A method and system for estimating and compensating phase noise in millimeter-wave LOS-MIMO OFDM

Abstract

The application discloses a millimeter wave LOS-MIMO OFDM phase noise estimation compensation method and system, which places a local pilot sequence in a corresponding position of an information sequence after coding and modulation, obtains a received signal r through frequency down-conversion and filtering sampling, extracts a received pilot sequence r from the received signal r through a demultiplexing module at a receiving end, divides a continuous part r p and a discrete part r p,1 in the received pilot, p,2 calculates an autocorrelation matrix of r p,1 and a cross-correlation vector of r p,1 and s p,1 , then performs minimum mean square error estimation on a phase noise spectrum Φ to obtain an estimated value, obtains a time domain part phase noise after IFFT, and then utilizes the discrete pilot to estimate a residual phase angle, so that the estimation and compensation of the phase noise are completed. The application is convenient for subsequent software processing, and can realize the suppression of the millimeter wave OFDM system phase noise under a lower implementation complexity through design according to the minimum mean square error criterion.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, specifically relating to a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method and system. Background Technology

[0002] With the increasing demand for high-speed data transmission in current military and civilian networks, lower wireless communication frequency bands are already congested and unable to meet the needs. Millimeter-wave bands, however, offer continuous wideband spectrum for high-speed data transmission, making millimeter-wave technology a hot research topic in current wireless communication technology. Furthermore, because millimeter-wave signals have a very large bandwidth, often exceeding the coherence bandwidth of the wireless channel, they experience frequency-selective fading. Therefore, OFDM transmission schemes with resistance to frequency-selective fading have become a key technology in millimeter-wave communication.

[0003] The advantages of millimeter-wave communication include:

[0004] (1) Large bandwidth: According to Shannon's formula, a large continuous bandwidth can bring a huge transmission rate, and also means flexible bandwidth allocation and high channel capacity.

[0005] (2) Allows for higher transmission power: Higher transmission power helps millimeter-wave transmission systems overcome the worse path loss caused by high-frequency signals.

[0006] (3) High anti-interference and security: Oxygen has a strong absorption effect on electromagnetic waves in the millimeter wave band except for the "atmospheric window". Moreover, obstacles such as walls have a great impact on the attenuation of millimeter waves. This greatly improves the security and anti-interference of millimeter wave wireless communication in short-range communication. At the same time, since the energy of millimeter wave wireless signals has high directionality, it can reduce interference between signals.

[0007] (4) Small antenna size and circuit integration: Millimeter wave wireless signals are high-frequency signals with wavelengths on the order of millimeters, resulting in antennas that are on the order of millimeters, which is conducive to integration and miniaturization. A greater advantage is that a range of antenna technologies, such as antenna arrays, can be used to compensate for the large path loss in free space.

[0008] However, millimeter-wave communication technology inevitably has some application limitations. For example, millimeter-wave systems require a relatively large number of base stations and antennas. Due to cost considerations, the hardware characteristics of micro base stations and antennas are not optimal, resulting in performance losses due to hardware non-ideal characteristics. One such non-ideal characteristic that significantly impacts reception performance is the phase noise of the oscillator. Phase noise causes phase rotation in the received signal and introduces inter-carrier interference, disrupting the orthogonality between OFDM subcarriers. These effects greatly limit the utilization of higher-order modulation schemes (such as QAM modulation). Moreover, oscillators in the millimeter-wave band have even higher phase noise levels, making it necessary to design algorithms to estimate and compensate for phase noise.

[0009] Phase noise suppression algorithms in OFDM systems can be categorized into three types: decision feedback-based methods, discrete pilot-based methods, and blind estimation methods. Decision feedback-based methods estimate phase noise using real-time decisions on transmitted symbols. The estimated values ​​are then used to remove phase noise, and new decision conditions are applied to the transmitted symbols. These conditions are then used again to optimize the phase noise estimate. This process is repeated a certain number of times, creating a feedback loop. Due to this iterative process, these schemes impose a significant computational burden on the receiver. Pilot-based schemes, utilizing discrete pilot subcarriers, are more attractive. Most pilot subcarrier-based schemes only estimate the DC phase noise component (CPE), while the higher-order phase noise component (ICI) is not estimated, or is assumed to be very small. To obtain high-accuracy phase noise estimation, both CPE and ICI should be estimated simultaneously. The main goal of blind estimation schemes is to jointly estimate phase noise and transmitted symbols. These methods typically use Bayesian filtering methods to jointly estimate the required parameters. Examples include variational inference and Monte Carlo methods. While these methods are statistically optimal, they are computationally intensive and may not be suitable for delay-sensitive wireless systems.

[0010] Due to the limited computing resources of FPGAs, it is necessary to reduce algorithm complexity. A pilot-based phase noise estimation and compensation scheme can be chosen. To improve estimation accuracy, it is necessary to estimate the DC component and several high-frequency components of the phase noise. Based on the power spectral density characteristics of phase noise in millimeter-wave devices, the energy is mainly concentrated in the DC and low-frequency components. Therefore, estimating only a few low-frequency components of the phase noise is sufficient to effectively suppress it, thus allowing for implementation with relatively low complexity. Summary of the Invention

[0011] The technical problem to be solved by the present invention is to provide a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method and system to address the shortcomings of the prior art, thereby solving the problem of high computational complexity in decision feedback phase noise estimation schemes and blind estimation schemes, so as to suppress the influence of phase noise and improve the capacity of communication systems.

[0012] The present invention adopts the following technical solution:

[0013] A millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method includes the following steps:

[0014] S1, transfer the local pilot sequence s p Placed at the corresponding position in the encoded and modulated information sequence d;

[0015] S2, the local pilot sequence s obtained in step S1 p After down-conversion and filtering sampling, the received signal r is obtained. The received pilot sequence r is extracted from the received signal r. p Distinguish between received pilot sequences r p The continuous part r in p,1 and discrete part r p,2 ;

[0016] S3. Calculate the received pilot sequence r obtained in step S2. p The continuous part r p,1 autocorrelation matrix and the received pilot sequence r p The continuous part r p,1 With s p,1 cross-correlation vector

[0017] S4. Based on the autocorrelation matrix obtained in step S3 and cross-correlation vector The phase noise spectrum Φ is estimated by performing minimum mean square error estimation to obtain the estimated phase noise spectrum value.

[0018] S5. Based on the phase noise spectrum estimate obtained in step S4 Calculate the temporal phase noise sample within one OFDM cycle Compensating for phase noise in the time domain yields a time-domain signal y with this phase noise eliminated. wo,phn0 ;

[0019] S6. Using the time-domain signal y obtained in step S5 wo,phn0 and discrete pilot s p,2 Estimate the residual phase rotation angle Phase noise compensation is then performed to obtain the time-domain signal y with all phase noise eliminated. wo,phn1 ;

[0020] S7. The time-domain signal y obtained in step S6 wo,phn1 Phase noise estimation and compensation are achieved by switching to the frequency domain via FFT and demodulating the signal.

[0021] Specifically, step S1 involves: processing the local pilot sequence s p Placed in subcarrier sequence number [0:N band -1] and [N] band :N band :N carr -1], i.e., s p It has a continuous part and a discrete part, denoted as s respectively. p,1 and s p,2 Place the information sequence d on other subcarriers; N band For continuous pilot numbers, N carr This refers to the number of OFDM subcarriers or the number of FFT / IFFT points; the complex baseband signal is modulated to the millimeter-wave band and sent into a Gaussian white noise channel for transmission.

[0022] Specifically, in step S3, r p,1 autocorrelation matrix Size is L×L, r p,1 With s p,1 cross-correlation vector Its size is L×1.

[0023] Furthermore, the autocorrelation matrix and cross-correlation vector They are respectively:

[0024]

[0025]

[0026] Specifically, in step S4, the phase noise spectrum estimate is... Its size is L×1.

[0027] Furthermore, the phase noise spectrum estimate for:

[0028]

[0029] in,(·) -1 This represents finding the inverse of a matrix.

[0030] Specifically, in step S5, the time-domain signal y wo,phn0 for:

[0031]

[0032] Where (·) represents element-wise product, y phn0 This refers to the time-domain received signal without phase noise compensation after removing the cyclic prefix.

[0033] Specifically, in step S6, the time-domain signal y wo,phn1 for:

[0034]

[0035] in, This represents the residual phase rotation angle.

[0036] Furthermore, the residual phase rotation angle Specifically:

[0037]

[0038] in,(·) H Represents the conjugate transpose, (·) T Represents matrix transpose. Let denote the Kronecker product of matrices, where A is a matrix.

[0039] Secondly, embodiments of the present invention provide a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation system, comprising:

[0040] The location module will store the local pilot sequence s p Placed at the corresponding position in the encoded and modulated information sequence d;

[0041] The differentiation module obtains the local pilot sequence s from the position module. p After down-conversion and filtering sampling, the received signal r is obtained. The received pilot sequence r is extracted from the received signal r. p Distinguish between received pilot sequences r p The continuous part r in p,1 and discrete part r p,2 ;

[0042] The vector module calculates the received pilot sequence r obtained from the discrimination module. p The continuous part r p,1 autocorrelation matrix and the received pilot sequence r p The continuous part r p,1 With s p,1 cross-correlation vector

[0043] The estimation module, based on the autocorrelation matrix obtained from the vector module... and cross-correlation vector The phase noise spectrum Φ is estimated by performing minimum mean square error estimation to obtain the estimated phase noise spectrum value.

[0044] The time-domain module uses the phase noise spectrum estimate obtained from the estimation module. Calculate the temporal phase noise sample within one OFDM cycle Compensating for phase noise in the time domain yields a time-domain signal y with this phase noise eliminated.wo,phn0 ;

[0045] The phase noise module utilizes the time-domain signal y obtained from the time-domain module. wo,phn0 and discrete pilot s p,2 Estimate the residual phase rotation angle Phase noise compensation is then performed to obtain the time-domain signal y with all phase noise eliminated. wo,phn1 ;

[0046] The compensation module converts the time-domain signal y obtained from the phase noise module into a signal that is not directly related to the compensation module. wo,phn1 Phase noise estimation and compensation are achieved by switching to the frequency domain via FFT and demodulating the signal.

[0047] Compared with the prior art, the present invention has at least the following beneficial effects:

[0048] A millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method is proposed. First, at the transmitting end, the pilot is divided into continuous and discrete pilots based on the power spectral characteristics of millimeter-wave phase noise. At the receiving end, the received analog data is filtered and sampled to convert it into a baseband equivalent discrete frequency domain signal, facilitating signal transmission and software processing. Dividing the transmitting pilot into continuous and discrete parts is adapted to the power spectral density characteristics of phase noise in millimeter-wave devices, enabling high-accuracy estimation. The low-frequency components of the phase noise are estimated using continuous pilots and the minimum mean square error criterion. The discrete pilots are used to estimate the phase rotation angle, completing the final phase noise estimation and compensation. The matrix inversion process for the minimum mean square error estimation utilizes matrix decomposition, resulting in a computationally inefficient implementation that is easy to implement in hardware and avoids the large computational burden on the receiver caused by feedback iterative calculations. Compared with blind estimation schemes, this invention reduces computational load and implementation complexity.

[0049] Furthermore, based on the strong low-pass characteristics of the phase noise power spectral density of millimeter-wave band devices, the continuous pilot portion is used to estimate several significant low-frequency components of the phase noise near zero frequency, and the discrete pilot portion is used to estimate the residual phase noise CPE effect. The power spectral density diagram of millimeter-wave phase noise is shown in the figure below. Most of the energy is concentrated in the 0–1 MHz frequency band, i.e., it has strong low-pass characteristics. Estimating several significant low-frequency components of the phase noise near zero frequency using the continuous pilot portion can effectively compensate for the phase noise effect. The discrete pilot portion is then used to further estimate the CPE effect for compensating for the phase noise.

[0050] Furthermore, in step S3, since the number of low-frequency components of the phase noise to be estimated is L, which is a relatively small value, the autocorrelation matrix... The dimension is L×L, and the complexity of inverting it is relatively low, and the autocorrelation matrix... and cross-correlation vector The computational complexity of the product is also relatively low, making it easy to implement on FPGA.

[0051] Furthermore, according to the MMSE criterion, the low-frequency component of the phase noise can be estimated and treated as the impulse response of a linear filter whose input is the received pilot signal r. p,1 The output is an estimate of the local pilot sequence. The local pilot sequence is estimated according to the MMSE criterion. With the actual transmitted local pilot sequence s p,1 The mean square error is minimized, from which the estimated value of the filter's impulse response can be derived.

[0052] Furthermore, It is the impulse response of the linear estimation filter, which corresponds to the conjugate of the phase noise in the time domain. Therefore, by converting it to the time domain and multiplying it with the received time domain signal, the effect of the phase noise can be compensated.

[0053] Furthermore, the time-domain signal y wo,phn0 This is the time-domain signal obtained after preliminary compensation for the phase noise effect estimated in S6. Next, the residual CPE is estimated using discrete pilot signals, also in the time domain. Then, y can be used... wo,phn0 With temporal residue Multiplication further optimizes the compensation for phase noise.

[0054] Furthermore, y wo,phn1 It is in y wo,phn0 Further compensation for residual The subsequent result can be considered as all phase noise having been compensated.

[0055] Furthermore, the residual phase rotation angle It is the result of averaging the residual phase rotation on the entire OFDM symbol using discrete pilots. This part is a supplement to the MMSE phase noise estimation and can further optimize the phase noise compensation performance.

[0056] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0057] In summary, this invention optimizes the phase noise compensation results, facilitates FPGA implementation, can compensate for the influence of phase noise, and further optimizes phase noise compensation.

[0058] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0059] Figure 1This is a block diagram of an OFDM transceiver system to which this invention applies;

[0060] Figure 2 A schematic diagram of the equivalent baseband discrete frequency domain signal sequence to be transmitted;

[0061] Figure 3 To implement the module flowchart;

[0062] Figure 4 When estimating the phase noise spectrum at L=4 points, a comparison is made between the proposed method and the theoretical curve without phase noise in an AWGN channel;

[0063] Figure 5 To estimate the phase noise spectrum at L=4 points, the transmitted EVM curves of this method and those required by the 5G NR standard are shown in the AWGN channel.

[0064] Figure 6 The time-domain phase noise estimation diagram when Eb / N0 = 24dB;

[0065] Figure 7 The receiver constellation diagram is shown when Eb / N0 = 24dB. Detailed Implementation

[0066] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0067] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0068] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0069] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0070] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0071] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0072] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0073] This invention provides a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method, which selects a local pilot sequence s at the transmitting end. p The local pilot sequence is placed at the corresponding position in the encoded and modulated information sequence d using a multiplexing module. This local pilot sequence is divided into continuous and discrete parts, used to estimate the phase noise spectral components of each part. After down-conversion and filtering sampling, the received signal r is obtained. The receiver then extracts the received pilot sequence rd from the received signal r using a demultiplexing module. p The continuous portion r in the received pilot signal p,1 and discrete part r p,2 Distinguish them, then calculate r. p,1 autocorrelation matrix and r p,1 With sp,1 cross-correlation vector Then, the phase noise spectrum Φ is estimated using minimum mean square error to obtain the estimated value. The phase noise in the time domain is obtained after IFFT, and the residual phase angle is estimated using discrete pilot signals, thus completing the estimation and compensation of phase noise. This invention facilitates subsequent software processing and, by designing based on the minimum mean square error criterion, can achieve phase noise suppression of millimeter-wave OFDM systems with low implementation complexity.

[0074] Please see Figure 1 This is a block diagram of an OFDM transceiver system, with N OFDM subcarriers. carr Divided into N band The number of channels is reduced to decrease the signal bandwidth of each channel, making it easier to implement on an FPGA. During up / down conversion, phase noise is introduced due to the non-ideal characteristics of the oscillator.

[0075] Please see Figure 3 The present invention provides a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method, comprising the following steps:

[0076] S1. Select the local pilot sequence s at the transmitting end. p The multiplexing module places it at the corresponding position in the encoded and modulated information sequence d, specifically at the following positions:

[0077] s p Placed in subcarrier sequence number [0:N band -1] and [N] band :N band :N carr -1], i.e., s p It has a continuous part and a discrete part, denoted as s respectively. p,1 and s p,2 The information sequence d is placed on other subcarriers. N band For continuous pilot numbers, N carr This refers to the number of OFDM subcarriers or the number of FFT / IFFT points. The complex baseband signal is modulated into the millimeter-wave band and transmitted through a Gaussian white noise channel. For a schematic diagram of the transmitted equivalent baseband discrete frequency domain signal sequence, please refer to [link to diagram]. Figure 2 .

[0078] S2. The signal arrives at the receiving end, undergoes down-conversion and filtering sampling to obtain the received signal r. The receiving end then uses a demultiplexing module to extract the received pilot sequence r from the received signal r. p The continuous portion r in the received pilot signal p,1 and discrete part r p,2 Distinguish;

[0079] S3, Calculate rp,1 autocorrelation matrix and r p,1 With s p,1 cross-correlation vector

[0080] r p,1 autocorrelation matrix Size is L×L, r p,1 With s p,1 cross-correlation vector Its size is L×1. Wherein,

[0081]

[0082]

[0083] S4. Based on the autocorrelation matrix and autocorrelation vector obtained in step S3, perform minimum mean square error estimation on the phase noise spectrum Φ to obtain the estimated phase noise spectrum value.

[0084] When estimating the phase noise spectrum using the minimum mean square error criterion, the estimated phase noise spectrum value is... The size is L×1, and the expression is:

[0085]

[0086] in,(·) -1 This represents finding the inverse of a matrix.

[0087] S5. Calculate the time-domain phase noise samples within one OFDM period based on the estimated phase noise spectrum. Compensating for phase noise in the time domain yields a time-domain signal y with this phase noise eliminated. wo,phn0 ;

[0088]

[0089] In this context, (·) represents element-wise multiplication.

[0090] S6, using y wo,phn0 and discrete pilot s p,2 Estimate the residual phase rotation angle This portion of the phase noise is then compensated to obtain the time-domain signal y with all phase noise eliminated. wo,phn1 ;

[0091] Take advantage of y wo,phn0 and discrete pilot s p,2 Estimate the residual phase rotation angle The method is as follows:

[0092]

[0093] in,(·) H Represents the conjugate transpose, (·) T Represents matrix transpose. Let A denote the Kronecker product of matrices, where matrix A = [1 0 1] 1×(Nband-1) ].

[0094] y wo,phn1 The calculation method is as follows:

[0095]

[0096] S7, convert the time-domain signal y wo,phn1 The frequency domain is converted using FFT and then demodulated.

[0097] In another embodiment of the present invention, a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation system is provided. This system can be used to implement the above-mentioned millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method. Specifically, the millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation system includes a position module, a discrimination module, a vector module, an estimation module, a time domain module, a phase noise module, and a compensation module.

[0098] The location module will store the local pilot sequence s. p Placed at the corresponding position in the encoded and modulated information sequence d;

[0099] The differentiation module obtains the local pilot sequence s from the position module. p After down-conversion and filtering sampling, the received signal r is obtained. The received pilot sequence r is extracted from the received signal r. p Distinguish between received pilot sequences r p The continuous part r in p,1 and discrete part r p,2 ;

[0100] The vector module calculates the received pilot sequence r obtained from the discrimination module. p The continuous part r p,1 autocorrelation matrix and the received pilot sequence r p The continuous part r p,1 With s p,1 cross-correlation vector

[0101] The estimation module, based on the autocorrelation matrix obtained from the vector module... and cross-correlation vector The phase noise spectrum Φ is estimated by performing minimum mean square error estimation to obtain the estimated phase noise spectrum value.

[0102] The time-domain module uses the phase noise spectrum estimate obtained from the estimation module. Calculate the temporal phase noise sample within one OFDM cycle Compensating for phase noise in the time domain yields a time-domain signal y with this phase noise eliminated. wo,phn0 ;

[0103] The phase noise module utilizes the time-domain signal y obtained from the time-domain module. wo,phn0 and discrete pilot s p,2 Estimate the residual phase rotation angle Phase noise compensation is then performed to obtain the time-domain signal y with all phase noise eliminated. wo,phn1 ;

[0104] The compensation module converts the time-domain signal y obtained from the phase noise module into a signal that is not directly related to the compensation module. wo,phn1 Phase noise estimation and compensation are achieved by switching to the frequency domain via FFT and demodulating the signal.

[0105] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method, including:

[0106] The local pilot sequence s p Placed at the corresponding position in the encoded and modulated information sequence d; for the local pilot sequence s p After down-conversion and filtering sampling, the received signal r is obtained. The received pilot sequence r is extracted from the received signal r. p Distinguish between received pilot sequences r p The continuous part r in p,1 and discrete part r p,2 ; Calculate the received pilot sequence r pThe continuous part r p,1 autocorrelation matrix and the received pilot sequence r p The continuous part r p,1 With s p,1 cross-correlation vector Based on the autocorrelation matrix and cross-correlation vector The phase noise spectrum Φ is estimated by performing minimum mean square error estimation to obtain the estimated phase noise spectrum value. Based on the phase noise spectrum estimate Calculate the temporal phase noise sample within one OFDM cycle Compensating for phase noise in the time domain yields a time-domain signal y with this phase noise eliminated. wo,phn0 Using time-domain signal y wo,phn0 and discrete pilot s p,2 Estimate the residual phase rotation angle Phase noise compensation is then performed to obtain the time-domain signal y with all phase noise eliminated. wo,phn1 ; the time-domain signal y wo,phn1 Phase noise estimation and compensation are achieved by switching to the frequency domain via FFT and demodulating the signal.

[0107] In another embodiment of the present invention, a storage medium is also provided, specifically a computer-readable storage medium (memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0108] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor to perform the following steps:

[0109] The local pilot sequence s p Placed at the corresponding position in the encoded and modulated information sequence d; for the local pilot sequence s pAfter down-conversion and filtering sampling, the received signal r is obtained. The received pilot sequence r is extracted from the received signal r. p Distinguish between received pilot sequences r p The continuous part r in p,1 and discrete part r p,2 ; Calculate the received pilot sequence r p The continuous part r p,1 autocorrelation matrix and the received pilot sequence r p The continuous part r p,1 With s p,1 cross-correlation vector Based on the autocorrelation matrix and cross-correlation vector The phase noise spectrum Φ is estimated by performing minimum mean square error estimation to obtain the estimated phase noise spectrum value. Based on the phase noise spectrum estimate Calculate the temporal phase noise sample within one OFDM cycle Compensating for phase noise in the time domain yields a time-domain signal y with this phase noise eliminated. wo,phn0 Using time-domain signal y wo,phn0 and discrete pilot s p,2 Estimate the residual phase rotation angle Phase noise compensation is then performed to obtain the time-domain signal y with all phase noise eliminated. wo,phn1 ; the time-domain signal y wo,phn1 Phase noise estimation and compensation are achieved by switching to the frequency domain via FFT and demodulating the signal.

[0110] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0111] Please see Figure 4 When estimating the phase noise spectrum at L=4 points, the comparison between the proposed method and the theoretical curve without phase noise in an AWGN channel shows that at a higher signal-to-noise ratio, the difference between the proposed method and the theoretical curve without phase noise is about 2dB, which can achieve good suppression of phase noise.

[0112] Please see Figure 5 The diagram shows the EVM curves of this method and the 5G NR standard requirements under the AWGN channel when estimating the phase noise spectrum at L=4 points. It can be seen that when Eb / N0=15dB, this method can already meet the QAM modulation transmission EVM requirements of 5G NR.

[0113] Please see Figure 6 The time-domain phase noise estimation is given when Eb / N0 = 24dB. The number of phase noise spectrum points is L = 4. It can be seen that the estimated phase noise can already compensate for the low-frequency part of the actual phase noise well. This part is the part with the most concentrated energy in the phase noise, so the phase noise can be estimated and suppressed well.

[0114] Please see Figure 7 The constellation diagram is given when Eb / N0 = 24dB. The estimated number of phase noise spectrum points is L = 4. It can be seen that after the phase noise is eliminated by this method, the receiving constellation diagram has eliminated the common phase rotation and some inter-carrier interference, and can achieve better receiving performance.

[0115] The above analysis leads to the following conclusions:

[0116] This method achieves the QAM modulation transmission EVM requirements of the 5G NR standard at Eb / N0 = 15dB, while the BER performance in the high signal-to-noise ratio region differs from the standard curve without phase noise by only 2dB. Therefore, the millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method based on discrete pilots proposed in this invention is well-suited for suppressing phase noise in millimeter-wave OFDM.

[0117] First, based on the strong low-pass characteristics of the phase noise power spectral density of millimeter-wave devices, a pilot structure combining continuous and discrete pilots was designed to estimate the significant low-frequency components of phase noise and further compensate for residual CPE, thereby optimizing the phase noise compensation results.

[0118] Second, the estimated number of low-frequency components of the phase noise is L, which is a relatively small value, thus contributing to the autocorrelation matrix of the phase noise. The dimension is L×L, and the complexity of inverting it is relatively low, and the autocorrelation matrix... and cross-correlation vector The computational complexity of the product is also relatively low, making it easy to implement on FPGA.

[0119] Third, according to the MMSE criterion, the low-frequency component of the phase noise can be estimated and treated as the impulse response of a linear filter whose input is the received pilot signal r. p,1The output is an estimate of the local pilot sequence. The local pilot sequence is estimated according to the MMSE criterion. With the actual transmitted local pilot sequence s p,1 The mean square error is minimized, from which the expression for the estimated impulse response of the filter can be derived as follows:

[0120] Fourth, based on the above The expression, It is a matrix of size L×L With a matrix of size L×1 The result of the multiplication is L×1. That is, the estimated number of low-frequency phase noise components is L.

[0121] Fifth, the impulse response of the linear estimation filter corresponds to the conjugate of the phase noise in the time domain. Therefore, by transforming it to the time domain and multiplying it with the received time domain signal, the influence of the phase noise can be compensated.

[0122] Sixth, the time-domain signal is obtained after the initial compensation of the phase noise effect estimated in S6. Next, the residual CPE is estimated using discrete pilots, which is also performed in the time domain. Then, it can be multiplied with the time-domain residual CPE to further optimize the compensation of phase noise.

[0123] Seventh, y wo,phn1 It is in y wo,phn0 Further compensation for residual The subsequent result can be considered as all phase noise having been compensated.

[0124] Eighth, residual phase rotation angle It is the result of averaging the residual phase rotation on the entire OFDM symbol using discrete pilots. This part is a supplement to the MMSE phase noise estimation and can further optimize the phase noise compensation performance.

[0125] In summary, this invention provides a millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method and system. Utilizing the strong low-pass characteristic of the millimeter-wave phase noise power spectral density, it achieves good phase noise suppression by estimating only L low-frequency phase noise components. The phase noise is estimated and compensated twice using both continuous and discrete pilot structures. Based on the MMSE criterion, the autocorrelation matrix obtained from the continuous pilots is used... and cross-correlation vector The phase noise spectrum Φ is estimated and then transferred to the time domain for compensation. Continuous pilot signals are then used to further compensate for the residual phase noise CPE. This achieves the QAM modulation transmission EVM requirements of the 5G NR standard at Eb / N0 = 15dB, while the BER performance in the high signal-to-noise ratio region is only 2dB different from the standard curve without phase noise.

[0126] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0127] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0128] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0129] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0130] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0132] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0133] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0134] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0135] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0136] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method, characterized in that, Includes the following steps: S1, local pilot sequence Placed in an encoded and modulated information sequence The corresponding position; S2. The local pilot sequence obtained in step S1 The received signal is obtained after down-conversion and filtering sampling. From the received signal Extract the received pilot sequence Distinguish between received pilot sequences continuous part and discrete part ; S3. Calculate the received pilot sequence obtained in step S2. continuous part autocorrelation matrix and the received pilot sequence continuous part With continuous part cross-correlation vector ; S4. Based on the autocorrelation matrix obtained in step S3 and cross-correlation vector For the phase noise spectrum By performing minimum mean square error estimation, the phase noise spectrum estimate is obtained. ; S5. Based on the phase noise spectrum estimate obtained in step S4 Calculate the temporal phase noise sample within one OFDM cycle By compensating for phase noise in the time domain, a time-domain signal with this phase noise eliminated is obtained. ; S6. Using the time-domain signal obtained in step S5 and discrete pilot Estimate the residual phase rotation angle Then, phase noise compensation is performed to obtain a time-domain signal with all phase noise eliminated. Time-domain signal for: in, The residual phase rotation angle; Residual phase rotation angle Specifically: in, Represents conjugate transpose. Represents matrix transpose. Represents the Kronecker product of matrices. For matrix ; S7. The time-domain signal obtained in step S6 Phase noise estimation and compensation are achieved by switching to the frequency domain via FFT and demodulating the signal.

2. The millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method according to claim 1, characterized in that, Step S1 specifically involves: [The following is a separate, unrelated step:] ...local pilot sequence The set of subcarriers mapped to OFDM symbols contains two types of subcarriers: the first type consists of subcarriers numbered from 0 to... The second type is the continuous subcarrier from the first; Starting with one subcarrier, For intervals, up to the first The discrete subcarriers, i.e. It has a continuous part and a discrete part, denoted as , ... and ; Sequence of information Placed on other subcarriers; For continuous pilot numbers, This refers to the number of OFDM subcarriers or the number of FFT / IFFT points. The complex baseband signal is modulated to the millimeter-wave band and sent into a Gaussian white noise channel for transmission.

3. The millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method according to claim 1, characterized in that, In step S3, autocorrelation matrix Size is , and cross-correlation vector Size is .

4. The millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method according to claim 3, characterized in that, Autocorrelation matrix and cross-correlation vector They are respectively:

5. The millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method according to claim 1, characterized in that, In step S4, the phase noise spectrum estimate is... The size is .

6. The millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method according to claim 5, characterized in that, Phase noise spectrum estimate for: in, This represents finding the inverse of a matrix.

7. The millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation method according to claim 1, characterized in that, In step S5, the time-domain signal for: in, Represents element-wise product. This refers to the time-domain received signal without phase noise compensation after removing the cyclic prefix.

8. A millimeter-wave LOS-MIMO OFDM phase noise estimation and compensation system, characterized in that, include: The location module will store the local pilot sequence. Placed in an encoded and modulated information sequence The corresponding position; The differentiation module distinguishes the local pilot sequences obtained from the location module. The received signal is obtained after down-conversion and filtering sampling. From the received signal Extract the received pilot sequence Distinguish between received pilot sequences continuous part and discrete part ; The vector module calculates the received pilot sequence obtained from the discrimination module. continuous part autocorrelation matrix and the received pilot sequence continuous part and cross-correlation vector ; The estimation module, based on the autocorrelation matrix obtained from the vector module... and cross-correlation vector For the phase noise spectrum By performing minimum mean square error estimation, the phase noise spectrum estimate is obtained. ; The time-domain module uses the phase noise spectrum estimate obtained from the estimation module. Calculate the temporal phase noise sample within one OFDM cycle By compensating for phase noise in the time domain, a time-domain signal with this phase noise eliminated is obtained. ; The phase noise module utilizes the time-domain signal obtained from the time-domain module. and discrete pilot Estimate the residual phase rotation angle Then, phase noise compensation is performed to obtain a time-domain signal with all phase noise eliminated. Time-domain signal for: in, The residual phase rotation angle; Residual phase rotation angle Specifically: in, Represents conjugate transpose. Represents matrix transpose. Represents the Kronecker product of matrices. For matrix ; The compensation module converts the time-domain signal obtained by the phase noise module into a signal that is... Phase noise estimation and compensation are achieved by switching to the frequency domain via FFT and demodulating the signal.

Images