CN100588194C - Self-adaptive channel estimation method based on two-dimensional minimum mean square criterion - Google Patents
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- CN100588194C CN100588194C CN200410000909A CN200410000909A CN100588194C CN 100588194 C CN100588194 C CN 100588194C CN 200410000909 A CN200410000909 A CN 200410000909A CN 200410000909 A CN200410000909 A CN 200410000909A CN 100588194 C CN100588194 C CN 100588194C
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Abstract
The invention relates to a self-adaptive channel estimation method based on two-dimensional minimal mean square criterion, wherein 2d-LMS criterion, i.e. the two-dimensional correlation of the channels is utilized for self-adapting channel evaluation, thus no channel statistic characteristic is required when conducting channel evaluation.
Description
Technical field
The present invention relates to communication technical field, relate in particular in a kind of ofdm system adaptive channel estimation method based on 2D-LMS (two-dimentional lowest mean square) criterion.
Background technology
Along with the high speed development of Internet (the Internet) and mobile communication technology, there is potential great demand in wireless data service at a high speed.Yet it is very difficult that high-speed data service is provided in abominable wireless channel environment, and therefore, industry is always for providing the Radio Transmission Technology with superperformance to carry out effort.Existing OFDM (OFDM) technology has the ability of antagonism ISI (intersymbol interference), can provide very high spectrum efficiency simultaneously, therefore is regarded as the professional most possible Radio Transmission Technology that adopts of high speed wireless data.OFDM has application very widely, comprising: XDSL (Digital Subscriber Loop), DAB/DVB (digital audio/video broadcasting), WLAN standard IEEE 802.11a and HIPERLAN/2, wireless metropolitan area network standard IEEE 802.16, or the like.
In order to guarantee that communication system can have good performance in wireless channel environment, the wireless fading channel that becomes in the time of must be to multipath is estimated.Can think the order of accuarcy of channel estimating has determined whether system can provide good wireless transmission quality.Promptly in ofdm system, the quality of channel estimating plays key effect to the performance of ofdm system.At present the channel estimation methods that adopts roughly can be divided into two big classes: blind estimation and based on the channel estimating of pilot tone.Though described blind estimation does not have the higher availability of frequency spectrum because do not need pilot tone, complexity is very high and performance is bad, at present still can't be practical; Described channel estimating based on pilot tone is divided into again based on LS (least square) criterion with based on MMSE (least mean-square error) criterion.Though the LS channel estimating is simple, compare with the MMSE channel estimating, in order to reach identical channel estimating performance (MSE (mean square error) with channel estimating weighs), there is SNR (signal to noise ratio) loss of 10-15dB.But in order to realize the MMSE channel estimating, need know channel statistical characteristic accurately, this can't realize in practice.
Document (Y. (G.) Li is arranged, L.J.Cimini, and N.R.Sollenberger, " Robust channel estimation for OFDM systems with rapid dispersivefading channels, " IEEE Trans.Commun., vol.46, pp.902-915, July1998.) propose the Robust channel estimating, can utilize the two-dimensional correlation characteristic of channel, and insensitive to the variation of channel statistical characteristic.But the Robust channel estimating still needs to know in advance several channel parameters: maximum doppler frequency, maximum multipath time delay and noise power, clearly these three parameters are difficult to obtain.So in order to adapt to unknown channel as much as possible, the Robust channel estimating need suppose that maximum doppler frequency, maximum multipath time delay and noise power all get bigger value, this has inevitably caused the accuracy of channel estimating to descend.
In addition, also has document (D.Schafhuber, G.Matz, and F.Hlawatsch, " Adaptive Wiener filters for time-varying channel estimation inwireless OFDM systems ", ICASSP ' 03, vol.4, pp.IV-688-IV-691,6-10Apr.2003.) channel estimating based on time domain LMS (lowest mean square) criterion proposed, though this method does not need to know channel statistic property, can only utilize the correlation of channel on this dimension of time-domain.Simultaneously, very sensitive based on the channel estimating of time domain LMS criterion for the variation of channel multi-path time delay, and the variation of this channel multi-path time delay is very common in actual environment.
Summary of the invention
In view of above-mentioned existing in prior technology problem, the purpose of this invention is to provide a kind of adaptive channel estimation method, thereby improve the accuracy of channel estimating in the wireless communication system based on two-dimentional lowest mean square criterion, improve the performance of wireless communication system.
The objective of the invention is to be achieved through the following technical solutions:
Described a kind of adaptive channel estimation method based on two-dimentional lowest mean square criterion comprises:
The frequency domain channel value of the pairing same sub-carrier location vector that to be arranged in one or more total dimensions be LM * 1 in A, the L that will initially receive OFDM OFDM symbol with N subcarrier, M=N/2
n, and n is a positive integer;
B, will multiply each other through the frequency domain channel value that rearranges and the current filter weights of 2D-LMS (two-dimentional lowest mean square) filter, the value of acquisition is as channel estimation results, and wherein, the process that obtains described filter weights comprises:
Difference between C, the current channel estimation results of calculating and the channel ideal value;
D, carry out the adjustment of filter weights according to the relation of setting, obtain the filter weights of using in the channel estimation process next time according to the current input vector of described difference and filter.
Described steps A comprises:
Receiving terminal use through data after the demodulate/decode and the output of former FFT (fast Fourier transform) module through decline and the signal that has a noise according to LS (least square) criterion carry out decision-feedback handle obtain filter needs but still without the input signal that rearranges;
Described decision-feedback handled be in the individual vector that to be arranged in a dimension be LM * 1 of the LM on the same sub-carrier location in each OFDM symbol in the pairing frequency domain channel value of OFDM symbol that L of obtaining have N subcarrier, or be arranged in a plurality of vectors, and the dimension of dimension when only being a vector that a plurality of vectors add together is identical, promptly also be LM * 1, M=N/2
n, and 2
nUsually should be less than or equal to log
2N, and n is a positive integer.
Described step B comprises:
One or more total dimensions vector that is LM * 1 is multiplied each other with the current filter weights of each self-corresponding filter respectively, and the value of Huo Deing merges the back as channel estimation results separately.
Described filter is 2D-LMS (two-dimentional lowest mean square) filter, and described two dimension is the time dimension and the frequency dimension of frequency domain channel.
Among the present invention, the acquisition process of the described channel ideal value of step C comprises:
Process decline that data after receiving terminal uses demodulate/decode and former FFT (fast Fourier transform) module are exported and the signal that has noise are estimated frequency domain channel according to LS (least square) criterion;
To handle through IDFT (against discrete fourier transform) through the result who estimates to obtain and be transformed to time-domain signal;
Described time-domain signal is carried out most powerful path catches to handle and obtain wherein stronger time-domain signal sample value, and time-domain signal sample value that will be stronger through DFT (discrete fourier transform) conversion return frequency domain and obtain the channel ideal value.
Described step D comprises:
The filter weights G that uses in the channel estimation process (k+1)=G (k)+μ (k) e (k) * p next time
H(k);
Wherein, described G (k) is current filter weights, and μ (k) is a step factor, and μ (k) value is 1/||p (k) ||
2, e (k) is the current described difference of step C, p
H(k) be the conjugate transpose result of L the pairing LM of an OFDM symbol vector that the frequency domain channel value is constituted rearranging at current process, described k is the count value of carrying out channel estimating.
Described steps A comprises:
When ofdm system is started working, transmitting terminal need send the known OFDM symbol of setting quantity as training sequence, receiving terminal receives the OFDM symbol of described setting quantity, and carry out channel estimating according to LS (least square) criterion, obtain the frequency domain channel value of the OFDM symbol correspondence of setting quantity, as the initial input value of filter;
The vector that it is LM * 1 that the frequency domain channel value that L of initially receiving is had a pairing same sub-carrier location in the OFDM symbol of N subcarrier is arranged in one or more total dimensions, M=N/2
n, and n is a positive integer.
Among the present invention, when ofdm system was started working, the initial value that carries out the filter weights described in the channel estimation process at described receiving terminal was complete 1 matrix.
Described adaptive channel estimation method based on two-dimentional lowest mean square criterion is applicable to ofdm system, comprises MIMO-OFDM (MIMO OFDM) system.
As seen from the above technical solution provided by the invention, the present invention is owing to adopted the 2D-LMS criterion, promptly utilize the two-dimensional correlation of channel to carry out channel estimating, thereby make channel estimating need not to know any channel statistical characteristic, can improve the accuracy of channel estimation results effectively, solve in the prior art owing to can't accurately obtaining the inaccurate problem of channel estimation results that the channel statistical characteristic causes.
Simultaneously, the adaptive channel estimation method based on the 2D-LMS criterion of the present invention does not also need to carry out any matrix inversion operation in implementation procedure, realizes simple; And, by selecting step factor through optimizing, the time that the present invention only needs several OFDM symbols just very rapid convergence to stable state.Another one advantage of the present invention be can be easily the compromise that is implemented between computation complexity and the channel estimating performance of the size of input vector by selective filter handle, and need not to change the physical structure of channel estimating.
Evidence method of the present invention will obviously be better than having other channel estimation methods that writes down in the document now on performance, and goes for the ofdm system under the different radio channel condition.
Description of drawings
Fig. 1 is the structural representation of ofdm system;
Fig. 2 is the rearrangement process schematic diagram of filter input vector p;
Fig. 3 is the theory diagram of 2D-LMS algorithm among the present invention;
Fig. 4 is parallel 2D-LMS Filter Structures schematic diagram;
Fig. 5 is the production process schematic diagram of reference signal;
The OFDM symbol frequency domain channel value that Fig. 6 is suitable for for the present invention choose the pattern schematic diagram;
Fig. 7 chooses the pattern schematic diagram for the inapplicable OFDM symbol of the present invention frequency domain channel value.
Embodiment
Method of the present invention is a kind of adaptive channel estimation method based on the 2D-LMS criterion, for realizing the present invention, the known OFDM symbol that needed to send earlier some (be generally 10 get final product with interior) before ofdm system begins to carry out channel estimating is as training sequence, just can enter a kind of then is the channel estimation process that iterates of chronomere with the OFDM symbol, and each iteration has comprised filtering (or being called estimation) altogether, calculated evaluated error and adaptive three steps of filter weights adjustment of carrying out.And carry out in the process of transfer of data at ofdm system, no longer need to insert pilot tone or training symbol, have higher spectrum efficiency.
Now in conjunction with the accompanying drawings to the embodiment of method of the present invention:
In ofdm system, be provided with the channel estimation process part at receiving terminal, the particular location of channel estimation process part is in FFT (fast Fourier transform) module and constellation and separates between the mapping block referring to Fig. 1.
The specific implementation process of channel estimation methods of the present invention is described below referring to accompanying drawing:
Step 1: when ofdm system initially enters operating state, in order to use the 2D-LMS algorithm to carry out channel estimating, at first need transmitting terminal to send the long training sequence of L OFDM symbol that is, L is usually less than 10, so that receiving terminal can carry out initial channel estimating according to LS (least square) criterion under initial situation, obtain corresponding frequency domain channel value;
The sub-carrier number of supposing ofdm system is N, simultaneously, also needs the initial value of the filter weights of filter to be set to G (0)=1, and promptly G (0) is complete 1 matrix.
Step 2: receiving terminal receives training sequence and carries out initial channel estimating according to LS (least square) criterion, obtain corresponding frequency domain channel value after, it is rearranged obtains p (0), so that carry out channel estimating;
Column vector p (k) is the input of 2D-LMS filter, and k is the count value of carrying out channel estimating, is rearranged by LM frequency domain channel value in L the OFDM symbol before the current time to obtain, and as shown in Figure 2, dimension is LM * 1, wherein M=N/2
n, n is positive integer such as value 0,1,2 as required, but should satisfy 2 usually
nBe less than or equal to log
2N, the value size of M has determined the size of the quantity chosen from the frequency domain channel value of N subcarrier correspondence;
In addition, usually when the number of subcarriers of ofdm system hour, use a filter that the pairing frequency domain channel of current OFDM symbol is estimated to get final product.And when the number of subcarriers of ofdm system is very big, then LM frequency domain channel value in L the OFDM symbol can be arranged as the identical vector of a plurality of dimensions, and multiply each other with the current filter weights of each self-corresponding filter respectively, obtain the channel estimating of the different piece of the pairing frequency domain channel of current OFDM symbol respectively, promptly when the sub-carrier number of ofdm system is very big, as N more than or equal to 2
9In order to reduce computation complexity, improve the real-time of algorithm, subcarrier in the OFDM symbol can be divided into identical several groups of size, use parallel 2D-LMS filter to carry out channel estimating then, as shown in Figure 4, just obtain the channel estimation results of current OFDM symbol after the combination of the channel estimation results of each filter.
Step 3: carry out channel estimating according to filter weights and through L the pairing LM of an OFDM symbol frequency domain channel value that rearranges, obtain current channel estimation results h (0)=G (0) * p (0);
Wherein, column vector h (k) is the frequency domain channel value that needs the current OFDM symbol of estimation, and dimension is N * 1; Matrix G (0) is the coefficient matrix of 2D-LMS filter, i.e. filter weights, and dimension is N * LM.
For guarantee the channel estimation process process continue carry out, after each channel estimation process process finishes, also need described filter weights is adjusted, with the filter weights after the acquisition renewal, and be used for next time channel estimation process process, referring to Fig. 3, the processing procedure that described filter weights is adjusted is as follows:
Step 4: calculate the error between current channel estimation results and ideal communication channel value;
That is to say that for calculating channel evaluated error e (k), will be appreciated that ideal channel response h ' theoretically (k), h ' (k) can't obtain in real system, therefore can only use corresponding estimated value; The present invention obtains h ' processing procedure (k) as shown in Figure 5, at first use data after the demodulate/decode (i.e. decoding) that receiving terminal receives and received signal to carry out DD (decision-feedback) and obtain frequency domain rough estimate value according to LS (least square) criterion, use IDFT (contrary discrete fourier transform) to handle this frequency domain rough estimate value transform then to time domain, re-use the most powerful path harvesting policy and obtain several more intense in time-domain signal footpaths, remaining time domain channel sample value all is changed to 0, and then use DFT (discrete fourier transform) processing conversion and return frequency domain, obtain the ideal channel response h ' estimated value (k) of more accurate current ofdm system;
Obtain described h ' (k) just can calculate after the value current channel estimation errors e (k)=h ' (k)-h (k).
Step 5: referring to Fig. 3, by adaptive filter weights controlling mechanism filter weights is adjusted, the promptly adaptive adjustment of carrying out filter weights according to e (k) value is upgraded, to obtain to be used for the filter weights of channel estimating next time;
Be specially, next time the filter weights G that uses in the channel estimation process (k+1)=G (k)+μ (k) e (k) * p
H(k), wherein, described G (k) is current filter weights, and μ (k) is a step factor, and μ (k) passes through optimization, i.e. μ (k)=1/||p (k) ||
2, p
H(k) be the conjugate transpose result of pairing LM the vector that the frequency domain channel value is constituted in L the OFDM symbol that rearranges at current process, described k is still for carrying out the count value of channel estimating.
Choosing of described step factor μ (k) is most important, and as can be seen, the step factor μ (k) that selects for use among the present invention obtains according to deriving from optimization criteria, is real-time change, rather than changeless.μ (k) is that the power according to filter input signal carries out self adaptation and adjusts, i.e. μ (k)=1/||p (k) ||
2
Among the present invention, only need to send L known OFDM symbol as training sequence in the training stage (being that ofdm system is started working the stage), and no longer needing to insert pilot tone or training symbol at the data transfer phase of ofdm system, this moment, the input signal p (k) of filter carried out rearranging acquisition again behind the DD (decision-feedback) according to the LS criterion by data and received signal after the use demodulate/decode.
Carry out in the normal data transmission procedure at ofdm system, method of the present invention mainly comprises three processing procedures: (1) determines that according to the input signal p (k) of current filter weights G (k) and filter current channel estimation results is h (k)=G (k) * p (k); (2) difference e of calculating between current channel estimation results and channel ideal value with reference to above-mentioned steps 4 (k); (3) carry out the adjustment of filter weights with reference to above-mentioned steps 5.(1), (2) are carried out in circulation in ofdm system, (3) three processes just can realize the real-time estimation to channel.
Among the present invention, the problem that should be noted that is, for the result who keeps each channel estimating can accumulate, promptly make channel estimating to carry out with adaptive iterative manner, this method has requirement for the position of LM frequency domain channel value in L the OFDM symbol that is used for constituting p (k), being specially what require to choose is identical sub-carrier positions in each OFDM symbol, the frequency domain channel value of promptly choosing OFDM symbol as shown in Figure 6 is satisfactory, and the frequency domain channel value of choosing OFDM symbol as shown in Figure 7 then is undesirable.
Among the present invention, by being different emitting antenna selecting suitable training sequences, the adaptive channel estimation method based on the 2D-LMS criterion provided by the invention also is suitable for for MIMO-OFDM (MIMO OFDM) system.Described is that the concrete grammar of different emitting antenna selecting suitable training sequence can reference literature I.Barhumi, G.Leus, and M.Moonen, " OptimalTraining Design for MIMO OFDM Systems in Mobile Wireless Channels ", IEEE Trans.Signal Processing, vol.51, pp.1615-1624, the training sequence design that June 2003. provides.
The above; only for the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, and anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claims.
Claims (9)
1, a kind of adaptive channel estimation method based on two-dimentional lowest mean square criterion is characterized in that comprising:
The frequency domain channel value of the pairing same sub-carrier location vector that to be arranged in one or more total dimensions be LM * 1 in A, the L that will initially receive OFDM OFDM symbol with N subcarrier, M=N/2
n, and n is a positive integer;
B, will multiply each other through the current filter weights of the frequency domain channel value that rearranges and 2D-LMS two dimension lowest mean square filter, the value of acquisition is as channel estimation results, and wherein, the process that obtains described filter weights comprises:
Difference between C, the current channel estimation results of calculating and the channel ideal value;
D, carry out the adjustment of filter weights according to the relation of setting, obtain the filter weights of using in the channel estimation process next time according to the current input vector of described difference and filter.
2, the adaptive channel estimation method based on two-dimentional lowest mean square criterion according to claim 1 is characterized in that described steps A comprises:
Receiving terminal use through data after the demodulate/decode and the output of former FFT fast Fourier transform module through decline and the signal that has a noise according to the LS criterion of least squares carry out decision-feedback handle obtain filter needs but still without the input signal that rearranges;
Described decision-feedback handled be in the individual vector that to be arranged in a dimension be LM * 1 of the LM on the same sub-carrier location in each OFDM OFDM symbol in the pairing frequency domain channel value of OFDM OFDM symbol that L of obtaining have N subcarrier, or be arranged in a plurality of vectors, and the dimension of dimension when only being a vector that a plurality of vectors add together is identical, promptly also be LM * 1, M=N/2
n, and 2
nBe less than or equal to log
2N, and n is a positive integer.
3, the adaptive channel estimation method based on two-dimentional lowest mean square criterion according to claim 2 is characterized in that described step B comprises:
One or more total dimensions vector that is LM * 1 is multiplied each other with the current filter weights of each self-corresponding filter respectively, and the value of Huo Deing merges the back as channel estimation results separately.
4, the adaptive channel estimation method based on two-dimentional lowest mean square criterion according to claim 1 is characterized in that the two dimension of described 2D-LMS two dimension lowest mean square filter is the time dimension and the frequency dimension of frequency domain channel.
5, according to arbitrary described adaptive channel estimation method among the claim 1-4, it is characterized in that the acquisition process of the described channel ideal value of step C comprises based on two-dimentional lowest mean square criterion:
Process decline that data after receiving terminal uses demodulate/decode and former FFT fast Fourier transform module are exported and the signal that has noise are estimated frequency domain channel according to the LS criterion of least squares;
To handle against discrete fourier transform through IDFT through the result who estimates to obtain and be transformed to time-domain signal;
Described time-domain signal is carried out most powerful path catch to handle and obtain wherein stronger time-domain signal sample value, and time-domain signal sample value that will be stronger is returned frequency domain through DFT discrete fourier transform conversion and obtained the channel ideal value.
6, the adaptive channel estimation method based on two-dimentional lowest mean square criterion according to claim 5 is characterized in that described step D comprises:
The filter weights G that uses in the channel estimation process (k+1)=G (k)+μ (k) e (k) * p next time
H(k);
Wherein, described G (k) is current filter weights, and μ (k) is a step factor, and μ (k) value is 1/ ‖ p (k) ‖
2, e (k) is the current described difference of step C, p
H(k) be the conjugate transpose result of L the pairing LM of an OFDM symbol vector that the frequency domain channel value is constituted rearranging at current process, described k is the count value of carrying out channel estimating.
7, the adaptive channel estimation method based on two-dimentional lowest mean square criterion according to claim 1 is characterized in that described steps A comprises:
When ofdm system is started working, transmitting terminal need send the known OFDM symbol of setting quantity as training sequence, receiving terminal receives the OFDM symbol of described setting quantity, and carry out channel estimating according to the LS criterion of least squares, obtain the frequency domain channel value of the OFDM symbol correspondence of setting quantity, as the initial input value of filter;
The vector that it is LM * 1 that the frequency domain channel value that L of initially receiving is had a pairing same sub-carrier location in the OFDM symbol of N subcarrier is arranged in one or more total dimensions, M=N/2
n, and n is a positive integer.
8, the adaptive channel estimation method based on two-dimentional lowest mean square criterion according to claim 7, it is characterized in that, when ofdm system was started working, the initial value that carries out the filter weights described in the channel estimation process at described receiving terminal was complete 1 matrix.
9, the adaptive channel estimation method based on two-dimentional lowest mean square criterion according to claim 1 is characterized in that, this method is applicable to ofdm system, comprises the MIMO-OFDM mimo OFDM systems.
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| OFDM通信系统中的一种通用的信道估计模型. 束锋，罗琳，吴乐南.电路与系统学报，第6卷第2期. 2001 * |
| Robust Channel Estimation forOFDMSystemswithRapidDispersive Fading Channels. Ye (Geoffrey) Li, Leonard J. Cimini, Jr., Nelson R.Sollenberger.IEEE TRANSACTIONS ON COMMUNICATIONS,Vol.46 No.7. 1998 * |
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