CN102291363B - Channel estimation and data detection method for OFDM (Orthogonal Frequency Division Multiplexing) system - Google Patents

Abstract

The invention relates to a channel estimation and data detection method for an OFDM (Orthogonal Frequency Division Multiplexing) system, in particular to a time delay domain base resolution based channel estimation and data detection method of the OFDM system in a high-speed moving scene, belonging to the field of wireless communication. The channel estimation and data detection method comprises the following steps of: resolving a channel frequency domain response matrix into two parts, i.e. a surface feature time delay domain and a surface feature ICI (Inter-Carrier Interference); and realizing the channel estimation of the OFDM system in the high-speed moving scene by simplifying the two parts. According to the channel estimation and data detection method disclosed by the invention, the ICI problem caused due to orthogonality misadjustment between subcarriers of the OFDM system under a time-varying channel can be effectively solved, and therefore influences caused by parameter time variant is overcome in a certain sense; bit error rate can be greatly reduced, the high-speed moving scene can be very well coped, and properties can not be reduced progressively with the increase of mobile carriers and base stations relative to mobile speed.

Description

A kind of channel estimating for ofdm system and data detection method

Technical field

The present invention relates to a kind of channel estimating for ofdm system and data detection method, channel estimating and the data detection method of the ofdm system particularly decomposing based on time delay domain base under a kind of high-speed mobile scene, belong to wireless communication field.

Technical background

OFDM (being called for short OFDM:Orthogonal Frequency Division Multiplexing) technology is high owing to having message transmission rate, anti-multipath interference performance is strong, spectrum efficiency is high, be easy to realize multiple access access and resource is distributed the advantages such as flexible, more and more comes into one's own.At present it is successfully for wired and radio communication, and is applied to the third generation mobile communication system.Certainly, yet there is the technical problem of many reality in the realization of OFDM technology in mobile communication system, and sub-carrier orthogonality problem is one of them comparatively crucial problem just.

In wireless communication system, the relative motion of sending and receiving stations makes channel produce Doppler effect and rapid fading.And Doppler frequency shift and channel rapid fading meeting are destroyed the orthogonality between ofdm system subcarrier, thereby cause the phase mutual interference (ICI, Inter-Carrier Interference) between subcarrier, make system performance degradation.Under high-speed mobile scene, the mobility of terminal is stronger, and channel time-varying characteristics are more obvious, and consequent Doppler effect and channel rapid fading are even more serious, and ICI is also further serious.This ICI being caused by channel time variation, makes ofdm system in carrying out the process of channel estimating, not only will consider how to eliminate additive noise and also must eliminate ICI.Overcoming ICI for the harmful effect of channel estimating, obtain channel status accurately, thereby finally realize ofdm system coherent demodulation, go back the data message that original sender sends, is a research emphasis of current OFDM technology.

Many conventional channel estimation methods are not considered the impact of ICI or ICI are used as to noise processed, therefore can not obtain channel condition information accurately.Some researchs overcome by preliminary treatment the ICI that channel time variation causes, thereby realize, utilize general channel estimation method to obtain channel condition information.In these preconditioning technique researchs, adopt coding techniques can eliminate ICI, its system is simple and realization is convenient, but the availability of frequency spectrum is low, does not meet the high efficiency of transmission requirement in modern communications, has restricted its application in practice; Adopt time domain shaping filter technology can suppress the be shaped secondary lobe of waveform and the band external leakage after shaping, thereby the influencing each other reduction ICI reducing between subcarrier can be used general channel estimation method, but when translational speed is relatively high, this method is no longer applicable; Adopt spatial domain linear antenna arrays to determine that the method for virtual fixed point or Doppler's diversity reception can resist Doppler frequency deviation, thereby eliminate ICI, but it has increased equipment complexity, and needed to be studied.Certainly, the algorithm for estimating that is applicable to ofdm system time varying channel is also in continuous proposition.Wherein some is directed to special or conditional channel, as when normalization Doppler frequency deviation is less than 0.1, thinks that channel tap is with linear change, carry out channel estimating, but owing to there is precondition, practical application is limited as condition.Some research by adopting minimum mean square error criterion (MMSE, Minimum MeanSquared Error) thus carry out to received signal Time-Frequency Domain Filtering processing and eliminate ICI and realize channel estimating, but its complexity is high and need known channel statistical information.Also have some algorithms to carry out channel estimating by increasing pilot tone point quantity, but the stronger required pilot tone point quantity of time variation is larger, this greatly reduces the availability of frequency spectrum.

Summary of the invention

The object of the invention is in order particularly to reduce computational complexity in the OFDM channel estimating of high-speed mobile scene, to improve practicality and avoid utilizing channel statistical information at mobile context, a kind of channel estimating for ofdm system and data detection method have been proposed, this method by channel frequency domain response matrix decomposition for characterizing time delay domain and characterizing two parts of ICI, and by the simple implementation to separately the channel estimating of ofdm system under high-speed mobile scene.

Thinking of the present invention is: regard ICI as between subcarrier confirmable influencing each other, and reduce the scope that influences each other between subcarrier by adding window function at system transmitting terminal; Ofdm system channel frequency domain response is decomposed into two parts that characterize time delay domain and characterize ICI; By carrying out the decomposition based on discrete prolate spheroid body sequence and carry out the constraint based on physics reality to characterizing the matrix of ICI part characterizing the matrix of time delay domain part, reduced the number of unknown parameter to be determined and obtained the relation equation that can solve; Utilize least square method to solve relation equation, and by the iteration denoising of making zero, can obtain channel frequency domain response matrix, thereby realize channel estimating; Utilize the special construction of gained channel frequency domain response matrix, realize the laddering Data Detection of pointwise.

The present invention is achieved by the following technical solutions.

A kind of channel estimating for ofdm system provided by the invention and data detection method, applicable ofdm system has following characteristics: transmitting terminal of the present invention carried out time domain windowing process and reduces to leak with suppressed sidelobes; The present invention is the channel estimation methods based on block pilot tone, requires pilot tone not exist in nonzero element and OFDM data symbol and is provided with virtual subnet carrier wave.The concrete steps of this method are as follows:

1) receiving terminal is set up the target function of channel estimating:

Wherein, R is for receiving the frequency domain representation of signal; it is the frequency domain representation that receives signal section in signal; W is additive noise; H is the corresponding matrix of channel frequency domain; X=[X ₀x ₁x _n-1] and X be known pilot sequence, X _i(i=0...N-1) be the code element on each subcarrier of transmitting terminal transmission; U _j=diag (μ _j) (j=1...P), μ wherein _jfor discrete prolate spheroid body basic sequence; it is the matrix being formed by pilot frequency sequence restructuring; for characterizing the matrix of doppler spread, p=1...P; The corresponding matrix H of channel frequency domain meets following relation:

2) receiving terminal utilization receives signal R and known matrix by least square method, by formula (1), solved the matrix obtaining containing noisy sign doppler spread

3) the receiving terminal R denoising of making zero to received signal, concrete steps are:

3.1 arrange the thresholding M that makes zero, right meet i < M and j < M item zero setting, wherein i, j ∈ [1, L];

3.2 utilize after zero setting with equation is asked for the partial noise in acknowledge(ment) signal;

3.3 utilize equation is asked for the acknowledge(ment) signal after denoising;

4) iteration denoising ask for channel frequency domain response matrix H, comprising:

4.1 repeating steps 1), 2), 3) realize iteration and make zero denoising so that additive noise W=0, its number of repetition is decided by signal to noise ratio;

4.2 execution steps 2) obtain

4.3 utilize obtain channel frequency domain response matrix H;

5) set up Data Detection target function, and utilize target function to ask for data to be tested, the target function of setting up is:

X(i+2)＝{R(i)-H(i，i-M:i+1)X(i-M:i+1)}/H(i，i+2)(2)

Wherein, i ∈ [M, N _d], M is the thresholding that makes zero, N _dfor data to be tested number; X (i-M:i+1) the sequence i-M to i+1 that represents to fetch data forms matrix; H (i, i-M:i+1) represents to get capable i-M to the i+1 row of H matrix i and forms matrix;

6) to step 5) required data to be tested detect differentiation;

7) repeating step 5) and step 6), the data that receive until all have all realized detecting to be differentiated;

Through above-mentioned seven steps, completed OFDM channel estimating and the Data Detection of decomposing based on time delay domain base.

Below the algorithmic derivation process of this invention is described, specific as follows:

1) decomposition of ofdm system channel frequency domain response matrix

Consider a wireless communication system, suppose that the signal that its transmitting terminal sends is:

$s\left(t\right)=x\left(t\right)e^{j2\mathrm{\&pi;}{f}_{c}t}---\left(3\right)$

Wherein, be the Equivalent Base-Band signal of transmitting terminal transmitted signal s (t), X (k) is pilot frequency sequence or data, and Equivalent Base-Band signal bandwidth is B; f _ccarrier frequency for transmitting terminal transmitted signal.The frequency domain representation of s (t) is:

S(w)＝X(w+w _c)(4)

First processing signals need to extract signal, and extract must be in time-domain intercept signal.The major way of time domain intercept signal is to carry out windowing; General ofdm system can think to have carried out adding the intercepting of rectangular window, and therefore, X (w) is the frequency domain representation of the Equivalent Base-Band signal after windowing.

Digital signal processing theory points out, time-domain windowed can cause the expansion of frequency spectrum, and this expansion has caused the leakage of spectrum energy.In order to reduce spread spectrum scope, can select the side lobe attenuations such as Brackman-Harris window, Hanning window, hamming window promptly window function carry out replace rectangle window.

In ofdm system wireless communication procedure, the received signal r (t) of receiving terminal is direct signal component and all multipath component sums, is expressed as:

Wherein, the corresponding direct projection of n=0 path, the number that N (t) is multipath; τ _n(t) be each footpath time delay and r wherein _n(t) be the path in each footpath, c is the light velocity; for Doppler phase shift and wherein v is object translational speed, θ _n(t) be the angle of v and each footpath incident direction, for Doppler frequency shift, f _cfor carrier frequency; Baseband signal after the windowing that x (t) sends for transmitting terminal, x (t-τ _n(t) baseband signal after each footpath time delay) sending for transmitting terminal; α _n(t) be the amplitude in each footpath; W is channel additive noise;

To carry out frequency domain representation and analyse in depth the decomposition that realizes channel frequency domain response by r (t) to received signal below.

At two OFDM symbols in the concern time, the number N of multipath (t), amplitude alpha _n(t), multidiameter delay τ _nand Doppler frequency shift (t) substantially remain unchanged, it is set as respectively to constant, be i.e. N (t)=Z, α _n(t)=α _n, τ _n(t)=τ _n, formula (5) is carried out to the frequency domain representation that Fourier transform can receive signal r (t):

$R\left(w\right)=\mathrm{HX}+W$

$={\mathrm{\&Sigma;}}_{n=0}^Z{\mathrm{\&alpha;}}_n{e}^{j{w}_{d_n}{\mathrm{\&tau;}}_n}{e}^{\mathrm{jw}{\mathrm{\&tau;}}_n}X(w-w_c-w_{d_n})+W---\left(6\right)$

Wherein, H is the corresponding matrix of channel frequency domain; X (*) is the frequency domain representation of transmitting terminal windowing baseband signal x (t); w _c=2 π f _c; w is the frequency domain representation of additive noise;

For ofdm system, receiving terminal will go carrier modulation, time-domain sampling to quantize and discrete Fourier transform to received signal, and wherein time-domain sampling is spaced apart ts, and the frequency domain interval of discrete Fourier transform is Δ f, and there is relation: ts* Δ f=1/N, N is the number of ofdm system subcarrier.So formula (6) can turn to:

$R\left(k\right)={\mathrm{\&Sigma;}}_{n=0}^Z{\mathrm{\&alpha;}}_n{e}^{j{w}_{d_n}{\mathrm{\&tau;}}_n}{e}^{j2\mathrm{\&pi;k\&Delta;f}{\mathrm{\&tau;}}_n}X(\mathrm{k\&Delta;f}-w_{d_n})+W---\left(7\right)$

Wherein, k=0,1,2 ..., N-1; Formula (7) is rewritten as to matrix form is:

$R={\mathrm{\&Sigma;}}_{n=0}^Z{\mathrm{\&alpha;}}_n{e}^{\mathrm{jw}{d}_n{\mathrm{\&tau;}}_n}{F}_n{X}_n+W---\left(8\right)$

Wherein, $F_n=\mathrm{diag}(e^{-j2\mathrm{\&pi;}*0*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}{e}^{-j2\mathrm{\&pi;}*1*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}\&CenterDot;\&CenterDot;\&CenterDot;e^{-j2\mathrm{\&pi;}*(N-1)*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n});$ $X_n=$ ${\left[\begin{array}{cccc}\stackrel{\&OverBar;}{X_0}& \stackrel{\&OverBar;}{X_1}& \&CenterDot;\&CenterDot;\&CenterDot;& {\stackrel{\&OverBar;}{X}}_{N-1}\end{array}\right]}^T,$ ${\stackrel{\&OverBar;}{X}}_1=X(\mathrm{i\&Delta;f}-w_{d_n})i\&Element;\left[\begin{array}{cc}0& N-1\end{array}\right];$ $R={\left[\begin{array}{cccc}{R}_0& R_1& \&CenterDot;\&CenterDot;\&CenterDot;& R_{N-1}\end{array}\right]}^T,$ W is channel additive noise matrix;

From formula (8), can find out, irrelevant with sub-carrier positions, i.e. frequency place in all signal bandwidths identical, therefore, can regard each footpath as not with a unknown quantity of frequency change; F _nitem has been described the impact of time delay for different sub carrier, can be used for characterizing multidiameter delay; And from X _ninterior perhaps expression formula can find out, X _nin each element only relevant with subcarrier and Doppler frequency shift.Therefore, available X _ncharacterize each footpath Doppler frequency shift, also can think to use X _ncharacterize ICI.

2) F _nmatrix and X _nthe expansion of matrix and simplification

From deriving above, $F_n=\mathrm{diag}(e^{-j2\mathrm{\&pi;}*0*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}{e}^{-j2\mathrm{\&pi;}*1*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}\&CenterDot;\&CenterDot;\&CenterDot;e^{-j2\mathrm{\&pi;}*(N-1)*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}).$ Consider F _ndiagonal of a matrix element: $e^{-j2\mathrm{\&pi;}*0*\mathrm{\&Delta;}{\mathrm{f\&tau;}}_n}{e}^{-j2\mathrm{\&pi;}*1*\mathrm{\&Delta;}{\mathrm{f\&tau;}}_n}\&CenterDot;\&CenterDot;\&CenterDot;e^{-j2\mathrm{\&pi;}*(N-1)*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n},$ If channel maximum multipath time delay is: τ _max, can be by any F _nwide when diagonal of a matrix element is regarded as is [0, (N-1) Δ f], and bandwidth is [0, τ _max] band-limited function.

And research shows, utilize the approximate band-limited function that relatively less prolate ellipsoid body sequence can be best, the notable feature of prolate ellipsoid body sequence be exactly can be by most concentration of energy of band-limited function in minority sequence and make time there is minimum energy leakage outside window.Based on this achievement in research, can be to F _nmatrix carries out the expansion based on prolate ellipsoid body sequence, establishes most concentration of energy P prolate ellipsoid body sequence μ of band-limited function _p(p=1...P) upper:

$F_n={\mathrm{\&Sigma;}}_{p=1}^P{y}_p^n\mathrm{diag}\left({\mathrm{\&mu;}}_p\right)---\left(9\right)$

Wherein, for F _nexpansion coefficient based on prolate ellipsoid body sequence; P is larger, and the expansion performance based on prolate ellipsoid body sequence is better, F after launching _nthe energy loss of matrix is less.

Below to X _nmatrix is analyzed simplification.

As previously mentioned, the windowing process of transmitting terminal makes signal produce spread spectrum, thereby a sub-carrier energy is expanded on other subcarriers, therefore, and X _nelement in matrix be equal to the weighting of corresponding code element on the front all subcarriers of windowing, and its weight coefficient is decided by window function.Can be formulated as:

X _n＝T _nX (10)

Wherein, X=[X ₀x ₁x _n-1], X _i(i=0...N-1) be the code element on each subcarrier of transmitting terminal transmission; represent weighting matrix; t _ijfor weighted term, represent the impact of i subcarrier of j subcarrier pair.

From digital signal processing theory, the spread spectrum function of each subcarrier is in full accord, equidirectional, with influencing each other between the subcarrier at interval; And spread spectrum is successively decreased rapidly along with the increase of frequency domain distance, after certain intervals, substantially can ignore.While adopting four coefficient Brackman-Harris windows, interval surpasses 2 subcarriers, and its impact can be ignored; While adopting hamming window or Hanning window, interval surpass 3 subcarriers its impact can ignore.

Therefore, can be to weighting matrix T _nelement do following constraint:

When meeting i-j=m-n, t _ij=t _mn, i, j, m, n ∈ [1, N]; When meeting | i-j | during > L, tij=0, wherein L is constant, represents scope or the thresholding of its left and right impact of subcarrier pair.While adopting four coefficient Brackman-Harris windows, can put L=2; While adopting hamming window or Hanning window, can put L=3.After this constraint:

By the T after formula (10) and constraint _nmatrix brings formula (8) into and suitable adjustment can obtain:

$R=\left\{{\mathrm{\&Sigma;}}_{p=1}^P\mathrm{diag}\left({\mathrm{\&mu;}}_p\right)\left({\mathrm{\&Sigma;}}_{n=0}^Z{y}_p^n{\mathrm{\&alpha;}}_n{e}^{j{w}_{d_n}{\mathrm{\&tau;}}_n}{T}_n\right)\right\}*X+W---\left(12\right)$

Obviously, in formula (12) can not change the weighting matrix T after constraint _nstructure and inherent restriction relation thereof, therefore weighting matrix T after the structure of item and inherent restriction relation thereof and constraint _nidentical.Desirable:

Wherein, i, j ∈ [1, N];

represent in element represent T _nin element t _ij.Formula (13) has realized the simplification of element entry, and its beneficial effect bringing is, the element after simplification no longer corresponding to single footpath, but the weighted sum in all footpaths, this makes can follow the tracks of in a sense the main energy of channel, thereby overcome the impact that Some Parameters time variation brings.

Will substitution formula (12) replaces ${\mathrm{\&Sigma;}}_{n=0}^Z{y}_p^n{\mathrm{\&alpha;}}_n{e}^{j{w}_{d_n}{\mathrm{\&tau;}}_n}{T}_n$ :

$R={\mathrm{\&Sigma;}}_{p=1}^P\mathrm{diag}\left({\mathrm{\&mu;}}_p\right){\stackrel{\&OverBar;}{T}}_{p}X+W---\left(14\right)$

When carry out based on pilot tone channel estimating time, R, X, diag (μ in formula (14) _p) be known terms, W is channel additive noise, for matrix to be asked, the total individual unknown parameter of P* (2L-1) is waited to solve.Now, channel frequency domain response matrix H is decomposed into the diag (μ that characterizes multidiameter delay completely _p) and sign Doppler frequency shift or ICI and: $H={\mathrm{\&Sigma;}}_{p=1}^P\mathrm{diag}\left({\mathrm{\&mu;}}_p\right){\stackrel{\&OverBar;}{T}}_p.$

3) the method for solving of middle unknown parameter and can solving condition for the ease of processing, right the second item constraint adjust:

When meeting i-j > L or i-j <-(L+1), t _ij=0, wherein L is constant, represents scope or the thresholding of its left and right impact of subcarrier pair.While adopting four coefficient Brackman-Harris windows, can put L=2; While adopting hamming window or Hanning window, can put L=3.

Now, total P*2L the unknown parameter of matrix waited to solve.And formula (15) can be expressed equivalently as:

Wherein, x _i(i ∈ [0...N-1]) is the i item of pilot frequency sequence X; p=1...P; subscript T represents transposition.

Can prove, when pilot frequency sequence X do not exist nonzero element or only two ends, border there is neutral element but border while respectively holding neutral element number to be less than L, matrix reversible, the present invention advises adopting the pilot frequency sequence that does not have neutral element.Formula (16) can be separated and is:

$\tilde{T}=\tilde{X}\backslash R+\tilde{X}\backslash W---\left(17\right)$

Due to the existence of noise, through type (17) is required noise has all superposeed on middle all elements.And middle element subscript meets | i-j | and during > L, therefore, while there is noise, in to should be zero element be no longer zero.Can extract noise based on this, then from receive signal, will go to remove, thereby realize acknowledge(ment) signal denoising.

4) solving with Data Detection of channel frequency domain response matrix H obtained by formula (17) be equal to and obtained (carrying out matrix restructuring).Thus, can utilize solve and obtain channel frequency domain response matrix H.

Non-pilot data part in OFDM symbol, meets formula R=HX, and R is the frequency domain representation that receiving terminal receives data division signal, and X is established data to be detected.

Due to and U _pcomputing has only changed with linear superposition first inherent constraint, but do not change second portion constraint, now the structure of H with similar, meet | i-j | during > L, t _ij=0, wherein L is constant, represents scope or the thresholding of its left and right impact of subcarrier pair.While adopting four coefficient Brackman-Harris windows, can put L=2; While adopting hamming window or Hanning window, can put L=3.

If adopt hamming window, can obtain in conjunction with R=HX:

R(i)＝H(i，i-2:i+1)X(i-2:i+1)+H(i，i+2)X(i+2)(18)

Wherein, R (i) represent to receive data on i the subcarrier that signal frequency domain represents R; H (i, i-2:i+1) represents to get capable i-2 to the i+1 row of H i and forms 1*4 matrix; X (i-2:i+1) represents to get the capable formation of X i-2 to i+1 4*1 matrix; H (i, i+2) represents that the element and the X (i+2) that get the capable i+2 row of H i represent to get the element at X i+2 place.

Visible, receive data on i the subcarrier that signal frequency domain represents R only with i subcarrier of transmitting terminal near limited several relevant.If R (i) and X (i-2:i+1) are known, exploitable channel frequency domain response matrix H and formula (18) solve X (i+2).

X(i+2)＝{R(i)-H(i，i-2:i+1)X(i-2:i+1)}/H(i，i+2)(19)

Therefore,, if X (1:4) is known, can recursion determines all unknown data X (5:N), thereby realize Data Detection.This detection method is simple, but requirement must have known primary data, if adopt virtual subnet carrier wave, primary data is zero.

It should be noted that, while there is noise, need to adjust formula (19), utilize H (i, i) but not H (i, i+2) carries out follow-up data detection.So formula (19) can be adjusted to:

X(i)＝{R(i)-H(i，i-2:i-1)X(i-2:i-1)}/H(i，i)(20)

X (i) is made after differentiation, can carry out using it as given data follow-up data detection.

In proof procedure of the present invention, by great many of experiments, find, as 2.26 < | H (i, i)/H (i, i+1) | < 2.46 and | H (i, i)/H (i, i+2) | > 26 and 2.26 < | H (i, i)/H (i, i-1) | < 2.46 and | H (i, i)/H (i, during i-2 > 26, the error rate is less, and occurs that the number of times of the non-zero error rate is less; When not meeting this relation extents, the error rate is larger, occurs that the number of times of the non-zero error rate is less.Think: when in H, element meets above-mentioned relation, the non-constant of coherence that comprises main energy footpath in channels in two OFDM mark spaces, now utilizes channel estimation method to obtain channel frequency domain response matrix H and the method for carrying out channel compensation with this cannot be followed the tracks of the quick variation of upper signal channel.Therefore, estimate and Data Detection deleterious, algorithm performance declines.Can weigh by the relation of H matrix element the quality of channel, thereby determine whether use channel or adopt which kind of mode to use channel.

Beneficial effect

The present invention is practical, and algorithm is realized simple, can effectively solve the ICI problem causing due to quadrature imbalance between ofdm system subcarrier under time varying channel; In algorithmic derivation process of the present invention, due to each footpath amplitude of channel and Doppler's impact have been carried out to the weighted sum in all footpaths, therefore overcome in a sense the impact that parameter time varying causes; The present invention is low and form structure is simple about Data Detection some of complex degree, and can greatly lower the error rate in conjunction with precoding and other detection meanss; This algorithm can be good at tackling high-speed mobile scene, and performance is not successively decreased with the increase of mobile vehicle and base station relative moving speed.

Accompanying drawing explanation

Fig. 1 is channel estimating of the present invention and detection method flow chart;

Fig. 2 is that the ofdm system subcarrier in the embodiment of the present invention arranges schematic diagram;

Fig. 3 is the transceiver system schematic diagram in the embodiment of the present invention.

Embodiment

Below in conjunction with drawings and Examples, the present invention will be further described.

The OFDM channel estimating and the data detection method that based on time delay domain base, decompose, as shown in Figure 1, the present invention is applied to multipath time varying channel to its flow process.The present invention is the channel estimation methods based on pilot tone, and its pilot tone and data subcarrier setting are as shown in Figure 2.

In wireless communication system, thus transmitting terminal by windowing, suppress the secondary lobe of shaping waveform and be shaped after band external leakage, thereby by the interference constraints between subcarrier in limited scope.When receiving terminal receives after ofdm signal, pilot portion is proposed, according to receiving signal frequency domain, express R, utilize prolate ellipsoid body sequence and set up target function in conjunction with local known pilot signal X, by least square method, solve target function, and gained solution is carried out to the iteration denoising of making zero, thereby obtain channel condition information comparatively accurately; Receiving terminal obtains after the channel estimation results based on pilot tone, utilize the relation between the data-signal that formula (20) provides, thereby node-by-node algorithm is differentiated the effective detection that realizes data;

Embodiment 1

Employing system bandwidth be 10MHz, the slot length ofdm signal that is 0.5ms as broadband wireless signal, there is not direct projection path in channel, design parameter arranges as shown in table 1; As shown in Figure 2, wherein the data subcarrier number of data division is made as 600 to the setting of ofdm signal sub-carriers; Transceiver system schematic diagram is shown in Fig. 3; It is 100 that algorithm arranges iterations; As 2.26 < | H (i, i)/H (i, i+1) | < 2.46 and | H (i, i)/H (i, i+2) | > 26 and 2.26 < | H (i, i)/H (i, i-1) | < 2.46 and | H (i, i) (i, is used channel to/H during i-2 > 26; Channel has 3 propagation paths, and each footpath average gain is respectively 25dB, 5dB and 10dB, and each footpath time delay is respectively: 1ts, 3ts and 7ts.

When terminal velocity is 120km/h, error rate when signal to noise ratio is 25dB is: 0.0021;

When terminal velocity is 200km/h, error rate when signal to noise ratio is 25dB is: 0.0026;

When terminal velocity is 360km/h, error rate when signal to noise ratio is 25dB is: 0.0036.

Table 1

Parameter name	Parameter arranges
		System carrier frequency	2GHz
System bandwidth	10MHz
		Subcarrier spacing	15kHz
OFDM modulation is counted	1024
		Modulation system	QPSK
Window function	Hamming window
		Send out number of antennas	1XnT
Channel condition	Rayleigh+awgn
		Motion velocity of mobile station (km/h)	120、200、360
Data block length (scheduling duration)	0.5ms
		Receive and survey synchronously	Desirable

Embodiment 2

Employing system bandwidth be 10MHz, the slot length ofdm signal that is 0.5ms as broadband wireless signal, there is direct projection path in channel, design parameter arranges as shown in table 2; As shown in Figure 2, wherein the data subcarrier number of data division is made as 600 to the setting of ofdm signal sub-carriers; Transceiver system schematic diagram as shown in Figure 3; It is 100 that algorithm arranges iterations; 2.26 < | H (i, i)/H (i, i+1) | < 2.46 and | H (i, i)/H (i, i+2) | > 26 and 2.26 < | H (i, i)/H (i, i-1) | < 2.46 and | H (i, i) (i, is used channel to/H during i-2 > 26; When channel have 3 propagation paths, each footpath average gain be 25,5 and 10dB, time delay be: ts, 3ts and 4ts, fading parameter are 20.

Terminal velocity is 120km/h, and error rate when signal to noise ratio is 25dB is: 0.0024;

Terminal velocity is 200km/h, and error rate when signal to noise ratio is 25dB is: 0.0037; Terminal velocity is 360km/h, and error rate when signal to noise ratio is 25dB is: 0.0048.

Table 2

The above is preferred embodiment of the present invention, and the present invention should not be confined to the disclosed content of this embodiment and accompanying drawing.Everyly do not depart from the equivalence completing under spirit disclosed in this invention or revise, all falling into the scope of protection of the invention.

Claims (2)

1. the channel estimating for ofdm system and data detection method, the transmitting terminal of described ofdm system carries out time-domain windowed processing to be revealed with suppressed sidelobes, the method is used block pilot tone, pilot tone does not exist in nonzero element and OFDM data symbol and is provided with subcarrier, it is characterized in that, the concrete steps of the method are as follows:

1) receiving terminal is set up the target function of channel estimating:

Wherein, R is for receiving the frequency domain representation of signal; it is the frequency domain representation that receives signal section in signal; W is additive noise; H is channel frequency domain response matrix; X=[X ₀x ₁x _n-1] be known pilot sequence, X _afor the code element on each subcarrier of transmitting terminal transmission, a=0 ..., N-1, N represents that ofdm system has N subcarrier; U _j=diag (μ _j), j=1 ..., P, wherein μ _jfor discrete prolate spheroid body basic sequence, P represents the number of prolate ellipsoid body sequence;

it is the matrix being formed by pilot frequency sequence restructuring; for characterizing the matrix of doppler spread, l is constant, represents the scope of its left and right impact of subcarrier pair, represent in element the weighted sum in all footpaths that represents the impact of i subcarrier of j subcarrier pair, i, j ∈ [1, L]; Channel frequency domain response matrix H meets following relation:

2) receiving terminal utilization receives signal R and known matrix by least square method, by formula (1), solved the matrix obtaining containing noisy sign doppler spread

3) the receiving terminal R denoising of making zero to received signal, concrete steps are:

3.1 arrange the thresholding M that makes zero, right meet i < M and j < M zero setting, i wherein, j ∈ [1, L];

3.2 utilize after zero setting with equation is asked for the partial noise receiving in signal;

3.3 utilize equation is asked for the reception signal after denoising;

4) iteration denoising ask for channel frequency domain response matrix H, comprising:

4.1 repeating steps 1), 2), 3) realize iteration and make zero denoising so that additive noise W=0, its number of repetition is decided by signal to noise ratio;

4.2 execution steps 2) obtain

4.3 utilize obtain channel frequency domain response matrix H;

5) set up Data Detection target function, and utilize target function to ask for data to be tested, the target function of setting up is:

X(i+2)＝{R(i)-H(i，i-M:i+1)X(i-M:i+1)}/H(i，i+2) (2)

Wherein, i ∈ [M, N _d], M is the thresholding that makes zero, N _dfor data to be tested number; X (i-M:i+1) sequence i-M to i+1 the element that represent to fetch data forms matrix; H (i, i-M:i+1) represents to get capable i-M to the i+1 row of H matrix i and forms matrix;

6) the required data to be tested of step 5) are detected to differentiation;

7) repeating step 5) and step 6), the data that receive until all have all realized detecting to be differentiated;

Through above-mentioned seven steps, completed OFDM channel estimating and the Data Detection of decomposing based on time delay domain base.

2. a kind of channel estimating for ofdm system according to claim 1 and data detection method, is characterized in that the modeling process of ofdm system frequency-domain expression to be:

1) ofdm system frequency-domain expression is decomposed into

$R={\mathrm{\&Sigma;}}_{n=0}^Z{\mathrm{\&alpha;}}_n{e}^{j{w}_{d_n}{\mathrm{\&tau;}}_n}{F}_n{X}_n+W---\left(3\right)$

Wherein, R=[R ₀r ₁r _n-1] ^tfor receiving signal frequency domain, represent; Z represents the number of multipath; α _nfor the amplitude gain corresponding to n footpath; it is the Doppler frequency shift in n footpath; τ _nit is the time delay in n footpath; W is channel additive noise matrix; $F_n=\mathrm{diag}\left(\begin{array}{cccc}{e}^{-j2\mathrm{\&pi;}*0*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}& e^{-j2\mathrm{\&pi;}*1*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}& ...& e^{-j2\mathrm{\&pi;}*(N-1)*\mathrm{\&Delta;f}{\mathrm{\&tau;}}_n}\end{array}\right),$ The impact of time delay for different sub carrier described, for characterizing multidiameter delay, the frequency domain interval that wherein Δ f is discrete Fourier transform, $X_n={\left[\begin{array}{cccc}{\stackrel{\&OverBar;}{X}}_0& {\stackrel{\&OverBar;}{X}}_1& ...& {\stackrel{\&OverBar;}{X}}_{N-1}\end{array}\right]}^T,{\stackrel{\&OverBar;}{X}}_a=X(\mathrm{a\&Delta;f}-w_{\mathrm{dn}}),a\&Element;[0,N-1],$ X _nin each element only relevant with subcarrier and Doppler frequency shift, be used for characterizing the ICI between each footpath Doppler frequency shift or subcarrier;

2) F _nderivation be:

By any F _nwide when diagonal of a matrix element is regarded as is [0, (N-1) Δ f], and bandwidth is [0, τ _max] band-limited function, the frequency domain interval that wherein Δ f is discrete Fourier transform, τ _maxfor channel maximum multipath time delay;

To F _nmatrix carries out the expansion based on prolate ellipsoid body sequence, establishes most concentration of energy of band-limited function at P prolate ellipsoid body sequence μ _p, p=1...P:

$F_n={\mathrm{\&Sigma;}}_{p=1}^P{y}_p^n\mathrm{diag}\left({\mathrm{\&mu;}}_p\right)---\left(4\right)$

Wherein, for F _nexpansion coefficient based on prolate ellipsoid body sequence, the numerical representation method of P expansion performance based on prolate ellipsoid body sequence and launch after F _nthe energy loss of matrix;

3) X _nsimplification process be:

By X _nelement in matrix be equal to the weighting of corresponding code element on all subcarriers before windowing, and its weight coefficient decides by window function, obtains:

X _n=T _nX ^T （5）

Wherein, X=[X ₀x ₁x _n-1], X _afor the code element on each subcarrier of transmitting terminal transmission, a=0 ..., N-1; represent weighting matrix, at weighting matrix in, represent T _nin element t _ij, t _ijthe weighted term that represents single footpath, refers to the impact of i subcarrier of j subcarrier pair;

To weighting matrix T _nelement do following constraint:

When meeting i-j=m-n, t _ij=t _mn, now i, j, m, n meet i, j, m, n ∈ [1, N]; When meeting | during i-j| > L, t _ij=0, wherein L is constant, represents the scope of its left and right impact of subcarrier pair, while adopting four coefficient Brackman-Harris windows, puts L=2; While adopting hamming window or Hanning window, put L=3;

After this constraint:

4) by the T after formula (5) and constraint _nmatrix is brought ofdm system frequency-domain expression into and can be obtained:

$R=\left\{{\mathrm{\&Sigma;}}_{p=1}^P\mathrm{diag}\left({\mathrm{\&mu;}}_p\right)\left({\mathrm{\&Sigma;}}_{n=0}^Z{y}_p^n{\mathrm{\&alpha;}}_n{e}^{j{w}_{d_n}{\mathrm{\&tau;}}_n}{T}_n\right)\right\}*X+W---\left(7\right)$

Get

Wherein,

represent in element represent T _nin element t _ij;

Will substitution formula (7) replaces :

When carry out based on pilot tone channel estimating time, R, X, diag (μ in formula (9) _p) be known terms, W is channel additive noise, for matrix to be asked, the total individual unknown parameter of P* (2L-1) is waited to solve; Now, channel frequency domain response matrix H is decomposed into the diag (μ that characterizes multidiameter delay completely _p) and sign Doppler frequency shift or ICI and: