CN101909024B - Method and device for estimating maximum Doppler frequency offset - Google Patents

Abstract

The invention discloses a method and a device for estimating the maximum Doppler frequency offset. The method comprises the following steps of: calculating channel estimation according to received signals; calculating an amplitude spectrum of the channel estimation, and filtering the amplitude spectrum; performing folding average on the amplitude spectrum after filtering; estimating the level of noise; calculating a detection threshold; and calculating and outputting the maximum Doppler frequency offset. The method and the device solve the problems that the estimation value of an algorithm for acquiring information of the Doppler frequency offset has poor stability or low estimation accuracy, further improve the stability and can acquire higher estimation accuracy.

Description

The method of estimation of maximum Doppler frequency offset and device

Technical field

The present invention relates to the communications field, in particular to a kind of method of estimation and device of maximum Doppler frequency offset.

Background technology

At present, OFDM (Orthogonal Frequency DivisionMultiplexing, referred to as OFDM) be widely applied in various wireless communication systems, for example, digital video broadcasting (Digital Video Broadcasting, referred to as DVB), WLAN (Wireless Local Area Network, referred to as WLAN), China Mobile multimedia video broadcast (China Mobile Multimedia Broadcasting, referred to as CMMB) etc.These system requirements can effectively be operated in various channel circumstances, for example, adapt to the various velocity intervals of travelling carriage, various carrier frequencies, various time lag and signal to noise ratio (Signal Noise Ratio, referred to as SNR).Therefore, it is very important prejudging channel quality and changing speed, and along with the continuous variation of channel circumstance, needing can adaptive land used selective system parameter.

In wireless mobile communications, due to the high-speed mobile of transmitter or receiver, can cause Doppler spread, this can affect the correct reception of signal and in numerous adaptive link transmission systems, system also needs to obtain the parameter information in channel.For example, the two-dimentional Wiener filtering channel estimation methods of ofdm system need to be known the Doppler frequency deviation size of channel.To pilot filtering, can improve this estimation result, and required transmitting power is lower by the bandwidth low pass filter identical with Doppler's maximum Doppler frequency offset.

In correlation technique, comprise obtaining the various algorithms that many frequency deviation informations have proposed: correlation method, level crossing rate method, diversity exchange rate method etc., wherein, correlation method is subject to channel noise effect, need accurately to estimate in advance the signal to noise ratio of channel, and poor performance under correlation method low signal-to-noise ratio.In fact, the auto-correlation function of noise is δ function, and when correlation method estimated signal energy, need to know noise size, just can remove the estimated bias that noise brings, even in the situation that accurately knowing noise signal to noise ratio, in the time of low signal-to-noise ratio, the poor stability of estimated value; And level crossing rate method, diversity exchange rate method can only estimate Doppler frequency deviation value roughly, estimated accuracy is low.

For poor stability or the low problem of estimated accuracy of algorithm estimated value of obtaining many frequency deviation informations in correlation technique, effective solution is not yet proposed at present.

Summary of the invention

For obtaining the poor stability of algorithm estimated value of many frequency deviation informations or the low problem of estimated accuracy in correlation technique and proposing the present invention, for this reason, main purpose of the present invention is to provide a kind of estimation scheme of improved maximum Doppler frequency offset, one of to address the above problem at least.

To achieve these goals, according to an aspect of the present invention, provide a kind of method of estimation of maximum Doppler frequency offset.

Comprise according to the method for estimation of maximum Doppler frequency offset of the present invention: according to receiving calculated signals channel estimating; Calculate the amplitude spectrum of channel estimating, and amplitude spectrum is carried out to filtering processing; Filtered amplitude spectrum is folded on average, and estimating noise level, calculates detection threshold, calculates and export maximum Doppler frequency offset.

Preferably, by following formula, amplitude spectrum is carried out to filtering processing: ${\hat{Y}}_{\mathrm{sm}}\left(k\right)={\mathrm{\&Sigma;}}_{-L\&le;n\&le;L}\hat{Y}\left(\mathrm{mod}(k-n,M)\right)h\left(k\right),$ Wherein, h (k) is filter coefficient, and mod (, M) and for M is carried out to modular arithmetic, M is counting of FFT conversion, 0≤k < M.

Preferably, by following formula, filtered amplitude spectrum is folded on average: ${\hat{Y}}_{\mathrm{half}}\left(k\right)=({\hat{Y}}_{\mathrm{sm}}\left(k\right)+{\hat{Y}}_{\mathrm{sm}}\left(\mathrm{mod}(M-k,M)\right))/2,$ Wherein,

for filtered amplitude spectrum, mod (, M) and for M is carried out to modular arithmetic, $0\&le;k\&le;\frac{M}{2}.$

Preferably, estimating noise level comprises: the maximum of calculating the amplitude spectrum after folding on average: ${\hat{Y}}_{\max }=\underset{0\&le;k<\frac{M}{2}}{\max }\left\{{\hat{Y}}_{\mathrm{half}}\left(k\right)\right\},$ Wherein,

for the amplitude spectrum after folding on average; Calculate the mean value of the partial frequency spectrum of the amplitude spectrum after folding on average: $\hat{N}=\underset{\frac{M}{4}<k<\frac{M}{2}}{\mathrm{mean}}\left\{{\hat{Y}}_{\mathrm{half}}\left(k\right)\right\};$ Calculating noise level is ${\hat{N}}_0:{\hat{N}}_0=\hat{N}/{\hat{Y}}_{\max }.$

Preferably, calculating detection threshold comprises: detection threshold thr is $\mathrm{thr}={\hat{Y}}_{\max }\&CenterDot;\mathrm{\&alpha;}+\hat{N}\&CenterDot;(1-\mathrm{\&alpha;}),$ Wherein, α is default 1 the constant that is less than,

for the maximum of amplitude spectrum,

for the mean value of partial frequency spectrum in the amplitude spectrum after folding on average.

Preferably, calculating maximum Doppler frequency offset comprises: search out according to following formula the largest index that spectrum value is greater than threshold value $k_{\mathrm{edge}}=\max \{k;|{\hat{Y}}_{\mathrm{half}}\left(k\right)|>\mathrm{thr},0\&le;k<\frac{M}{4}\},$ Wherein,

for the amplitude spectrum after folding on average, thr is detection threshold, and M is counting of FFT conversion; According to largest index k _edgecalculate maximum Doppler frequency offset f _d: $f_d=\frac{k_{\mathrm{edge}}}{M}\&CenterDot;\frac{1}{T},$ Wherein, the sampling time interval that T is channel estimating.

Preferably, according to largest index k _edgecalculate maximum Doppler frequency offset f _dbefore, said method also comprises: according to following formula, largest index is carried out to linear interpolation, obtain revised largest index k _edge, so that according to revised largest index k _edgecalculate maximum Doppler frequency offset f _d: $k_{\mathrm{edge}}=k_{\mathrm{edge}}+(\mathrm{thr}-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right))/({\hat{Y}}_{\mathrm{half}}(k_{\mathrm{edge}}+1)-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right)).$

Preferably, according to largest index k _edgecalculate maximum Doppler frequency offset f _dafterwards, said method also comprises: calculate and upgrade filter coefficient according to noise level and maximum Doppler frequency offset.

Preferably, calculate and upgrade filter coefficient according to noise level and maximum Doppler frequency offset and comprise: judge noise level

whether be less than predetermined threshold value TH, if so, it is unit impulse function that filter coefficient is set; Otherwise the sigma value that filter coefficient is set is σ=β (f _dmT) Gaussian filter, and normalization Gaussian filter.

Preferably, after calculating according to noise level and maximum Doppler frequency offset and upgrading filter coefficient, said method also comprises: according to the filter coefficient after upgrading, amplitude spectrum is carried out to filtering processing.

To achieve these goals, according to a further aspect in the invention, provide a kind of estimation unit of maximum Doppler frequency offset.

Comprise according to the estimation unit of maximum Doppler frequency offset of the present invention: the first computing module, for according to receiving calculated signals channel estimating; The second computing module, for calculating the amplitude spectrum of the channel estimating that the first computing module obtains; Filtration module, carries out filtering processing for the amplitude spectrum that the second computing module is obtained; Processing module, for the filtered amplitude spectrum of filtration module is folded on average, estimating noise level, calculates detection threshold, calculates and export maximum Doppler frequency offset.

Preferably, said apparatus also comprises: the 3rd computing module, for the noise level and the maximum Doppler frequency offset calculating filter coefficient that obtain according to processing module; Update module, upgrades for the filter coefficient that uses the 3rd computing module to obtain.

By the present invention, calculate the amplitude spectrum of channel estimating, filtered amplitude spectrum is folded on average, estimating noise level, calculate detection threshold, calculate and export maximum Doppler frequency offset, solved poor stability or the low problem of estimated accuracy of the algorithm estimated value of obtaining many frequency deviation informations in correlation technique, and then improved stability, and can obtain higher estimated accuracy.

Brief description of the drawings

Accompanying drawing described herein is used to provide a further understanding of the present invention, forms the application's a part, and schematic description and description of the present invention is used for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:

Fig. 1 is according to the flow chart of the method for estimation of the maximum Doppler frequency offset of the embodiment of the present invention;

Fig. 2 is the schematic diagram of the frame structure of the CMMB system physical layer of one of applied environment according to the embodiment of the present invention;

Fig. 3 is the schematic diagram of OFDM symbol composition structure in Fig. 2;

Fig. 4 is the schematic diagram that is assigned as data subcarrier, scattered pilot and continuous pilot, the method for salary distribution according to effective subcarrier of the OFDM symbol of the embodiment of the present invention;

Fig. 5 is the schematic diagram of estimating structure according to the maximum Doppler frequency offset of the embodiment of the present invention;

Fig. 6 is according to the structured flowchart of the estimation unit of the maximum Doppler frequency offset of the embodiment of the present invention;

Fig. 7 is the preferred structure block diagram according to the estimation unit of the maximum Doppler frequency offset of the embodiment of the present invention.

Embodiment

Functional overview

Consider poor stability or the low problem of estimated accuracy of the algorithm estimated value of obtaining many frequency deviation informations in correlation technique, the embodiment of the present invention provides a kind of Doppler frequency deviation obtaining method of CMMB system, the scattered pilot that receives signal with frequency domain obtains Doppler frequency deviation, based on spectral method, detect spectral width and estimate Doppler frequency deviation; Carry out filtering according to the suitable filter of may big or smallly selecting of doppler values to composing, then, spectrum carried out to doubling average, by detection filter, the spectrum after doubling is average, makes algorithm can obtain high stability in low signal-to-noise ratio adverse circumstances.The estimation of Doppler frequency deviation does not need to obtain channel signal to noise ratio, and noise is estimated to disturb little to Doppler frequency deviation, and can obtain higher estimated accuracy.Overcome and adopted the deficiency that in ofdm system, its Doppler frequency deviation is estimated in the past.

It should be noted that, in the situation that not conflicting, the feature in embodiment and embodiment in the application can combine mutually.Describe below with reference to the accompanying drawings and in conjunction with the embodiments the present invention in detail.

Embodiment of the method

According to embodiments of the invention, provide a kind of method of estimation of maximum Doppler frequency offset.Fig. 1 is according to the flow chart of the method for estimation of the maximum Doppler frequency offset of the embodiment of the present invention, and as shown in Figure 1, the method comprises that following step 102 is to step 106:

Step 102, according to receiving calculated signals channel estimating.

Step 104, calculates the amplitude spectrum of channel estimating, and amplitude spectrum is carried out to filtering processing.

Step 106, folds on average filtered amplitude spectrum, and estimating noise level is calculated detection threshold, calculates and export maximum Doppler frequency offset.

It should be noted that, detection threshold is chosen for $\mathrm{thr}={\hat{Y}}_{\max }\&CenterDot;\mathrm{\&alpha;}+\hat{N}\&CenterDot;(1-\mathrm{\&alpha;}),$ Wherein, α is default 1 the constant that is less than,

for the maximum of spectrum,

average for partial spectrum value, generally chooses the mean value of the rear portion frequency spectrum of folding amplitude spectrum.

In the time calculating maximum Doppler frequency offset, first, search out the largest index that spectrum value is greater than threshold value $k_{\mathrm{edge}}=\max \{k;|{\hat{Y}}_{\mathrm{half}}\left(k\right)|>\mathrm{thr},0\&le;k<\frac{M}{4}\},$ Wherein,

for the spectrum after doubling on average, thr is detection threshold, and M is that FFT counts; Preferably, in order to improve resolution, can carry out linear interpolation to above-mentioned largest index (marginal point) according to following formula, so that according to revised largest index k _edgecalculate maximum Doppler frequency offset f _d: $k_{\mathrm{edge}}=k_{\mathrm{edge}}+(\mathrm{thr}-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right))/({\hat{Y}}_{\mathrm{half}}(k_{\mathrm{edge}}+1)-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right)),$ Then, output Doppler frequency deviation estimated value $f_d=\frac{k_{\mathrm{edge}}}{M}\&CenterDot;\frac{1}{T},$ Wherein, the sampling time interval that T is channel estimating.

After this, according to noise level and the maximum Doppler frequency offset estimated, calculating filter coefficient, upgrades filter coefficient, to amplitude spectrum is carried out to filtering processing according to the filter coefficient after upgrading.Turn back to step 102, repeat above step.

Particularly, judgement

with

whether ratio is less than predetermined threshold value TH, and if so, filter coefficient is set is unit impulse function; Otherwise filter coefficient is set to sigma value for σ=β (f _dmT) Gaussian filter, and normalization Gaussian filter.Gaussian filter coefficient is h _g(k)=exp (k ²/ (2 σ ²)), 0≤| k| < 3 σ; After coefficient normalization, be h (k)=h _g(k)/∑ _kh _g(k).

By this embodiment, a kind of method for mobile communication system estimating Doppler frequency deviation is provided, the method can obtain higher estimated accuracy, and its estimated accuracy is not subject to the impact of channel estimation results.

Below in conjunction with example, the implementation procedure of the embodiment of the present invention is described in detail.

Ofdm system has many types, and for different types of ofdm system, the implementation procedure of specific embodiments of the invention is different.The situation that is applied to this ofdm system of CMMB with the present invention below describes.

Fig. 2 is the schematic diagram of the frame structure of the CMMB system physical layer of one of applied environment according to the embodiment of the present invention, as shown in Figure 2, in CMMB system in the frame structure of physical layer, 40 time slots (time slot 0 is to time slot 39) will be divided into for 1 second, each time slot 25ms, each time slot is made up of 1 beacon and 53 OFDM symbols (OFDM symbol 0 to OFDM symbol 52).

Fig. 3 is the schematic diagram of OFDM symbol composition structure in Fig. 2, and as shown in Figure 3, OFDM symbol is made up of Cyclic Prefix (Cycle Prefix, referred to as CP) and OFDM data volume.OFDM data volume length (T _u) be 409.6 μ s, length of the cycle (T _cP) be 51.2 μ s, OFDM symbol lengths (T _s) be 460.8 μ s.

Fig. 4 is the schematic diagram that is assigned as data subcarrier, scattered pilot and continuous pilot, the method for salary distribution according to effective subcarrier of the OFDM symbol of the embodiment of the present invention, as shown in Figure 4, the effective subcarrier that shows OFDM symbol is assigned as data subcarrier, scattered pilot and continuous pilot, the method for salary distribution.

Fig. 5 is the schematic diagram of estimating structure according to the maximum Doppler frequency offset of the embodiment of the present invention, and as shown in Figure 5, based on above-mentioned frame structure, Doppler in the embodiment of the present invention (Doppler) frequency deviation obtaining method comprises the following steps:

Step 1: by receiving calculated signals channel estimating.

Particularly, extract pilot sub-carrier and receive signal,, extract the continuous pilot signal that receives frequency-region signal in time slot, the continuous pilot signal sending due to CMMB system is fixed value 1, in fact the continuous pilot signal receiving is the channel response of pilot tone point, the corresponding one group of channel estimating sampled value of each pilot sub-carrier.

Step 2: calculate the amplitude spectrum of channel estimating, that is, calculate the amplitude spectrum of pilot signal.

The pilot signal of extracting is done to M point fast Fourier transformation algorithm (Fast Fourier Transform Algorithm, referred to as FFT) conversion about time orientation.The corresponding one group of FFT transform data of each continuous pilot subcarrier, to the transform data processing that takes absolute value, obtains amplitude spectrum.The amplitude spectrum of different continuous pilot is summed up on average, obtain a time slot amplitude spectrum, be designated as

Step 3: time slot amplitude spectrum is carried out to filtering processing, can effectively suppress amplitude spectrum noise burr, make spectrum become smooth, be easy to detect.

The coefficient of supposing filter is designated as { h (k) } _-L≤k≤L, right

while carrying out filtering, boundary value is pressed periodic extension processing, carries out filtering according to following formula:

${\hat{Y}}_{\mathrm{sm}}\left(k\right)={\mathrm{\&Sigma;}}_{-L\&le;n\&le;L}\hat{Y}\left(\mathrm{mod}(k-n,M)\right)h\left(k\right)$ 0≤k＜M

Wherein, h (k) is filter coefficient, and mod (, M) and for M is carried out to modular arithmetic, M is counting of FFT conversion.

Step 4: to filtered amplitude spectrum, fold on average, estimating noise level, calculates detection threshold, detection computations maximum Doppler frequency offset, output Doppler frequency deviation estimated value.Compose doubling by handle average, can reduce boundary of spectrum and detect the probability of erroneous judgement, obtained the level of noise simultaneously by amplitude spectrum, select adaptively detection threshold according to noise.

The folding average formula of amplitude spectrum is as follows:

${\hat{Y}}_{\mathrm{half}}\left(k\right)=({\hat{Y}}_{\mathrm{sm}}\left(k\right)+{\hat{Y}}_{\mathrm{sm}}\left(\mathrm{mod}(M-k.M)\right))/2$

Wherein,

for filtered amplitude spectrum, mod (, M) and for M is carried out to modular arithmetic, $0\&le;k<\frac{M}{2}.$

Calculate the maximum of folding average amplitude spectrum:

${\hat{Y}}_{\max }=\underset{0\&le;k<\frac{M}{2}}{\max }\left\{{\hat{Y}}_{\mathrm{half}}\left(k\right)\right\}$

Wherein,

for the amplitude spectrum after folding on average.

Calculate the mean value of folding average amplitude spectrum part value of frequency point:

$\hat{N}=\underset{\frac{M}{4}<k<\frac{M}{2}}{\mathrm{mean}}\left\{{\hat{Y}}_{\mathrm{half}}\left(k\right)\right\}$

Calculate

with

ratio, be designated as

${\hat{N}}_0=\hat{N}/{\hat{Y}}_{\max }$

And with this ratio

measure noise level, and retain for next step.

Calculate detection threshold:

$\mathrm{thr}={\hat{Y}}_{\max }\&CenterDot;\mathrm{\&alpha;}+\hat{N}\&CenterDot;(1-\mathrm{\&alpha;})$

Wherein, factor-alpha is to preset to be not more than 1 positive number, for example, chooses α=0.5.

Detected edge points position:

$k_{\mathrm{edge}}=\max \{k;|{\hat{Y}}_{\mathrm{half}}\left(k\right)|>\mathrm{thr},0\&le;k<\frac{M}{4}\}$

The k trying to achieve _edgefor integer value.To function

carry out linear interpolation, improve marginal point resolution.Revise k _edgevalue:

$k_{\mathrm{edge}}=k_{\mathrm{edge}}+\frac{\mathrm{thr}-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right)}{{\hat{Y}}_{\mathrm{half}}(k_{\mathrm{edge}}+1)-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right)}$

Calculate maximum Doppler frequency offset with following formula:

$f_d=\frac{k_{\mathrm{edge}}}{M}\&CenterDot;\frac{1}{T}$

Wherein, T is an OFDM symbol duration; Then, output maximum Doppler frequency offset f _d.

Step 5: according to noise level and the maximum Doppler frequency offset estimated in step 4, calculating filter coefficient, upgrades filter coefficient.Get back to step 1, repeat above step.

Judge noise level

whether be greater than predetermined threshold TH, if

be greater than predetermined threshold TH, do not need to carry out filtering, that is, coefficient is set to h (0)=1, h (k)=0, wherein, k ≠ 0;

Otherwise filter coefficient is set to Gaussian filter coefficient.

Gaussian filter parameter σ size is determined by following formula:

σ＝β·(f _dMT)

Wherein, constant beta value is to be less than 1 positive number, can preset.

Gaussian filter coefficient is:

$h_g\left(k\right)=\exp (-\frac{k^2}{2{\mathrm{\&sigma;}}^2})$ 0≤|k|＜3σ

And by the normalization of Gaussian filter coefficient:

$h\left(k\right)=\frac{h_g\left(k\right)}{\underset{k}{\mathrm{\&Sigma;}}{h}_g\left(k\right)}$

Return to step 1, repeating step 1 to 5.

It should be noted that, in step 5, selected Gaussian filter, window function that also can choice for use other types, in like manner, according to last time Doppler's estimated value select the width of window function.

Device embodiment

According to embodiments of the invention, provide a kind of estimation unit of maximum Doppler frequency offset.Fig. 6 is according to the structured flowchart of the estimation unit of the maximum Doppler frequency offset of the embodiment of the present invention, and as shown in Figure 6, this device comprises: the first computing module 2, the second computing modules 4, and filtration module 6, processing module 8, is described said structure below.

The first computing module 2, for according to receiving calculated signals channel estimating; The second computing module 4, is connected to the first computing module 2, for calculating the amplitude spectrum of the channel estimating that the first computing module 2 obtains; Filtration module 6, is connected to the second computing module 4, carries out filtering processing for the amplitude spectrum that the second computing module 4 is obtained; Processing module 8, is connected to filtration module 6, and for the filtered amplitude spectrum of filtration module 6 is folded on average, estimating noise level, calculates detection threshold, calculates and export maximum Doppler frequency offset.

Fig. 7 is the preferred structure block diagram according to the estimation unit of the maximum Doppler frequency offset of the embodiment of the present invention, and as shown in Figure 7, preferably, said apparatus also comprises:

The 3rd computing module 72, is connected to processing module 8, for the noise level and the maximum Doppler frequency offset calculating filter coefficient that obtain according to processing module 8; Update module 74, is connected to the 3rd computing module 72, upgrades, so that filtration module 6 carries out filtering processing according to the filter coefficient after upgrading for the filter coefficient that uses the 3rd computing module 72 to obtain.

In sum, pass through the above embodiment of the present invention, method based on detecting the U-shaped spectral width of Doppler is provided, select adaptively the filter of parameter to carry out filtering according to width and the noise level of spectrum, the folding average treatment of spectrum, and select adaptively detection threshold according to noise level, make noise jamming little, can under low signal-to-noise ratio channel, work, Doppler frequency deviation estimated accuracy is high.

Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on the network that multiple calculation elements form, alternatively, they can be realized with the executable program code of calculation element, thereby, they can be stored in storage device and be carried out by calculation element, or they are made into respectively to each integrated circuit modules, or the multiple modules in them or step are made into single integrated circuit module to be realized.Like this, the present invention is not restricted to any specific hardware and software combination.

The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.

Claims (10)

1. a method of estimation for maximum Doppler frequency offset, is characterized in that, comprising:

According to receiving calculated signals channel estimating;

Calculate the amplitude spectrum of described channel estimating, and described amplitude spectrum is carried out to filtering processing;

Filtered described amplitude spectrum is folded on average, estimate the noise level of folding amplitude spectrum after average according to the mean value of the partial frequency spectrum of the maximum of the amplitude spectrum after folding average and folding amplitude spectrum after average, according to the detection threshold of the folding amplitude spectrum after average of the mean value calculation of the partial frequency spectrum of the maximum of the amplitude spectrum after folding average and folding amplitude spectrum after average, calculate the maximum Doppler frequency offset of folding amplitude spectrum after average according to folding amplitude spectrum after average and detection threshold;

Calculate and upgrade filter coefficient according to described noise level and described maximum Doppler frequency offset.

2. method according to claim 1, is characterized in that, by following formula, described amplitude spectrum is carried out to filtering processing:

${\hat{Y}}_{\mathrm{sm}}\left(k\right)={\mathrm{\&Sigma;}}_{-L\&le;n\&le;L}\hat{Y}\left(\mathrm{mod}(k-n,M)\right)h\left(k\right),$ Wherein, h (k) is filter coefficient, and mod (, M) and for M is carried out to modular arithmetic, M is counting of FFT conversion, 0≤k<M.

3. method according to claim 1, is characterized in that, by following formula, filtered described amplitude spectrum is folded on average:

${\hat{Y}}_{\mathrm{half}}\left(k\right)=({\hat{Y}}_{\mathrm{sm}}\left(k\right)+{\hat{Y}}_{\mathrm{sm}}\left(\mathrm{mod}(M-k,M)\right))/2,$ Wherein,

for filtered described amplitude spectrum, mod (, M) and for M is carried out to modular arithmetic,

4. method according to claim 1, is characterized in that, estimates that described noise level comprises:

Calculate the maximum of the described amplitude spectrum after folding on average: wherein,

for the described amplitude spectrum after folding on average;

Calculate the mean value of the partial frequency spectrum of the described amplitude spectrum after folding on average: wherein, M is counting of FFT conversion;

Calculating described noise level is

5. method according to claim 1, is characterized in that, calculates described detection threshold and comprises:

Described detection threshold thr is wherein, α is default 1 the constant that is less than,

for the maximum of described amplitude spectrum,

for the mean value of partial frequency spectrum in the described amplitude spectrum after folding on average.

6. method according to claim 1, is characterized in that, calculates described maximum Doppler frequency offset and comprises:

Search out according to following formula the largest index that spectrum value is greater than threshold value $k_{\mathrm{edge}}=\max \{k;|{\hat{Y}}_{\mathrm{half}}\left(k\right)|>\mathrm{thr},0\&le;k<\frac{M}{4}\},$ Wherein,

for the described amplitude spectrum after folding on average, thr is described detection threshold, and M is counting of FFT conversion;

According to described largest index k _edgecalculate described maximum Doppler frequency offset f _d:

wherein, the sampling time interval that T is channel estimating.

7. method according to claim 6, is characterized in that, according to described largest index k _edgecalculate described maximum Doppler frequency offset f _dbefore, described method also comprises:

According to following formula, described largest index is carried out to linear interpolation, obtain revised described largest index k _edge, so that according to described revised largest index k _edgecalculate described maximum Doppler frequency offset f _d:

$k_{\mathrm{edge}}=k_{\mathrm{edge}}+(\mathrm{thr}-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right))\text{/}({\hat{Y}}_{\mathrm{half}}(k_{\mathrm{edge}}+)-{\hat{Y}}_{\mathrm{half}}\left(k_{\mathrm{edge}}\right)).$

8. method according to claim 7, is characterized in that, calculates and upgrade filter coefficient to comprise according to described noise level and described maximum Doppler frequency offset:

Judge described noise level

whether be less than predetermined threshold value TH, if so, it is unit impulse function that described filter coefficient is set; Otherwise the sigma value that described filter coefficient is set is σ=β (f _dmT) Gaussian filter, and Gaussian filter described in normalization; Wherein, M is counting of FFT conversion, and T is an OFDMA symbol duration, and β is less than 1 positive number.

9. method according to claim 1, is characterized in that, after calculating according to described noise level and described maximum Doppler frequency offset and upgrading filter coefficient, described method also comprises:

According to the described filter coefficient after upgrading, described amplitude spectrum is carried out to filtering processing.

10. an estimation unit for maximum Doppler frequency offset, is characterized in that, comprising:

The first computing module, for according to receiving calculated signals channel estimating;

The second computing module, for calculating the amplitude spectrum of the described channel estimating that described the first computing module obtains;

Filtration module, carries out filtering processing for the described amplitude spectrum that described the second computing module is obtained;

Processing module, for the filtered described amplitude spectrum of described filtration module is folded on average, estimate the noise level of folding amplitude spectrum after average according to the mean value of the partial frequency spectrum of the maximum of the amplitude spectrum after folding average and folding amplitude spectrum after average, according to the detection threshold of the folding amplitude spectrum after average of the mean value calculation of the partial frequency spectrum of the maximum of the amplitude spectrum after folding average and folding amplitude spectrum after average, calculate the maximum Doppler frequency offset of folding amplitude spectrum after average according to folding amplitude spectrum after average and detection threshold;

The 3rd computing module, for the described noise level and the described maximum Doppler frequency offset calculating filter coefficient that obtain according to described processing module;

Update module, upgrades for the described filter coefficient that uses described the 3rd computing module to obtain.

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