采用的相关技术，蒙特卡罗极化码译码是蒙特卡罗极化码编码的逆过程。
在一种实现方式中，所述发射端装置包括：蒙特卡罗极化码编码器，用于采用蒙特卡罗法构造的极化码对初始序列进行编码，得到编码信号；第一信道调制器，用于对所述编码信号进行QPSK调制；OFDM调制器，用于对QPSK调制后的信号进行OFDM调制；数模转换器，用于将数字信号转换成模拟信号；发射换能器，用于在水声信道发射声波。
具体地，发射端装置包括蒙特卡罗极化码编码器、第一信道调制器、OFDM调制器、数模转换器和发射换能器。在本实施例中，如图2所示，蒙特卡罗极化码编码器采用蒙特卡罗极化码构造，与以往的极化码不同，蒙特卡罗极化法是通过实验计算相应的事件发生概率的方法，其应用于极化信道的筛选后可以获得不同极化子信道的出错概率，充分利用了水声信道的特点，对极化码的构造进行了改进。第一信道调制器的调制方式包括但不局限于BPSK、QPSK、QAM、16PSK等调制方式，在本实施例中采用的QPSK调制。信号经过QPSK调制后还需进行OFDM调制，此时的发射序列如图3所示，OFDM调制后的信号再经过数模转换后转换成模拟信号通过发射换能器发射声波。
在一种实现方式中，所述接收端装置包括：接收换能器，用于在水声信道接收声波；模数转换器，用于将模拟信号转换成数字信号；混合信道估计模块，用于将基于导频信号的信道估计方式与块间处理的信道估计方 式融合后进行信道估计；其中，所述块间处理的信道估计方式为根据前一个OFDM块的信道估计结果来进行当前OFDM块的译码；信道均衡器，用于对信道的特性进行补偿；OFDM解调器，用于对信道均衡器输出的信号进行OFDM解调；信道解调器，用于对QPSK解调后的信号进行QPSK解调；蒙特卡罗极化码译码器，用于对OFDM解调器输出的信号进行译码；极化码编码器，用于将所述蒙特卡罗极化码译码器译码后的信号进行重编码；第二信道调制器，用于将所述极化码编码器编码后的信号进行QPSK调制；块间处理的信道估计模块，用于根据前一个OFDM块的信道估计结果来进行当前OFDM块的译码。
具体地，接收端装置包括接收换能器、模数转换器、混合信道估计模块、信道均衡器、信道解调器、OFDM解调器、蒙特卡罗极化码译码器、极化码编码器、第二信道调制器和块间处理的信道估计模块。接收换能器接收了水声信道中包含噪声的声波后，通过模数转换成数字信号。为了提高信道估计的准确性，采用混合信道估计模块，将基于导频信号的信道估计方式与块间处理的信道估计方式进行融合，由于块间处理的信道估计方式为根据前一个OFDM块的信道估计结果来进行当前OFDM块的译码，这样也就意味着，当前OFDM块的蒙特卡罗极化码译码与前一个OFDM块的蒙特卡罗极化码译码进行了级联迭代，实现了水声OFDM通信***性能的提升。信号经过估计后会通过信道均衡器对信道的特性进行补偿，接着根据与发射端相逆的处理过程，会通过信道解调器进行信道解调，解调方式同样包括但不局限于BPSK、QPSK、QAM、16PSK等解调方式。在本实施例中，进行QPSK解调，然后通过OFDM解调器进行解调，采用蒙特卡罗极化码译码器译码。值得注意的是，与相关技术相比，本***在接收端装置中增加了极化码编码器和第二信道调制器，极化码编码器可以是本申请实施例中的蒙特卡罗极化码编码器，也可以是相关技术中的极化码编码器。通过极化码编码器将所述接收端装置中蒙特卡罗极化码译码器译码后的信号进行重编码，然后通过第二信道调制器进行QPSK调制,最后将QPSK调制后的信号输入到块间处理的信道估计模块，块间处理的信道估计模块根据QPSK调制后的信号和预处理信号进行信道估计，得到第二信道传递函数，假设将该第二信道传递函数看作前一个OFDM块的信道估计结果，那么这个第二信道传递函数可以用于对当前OFDM块的译码。
在一种实现方式中，所述蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联，形成循环迭代。
具体地，如图4所示，蒙特卡罗极化码译码器与信道均衡器连接，信道均衡器与混合信道估计模块连接，将蒙特卡罗极化码译码器与信道均衡器以及混合信道估计模块看作一个处理模块，处理模块的输出通过极化码重编码、QPSK调制和块间处理的信道估计模块后再次输入到处理模块中，因此，上述过程是一次循环迭代的过程。
本***的特点：
1.本申请提出了一种蒙特卡罗法构造极化码。与以往极化码编码方式不同，该方案是一种通过实验计算相应事件发生概率的方法，将其应用于极化信道的筛选中，可以获得不同极化子信道的出错概率；其次，本申请充分利用了水声信道特点，对极化码的构造方案进行了改进。
2.在接收端装置，改进信道估计方案，改进后的信道估计方案便于实现与极化码解码器的进一步结合。
3.在接收端装置，将改进的信道估计方案与极化码解码器进行级联迭代，实现了水声OFDM通信***性能的提升。
示例性方法
本实施例提供一种基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，该方法可以应用于水声通信的智能终端。
在一种实现方式中，采用蒙特卡罗法构造的极化码对初始序列进行编码，得到编码信号包括：基于导频信号进行信道估计，得到信道状态信息；基于所述信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码；采用蒙特卡罗极化码构造结果对初始序列进行编码，得到编码序列。
具体地，***发射端装置输入训练序列，训练序列为随机的数，由0和1组成，训练序列经过QPSK调制后再经过OFDM调制、添加导频LFM，导频还可以采用HFM和CW等信号及LFM、HFM和CW组合等形式。然后经过数模转换后，通过发射换能器发射至水声信道，在接收端装置通过接收换能器接收，然后经过模数转换后，移除导频LFM，OFDM解调，得到接收序列，根据接收序列和输入训练序列进行信道估计，得到信道状态信息，也即信道传递函数。本申请实施例中的蒙特卡罗极化码基于该信道状态信息的蒙特卡罗法构造。相应的，所述基于所述信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码包括如下步骤：基于预设的码长和预设的码率生成二进制随机序列；将所述二进制随机序列进行极化码编码和信道调制后输入所述信道状态信息对应的水声信道；将所述信道状态信息对应的水声信道输出的信号进行信道解调和极化码译码；重复执行基于预设的码长和预设的码率生成二进制随机序列的步骤M次，统计极化码译码过程中各个子信道的出错个数；基于预设的公式，根据重复执行次数M和所述出错个数，得到各个子信道的误码率；根据各个子信道的误码率，构造蒙特卡罗极化码。
具体地，蒙特卡罗是一种通过实验计算相应事件发生概率的方法，将其应用于极化信道的筛选中，可以获得不同极化子信道的出错概率。假定在水声信道中传输极化码元为随机事件ξ，则在一次事件中发生SC译码后的极化码与发送端初始序列不同为事件A。当A发生时，则ξ取值为1，若A未发生，则ξ取值为0。假定蒙特卡罗实验的总次数为M，A发生的总次数为v，则频数v为一个随机变量，单个子信道的误码率(Bit Error Rate,BER)可表示为：
依据大数定理，当实验次数足够多时上式成立的概率为1，由上述模型得到的概率近似为单个极化子信道的误码率。因此，只要已知水声信道的状态信息，通过蒙特卡罗方法即可迭代计算子信道误码率的统计信息。
根据式，水声OFDM第k个子载波对应的发送信号为：
其中，s[k]为第k个子载波对应的发送符号，fk为第k个子载波频率。设水声信道的冲激响应为：
其中，N为多径数目，hi和τi分别表示水声信道第i径对应的幅值和时延。则经过水声信道传播后，接收端接收到的信号为：
其中，Ai＝his[k]，θi＝2πfkτi表示第i径接收信号的相位延迟。将(3)式的右边用复数形式表示，得：
化简为单矢量表达形式：
其中，和2πfkt+θ分别表示接收信号矢量的模和相位角。浅海水声信道满足广义非相关散射条件，即当多径数N较大时，各多径随机变量Ai相互独立，θi在[0，2π)均匀分布。根据中心极限定理：变量个数很大时，独立随机变量之和的概率分布收敛于正态分布，因此，a，b～N(0，σc 2)，其中方差值σc 2为接收信号包络的平均功率，a和b的联合概率分布为：
则接收信号包络分布为：
由(8)式可见，在不考虑多普勒频移影响下，多径水声信道的包络分布服从瑞利分布，其方差σc 2为接收信号包络的平均功率。对于水声OFDM通信***方差σc 2与信道状态信息估计值的关系为：
其中，R为Polar码码率，SA为OFDM子载波集。假设预设的码长N(如8)，码率为R，码率包括但不局限于1/4、1/2、3/4，依据码长和码率生成一组长度K＝NR的二进制随机序列，将所述二进制随机序列进行极化码编码和信 道调制后输入(9)式中的信道状态信息对应的水声信道；此处的极化码为相关技术中的任一种极化码。然后将所述信道状态信息对应的水声信道输出的信号进行信道解调和极化码译码，依据蒙特卡罗法，重复执行基于预设的码长和预设的码率生成二进制随机序列；将所述二进制随机序列进行极化码编码和信道调制后输入所述信道状态信息对应的水声信道；将所述信道状态信息对应的水声信道输出的信号进行信道解调和极化码译码的步骤重复M次，统计极化码译码过程中各个子信道的出错个数V，依据公式(1)可以计算出各极化子信道的误码率BER，根据各个子信道的误码率，构造蒙特卡罗极化码。相应的，所述根据各个子信道的误码率，构造蒙特卡罗极化码包括如下步骤：将各个子信道的误码率按照从小到大进行排序；将排序靠前的K个误码率对应的子信道作为信息位集合；将信息位集合作为蒙特卡罗极化码的构造结果。也就是说，蒙特卡罗法构造Polar通过迭代累积子信道BER值，并从中选出BER值相对较小的信道作为信息传输信道。
具体地，将各个子信道的误码率按照从小到大进行排序，将排序靠前的K个误码率对应的子信道作为信息位集合，其余子信道选取为传输冻结位集合。蒙特卡罗法构造Polar码过程符合大数定律，即运算次数越多，各子信道BER估计值越趋近于真实值，所构造Polar码的性能也接近理想Polar码的性能。假设循环108次时构造出的Polar码为理想的Polar码，记理想Polar码的信息位集合为Aref，循环M次运算所构造Polar码的信息位集合为A，则d＝crad(Aref)-crad(Aref∩A)表示集合A与集合Aref之间不同元素的个数，其中crad(X)表示取集合X中元素个数。将信息位集合作为蒙特卡罗极化码的构造结果，也即将信息位集合作为信息传输信道。
相关技术中，LS方法的信道估计结果在低信噪比情况下受到信道噪声影响，且在时变信道中仅采用训练序列估计无法及时得出信道变化信息。为了改进LS方法的信道估计性能，采用将OFDM接收端所有子载波上的接收信息用于信道估计，并与导频序列的LS估计结果结合的方法，可以补充LS估计结果中的信道变化信息。
在OFDM***中，每帧数据传输五组OFDM符号数据，本申请将极化码的译码与OFDM信道估计结合，采用块间处理的信道估计方式，即通过前一个OFDM块的信道估计结果用于当前OFDM块的译码。在时变信道中，将块间处理的信道估计方式与基于导频信号的信道估计方法相结合，设置一种借助信道译码估计值的迭代接收机，从而提高信道估计准确性，减少导频子载波***的使用。
在一种实现方式中，所述将基于导频信号的信道估计方式与块间处理的信道估计方式融合后进行信道估计包括如下步骤：将接收信号从时域转换到频域，得到预处理信号；基于所述预处理信号中的导频信号对信道进行估计，得到当前OFDM符号对应的第一信道传递函数；获取前一个OFDM符号对应的译码信号；根据前一个OFDM符号对应的译码信号，得到前一个OFDM 符号对应的第二信道传递函数；将当前OFDM符号对应的第一信道传递函数和前一个OFDM符号对应的第二信道传递函数进行融合，得到混合信道传递函数。
具体地，如图4所示，对于接收到的第m帧信号，将接收信号通过FFT从时域转换到频域，得到预处理信号，预处理信号中包含导频信号，对于第一组OFDM序列，基于导频信号进行信道估计得到第一信道传递函数后，仅采用进行信道均衡和译码，假定该组第一个OFDM符号译码输出值准确，获取该OFDM符号对应的译码信号；将该OFDM符号对应的译码信号进行极化码重编码和信道调制，得到调制信号；然后根据所述调制信号和所述预处理信号对信道进行估计，得到第二信道传递函数，也即结合预处理输出的相应序列，可得出相应的信道估计值(第二信道传递函数)为：
其中，ym(n-1)表示第m帧接收信号中的第n-1组OFDM序列，表示其对应译码输出序列经过重编码和QPSK调制的输出序列。
得到第一信道函数和第二函数后，将当前OFDM符号对应的第一信道传递函数和前一个OFDM符号对应的第二信道传递函数进行融合，得到混合信道传递函数。在本实施例中，将迭代译码估计值(也即第二信道传递函数)和第一信道传递函数输入混合估计模块用于第n组OFDM序列的信道估计，对第一信道传递函数和第二信道传递函数进行加权平均，定义加权系数δ∈(0，1)，则混合信道估计(也即混合信道传递函数)的输出为：
在一种实现方式中，将初始序列进行蒙特卡罗极化码编码和调制处理之后包括如下步骤：将进行蒙特卡罗极化码编码和调制处理后的初始序列进行符号映射、串并转换、子载波分配、导频***、快速傅里叶逆变换、循环前缀的添加处理和并串转换。
具体地，符号映射、串并转换、子载波分配、导频***、快速傅里叶逆变换、循环前缀的添加处理和并串转换为水声OFDM通信***的常规处理方式，在此不再赘述。
在一种实现方式中，将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码包括如下步骤：将包含噪声的声波进行模数转换、串并转换、循环前缀的移除处理、快速傅里叶变换、混合信道估计、均衡、导频的去除处理、并串转换、解调和蒙特卡罗极化码译码， 得到译码序列。上述处理过程为相关技术，在此不再赘述。
图5为子信道BER随循环次数的变化图；图6为出错位d随循环次数的变换示意图，图7为码长512时，蒙特卡罗构造法的归一化判决因子分布图；图中点为蒙特卡罗构造方法的判决因子，即BER的分布情况。由图可知，该构造方法的判决因子均呈现一定的极化特征，BER分布极化特征明显。图8为码长2048时，蒙特卡罗构造法的归一化判决因子分布图，从图中可以看出不同码长的判决因子具有近似的分布情况，同时码长更长的信道极化特征更明显。由图6-8可知，当M小于103时，各子信道的BER变化剧烈，当M在103和105之间时，各子信道的BER小幅变化，而当M大于105时，各子信道BER值趋于稳定。用蒙特卡罗法构造Polar码时，计算量和运算时间随循环次数的增大而线性增加，实际应用时，应综合性能和运算时间选择合适的循环次数，综合考虑图6-7的统计信息和图6-8的BER曲线，后续在不同浅海水声信道中构造Polar码时，循环次数M取值为106。
基于上述实施例，本申请还提供了一种智能终端，其原理框图可以如图9所示。该智能终端包括通过***总线连接的处理器、存储器、网络接口、显示屏、温度传感器。其中，该智能终端的处理器用于提供计算和控制能力。该智能终端的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作***和计算机程序。该内存储器为非易失性存储介质中的操作***和计算机程序的运行提供环境。该智能终端的网络接口用于与外部的终端通过网络连接通信。该计算机程序被处理器执行时以实现一种基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法。该智能终端的显示屏可以是液晶显示屏或者电子墨水显示屏，该智能终端的温度传感器是预先在智能终端内部设置，用于检测内部设备的运行温度。
本领域技术人员可以理解，图9中的原理图，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的智能终端的限定，具体的智能终端可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
在一个实施例中，提供了一种智能终端，包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行所述一个或者一个以上程序包含用于进行以下操作的指令：
采用蒙特卡罗法构造的极化码对初始序列进行编码，得到编码信号包括：
基于导频信号进行信道估计，得到信道状态信息；
基于所述信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码；
采用蒙特卡罗极化码对初始序列进行编码，得到编码序列。
所述基于所述信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码包括：
基于预设的码长和预设的码率生成二进制随机序列；
将所述二进制随机序列进行极化码编码和信道调制后输入所述信道状态信息对应的水声信道；
将所述信道状态信息对应的水声信道输出的信号进行信道解调和极化码译码；
重复执行基于预设的码长和预设的码率生成二进制随机序列的步骤M次，统计极化码译码过程中各个子信道的出错个数；
基于预设的公式，根据重复执行次数M和所述出错个数，得到各个子信道的误码率；
根据各个子信道的误码率，构造蒙特卡罗极化码。
所述根据各个子信道的误码率，构造蒙特卡罗极化码包括：
将各个子信道的误码率按照从小到大进行排序；
将排序靠前的K个误码率对应的子信道作为信息位集合；
将信息位集合作为蒙特卡罗极化码的构造结果。
所述将基于导频信号的信道估计方式与块间处理的信道估计方式融合后进行信道估计包括：
将接收信号从时域转换到频域，得到预处理信号；
基于所述预处理信号中的导频信号对信道进行估计，得到当前OFDM符号对应的第一信道传递函数；
获取前一个OFDM符号对应的译码信号；
根据前一个OFDM符号对应的译码信号，得到前一个OFDM符号对应的第二信道传递函数；
将当前OFDM符号对应的第一信道传递函数和前一个OFDM符号对应的第二信道传递函数进行融合，得到混合信道传递函数。
所述根据前一个OFDM符号对应的译码信号，得到前一个OFDM符号对应的第二信道传递函数包括：
将前一个OFDM符号对应的译码信号进行极化码重编码和信道调制，得到调制信号；
根据所述调制信号和所述预处理信号对信道进行估计，得到第二信道传递函数。
将初始序列进行蒙特卡罗极化码编码和调制处理之后包括：
将进行蒙特卡罗极化码编码和调制处理后的初始序列进行符号映射、串并转换、子载波分配、导频***、快速傅里叶逆变换、循环前缀的添加处理和并串转换。
将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码包括：
将包含噪声的声波进行模数转换、串并转换、循环前缀的移除处理、快速傅里叶变换、混合信道估计、均衡、导频的去除处理、并串转换、解调和蒙特卡罗极化码译码，得到译码序列。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)，以及存储器总线动态RAM(RDRAM)等。
综上所述，本申请公开了一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，所述***包括：发射端装置，用于将初始序列进行蒙特卡罗极化码编码和调制处理，得到OFDM信号，并发射包含OFDM信号的声波；其中，所述蒙特卡罗极化码基于蒙特卡罗法和信道状态信息构造；接收端装置，用于在水声信道接收包含噪声的声波，并将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码，得到译码序列；其中，所述接收端装置中的蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联。本申请实施例在发射端装置采用蒙特卡罗法和信道估计构造极化码，可以在不同浅海水声信道中构造采用蒙特卡罗极化码构造结果进行极化码译码，在接收端装置采用混合信道估计，提高信道估计准确性，将混合信道估计模块、均衡器与蒙特卡罗极化码译码器级联，构成循环迭代运算，提高整个通信***的性能。
基于上述实施例，本申请公开了一种基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，应当理解的是，本申请的应用不限于上述的举例，对本领域普通技术人员来说，可以根据上述说明加以改进或变换，所有这些改进和变换都应属于本申请所附权利要求的保护范围。

Claims (13)

  1. 一种基于蒙特卡罗极化码的译码级联迭代的水声通信***，其中，所述***包括：
    发射端装置，用于将初始序列进行蒙特卡罗极化码编码和调制处理，得到OFDM信号，并发射包含OFDM信号的声波；其中，所述蒙特卡罗极化码基于信道估计结果进行蒙特卡罗构造；
    接收端装置，用于在水声信道接收包含噪声的声波，并将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码，得到译码序列；其中，所述接收端装置中的蒙特卡罗极化码译码器与混合信道估计模块、均衡器级联。
  2. 根据权利要求1所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***，其中，所述发射端装置包括：
    蒙特卡罗极化码编码器，用于采用蒙特卡罗法构造的极化码对初始序列进行编码，得到编码信号；
    第一信道调制器，用于对所述编码信号进行QPSK调制；
    OFDM调制器，用于对QPSK调制后的信号进行OFDM调制；
    数模转换器，用于将数字信号转换成模拟信号；
    发射换能器，用于在水声信道发射声波。
  3. 根据权利要求1所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***，其中，所述接收端装置包括：
    接收换能器，用于在水声信道接收声波；
    模数转换器，用于将模拟信号转换成数字信号；
    混合信道估计模块，用于将基于导频信号的信道估计方式与块间处理的信道估计方式融合后进行信道估计；其中，所述块间处理的信道估计方式为根据前一个OFDM块的信道估计结果来进行当前OFDM块的译码；
    信道均衡器，用于对信道的特性进行补偿；
    OFDM解调器，用于对QPSK解调后的信号进行OFDM解调；
    信道解调器，用于对信道均衡器输出的信号进行QPSK解调；
    蒙特卡罗极化码译码器，用于对OFDM解调器输出的信号进行译码；
    极化码编码器，用于将所述蒙特卡罗极化码译码器译码后的信号进行重编码；
    第二信道调制器，用于将所述极化码编码器编码后的信号进行QPSK调制；
    块间处理的信道估计模块，用于根据前一个OFDM块的信道估计结果来进行当前OFDM块的译码。
  4. 根据权利要求3所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***，其中，所述蒙特卡罗极化码译码器与混合信道估计模块、均衡 器级联，形成循环迭代。
  5. 一种如权利要求1-4任一项所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，其中，采用蒙特卡罗法构造的极化码对初始序列进行编码，得到编码信号包括：
    基于导频信号进行信道估计，得到信道状态信息；
    基于所述信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码；
    采用蒙特卡罗极化码对初始序列进行编码，得到编码信号。
  6. 根据权利要求5所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，其中，所述基于所述信道状态信息和蒙特卡罗法，构造蒙特卡罗极化码包括：
    基于预设的码长和预设的码率生成二进制随机序列；
    将所述二进制随机序列进行极化码编码和信道调制后输入所述信道状态信息对应的水声信道；
    将所述信道状态信息对应的水声信道输出的信号进行信道解调和极化码译码；
    重复执行基于预设的码长和预设的码率生成二进制随机序列的步骤M次，统计极化码译码过程中各个子信道的出错个数；
    基于预设的公式，根据重复执行次数M和所述出错个数，得到各个子信道的误码率；
    根据各个子信道的误码率，构造蒙特卡罗极化码。
  7. 根据权利要求6所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，其中，所述根据各个子信道的误码率，构造蒙特卡罗极化码包括：
    将各个子信道的误码率按照从小到大进行排序；
    将排序靠前的K个误码率对应的子信道作为信息位集合；
    将信息位集合作为蒙特卡罗极化码的构造结果。
  8. 根据权利要求5所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，其中，所述将基于导频信号的信道估计方式与块间处理的信道估计方式融合后进行信道估计包括：
    将接收信号从时域转换到频域，得到预处理信号；
    基于所述预处理信号中的导频信号对信道进行估计，得到当前OFDM符号对应的第一信道传递函数；
    获取前一个OFDM符号对应的译码信号；
    根据前一个OFDM符号对应的译码信号，得到前一个OFDM符号对应的第二信道传递函数；
    将当前OFDM符号对应的第一信道传递函数和前一个OFDM符号对应的第二信道传递函数进行融合，得到混合信道传递函数。
  9. 根据权利要求8所述的基于蒙特卡罗极化码的译码级联迭代的水声 通信***的信号处理方法，其中，所述根据前一个OFDM符号对应的译码信号，得到前一个OFDM符号对应的第二信道传递函数包括：
    将前一个OFDM符号对应的译码信号进行极化码重编码和信道调制，得到调制信号；
    根据所述调制信号和所述预处理信号对信道进行估计，得到第二信道传递函数。
  10. 根据权利要求5所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，其中，将初始序列进行蒙特卡罗极化码编码和调制处理之后包括：
    将进行蒙特卡罗极化码编码和调制处理后的初始序列进行符号映射、串并转换、子载波分配、导频***、快速傅里叶逆变换、循环前缀的添加处理和并串转换。
  11. 根据权利要求5所述的基于蒙特卡罗极化码的译码级联迭代的水声通信***的信号处理方法，其中，将包含噪声的声波进行模数转换、混合信道估计、均衡、解调和蒙特卡罗极化码译码包括：
    将包含噪声的声波进行模数转换、串并转换、循环前缀的移除处理、快速傅里叶变换、混合信道估计、均衡、导频的去除处理、并串转换、解调和蒙特卡罗极化码译码，得到译码序列。
  12. 一种智能终端，其中，所述智能终端包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行所述一个或者一个以上程序包含用于执行如权利要求5-11中任意一项所述的方法。
  13. 一种非临时性计算机可读存储介质，其中，当所述存储介质中的指令由电子设备的处理器执行时，使得电子设备能够执行如权利要求5-11中任意一项所述的方法。
PCT/CN2023/119224 2022-09-28 2023-09-15 基于蒙特卡罗极化码的译码级联迭代的水声通信*** WO2024067178A1 (zh)

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