A channel equalization method and system for SC-IFDMA system

Abstract

This invention discloses a channel equalization method for an SC-IFDMA system, comprising the following steps: transforming the received data of the SC-IFDMA system to the frequency domain; obtaining pilot symbols and data symbols according to the system frame structure; estimating the current signal-to-noise ratio (SNR) and current channel characteristics based on the pilot symbols to obtain estimated SNR and channel estimation parameters; calculating channel equalizer coefficients based on the estimated SNR and channel estimation parameters; passing the data symbols through the channel equalizer, setting the number of iterations, and iteratively equalizing the data symbols using the channel equalizer coefficients; transforming the equalized data symbols to the time domain and making a decision; determining whether the current number of iterations is the set number; if the set number is reached, outputting the current data symbol as the final iterative equalization result. The method disclosed in this invention improves equalization performance while keeping most of the processing in the frequency domain, reducing the complexity of signal processing.

Description

Technical Field

[0001] This invention relates to the field of wireless communication computing, and in particular to a channel equalization method and system for an SC-IFDMA system. Background Technology

[0002] In existing communication systems, single-carrier interleaved frequency division multiple access (SC-IFDMA) communication systems offer superior advantages in certain application scenarios. It combines the strengths of single-carrier frequency domain equalization (SC-FDE) and orthogonal frequency division multiple access (OFDMA) systems. It can utilize frequency domain equalization techniques to overcome frequency-selective fading, and it can divide the bandwidth into different subcarriers using orthogonal frequency division, dynamically allocating these subcarriers to different users to meet the characteristics of multiple access. Furthermore, SC-IFDMA achieves lower system complexity and a lower peak-to-average power ratio without reducing system capacity or multiple access capabilities, significantly reducing the cost of power amplifiers and transmitters. Therefore, SC-IFDMA is gaining increasing popularity.

[0003] SC-IFDMA systems offer greater scalability for various application scenarios. To suppress subcarrier crosstalk and inter-symbol interference during transmission, based on the signal characteristics of SC-IFDMA, a cyclic prefix (CP) of a certain length is simply added. This involves copying the data from the tail portion of the subcarriers to the very beginning of the symbol. In this way, the orthogonality of the subcarriers can still be guaranteed when multipath effects occur. The duration of the CP should be greater than the maximum delay spread.

[0004] In SC-IFDMA systems, pilot signals can be inserted as needed. Pilot signals consist of a data preamble and pilot symbols. A data preamble is added before the data frame to synchronize the signal at the receiver; it is generally a constant envelope sequence with good autocorrelation, and the start of signal acquisition is considered achieved when the correlation peak exceeds the synchronization threshold. Pilot symbols are used for channel estimation and equalization. By comparing the pilot symbols at both the transmitting and receiving ends, the channel characteristics and quality can be estimated. Different equalization algorithms can then be used to equalize the received data, obtaining the soft information sequence at the receiver.

[0005] Channel equalization algorithms are generally applied in fading channels. Linear equalizers, such as zero-forcing equalization and minimum mean square error (MMSE) equalization, are widely used due to their ease of implementation. However, in deep fading channels and low signal-to-noise ratio scenarios, linear equalizers are significantly affected by noise, greatly limiting their performance. Nonlinear equalizers can effectively suppress noise and exhibit superior performance in ionospheric scattering channels. Block iterative decision feedback equalizers are a type of nonlinear equalizer. They use an iterative approach, performing equalization in the frequency domain, transforming to the time domain for decision, and then transforming back to the frequency domain for iterative equalization, resulting in superior performance. However, since the equalizer coefficients need to be recalculated in each iteration, they have significant complexity. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a channel equalization method and system for SC-IFDMA systems, thereby resolving the performance and complexity issues of channel equalization algorithms in SC-IFDMA systems.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows:

[0008] A channel equalization method for an SC-IFDMA system includes the following steps:

[0009] Step 1: Convert the received data of the SC-IFDMA system to the frequency domain, and obtain the pilot symbols and data symbols according to the frame structure of the SC-IFDMA system.

[0010] Step 2: Estimate the current signal-to-noise ratio and current channel characteristics based on the pilot symbols to obtain the estimated signal-to-noise ratio and channel estimation parameters;

[0011] Step 3: Calculate the channel equalizer coefficients based on the estimated signal-to-noise ratio and channel estimation parameters;

[0012] Step 4: Pass the data symbols through the channel equalizer, set the number of iterations, and use the channel equalizer coefficients to iteratively equalize the data symbols.

[0013] Step 5: Transform the equalized data symbols to the time domain and make a decision;

[0014] Step 6: Determine if the current iteration count is the set number. If the set number has not been reached, return to step 4. If the set number has been reached, output the current data symbol as the final iterative equilibrium result.

[0015] In the above scheme, the SC-IFDMA system frame structure is designed as follows: assuming the total number of subcarriers per symbol is M, the total number of subcarriers is evenly distributed among all users, and each user has N subcarriers, where N is an even number, and M = number of users × N; each frame contains 16 data symbols. For each user's data to be transmitted, a CAZAC sequence of length N is inserted as a pilot symbol every four data symbols, for a total of four identical pilot symbols. The formula for generating the pilot symbol of length N is:

[0016]

[0017] Where n is the nth data of the pilot symbol, and K is the root value of this pilot symbol;

[0018] After inserting the pilot symbol, the total number of transmitted symbols is 20. Then, all transmitted symbols are mapped onto M subcarriers.

[0019] In the above scheme, the specific methods for estimating the signal-to-noise ratio and channel estimation parameters in step 2 are as follows:

[0020] Suppose that four identical pilot symbols of length N are inserted at the transmitting end, denoted as P. (1) (k), P (2) (k), P (3) (k), P (4) (k), k = 1, 2, ..., N, where k is the k-th element of the corresponding pilot symbol; these 4 pilot symbols received at the receiving end are denoted as Y. (1) (k), Y (2) (k), Y (3) (k), Y (4) (k), k = 1, 2, ..., N; take the average power of the received pilot symbols as the average signal power Power_s, and take the average power of the difference between the received pilot symbols as the noise power Power_n, then estimate the signal-to-noise ratio. for:

[0021]

[0022] Y (1) (k), Y (2) (k), Y (3) (k), Y (4) (k) Transform to the frequency domain, and the corresponding channel estimation parameters are calculated as follows:

[0023] H (i) (k)=FFT(Y (i) (k)) / FFT(P (i) (k)), i = 1, 2, 3, 4

[0024] Take their mean as the channel estimation parameter:

[0025]

[0026] In a further technical solution, the formulas for calculating the average signal power Power_s and the noise power Power_n are as follows:

[0027]

[0028]

[0029] Where Re represents the real part, Im represents the imaginary part, and Y... (i) (j) represents the j-th value in the i-th received pilot symbol. Each pilot symbol has N values.

[0030] In the above scheme, step 3, the channel equalizer parameters include the feedforward filter coefficients C(k) and the feedback filter coefficients B(k), which are calculated as follows:

[0031]

[0032]

[0033] in, For the k-th coefficient of the channel estimation parameters, for The corresponding conjugate parameter, α, is a constant that remains unchanged in each iteration. It is calculated as follows:

[0034]

[0035] In the above scheme, the specific method of step 4 is as follows: after the data is FFT transformed to the frequency domain, the data is IFFT transformed back to the time domain after passing through the feedforward filter, the data is hard-decision is made, and then FFT transformed to the frequency domain again and sent to the feedback filter. After iterating several times, the decision is output.

[0036] In the above scheme, step 4, the calculation method for frequency domain iterative equalization of the received data is as follows:

[0037]

[0038] Among them, R m (k) represents the k-th frequency domain data after the m-th iteration. For R m (k) is the frequency domain transformation after being transformed to the time domain and then decided, where R0(k) is the received k-th frequency domain data.

[0039] In further technical solutions, R0(k), The calculation formula is as follows:

[0040] R0(k) = FFT(r0(n))

[0041] r m (n) = IFFT(R) m (k))

[0042]

[0043] Where r0(n) is the nth element of the time-domain data received by the channel equalizer, R0(k) is the element corresponding to the frequency domain transformation of r0(n), and r m (n) represents the nth element of the time-domain data after the mth iteration. For r m The nth element of the decision output of (n) is determined by hard decision based on the sign if the transmitter uses BPSK modulation. Hard decision is performed after demodulation of other modulation methods.

[0044] A channel equalization system for an SC-IFDMA system includes a signal-to-noise ratio estimation module, a channel estimation module, and a channel equalization module;

[0045] The signal-to-noise ratio (SNR) estimation module is used to calculate the signal power and noise power based on the pilot symbols at the receiving end, and to calculate the estimated SNR.

[0046] The channel estimation module is used to calculate channel estimation parameters in the frequency domain based on the pilot symbols at the receiving end.

[0047] The channel equalization module is used to calculate the channel equalizer parameters based on the estimated signal-to-noise ratio and channel estimation parameters, including the feedforward filter coefficients C(k) and the feedback filter coefficients B(k), and to perform iterative equalization on the received data.

[0048] Through the above technical solutions, the channel equalization method and system for SC-IFDMA provided by the present invention have the following beneficial effects:

[0049] (1) The present invention adopts the SC-IFDMA system architecture and inserts pilot symbols into the data symbols, which does not require occupying the subcarrier resources of the SC-IFDMA system and improves the bandwidth utilization.

[0050] (2) This invention uses a constant envelope autocorrelation sequence as pilot symbols and a synchronization preamble, achieving sequence reusability. At the same time, it ensures the low peak-to-average power ratio (PAPR) characteristics of the SC-IFDMA system without disrupting the frame structure, and does not affect the high-power operating environment of the system. The pilot symbols of each frame can guarantee the real-time performance of signal-to-noise ratio estimation and channel characteristic estimation.

[0051] (3) The improved low-complexity frequency domain decision feedback equalizer proposed in this invention keeps the coefficients of the feedforward filter and the feedback filter unchanged during the iteration process. While improving the equalization performance, it makes most of the processing in the frequency domain and reduces the complexity of signal processing.

[0052] (4) The present invention also provides a channel equalization system for SC-IFDMA system, which provides the signal processing calculation method for each processing module. Through modularization, the same module can be called multiple times, so that the computational resources consumed by each module are kept to a minimum. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0054] Figure 1 A schematic diagram of an SC-IFDMA system;

[0055] Figure 2 The frame structure diagram of the designed SC-IFDMA system;

[0056] Figure 3 This is a flowchart of a channel equalization method for an SC-IFDMA system disclosed in this invention;

[0057] Figure 4 This is a structural diagram of an SC-IFDMA channel equalization system;

[0058] Figure 5 This is a diagram showing the received signal structure for 500k bandwidth SC-IFDMA communication.

[0059] Figure 6 A structural diagram of a 500k bandwidth SC-IFDMA data symbol or SC-IFDMA pilot symbol;

[0060] Figure 7 This is a pilot symbol constellation diagram with a length of 128;

[0061] Figure 8 This is a structural diagram of the signal-to-noise ratio estimation module. Detailed Implementation

[0062] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0063] This invention provides a channel equalization method for SC-IFDMA systems, the targeted SC-IFDMA system being as follows: Figure 1 As shown. The transmitting end of the system includes a synchronization preamble generation module, an FFT transform module, a pilot insertion module, a subcarrier mapping module, and an IFFT transform module; the receiving end of the system includes a time-domain synchronization module, an FFT transform module, a subcarrier demapping module, a signal-to-noise ratio estimation module, a channel estimation module, a channel equalization module, and an IFFT transform module.

[0064] SC-IFDMA supports simultaneous processing by multiple users. After the system transmitter inputs the source information of a user, it first generates a synchronization preamble and adds it to the front end of the information for the synchronization acquisition of the receiver signal. Then, it performs FFT transformation to the frequency domain and inserts pilot symbols in the frequency domain for receiver signal processing. After that, the frequency domain data is mapped to the subcarrier of this user and transformed to the time domain by IFFT to complete the single-carrier transmitter processing.

[0065] The receiver first captures the synchronization preamble to determine the signal location, then performs an FFT transformation to the frequency domain for signal processing. Following the same method as the transmitter, it extracts the pilot symbols and uses them to estimate the signal-to-noise ratio and channel. The results are then sent to an equalizer for channel equalization. After equalization, the data is transformed to the time domain using an IFFT to obtain the received soft information.

[0066] Specifically, the functions of each module are as follows:

[0067] Synchronization preamble generation module: A synchronization preamble sequence is placed at the beginning of the information to be sent at the sending end. The synchronization preamble sequence is a CAZAC sequence with constant envelope and good autocorrelation.

[0068] Time-domain synchronization module: The receiving end can capture the synchronization preamble by sliding correlation, determine the position of the data symbol according to the frame structure, and receive the subsequent information.

[0069] FFT Transform Module: Based on the characteristics of SC-IFDMA symbols, the time-domain data is transformed into the frequency domain using FFT.

[0070] IFFT Transform Module: Transforms frequency domain data to the time domain using IFFT transformation.

[0071] Pilot insertion module: The transmitting end inserts pilot symbols at equal intervals into the data symbols as reference signals. The pilot symbols are CAZAC sequences of corresponding lengths.

[0072] Subcarrier mapping module: The SC-IFDMA system supports multi-user transmission by dividing the total subcarriers to different users. After each user generates and transmits information, it is mapped to all subcarriers through interleaving mapping.

[0073] Subcarrier demapping module: The SC-IFDMA system supports multi-user transmission, which divides the total number of subcarriers to different users and obtains the frequency domain data corresponding to the current user through demapping.

[0074] Signal-to-noise ratio (SNR) estimation module: Calculates the estimated SNR of the current channel environment using the pilot symbols received by the receiver.

[0075] Channel estimation sequence: The channel estimation parameters are calculated by the receiver using the pilot symbols inserted at the transmitter as reference signals.

[0076] Channel equalization module: Frequency domain equalization is performed through an improved low-complexity block iterative decision feedback equalizer to obtain soft information of SC-IFDMA data symbols.

[0077] like Figure 2 As shown, the SC-IFDMA system frame structure is designed as follows: assuming the total number of subcarriers per symbol is M, the total subcarriers are evenly distributed among all users, with each user having N subcarriers (N is an even number), and M = number of users × N; each frame contains 16 data symbols. For each user's data to be transmitted, a CAZAC sequence of length N is inserted as a pilot symbol every four data symbols, for a total of four identical pilot symbols. The formula for generating the pilot symbol of length N is:

[0078]

[0079] Where n is the nth data of the pilot symbol, and K is the root value of this pilot symbol;

[0080] After inserting the pilot symbol, the total number of transmitted symbols is 20. Then, all transmitted symbols are mapped onto M subcarriers.

[0081] This invention discloses a channel equalization method for the aforementioned SC-IFDMA system, such as... Figure 3 As shown, it includes the following steps:

[0082] Step 1: Convert the received data of the SC-IFDMA system to the frequency domain, and obtain the pilot symbols and data symbols according to the frame structure of the SC-IFDMA system.

[0083] Let P be the four identical pilot symbols of length N. (1) (k),P (2) (k),P (3) (k),P(4) (k), k = 1, 2, ..., N, where k is the k-th element of the corresponding pilot symbol; these 4 pilot symbols received at the receiving end are denoted as Y. (1) (k), Y (2) (k), Y (3) (k), Y (4) (k), k = 1, 2, ..., N.

[0084] Step 2: Estimate the current signal-to-noise ratio and current channel characteristics based on the pilot symbols to obtain the estimated signal-to-noise ratio and channel estimation parameters.

[0085] If the average power of the received pilot symbols is taken as the average signal power Power_s, and the average power of the difference between the received pilot symbols is taken as the noise power Power_n, then the signal-to-noise ratio can be estimated. for:

[0086]

[0087] Specifically, the formulas for calculating the mean signal power Power_s and the noise power Power_n are as follows:

[0088]

[0089]

[0090] Where Re represents the real part, Im represents the imaginary part, and Y... (i) (j) represents the j-th value in the i-th received pilot symbol. Each pilot symbol has N values.

[0091] Y (1) (k), Y (2) (k), Y (3) (k), Y (4) (k) Transform to the frequency domain, and the corresponding channel estimation parameters are calculated as follows:

[0092] H (i) (k)=FFT(Y (i) (k)) / FFT(P (i) (k)), i = 1, 2, 3, 4

[0093] Take their mean as the channel estimation parameter:

[0094]

[0095] Therefore,

[0096]

[0097] in, This is the k-th element of the channel estimation parameters.

[0098] Step 3: Calculate the channel equalizer coefficients based on the estimated signal-to-noise ratio and channel estimation parameters. The channel equalizer parameters include the feedforward filter coefficients C(k) and the feedback filter coefficients B(k), which are calculated as follows:

[0099]

[0100]

[0101] in, For the k-th coefficient of the channel estimation parameters, for The corresponding conjugate parameter, α, is a constant that remains unchanged in each iteration. It is calculated as follows:

[0102]

[0103] Step 4: Pass the data symbols through the channel equalizer, set the number of iterations, and use the channel equalizer coefficients to iteratively equalize the data symbols.

[0104] Step 5: Transform the equalized data symbols to the time domain and make a decision;

[0105] Step 6: Determine if the current iteration count is the set number. If the set number has not been reached, return to step 4. If the set number has been reached, output the current data symbol as the final iterative equilibrium result.

[0106] The specific method is as follows: after the data is transformed to the frequency domain by FFT, the data is then transformed back to the time domain by IFFT after passing through the feedforward filter. After hard decision on the data, it is transformed to the frequency domain by FFT again and sent to the feedback filter. After several iterations, the decision is output.

[0107] The calculation method for frequency domain iterative equalization of received data is as follows:

[0108]

[0109] Among them, R m (k) represents the k-th frequency domain data after the m-th iteration. For R m (k) is the frequency domain transformation after being transformed to the time domain and then decided, where R0(k) is the received k-th frequency domain data.

[0110] Specifically, R0(k), The calculation formula is as follows:

[0111] R0(k) = FFT(r0(n))

[0112] rm (n) = IFFT(R) m (k))

[0113]

[0114] Where r0(n) is the nth element of the time-domain data received by the channel equalizer, R0(k) is the element corresponding to the frequency domain transformation of r0(n), and r m (n) represents the nth element of the time-domain data after the mth iteration. For r m The nth element of the decision output of (n) is determined by hard decision based on the sign if the transmitter uses BPSK modulation. Hard decision is performed after demodulation of other modulation methods.

[0115] This invention discloses a channel equalization system for an SC-IFDMA system, such as... Figure 4 As shown, the system includes a signal-to-noise ratio estimation module, a channel estimation module, and a channel equalization module;

[0116] The signal-to-noise ratio (SNR) estimation module is used to calculate the signal power and noise power based on the pilot symbols at the receiving end, and to calculate the estimated SNR.

[0117] The channel estimation module is used to calculate channel estimation parameters in the frequency domain based on the pilot symbols received at the receiving end.

[0118] The channel equalization module is used to calculate the channel equalizer parameters based on the estimated signal-to-noise ratio and channel estimation parameters, including the feedforward filter coefficients C(k) and the feedback filter coefficients B(k), and to perform iterative equalization on the received data.

[0119] After synchronizing with the received signal at the receiver of the SC-IFDMA system, pilot symbols and data symbols are extracted through the frame structure. After FFT transformation to the frequency domain, channel estimation and signal-to-noise ratio (SNR) estimation are performed using the pilot symbols. Then, the feedforward filter coefficients and feedback filter coefficients are calculated using the channel estimation parameters and the estimated SNR. The data symbols are then IFFT-transformed to the time domain after passing through the feedforward filter for decision-making. The decision result is then FFT-transformed to the frequency domain, passed through the feedback filter, and iterated. The specific parameters will be described below. In practical applications, Table 1 provides the parameters for two SC-IFDMA systems with bandwidths of 250kHz and 500kHz.

[0120] Table 1 SC-IFDMA Communication System Parameters

[0121]

[0122] To illustrate the effectiveness of the present invention in practical use, in this embodiment, the parameters in number 1 are selected for explanation.

[0123] The signal received by the receiver is as follows Figure 5 As shown, it includes a synchronization preamble sequence, 16 SC-IFDMA data symbols, and 4 SC-IFDMA pilot symbols. The SC-IFDMA data symbols and SC-IFDMA pilot symbols have the same structure, as shown below. Figure 6 As shown, all data blocks are 512 bytes in length. The synchronization preamble sequence and the local sequence are correlated; if the correlation peak exceeds the synchronization threshold, the data symbols and pilot symbols can be extracted. Figure 7 This is a pilot symbol constellation diagram with a length of 128.

[0124] Then you can proceed according to, for example Figure 4 The system shown performs channel equalization. Specifically, the signal-to-noise ratio (SNR) estimation module calculates the signal power and noise power according to the first formula, and then calculates the SNR. For example... Figure 8 As shown, multiplier one performs the squaring operation on the signal power in the first formula, and then accumulates the real and imaginary power through adder one. The pilot symbol subtraction operation can be performed by delaying the output by one pilot symbol in buffer D. The real and imaginary signals after subtraction are sent to multiplier two for squaring, and then the real and imaginary power of the subtracted data are accumulated by adder two. After subtraction through registers, the result is sent to divider for division.

[0125] The first formula includes:

[0126]

[0127]

[0128]

[0129] Where Power_s and Power_n are the estimated signal power and noise power, respectively, Re represents the real part, and Im represents the imaginary part. (i) (j) represents the j-th value in the i-th received pilot symbol. Each pilot symbol has a total of 128 values.

[0130] The channel estimation module calculates the channel estimation parameters according to the second formula, which is:

[0131]

[0132] in, This is the k-th element of the channel estimation parameters. The conjugate parameter is used to insert pilot symbols at the transmitting end. The conjugate parameter can be obtained by inverting the imaginary part.

[0133] The channel equalization module calculates the feedforward filter coefficients C(k) and feedback filter coefficients B(k) of the channel equalizer according to the third formula, which is:

[0134]

[0135]

[0136]

[0137] Where C(k) and B(k) are the coefficients of the feedforward filter and the feedback filter, respectively. These are the conjugate parameters corresponding to the channel estimation parameters.

[0138] The channel equalization module performs iterative equalization of received data according to the fourth formula, which is:

[0139] R0(k) = FFT(r0(n))

[0140] r m (n) = IFFT(R) m (k))

[0141]

[0142]

[0143] Where r0(n) is the nth element of the time-domain data received by the channel equalization module, and R0(k) is the element corresponding to the frequency domain transformation of r0(n). m (n) represents the nth element of the time-domain data after the mth iteration. For r m The nth element of the decision output of (n) is determined by hard decision based on the sign if the transmitter uses BPSK modulation. r m (n)>0, and hard decision is performed after demodulation of other modulation methods.

[0144] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A channel equalization method for an SC-IFDMA system, characterized in that, Includes the following steps: Step 1: Convert the received data of the SC-IFDMA system to the frequency domain, and obtain the pilot symbols and data symbols according to the frame structure of the SC-IFDMA system. Step 2: Estimate the current signal-to-noise ratio and current channel characteristics based on the pilot symbols to obtain the estimated signal-to-noise ratio and channel estimation parameters; Step 3: Calculate the channel equalizer parameters based on the estimated signal-to-noise ratio and channel estimation parameters; Step 4: Pass the data symbols through the channel equalizer, set the number of iterations, and use the channel equalizer parameters to perform iterative equalization on the data symbols; Step 5: Transform the equalized data symbols to the time domain and make a decision; Step 6: Determine if the current iteration count is the set number. If the set number has not been reached, return to Step 4. If the set number has been reached, output the current data symbol as the final iterative equilibrium result. In step 3, the channel equalizer parameters include the feedforward filter coefficients. and feedback filter coefficients ; In step 4, the calculation method for frequency domain iterative equalization of the received data is as follows: ； in, For the first After the nth iteration Individual frequency domain data, for Frequency domain transformation after transformation to the time domain and decision-making. For the received first Individual frequency domain data; , The calculation formula is as follows: ； ； ； in, The first time domain data received by the channel equalizer One element, for The elements corresponding to the frequency domain transform, For the first The time-domain data after the iteration One element, for The first judgment output For each element, if the transmitting end uses BPSK modulation, the decision method is hard decision based on the sign, i.e. ; Other modulation methods are demodulated and then subjected to hard decision.

2. The channel equalization method for an SC-IFDMA system according to claim 1, characterized in that, The SC-IFDMA system frame structure is designed such that, assuming the total number of subcarriers per symbol is... The total number of subcarriers is evenly distributed among all users, with each user having the following number of subcarriers: , Even number, =Number of users × ; Each data frame contains 16 data symbols. Therefore, for each user's data to be transmitted, the insertion length is [length to be inserted] every 4 data symbols. The CAZAC sequence was used as the pilot symbol, with a total of 4 identical pilot symbols inserted, the length of which was... The formula for generating pilot symbols is: ； in, The pilot symbol of the first One data point, The root value of this pilot symbol; After inserting the pilot symbol, the total number of transmitted symbols is 20. Then, all transmitted symbols are mapped to... On each subcarrier.

3. The channel equalization method for an SC-IFDMA system according to claim 1, characterized in that, In step 2, the specific methods for estimating the signal-to-noise ratio and channel estimation parameters are as follows: Assume that a total of 4 identical lengths are inserted at the sending end. The pilot symbol is denoted as For the corresponding pilot symbol There are 4 pilot symbols received at the receiving end, denoted as 4 elements; ; The average power of the received pilot symbols is taken as the average signal power. The average power of the difference between the pilot symbols at the receiving end is taken as the noise power. Then estimate the signal-to-noise ratio. for: ； Will Transforming to the frequency domain, the corresponding channel estimation parameters are calculated as follows: ； Take their mean as the channel estimation parameter: 。 4. The channel equalization method for an SC-IFDMA system according to claim 3, characterized in that, Mean signal power and noise power The calculation formula is as follows: ； ； in, Representative of the actual department, Represents the imaginary part. Indicates the first The first received pilot symbol Each pilot symbol has [number] values. Values.

5. The channel equalization method for an SC-IFDMA system according to claim 1, characterized in that, Feedforward filter coefficients and feedback filter coefficients The calculation method is as follows: ； ， ； in, The first of the channel estimation parameters One coefficient, for The corresponding conjugate parameter, It is a constant that remains unchanged in each iteration, and is calculated as follows: 。 6. The channel equalization method for an SC-IFDMA system according to claim 1, characterized in that, The specific method of step 4 is as follows: after the data is FFT transformed to the frequency domain, the data is passed through the feedforward filter and then IFFT transformed back to the time domain. After hard decision on the data, it is FFT transformed to the frequency domain again and sent to the feedback filter. After several iterations, the decision is output.

7. A channel equalization system for an SC-IFDMA system, employing the channel equalization method for an SC-IFDMA system as described in claim 1, characterized in that, It includes a signal-to-noise ratio estimation module, a channel estimation module, and a channel equalization module; The signal-to-noise ratio (SNR) estimation module is used to calculate the signal power and noise power based on the pilot symbols at the receiving end, and to calculate the estimated SNR. ; The channel estimation module is used to calculate channel estimation parameters in the frequency domain based on the pilot symbols at the receiving end. ; The channel equalization module is used to calculate the channel equalizer parameters, including feedforward filter coefficients, based on the estimated signal-to-noise ratio and channel estimation parameters. Feedback filter coefficients And iteratively balance the data received.

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