CN114244670B - Blind channel estimation method and system based on channel coding assistance - Google Patents
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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
Technical Field
The invention relates to a blind channel estimation method and a blind channel estimation system assisted by channel coding, belonging to the field of communication signal processing.
Background
Orthogonal Frequency Division Multiplexing (OFDM) technology has been widely used in various standards due to its outstanding advantages such as high spectral efficiency and resistance to multipath fading, for example: 802.11, long Term Evolution (LTE), wiMAX, etc. To counteract the effects of multipath fading, OFDM communication systems require channel estimation and equalization. The traditional channel estimation algorithm is mainly a frequency domain pilot frequency assistance-based non-blind channel estimation method, and includes a Least Square (LS) algorithm, a Minimum Mean Square Error (MMSE) algorithm, a Linear Minimum Mean Square Error (LMMSE) algorithm, a Discrete Fourier Transform (DFT) algorithm, and the like. The above algorithm relies on pilot symbols inserted into the OFDM signal, which results in the consumption of time-frequency resources and the reduction of transmission rate in the OFDM system. For the deficiency, a blind channel estimation algorithm can be adopted in the OFDM system, and this kind of method does not need to insert pilot symbols into the transmission signal, so the frequency band utilization rate of the OFDM system can be obviously improved, and the method mainly includes two categories: statistical methods and deterministic methods. The former uses the statistical characteristics of the transmitted and received signals, such as correlation function, correlation matrix, etc., to realize the function of channel estimation, wherein more methods including subspace method and linear precoding method are used; the latter utilizes the inherent characteristics of the transmitted modulated signal, and the corresponding signal processing module of the method is generally placed after the DFT operation of the receiving end, wherein the maximum likelihood blind estimation method, the blind estimation algorithm based on the additive pilot frequency and the blind estimation algorithm based on the receiving diversity are more used. However, all the above blind estimation algorithms have large computational complexity, and the channel estimation accuracy is not high.
Disclosure of Invention
Aiming at the following technical defects of the existing OFDM system channel estimation method: the problem that the frequency spectrum utilization rate is reduced due to the fact that pilot frequency symbols are inserted in a traditional non-blind estimation method; and (II) the traditional blind estimation method has the defects of high computational complexity and poor estimation performance. The invention mainly aims to provide a blind channel estimation method and a blind channel estimation system based on channel coding assistance, wherein hard decision bit information output by a decoder is iteratively fed back to a channel estimation module, and the hard decision bit information is used as prior information of transmitted data to replace the function of an original pilot frequency symbol, so that the blind channel estimation method and the blind channel estimation system have the following main advantages: a pilot frequency symbol does not need to be inserted at a sending end, so that the problem of frequency spectrum utilization rate reduction caused by the insertion of the pilot frequency symbol is avoided, and the throughput of the OFDM system is obviously improved; and secondly, on the basis of a 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 purpose of the invention is realized by the following technical scheme.
The invention discloses a blind channel estimation method based on channel coding assistance, which comprises the following steps:
step one, a signal having the following frame format is transmitted.
The frame format is: length of N sym In an OFDM frame of symbols, pilot information is inserted into the first symbol, followed by (N) sym -1) OFDM symbols without inserting additional pilot symbols.
And step two, receiving the signal sent in the step one, extracting a pilot frequency symbol in the first OFDM symbol, and performing frequency domain channel estimation.
X (n) represents the transmitted time domain signal, h (n) represents the taps of the multipath channel, the number of channel taps is L, ω (n) represents the noise, y (n) represents the received signal, x represents the linear convolution, the received signal is represented by the following formula,
after removing the cyclic prefix, the effective sequence of the received OFDM symbol is as follows,
wherein
Which represents a cyclic convolution, N is the number of FFT points of the OFDM system. Note N sc A frequency domain expression of received data is expressed by the following formula, where X (k) is a DFT transform of X (n), H (k) is a DFT transform of H (n), Y (k) is a DFT transform of Y (n), and W (k) is a DFT transform of ω (n) for the number of OFDM subcarriers,
Y(k)＝X(k)·H(k)+W(k),k＝0,...,N sc -1 (3)
let 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,
the estimated value of H (k) is derived by LS estimation algorithm when X (k) is known. Note X p (k) Is a pilot symbol, X p ＝[X p (0),...,X p (N sc -1)] T ，
LS estimate of H->
As shown in the following formula,
obtaining the LS channel estimation result of the first OFDM symbol according to the formula
Each element in>
The expression of (a) is as follows,
and (i) in the corner mark represents the ith OFDM symbol.
And step three, using the channel estimation result of the first OFDM symbol to perform channel equalization on the second OFDM symbol, and performing subsequent digital demodulation and channel decoding on the equalized result to obtain a variable node output result of the decoder. The flow in step three is not limited to processing the second OFDM symbol, and the same operation needs to be performed when all the OFDM symbols perform channel estimation from the second OFDM symbol, that is, the iterative process of the method of the present invention is started from step three. To emphasize generality, the OFDM symbol processed in the subsequent step three is the ith OFDM symbol, i =2,3.
Using the channel estimation result of the i-1 th OFDM symbol to perform channel equalization on the i-th OFDM symbol, starting from the second OFDM symbol, inserting no pilot symbol, and performing channel equalization
The expression is as follows,
then, the subsequent digital demodulation process is carried out to obtain the soft information of each bit
M = 0.., M-1,M is &>
The bit number after digital demodulation transmits the bit soft information to an LDPC decoder to carry out LDPC channel decoding to obtain decoding output of all variable nodes including check bitsResult->
m＝0,...,M-1。
And step four, carrying out hard decision on the output result of the variable node of the decoder in the step three to obtain bit information, and carrying out digital modulation on the bit information again to obtain a modulation symbol which is called an Iterative Pilot Symbol (IPS) hereinafter. Due to the coding gain brought by the decoder, the accuracy of the IPS symbol is obviously improved compared with the result of channel equalization in the third step, and the equivalent pilot frequency symbol is used for assisting blind channel estimation. Because pilot frequency symbols are not actually inserted in the signal, compared with a communication system adopting non-blind channel estimation, the communication system improves the frequency spectrum utilization rate.
Output result of LDPC decoding
Making hard decision to obtain sequence b (i) (M), M = 0.,. 1, the result is in the form of 0 and 1 bits, the decoded hard decision output result is digitally modulated again, the modulation mode is the same as the original digital modulation mode of the signal, and the modulation result is regarded as an equivalent pilot symbol IPS and is recorded as ∑ er>
i＝2,3,...。
And step five, the iterative pilot symbol IPS obtained in the step three is taken as prior information of the ith OFDM symbol, the IPS is taken as the pilot symbol, channel estimation of the ith OFDM symbol is carried out based on a non-blind channel estimation algorithm, the purpose of carrying out blind channel estimation by the non-blind estimation algorithm is achieved, and compared with the traditional blind channel estimation, the implementation complexity is reduced and the estimation precision is improved. In the estimation algorithm process, firstly, the signal is subjected to LS algorithm-based channel estimation, and then the estimation result of the LS algorithm is subjected to DFT transformation-based denoising processing to obtain the estimation result of the DFT channel estimation algorithm. The denoising processing based on DFT conversion in the step has two purposes, one is to improve the accuracy of channel estimation and improve the error code performance of the communication system; and secondly, noise introduced in the equalization process is reduced, the convergence of the iterative structure is optimized, and the iterative channel estimation structure can be guaranteed to be converged under a lower signal-to-noise ratio.
The IPS is fed back to a channel estimation module, the IPS is regarded as a pilot symbol, and a channel CFR estimation value of the ith OFDM symbol is estimated based on an LS algorithm
And carrying out denoising algorithm processing based on DFT (discrete Fourier transform) on the CFR result obtained by the LS channel estimation algorithm. IDFT conversion is firstly carried out on the estimation result of the LS algorithm to obtain the channel impulse response
As shown in the following formula,
in the channel impulse response
Effective tap information is reserved, the noise of the rest part is set to zero, and the de-noised channel pulse response->
As shown in the following formula, a compound represented by,
then will be
DFT conversion is carried out to obtain the CFR estimation of the ith OFDM symbol based on the DFT channel estimation algorithmResult->
And step six, repeating the step three to the step five, wherein due to the amplification effect of the LDPC decoding on the data SNR and the suppression effect of the DFT denoising algorithm on noise, the channel estimation result CFR of each iteration is gradually accurate, and the estimation accuracy and the error code performance almost the same as those of the non-blind estimation method are achieved under the condition that the received signal-to-noise ratio is large enough.
The invention also discloses a blind channel estimation system based on channel coding assistance, which is used for realizing the blind channel estimation method based on channel coding assistance. The blind channel estimation system based on the channel coding assistance mainly comprises 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 comprises an LS estimation module and a denoising module based on DFT transformation. The channel estimation module relates to a second step and a fifth step, wherein the denoising module based on DFT (discrete Fourier transform) 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 relate to the third step, the channel equalization module compensates the received signal according to the result of channel estimation, and the digital demodulation module performs constellation mapping on the compensated signal to obtain bit soft information and provide input for the channel decoding module. And a channel decoding module relates to a third step, improves the anti-noise performance of the communication system through channel decoding, and ensures the convergence of an iterative structure. The hard decision module and the digital modulation module relate to the fourth step, the hard decision module decides the soft information result output by the channel decoding into 0 bit and 1 bit, and the digital modulation module re-modulates the result output by the hard decision into a digital modulation symbol to provide an equivalent pilot frequency 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 noise immunity of the communication system. The iterative blind channel estimation method based on LDPC coding assistance is abbreviated as LDPC-ICE (LDPC-code-aided iterative channel estimation).
Has the advantages that:
1. the blind channel estimation method and the blind channel estimation system based on the channel coding assistance, disclosed by the invention, use the same channel estimation algorithm of non-blind channel estimation, but do not insert pilot symbols in signals, so that the computation complexity of blind channel estimation is reduced, and the spectrum utilization rate is improved. The output of the variable node of the decoder is subjected to hard decision and modulation to obtain IPS for calculation of an auxiliary estimation module, and the channel estimation algorithm is completely the same as a non-blind estimation method based on pilot symbol assistance. Compared with a non-blind channel estimation structure, the blind channel estimation structure provided by the invention only needs to add a hard decision device and a modulation module. In the hardware implementation process, the hard decision device only relates to the judgment of the sign bit, and the modulation module only needs a simple lookup table structure and occupies few hardware resources. Therefore, the blind channel estimation system provided by the invention can achieve the calculation complexity similar to that of a non-blind channel estimation system, and is far lower than that of the traditional blind channel estimation algorithm.
2. The invention discloses a blind channel estimation method and a system based on channel coding assistance, wherein a feedback loop is added on the basis of a traditional OFDM receiver, the feedback loop comprises a hard decision device and a modulation module, the structure is simpler, and compared with the traditional flow, other signal processing flows are not greatly changed, so that the blind channel estimation method and the system are easy to transplant into the existing communication system.
3. The invention discloses a blind channel estimation method and a blind channel estimation system based on channel coding assistance, wherein a channel decoding module and a denoising module based on DFT (discrete Fourier transform) are introduced into an iterative feedback loop, the former ensures that an iterative structure can be converged, and the latter optimizes the convergence effect of the iterative structure at a lower signal-to-noise ratio. Under the condition of higher signal-to-noise ratio, the iterative channel estimation performance of the invention is converged under the condition of higher signal-to-noise ratio.
4. The invention discloses a blind channel estimation method and a blind channel estimation system based on channel coding assistance, which adopt a denoising module based on DFT transformation to reduce the noise variance of an estimation result and improve the channel estimation performance.
Drawings
FIG. 1 is a schematic flow chart of a blind channel estimation method and system based on channel coding assistance according to the present invention;
fig. 2 is a block diagram of a signal processing architecture of a receiver of the OFDM communication system of the present invention;
FIG. 3 is a schematic diagram of a denoising module based on DFT transform;
FIG. 4 is a graph comparing BER performance curves of the blind channel estimation method based on channel coding assistance according to the present invention and the conventional non-blind channel estimation method;
fig. 5 is a graph comparing NMSE performance curves of the blind channel estimation method based on channel coding assistance according to the present invention and the conventional non-blind channel estimation method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and with reference to the accompanying drawings.
The system parameters in this example are shown in the following table:
the overall flow chart of the blind estimation method proposed by the present embodiment is shown in fig. 1, the block diagram of the receiver system is shown in fig. 2,
the embodiment discloses a blind channel estimation method based on channel coding assistance, which comprises the following specific implementation steps:
step one, a signal having the following frame format is transmitted.
The frame format is: in the OFDM frame with the length of 120 symbols, pilot information is inserted into the first symbol, and additional pilot symbols do not need to be inserted into the subsequent 119 OFDM symbols.
And step two, receiving the signal sent in the step one, extracting a pilot frequency symbol in the first OFDM symbol, and performing frequency domain channel estimation.
X (n) represents the transmitted time domain signal, h (n) represents the taps of the multipath channel, the number of channel taps is 10, ω (n) represents the noise, y (n) represents the received signal, x represents the linear convolution, the received signal is represented by the following equation,
after removing the cyclic prefix, the effective sequence of the received OFDM symbol is represented as follows,
wherein
Representing a circular convolution, the FFT point number of the OFDM system is 1024. In the embodiment, the frequency domain expression of the received data is shown as the following formula, where the number of OFDM subcarriers is 960, x (k) is x (n), H (k) is H (n), Y (k) is Y (n), and W (k) is ω (n),
Y(k)＝X(k)·H(k)+W(k),k＝0,...,959 (14)
note that 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 representation of the received data frequency domain expression is,
when X (k) is known, an estimated value of H (k) is obtained by an LS estimation algorithm. Note X p (k) Is a pilot symbol, X p ＝[X p (0),...,X p (959)] T ，
LS estimate of H->
As shown in the following formula, a compound represented by,
based on the above formula, the LS channel estimation result of the first OFDM symbol
In each element>
The expression of (a) is as follows,
and (i) in the corner mark represents the ith OFDM symbol.
And step three, using the channel estimation result of the first OFDM symbol to perform channel equalization on the second OFDM symbol, and performing subsequent digital demodulation and channel decoding on the equalization result to obtain a variable node output result of the decoder. The flow of the third step is not limited to processing the second OFDM symbol, and from the second OFDM symbol, the same operation needs to be performed when all OFDM symbols perform channel estimation, that is, the iterative process of the method of the present invention is started from the third step. To emphasize generality, the OFDM symbol processed in the subsequent step three is the ith OFDM symbol, i =2,3.
Using the channel estimation result of the (i-1) th OFDM symbol to perform channel equalization on the (i) th OFDM symbol, no pilot symbol is inserted into the signal from the second OFDM symbol, and the result after the channel equalization
The expression is as follows,
then, the subsequent digital demodulation process is carried out to obtain the soft information of each bit
m＝0,...,1919，/>
The bit number after digital demodulation is 1920, the bit soft information is transmitted to an LDPC decoder to carry out LDPC channel decoding, and decoding output results of all variable nodes including check bits are obtained>
m＝0,...,1919。
And step four, carrying out hard decision on the output result of the variable node of the decoder in the step three to obtain bit information, carrying out digital modulation on the bit information again, and obtaining a modulation symbol which is called Iterative Pilot Symbols (IPS) hereinafter. Due to coding gain brought by a decoder, compared with the result of channel equalization in the third step, the accuracy of the IPS symbol is obviously improved, and the equivalent pilot frequency symbol is used for assisting blind channel estimation. Because pilot frequency symbols are not actually inserted in the signal, compared with a communication system adopting non-blind channel estimation, the communication system improves the frequency spectrum utilization rate.
Output result of LDPC decoding
Hard decision is carried out to obtain a sequence b (i) (m), m = 0. (1919), the result is in the form of 0 and 1 bits, the decoded hard decision output result is digitally modulated again, the modulation mode of the decoded hard decision output result is the same as the original digital modulation mode of the signal, and the modulation result is regarded as an equivalent pilot symbol IPS and is marked as ÷ reserved>
i＝2,3,...120。
And step five, the iterative pilot symbol IPS obtained in the step three is regarded as the prior information of the ith OFDM symbol, the IPS is taken as the pilot symbol, channel estimation of the ith OFDM symbol is carried out based on a non-blind channel estimation algorithm, the purpose of carrying out blind channel estimation by the non-blind estimation algorithm is achieved, and compared with the traditional blind channel estimation, the implementation complexity is reduced and the estimation precision is improved. In the estimation algorithm process, firstly, the LS algorithm-based channel estimation is performed on the signal, and then the DFT transform-based denoising processing is performed on the estimation result of the LS algorithm to obtain the estimation result of the DFT channel estimation algorithm, and a schematic diagram of a denoising module based on the DFT transform is shown in fig. 3. The denoising processing based on DFT conversion in the step has two purposes, one is to improve the accuracy of channel estimation and improve the error code performance of the communication system; secondly, noise introduced in the equalization process is reduced, convergence of the iterative structure is optimized, and it is ensured that the iterative channel estimation structure can converge at a lower signal-to-noise ratio, as shown in fig. 4 and 5.
The IPS is fed back to a channel estimation module, the IPS is regarded as a pilot symbol, and a channel CFR estimation value of the ith OFDM symbol is estimated based on an LS algorithm
And carrying out denoising algorithm processing based on DFT (discrete Fourier transform) on the CFR result obtained by the LS channel estimation algorithm. IDFT conversion is firstly carried out on the estimation result of the LS algorithm to obtain the channel impulse response
As shown in the following formula,
in the channel impulse response
Effective tap information is reserved in the channel, the noise of the rest part is set to zero, and the de-noised channel pulse response->
As shown in the following formula, a compound represented by,
then will be
Performing DFT transformation to obtain the CFR estimation result based on DFT channel estimation algorithm for the ith OFDM symbol>
And step six, repeating the step three to the step five, wherein due to the amplification effect of the LDPC decoding on the data SNR and the suppression effect of the DFT denoising algorithm on noise, the channel estimation result CFR of each iteration is gradually accurate, and the estimation accuracy and the error code performance almost the same as those of the non-blind estimation method are achieved under the condition that the received signal-to-noise ratio is large enough.
To sum up, as shown in fig. 2, this embodiment further 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 the channel coding assistance mainly comprises 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 comprises an LS estimation module and a denoising module based on DFT transformation. The channel estimation module relates to a second step and a fifth step, wherein the denoising module based on DFT (discrete Fourier transform) 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 relate to a third step, the channel equalization module compensates the received signal according to the result of channel estimation, and the digital demodulation module performs constellation mapping on the compensated signal to obtain bit soft information and provide input for the channel decoding module. And a channel decoding module relates to a third step, improves the anti-noise performance of the communication system through channel decoding, and ensures the convergence of an iterative structure. The hard decision module and the digital modulation module relate to the fourth step, the hard decision module decides the soft information result output by the channel decoding into 0 bit and 1 bit, and the digital modulation module re-modulates the result output by the hard decision into a digital modulation symbol to provide an equivalent pilot frequency symbol IPS for the channel estimation module.
I.e. the iteration flow referred to by the dashed arrow in fig. 2. Blind channel estimation results as the number of iterations increases
Gradually converges towards the performance of the non-blind channel estimation, using Normalized Mean Square Error (NMSE) as a measure of accuracy, as shown in fig. 5; using blind channel estimation results +>
The bit error rate performance of the channel equalization also gradually converges to the performance of the non-blind channel equalization, as shown in fig. 4; and the iterative blind channel estimation method has a fast convergence rate, and the error rate performance curve equalized by using the channel estimation result of the second iteration almost coincides with the error rate performance curve equalized by the non-blind channel, as shown in fig. 4. From the performance curves of LDPC-ICE-LS in FIGS. 4 and 5, it can be seen that the iteration at E is performed using the LS algorithm b /N 0 >At 10dB, the error code performance and the estimation accuracy performance can also converge to the same performance as the non-blind LS channel estimation method, but on one hand, the performance is far from the iterative blind channel estimation method using denoising processing based on DFT (discrete Fourier transform)(ii) a On the other hand, in E b /N 0 <At 10dB, the error performance and estimation accuracy performance diverge with increasing iteration number and cannot converge. This shows that the necessity of adding de-noising processing based on DFT transformation in the iterative process improves the performance of the estimation method and optimizes the effect of iterative convergence.
(in the figure, LDPC-ICE-LS represents LDPC-ICE method based on LS algorithm, LDPC-ICE-DFT represents LDPC-ICE method based on DFT algorithm, and Pilot-assisted LS channel estimation method).
The blind channel estimation method based on channel coding assistance is built as an embodiment of the present invention, and the present invention should not be limited to the disclosure of the embodiment and the drawings. It is intended that all equivalents and modifications which do not depart from the spirit of the invention disclosed herein are deemed to be within the scope of the invention.
Claims (4)
1. A blind channel estimation method based on channel coding assistance is characterized in that: comprises the following steps of (a) carrying out,
step one, sending a signal with the following frame format;
the frame format is: length N sym In a one symbol OFDM frame, pilot information is inserted into the first symbol, followed by (N) sym -1) no additional pilot symbols need to be inserted for OFDM symbols;
step two, receiving the signal sent in the step one, extracting a pilot frequency symbol in the first OFDM symbol, and performing frequency domain channel estimation;
step three, using the channel estimation result of the first OFDM symbol to perform channel equalization on the second OFDM symbol, and performing subsequent digital demodulation and channel decoding on the equalization result to obtain a variable node output result of a decoder; the flow of the third step is not limited to processing the second OFDM symbol, and from the second OFDM symbol, the same operation needs to be performed when all the OFDM symbols perform channel estimation, that is, iteration starts from the third step;
the third step is to realize the method as follows,
using the channel estimation result of the i-1 th OFDM symbol to the i-th OFDM symbolThe OFDM symbol is subjected to channel equalization, no pilot symbol is inserted into the signal from the second OFDM symbol, and the result after channel equalization
The expression is as follows,
then, the subsequent digital demodulation process is carried out to obtain the soft information of each bit
M is
The bit number after digital demodulation transmits bit soft information to an LDPC decoder to carry out LDPC channel decoding to obtain decoding output results of all variable nodes including check bits>
Step four, carrying out hard decision on the output result of the variable node of the decoder in the step three to obtain bit information, carrying out digital modulation on the bit information again, and obtaining a modulation symbol which is an Iterative Pilot Symbol (IPS); due to coding gain brought by a decoder, compared with the result of channel equalization in the third step, the accuracy of the IPS symbol is obviously improved, and the equivalent pilot frequency symbol is used for assisting blind channel estimation, so that the frequency spectrum utilization rate is improved;
in step four, the result is output by decoding LDPC
Making hard decision to obtain sequence b (i) (M), M =0, …, M-1, the result is in the form of 0, 1 bit, the decoded hard decision output result is re-digitally modulated in the same way as the original signalThe digital modulation mode is the same, the modulation result is the equivalent pilot symbol IPS which is recorded as ^ er>
Step five, the iterative pilot symbol IPS obtained in the step three is prior information of the ith OFDM symbol, the IPS is used as the pilot symbol, channel estimation of the ith OFDM symbol is carried out based on a non-blind channel estimation algorithm, the purpose of carrying out blind channel estimation by the non-blind channel estimation algorithm is achieved, and compared with the traditional blind channel estimation, the implementation complexity is reduced and the estimation precision is improved; in the channel estimation algorithm process, firstly, performing channel estimation based on an LS channel estimation algorithm on a signal, and then performing denoising processing based on DFT transformation on an estimation result of the LS channel estimation algorithm to obtain an estimation result of the DFT channel estimation algorithm; the denoising processing based on DFT conversion in the step has two purposes, one is to improve the accuracy of channel estimation and improve the error code performance of the communication system; secondly, noise introduced in the equalization process is reduced, and the convergence of an iterative structure is optimized;
in the fifth step, the process is carried out,
feeding back IPS to channel estimation module, using IPS as pilot symbol, and estimating channel estimation result of ith OFDM symbol based on LS channel estimation algorithm
/>
Performing DFT denoising algorithm processing based on DFT transformation on a channel estimation result obtained by an LS channel estimation algorithm; IDFT conversion is firstly carried out on the estimation result of the LS channel estimation algorithm to obtain the channel impulse response
As shown in the following formula,
in the channel impulse response
Effective tap information is reserved, the noise of the rest part is set to zero, and the de-noised channel pulse response->
As shown in the following formula,
then will be
DFT conversion is carried out to obtain the channel estimation result of the ith OFDM symbol based on the DFT channel estimation algorithm
And step six, repeating the step three to the step five, wherein due to the amplification effect of the LDPC decoding on the data SNR and the suppression effect of the DFT denoising algorithm on noise, the channel estimation result of each iteration is gradually accurate, and the same estimation accuracy and error code performance as those of the non-blind channel estimation algorithm are achieved under the condition that the received signal-to-noise ratio is large enough.
2. A blind channel estimation method based on channel coding assistance according to claim 1, characterized in that: the second step is realized by the method that,
x (n) represents the transmitted time domain signal, h (n) represents the taps of the multipath channel, the number of channel taps is L, ω (n) represents the noise, y (n) represents the received signal, x represents the linear convolution, the received signal is represented by the following formula,
after removing the cyclic prefix, the effective sequence of the received OFDM symbol is shown as the following formula,
wherein
Representing cyclic convolution, wherein N is the FFT point number of the OFDM system; note N sc A DFT transform in which X (k) is X (n), H (k) is H (n), Y (k) is Y (n), and W (k) is ω (n) for the number of OFDM subcarriers, and a frequency domain expression of the received data is shown as follows,
Y(k)＝X(k)·H(k)+W(k),k＝0,…,N sc -1 (3)
note the book
The matrix representation of the received data frequency domain representation is,
obtaining an estimated value of H (k) by an LS channel estimation algorithm when X (k) is known; note X p (k) In order to be a pilot symbol,
LS channel estimation result of H->
As shown in the following formula, a compound represented by,
based on the above formula, the LS channel estimation result of the first OFDM symbol
In each element>
The expression of (a) is as follows,
and (i) in the corner mark represents the ith OFDM symbol.
3. Channel coding aided blind channel estimation system for implementing a channel coding aided blind channel estimation method according to claim 1 or 2, characterized in that: the device mainly comprises 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 comprises an LS estimation module and a denoising module based on DFT transformation; the channel estimation module relates to a second step and a fifth step, wherein the denoising module based on DFT (discrete Fourier transform) 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 relate to the third step, the channel equalization module compensates the received signal according to the result of channel estimation, and the digital demodulation module performs constellation mapping on the compensated signal to obtain bit soft information and provide input for the channel decoding module; the channel decoding module relates to the third step, 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 relate to the fourth step, the hard decision module decides the soft information result output by the channel decoding into 0 bit and 1 bit, the digital modulation module re-modulates the result output by the hard decision into a digital modulation symbol, and an equivalent pilot frequency symbol IPS is provided for the channel estimation module.
4. The blind channel estimation system based on channel coding assistance of claim 3, wherein: in the channel coding process, a Low-Density Parity-Check (LDPC) code with excellent error correction performance is used to enhance the anti-noise performance of the channel estimation and communication system; the iterative blind channel estimation method based on LDPC coding assistance is abbreviated as LDPC-ICE (LDPC-code-aided iterative channel estimation).
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