A dual-selective channel estimation and equalization method based on single-carrier waveform

Abstract

The present invention discloses a dual-selective channel estimation and equalization method based on a single-carrier waveform, comprising: transferring the time-domain data symbols of the transmitter to the DAFT domain through discrete affine Fourier transform, then performing pilot replacement on the data in the transmission frame to obtain the DAFT domain signal after the pilot is replaced; transferring the DAFT domain signal after the pilot is replaced back to the time domain through discrete affine inverse Fourier transform and performing signal transmission; after passing through the dual-selective channel, the receiver transfers the received signal to the DAFT domain through DAFT, performs channel estimation and equalization using known pilot iterations in the DAFT domain, and finally transfers the received signal to the time domain through discrete affine inverse Fourier transform and detects the transmitted data symbols. The present invention innovatively performs dual-selective channel estimation and equalization in the DAFT domain based on a single-carrier waveform and pilot multiplexing, providing a new and effective solution for channel estimation and equalization of single-carrier systems under dual-selective channels.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a dual-selection channel estimation and equalization method based on a single carrier waveform. Background Art

[0002] With the advancement of communication technology, people's requirements for communication systems are becoming increasingly stringent. In the current 5G era, we are gradually moving towards the era of the Internet of Everything. The next generation of mobile communications—6G—is expected to usher in an era of intelligent connectivity, integrating multiple capabilities such as communication, perception, and computing. Common application scenarios for 6G include communications between users, high-speed rail, connected vehicles, aviation, and satellites. Therefore, reliable communication at high carrier frequencies during high-speed mobility has become one of the most pressing challenges in the development of wireless communication technology.

[0003] In previous 4G and 5G wireless communication technologies, traditional multi-carrier technologies, such as Orthogonal Frequency Division Multiplexing (OFDM), were widely used in broadband communications due to their excellent resistance to multipath fading and frequency-selective propagation. However, in dual-selective channels, the channels exhibit both time-selective and frequency-selective fading. Under high mobile rates and Doppler shift, the orthogonality between subcarriers in an OFDM system is destroyed, potentially leading to inter-symbol interference (ISI) and inter-subcarrier interference (ISI), which can affect system performance. To meet the communication requirements of high mobile rates and achieve good performance in dual-selective channels, many new signal modulation techniques have been proposed, and DAFT-based DFDM technology was born within this context.

[0004] DAFT is a generalized Fourier transform, a generalization of the discrete Fourier transform. DFT-based RF division multiplexing (DDM) technology adjusts the parameters of two linear frequency-modulated pulses so that the impulse response in the discrete Fourier domain represents the complete delay-Doppler information of the dual-selective channel, achieving full diversity gain in the dual-selective channel.

[0005] Waveforms based on single-carrier technology, due to their low peak-to-average power ratio and strong anti-interference capabilities, are expected to become the waveforms for next-generation mobile communications. However, current research on single-carrier technology remains limited to channel estimation and equalization in the discrete Fourier transform domain, which cannot adapt to the interference caused by the time-varying characteristics of dual-selective channels. Furthermore, research on channel estimation and equalization in the DAFT domain is still lacking. Summary of the Invention

[0006] Aiming at the blank of DAFT in the field of single carrier technology, the present invention proposes a dual-selection channel estimation and equalization method based on single carrier waveform, which uses DAFT to DAFT domain to perform channel estimation and equalization.

[0007] To achieve the above object, the present invention provides a dual-selection channel estimation and equalization method based on a single carrier waveform, comprising:

[0008] The time-domain data symbols at the transmitter are transferred to the DAFT domain through discrete affine Fourier transform, and then the pilot is replaced by the data in the transmission frame to obtain the DAFT domain signal after the pilot is replaced;

[0009] Converting the pilot-replaced DAFT domain signal back to the time domain through discrete affine inverse Fourier transform and sending the signal;

[0010] After the dual channel selection, the receiver transfers the received signal to the DAFT domain through DAFT, uses known pilot iterations in the DAFT domain to perform channel estimation and equalization, and finally transfers it to the time domain through discrete affine inverse Fourier transform and detects the transmitted data symbols.

[0011] Preferably, the transmission frame includes a pilot and data;

[0012] The pilot is a training sequence known to both the transmitter and receiver, and is used to estimate the channel when receiving the signal.

[0013] The data is information that needs to be sent.

[0014] Preferably, the process of obtaining the DAFT domain signal after the pilot is replaced includes:

[0015] The time domain data symbols are transformed into DAFT domain data symbols through DAFT, and then the first DAFT domain data symbol is replaced by a pilot, and finally converted back into a time domain signal through inverse DAFT.

[0016] Preferably, the process of transferring the received signal to the DAFT domain by the receiving end through DAFT includes:

[0017] The transmitted signal passes through a dual-selection channel under specific channel characteristics to obtain a received signal;

[0018] The time domain signal received by the receiving end is converted into a DAFT domain signal through DAFT, a channel coarse estimation is first performed in the DAFT domain to obtain a preliminary channel matrix, and then symbol detection is performed to obtain an estimated signal.

[0019] Preferably, the process of iteratively performing channel estimation and equalization using known pilots in the DAFT domain includes:

[0020] performing interference cancellation on the estimated signal to remove interference of the data on the pilot signal, and further using the interference-cancelled signal for channel estimation;

[0021] Based on the updated estimation of the channel state information, symbol detection and interference cancellation are iteratively performed to finally obtain the estimated channel matrix;

[0022] Minimum mean square error equalization is performed based on the finally estimated channel matrix to obtain a final estimated signal.

[0023] Preferably, when minimum mean square error equalization is performed based on the finally estimated channel matrix, the minimum mean square error equalization coefficient is expressed as:

[0024]

[0025] in, for The conjugate transpose of is the final estimated channel matrix, SNR is the data signal-to-noise ratio, I N is the N×N identity matrix.

[0026] Compared with the prior art, the present invention has the following advantages and technical effects:

[0027] (1) The present invention is designed based on the application of DAFT in single-carrier waveform technology, filling the gap in channel estimation and equalization of DAFT in single-carrier technology.

[0028] (2) In the transmission frame structure of the present invention, only one pilot symbol that replaces the original data symbol is required to complete channel estimation and equalization, which greatly improves the spectrum efficiency of transmission.

[0029] (3) The channel estimation and equalization method of the present invention can overcome the time selective fading and frequency selective fading generated in the dual-selective channel, and improve the channel estimation accuracy and bit error rate performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0031] Figure 1 Schematic diagram of a method flow in an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of a DAFT domain transmission frame structure according to an embodiment of the present invention;

[0033] Figure 3 is a system block diagram of an embodiment of the present invention;

[0034] Figure 4 FIG. 1 is a schematic diagram of bit error rate performance simulation under integer Doppler frequency shift and ideal channel state information according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0036] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0037] Example 1

[0038] like Figure 1-4 As shown, this embodiment provides a dual-selection channel estimation and equalization method based on a single carrier waveform, including the following steps:

[0039] The transmitter's time-domain data symbols are converted to the DAFT domain using a discrete affine Fourier transform (DAFT). Then, part of the data in the transmitted frame is replaced with a pilot signal, and an inverse DAFT is performed to transform it back to the time domain and transmit it. After dual channel selection, the receiver uses DAFT to convert the received signal to the DAFT domain. Channel estimation and equalization are performed iteratively in the DAFT domain using known pilot signals. Finally, an inverse DAFT transform is performed to convert the signal to the time domain and detect the transmitted data symbols.

[0040] Furthermore, for the structure of the sending frame:

[0041] The transmission frame consists of a pilot and data. The pilot is a training sequence known to both the sender and receiver, used to estimate the channel when receiving the signal. The data is the information to be transmitted. The time-domain data symbols are transformed into DAFT-domain data symbols through DAFT, and the first DAFT-domain data symbol is then replaced with the pilot. Finally, the data is converted back into the time-domain signal through inverse DAFT.

[0042] Furthermore, in the channel estimation at the receiving end:

[0043] To improve the accuracy of channel estimation, the time domain signal received by the receiving end is converted into a DAFT domain signal through DAFT. A rough channel estimation is first performed in the DAFT domain to obtain a preliminary channel matrix, and then symbol detection is performed. After that, the estimated signal obtained by detection is used to perform interference cancellation to remove the interference of data on the pilot, and the signal after interference cancellation is further used for channel estimation. As the channel state information is updated and estimated, symbol detection and interference cancellation are iteratively performed, and the estimated channel matrix is ​​finally obtained. Optionally, in the DAFT domain equalization at the receiver:

[0044] Furthermore, after obtaining the final estimated effective channel matrix through channel estimation, minimum mean square error equalization is performed to obtain the final estimated signal. The minimum mean square error equalization coefficient is expressed as:

[0045]

[0046] in, for The conjugate transpose of is the final estimated channel matrix, SNR is the data signal-to-noise ratio, I N is the N×N identity matrix.

[0047] Example 2

[0048] This embodiment provides a dual-selection channel estimation and equalization method based on a single carrier waveform, which can be applied to a wireless communication system. The wireless communication system inserts a pilot signal using a DAFT domain pilot multiplexing technique at the transmitting end, and performs channel estimation and equalization in the DAFT domain of the receiving end using the pilot signal known to the transmitting end. The method specifically includes the following steps:

[0049] S1. Use DAFT to convert the time domain signal of the transmitter into the DAFT domain, replace the first data with the pilot, and then perform inverse transform back to the time domain. The obtained signal is used as the system's transmission signal.

[0050] S2: The transmitted signal passes through a dual-selective channel with specific channel characteristics to obtain the received signal. To improve the accuracy of channel estimation, the time-domain signal received by the receiver is converted into a DAFT-domain signal using DAFT. Channel estimation is first performed in the DAFT domain to obtain a preliminary effective channel matrix, followed by symbol detection. The estimated signal is then subjected to interference cancellation to remove interference from the data on the pilot signal. The interference-free signal is then used for further channel estimation. As the channel state information is updated and estimated, symbol detection and interference cancellation are iteratively performed, ultimately obtaining an estimated effective frequency-domain channel matrix.

[0051] S3. After obtaining the final estimated effective channel matrix through channel estimation, minimum mean square error equalization is performed, and then the final estimated signal is obtained through inverse transformation.

[0052] like Figure 2 As shown, this embodiment provides a structural diagram of a transmission frame to illustrate the symbol distribution of the transmission signal; it is composed of two types of symbols, pilot and data. The transmission frame consists of pilot and data. The pilot is a training sequence known to both the sender and the receiver, used to estimate the channel when receiving the signal; the data is the information to be sent; the time domain data symbols are transformed into DAFT signals through DAFT, and then the first DAFT domain data symbol is replaced by the pilot;

[0053] like Figure 3 As shown, the transmitter of this embodiment transforms the generated time-domain signal into the DAFT domain through DAFT, replaces some of the data in the transmit frame with pilots, and then performs inverse DAFT to transform the signal into the time domain. After passing through the dual-selection channel, it is transformed into the DAFT domain through DAFT. In the DAFT domain, channel estimation is performed using the pilots known to the transmitter, acquiring various characteristics of the dual-selection channel, constructing an effective DAFT domain channel matrix, and then performing DAFT domain equalization. In the channel estimation and equalization phase, the DAFT domain signal received by the receiver is first subjected to channel estimation to obtain a preliminary effective channel matrix, followed by symbol detection. The estimated signal is then subjected to interference cancellation. As the channel state information is updated and estimated, symbol detection and interference cancellation are iteratively performed to obtain the final estimated effective DAFT domain channel matrix.

[0054] To further optimize the solution and illustrate the technical advancement of the method of this embodiment, the bit error rate performance of the dual-selection channel estimation and equalization method based on a single carrier waveform proposed in this embodiment under integer Doppler frequency shift is simulated on a MATLAB platform.

[0055] The simulation parameters are set as follows: the carrier frequency and bandwidth are 4 GHz and 32 kHz, respectively; the number of input symbols N = 128; the maximum channel delay is 39 μs, which is 5 after normalization; the maximum channel Doppler shift is 2 kHz, which is 2 after normalization; the number of channels P = 3; the channel complex gain is generated by an independent complex random variable with zero mean 1 / P and variance; the normalized channel delay 1 = [0, 2, 5]; the normalized channel Doppler shift in the ith channel is in, represents the maximum Doppler shift, θ i The signal-to-noise ratio (SNRp) of the pilot signal is 40 dB, and the modulation method is binary phase keying. Figure 4 As shown, Figure 4 The bit error rate performance of the dual-selective channel estimation and equalization method based on a single carrier waveform is demonstrated through simulation results and compared with the performance under ideal channel state information. Both schemes use linear minimum mean square error for symbol detection.

[0056] Through simulation, it can be seen that this embodiment has the following technical advancements:

[0057] Compared with the ideal channel state information corresponding to this embodiment, the bit error rate performance is close; compared with the method without iterative interference cancellation, the present invention has better bit error rate performance; the number of pilots used in the channel estimation of the present invention is 1, and the first data is replaced, and the pilot overhead ratio is only 0.195%, which greatly reduces the pilot overhead and improves the spectrum efficiency of the system.

[0058] This embodiment converts the transmitter's time-domain data symbols into the DAFT domain using DAFT, replaces the first data with a pilot, and then performs an inverse transform back to the time domain. The resulting signal serves as the system's input signal. The input signal is then passed through a dual-selective channel with specific channel characteristics to obtain a received signal. The time-domain signal received by the receiver is converted into the DAFT domain using DAFT, where channel estimation is performed to obtain a preliminary effective channel matrix, followed by symbol detection. The detected estimated signal is then subjected to interference cancellation. As the channel state information is updated and estimated, symbol detection and interference cancellation are iteratively performed to obtain the final estimated effective DAFT domain channel matrix. After obtaining the final estimated effective channel matrix through channel estimation, minimum mean square error equalization is performed to obtain the final estimated signal.

[0059] This embodiment is designed based on the application of DAFT in single-carrier waveform technology, filling the gap in channel estimation and equalization of DAFT in single-carrier technology.

[0060] In the transmission frame structure of this embodiment, only one pilot symbol that replaces the original data symbol is needed to complete channel estimation and equalization, which greatly improves the spectrum efficiency of transmission.

[0061] The channel estimation and equalization method of this embodiment can overcome time selective fading and frequency selective fading generated in a dual-selective channel, thereby improving the channel estimation accuracy and bit error rate performance of the system.

[0062] Example 3

[0063] This embodiment further discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first embodiment.

[0064] Example 4

[0065] This embodiment further discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in the first embodiment are implemented.

[0066] Example 5

[0067] This embodiment further discloses a computer program product, including a computer program, which implements the steps of the method described in the first embodiment when executed by a processor.

[0068] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A dual-selection channel estimation and equalization method based on a single carrier waveform, characterized in that: include: The time-domain data symbols at the transmitter are transferred to the DAFT domain through discrete affine Fourier transform, and then the pilot is replaced by the data in the transmission frame to obtain the DAFT domain signal after the pilot is replaced; Converting the pilot-replaced DAFT domain signal back to the time domain through discrete affine inverse Fourier transform and sending the signal; After the dual channel selection, the receiver uses DAFT to transfer the received signal to the DAFT domain. In the DAFT domain, it uses known pilots to iteratively perform channel estimation and equalization. Finally, it uses the inverse discrete affine Fourier transform to transfer the received signal to the time domain and detect the transmitted data symbols. The process of transferring the received signal to the DAFT domain at the receiving end includes: The transmitted signal passes through a dual-selection channel under specific channel characteristics to obtain a received signal; Converting the time domain signal received by the receiving end into a DAFT domain signal through DAFT, performing rough channel estimation in the DAFT domain to obtain a preliminary channel matrix, and then performing symbol detection to obtain an estimated signal; The process of iterative channel estimation and equalization using known pilots in the DAFT domain includes: performing interference cancellation on the estimated signal to remove interference of the data on the pilot signal, and further using the interference-cancelled signal for channel estimation; Based on the updated estimation of the channel state information, symbol detection and interference cancellation are iteratively performed to finally obtain the estimated channel matrix; Minimum mean square error equalization is performed based on the finally estimated channel matrix to obtain a final estimated signal.

2. The method according to claim 1, characterized in that The transmission frame includes a pilot and data; The pilot is a training sequence known to both the transmitter and receiver, and is used to estimate the channel when receiving the signal. The data is information that needs to be sent.

3. The method according to claim 1, characterized in that The process of obtaining the DAFT domain signal after the pilot is replaced includes: The time domain data symbols are transformed into DAFT domain data symbols through DAFT, and then the first DAFT domain data symbol is replaced by a pilot, and finally converted back into a time domain signal through inverse DAFT.

4. The method according to claim 1, wherein When minimum mean square error equalization is performed based on the finally estimated channel matrix, the minimum mean square error equalization coefficient is expressed as: in, for The conjugate transpose of is the final estimated channel matrix, SNR is the data signal-to-noise ratio, I N is the N×N identity matrix.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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