A short wave SC-FDM block iterative equalization method of residual inter-code interference cancellation

Abstract

This invention belongs to the field of wireless communication and relates to a shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation, comprising: acquiring the signal y at the receiving end. n For signal y n Perform an FFT to obtain the frequency domain signal Y. k For signal Y k Feedforward equalization and MMSE feedback equalization are performed to obtain the feedforward equalized signal Z. k and feedback equalization signal G k，0 ; will signal Z k G k，0 The equalized signal D is obtained by superposition. k，0 For the equalization signal D k，0 Perform IFFT to obtain the time-domain signal r n，0 For signal r n，0 The decision signal is used to obtain the decision signal. Residual inter-symbol interference (ISI) is then estimated on the signal to obtain the residual ISI factor. Based on this factor, the frequency domain signal Y is analyzed. k Perform feedback equalization to obtain the feedback equalization signal G. k，1 ; will signal Z k and signal G k，1 The equalized signal D is obtained by superposition. k,1 For the equalization signal D k,1 Perform IFFT operation to obtain the time-domain signal r n,1 For time-domain signal r n,1 The present invention performs noise suppression and residual inter-symbol interference cancellation operations in the time and frequency domains respectively in MMSE feedback equalization, thereby improving the equalization accuracy.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication and relates to a shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation. Background Technology

[0002] Shortwave communication is a means of wireless communication that utilizes electromagnetic waves with wavelengths ranging from 100m to 10m and frequencies from 3MHz to 30MHz. Relying on atmospheric ionospheric reflection, shortwave communication enables global data communication and has been widely used in military, meteorological, and disaster relief fields. Although new radio communication systems are constantly emerging, shortwave remains irreplaceable. However, the biselective fading characteristics of shortwave channels can cause multipath interference, signal fading, and the Doppler effect, leading to severe signal distortion and making it difficult to maintain the reliability of shortwave communication. Therefore, relevant technologies are needed to overcome these interferences and improve the performance of shortwave communication systems.

[0003] Currently, the main technologies for combating multipath effects are single-carrier transmission and multi-carrier transmission. Single-carrier frequency domain equalization (SC-FDE) is an important single-carrier technology with advantages such as resistance to multipath fading, improved signal quality and stability, and low implementation complexity. In multi-carrier transmission, orthogonal frequency division multiplexing (OFDM) technology is widely used due to its low implementation complexity and good anti-interference and anti-fading capabilities. Single-carrier frequency division multiplexing (SC-FDM) technology combines the advantages of both OFDM and SC-FDE and is a key technology for uplink transmission in current wireless communication systems. SC-FDM improves spectrum utilization through frequency division multiplexing, supports high-speed data transmission, and has a low peak-to-average power ratio (PAPR) and strong anti-multipath interference capabilities, providing stable and reliable data services.

[0004] The main frequency domain equalization methods for SC-FDM include zero-forcing (ZF) equalization and minimum mean square error (MMSE) equalization, both of which are linear equalization methods. To achieve better error performance, nonlinear equalization methods, such as iterative equalization or decision feedback equalization, are often used. In time-domain decision feedback equalization (TD-DFE), the feedforward filter is implemented in the time domain, the feedback process is performed symbol-by-symbol, and the time-domain feedback filter is applied to previously detected symbols. To address residual inter-symbol interference (RISI) after MMSE equalization, the paper "Anovel decision feedback equalizer for SC-FDE system" proposes an MMSE-RISIC algorithm, which estimates and eliminates residual RISI using decision data. Although TD-DFE provides satisfactory performance, its implementation complexity is high. To reduce complexity, the hybrid decision-feedback equalization (H-DFE) proposed in the papers "On the comparison between OFDM and single-carrier modulation with a DFE using a frequency-domain feedforward filter" and "A. Benyamin-Seeyar and B. Eidson, 'Frequency domain equalization for single-carrier broadband wireless systems'" designs the feedforward filter and feedback filter separately in the frequency and time domains. However, the complexity of H-DFE remains high. The paper "Single carrier frequency domain equalization with time domain noise prediction for wideband wireless communications" proposes a noise prediction decision feedback equalization (NP-DFE) structure, consisting of a linear frequency domain equalizer and a time domain noise predictor, similar to the HDFE structure.To overcome the shortcomings of TD-DFE and H-DFE mentioned above, the paper "Iterative design and detection of a DFE in the frequency domain" further proposes iterative block decision feedback equalization. Unlike TD-DFE and H-DFE, both the feedforward filter and the feedback filter are designed based on block-based frequency domain processing. Compared with TD-DFE and H-DFE, IBDFE can significantly reduce complexity and improve performance. To reduce the complexity of IBDFE, the paper "Low-complexity iterative frequency domain decision feedback equalization" proposes low-complexity iterative block decision feedback equalization (LC-IBDFE). The paper "A simplified IBDFE algorithm in a single-carrier frequency domain equalization system" addresses the high complexity of IBDFE by proposing a simplified IBDFE structure, which greatly reduces complexity at the expense of some performance. The paper "An Improved SC-FDE Block Iterative Decision Feedback Equalizer" proposes a low-complexity MMSE-IBDFE equalization algorithm to address the high computational complexity of the IBDFE algorithm, significantly reducing its implementation complexity. The paper "An Estimated δ-Based Iterative Block Decision Feedback Equalization in SC-FDE System. Electronics" proposes a feedback structure based on residual interference signal cancellation technology, which significantly improves bit error rate performance at the cost of lower complexity.

[0005] However, the MMSE-IBDFE equalization algorithm fails to take into account the impact of channel noise and residual inter-symbol interference on performance, resulting in relatively low equalization accuracy. Summary of the Invention

[0006] To address the aforementioned problems in the prior art, this invention employs a shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation, comprising:

[0007] S1. Obtain the signal y from the receiver of the SC-FDM system. n For signal y n Perform an FFT operation to obtain the frequency domain signal Y. k ;

[0008] S2, for the frequency domain signal Y kFeedforward equalization and MMSE feedback equalization are performed separately to obtain the feedforward equalized signal Z. k and feedback equalization signal G k，0 ;

[0009] S3, feedforward equalization signal Z k and feedback equalization signal G k，0 Superposition yields the equalized signal D. k，0 ;

[0010] S4. For the equalization signal D k，0 Perform IFFT operation to obtain the time-domain signal r n，0 For time-domain signal r n，0 Make a judgment and receive a judgment signal.

[0011] S5, Regarding the judgment signal Residual inter-symbol interference (ISI) is estimated to obtain the residual ISI factor.

[0012] S6. Based on the residual inter-symbol interference factor For frequency domain signal Y k Perform feedback equalization to obtain the feedback equalization signal G. k，1 ;

[0013] S7, feedforward equalization signal Z k and feedback equalization signal G k，1 Superposition yields the equalized signal D. k,1 ;

[0014] S8. For the equalization signal D k,1 Perform IFFT operation to obtain the time-domain signal r n,1 For time-domain signal r n,1 Make a judgment and receive a judgment signal.

[0015] Among them, SC-FDM is single-carrier frequency domain equalization, FFT is fast Fourier transform, MMSE is minimum mean square error, and IFFT is inverse fast Fourier transform.

[0016] Beneficial effects:

[0017] 1. This invention utilizes the decision signals of feedforward equalization and MMSE feedback equalization to perform noise suppression and residual inter-symbol interference cancellation operations in the time-frequency domain during MMSE feedback equalization, thereby improving equalization accuracy. 2. The decision signal of feedforward equalization integrates the signals from feedforward equalization and MMSE feedback equalization for noise suppression. The fused signal has removed most of the interference and is closer to the original transmitted signal. Therefore, using the fused signal for residual inter-symbol interference estimation can further reduce estimation errors, making it more accurate than using the decision signal after feedback equalization for inter-symbol interference estimation. Using the estimated interference factor for MMSE feedback equalization to eliminate inter-symbol interference can further improve equalization accuracy. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of a single-carrier frequency division multiplexing system provided in an embodiment of the present invention;

[0019] Figure 2 This is a data frame structure diagram provided in an embodiment of the present invention;

[0020] Figure 3 A structural diagram of a shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation provided in an embodiment of the present invention;

[0021] Figure 4 A schematic diagram illustrating the convergence of a shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation provided in an embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram illustrating the performance comparison under different subcarrier mapping methods provided in an embodiment of the present invention;

[0023] Figure 6 This is a schematic diagram showing the performance comparison under three shortwave environments provided in an embodiment of the present invention;

[0024] Figure 7 This is a schematic diagram showing the performance comparison of three equalization algorithms under adverse channel conditions provided in an embodiment of the present invention.

[0025] Figure 8 This is a schematic diagram showing the performance comparison of three equalization algorithms under good channel conditions provided in an embodiment of the present invention;

[0026] Figure 9 This is a schematic diagram comparing the performance of various algorithms provided in the embodiments of the present invention in a three-dimensional graph. Detailed Implementation

[0027] 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 embodiments of the present invention, and not all embodiments. 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.

[0028] SC-FDM is a single-carrier modulation technique with frequency-domain equalization at the receiver and allows for the parallel transmission of data from multiple users. It is a variant of OFDM with additional FFT and IFFT processing blocks at the transmitter and receiver, respectively.

[0029] like Figure 1 As shown, at the transmitter of the SC-FDM system, the input data stream is first modulated to convert it into a form suitable for transmission. Next, serial-to-parallel conversion transforms the data stream into multiple parallel data streams. Then, an M-point Fast Fourier Transform (FFT) is used to convert the signal from the time domain to the frequency domain, followed by subcarrier mapping, mapping data symbols onto different subcarriers for transmission. Subsequently, an N-point Inverse Fast Fourier Transform (IFFT) (where N > M) is performed, and a cyclic prefix (CP) is added. The system data frame structure after CP insertion is as follows. Figure 2 As shown, this structure can effectively reduce inter-symbol interference caused by multipath effects. If the CP length is the same as or longer than the multipath channel delay spread, orthogonality between different subcarriers can also be ensured, thus avoiding interference. Finally, the signal is converted from a digital signal to an analog signal via a digital-to-analog converter (DAC) for transmission through the physical channel.

[0030] At the receiving end, the analog signal is first converted back to a digital signal via digital-to-analog conversion. After removing the cyclic prefix, an N-point FFT transform is performed to convert the SC-FDM signal to the frequency domain. In the frequency domain, subcarrier inverse mapping and frequency domain equalization are performed. Frequency domain equalization can effectively compensate for the multipath effect of the channel and reduce the impact of frequency-selective fading caused by inter-symbol interference (ISI) on the system. Next, an M-point IFFT transforms the signal back to the time domain. Finally, parallel-to-serial conversion and decision processing are performed to recover the data transmitted by the transmitter.

[0031] In SC-FDM systems, there are two main subcarrier allocation methods. The first is centralized mapping, which maps all user data onto contiguous subcarriers, forming a single frequency domain block. The second is distributed mapping, which divides the bandwidth into a set of non-contiguous subcarrier blocks and maps each user's data onto one of these subcarrier sets, thus achieving diversity in the frequency domain. A special case of distributed mapping is interleaved mapping, which divides the bandwidth at the maximum interval and maps user data onto these divided subcarriers to achieve diversity in both the time and frequency domains. After subcarrier allocation, an N-point inverse FFT (IFFT) is used to transform the signal to the time domain.

[0032] In an SC-FDM system, the total number of users equals the bandwidth spreading factor Q = N / M, where N is the total number of subcarriers. This paper will transmit the user data block tail L before transmission. cp Each symbol copied to the data block header forms a cyclic prefix, which is typically removed before any major processing. If the CP length is the same as or longer than the multipath channel delay spread, it helps prevent inter-block interference (IBI) and also ensures orthogonality between different subcarriers, thus avoiding interference between subcarriers.

[0033] like Figure 3 As shown, based on the above-mentioned SC-FDM system, this invention employs a shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation, comprising:

[0034] S1. Obtain the signal y from the receiver of the SC-FDM system. n For signal y n Perform an FFT operation to obtain the frequency domain signal Y. k ;

[0035] Assume the transmitted signal from the transmitter is xn = [x0, x1, ..., xn]. (N-1) ] T After inserting the cyclic prefix CP, the signal is transmitted through a wireless channel. The receiving end receives the transmitted signal and converts it back to a digital signal using a digital-to-analog converter. The cyclic prefix CP is then removed from the digital signal to obtain the signal y. n =[y0,y1,…,y (N-1) ] T Its time-domain expression can be written as:

[0036]

[0037] Among them, h n It is the channel impulse response matrix, vn It has a mean of 0 and a variance of σ. 2 Additive white Gaussian noise.

[0038] Received signal y n After FFT transformation, it can be represented as:

[0039] Y k =H k X k +V k (2)

[0040] Where MMSE is the minimum mean square error, H k It is the channel impulse response matrix, X k For the transmit signal of the SC-FDM system's transmitter, V k It has a mean of 0 and a variance of σ. 2 Additive white Gaussian noise.

[0041] S2, for the frequency domain signal Y k Feedforward equalization and MMSE feedback equalization are performed separately to obtain the feedforward equalized signal Z. k and feedback equalization signal G k，0 ;

[0042] For frequency domain signal Y k Separate feedforward equalization includes: for the frequency domain signal Y k By sequentially performing feedforward FDE (frequency domain equalization) and Delay, the feedforward equalized signal Z is obtained. k .

[0043] For frequency domain signal Y k Feedback balancing includes:

[0044] S21, Regarding signal y n Perform MMSE equalization to obtain the equalized signal T. k and judgment signal

[0045] For signal y n Performing MMSE equalization includes:

[0046] S211. Using the MMSE equalizer to adjust the frequency domain signal Y k The process is performed to obtain the equalized signal T. k ;

[0047] MMSE equalizer coefficients in, σ is the conjugate matrix of the channel impulse response matrix. 2 Let P be the noise power of the additive white Gaussian noise in the SC-FDM system, and let P be the power of the transmitted signal at the transmitter of the SC-FDM system.

[0048] From equation (2), we can see that the data signal after MMSE equalization is:

[0049] T k =W k Y k (3)

[0050]

[0051] in

[0052]

[0053] Δ k =[Δ0,Δ1,…,Δ N-1 ] T The frequency domain form of the residual inter-symbol interference after equalization. This is frequency domain noise.

[0054] S212, Regarding the equalization signal T k Perform IFFT operation to obtain the time-domain signal s n,0 ;

[0055] Applying an IFFT to equation (4) yields:

[0056]

[0057] In the formula, δ n and These are the residual inter-symbol interference and noise interference after MMSE equalization.

[0058] S213, Regarding the time-domain signal s n,0 Make a judgment and receive a judgment signal.

[0059] S22, Regarding the judgment signal Noise interference is estimated to obtain the noise interference factor Q. k ;

[0060] On the judgment signal Noise interference estimation includes:

[0061] For signal Perform an FFT operation to obtain the signal S. k,0 ; will signal S k,0 and signal T k Superposition yields signal P. k ; Calculate the coefficients of the noise predictor Signal P k With coefficient B k Multiplying them together yields the noise interference factor Q. kAmong them, H m Let N be the channel impulse response matrix of subcarrier m, where m is the index of the subcarrier in the SC-FDM system, and N is the total number of subcarriers in the SC-FDM system.

[0062] The calculation of the coefficients for the noise predictor includes:

[0063] Assume R k =X k Then the error E k for:

[0064] E k =U k -X k =(1-B k (W) k H k -1)X k +(1-B k W k V k (8)

[0065] Construct the mean square error E[ε]:

[0066]

[0067] Introduce constraints:

[0068]

[0069] Among them, B m To predict the noise coefficients on the m-th subcarrier, a cost function J is constructed using the Lagrange multiplier method:

[0070]

[0071] Where λ is the Lagrange multiplier, derived from...

[0072]

[0073] have to

[0074]

[0075] in, W is the coefficient of the MMSE equalizer. k conjugate, B is the coefficient of the noise predictor. k The conjugate of W can be seen. k With B k Irrelevant, substitute J, then by

[0076]

[0077] have to

[0078]

[0079] Then through

[0080]

[0081] in, For the conjugate of the noise prediction coefficients on the m-th subcarrier, we get

[0082]

[0083] but

[0084]

[0085] As can be seen from the formula, the noise prediction structure and MMSE equalization are independent of each other, and as long as the channel information H is obtained... k Then the equalizer coefficient W k With noise predictor coefficient B k Therefore, the coefficients of the noise predictor do not need to be updated during the iteration process, which simplifies the iteration calculation process and improves the equalization efficiency.

[0086] S23, Based on the noise interference factor Q k For the equalization signal T k Processing is performed to obtain a decision signal.

[0087] Based on the noise interference factor Q k For the equalization signal T k The processing includes: equalizing the signal T k and noise interference factor Q k By superimposing the signals, a noise-canceling signal U is obtained. k For signal U k Perform IFFT operation to obtain the time-domain signal u n For time-domain signal u n Make a judgment and receive a judgment signal.

[0088] S24, Regarding the judgment signal Perform FFT operation to obtain the frequency domain signal S k,1 ;

[0089] S25, Regarding the frequency domain signal S k,1 Perform a feedback equalization process (FDE) to obtain the feedback equalization signal G. k，0 .

[0090] S3, feedforward equalization signal Z k and feedback equalization signal G k，0Superposition yields the equalized signal D. k，0 ;

[0091] S4. For the equalization signal D k，0 Perform IFFT operation to obtain the time-domain signal r n，0 For time-domain signal r n，0 Make a judgment and receive a judgment signal.

[0092] S5, Regarding the judgment signal Residual inter-symbol interference (ISI) is estimated to obtain the residual ISI factor.

[0093] For signal Perform an FFT operation to obtain the frequency domain signal R. k Calculate signal Y k The frequency domain form of residual inter-symbol interference Δ k , will signal R k Substitution The estimated residual inter-symbol interference is obtained. right Perform IFFT operations to obtain the estimated residual inter-symbol interference factor.

[0094] Judgment Signal The signal after MMSE feedback equalization, which combines feedforward equalization and noise suppression, has removed most of the interference and is closer to the original transmitted signal. Therefore, using the fused signal for residual inter-symbol interference estimation can further reduce the estimation error, making it more accurate than using the decision signal after feedback equalization for inter-symbol interference estimation. Using the estimated interference factor for MMSE feedback equalization to eliminate inter-symbol interference can further improve the equalization accuracy.

[0095] S6. Based on the residual inter-symbol interference factor For frequency domain signal Y k Perform feedback equalization to obtain the feedback equalization signal R. k，1 ;

[0096] Based on residual inter-symbol interference factor For frequency domain signal Y k Feedback equalization includes: converting the time-domain signal u n and residual inter-symbol interference factor Superposition yields a signal s that eliminates residual inter-symbol interference. n,2 For signal s n,2 Make a judgment and receive a judgment signal. On the judgment signal Perform FFT operation to obtain the frequency domain signal S k,2 For frequency domain signal S k,2Perform a feedback equalization process (FDE) to obtain the feedback equalization signal G. k，1 .

[0097] S7, feedforward equalization signal Z k and feedback equalization signal G k，1 Superposition yields the equalized signal D. k,1 ;

[0098] S8. For the equalization signal D k,1 Perform IFFT operation to obtain the time-domain signal r n,1 For time-domain signal r n,1 Make a judgment and receive a judgment signal.

[0099] Table 1 compares the complexity of several different equalization algorithms, where N represents the number of FFT transformation points and N1 represents the number of iterations of the IBDFE algorithm. Compared with the traditional IBDFE algorithm, the MMSE-IBDFE algorithm significantly reduces the complexity by eliminating the iteration mechanism. The block iterative equalization method proposed in this invention is slightly more complex than the former, but still less complex than the traditional IBDFE algorithm.

[0100] Table 1 Comparison of the complexity of various IBDFE equalization algorithms

[0101]

[0102] To verify the effectiveness of the equalization method proposed in this invention in shortwave communication, this invention simulates and compares several equalization algorithms. In the simulation, the channel model adopts a shortwave channel with mid-latitude quiet conditions (iturHFMQ), the communication model adopts an SC-FDM system, it is assumed that the channel synchronization is relatively ideal, and compressed sensing (CS) channel estimation is used for channel estimation. The relevant parameters of the system are shown in Table 2.

[0103] Table 2 System Simulation Parameters

[0104]

[0105] Table 3 provides a brief introduction and analysis of shortwave channels in three different environments from the perspectives of multipath delay spread and Doppler spread. iturHFMQ, iturHFMM, and iturHFMD are a series of standard channel models defined by the International Telecommunication Union Radiocommunication Sector (ITU-R).

[0106] Table 3 Shortwave Channel Parameters

[0107]

[0108] like Figure 4As shown, after two iterations, the method of this invention has essentially converged. The theoretical part shows that the method proposed in this invention is equivalent to the MMSE-IBDFE equalization algorithm with zero iterations, and achieves good results with only one iteration, at a bit error rate of 10%. -4 A gain of 0.85dB can be obtained at that time.

[0109] Figure 5 To compare the performance of the method of this invention under different subcarrier mapping methods in a favorable shortwave environment, the number of iterations was set to 2. Figure 5 As can be seen, in well-drained shortwave fading channels, the interleaved mapping method has a more significant advantage in bit error rate performance than the centralized mapping method. This is because the interleaved mapping method, through distributed subcarrier allocation, can better utilize frequency domain diversity, resist frequency-selective fading and inter-symbol interference, and thus provide better bit error rate performance.

[0110] Figure 6 This section compares the performance of the method of this invention under three different shortwave channel environments. The number of iterations is set to 2. From... Figure 6 A comprehensive comparison reveals that the equalization algorithm fully leverages its advantages and significantly reduces the bit error rate (BER) under favorable channel conditions. However, under moderate and adverse channel conditions, the equalization effect weakens due to increased channel fading and interference, resulting in a higher BER. Therefore, the better the channel conditions, the better the performance of the equalization algorithm.

[0111] Figure 7 This section compares the performance of the various equalization algorithms described above under adverse channel conditions. The traditional IBDFE algorithm and the method proposed in this invention both use a 2-iteration-time ratio. Since the MMSE-IBDFE algorithm eliminates the iterative block structure, it is used directly for comparison.

[0112] from Figure 7 As can be seen, the method proposed in this invention has a certain performance improvement compared with other algorithms under harsh channel conditions. The improvement is not obvious in the low signal-to-noise ratio region, but as the signal-to-noise ratio increases, the improved algorithm gradually shows its advantages and significantly reduces the bit error rate, especially in the case of high signal-to-noise ratio.

[0113] Figure 8 This section compares the performance of the various equalization algorithms described above under favorable channel conditions. The traditional IBDFE algorithm and the method proposed in this invention both use an iteration count of 2.

[0114] from Figure 8 It can be clearly seen that when the bit error rate is 10... -4At that time, the method proposed in this invention has a performance gain of approximately 1.8 dB compared to the MMSE-IBDFE algorithm with two iterations, and a performance improvement of 1.25 dB compared to the traditional IBDFE algorithm. This is because ZF equalization forces ISI to zero but does not consider noise amplification, while the method proposed in this invention improves noise processing and effectively cancels residual inter-symbol interference. As the signal-to-noise ratio increases, ISI becomes an important factor affecting the equalization performance of the system, and the bit error rate performance of the above equalization algorithms also increases accordingly. This indicates that the method proposed in this invention has a more significant equalization effect under high signal-to-noise ratio conditions.

[0115] To more clearly observe the improvement effect, Figure 9 The figure shows a 3D comparison of various equalization algorithms, with the proposed method using a 2-iteration method. The results demonstrate that the equalizer's bit error rate performance improves with increasing symbol rate. This is because as the number of symbols transmitted per unit time increases, the subcarrier spacing also increases. A larger subcarrier spacing reduces spectral overlap between adjacent subcarriers, thereby reducing inter-symbol interference and improving the system's bit error rate performance. Furthermore, the figure clearly shows that the improved algorithm exhibits superior performance compared to other equalization algorithms under favorable shortwave conditions.

[0116] The above-described embodiments further illustrate the purpose, technical solution, and advantages of the present invention. It should be understood that the above-described embodiments are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made to the present invention within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation, characterized in that, include: S1. Obtain the signal y from the receiver of the SC-FDM system. n For signal y n Perform an FFT operation to obtain the frequency domain signal Y. k ; S2, for the frequency domain signal Y k Feedforward equalization and MMSE feedback equalization are performed separately to obtain the feedforward equalized signal Z. k and feedback equalization signal G k，0 ; S3, feedforward equalization signal Z k and feedback equalization signal G k，0 Superposition yields the equalized signal D. k，0 ; S4. For the equalization signal D k，0 Perform IFFT operation to obtain the time-domain signal r n，0 For time-domain signal r n，0 Make a judgment and receive a judgment signal. S5, Regarding the judgment signal Residual inter-symbol interference (ISI) is estimated to obtain the residual ISI factor. S6. Based on the residual inter-symbol interference factor For frequency domain signal Y k Perform MMSE feedback equalization to obtain the feedback equalization signal G. k，1 ; S7, feedforward equalization signal Z k and feedback equalization signal G k，1 Superposition yields the equalized signal D. k,1 ; S8. For the equalization signal D k,1 Perform IFFT operation to obtain the time-domain signal r n,1 For time-domain signal r n,1 Make a judgment and receive a judgment signal. Among them, SC-FDM is single-carrier frequency domain equalization, FFT is fast Fourier transform, IFFT is inverse fast Fourier transform, and MMSE is minimum mean square error.

2. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 1, characterized in that, Acquire the signal y at the receiver of the SC-FDM system n This includes: the receiver of an SC-FDM system receives the signal transmitted through the channel, converts the transmitted signal back to a digital signal through digital-to-analog conversion, removes the cyclic prefix (CP) from the digital signal, and obtains the signal y. n .

3. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 2, characterized in that, Step S2 applies the frequency domain signal Y k Performing MMSE feedback equalization includes: S21, Regarding signal y n Perform MMSE equalization to obtain the equalized signal T. k and judgment signal S22, Regarding the judgment signal Noise interference is estimated to obtain the noise interference factor Q. k ; S23, Based on the noise interference factor Q k For the equalization signal T k Processing is performed to obtain a decision signal. S24, Regarding the judgment signal Perform FFT operation to obtain the frequency domain signal S k,1 ; S25, Regarding the frequency domain signal S k,1 Perform a feedback equalization process (FDE) to obtain the feedback equalization signal G. k,0 ; where FDE stands for frequency domain equalization.

4. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 3, characterized in that, For signal y n Performing MMSE equalization includes: S211. Using the MMSE equalizer to adjust the frequency domain signal Y k The process is performed to obtain the equalized signal T. k ; S212, Regarding the equalization signal T k Perform IFFT operation to obtain the time-domain signal s n,0 ; S213, Regarding the time-domain signal s n,0 Make a judgment and receive a judgment signal.

5. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 3, characterized in that, On the judgment signal Noise interference estimation includes: For signal Perform an FFT operation to obtain the signal S. k,0 ; will signal S k,0 and signal T k Superposition yields signal P. k ; Calculate the coefficients of the noise predictor According to signal P k With coefficient B k Obtain the noise interference factor Q k Among them, H k Let σ be the channel impulse response matrix. 2 H represents the noise power of the SC-FDM system, P represents the power of the transmitted signal at the transmitter of the SC-FDM system, and H represents the noise power. m Let be the channel impulse response matrix of the m-th subcarrier, where m is the index of the subcarrier in the SC-FDM system, and N is the total number of subcarriers in the SC-FDM system.

6. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 5, characterized in that, Calculating the coefficients of the noise predictor includes: constructing the mean square error E[ε] and introducing constraints. The cost function is constructed using the Lagrange multiplier method. Estimate the coefficients of the MMSE equalizer based on the cost function J, and estimate the coefficients B of the noise predictor based on the estimated coefficients of the MMSE equalizer and the cost function J. k Where λ is the Lagrange multiplier, and B m Let be the noise prediction coefficient on the m-th subcarrier.

7. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 3, characterized in that, Based on the noise interference factor Q k For the equalization signal T k The processing includes: equalizing the signal T k and noise interference factor Q k By superimposing the signals, a noise-canceling signal U is obtained. k For signal U k Perform IFFT operation to obtain the time-domain signal u n For time-domain signal u n Make a judgment and receive a judgment signal.

8. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 7, characterized in that, Based on residual inter-symbol interference factor For frequency domain signal Y k Performing MMSE feedback equalization includes: converting the time-domain signal u n and residual inter-symbol interference factor Superposition yields a signal s that eliminates residual inter-symbol interference. n,2 For signal s n,2 Make a judgment and receive a judgment signal. On the judgment signal Perform FFT operation to obtain the frequency domain signal S k,2 For frequency domain signal S k,2 Perform a feedback equalization process (FDE) to obtain the feedback equalization signal G. k,1 .

9. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 1, characterized in that, According to the signal Residual inter-symbol interference estimation includes: estimating the signal Perform an FFT operation to obtain the frequency domain signal R. k Calculate signal Y k The frequency domain form of residual inter-symbol interference Δ k , will signal R k Substitute Δ k The estimated residual inter-symbol interference is obtained. right Perform IFFT operations to obtain the estimated residual inter-symbol interference factor.

10. The shortwave SC-FDM block iterative equalization method for residual inter-symbol interference cancellation according to claim 9, characterized in that, Calculate signal T k The frequency domain form of residual intersymbol interference includes: coefficients of the MMSE equalizer. Frequency domain signal Y k =H k X k +V k Then the equalization signal in, H is the conjugate matrix of the channel impulse response matrix. k Let X be the channel impulse response matrix. k For the transmitted signal of the SC-FDM system's transmitter, σ 2 Let V be the noise power of the transmitted signal at the transmitter of the SC-FDM system, and P be the power of the transmitted signal at the transmitter of the SC-FDM system. k It is additive white Gaussian noise. For frequency domain noise, For signal Z k The frequency domain form of residual inter-symbol interference.

Images