Oqam-dft-s-ofdm waveform phase noise estimation method

Abstract

This application relates to an OQAM-DFT-s-OFDM waveform phase noise estimation method, belonging to the field of wireless communication technology. This application maintains low complexity at the transmitter by jointly generating PTRS modulation symbols and data modulation symbols at the transmitter and transmitting OQAM real and imaginary parts separately, which is beneficial for hardware implementation. At the receiver, the corresponding PTRS modulation symbols extracted from the filtered OQAM signal within the PTRS block are summed using real and imaginary methods to obtain a first signal and a second signal. The first signal is multiplied by a first preset coefficient to obtain a third signal, and the second signal is multiplied by a second preset coefficient to obtain a fourth signal. By using the imaginary difference between the multiples of the first and second preset coefficients, the PTRS modulation symbol as a reference signal can be eliminated, thus obtaining a fifth signal. The phase of this fifth signal is the phase noise, reducing the impact of interference on the estimated phase noise value.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to an OQAM-DFT-s-OFDM waveform phase noise estimation method. Background Technology

[0002] Terahertz and Asia Pacific Hertz (APH) communications, due to their ultra-wide bandwidth characteristics, have become key technologies used in 6G wireless systems. However, their high carrier frequencies bring severe power amplifier (PA) nonlinearity and significant phase noise problems, posing stringent requirements for waveform design. Low peak-to-average power ratio (PAPR) and high spectral efficiency are the core performance indicators for 6G waveform design in the terahertz / APH bands. Discrete Fourier transform-spread orthogonal frequency division multiplexing (DFT-s-OFDM) has become a candidate waveform for this scenario due to its inherent PAPR advantage. However, traditional DFT-s-OFDM struggles to simultaneously achieve low PAPR, high spectral efficiency, and robustness to phase noise and PA nonlinearity.

[0003] The Offset Quadrature Amplitude Modulation (OQAM) combined with DFT-s-OFDM forms the Offset Quadrature Amplitude Modulation-Discrete Fourier Transform-spread Orthogonal Frequency Division Multiplexing (OQAM-DFT-s-OFDM) waveform. By transmitting the real and imaginary parts of the complex modulation symbols separately, it further reduces PAPR and possesses excellent out-of-band radiation suppression characteristics, making it a preferred waveform for terahertz communication. However, the time-domain structured interference generated by the separate transmission of the real and imaginary parts in the OQAM-DFT-s-OFDM waveform causes the phase noise estimation assumptions of the traditional Phase Tracking Reference Signal (PTRS) scheme to fail. The receiver cannot effectively distinguish between the useful PTRS signal and interference, resulting in extremely low phase noise estimation accuracy and a degraded system demodulation performance.

[0004] Existing PTRS improvement schemes for OQAM-DFT-s-OFDM (such as redundant PTRS and joint PTRS) require complex interference control and signal processing at the transmitter, which increases the complexity of hardware implementation and has the problem of excessively high average PTRS power, affecting the overall transmission performance of the system.

[0005] In addition, the strong phase noise and PA nonlinearity superposition in terahertz communication scenarios further exacerbate the difficulty of phase noise estimation of OQAM-DFT-s-OFDM waveforms. Existing solutions cannot achieve reliable phase tracking in this harsh channel environment, which restricts the practical application of OQAM-DFT-s-OFDM waveforms in 6G terahertz communication.

[0006] Therefore, it is necessary to provide a new technical solution to improve one or more of the problems existing in the above solutions.

[0007] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] The purpose of this application is to provide an OQAM-DFT-s-OFDM waveform phase noise estimation method, thereby overcoming one or more problems caused by the limitations and defects of related technologies to a certain extent.

[0009] An OQAM-DFT-s-OFDM waveform phase noise estimation method provided in the embodiments of this application includes: The transmitting end combines PTRS modulation symbols and data modulation symbols to form a complex modulation symbol sequence to be transmitted; The complex modulation symbol sequence is subjected to OQAM real and imaginary part separation, and an OQAM symbol sequence is constructed; The OQAM symbol sequence is sequentially subjected to DFT spread spectrum, FDSS filtering, IDFT modulation and signal conversion processing to obtain the OQAM-DFT-s-OFDM waveform. The OQAM-DFT-s-OFDM waveform is recorded as the OQAM signal and transmitted through the terahertz channel. The receiving end receives the OQAM signal, performs frequency domain demodulation and filtering, extracts the corresponding PTRS modulation symbol within the PTRS block from the filtered OQAM signal, and performs real-domain summation on the PTRS modulation symbol to obtain the first signal, and performs imaginary-domain summation on the PTRS modulation symbol to obtain the second signal. The first signal is multiplied by a first preset coefficient to obtain the third signal, and the second signal is multiplied by a second preset coefficient to obtain the fourth signal; wherein the multipliers between the first preset coefficient and the second preset coefficient differ by an imaginary number; The third signal and the fourth signal are summed to obtain the fifth signal. The phase noise estimate of the fifth signal is then calculated.

[0010] In the embodiments of this application, the step of the transmitting end jointly generating PTRS modulation symbols and data modulation symbols to form a complex modulation symbol sequence to be transmitted includes: The PTRS modulation symbol is obtained by modulating the PTRS pseudo-random sequence using M-PSK. The data bits are modulated using M-QAM to obtain the data modulation symbol; The PTRS modulation symbols are evenly inserted into the data modulation symbols in units of PTRS blocks to form the complex modulation symbol sequence.

[0011] In the embodiments of this application, the expression of the complex modulation symbol sequence is as follows: (1) In the formula, Represents a complex modulation symbol sequence. Represents the real part of the complex modulation symbol sequence. The imaginary part of the complex modulation symbol sequence is represented by j, where j represents the imaginary number. Indicates the index of the complex modulation symbol sequence.

[0012] In the embodiments of this application, the OQAM symbol sequence satisfies the following conditions: When the index of the OQAM symbol sequence is even, (2) When the index of the OQAM symbol sequence is odd, (3) In the formula, Represents the OQAM symbol sequence, Indicates the index of the OQAM symbol sequence.

[0013] In the embodiments of this application, the PTRS modulation symbols include real-domain PTRS modulation symbols and virtual-domain PTRS modulation symbols.

[0014] In the embodiments of this application, the summation of the real number field represents all positions within the PTRS block where the real-field PTRS modulation symbol is located, and the summation of the imaginary number field represents all positions within the PTRS block where the imaginary-field PTRS modulation symbol is located.

[0015] In the embodiments of this application, the receiving end receives the OQAM signal, performs frequency domain demodulation and filtering, extracts the corresponding PTRS modulation symbols within the PTRS block from the filtered OQAM signal, and performs real-domain summation on the PTRS modulation symbols to obtain a first signal, and performs imaginary-domain summation on the PTRS modulation symbols to obtain a second signal, the steps of which include: The expression for the first signal is as follows: (4) In the formula, Indicates the first signal. Represents the real part of the first signal. Let j represent the imaginary part of the first signal, and j represent the imaginary number. This represents the weighting coefficient for the real part. Represents real-domain PTRS modulation symbols. This indicates the number of PTRS modulation symbols within each PTRS block. The odd index representing the OQAM symbol sequence, 'm' represents the PTRS block index. Let m be the starting index of the m-th PTRS block. Represents the phase factor. Represents the real part of the phase factor. Represents the imaginary part of the phase factor. This represents the interference of the imaginary part of a real signal. Noise representing a real signal; The expression for the second signal is as follows: (5) In the formula, Indicates the second signal. This represents the real part of the second signal. Indicates the imaginary part of the second signal. Indicates the imaginary part weighting coefficient. Represents the virtual domain PTRS modulation symbol. The even index of the OQAM symbol sequence. This represents the interference of the real part of the virtual signal. Noise representing a virtual signal.

[0016] In the embodiments of this application, the first preset coefficient is 1 or -1, and the second preset coefficient is j or -j.

[0017] In embodiments of this application, the step of summing the third signal and the fourth signal to obtain a fifth signal, and calculating the phase noise estimate of the fifth signal, includes: When the first preset coefficient is 1, the expression for the fifth signal is as follows: (6) In the formula, Indicates the fifth signal. Noise representing a real signal; The phase factor is calculated from the fifth signal, and the phase noise is obtained by solving it; wherein the expression for the phase factor is as follows: (7) In the formula, Represents the phase factor. Indicates phase noise; =angle(e jθ[m] (8) In the formula, angle(e jθ[m] This indicates that the phase factor is solved; The phase noise estimate of the fifth signal is obtained by interpolating the phase noise of each PTRS block.

[0018] In the embodiments of this application, the expression for the phase noise estimate of the fifth signal is as follows: (9) In the formula, This represents the estimated phase noise value of the fifth signal.

[0019] The technical solutions provided by the embodiments of this application may include the following beneficial effects: In one embodiment of this application, the above method achieves several advantages. First, it eliminates the need for complex interference control at the transmitting end. Only the joint generation of PTRS modulation symbols and data modulation symbols, along with the separate transmission of OQAM real and virtual components, at the transmitting end maintains low complexity and facilitates hardware implementation. Second, at the receiving end, the corresponding PTRS modulation symbols extracted from the filtered OQAM signal within the PTRS block are summed using real and virtual components to obtain a first signal and a second signal. The first signal is multiplied by a first preset coefficient to obtain a third signal, and the second signal is multiplied by a second preset coefficient to obtain a fourth signal. Since the multiples between the first and second preset coefficients differ by an imaginary number, the PTRS modulation symbol reference signal can be eliminated, resulting in a fifth signal. The phase of this fifth signal is the phase noise, reducing the impact of interference on the phase noise estimation. By summing and jointly solving the real and virtual components of the PTRS modulation symbols at the receiving end, phase noise estimation under structured interference is achieved. This approach maintains low complexity at the transmitting end and low power characteristics of PTRS, adapting to communication environments with strong terahertz phase noise and PA nonlinearity.

[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0022] Figure 1 This schematically illustrates a flowchart of the steps of the OQAM-DFT-s-OFDM waveform phase noise estimation method in an exemplary embodiment of this application; Figure 2 This schematically illustrates the processing flowchart involved in the transmitter of the OQAM-DFT-s-OFDM system in an exemplary embodiment of this application; Figure 3 This schematically illustrates the processing flowchart involved in the receiver of the OQAM-DFT-s-OFDM system in an exemplary embodiment of this application; Figure 4 This schematic diagram illustrates the time-domain distribution of the complex modulation symbol sequence in an exemplary embodiment of this application. Figure 5 The diagram illustrates the distribution of PTRS blocks in an exemplary embodiment of this application. Figure 6 The illustration schematically shows the PAPR test results under 64QAM, 60 resource blocks, and orthogonal frequency division multiplexing with cyclic prefix in an exemplary embodiment of this application; Figure 7 The illustration shows the error vector magnitude test results under 16QAM and 60 resource blocks in an exemplary embodiment of this application. Detailed Implementation

[0023] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0024] Furthermore, the accompanying drawings are merely illustrative of this application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore, repeated descriptions of them will be omitted.

[0025] This example implementation provides a method for estimating the phase noise of an OQAM-DFT-s-OFDM waveform. (Reference) Figure 1 As shown, the method may include steps S101 to S106.

[0026] In step S101, the transmitting end combines the PTRS modulation symbols and the data modulation symbols to form a complex modulation symbol sequence to be transmitted.

[0027] Step S102: Separate the real and imaginary parts of the complex modulation symbol sequence into OQAM and construct the OQAM symbol sequence.

[0028] Step S103: Perform DFT spread spectrum, FDSS filtering, IDFT modulation and signal conversion processing on the OQAM symbol sequence in sequence to obtain the OQAM-DFT-s-OFDM waveform. Record the OQAM-DFT-s-OFDM waveform as the OQAM signal and transmit it through the terahertz channel.

[0029] Step S104: The receiving end receives the OQAM signal, performs frequency domain demodulation and filtering, extracts the corresponding PTRS modulation symbol within the PTRS block from the filtered OQAM signal, and sums the PTRS modulation symbols in the real domain to obtain the first signal, and sums the PTRS modulation symbols in the imaginary domain to obtain the second signal.

[0030] Step S105: Multiply the first signal by the first preset coefficient to obtain the third signal, and multiply the second signal by the second preset coefficient to obtain the fourth signal; wherein the multiples between the first preset coefficient and the second preset coefficient differ by an imaginary number.

[0031] Step S106: Summate the third signal and the fourth signal to obtain the fifth signal, and calculate the phase noise estimate of the fifth signal.

[0032] In one embodiment of this application, the above method achieves several advantages. First, it eliminates the need for complex interference control at the transmitting end. Only the joint generation of PTRS modulation symbols and data modulation symbols, along with the separate transmission of OQAM real and virtual components, at the transmitting end maintains low complexity and facilitates hardware implementation. Second, at the receiving end, the corresponding PTRS modulation symbols extracted from the filtered OQAM signal within the PTRS block are summed using real and virtual components to obtain a first signal and a second signal. The first signal is multiplied by a first preset coefficient to obtain a third signal, and the second signal is multiplied by a second preset coefficient to obtain a fourth signal. Since the multiples between the first and second preset coefficients differ by an imaginary number, the PTRS modulation symbol reference signal can be eliminated, resulting in a fifth signal. The phase of this fifth signal is the phase noise, reducing the impact of interference on the phase noise estimation. By summing and jointly solving the real and virtual components of the PTRS modulation symbols at the receiving end, phase noise estimation under structured interference is achieved. This approach maintains low complexity at the transmitting end and low power characteristics of PTRS, adapting to communication environments with strong terahertz phase noise and PA nonlinearity.

[0033] Below, we will refer to Figures 2 to 5 The steps of the method described above in this example embodiment will be explained in more detail.

[0034] Before explaining the waveform phase noise estimation method of OQAM-DFT-s-OFDM, we will first introduce the processing flow involved at the transmitter and receiver of the OQAM-DFT-s-OFDM system.

[0035] like Figure 2 As shown, at the transmitter of the OQAM-DFT-s-OFDM system, it mainly completes six key steps: data bit modulation, PTRS pseudo-random sequence modulation → OQAM real and imaginary component time-domain separation and reconstruction → DFT spread spectrum → Frequency-Domain Spectral Shaping (FDSS) filtering → Inverse Discrete Fourier Transform (IDFT) modulation → Digital-to-Analog Converter (DAC), RF up-conversion, and transmission. These steps are detailed below: (1) Data bit modulation, PTRS pseudo-random sequence modulation Data bits are modulated using M-ary Quadrature Amplitude Modulation (M-QAM) and PTRS pseudo-random sequences are modulated using M-ary Phase Shift Keying (M-PSK) to form complex modulated symbol sequences. The expression for the complex modulated symbol sequence is as follows: (1) In the formula, Represents a complex modulation symbol sequence. Represents the real part of the complex modulation symbol sequence. The imaginary part of the complex modulation symbol sequence is represented by j, where j represents the imaginary number. Indicates the index of the complex modulation symbol sequence.

[0036] When data bits are modulated into data modulation symbols, the complex modulation symbol sequence... The values ​​are random modulation values, which follow a uniform distribution of M-QAM constellation points; When a PTRS pseudo-random sequence is modulated into PTRS modulation symbols, the complex modulation symbol sequence Known constants (such as ±Q±jQ, where Q can be the real or imaginary part of the outermost constellation point of QAM) are used for subsequent phase noise estimation.

[0037] (2) OQAM real and imaginary components temporal domain separation and reconstruction The process of separating and reconstructing the real and imaginary components in the time domain of OQAM is the main difference between OQAM-DFT-s-OFDM and traditional DFT-s-OFDM. This involves reconstructing the real and imaginary components of the complex modulation symbol sequence in the time domain. The imaginary part of the complex modulated symbol sequence The symbols are separated and reconstructed into a real-virtual symbol sequence of twice the length, i.e., the OQAM symbol sequence, to achieve staggered transmission of time-domain location.

[0038] The OQAM symbol sequence satisfies the following condition: When the index of the OQAM symbol sequence is even, (2) When the index of the OQAM symbol sequence is odd, (3) In the formula, Represents the OQAM symbol sequence, Indicates the index of the OQAM symbol sequence. When When it is even, that is = ,when When it is an odd number, that is = As can be seen from formula (2), the real part is transmitted at even positions of the OQAM symbol sequence, and as can be seen from formula (3), the imaginary part is transmitted at odd positions of the OQAM symbol sequence. For the index of the OQAM symbol sequence, further, It is the time-domain index of the OQAM symbol sequence, with real and imaginary symbols being transmitted alternately in the time domain. =2 or 2 +1, the length of the complex modulation symbol sequence is from Expand to Completely avoiding the superposition of real and imaginary parts at the same time domain position is the main guarantee for low PAPR. Indicates the DFT length. This indicates a length of twice the DFT.

[0039] (3) DFT spread spectrum For the reconstructed OQAM symbol sequence Performing DFT spread spectrum, DFT spread spectrum refers to Pointed DFT spreading completes the spreading and converts the signal to the frequency domain. The expression for the frequency domain signal is as follows: (10) in, Represents frequency domain signals, Indicates the frequency domain subcarrier index. Indices representing the index of a complex modulation symbol sequence, This represents the DFT factor, compared to N in traditional DFT-s-OFDM. DFT Compared to the point DFT, the length of the DFT here is doubled, matching the length of the OQAM symbol sequence after real-to-virtual separation.

[0040] (4) FDSS filtering To further reduce PAPR and optimize spectral characteristics, the frequency domain signal of the DFT output is... Perform FDSS filtering, using the filter factor Weighted shaping is performed on the frequency domain signal, and the filtered frequency domain signal is retained as follows: The main function of filtering is to suppress out-of-band radiation of the signal, while smoothing the frequency domain amplitude and further reducing the time domain PAPR.

[0041] (5) IDFT modulation The frequency domain signal after FDSS filtering is first zero-filled, and then IDFT modulation is performed. IDFT modulation refers to N-point IDFT modulation, which converts the frequency domain signal into an oversampled time-domain baseband signal. The expression of the time-domain baseband signal is as follows: (11) in, Let n represent the time-domain baseband signal, where n ∈ {0, 1, ..., N-1}, and N represents the IDFT length. This represents the IDFT factor. Oversampling aims to improve the continuity of the time-domain baseband signal and reduce distortion in subsequent radio frequency processing, such as... Figure 4 As shown.

[0042] (6) DAC, RF upconversion and transmission The time-domain baseband signal output by IDFT After sequential DAC, RF upconversion, and power amplification, the OQAM signal is obtained and finally transmitted through the antenna; Due to the low PAPR characteristic of OQAM's real-virtual separation, the signal's sensitivity to PA nonlinearity is much lower than that of traditional Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM), eliminating the need for large output back-off (OBO) and improving transmission efficiency.

[0043] The signal demodulation process at the receiving end is as follows: like Figure 3 As shown, the receiver mainly completes eight key steps: reception, RF down-conversion and analog-to-digital (ADC) conversion → DFT processing → Nyquist filtering and channel compensation → zero-filling and IDFT processing → OQAM structured interference extraction and characterization → PTRS-based phase noise estimation and compensation → real-virtual component separation and interference cancellation → complex modulation symbol sequence reconstruction and data demodulation. The key challenge is addressing the deterministic structured interference introduced by OQAM real-virtual component separation (the root cause of traditional PTRS failure). The specific process is as follows: (1) Receiving, RF downconversion and ADC After receiving the OQAM signal, the receiver sequentially performs low-noise amplification, RF down-conversion (shifting to baseband), and ADC to obtain the baseband received signal. The sampling rate of the baseband received signal is consistent with the sampling rate of the time-domain baseband signal at the transmitting end. The expression for the baseband received signal is as follows: (12) In the formula, Indicates the baseband received signal. This represents the time-domain phase noise introduced by the terahertz high-frequency carrier. This indicates a random phase shift, which can cause signal constellation point rotation and degrade demodulation performance. This represents additive white Gaussian noise. , Represents variance. This indicates that the expression follows a pattern with a mean of 0 and a variance of 0. The Gaussian distribution.

[0044] During channel transmission, the transmitted signal (i.e., the OQAM signal) is transmitted to the receiver through a terahertz wireless channel. Two main types of impairments (typical characteristics of terahertz communication) are introduced into the channel: time-domain phase noise and additive white Gaussian noise.

[0045] (2) DFT processing Baseband received signal Performing DFT processing, specifically N-point DFT processing, converts the time-domain baseband signal into a frequency-domain signal, achieving impairment separation in the time and frequency domains. The expression for the frequency-domain signal is as follows: (13) in, Represents frequency domain signals, This is frequency domain phase noise, which is derived from random phase shift θ[n]. Indicates the filter factor. For frequency domain noise, This represents additive white Gaussian noise in the time domain. The frequency domain noise is obtained by performing a DFT on the additive white Gaussian noise in the time domain.

[0046] (3) Nyquist filtering and channel compensation If the transmitter's FDSS filter is not an ideal Nyquist filter, the filter factor needs to be replaced with ideal Nyquist filter coefficients. Simultaneously, preliminary compensation for channel fading is performed to obtain the corrected frequency domain signal. The expression for the corrected frequency domain signal is as follows: (14) In the formula, This represents the corrected frequency domain signal. This represents the coefficients of an ideal Nyquist filter. The main function of Nyquist filtering is to eliminate inter-symbol interference introduced by FDSS filtering at the transmitter and channel transmission, thus ensuring the orthogonality of the signals.

[0047] (4) Zero padding and IDFT processing To match the length of the OQAM symbol sequence after real-to-virtual separation at the transmitter, the corrected frequency domain signal is zero-padded to the length. Then perform IDFT processing. IDFT refers to... Pointed IDFT processing converts the corrected frequency domain signal into a time domain baseband signal, yielding the recovered real-to-virtual symbol sequence, i.e., the recovered OQAM symbol sequence. The expression for the recovered OQAM symbol sequence is as follows: (15) in, This represents the recovered OQAM symbol sequence. Indicates the index of the recovered OQAM symbol sequence. The impulse response of the Nyquist filter. To recover noise in the time domain, Indicates phase noise, This represents the phase noise factor.

[0048] (5) OQAM structured interference extraction and characterization OQAM structured interference extraction and characterization is a crucial step at the receiver end of an OQAM-DFT-s-OFDM system. Because real and virtual components are transmitted separately in the time domain, It introduces deterministic structured interference (which is absent in traditional DFT-s-OFDM), and the main characteristics of the interference are as follows: Odd positions in the OQAM symbol sequence =2 The imaginary part of the +1 symbol is disturbed by the real part of the OQAM symbol sequence at even positions. Even positions of the OQAM symbol sequence =2 The real part of the symbol is disturbed by the imaginary part of the OQAM symbol sequence at odd positions; There is no interference between signs in the same odd or even position, and the interference of the real part sign is a pure imaginary number, while the interference of the imaginary part sign is a pure real number.

[0049] The finally recovered OQAM symbol sequence can be represented in the following form with interference: (16) in, Phase noise representing the position of the real part. Phase noise factor representing the position of the imaginary part. The time-domain reconstruction noise representing the location of the real part. Phase noise representing the position of the imaginary part. The phase noise factor representing the position of the real part. The time-domain recovery noise represents the location of the imaginary part. For the imaginary interference of the real part sign, To prevent real number interference with the sign of the imaginary part, and Both are deterministic values ​​where sending and receiving are predictable.

[0050] (6) Phase noise estimation and compensation based on PTRS Traditional DFT-s-OFDM's PTRS fails because it does not consider structured interference from OQAM. The receiver needs to perform phase noise estimation. The main idea is to take advantage of the determinism of the interference, design the interference value as a constant value known to both the transmitter and receiver, and then solve for the phase noise factor using the PTRS modulation symbols. The phase noise is obtained through the above PTRS estimation. Afterwards, Phase compensation is performed to obtain the phase-compensated OQAM symbol sequence. This eliminates the effects of phase noise.

[0051] (7) Separation of real and virtual components and cancellation of interference Phase-compensated OQAM symbol sequence Perform real-to-virtual component separation. Extract the real part from the even-numbered positions of the phase-compensated OQAM symbol sequence: =Re{ Extract the imaginary part from the odd positions of the phase-compensated OQAM symbol sequence: =Im{ Finally, the real and imaginary components, free from interference and phase noise, are recovered. This represents the real part of the phase-compensated OQAM symbol sequence. Indicates index 2 OQAM symbol sequence, Re represents the phase noise factor at even positions in the OQAM symbol sequence, where Re{·} denotes taking the real part. This represents the imaginary part of the phase-compensated OQAM symbol sequence. Indicates index 2 +1 OQAM symbol sequence, The phase noise factor represents the odd-numbered positions of the OQAM symbol sequence, and Im{·} denotes taking the imaginary part.

[0052] (8) Reconstruction of complex modulated symbol sequences and data demodulation The real part of the phase-compensated OQAM symbol sequence The imaginary part of the phase-compensated OQAM symbol sequence Reconstructed into the recovered complex modulation symbol sequence = +j Then, through M-QAM inverse modulation and M-PSK inverse modulation (such as 64QAM inverse mapping), the complex modulation symbol sequence is converted into a binary bit stream, completing the final data demodulation. Among them, 64QAM stands for 64-Quadrature Amplitude Modulation, which means 64th-order quadrature amplitude modulation.

[0053] Figure 4 The figure shows the time-domain distribution of the complex modulation symbol sequence, including imaginary signal j1, imaginary signal j2, real signal 1, and real signal 2. The imaginary signal refers to the imaginary part of the complex modulation symbol sequence, and the real signal refers to the real part. j1 and j2 are used to distinguish between different imaginary signals.

[0054] In existing technologies, PTRS schemes for DFT-s-OFDM are mainly based on interference-free reference symbol design. This involves uniformly inserting M-PSK modulated PTRS symbols into the data modulation symbols, and then using known PTRS values ​​for phase noise estimation at the receiver. However, this scheme cannot adapt to the structured interference characteristics of OQAM-DFT-s-OFDM, and the receiver cannot separate the interference from the useful reference signal, resulting in phase noise estimation failure. To address this issue, existing improved schemes often control interference by designing redundant PTRS or using combined PTRS. However, these schemes increase the signal processing complexity at the transmitter, and some schemes suffer from excessively high PTRS power, affecting the overall system transmission performance.

[0055] The following section will elaborate on the relevant content of PTRS.

[0056] For OFDM, the reference signal densities for both uplink and downlink can be configured identically. This configuration can include both the frequency domain density and the time domain density of the reference signal.

[0057] In one example, the temporal density configuration of the reference signal can be as shown in Table 1.

[0058] Table 1. Configuration of the temporal density of the reference signal Among them, I MCS The MCS (Modulation Sequence) refers to the data carried on the data signal corresponding to the reference signal. Typically, the MCS can include at least one of the following parameters: modulation order, target code rate, and spectral efficiency. ptrs-MCS is the threshold for the MCS. Taking modulation order as an example, ptrs-MCS1 indicates a modulation order of 2, ptrs-MCS2 indicates a modulation order of 4, and ptrs-MCS3 indicates a modulation order of 6. That is, if the modulation order is less than 2, there is no reference signal in the time domain density, and correspondingly, no reference signal in the frequency domain density. If the modulation order is greater than or equal to 2 and less than 4, there is one reference signal in every four time units in the time domain density. Here, a time unit can be a time slot, symbol, mini-time slot, subframe, or radio frame, etc., which is not specifically limited in this application. If the modulation order is greater than or equal to 4 and less than 6, there is one reference signal in every two time units in the time domain density, and so on.

[0059] In one example, the frequency domain density of the reference signal can be configured as shown in Table 2.

[0060] Table 2. Frequency domain density configuration of the reference signal Among them, scheduling bandwidth usually refers to the bandwidth scheduled by downlink control information messages, N RB N represents the number of resource blocks. RB0 N represents the first threshold number of resource blocks. RB1 N represents the second threshold number of resource blocks. RB0 and N RB1 The value of can be flexibly configured, and this application does not limit it. If the number of resource blocks corresponding to the scheduling block is less than the first threshold number of resource blocks, there is no reference signal in the frequency domain density, and correspondingly, there is no reference signal in the time domain density. If the number of resource blocks corresponding to the scheduling block is greater than or equal to the first threshold number of resource blocks, and the number of resource blocks is less than the second threshold number of resource blocks, there are 2 reference signals in the frequency domain density. If the number of resource blocks corresponding to the scheduling block is greater than or equal to the second threshold number of resource blocks, there are 4 reference signals in the frequency domain density.

[0061] For DFT-s-OFDM, the reference signal density typically depends on the scheduling bandwidth; therefore, only the reference signal density in the frequency domain is considered, as shown in Table 3. Where N... RB2 N represents the third threshold number of resource blocks. RB3 N represents the fourth threshold number of resource blocks. RB4This represents the fifth threshold for the number of resource blocks. The values ​​from the first to the fifth threshold for the number of resource blocks can be flexibly configured and are not limited. If the number of resource blocks corresponding to the scheduling bandwidth is greater than or equal to the first threshold for the number of resource blocks, and the number of resource blocks is less than the second threshold for the number of resource blocks, then the scheduling bandwidth has 2 reference signal blocks, and each reference signal block has 2 reference signals. It can be seen that if the number of resource blocks corresponding to the scheduling bandwidth is greater than or equal to the second threshold for the number of resource blocks, and the number of resource blocks is less than the third threshold for the number of resource blocks, then the scheduling bandwidth has 2 reference signal blocks, and each reference signal block has 4 reference signals. If the number of resource blocks corresponding to the scheduling bandwidth is greater than or equal to the third threshold for the number of resource blocks, and the number of resource blocks is less than the fourth threshold for the number of resource blocks, then the scheduling bandwidth has 4 reference signal blocks, and each reference signal block has 2 reference signals. If the number of resource blocks corresponding to the scheduling bandwidth is greater than or equal to the fourth threshold for the number of resource blocks, and the number of resource blocks is less than the fifth threshold for the number of resource blocks, then the scheduling bandwidth has 4 reference signal blocks, and each reference signal block has 4 reference signals. If the number of resource blocks corresponding to the scheduling bandwidth is greater than or equal to the fifth threshold of the number of resource blocks, then there are 8 reference signal blocks in the scheduling bandwidth, and each reference signal block contains 4 reference signals.

[0062] It should be understood that Tables 1 to 3 above can all be scheduled by signaling, such as radio resource control messages, downlink control messages, media access control-control element messages, etc., without any specific limitations.

[0063] Table 3 shows the number of reference signal blocks and the configuration of the number of reference signals within each reference signal block. N represents the IDFT length, which is typically the number of sampling points in the time domain after the OFDM time-domain transform, i.e., the number of points in the IDFT. The OFDM time-domain transform is the IDFT. Therefore, N is the number of sampling points. Regarding the use of PTRS blocks, an OFDM symbol contains N sampling points, and M PTRS blocks are evenly inserted among these N sampling points. Each PTRS block contains... One PTRS modulation symbol. M represents the number of PTRS blocks. For example... Figure 5 As shown, an OFDM symbol contains 5 PTRS blocks, and each PTRS block contains 4 PTRS modulation symbols.

[0064] The steps of the OQAM-DFT-s-OFDM waveform phase noise estimation method are described below.

[0065] In step S101, the transmitting end combines the PTRS modulation symbols and data modulation symbols to generate a complex modulation symbol sequence to be transmitted.

[0066] In one embodiment, step S101 includes the following: The PTRS pseudo-random sequence is modulated using M-PSK to obtain the PTRS modulation symbol; Data bits are modulated using M-QAM to obtain data modulation symbols; The PTRS modulation symbols are evenly inserted into the data modulation symbols in units of PTRS blocks to form a complex modulation symbol sequence.

[0067] It is understandable that the power of the PTRS modulation symbol matches the outermost constellation point of the data modulation symbol, and the complex modulation symbol sequence includes the real part and the imaginary part of the complex modulation symbol sequence.

[0068] The PTRS pseudo-random sequence is modulated using M-PSK to obtain PTRS modulation symbols, and the data bits are modulated using M-QAM to obtain PTRS modulation symbols. The PTRS modulation symbols are then uniformly inserted into the data modulation symbols in PTRS blocks to form a complex modulation symbol sequence.

[0069] Furthermore, the expression for the complex modulation symbol sequence is as shown in the aforementioned formula (1), which will not be elaborated upon here.

[0070] In step S102, the complex modulation symbol sequence is separated into real and imaginary parts using OQAM, and an OQAM symbol sequence is constructed.

[0071] Specifically, this step is the same as the aforementioned process of separating and reconstructing the real and imaginary components of OQAM in the time domain, and will not be described in detail here. The real part and the imaginary part of the complex modulation symbol sequence are separated and reconstructed into an OQAM symbol sequence of twice the length, thereby achieving staggered transmission in the time domain.

[0072] Furthermore, the conditions satisfied by the OQAM symbol sequence are shown in the aforementioned formulas (2) and (3), which will not be elaborated upon here.

[0073] In one embodiment, the PTRS modulation symbols include real-domain PTRS modulation symbols and virtual-domain PTRS modulation symbols.

[0074] Specifically, all real-domain PTRS modulation symbols within the PTRS block have the same sign, meaning that all real-domain PTRS modulation symbols within the PTRS block are either all positive or all negative. Similarly, all imaginary-domain PTRS modulation symbols within the PTRS block have the same sign, meaning that all imaginary-domain PTRS modulation symbols within the PTRS block are either all positive or all negative. In this case, the phase noise estimation performance is the best.

[0075] After separating the real and virtual domains of the PTRS modulation symbols within a PTRS block, it can be divided into real-domain PTRS modulation symbols and virtual-domain PTRS modulation symbols. The real-domain PTRS modulation symbols include all positions within the PTRS block where the real-domain PTRS modulation symbols reside. The location; the virtual domain PTRS modulation symbol includes all locations of the virtual domain PTRS modulation symbols within the PTRS block, that is... Location.

[0076] In one embodiment, the summation in the real field represents all positions within the PTRS block where the real-field PTRS modulation symbol is located, and the summation in the imaginary field represents all positions within the PTRS block where the imaginary-field PTRS modulation symbol is located.

[0077] Specifically, all positions within the PTRS block containing the real-domain PTRS modulation symbol are odd-numbered index positions after separating the real and virtual domains of the PTRS modulation symbol, while all positions within the PTRS block containing the virtual-domain PTRS modulation symbol are even-numbered index positions after separating the real and virtual domains of the PTRS modulation symbol.

[0078] In step S103, the OQAM symbol sequence is sequentially subjected to DFT spread spectrum, FDSS filtering, IDFT modulation and signal conversion processing to obtain the OQAM-DFT-s-OFDM waveform. The OQAM-DFT-s-OFDM waveform is recorded as the OQAM signal and transmitted through the terahertz channel.

[0079] It is understandable that performing DFT spreading on the reconstructed OQAM symbol sequence refers to performing DFT spreading on the reconstructed OQAM symbol sequence. Point DFT spread spectrum is performed to complete the spread spectrum and convert it into a frequency domain signal. The expression of the frequency domain signal is shown in the aforementioned formula (10).

[0080] After FDSS filtering of the frequency domain signal, N-point IDFT modulation is performed to generate a time-domain baseband signal, the expression of which is shown in the aforementioned formula (11). Then, the time-domain baseband signal is processed by signal conversion to obtain an OQAM signal, which is then transmitted through a terahertz channel. The transmitter does not require additional interference control or PTRS modulation symbol optimization, maintaining the same signal processing flow as the traditional OQAM-DFT-s-OFDM, thus achieving low complexity. The FDSS filtering of the frequency domain signal can be referred to in the aforementioned FDSS filtering process, which will not be elaborated here. The signal conversion process includes DAC, RF upconversion, and power amplification. The signal conversion processing of the time-domain baseband signal and the transmission of the OQAM signal through the terahertz channel can be referred to in the aforementioned DAC, RF upconversion, and transmission process, which will not be elaborated here.

[0081] In step S104, the receiving end receives the OQAM signal, performs frequency domain demodulation and filtering, extracts the corresponding PTRS modulation symbol within the PTRS block from the filtered OQAM signal, and performs real-domain summation on the PTRS modulation symbol to obtain the first signal, and performs imaginary-domain summation on the PTRS modulation symbol to obtain the second signal.

[0082] Understandably, after receiving the OQAM signal contaminated with phase noise, PA nonlinearity, and additive white Gaussian noise, the receiving end needs to first perform the aforementioned RF down-conversion and analog-to-digital conversion process to obtain the baseband received signal. Then, the baseband received signal undergoes frequency domain demodulation and Nyquist filtering. The PTRS modulation symbol is then extracted from the filtered OQAM signal, and its real-domain summation yields the first signal, while its imaginary-domain summation yields the second signal. The PTRS modulation symbol serves as the reference signal.

[0083] It should be noted that the frequency domain modulation and Nyquist filtering of the baseband received signal can be understood by referring to the "DFT processing" process described above and the "Nyquist filtering" process in "Nyquist filtering and channel compensation". This application will not elaborate on them here.

[0084] After frequency domain demodulation and Nyquist filtering of the baseband received signal, the filtered OQAM signal is obtained. The real and imaginary components of the signal are then separated. Specifically, the PTRS modulation symbol is extracted from the filtered OQAM signal, and the first signal is obtained by summing the real number domain and the second signal is obtained by summing the imaginary number domain.

[0085] Furthermore, the expression for the first signal is as follows: (4) In the formula, Indicates the first signal. Represents the real part of the first signal. Let j represent the imaginary part of the first signal, and j represent the imaginary number. This represents the weighting coefficient for the real part. Represents real-domain PTRS modulation symbols. This indicates the number of PTRS modulation symbols within each PTRS block. The odd index representing the OQAM symbol sequence, 'm' represents the PTRS block index. Let m be the starting index of the m-th PTRS block. Represents the phase factor. Represents the real part of the phase factor. Represents the imaginary part of the phase factor. This represents the interference of the imaginary part of a real signal. Noise representing a real signal; The expression for the second signal is as follows: (5) In the formula, Indicates the second signal. This represents the real part of the second signal. Indicates the imaginary part of the second signal. Indicates the imaginary part weighting coefficient. Represents the virtual domain PTRS modulation symbol. The even index of the OQAM symbol sequence. This represents the interference of the real part of the virtual signal. Noise representing a virtual signal.

[0086] In step S105, the first signal is multiplied by a first preset coefficient to obtain the third signal, and the second signal is multiplied by a second preset coefficient to obtain the fourth signal; wherein the multiples between the first preset coefficient and the second preset coefficient differ by an imaginary number.

[0087] Furthermore, the first preset coefficient is 1 or -1, and the second preset coefficient is j or -j.

[0088] It is understandable that the third signal is obtained by multiplying the first signal by a first preset coefficient, where the first preset coefficient is denoted by 'a'. Therefore, the third signal is a( The value of 'a' can be 1 or -1. The fourth signal is obtained by multiplying the second signal by the second preset coefficient, denoted by 'b'. Therefore, the fourth signal is b(…). b can take the value j or -j.

[0089] In step S106, the third signal and the fourth signal are summed to obtain the fifth signal, and the phase noise estimate of the fifth signal is calculated.

[0090] In one embodiment, the expression for the fifth signal is as follows: (6) In the formula, Indicates the fifth signal. Noise representing a real signal; The phase factor is obtained by calculating the fifth signal, and the phase noise is obtained by solving it; the expression for the phase factor is as follows: (7) In the formula, Represents the phase factor. Indicates phase noise; =angle(ejθ[m] (8) In the formula, angle(e jθ[m] This indicates that the phase factor is solved; The phase noise estimate of the fifth signal is obtained by interpolating the phase noise of each PTRS block.

[0091] In one embodiment, the expression for the phase noise estimate of the fifth signal is as follows: (9) In the formula, This represents the estimated phase noise value of the fifth signal.

[0092] It is understandable that the multiples between the first and second preset coefficients differ by a factor of j, which can eliminate the reference signal and obtain the fifth signal. The phase of this fifth signal is the phase noise, thus reducing the impact of interference on the estimated phase noise.

[0093] Multiply the fifth signal by -j, and use... Given the characteristics of real signals, the phase factor can be separated simply by estimating the phase. The phase noise is then calculated. By interpolating the phase noise of each PTRS block, the estimated phase noise values ​​for all data symbols are obtained, thus completing the full sequence phase tracking.

[0094] The following comparison with traditional DFT-s-OFDM schemes, redundant PTRS schemes, and combined PTRS schemes will further illustrate this application.

[0095] The traditional DFT-s-OFDM scheme involves uniformly inserting PTRS modulated symbols generated by Quadrature Phase Shift Keying (QPSK) from a Gold sequence into the data symbols in a block structure. The PTRS transmit power is matched with the outermost constellation point of the data symbols. At the receiver, the data symbols within each PTRS block are superimposed in phase, and the phase noise is estimated using a least squares algorithm. The phase noise values ​​of all data symbols are obtained by interpolation. This scheme is based on the assumption of no structured interference at the receiver and is only applicable to DFT-s-OFDM systems with synchronous transmission of real and imaginary parts.

[0096] Existing technical solution 1: Redundant PTRS scheme, namely the redundant PTRS scheme of OQAM-DFT-s-OFDM. This scheme simulates the signal processing flow of the receiver at the transmitter. By designing some PTRS symbols to adjust the interference value to a specific value known at the receiver, the remaining PTRS symbols are used for phase noise estimation. This scheme achieves controllable interference through redundant PTRS symbols, but it will result in the average PTRS power being higher than that of the traditional DFT-s-OFDM PTRS average power, and the transmitter needs to perform complex interference calculations and symbol design.

[0097] Existing technical solution 2: Joint PTRS scheme, namely the joint PTRS scheme of OQAM-DFT-s-OFDM. This scheme jointly designs all PTRS symbols within a PTRS block so that the superposition of all PTRS symbols and interference within the block is a specific value known to the receiver. Phase noise estimation is achieved through this superposition. This scheme reduces PTRS power, but the transmitter needs to jointly optimize the PTRS symbols within the PTRS block, resulting in high signal processing complexity. Furthermore, the noise superposition at the receiver is correlated, which reduces the signal-to-noise ratio.

[0098] While redundant PTRS and joint PTRS schemes can achieve phase noise estimation for OQAM-DFT-s-OFDM, they both increase the signal processing complexity at the transmitter. They require calculating the interference value at the transmitter and then calculating the corresponding reference signal value based on the interference value, which is not conducive to hardware implementation. Typically, the transmitter is the terminal, and the computing chip of the terminal is much weaker than the computing chip of the base station. Therefore, these two schemes are not conducive to the implementation of terminal equipment.

[0099] Since the filter coefficients are less than 1, redundant PTRS schemes and joint PTRS schemes require additional signal power to ensure a fixed interference value. This application uses a transmitted reference signal to cancel out the interference (the fifth signal), and then uses the interference for phase noise estimation. Therefore, it does not require additional power to preset the interference value and can obtain a better phase noise estimate. Figure 6 It can be seen that this application exhibits optimal performance in terms of PAPR. Compared to the traditional DFT-s-OFDM scheme, the OQAM signal has a lower PAPR due to its more uniform signal distribution. Internally, because this application does not require additional signal power to generate the signal value, the level of surrounding interference is kept at a preset value, thus giving it optimal performance among these schemes. Regarding the modulation signal, this application introduces minimal received signal distortion error. Therefore, the amplifier does not require greater back-off power to avoid signal distortion, allowing for higher transmission power and coverage over a wider area.

[0100] from Figure 7It can be seen that, under the same amplifier power back-off, the technical solution of this application has the smallest error vector amplitude, indicating that its performance is the best. Here, 16QAM stands for 16-Quadrature Amplitude Modulation, which means 16th-order quadrature amplitude modulation.

[0101] This application enables OQAM signals to maintain low PAPR and high spectral efficiency while possessing excellent robustness to PA nonlinearity and strong phase noise in terahertz communication, making it the preferred waveform for 6G terahertz / Asia Pacific Hertz communication. The generation and insertion methods of PTRS modulation symbols are compatible with the PTRS scheme in the traditional 3rd Generation Partnership Project (3GPP) standard, adding only real and virtual domain summation and joint operation steps at the receiver, making it easy to integrate and upgrade with existing communication systems.

[0102] It should be noted that this application can be directly extended to the following scenarios.

[0103] 1. Multi-carrier scenario extension: It can be directly extended to multi-carrier OQAM-DFT-s-OFDM systems. Only an inverted phase tracking reference signal (Inverted PTRS) needs to be designed independently on each carrier to maintain the synchronous insertion and joint solution of PTRS blocks of each carrier. It is suitable for multi-carrier transmission scenarios of ultra-wideband terahertz communication. 2. Multi-antenna scenario expansion: It can be combined with multiple-input multiple-output and large-scale antenna array technologies, and independently design Inverted PTRS at each antenna port. Phase noise estimation in multi-antenna scenarios is achieved through spatial multiplexing, which is suitable for multi-antenna transmission systems of 6G terahertz communication. 3. Multi-user scenario expansion: It can be applied to terahertz multi-user access systems, allocating independent PTRS block resources to each user, and realizing parallel phase noise estimation for multiple users through resource partitioning, thereby improving the transmission performance of multi-user systems; 4. Extension to other OQAM multicarrier waveform scenarios: It can be extended to other OQAM multicarrier waveform scenarios with real and virtual parts, such as OQAM-filter bank multicarrier. By adapting to the time-domain interference characteristics of different waveforms and adjusting the weighting coefficients and joint operation methods at the receiver, phase noise estimation can be achieved. It is suitable for various low PAPR OQAM multicarrier communication systems.

[0104] It should be noted that although the steps of the method in this application are described in a specific order in the accompanying drawings, this does not require or imply that these steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps. Furthermore, it is readily understood that these steps may be executed synchronously or asynchronously, for example, in multiple modules / processes / threads.

[0105] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

Claims

1. A method for estimating phase noise of OQAM-DFT-s-OFDM waveforms, characterized in that, The method includes: The transmitting end combines PTRS modulation symbols and data modulation symbols to form a complex modulation symbol sequence to be transmitted; The complex modulation symbol sequence is subjected to OQAM real and imaginary part separation, and an OQAM symbol sequence is constructed; The OQAM symbol sequence is sequentially subjected to DFT spread spectrum, FDSS filtering, IDFT modulation and signal conversion processing to obtain the OQAM-DFT-s-OFDM waveform. The OQAM-DFT-s-OFDM waveform is recorded as the OQAM signal and transmitted through the terahertz channel. The receiving end receives the OQAM signal, performs frequency domain demodulation and filtering, extracts the corresponding PTRS modulation symbol within the PTRS block from the filtered OQAM signal, and performs real-domain summation on the PTRS modulation symbol to obtain the first signal, and performs imaginary-domain summation on the PTRS modulation symbol to obtain the second signal. The first signal is multiplied by a first preset coefficient to obtain the third signal, and the second signal is multiplied by a second preset coefficient to obtain the fourth signal; wherein the multipliers between the first preset coefficient and the second preset coefficient differ by an imaginary number; The third signal and the fourth signal are summed to obtain the fifth signal. The phase noise estimate of the fifth signal is then calculated.

2. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 1, characterized in that, The step of generating a complex modulation symbol sequence to be transmitted by jointly generating PTRS modulation symbols and data modulation symbols at the transmitting end includes: The PTRS modulation symbol is obtained by modulating the PTRS pseudo-random sequence using M-PSK. The data bits are modulated using M-QAM to obtain the data modulation symbol; The PTRS modulation symbols are evenly inserted into the data modulation symbols in units of PTRS blocks to form the complex modulation symbol sequence.

3. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 1, characterized in that, The expression for the complex modulation symbol sequence is as follows: （1） In the formula, Represents a complex modulation symbol sequence. Represents the real part of the complex modulation symbol sequence. The imaginary part of the complex modulation symbol sequence is represented by j, where j represents the imaginary number. Indicates the index of the complex modulation symbol sequence.

4. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 3, characterized in that, The OQAM symbol sequence satisfies the following condition: When the index of the OQAM symbol sequence is even, (2) When the index of the OQAM symbol sequence is odd, (3) In the formula, Represents the OQAM symbol sequence, Indicates the index of the OQAM symbol sequence.

5. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 1, characterized in that, The PTRS modulation symbols include real-domain PTRS modulation symbols and virtual-domain PTRS modulation symbols.

6. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 5, characterized in that, The summation in the real field represents all positions within the PTRS block where the real-field PTRS modulation symbol is located, and the summation in the imaginary field represents all positions within the PTRS block where the imaginary-field PTRS modulation symbol is located.

7. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 1, characterized in that, The steps of receiving the OQAM signal, performing frequency domain demodulation and filtering, extracting the corresponding PTRS modulation symbols within the PTRS block from the filtered OQAM signal, summing the PTRS modulation symbols in the real domain to obtain a first signal, and summing the PTRS modulation symbols in the imaginary domain to obtain a second signal include: The expression for the first signal is as follows: （4） In the formula, Indicates the first signal. Represents the real part of the first signal. Let j represent the imaginary part of the first signal, and j represent the imaginary number. This represents the weighting coefficient for the real part. Represents real-domain PTRS modulation symbols. This indicates the number of PTRS modulation symbols within each PTRS block. The odd index representing the OQAM symbol sequence, 'm' represents the PTRS block index. Let m be the starting index of the m-th PTRS block. Represents the phase factor. Represents the real part of the phase factor. Represents the imaginary part of the phase factor. This represents the interference of the imaginary part of a real signal. Noise representing a real signal; The expression for the second signal is as follows: （5） In the formula, Indicates the second signal. This represents the real part of the second signal. Indicates the imaginary part of the second signal. Indicates the imaginary part weighting coefficient. Represents the virtual domain PTRS modulation symbol. The even index of the OQAM symbol sequence. This represents the interference of the real part of the virtual signal. Noise representing a virtual signal.

8. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 7, characterized in that, The first preset coefficient is 1 or -1, and the second preset coefficient is j or -j.

9. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 8, characterized in that, The step of summing the third signal and the fourth signal to obtain the fifth signal, and calculating the phase noise estimate of the fifth signal, includes: When the first preset coefficient is 1, the expression for the fifth signal is as follows: （6） In the formula, Indicates the fifth signal. Noise representing a real signal; The phase factor is calculated from the fifth signal, and the phase noise is obtained by solving it; wherein the expression for the phase factor is as follows: （7） In the formula, Represents the phase factor. Indicates phase noise; =angle(e jθ[m] )(8) In the formula, angle(e jθ[m] This indicates that the phase factor is solved; The phase noise estimate of the fifth signal is obtained by interpolating the phase noise of each PTRS block.

10. The OQAM-DFT-s-OFDM waveform phase noise estimation method according to claim 9, characterized in that, The expression for the phase noise estimate of the fifth signal is as follows: （9） In the formula, This represents the estimated phase noise value of the fifth signal.

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