Doppler frequency shift estimation method based on bit error rate

Abstract

The invention provides a Doppler frequency shift estimation method based on an error rate. According to the method, Doppler frequency shift estimation is carried out based on the BER, and the Doppler factor can be estimated more accurately, especially in an underwater acoustic channel with strong frequency dispersion effect and noise interference. Compared with a traditional method based on signal feature matching, the Doppler estimation based on BER optimization can effectively reduce estimation errors, and the overall efficiency and performance of a communication system are effectively improved. According to the method, initial estimation is obtained in time-frequency domain analysis, and Doppler compensation is carried out on the basis, so that the problem of high calculation complexity possibly existing in a global search or iterative optimization method is avoided, the requirements of a real-time communication system can be met, and the calculation overhead is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater acoustic communication, and in particular to a Doppler frequency shift estimation method based on bit error rate. Background Art

[0002] Underwater acoustic communication technology is a core pillar of marine information transmission and is widely used in underwater engineering, marine science research, and the offshore oil industry. However, the inherent characteristics of underwater acoustic channels, such as limited bandwidth and severe delay spread, can induce intersymbol interference (ISI), significantly impacting the reliability of communication systems. Orthogonal frequency division multiplexing (OFDM) technology, with its excellent ISI immunity and efficient spectrum utilization, has become an ideal solution for underwater acoustic communication. However, OFDM systems are extremely sensitive to the Doppler effect and phase noise. Without effective Doppler estimation and compensation, system performance will significantly degrade. Therefore, accurately estimating and compensating for the Doppler effect is a key issue in underwater acoustic OFDM communication. Existing Doppler estimation algorithms mainly fall into two categories: The first method uses pre-designed preamble and postamble signals to estimate the Doppler factor by measuring the time difference between their spectral peaks. While simple and representative, this method is only applicable to single-carrier systems and is not suitable for OFDM systems. The second method estimates the Doppler frequency by searching for the maximum correlation peak. Although this method can achieve Doppler estimation to a certain extent, its computational complexity is very high, and in the presence of cluster correlation peaks, it is difficult to accurately distinguish the maximum correlation peak, which leads to large estimation errors. Generally speaking, the core idea of these two methods is to find the signal level that best matches the standard signal in the time domain or time-frequency domain, and compensate accordingly to achieve the bit-level target of minimum bit error rate (BER). However, due to the significant dispersion effect of the underwater acoustic channel, the optimal matching signal level does not necessarily correspond to the Doppler factor that can achieve the minimum BER during the demodulation process, resulting in a mismatch between the estimation and the actual requirements of the system. To solve this problem, the Doppler estimation method based on BER search is further optimized on the basis of traditional signal matching, so that the estimation of the Doppler factor is more in line with the actual requirements of the OFDM demodulation process, thereby effectively reducing the estimation error and improving the communication performance of the system.

[0003] During the implementation of the present invention, the following deficiencies were discovered in the prior art: 1) Many traditional methods rely on specific signal characteristics to estimate the Doppler factor. However, in complex underwater acoustic environments, dispersion and noise can blur these characteristics, causing the estimated results to deviate from the optimal BER target. 2) Some methods rely on global search or iterative optimization to obtain the optimal Doppler factor. While this may improve accuracy, it significantly increases the computational effort, making it difficult to meet the requirements of real-time communication. Summary of the Invention

[0004] The purpose of the present invention is to provide a Doppler shift estimation method based on bit error rate to solve the problems of residual frequency offset and large estimation error caused by the Doppler effect in underwater acoustic OFDM communication systems, and at the same time solve the problem of high BER caused by dispersion effect and noise interference.

[0005] The present invention is achieved through the following technical solution. The present invention proposes a Doppler frequency shift estimation method based on bit error rate, which includes the following steps:

[0006] Step 1: Generate an OFDM signal and modulate it. Then, use IFFT to convert the signal to the time domain and add a cyclic prefix to simulate the OFDM signal transmission process in an actual communication system.

[0007] Step 2: The OFDM signal from step 1 passes through the underwater acoustic channel and is affected by the Doppler frequency shift, thereby forming a received signal;

[0008] Step 3: Performing time-frequency domain analysis on the received signal in step 2 to determine the range of the bit-level Doppler search to obtain an initial estimate;

[0009] Step 4: Based on the initial estimation in step 3, search for the Doppler factor that minimizes the signal BER within the estimation range and perform compensation to optimize the system performance.

[0010] Furthermore, in step 1, the channel impulse response is modeled as:

[0011]

[0012] Where h(t) is the low-frequency underwater acoustic channel, L is the total number of tap delays in the system model, and h i is the complex gain of the i-th path, δ is the unit pulse function, τ i (t) is the initial delay of the i-th path, τ is the delay component, and i is the path component.

[0013] Furthermore, in step 1, it is assumed that the Doppler factor on each path is are the same, then the delay of the i-th path is expressed as:

[0014]

[0015] where τ i is the initial delay of the i-th path.

[0016] Furthermore, in step 1, assuming that the input bit stream data is QAM mapped and then subjected to inverse fast Fourier transform, the transmitted OFDM signal is represented as:

[0017]

[0018] Among them, S A is the set of all subcarriers, s(k) is the signal after inverse fast Fourier transform, k is the subcarrier index, Δf = 1 / T is the frequency interval between adjacent subcarriers, f c is the center frequency of the subcarrier, and T is the length of the OFDM signal.

[0019] Furthermore, in step 2, assuming h i , τ i as well as It remains unchanged within an OFDM symbol period. At this time, after an OFDM symbol x(t) passes through the low-frequency underwater acoustic channel h(τ), the received signal is obtained:

[0020] y(t)=x(t)*h(t)+n(t) (4)

[0021] Where n(t) is complex additive white Gaussian noise; the received signal model is expressed as:

[0022]

[0023] The Doppler of each subcarrier is written as:

[0024]

[0025] Furthermore, in step 3, the process of performing Doppler estimation in the time domain is expressed as:

[0026]

[0027] Among them, T r and T t Respectively represent the length of time for receiving and sending signals.

[0028] Furthermore, in step 3, the Doppler estimation process in the frequency domain is expressed as:

[0029]

[0030] Among them, f r and f t are the frequencies of single-frequency receiving signal and single-frequency transmitting signal respectively.

[0031] Furthermore, in step 4, assume that x f is the transmitted signal in the frequency domain, then the cost function based on BER is expressed as:

[0032]

[0033] Where F is the N×N dimensional discrete Fourier transform matrix DFT, expressed as:

[0034]

[0035] e represents the Doppler frequency shift of N subcarriers, which is expressed as:

[0036]

[0037] Where B = NΔf represents the signal bandwidth; Sdec is defined as the decision function, expressed as:

[0038]

[0039] where R f is the OFDM symbol at the receiving end, real[·] and imag[·] are the real and imaginary parts of the complex number; the BER optimization problem is expressed as:

[0040]

[0041] Where (c1, c2) is the Doppler search range; according to the above process, the Doppler estimation problem can be formulated as searching for the optimal BER.

[0042] The present invention also provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the Doppler frequency shift estimation method based on bit error rate when executing the computer program.

[0043] The present invention also provides a computer-readable storage medium for storing computer instructions, wherein the computer instructions, when executed by a processor, implement the steps of the Doppler frequency shift estimation method based on bit error rate.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] By using BER-based Doppler shift estimation, this method can more accurately estimate the Doppler factor, particularly in underwater acoustic channels with strong dispersion and noise interference. Compared with traditional methods based on signal feature matching, BER-optimized Doppler estimation can effectively reduce estimation errors and improve the overall efficiency and performance of the communication system.

[0046] This method obtains an initial estimate in the time-frequency domain analysis and performs Doppler compensation based on this estimate, avoiding the high computational complexity that may exist in global search or iterative optimization methods. It can meet the needs of real-time communication systems and effectively reduce computational overhead.

[0047] The present invention can still work effectively in an underwater acoustic channel with severe frequency dispersion effect and noise interference, adapts to complex environments by optimizing the Doppler estimation process, and improves the reliability and stability of the underwater acoustic OFDM communication system.

[0048] By comprehensively considering time-frequency domain analysis and bit error rate optimization in the Doppler estimation process, the present invention can accurately compensate for Doppler frequency shift in actual communication, ensure the optimal performance of the OFDM system, thereby effectively reducing BER and improving the transmission quality of the system.

[0049] This invention effectively reduces the impact of the Doppler effect on OFDM signals through precise Doppler shift estimation and compensation, thereby avoiding performance losses caused by ISI and frequency deviation. This not only improves the reliability of underwater acoustic communication systems, but also optimizes spectrum utilization efficiency, further enhancing the overall system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0051] Figure 1 This is a flow chart of a Doppler frequency shift estimation method based on bit error rate according to the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0053] Combine Figure 1 The present invention proposes a Doppler frequency shift estimation method based on bit error rate, which includes the following steps:

[0054] Step 1: Generate an OFDM signal and modulate it. Then, use IFFT to convert the signal to the time domain and add a cyclic prefix to simulate the OFDM signal transmission process in an actual communication system.

[0055] In step 1, the channel impulse response is modeled as:

[0056]

[0057] Where h(t) is the low-frequency underwater acoustic channel, L is the total number of tap delays in the system model, and h i is the complex gain of the i-th path, δ is the unit pulse function, τ i (t) is the initial delay of the i-th path, τ is the delay component, and i is the path component.

[0058] Assume that the Doppler factor on each path is are the same, then the delay of the i-th path is expressed as:

[0059]

[0060] where τ i is the initial delay of the i-th path.

[0061] Assume that the input bit stream data is QAM mapped and then passed through the inverse fast Fourier transform; the transmitted OFDM signal at this time is represented as:

[0062]

[0063] Among them, S A is the set of all subcarriers, s(k) is the signal after inverse fast Fourier transform, k is the subcarrier index, Δf = 1 / T is the frequency interval between adjacent subcarriers, f c is the center frequency of the subcarrier, and T is the length of the OFDM signal.

[0064] Step 2: The OFDM signal from step 1 passes through the underwater acoustic channel and is affected by the Doppler frequency shift, thereby forming a received signal;

[0065] In step 2, assume that h i , τ i as well as It remains unchanged within an OFDM symbol period. At this time, after an OFDM symbol x(t) passes through the low-frequency underwater acoustic channel h(τ), the received signal is obtained:

[0066] y(t)=x(t)*h(t)+n(t) (4)

[0067] Where n(t) is complex additive white Gaussian noise; the received signal model is expressed as:

[0068]

[0069] The Doppler of each subcarrier is written as:

[0070]

[0071] Step 3: Performing time-frequency domain analysis on the received signal in step 2 to determine the range of the bit-level Doppler search to obtain an initial estimate;

[0072] In step 3, the process of Doppler estimation in the time domain is expressed as:

[0073]

[0074] Among them, T r and T t Respectively represent the length of time for receiving and sending signals.

[0075] The Doppler estimation process in the frequency domain is expressed as:

[0076]

[0077] Among them, f r and f t are the frequencies of single-frequency receiving signal and single-frequency transmitting signal respectively.

[0078] The range of the bit-level Doppler search is determined according to the above time-frequency domain estimation method to obtain an initial estimate.

[0079] Step 4: Based on the initial estimation in step 3, search for the Doppler factor that minimizes the signal BER within the estimation range and perform compensation to optimize the system performance.

[0080] In step 4, assume that x f is the transmitted signal in the frequency domain, then the cost function based on BER is expressed as:

[0081]

[0082] Where F is the N×N dimensional discrete Fourier transform matrix DFT, expressed as:

[0083]

[0084] e represents the Doppler frequency shift of N subcarriers, which is expressed as:

[0085]

[0086] Where B = NΔf represents the signal bandwidth; Sdec is defined as the decision function, expressed as:

[0087]

[0088] where R f is the OFDM symbol at the receiving end, real[·] and imag[·] are the real and imaginary parts of the complex number; the BER optimization problem is expressed as:

[0089]

[0090] Where (c1, c2) is the Doppler search range; according to the above process, the Doppler estimation problem can be formulated as searching for the optimal BER.

[0091] The present invention also provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the Doppler frequency shift estimation method based on bit error rate when executing the computer program.

[0092] The present invention also provides a computer-readable storage medium for storing computer instructions, wherein the computer instructions, when executed by a processor, implement the steps of the Doppler frequency shift estimation method based on bit error rate.

[0093] The memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. The non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DRRAM). It should be noted that the memory of the methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0094] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disc (SSD)).

[0095] During implementation, each step of the above method can be completed by an integrated logic circuit of the hardware in the processor or by instructions in the form of software. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it will not be described in detail here.

[0096] It should be noted that the processor in the embodiments of the present application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiment can be completed by an integrated logic circuit of the hardware in the processor or by instructions in the form of software. The above processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0097] The above is a detailed introduction to the Doppler frequency shift estimation method based on bit error rate proposed in the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A Doppler shift estimation method based on bit error rate, characterized in that: The method comprises the following steps: Step 1: Generate an OFDM signal and modulate it. Then, use IFFT to convert the signal to the time domain and add a cyclic prefix to simulate the OFDM signal transmission process in an actual communication system. Step 2: The OFDM signal from step 1 passes through the underwater acoustic channel and is affected by the Doppler frequency shift, thereby forming a received signal; Step 3: Performing time-frequency domain analysis on the received signal in step 2 to determine the range of the bit-level Doppler search to obtain an initial estimate; Step 4: Based on the initial estimation in step 3, search for the Doppler factor that minimizes the signal BER within the estimation range and perform compensation to optimize the system performance.

2. The method according to claim 1, characterized in that In step 1, the channel impulse response is modeled as: Where h(t) is the low-frequency underwater acoustic channel, L is the total number of tap delays in the system model, and h i is the complex gain of the i-th path, δ is the unit pulse function, τ i (t) is the initial delay of the i-th path, τ is the delay component, and i is the path component.

3. The method according to claim 2, characterized in that In step 1, assume that the Doppler factor on each path is are the same, then the delay of the i-th path is expressed as: where τ i is the initial delay of the i-th path.

4. The method according to claim 3, characterized in that In step 1, assuming that the input bit stream data is QAM mapped and then subjected to inverse fast Fourier transform, the transmitted OFDM signal is represented as: Among them, S A is the set of all subcarriers, s(k) is the signal after inverse fast Fourier transform, k is the subcarrier index, Δf = 1 / T is the frequency interval between adjacent subcarriers, f c is the center frequency of the subcarrier, and T is the length of the OFDM signal.

5. The method according to claim 4, characterized in that In step 2, assume that h i , τ i as well as It remains unchanged within an OFDM symbol period. At this time, after an OFDM symbol x(t) passes through the low-frequency underwater acoustic channel h(τ), the received signal is obtained: y(t)=x(t)*h(t)+n(t) (4) Where n(t) is complex additive white Gaussian noise; the received signal model is expressed as: The Doppler of each subcarrier is written as:

6. The method according to claim 5, characterized in that In step 3, the process of Doppler estimation in the time domain is expressed as: Among them, T r and T t Respectively represent the length of time for receiving and sending signals.

7. The method according to claim 6, characterized in that In step 3, the Doppler estimation process in the frequency domain is expressed as: Among them, f r and f t are the frequencies of single-frequency receiving signal and single-frequency transmitting signal respectively.

8. The method according to claim 7, characterized in that In step 4, assume that x f is the transmitted signal in the frequency domain, then the cost function based on BER is expressed as: Where F is the N×N dimensional discrete Fourier transform matrix DFT, expressed as: e represents the Doppler frequency shift of N subcarriers, which is expressed as: Where B = NΔf represents the signal bandwidth; Sdec is defined as the decision function, expressed as: where R f is the OFDM symbol at the receiving end, real[·] and imag[·] are the real and imaginary parts of the complex number; the BER optimization problem is expressed as: Where (c1, c2) is the Doppler search range; according to the above process, the Doppler estimation problem can be formulated as searching for the optimal BER.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium for storing computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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