Frequency offset compensation method and device of terahertz communication system and electronic equipment
Patent Information
- Application Number
- CN202510466521.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-15
- Publication Date
- 2026-10-23
Smart Images
Figure CN122969940A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of terahertz communication technology, and more specifically, to a frequency offset compensation method, apparatus and electronic equipment for a terahertz communication system. Background Technology
[0002] With the rapid development of modern communication technology, terahertz communication, with its ultra-wide bandwidth and high-speed transmission capabilities, has become one of the main candidates for next-generation communication technology. However, the high-frequency characteristics of terahertz communication systems make frequency offset problems particularly significant. These frequency offset problems are mainly caused by frequency mismatch between the transmitter and receiver and the Doppler effect.
[0003] Most existing frequency offset estimation methods are geared towards traditional wireless communication systems, mainly targeting narrowband or intermediate frequency communication environments. Traditional frequency offset estimation methods are difficult to meet the ultra-wideband and high-speed transmission requirements of terahertz communication systems. Especially when the frequency offset is large, the convergence and accuracy of traditional algorithms decrease significantly.
[0004] Public content
[0005] In view of this, the present disclosure provides a frequency offset compensation method, apparatus and electronic equipment for a terahertz communication system.
[0006] One aspect of this disclosure provides a frequency offset compensation method for a terahertz communication system, wherein the frequency offset compensation method includes: determining a baseband signal based on sequence information of a pseudo-random sequence; performing signal processing on the baseband signal based on a frequency offset signal and a noise signal to obtain a received signal; calculating a correlation cost function within a first search window based on a first step length to determine a first frequency offset estimation result; calculating the correlation cost function within a second search window based on a second step length to obtain a second frequency offset estimation result; and determining a frequency offset compensation result based on a compensation signal generated from the received signal and the second frequency offset estimation result.
[0007] According to embodiments of this disclosure, determining the baseband signal based on the sequence information of the pseudo-random sequence includes: determining a pilot signal based on the sequence information of the pseudo-random sequence; mapping multiple data symbols onto a carrier signal using an orthogonal amplitude modulation method to generate a modulation signal; and splicing the pilot signal and the modulation signal to obtain the baseband signal.
[0008] According to embodiments of this disclosure, the method further includes: generating multiple random binary data based on the orthogonal amplitude modulation order; and searching the multiple random binary data using a constellation diagram to obtain multiple data symbols.
[0009] According to embodiments of this disclosure, the above-mentioned signal processing of the baseband signal based on the frequency offset signal and the noise signal to obtain the received signal includes: upsampling the baseband signal based on a linear interpolation method to obtain an intermediate tether signal; pulse shaping the intermediate baseband signal using a raised cosine filter to obtain the transmitted signal; and determining the received signal based on the frequency offset signal and the noise signal during the transmission of the transmitted signal in the wireless channel.
[0010] According to an embodiment of this disclosure, the above-mentioned calculation of the correlation cost function within a first search window based on the first step length to determine the first frequency offset estimation result includes: performing the above-mentioned fast Fourier transform on the received signal and the pilot signal respectively to calculate the cross power spectral density of the received signal and the pilot signal in the frequency domain; determining the above-mentioned correlation cost function between the received signal and the pilot signal based on the above-mentioned cross power spectral density; and determining the first frequency offset estimation result corresponding to the maximum value of the above-mentioned correlation cost function within the first search window based on the above-mentioned first step length.
[0011] According to embodiments of this disclosure, the method further includes: determining the first search window and the first step length based on the local oscillator signal frequency, the crystal oscillator frequency accuracy, and the frequency multiplication factor.
[0012] According to an embodiment of this disclosure, the calculation of the correlation cost function within a second search window based on a second step size to obtain a second frequency offset estimation result includes: determining an intermediate frequency offset estimation result corresponding to the maximum value of the correlation cost function based on the second search range and the second step size; calculating the phase difference between the received signal and the pilot signal based on the intermediate frequency offset estimation result; linearly fitting the phase difference between the received signal and the pilot signal to obtain a curve relating the phase change rate to time; and determining the second frequency offset estimation result based on the curve relating the phase change rate to time.
[0013] According to an embodiment of this disclosure, determining the frequency offset compensation result based on the compensation signal generated from the received signal and the second frequency offset estimation result includes: generating the compensation signal based on the second frequency offset estimation result and the time series of the received signal, wherein the time series of the received signal is determined based on the sampling information of the received signal; and obtaining the frequency offset compensation result based on the product of the compensation signal and the received signal.
[0014] Another aspect of this disclosure provides a frequency offset compensation device for a terahertz communication system, wherein the frequency offset compensation device includes: a signal generation module for determining a baseband signal based on sequence information of a pseudo-random sequence; a signal processing module for performing signal processing on the baseband signal based on a frequency offset signal and a noise signal to obtain a received signal; a first calculation module for calculating a correlation cost function within a first search window based on a first step size to obtain a first frequency offset estimation result; a second calculation module for calculating the correlation cost function within a second search window based on a second step size to obtain a second frequency offset estimation result; and a compensation result determination module for determining a frequency offset compensation result based on a compensation signal generated from the received signal and the second frequency offset estimation result.
[0015] Another aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the method described in any of the preceding descriptions.
[0016] The frequency offset compensation method for terahertz communication systems provided in the embodiments of this disclosure enhances the resistance of frequency offset estimation to channel noise by introducing a pseudo-random sequence with constant envelope and ideal autocorrelation characteristics as a pilot signal. In addition, by calculating the correlation of the cost function and combining a coarse and fine two-stage frequency offset estimation method, the approximate range of frequency offset is quickly locked by coarse estimation, and the estimation result is further optimized by fine correction, which effectively reduces the amount of computation and can maintain high estimation accuracy even when the signal-to-noise ratio is low. Efficient frequency offset estimation is achieved in the range of frequency offset up to ±1 GHz. Attached Figure Description
[0017] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:
[0018] Figure 1 A flowchart illustrating a frequency offset compensation method for a terahertz communication system according to an embodiment of the present disclosure is shown schematically.
[0019] Figure 2 A schematic diagram illustrating a first frequency offset estimation result according to a specific embodiment of the present disclosure is shown.
[0020] Figure 3 A schematic diagram illustrating a second frequency offset estimation result according to a specific embodiment of the present disclosure is shown.
[0021] Figure 4 The diagram illustrates the signal waveforms before and after compensation according to a specific embodiment of the present disclosure.
[0022] Figure 5 A schematic diagram of the compensated signal power spectral density according to a specific embodiment of the present disclosure is shown.
[0023] Figure 6 A schematic diagram illustrating the compensated frequency offset estimate according to a specific embodiment of the present disclosure is shown.
[0024] Figure 7 A schematic diagram illustrating the compensated frequency offset estimation error according to a specific embodiment of the present disclosure is shown.
[0025] Figure 8 A block diagram schematically illustrates a frequency offset compensation device for a terahertz communication system according to an embodiment of the present disclosure; and
[0026] Figure 9 A block diagram of an electronic device for a frequency offset compensation method for a terahertz communication system according to an embodiment of the present disclosure is shown schematically. Detailed Implementation
[0027] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.
[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.
[0029] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.
[0030] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).
[0031] With the rapid development of modern communication technology, terahertz communication, with its ultra-wide bandwidth and high-speed transmission capabilities, has become one of the main candidates for next-generation communication technology. However, the high-frequency characteristics of terahertz communication systems make frequency offset problems particularly significant. These frequency offset problems are mainly caused by frequency mismatch between the transmitter and receiver and the Doppler effect. Specifically, due to the non-ideals of hardware components, the local oscillators at the transmitting and receiving ends may have frequency deviations; furthermore, in mobile communication scenarios, the relative motion between the transmitting and receiving ends can cause frequency shifts. Therefore, frequency offset problems can lead to inter-symbol interference (ISI) and signal demodulation failures, thus severely affecting the performance of the communication system.
[0032] Existing frequency offset estimation methods are mostly geared towards traditional wireless communication systems, primarily targeting narrowband or intermediate frequency communication environments. However, in the terahertz band, terahertz signals are often generated through microwave local oscillator frequency doubling (e.g., 10GHz local oscillator). From 100 times the frequency to 1THz, even a tiny frequency error (e.g., 1 ppm) in a crystal oscillator, after being amplified by frequency multiplication, can result in an actual frequency offset reaching hundreds of MHz or even GHz levels, leading to a large frequency offset value. Simultaneously, due to the extremely short wavelength in the terahertz band (e.g., 0.3 mm for 1 THz), even a small relative speed between the transmitter and receiver in a moving scenario can cause a significant Doppler shift. Furthermore, ultra-wideband signals are more sensitive to frequency offset; even a small residual frequency offset can introduce severe phase rotation and inter-symbol interference. Traditional pilot-based phase interpolation methods cannot guarantee phase continuity in wideband channels, leading to signal distortion after compensation. Therefore, traditional frequency offset estimation methods, at this level of frequency offset, have insufficient search range and slow convergence speed, resulting in estimation failure, significantly reduced convergence and accuracy, and failing to meet the ultra-wideband and high-speed transmission requirements of terahertz communication systems.
[0033] To address the aforementioned issues, embodiments of this disclosure provide a frequency offset compensation method for terahertz communication systems. By introducing a pseudo-random sequence with constant envelope and ideal autocorrelation characteristics as a pilot signal, the resistance of frequency offset estimation to channel noise is enhanced. Furthermore, through correlation calculation of the cost function and combining a coarse and fine two-stage frequency offset estimation method, the approximate range of the frequency offset is quickly determined through coarse estimation, followed by fine correction to further optimize the estimation results. This effectively reduces the computational load and maintains high estimation accuracy even under low signal-to-noise ratio conditions, achieving high accuracy even with frequency offsets as high as [insert value here]. Efficient frequency offset estimation was achieved within the specified range.
[0034] Specifically, embodiments of this disclosure provide a frequency offset compensation method for a terahertz communication system, comprising: determining a baseband signal based on sequence information of a pseudo-random sequence; performing signal processing on the baseband signal based on a frequency offset signal and a noise signal to obtain a received signal; calculating a correlation cost function within a first search window based on a first step length to determine a first frequency offset estimation result; calculating a correlation cost function within a second search window based on a second step length to obtain a second frequency offset estimation result; and determining a frequency offset compensation result based on a compensation signal generated from the received signal and the second frequency offset estimation result.
[0035] It should be noted that the frequency offset compensation method, apparatus, and electronic equipment for terahertz communication systems determined in the embodiments of this disclosure can be used in the field of terahertz communication technology. The frequency offset compensation method, apparatus, and electronic equipment for terahertz communication systems determined in the embodiments of this disclosure can also be used in any field other than the technical field of this disclosure, such as the field of high-frequency signal processing technology. The application fields of the frequency offset compensation method, apparatus, and electronic equipment for terahertz communication systems determined in the embodiments of this disclosure are not limited.
[0036] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.
[0037] Figure 1 A flowchart illustrating a frequency offset compensation method for a terahertz communication system according to an embodiment of the present disclosure is shown.
[0038] like Figure 1 As shown, the frequency offset compensation method includes operations S110~S150.
[0039] In operation S110, the baseband signal is determined based on the sequence information of the pseudo-random sequence.
[0040] In operation S120, the baseband signal is processed based on the frequency deviation signal and noise signal to obtain the received signal.
[0041] In operation S130, the correlation cost function is calculated within the first search window based on the first step length to determine the first frequency offset estimation result.
[0042] In operation S140, the correlation cost function is calculated within the second search window based on the second step size to obtain the second frequency offset estimation result.
[0043] In operation S150, the frequency offset compensation result is determined based on the compensation signal generated by the received signal and the second frequency offset estimation result.
[0044] According to embodiments of this disclosure, in a communication system, a pseudo-random sequence can be used as a data source. By performing encoding and modulation on the pseudo-random sequence, it can be converted into a baseband signal suitable for transmission. The pseudo-random sequence may include a non-binary complex sequence (such as a Zadoff-Chu sequence) possessing a constant envelope, ideal autocorrelation, and cross-correlation, and can be used as a random access preamble sequence to achieve synchronization channel estimation.
[0045] According to specific embodiments of this disclosure, the sequence information of the Zadoff-Chu sequence may include sequence length and sequence root index, wherein the sequence length can be used to determine the synchronization accuracy and frequency domain characteristics of the pseudo-random sequence, and the sequence root index can be used to determine the generation method and periodicity of the pseudo-random sequence.
[0046] Specifically, compared to traditional pseudo-random sequences (such as m-sequences and Gold sequences), the Zadoff-Chu sequence possesses ideal autocorrelation characteristics, meaning that the sequence length and root index satisfy the coprime condition (gcd(L,r)=1). In this case, the cyclic autocorrelation function of the Zadoff-Chu sequence exhibits an ideal impulse response at zero frequency offset and zero sidelobes at non-zero frequency offsets. Therefore, this coprime condition ensures that the phase increment maintains a globally linear characteristic, allowing the phase rotation caused by frequency offset to be accurately estimated through linear regression, thus enabling high-precision frequency offset compensation.
[0047] Furthermore, since the Zadoff-Chu sequence has a constant envelope characteristic and a low peak-to-average power ratio (PAPR), which is always 0 dB, significantly lower than other pseudo-random sequences, the use of the Zadoff-Chu sequence in the specific embodiments of this disclosure can improve the anti-interference capability of the system in terahertz communication systems.
[0048] According to embodiments of this disclosure, when the sequence length and root index of the Zadoff-Chu sequence satisfy the coprime condition, a pilot signal is generated based on this sequence information, and a baseband signal is obtained by signal processing the pilot signal.
[0049] According to embodiments of this disclosure, the baseband signal can be transmitted through a wireless channel to obtain a received signal including frequency deviation and Gaussian noise.
[0050] According to embodiments of this disclosure, in order to estimate the carrier frequency deviation of the received signal, the frequency deviation result can be determined by two frequency deviation estimations.
[0051] Specifically, the correlation cost function is calculated within the first search window based on the first step length to determine the first frequency offset estimation result. Based on the first frequency offset estimation result, the second search window and the second step length are determined, and the correlation cost function is calculated within the second search window based on the second step length to obtain the second frequency offset estimation result.
[0052] According to embodiments of this disclosure, the correlation cost function can be defined as a correlation measure between the received signal and the pilot signal determined based on a pseudo-random sequence.
[0053] Specifically, for each pilot signal within the search window, its frequency is offset according to the frequency offset assumption, and then its correlation with the received signal is calculated. This calculation process traverses the entire search window and generates a cost function value for each pilot signal. Based on multiple cost function values within the search window, the frequency offset estimate is determined.
[0054] According to embodiments of this disclosure, a first search window can be used to characterize the coarse search frequency range of the first frequency offset estimation, i.e., the set of possible frequency offset values. For example, the first search window can be configured as [-1GHz, +1GHz].
[0055] According to embodiments of this disclosure, the first step length can be used to characterize the frequency resolution when searching within a coarse search range. The first step length can be determined to be a large value to quickly narrow down the possible frequency offset range. For example, in the case of a first search window of [-1 GHz, +1 GHz], the first step length can be configured to 1 MHz or 200 kHz.
[0056] According to embodiments of this disclosure, the first frequency offset estimation result can be used to characterize the optimal frequency offset value obtained by calculating the correlation cost function based on the first step length within the first search window.
[0057] According to embodiments of this disclosure, the second search window can be determined based on the first frequency offset estimation result. For example, using the first frequency offset estimation result as the search center, a smaller second search window is determined, such as [-1MHz, +1MHz]. This ensures that a sufficiently fine frequency search can be performed within the second search window.
[0058] According to embodiments of this disclosure, the second step size can be determined based on the first step size and the signal-to-noise ratio. The second step size can be configured to 10 kHz.
[0059] According to embodiments of this disclosure, the correlation cost function is calculated within a second search window based on a second step size, and the resulting optimal frequency offset value can be used as the second frequency offset estimation result.
[0060] According to embodiments of this disclosure, during the frequency offset compensation process, a compensation signal can be generated based on the received signal and the second frequency offset estimation result, and the frequency offset in the received signal can be eliminated by the compensation signal, so that the center frequency of the compensated signal spectrum is restored to the frequency of the original signal.
[0061] According to embodiments of this disclosure, after frequency offset compensation of the received signal, the accuracy of frequency offset compensation can be verified and evaluated by calculating the power spectral density and frequency offset estimation error of the signal before and after compensation.
[0062] Based on this, the embodiments of this disclosure enhance the resistance of frequency offset estimation to channel noise by introducing a pseudo-random sequence with constant envelope and ideal autocorrelation characteristics as a pilot signal. Furthermore, by calculating the correlation of the cost function and combining a coarse and fine two-stage frequency offset estimation method, the approximate range of the frequency offset is quickly determined through coarse estimation, followed by fine correction to further optimize the estimation results. This effectively reduces the computational load and maintains high estimation accuracy even under low signal-to-noise ratio conditions, achieving high frequency offsets. Efficient frequency offset estimation was achieved within the specified range.
[0063] According to embodiments of this disclosure, determining a baseband signal based on sequence information of a pseudo-random sequence includes: determining a pilot signal based on sequence information of a pseudo-random sequence; mapping multiple data symbols onto a carrier signal using an orthogonal amplitude modulation method to generate a modulation signal; and concatenating the pilot signal and the modulation signal to obtain the baseband signal.
[0064] According to embodiments of this disclosure, pilot signals can be generated using the root index and length of the Zadoff-Chu sequence. Specifically, the pilot signals are generated as follows:
[0065] (1);
[0066] In the formula, Z(n) represents the pilot signal, L represents the sequence length, r represents the sequence root index, and n represents the element index included in the sequence. Since the sequence length and sequence root index must satisfy the coprime condition gcd(L,r)=1, in the specific embodiments of this disclosure, the sequence length L of the Zadoff-Chu sequence can be configured as 1533, and the sequence root index r is configured as 25.
[0067] According to embodiments of this disclosure, a quadrature amplitude modulation (QAM) method can be used to map binary data into data symbols, and then the data symbols can be mapped onto a carrier signal to obtain a modulated signal. The modulated signal can be used to represent a complex-valued signal obtained by mapping random data symbols onto a carrier signal.
[0068] According to embodiments of this disclosure, the modulation signal and the pilot signal are concatenated to obtain a complete frame signal, which is then used as the baseband signal. The baseband signal is represented as follows:
[0069] (2);
[0070] In the formula, Z(n) represents the baseband signal, Z(n) represents the pilot signal, and d i Represents the modulated signal, where, .
[0071] According to embodiments of this disclosure, the data symbol generation step includes: generating multiple random binary data based on the orthogonal amplitude modulation order; and searching the multiple random binary data using a constellation diagram to obtain multiple data symbols.
[0072] For example, in quadrature amplitude modulation of order M, each data symbol requires k = log2(M) binary bits. Specifically, in 1024-order QAM modulation, since 2 10 =1024, so each data symbol represents 10 binary bits. Therefore, the generated random binary data sequence is: ,in According to the QAM modulation rules, binary data is mapped to complex numerical symbols. Specifically, the 10 binary bits are divided into two groups of 5 binary bits each. Each group of binary bits is converted into a decimal integer to obtain the real and imaginary indices of the data symbol. Based on the real and imaginary indices, the corresponding data symbol in the QAM constellation diagram is found. The above steps are repeated to obtain multiple data symbols.
[0073] Based on this, embodiments of this disclosure generate pilot signals using pseudo-random sequences (such as Zadoff-Chu sequences). In complex channel environments, these pilot signals can achieve signal synchronization quickly and accurately, reducing the bit error rate and improving the system's robustness to frequency offset, time delay, and multipath effects. Furthermore, mapping random binary data to high-order QAM symbols enables high-speed data transmission within a limited bandwidth, improving the spectral efficiency of the communication system.
[0074] According to embodiments of this disclosure, signal processing is performed on the baseband signal based on the frequency deviation signal and the noise signal to obtain the received signal, including: upsampling the baseband signal based on a linear interpolation method to obtain an intermediate tether signal; pulse shaping the intermediate baseband signal using a raised cosine filter to obtain a transmitted signal; and determining the received signal based on the frequency deviation signal and the noise signal during the transmission of the transmitted signal in the wireless channel.
[0075] According to embodiments of this disclosure, the sampling rate of the baseband signal is increased to the system sampling rate using interpolation methods such as zero interpolation or linear interpolation to obtain an intermediate baseband signal, thereby meeting the high-precision sampling requirements. The sampling rate of the baseband signal can be expressed as the symbol rate Rs, and the system sampling rate can be expressed as Fs. In a specific embodiment of this disclosure, the symbol rate Rs can be configured to 20 GHz to support high-speed data transmission; the system sampling rate Fs can be configured to 60 GHz to meet the sampling requirements of terahertz high-frequency, high-bandwidth signals.
[0076] According to embodiments of this disclosure, the upsampled intermediate baseband signal is pulse-shaped using a pulse-shaping filter, such as a raised cosine filter, to obtain the transmitted signal. The transmitted signal is represented as follows:
[0077] (3);
[0078] In the formula, s(t) represents the transmitted signal, s up h(t) represents the intermediate baseband signal, and h(t) represents the pulse shaping filter. This represents the convolution operation.
[0079] According to embodiments of this disclosure, due to the frequency offset or Doppler effect of the local oscillator at the transceiver end, the transmitted signal will be introduced with frequency offset and Gaussian white noise during transmission through the wireless channel. Therefore, the received signal is represented as follows:
[0080] (4);
[0081] In the formula, r(t) represents the received signal, and f offset The frequency offset of the received signal is represented by n(t), and the noise signal is represented by n(t).
[0082] According to embodiments of this disclosure, when there is a frequency offset f offset In this case, the phase change of the received signal r(t) is as follows:
[0083] (5);
[0084] In the formula, T represents the phase of the received signal in the frequency domain. s Indicates the sampling period. Indicates additive phase noise. The frequency offset value f of the received signal offset In one specific embodiment of this disclosure, the number of observations N=L=1533. ,in, , representing the phase noise variance.
[0085] According to an embodiment of this disclosure, calculating the correlation cost function within a first search window based on the first step length to determine the first frequency offset estimation result includes: performing Fast Fourier Transform on the received signal and the pilot signal respectively to calculate the cross power spectral density of the received signal and the pilot signal in the frequency domain; determining the correlation cost function between the received signal and the pilot signal based on the cross power spectral density; and determining the first frequency offset estimation result corresponding to the maximum value of the correlation cost function within the first search window based on the first step length.
[0086] According to embodiments of this disclosure, a first search window can be used to characterize the frequency search range for performing a coarse frequency offset search on the received signal to quickly determine the initial value of the frequency offset. This frequency search range can be determined based on the local oscillator signal frequency, the crystal oscillator frequency accuracy, and the frequency doubling order. Specifically, the frequency search range = Microwave local oscillator signal frequency Crystal oscillator frequency accuracy (ppm) Frequency multiplication Doppler frequency shift. The frequency harmonic can be used to represent the number of times the frequency is multiplied from microwave to terahertz, while the Doppler frequency shift can be used to represent the frequency shift caused by the relative motion between the transmitter and receiver.
[0087] In a specific embodiment of this disclosure, when the microwave local oscillator signal frequency is f LO =10GHz, crystal oscillator frequency accuracy of 2ppm, frequency doubling order of M=10, Doppler frequency shift of f doppler In the case of 1MHz, the frequency search range is: To cover the possible frequency offset range and improve estimation efficiency, the search range can be set to... The step size is 1MHz.
[0088] According to a specific embodiment of this disclosure, multiple frequency offset sampling points are determined within the first search window at intervals of one step length. For each frequency offset sampling point, a Fast Fourier Transform is performed on the received signal and pilot signal corresponding to that frequency point to calculate the cross-power spectral density of the received signal and pilot signal in the frequency domain, thereby obtaining the correlation cost function between the received signal and pilot signal. Specifically, the correlation cost function is represented as follows:
[0089] (6);
[0090] In the formula, J(f) represents the correlation cost function, f represents the frequency offset value to be estimated, r(n) represents the received signal at the nth frequency offset sampling point, Z(n) represents the pilot signal at the nth frequency offset sampling point, and N P T represents the number of sampling points for the pilot signal. s This represents the sampling period. Where N is the number of sampling points for the pilot signal.P It can be determined based on the number of sampling points λ for each data symbol and the sequence length λ of the Zadoff-Chu sequence. For example, .
[0091] According to a specific embodiment of this disclosure, the correlation cost function is calculated in parallel within the first search window, and the frequency offset value corresponding to the maximum value of the correlation cost function is determined as the first frequency offset estimation result.
[0092] (7);
[0093] In the formula, This represents the result of the first frequency offset estimation.
[0094] Figure 2 A schematic diagram illustrating a first frequency offset estimation result according to a specific embodiment of the present disclosure is shown.
[0095] like Figure 2 As shown, the correlation cost function is calculated in parallel within the first search window. The maximum value of the determined correlation cost function is the peak value of the curve. The calculated value of the correlation cost function is approximately 1540, and the corresponding frequency offset estimate is approximately 400MHz. Further fine frequency offset estimation is then performed within a relatively small range near this frequency offset estimate.
[0096] Based on this, the embodiments of this disclosure utilize a correlation cost function to quantify the matching degree between the received signal and the pilot signal, enabling the method to have stronger resistance to frequency offset and effectively support the high bandwidth and high data rate requirements of terahertz communication. When the frequency offset is small, the cost function value is large, and vice versa. By maximizing the cost function within a large search range, a rough frequency offset value is initially estimated, and the approximate range of the frequency offset is quickly locked.
[0097] According to embodiments of this disclosure, the correlation cost function is calculated within a second search window based on a second step size to obtain a second frequency offset estimation result, including: determining an intermediate frequency offset estimation result corresponding to the maximum value of the correlation cost function based on a second search range and a second step size; calculating the phase difference between the received signal and the pilot signal based on the intermediate frequency offset estimation result; performing linear fitting on the phase difference between the received signal and the pilot signal to obtain a curve relating the phase change rate to time; and determining the second frequency offset estimation result based on the curve relating the phase change rate to time.
[0098] According to embodiments of this disclosure, the second search window and the second step size are narrowed based on the first frequency offset estimation result to improve resolution. The second step size can be calculated based on the first step size and the signal-to-noise ratio. The specific calculation method is as follows:
[0099] (8);
[0100] In the formula, Indicates the second step length. K represents the first step length, and K represents the signal-to-noise ratio.
[0101] For example, by narrowing the second search window to [-1MHz, 1MHz], the second step size can be reduced to 10kHz when the first step size is 1MHz and the signal-to-noise ratio is 100.
[0102] According to embodiments of this disclosure, multiple relevance cost functions are calculated within a second search window based on a second step size. The frequency offset value corresponding to the maximum value of the multiple relevance cost functions is used as the intermediate frequency offset estimation result. The intermediate frequency offset estimation result is represented as follows:
[0103] (9);
[0104] In the formula, This represents the intermediate frequency offset estimation result.
[0105] According to embodiments of this disclosure, while ensuring that the received signal and the pilot signal are aligned in the time domain, the phase difference between the received signal and the pilot signal is calculated at the frequency sampling point corresponding to the intermediate frequency offset estimation result. A linear fit is then performed on this phase difference to obtain a curve relating the phase change rate to time. The second frequency offset estimation result is calculated based on the slope of this curve. Specifically, the second frequency offset estimation result is represented as follows:
[0106] (10);
[0107] (11);
[0108] In the formula, f represents the slope. fine This represents the result of the second frequency offset estimation.
[0109] Figure 3 A schematic diagram illustrating a second frequency offset estimation result according to a specific embodiment of the present disclosure is shown.
[0110] like Figure 3 As shown, the correlation cost function is calculated in parallel within the second search window. The maximum value of the determined correlation cost function is the peak value of the curve, which is approximately 1534.6. The corresponding frequency offset estimate is approximately 399.98MHz.
[0111] Based on this, the embodiments of this disclosure, by performing a coarse estimation within a first search range and then a fine search using a smaller step size and a narrower search range, help to further reduce the error range of frequency offset estimation and improve the accuracy of the estimation. Through a two-stage estimation method combining coarse and fine estimation, the computational load is significantly reduced and the search time is shortened, avoiding the performance degradation of traditional methods under large frequency offset conditions. Simultaneously, it maintains high estimation accuracy even with a large frequency offset range, thus achieving a breakthrough in rapid response capability and computational efficiency in practical communication scenarios.
[0112] According to embodiments of this disclosure, determining a frequency offset compensation result based on a compensation signal generated from the received signal and a second frequency offset estimation result includes: generating a compensation signal based on the second frequency offset estimation result and a time series of the received signal; and obtaining the frequency offset compensation result based on the product of the compensation signal and the received signal.
[0113] According to embodiments of this disclosure, the compensation signal can be generated based on the second frequency offset estimation result and a time series. The phase of the compensation signal changes linearly with time to compensate for the frequency offset in the received signal. The time series can be generated based on the sampling rate of the received signal (i.e., the system sampling rate) and the number of sampling points. Specifically, the time series and the compensation signal are represented as follows:
[0114] (12);
[0115] (13);
[0116] In the formula, t represents the time series, N represents the number of sampling points of the received signal, and s comp (t) represents the compensation signal, and Ts represents the sampling period, which can be based on the sampling rate F of the received signal. s Sure.
[0117] According to embodiments of this disclosure, the received signal is multiplied by the compensation signal to obtain a frequency offset compensation signal, thereby eliminating frequency offset interference and restoring the correct frequency of the signal. Specifically, the frequency offset compensation signal is represented as follows:
[0118] (14);
[0119] In the formula, r comp (t) represents the frequency offset compensation signal.
[0120] According to embodiments of this disclosure, after determining the frequency offset compensation signal, the frequency offset compensation result can be verified based on the power spectral density of the signals before and after compensation.
[0121] Figure 4 The diagram illustrates the signal waveforms before and after compensation according to a specific embodiment of the present disclosure.
[0122] like Figure 4 As shown, after compensating for the frequency offset of the received signal using the above method, it can be seen that the frequency offset compensated signal obtained in the time domain is close to the original signal without frequency offset.
[0123] Figure 5 A schematic diagram of the compensated signal power spectral density according to a specific embodiment of the present disclosure is shown.
[0124] like Figure 5 As shown, after compensating for the frequency offset of the received signal using the above method, it can be seen that the power spectral density of the frequency offset compensated signal is close to the theoretical value.
[0125] According to embodiments of this disclosure, the compensation accuracy of the above-described frequency offset compensation method can also be evaluated through the frequency offset estimation error. Specifically, the frequency offset estimation error is calculated as follows:
[0126] (15);
[0127] In the formula, Error represents the frequency offset estimation error, f offset f represents the frequency offset of the received signal. fine This represents the result of the second frequency offset estimation.
[0128] Figure 6 A schematic diagram illustrating the compensated frequency offset estimate according to a specific embodiment of the present disclosure is shown.
[0129] like Figure 6 As shown, after compensating for the frequency offset of the received signal using the above method, it can be seen that the second frequency offset estimation result is 399.981035MHz, the actual frequency offset value of the received signal is 400MHz, the frequency offset estimation error is less than 1kHz, and the frequency offset estimation value of the frequency offset compensated signal is close to the actual value.
[0130] Based on this, the embodiments of this disclosure can significantly reduce the frequency difference between the received and transmitted signals through accurate frequency offset estimation and compensation signal generation. This helps improve signal synchronization accuracy and ensures the stability and reliability of data during transmission. Frequency offset compensation can effectively compensate for signal distortion under complex channel conditions, thereby reducing the bit error rate.
[0131] Figure 7 A schematic diagram illustrating the compensated frequency offset estimation error according to a specific embodiment of the present disclosure is shown.
[0132] like Figure 7 As shown, after compensating for the frequency offset of the received signal using the above method, the calculated frequency offset estimation error is 0.004741%, which is less than 0.1%.
[0133] Figure 8 A block diagram of a frequency offset compensation device for a terahertz communication system according to an embodiment of the present disclosure is shown schematically.
[0134] like Figure 8 As shown, the frequency offset compensation device 800 of the terahertz communication system includes a signal generation module 810, a signal processing module 820, a first calculation module 830, a second calculation module 840, and a compensation result determination module 850.
[0135] The signal generation module 810 is used to determine the baseband signal based on the sequence information of the pseudo-random sequence, wherein the sequence information of the pseudo-random sequence includes the sequence length and the sequence root index.
[0136] The signal processing module 820 is used to process the baseband signal based on the frequency deviation signal and the noise signal to obtain the received signal.
[0137] The first calculation module 830 is used to calculate the correlation cost function within the first search window based on the first step length, and obtain the first frequency offset estimation result.
[0138] The second calculation module 840 is used to calculate the correlation cost function within the second search window based on the second step size, and obtain the second frequency offset estimation result.
[0139] The compensation result determination module 850 is used to determine the frequency offset compensation result based on the compensation signal generated by the received signal and the second frequency offset estimation result.
[0140] According to embodiments of this disclosure, the signal generation module 810 includes a pilot signal generation unit, a modulation signal generation unit, and a signal splicing unit.
[0141] The pilot signal generation unit is used to determine the pilot signal based on the sequence information of the pseudo-random sequence.
[0142] The modulation signal generation unit is used to map multiple data symbols onto a carrier signal based on the quadrature amplitude modulation method to generate a modulation signal.
[0143] The signal splicing unit is used to splice the pilot signal and the modulation signal to obtain the baseband signal.
[0144] According to embodiments of this disclosure, the signal generation module 810 further includes a data generation unit and a data symbol determination unit.
[0145] The data generation unit is used to generate multiple random binary data based on the quadrature amplitude modulation order.
[0146] The data symbol determination unit is used to search multiple random binary data using a constellation diagram to obtain multiple data symbols.
[0147] According to embodiments of this disclosure, the signal processing module 820 includes an upsampling unit, a pulse shaping unit, and a received signal determination unit.
[0148] The upsampling unit is used to upsample the baseband signal based on a linear interpolation method to obtain the intermediate tether signal.
[0149] The pulse shaping unit is used to perform pulse shaping processing on the intermediate baseband signal using a raised cosine filter to obtain the transmitted signal.
[0150] The received signal determination unit is used to determine the received signal based on the frequency offset signal and noise signal of the transmitted signal during the wireless channel transmission process.
[0151] According to an embodiment of this disclosure, the first calculation module 830 includes a signal transformation unit, a cost function determination unit, and a first result determination unit.
[0152] The signal transformation unit is used to perform fast Fourier transform on the received signal and the pilot signal respectively, and calculate the cross power spectral density of the received signal and the pilot signal in the frequency domain.
[0153] The cost function determination unit is used to determine the correlation cost function between the received signal and the pilot signal based on the cross power spectral density.
[0154] The first result determination unit is used to determine the first frequency offset estimation result corresponding to the maximum value of the correlation cost function within the first search window, based on the first step length.
[0155] According to embodiments of this disclosure, the first calculation module 830 further includes a search range determination unit.
[0156] The search range determination unit is used to determine the first search window and the first step length based on the local oscillator signal frequency, crystal oscillator frequency accuracy, and frequency multiplication factor.
[0157] According to embodiments of this disclosure, the second calculation module 840 includes an intermediate result determination unit, a phase calculation unit, a fitting unit, and a second result determination unit.
[0158] The intermediate result determination unit is used to determine the intermediate frequency offset estimation result corresponding to the maximum value of the correlation cost function based on the second search range and the second step size.
[0159] The phase calculation unit is used to calculate the phase difference between the received signal and the pilot signal based on the intermediate frequency offset estimation result.
[0160] The fitting unit is used to linearly fit the phase difference between the received signal and the pilot signal to obtain the relationship curve between the phase change rate and time.
[0161] The second result determination unit is used to determine the second frequency offset estimation result based on the relationship curve between the phase change rate and time.
[0162] According to embodiments of this disclosure, the compensation result determination module 850 includes a compensation signal generation unit and a compensation result determination unit.
[0163] The compensation signal generation unit is used to generate a compensation signal based on the second frequency offset estimation result and the time series of the received signal.
[0164] The compensation result determination unit is used to obtain the frequency offset compensation result based on the product of the compensation signal and the received signal.
[0165] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-a-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.
[0166] For example, any and more of the signal generation module 810, signal processing module 820, first calculation module 830, second calculation module 840, and compensation result determination module 850 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least some of the functions of one or more of these modules / units / subunits can be combined with at least some of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the signal generation module 810, signal processing module 820, first calculation module 830, second calculation module 840, and compensation result determination module 850 can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the signal generation module 810, signal processing module 820, first calculation module 830, second calculation module 840, and compensation result determination module 850 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.
[0167] It should be noted that the frequency offset compensation device part of the terahertz communication system in the embodiments of this disclosure corresponds to the frequency offset compensation method part of the terahertz communication system in the embodiments of this disclosure. For a detailed description of the frequency offset compensation device of the terahertz communication system, please refer to the frequency offset compensation method part of the terahertz communication system, which will not be repeated here.
[0168] Figure 9 A block diagram of an electronic device for a frequency offset compensation method for a terahertz communication system according to an embodiment of the present disclosure is shown schematically. Figure 9 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.
[0169] like Figure 9As shown, an electronic device according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory ROM 902 or a program loaded from a storage portion 908 into a random access memory RAM 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.
[0170] RAM 903 stores various programs and data required for the operation of the electronic device. Processor 901, ROM 902, and RAM 903 are interconnected via bus 904. Processor 901 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 902 and / or RAM 903. It should be noted that the programs may also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.
[0171] According to embodiments of this disclosure, the electronic device may further include an input / output (I / O) interface 905, which is also connected to a bus 904. The electronic device may also include one or more of the following components connected to the input / output (I / O) interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the input / output (I / O) interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 910 as needed so that computer programs read from it can be installed into the storage section 908 as needed.
[0172] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 909, and / or installed from removable medium 911. When the computer program is executed by processor 901, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.
[0173] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.
[0174] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
[0175] For example, according to embodiments of this disclosure, a computer-readable storage medium may include the ROM 902 and / or RAM 903 described above and / or one or more memories other than ROM 902 and RAM 903.
[0176] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the frequency offset compensation method for the terahertz communication system provided in the embodiments of this disclosure.
[0177] When the computer program is executed by the processor 901, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.
[0178] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 909, and / or installed from a removable medium 911. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.
[0179] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include, but are not limited to, languages such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).
[0180] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.
[0181] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.
Claims
1. A frequency offset compensation method for a terahertz communication system, wherein, The frequency offset compensation method includes: Based on the sequence information of a pseudo-random sequence, the baseband signal is determined, wherein the pseudo-random sequence includes a Zadoff-Chu sequence, and the sequence information of the Zadoff-Chu sequence includes the sequence length and the sequence root index, wherein the sequence length and the sequence root index satisfy the coprime condition. The baseband signal is processed based on the frequency deviation signal and the noise signal to obtain the received signal; The correlation cost function is calculated within the first search window based on the first step length to determine the first frequency offset estimation result, wherein the correlation cost function is determined based on the sequence information of the pseudo-random sequence and the received signal; The relevance cost function is calculated within a second search window based on a second step size to obtain a second frequency offset estimation result, wherein the second search window and the second step size are determined based on the first frequency offset estimation result; and The frequency offset compensation result is determined based on the compensation signal generated by the received signal and the second frequency offset estimation result.
2. The frequency offset compensation method according to claim 1, wherein, The determination of the baseband signal based on the sequence information of the pseudo-random sequence includes: Based on the sequence information of the pseudo-random sequence, the pilot signal is determined; A modulated signal is generated by mapping multiple data symbols onto a carrier signal using an orthogonal amplitude modulation method, wherein the data symbols are obtained by mapping multiple random binary data; and The baseband signal is obtained by splicing the pilot signal and the modulation signal.
3. The frequency offset compensation method according to claim 2, wherein, The method further includes: Based on the quadrature amplitude modulation order, multiple random binary data are generated; and By using a constellation diagram to search the multiple random binary data, multiple data symbols are obtained.
4. The frequency offset compensation method according to claim 1, wherein, The signal processing of the baseband signal based on the frequency deviation signal and the noise signal to obtain the received signal includes: The baseband signal is upsampled using a linear interpolation method to obtain the intermediate tether signal. The intermediate baseband signal is pulse-shaped using a raised cosine filter to obtain the transmitted signal; and The received signal is determined based on the frequency offset signal and the noise signal during the transmission of the transmitted signal in the wireless channel.
5. The frequency offset compensation method according to claim 2, wherein, The step of calculating the relevance cost function within the first search window based on the first step length to determine the first frequency offset estimation result includes: The fast Fourier transform is performed on the received signal and the pilot signal respectively to calculate the cross power spectral density of the received signal and the pilot signal in the frequency domain. Based on the cross-power spectral density, determine the correlation cost function between the received signal and the pilot signal; and Based on the first step length, a first frequency offset estimation result corresponding to the maximum value of the correlation cost function is determined within the first search window.
6. The frequency offset compensation method according to claim 5, wherein, The method further includes: Based on the local oscillator signal frequency, crystal oscillator frequency accuracy, and frequency multiplication factor, the first search window and the length of the first step are determined.
7. The frequency offset compensation method according to claim 1, wherein, The calculation of the relevance cost function within the second search window based on the second step size to obtain the second frequency offset estimation result includes: Based on the second search range and the second step size, determine the intermediate frequency offset estimation result corresponding to the maximum value of the correlation cost function; Based on the intermediate frequency offset estimation result, the phase difference between the received signal and the pilot signal is calculated; A linear fit is performed on the phase difference between the received signal and the pilot signal to obtain a curve showing the relationship between the phase change rate and time; and Based on the relationship curve between the phase change rate and time, the second frequency offset estimation result is determined.
8. The frequency offset compensation method according to claim 1, wherein, The determination of the frequency offset compensation result based on the compensation signal generated from the received signal and the second frequency offset estimation result includes: Based on the second frequency offset estimation result and the time series of the received signal, the compensation signal is generated, wherein the time series of the received signal is determined based on the sampling information of the received signal; and The frequency offset compensation result is obtained based on the product of the compensation signal and the received signal.
9. A frequency offset compensation device for a terahertz communication system, wherein, The frequency offset compensation device includes: A signal generation module is used to determine a baseband signal based on the sequence information of a pseudo-random sequence, wherein the pseudo-random sequence includes a Zadoff-Chu sequence, and the sequence information of the Zadoff-Chu sequence includes the sequence length and the sequence root index, wherein the sequence length and the sequence root index satisfy a coprime condition. The signal processing module is used to perform signal processing on the baseband signal based on the frequency deviation signal and the noise signal to obtain the received signal; The first calculation module is used to calculate the correlation cost function within the first search window based on the first step length to obtain the first frequency offset estimation result, wherein the correlation cost function is determined based on the sequence information of the pseudo-random sequence and the received signal; The second calculation module is used to calculate the relevance cost function within a second search window based on a second step size, to obtain a second frequency offset estimation result, wherein the second search window and the second step size are determined based on the first frequency offset estimation result; and The compensation result determination module is used to determine the frequency offset compensation result based on the compensation signal generated by the received signal and the second frequency offset estimation result.
10. An electronic device, comprising: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 8.