CN114244670B - Blind channel estimation method and system based on channel coding assistance - Google Patents

Abstract

The invention discloses a blind channel estimation method and a blind channel estimation system based on channel coding assistance, and belongs to the field of communication signal processing. The invention feeds back the hard decision bit information output by the decoder to the channel estimation module in an iterative way, and takes the hard decision bit information as prior information of sending data to replace the function of the original pilot frequency symbol, thereby leading the invention to have the following main advantages: pilot symbols do not need to be inserted at a transmitting end, so that the problem of frequency spectrum utilization rate reduction caused by the insertion of the pilot symbols is avoided, and the throughput of the OFDM system is remarkably improved; on the basis of the non-blind channel estimation method, the blind channel estimation is realized by taking the hard decision bit information as the prior information of the transmitted data to replace the function of the original pilot frequency symbol, so that the method has the estimation complexity and the estimation precision which are similar to those of the non-blind channel estimation method, and can achieve the error rate performance which is approximate to the theoretical limit. The invention adds a feedback loop on the basis of the OFDM receiver, has simple structure and is easy to transplant.

Description

A blind channel estimation method and system based on channel coding assistance

Technical Field

The invention relates to a channel coding assisted blind channel estimation method and system, belonging to the field of communication signal processing.

Background Art

Orthogonal Frequency Division Multiplexing (OFDM) technology has been widely used in various standards, such as 802.11, Long Term Evolution (LTE), WiMAX, etc., due to its outstanding advantages such as high spectrum efficiency and resistance to multipath fading. In order to offset the impact of multipath fading, OFDM communication systems need to perform channel estimation and equalization. Traditional channel estimation algorithms are mainly non-blind channel estimation methods based on frequency domain pilot assistance, including the least squares (LS) algorithm, the minimum mean square error (MMSE) algorithm, the linear minimum mean square error (LMMSE) algorithm, and the discrete Fourier transform (DFT) algorithm. The above algorithms rely on the pilot symbols inserted into the OFDM signal, and the insertion of pilot symbols will lead to the consumption of time and frequency resources of the OFDM system and the reduction of the transmission rate. To address this shortcoming, blind channel estimation algorithms can be used in OFDM systems. Such methods do not require the insertion of pilot symbols in the transmitted signal, so they can significantly improve the frequency band utilization of the OFDM system. They are mainly divided into two categories: statistical methods and deterministic methods. The former utilizes the statistical characteristics of the transmitted and received signals, such as correlation functions, correlation matrices, etc., to achieve the channel estimation function. Among them, the more commonly used methods include subspace methods and methods based on linear precoding; the latter utilizes the inherent characteristics of the transmitted modulated signal. The signal processing module corresponding to this method is generally placed after the DFT operation at the receiving end. Among them, the more commonly used methods include maximum likelihood blind estimation methods, blind estimation algorithms based on additive pilots, and blind estimation algorithms based on receiving diversity. However, all of the above blind estimation algorithms have large computational complexity and their channel estimation accuracy is not high.

Summary of the invention

Aiming at the following technical defects in the existing OFDM system channel estimation method: (i) the problem of reduced spectrum utilization caused by inserting pilot symbols in the traditional non-blind estimation method; (ii) the shortcomings of high computational complexity and poor estimation performance in the traditional blind estimation method. The main purpose of the present invention is to provide a blind channel estimation method and system based on channel coding assistance, iteratively feed back the hard decision bit information output by the decoder to the channel estimation module, and use the hard decision bit information as the prior information of the transmitted data to replace the function of the original pilot symbol, so that the present invention has the following main advantages: (i) there is no need to insert pilot symbols at the transmitting end, thereby avoiding the problem of reduced spectrum utilization caused by inserting pilot symbols, and significantly improving the throughput of the OFDM system; (ii) on the basis of the non-blind channel estimation method, by using the hard decision bit information as the prior information of the transmitted data to replace the function of the original pilot symbol, blind channel estimation is realized, so that the present invention has the estimation complexity and estimation accuracy similar to the non-blind channel estimation method, and can achieve the bit error rate performance close to the theoretical limit.

The purpose of the present invention is achieved through the following technical solutions.

The present invention discloses a blind channel estimation method based on channel coding assistance, comprising the following steps:

Step 1: Send a signal with the following frame format.

The frame format is: in an OFDM frame with a length of N _sym symbols, pilot information is inserted into the first symbol, and no additional pilot symbols need to be inserted into the subsequent (N _sym -1) OFDM symbols.

Step 2: Receive the signal sent in step 1, extract the pilot symbol in the first OFDM symbol, and perform frequency domain channel estimation.

Let x(n) represent the transmitted time domain signal, h(n) represent the tap of the multipath channel, the number of channel taps is L, ω(n) represent the noise, y(n) represent the received signal, * represent linear convolution, and the received signal is shown in the following formula:

After removing the cyclic prefix, the effective sequence of the received OFDM symbol is as follows,

表示循环卷积，N为OFDM系统的FFT点数。记N_sc为OFDM子载波个数，X(k)为x(n)的DFT变换，H(k)为h(n)的DFT变换，Y(k)为y(n)的DFT变换，W(k)为ω(n)的DFT变换，接收数据的频域表达式如下式所示，in

Represents circular convolution, N is the number of FFT points in the OFDM system. Let _Nsc be the number of OFDM subcarriers, X(k) be the DFT transform of x(n), H(k) be the DFT transform of h(n), Y(k) be the DFT transform of y(n), W(k) be the DFT transform of ω(n), and the frequency domain expression of the received data is as follows:

Y(k)＝X(k)·H(k)+W(k),k＝0,...,N _sc -1 (3)

H＝[H(0),...,H(N_sc-1)]^T，Y＝[Y(0),...,Y(N_sc-1)]^T，W＝[W(0),...,W(N_sc-1)]^T，接收数据频域表达式的矩阵表示为，Remember X=[X(0),...,X(N _sc -1)] ^T ,

H＝[H(0),...,H(N _sc -1)] ^T ，Y＝[Y(0),...,Y(N _sc -1)] ^T ，W＝[W(0 ),...,W(N _sc -1)] ^T , the matrix of the received data frequency domain expression is expressed as,

H的LS估计值

如下式所示，When X(k) is known, the estimated value of H(k) is obtained by the LS estimation algorithm. Let _Xp (k) be the pilot symbol, _Xp = [ _Xp (0), ..., _Xp ( _Nsc -1)] ^T ,

LS estimate of H

As shown in the following formula,

中各个元素

的表达式为，According to the above formula, the LS channel estimation result of the first OFDM symbol is

Each element

The expression of is,

The (i) in the superscript represents the i-th OFDM symbol.

Step three, using the channel estimation result of the first OFDM symbol, channel equalize the second OFDM symbol, and perform subsequent digital demodulation and channel decoding on the equalized result to obtain the decoder variable node output result. The process of step three is not limited to processing the second OFDM symbol. From the second OFDM symbol onwards, the same operation needs to be performed when channel estimating all OFDM symbols, that is, the iterative process of the method of the present invention begins from step three. In order to emphasize the generality, the OFDM symbol processed in step three is subsequently recorded as the i-th OFDM symbol, i = 2, 3,...

表达式为，Use the channel estimation result of the i-1th OFDM symbol to perform channel equalization on the i-th OFDM symbol. From the second OFDM symbol onwards, no pilot symbol is inserted into the signal. The result after channel equalization is

The expression is,

m＝0,...,M-1，M为

数字解调后的比特数，将比特软信息传递给LDPC译码器，进行LDPC信道译码，得到包括校验位在内所有变量节点的译码输出结果

m＝0,...,M-1。After that, the subsequent digital demodulation process is carried out to obtain the soft information of each bit.

m＝0,...,M-1, M is

The number of bits after digital demodulation, the bit soft information is passed to the LDPC decoder, LDPC channel decoding is performed, and the decoding output results of all variable nodes including the check bit are obtained

m＝0,...,M-1.

Step 4, hard decision is performed on the output result of the decoder variable node in step 3 to obtain bit information, and the bit information is re-digitally modulated, and the obtained modulation symbol is hereinafter referred to as iterative pilot symbol (IPS). Due to the coding gain brought by the decoder, the accuracy of the result of the IPS symbol is significantly improved compared with the channel equalization in step 3, and this equivalent pilot symbol is used to assist blind channel estimation. Since the pilot symbol is not actually inserted into the signal, the communication system of the present invention improves the spectrum utilization compared with the communication system using non-blind channel estimation.

进行硬判决得到序列b⁽ⁱ⁾(m),m＝0,...,M-1，此结果为0、1比特形式，将译码的硬判决输出结果重新进行数字调制，其调制方式应与信号原本数字调制方式相同，调制结果看作等效的导频符号IPS，记为

i＝2,3,...。Output results of LDPC decoding

A hard decision is made to obtain the sequence b ⁽ⁱ⁾ (m), m = 0, ..., M-1. This result is in the form of 0 and 1 bits. The decoded hard decision output result is digitally modulated again. Its modulation method should be the same as the original digital modulation method of the signal. The modulation result is regarded as an equivalent pilot symbol IPS, which is recorded as

i＝2,3,...

Step 5, regard the iterative pilot symbol IPS obtained in step 3 as the prior information of the i-th OFDM symbol, use IPS as the pilot symbol, and perform channel estimation of the i-th OFDM symbol based on the non-blind channel estimation algorithm, so as to achieve the purpose of blind channel estimation with the non-blind estimation algorithm. Compared with the traditional blind channel estimation, it reduces the implementation complexity and improves the estimation accuracy. In the estimation algorithm process, firstly, the signal is estimated based on the LS algorithm, and then the estimation result of the LS algorithm is denoised based on the DFT transform to obtain the estimation result of the DFT channel estimation algorithm. There are two purposes for the denoising based on the DFT transform in this step. One is to improve the accuracy of channel estimation and improve the error performance of the communication system; the other is to reduce the noise introduced in the equalization process, optimize the convergence of the iterative structure, and ensure that the iterative channel estimation structure can converge at a lower signal-to-noise ratio.

Feedback IPS to the channel estimation module, treat IPS as a pilot symbol, and estimate the channel CFR estimate of the i-th OFDM symbol based on the LS algorithm

如下式所示，The CFR result obtained by the LS channel estimation algorithm is processed by a denoising algorithm based on DFT transform. The estimation result of the LS algorithm is first subjected to IDFT transform to obtain the channel impulse response

As shown in the following formula,

中保留有效抽头信息，将其余部分的噪声置零，得到去噪后的信道脉冲响应

如下式所示，The channel impulse response

The effective tap information is retained, and the noise of the rest is set to zero to obtain the denoised channel impulse response

As shown in the following formula,

进行DFT变换，得到第i个OFDM符号基于DFT信道估计算法的CFR估计结果

Then

Perform DFT transformation to obtain the CFR estimation result of the i-th OFDM symbol based on the DFT channel estimation algorithm

Step 6: Repeat steps 3 to 5. Due to the amplification effect of LDPC decoding on data SNR and the noise suppression effect of DFT denoising algorithm, the channel estimation result CFR of each iteration will gradually become more accurate. When the received signal-to-noise ratio is large enough, it can achieve almost the same estimation accuracy and bit error performance as the non-blind estimation method.

The present invention also discloses a blind channel estimation system based on channel coding assistance, which is used to implement the blind channel estimation method based on channel coding assistance. The blind channel estimation system based on channel coding assistance is mainly composed of a channel estimation module, a channel equalization module, a digital demodulation module, a channel decoding module, a hard decision module and a digital modulation module. The channel estimation module includes an LS estimation module and a denoising module based on DFT transformation. The channel estimation module involves steps 2 and 5, wherein the denoising module based on DFT transformation reduces the noise variance of the channel estimation result, improves the channel estimation performance, and optimizes the convergence effect of the iterative structure. The channel equalization module and the digital demodulation module involve step 3, the channel equalization module compensates the received signal according to the result of the channel estimation, and the digital demodulation module performs constellation diagram demapping on the compensated signal to obtain bit soft information, which provides input for the channel decoding module. The channel decoding module involves step 3, which improves the anti-noise performance of the communication system through channel decoding, and ensures the convergence of the iterative structure. The hard decision module and the digital modulation module involve step four. The hard decision module judges the soft information result output by the channel decoding as 0 or 1 bit, and the digital modulation module remodulates the result output by the hard decision into a digital modulation symbol to provide an equivalent pilot symbol IPS for the channel estimation module.

Preferably, in the channel coding process, a low-density parity check (LDPC) code with excellent error correction performance is used to enhance the channel estimation and the anti-noise performance of the communication system. The iterative blind channel estimation method based on LDPC coding assistance is referred to as LDPC-ICE (LDPC-code-aided iterative channel estimation).

Beneficial effects:

1. The present invention discloses a blind channel estimation method and system based on channel coding assistance, which uses the same channel estimation algorithm as the non-blind channel estimation, but does not insert pilot symbols into the signal, thereby reducing the computational complexity of the blind channel estimation and improving the spectrum utilization rate. The output of the decoder variable node is subjected to hard decision and modulation to obtain IPS for the calculation of the auxiliary estimation module. This channel estimation algorithm is exactly the same as the non-blind estimation method based on pilot symbol assistance. Compared with the non-blind channel estimation structure, the blind channel estimation structure proposed in the present invention only needs to add a hard decision maker and a modulation module. In the hardware implementation process, the hard decision maker only involves the judgment of the sign bit, and the modulation module only needs a simple lookup table structure, which occupies very few hardware resources. Therefore, the blind channel estimation system proposed in the present invention can achieve a computational complexity similar to that of the non-blind channel estimation system, which is much lower than the traditional blind channel estimation algorithm.

2. The present invention discloses a blind channel estimation method and system based on channel coding assistance, which adds a feedback loop on the basis of a traditional OFDM receiver. The feedback loop includes a hard decision maker and a modulation module. The structure is relatively simple, and other signal processing processes are not significantly changed compared to traditional processes, and can be easily transplanted into existing communication systems.

3. The present invention discloses a blind channel estimation method and system based on channel coding assistance, which introduces a channel decoding module and a denoising module based on DFT transformation in the iterative feedback loop. The former ensures that the iterative structure can converge, and the latter optimizes the convergence effect of the iterative structure at a lower signal-to-noise ratio. Under a higher signal-to-noise ratio, the iterative channel estimation performance of the present invention is converged under a higher signal-to-noise ratio.

4. The present invention discloses a blind channel estimation method and system based on channel coding assistance, which adopts a denoising module based on DFT transformation to reduce the noise variance of the estimation result and improve the channel estimation performance.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of a blind channel estimation method and system flow based on channel coding assistance according to the present invention;

2 is a block diagram of a receiver signal processing structure of an OFDM communication system according to the present invention;

FIG3 is a schematic diagram of a denoising module based on DFT transformation;

FIG4 is a comparison diagram of BER performance curves of the blind channel estimation method based on channel coding assistance according to the present invention and the traditional non-blind channel estimation method;

FIG5 is a comparison diagram of NMSE performance curves of the blind channel estimation method based on channel coding assistance according to the present invention and the traditional non-blind channel estimation method.

DETAILED DESCRIPTION

In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in combination with specific implementation examples and with reference to the accompanying drawings.

The system parameters in this embodiment are shown in the following table:

The overall flow chart of the blind estimation method proposed in this embodiment is shown in FIG1 , and the block diagram of the receiver system is shown in FIG2 .

This embodiment discloses a blind channel estimation method based on channel coding assistance, and the specific implementation steps are as follows:

Step 1: Send a signal with the following frame format.

The frame format is: in an OFDM frame with a length of 120 symbols, the first symbol is inserted with pilot information, and no additional pilot symbols need to be inserted into the subsequent 119 OFDM symbols.

Step 2: Receive the signal sent in step 1, extract the pilot symbol in the first OFDM symbol, and perform frequency domain channel estimation.

Let x(n) represent the transmitted time domain signal, h(n) represent the tap of the multipath channel, the number of channel taps is 10, ω(n) represent the noise, y(n) represent the received signal, * represent linear convolution, and the received signal is shown in the following formula:

After removing the cyclic prefix, the effective sequence of the received OFDM symbol is expressed as follows:

表示循环卷积，OFDM系统的FFT点数为1024。实施例中OFDM子载波个数为960，X(k)为x(n)的DFT变换，H(k)为h(n)的DFT变换，Y(k)为y(n)的DFT变换，W(k)为ω(n)的DFT变换，接收数据的频域表达式如下式所示，in

represents circular convolution, and the number of FFT points of the OFDM system is 1024. In the embodiment, the number of OFDM subcarriers is 960, X(k) is the DFT transform of x(n), H(k) is the DFT transform of h(n), Y(k) is the DFT transform of y(n), W(k) is the DFT transform of ω(n), and the frequency domain expression of the received data is shown in the following formula:

Y(k)＝X(k)·H(k)+W(k),k＝0,...,959 (14)

H＝[H(0),...,H(959)]^T，Y＝[Y(0),...,Y(959)]^T，W＝[W(0),...,W(959)]^T，接收数据频域表达式的矩阵表示为，Let X = [X(0),...,X(959)] ^T ,

H＝[H(0),...,H(959)] ^T ，Y＝[Y(0),...,Y(959)] ^T ，W＝[W(0),...,W(959)] ^T ，the matrix of the received data frequency domain expression is:

H的LS估计值

如下式所示，When X(k) is known, the estimated value of H(k) is obtained by the LS estimation algorithm. Let _Xp (k) be the pilot symbol, _Xp = [ _Xp (0),..., _Xp (959)] ^T ,

LS estimate of H

As shown in the following formula,

中各个元素

的表达式为，According to the above formula, the LS channel estimation result of the first OFDM symbol is

Each element

The expression of is,

The (i) in the superscript represents the i-th OFDM symbol.

Step three, using the channel estimation result of the first OFDM symbol, perform channel equalization on the second OFDM symbol, and perform subsequent digital demodulation and channel decoding on the equalization result to obtain the decoder variable node output result. The process of step three is not limited to processing the second OFDM symbol. From the second OFDM symbol onwards, the same operation needs to be performed when channel estimating all OFDM symbols, that is, the iterative process of the method of the present invention begins from step three. In order to emphasize the generality, the OFDM symbol processed in step three is subsequently recorded as the i-th OFDM symbol, i = 2, 3, ... 120.

表达式为，Use the channel estimation result of the i-1th OFDM symbol to perform channel equalization on the i-th OFDM symbol. From the second OFDM symbol onwards, no pilot symbol is inserted into the signal. The result after channel equalization is

The expression is,

m＝0,...,1919，

数字解调后的比特数为1920，将比特软信息传递给LDPC译码器，进行LDPC信道译码，得到包括校验位在内所有变量节点的译码输出结果

m＝0,...,1919。After that, the subsequent digital demodulation process is carried out to obtain the soft information of each bit.

m＝0,...,1919，

The number of bits after digital demodulation is 1920. The bit soft information is passed to the LDPC decoder for LDPC channel decoding to obtain the decoding output results of all variable nodes including the check bit.

m＝0,...,1919.

Step 4, hard decision is performed on the output result of the decoder variable node in step 3 to obtain bit information, and the bit information is re-digitally modulated, and the obtained modulation symbol is hereinafter referred to as iterative pilot symbol (IPS). Due to the coding gain brought by the decoder, the accuracy of the result of the IPS symbol is significantly improved compared with the channel equalization in step 3, and this equivalent pilot symbol is used to assist blind channel estimation. Since the pilot symbol is not actually inserted into the signal, the communication system of the present invention improves the spectrum utilization compared with the communication system using non-blind channel estimation.

进行硬判决得到序列b⁽ⁱ⁾(m),m＝0,...,1919，此结果为0、1比特形式，将译码的硬判决输出结果重新进行数字调制，其调制方式应与信号原本数字调制方式相同，调制结果看作等效的导频符号IPS，记为

i＝2,3,...120。Output results of LDPC decoding

A hard decision is made to obtain the sequence b ⁽ⁱ⁾ (m), m = 0, ..., 1919. This result is in the form of 0 and 1 bits. The decoded hard decision output result is re-digitally modulated. Its modulation method should be the same as the original digital modulation method of the signal. The modulation result is regarded as an equivalent pilot symbol IPS, which is recorded as

i＝2,3,...120.

Step 5: The iterative pilot symbol IPS obtained in step 3 is regarded as the prior information of the i-th OFDM symbol. With IPS as the pilot symbol, the channel estimation of the i-th OFDM symbol is performed based on the non-blind channel estimation algorithm, so as to achieve the purpose of blind channel estimation with the non-blind estimation algorithm. Compared with the traditional blind channel estimation, the implementation complexity is reduced and the estimation accuracy is improved. In the estimation algorithm process, the signal is firstly subjected to channel estimation based on the LS algorithm, and then the estimation result of the LS algorithm is subjected to denoising based on the DFT transform to obtain the estimation result of the DFT channel estimation algorithm. The schematic diagram of the denoising module based on the DFT transform is shown in FIG3. There are two purposes for the denoising based on the DFT transform in this step. One is to improve the accuracy of the channel estimation and improve the error performance of the communication system; the other is to reduce the noise introduced in the equalization process, optimize the convergence of the iterative structure, and ensure that the iterative channel estimation structure can converge at a lower signal-to-noise ratio, as shown in FIG4 and FIG5.

Feedback IPS to the channel estimation module, treat IPS as a pilot symbol, and estimate the channel CFR estimate of the i-th OFDM symbol based on the LS algorithm

如下式所示，The CFR result obtained by the LS channel estimation algorithm is processed by a denoising algorithm based on DFT transform. The estimation result of the LS algorithm is first subjected to IDFT transform to obtain the channel impulse response

As shown in the following formula,

中保留有效抽头信息，将其余部分的噪声置零，得到去噪后的信道脉冲响应

如下式所示，The channel impulse response

The effective tap information is retained, and the noise of the rest is set to zero to obtain the denoised channel impulse response

As shown in the following formula,

进行DFT变换，得到第i个OFDM符号基于DFT信道估计算法的CFR估计结果

Then

Perform DFT transformation to obtain the CFR estimation result of the i-th OFDM symbol based on the DFT channel estimation algorithm

Step 6: Repeat steps 3 to 5. Due to the amplification effect of LDPC decoding on data SNR and the noise suppression effect of DFT denoising algorithm, the channel estimation result CFR of each iteration will gradually become more accurate. When the received signal-to-noise ratio is large enough, it can achieve almost the same estimation accuracy and bit error performance as the non-blind estimation method.

In summary, as shown in FIG2, the present embodiment also discloses a blind channel estimation system based on channel coding assistance, which is used to implement the blind channel estimation method based on channel coding assistance. The blind channel estimation system based on channel coding assistance is mainly composed of a channel estimation module, a channel equalization module, a digital demodulation module, a channel decoding module, a hard decision module and a digital modulation module. The channel estimation module includes an LS estimation module and a denoising module based on DFT transformation. The channel estimation module involves steps 2 and 5, wherein the denoising module based on DFT transformation reduces the noise variance of the channel estimation result, improves the channel estimation performance, and optimizes the convergence effect of the iterative structure. The channel equalization module and the digital demodulation module involve step 3, the channel equalization module compensates the received signal according to the result of the channel estimation, and the digital demodulation module performs constellation diagram demapping on the compensated signal to obtain bit soft information, which provides input for the channel decoding module. The channel decoding module involves step 3, which improves the anti-noise performance of the communication system through channel decoding and ensures the convergence of the iterative structure. The hard decision module and the digital modulation module involve step four. The hard decision module judges the soft information result output by the channel decoding as 0 or 1 bit, and the digital modulation module remodulates the result output by the hard decision into a digital modulation symbol to provide an equivalent pilot symbol IPS for the channel estimation module.

的精确度逐渐向非盲信道估计的性能收敛，使用归一化均方误差(NMSE)作为精确度的衡量标准，如图5所示；使用盲信道估计结果

进行信道均衡的误码率性能也逐渐向非盲信道均衡的性能收敛，如图4所示；并且此迭代式盲信道估计方法的收敛速度很快，使用第二次迭代的信道估计结果进行均衡的误码率性能曲线已经几乎与非盲信道均衡的误码率性能曲线相重合，如图4所示。从图4和图5中LDPC-ICE-LS的性能曲线可以看出，使用LS算法进行迭代在E_b/N₀>10dB时，误码性能和估计准确度性能也能收敛到和非盲LS信道估计方法相同的性能，但一方面，其性能与使用基于DFT变换的去噪处理的迭代式盲信道估计方法有很大的差距；另一方面，在E_b/N₀<10dB时，其误码性能和估计准确度性能是随着迭代次数增加而发散的，无法收敛。这说明在迭代过程中加入基于DFT变换的去噪处理的必要性，提升估计方法的性能，并且优化迭代收敛的效果。That is, the iterative process involved in the dotted arrow in Figure 2. As the number of iterations increases, the blind channel estimation results

The accuracy of the channel estimation gradually converges to the performance of non-blind channel estimation, using the normalized mean square error (NMSE) as the accuracy measure, as shown in Figure 5; using the blind channel estimation results

The bit error rate performance of channel equalization gradually converges to the performance of non-blind channel equalization, as shown in Figure 4; and the convergence speed of this iterative blind channel estimation method is very fast. The bit error rate performance curve of equalization using the channel estimation result of the second iteration has almost overlapped with the bit error rate performance curve of non-blind channel equalization, as shown in Figure 4. From the performance curves of LDPC-ICE-LS in Figures 4 and 5, it can be seen that when E _b /N ₀ >10dB is used for iteration using the LS algorithm, the bit error performance and estimation accuracy performance can also converge to the same performance as the non-blind LS channel estimation method, but on the one hand, its performance is far behind that of the iterative blind channel estimation method using DFT-based denoising processing; on the other hand, when E _b /N ₀ <10dB, its bit error performance and estimation accuracy performance diverge with the increase in the number of iterations and cannot converge. This shows the necessity of adding DFT-based denoising processing in the iterative process to improve the performance of the estimation method and optimize the effect of iterative convergence.

(In the figure, LDPC-ICE-LS represents the LDPC-ICE method based on the LS algorithm, LDPC-ICE-DFT represents the LDPC-ICE method based on the DFT algorithm, and Pilot-assisted LS represents the pilot-assisted LS channel estimation method).

The above-mentioned channel coding-assisted blind channel estimation method is an embodiment of the present invention, and the present invention should not be limited to the contents disclosed in the embodiment and the accompanying drawings. Any equivalent or modification completed without departing from the spirit disclosed in the present invention shall fall within the protection scope of the present invention.

Claims (4)

1. A blind channel estimation method based on channel coding assistance, characterized in that it comprises the following steps: Step 1, sending a signal having the following frame format; The frame format is: in an OFDM frame with a length of N _sym symbols, the first symbol is inserted with pilot information, and no additional pilot symbols are inserted into the subsequent (N _sym -1) OFDM symbols; Step 2, receiving the signal sent in step 1, extracting the pilot symbol in the first OFDM symbol, and performing frequency domain channel estimation; Step 3: Use the channel estimation result of the first OFDM symbol to perform channel equalization on the second OFDM symbol, and perform subsequent digital demodulation and channel decoding on the equalization result to obtain the output result of the decoder variable node; the process of step 3 is not limited to processing the second OFDM symbol. From the second OFDM symbol onwards, the same operation needs to be performed when channel estimating all OFDM symbols, that is, iterate from step 3; The implementation method of step three is: Use the channel estimation result of the i-1th OFDM symbol to perform channel equalization on the i-th OFDM symbol. From the second OFDM symbol onwards, no pilot symbol is inserted into the signal. The result after channel equalization is

The expression is,

After that, the subsequent digital demodulation process is carried out to obtain the soft information of each bit.

M is

The number of bits after digital demodulation, the bit soft information is passed to the LDPC decoder, LDPC channel decoding is performed, and the decoding output results of all variable nodes including the check bit are obtained.

Step 4: hard decision is performed on the output result of the decoder variable node in step 3 to obtain bit information, and the bit information is re-digitally modulated to obtain a modulation symbol, which is an iterative pilot symbol (IPS). Due to the coding gain brought by the decoder, the accuracy of the IPS symbol is significantly improved compared with the result of the channel equalization in step 3. This equivalent pilot symbol is used to assist blind channel estimation and improve spectrum utilization. In step 4, the LDPC decoding output result

A hard decision is made to obtain the sequence b ⁽ⁱ⁾ (m), m = 0, ..., M-1. This result is in the form of 0 and 1 bits. The decoded hard decision output result is digitally modulated again. Its modulation method should be the same as the original digital modulation method of the signal. The modulation result is an equivalent pilot symbol IPS, which is recorded as

Step 5: The iterative pilot symbol IPS obtained in step 3 is used as the prior information of the i-th OFDM symbol, and IPS is used as the pilot symbol. Channel estimation of the i-th OFDM symbol is performed based on a non-blind channel estimation algorithm, so as to achieve the purpose of blind channel estimation using a non-blind channel estimation algorithm. Compared with the traditional blind channel estimation, the implementation complexity is reduced and the estimation accuracy is improved. In the channel estimation algorithm process, the signal is firstly subjected to channel estimation based on the LS channel estimation algorithm, and then the estimation result of the LS channel estimation algorithm is subjected to denoising processing based on the DFT transform to obtain the estimation result of the DFT channel estimation algorithm. The denoising processing based on the DFT transform in this step has two purposes: one is to improve the accuracy of channel estimation and enhance the error performance of the communication system; the other is to reduce the noise introduced in the equalization process and optimize the convergence of the iterative structure. In step five, Feedback IPS to the channel estimation module, take IPS as the pilot symbol, and estimate the channel estimation result of the i-th OFDM symbol based on the LS channel estimation algorithm

The channel estimation result obtained by the LS channel estimation algorithm is processed by the DFT denoising algorithm based on DFT transformation; the estimation result of the LS channel estimation algorithm is first subjected to IDFT transformation to obtain the channel impulse response

As shown in the following formula,

The channel impulse response

The effective tap information is retained, and the noise of the rest is set to zero to obtain the denoised channel impulse response

As shown in the following formula,

Then

Perform DFT transformation to obtain the channel estimation result of the i-th OFDM symbol based on the DFT channel estimation algorithm

Step 6: Repeat steps 3 to 5. Due to the amplification effect of LDPC decoding on data SNR and the noise suppression effect of DFT denoising algorithm, the channel estimation result of each iteration will gradually become more accurate, and when the received signal-to-noise ratio is large enough, it will achieve the same estimation accuracy and error performance as the non-blind channel estimation algorithm. 2. A blind channel estimation method based on channel coding assistance as claimed in claim 1, characterized in that: the implementation method of step 2 is: Let x(n) represent the transmitted time domain signal, h(n) represent the tap of the multipath channel, the number of channel taps is L, ω(n) represent the noise, y(n) represent the received signal, * represent linear convolution, and the received signal is shown in the following formula:

After removing the cyclic prefix, the effective sequence of the received OFDM symbol is as follows,

in

represents circular convolution, N is the number of FFT points in the OFDM system; N _sc is the number of OFDM subcarriers, X(k) is the DFT transform of x(n), H(k) is the DFT transform of h(n), Y(k) is the DFT transform of y(n), W(k) is the DFT transform of ω(n), and the frequency domain expression of the received data is shown in the following formula: Y(k)＝X(k)·H(k)+W(k),k＝0,…,N _sc -1 (3) remember

The matrix representation of the received data frequency domain expression is:

When X(k) is known, the estimated value of H(k) is obtained by the LS channel estimation algorithm; _Xp (k) is denoted as the pilot symbol,

LS channel estimation results of H

As shown in the following formula,

According to the above formula, the LS channel estimation result of the first OFDM symbol is

Each element

The expression of is,

The (i) in the superscript represents the i-th OFDM symbol. 3. A blind channel estimation system based on channel coding assistance, used to implement a blind channel estimation method based on channel coding assistance as described in claim 1 or 2, characterized in that: it is mainly composed of a channel estimation module, a channel equalization module, a digital demodulation module, a channel decoding module, a hard decision module and a digital modulation module; the channel estimation module includes an LS estimation module and a denoising module based on DFT transformation; the channel estimation module involves steps 2 and 5, wherein the denoising module based on DFT transformation reduces the noise variance of the channel estimation result, improves the channel estimation performance, and optimizes the convergence effect of the iterative structure; the channel equalization module and the digital demodulation module The module involves step three, the channel equalization module compensates the received signal according to the result of channel estimation, and the digital demodulation module performs constellation diagram de-mapping on the compensated signal to obtain bit soft information, which provides input for the channel decoding module; the channel decoding module involves step three, which improves the anti-noise performance of the communication system through channel decoding and ensures the convergence of the iterative structure; the hard decision module and the digital modulation module involve step four, the hard decision module judges the soft information result of the channel decoding output as 0 or 1 bit, and the digital modulation module re-modulates the result of the hard decision output into a digital modulation symbol, which provides an equivalent pilot symbol IPS for the channel estimation module. 4. The blind channel estimation system based on channel coding assistance as described in claim 3 is characterized in that: in the channel coding process, a low-density parity check (LDPC) code with excellent error correction performance is used to enhance the channel estimation and the anti-noise performance of the communication system; and the iterative blind channel estimation method based on LDPC coding assistance is referred to as LDPC-ICE (LDPC-code-aided iterative channel estimation).

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