CN100438399C

CN100438399C - Timing tracking apparatus, receiver, timing tracking and regulating method

Info

Publication number: CN100438399C
Application number: CNB2005100735390A
Authority: CN
Inventors: 牟秀红
Original assignee: Beijing T3G Technology Co Ltd
Current assignee: Beijing T3G Technology Co Ltd
Priority date: 2005-06-02
Filing date: 2005-06-02
Publication date: 2008-11-26
Anticipated expiration: 2025-06-02
Also published as: CN1688120A

Abstract

The present invention provides a timing tracking device, a receiving device and a timing tracking and regulating method. The timing tracking device uses the data of an early sampling point and a late sampling point to calculate a timing error. The timing tracking device comprises a data separating device, a G (tau/Tc) calculator, an equalizer and a timing error calculator, wherein the data separator is used for separating the data of the early sampling point and the late sampling point from receiving data, the early sampling point and the late sampling point are used for a training sequence, the calculator is used for calculating G (tau/Tc) according to the training sequence data separated from the data separating device, the equalizer is used for calculating the equalizing value of G (tau/Tc) of n sub-frames, and the timing error calculator is used for calculating a timing error according to the equalizing value output by the equalizer.

Description

Timing tracking apparatus, receiving apparatus, timing tracking and adjusting method

Technical Field

The present invention relates to a timing tracking device, a receiving device, a timing tracking and adjusting method in a wireless communication system, and more particularly, to a timing tracking device, a receiving device, a timing tracking and adjusting method in a time division synchronous code division multiple access (TD-SCDMA) mobile terminal.

Background

In order to correctly receive information transmitted from a Base Station (BS) in a digital mobile communication system, a mobile terminal (UE) must periodically sample and perform data frame analysis on a received signal with correct clock information, that is, a locally generated PN code needs to be synchronized with a PN code in the received signal, that is, downlink synchronization with the base station needs to be achieved. The downlink synchronization of the mobile terminal is divided into two stages of synchronous establishment and synchronous tracking.

(1) Synchronization establishment phase

The mobile terminal does not know whether the base station transmits a signal at the beginning, and therefore, a search process is required, namely, a synchronous training sequence transmitted by the base station is searched and captured within a certain frequency and time range, and the position of a data frame and the phase of a sampling clock are determined according to the synchronous training sequence. This phase is also referred to as synchronization establishment. That is, the phase difference between the signal transmitted from the other party and the local signal is within the synchronization maintaining range, i.e., within one chip.

(2) Synchronous tracking phase

Once this stage is completed, the synchronous tracking process is entered, i.e. the synchronization is continuously maintained, and the synchronization is not lost due to external influence. That is, no matter what kind of factors the phases at both ends shift, as long as the difference between the shifted phases is within the synchronization holding range, the synchronization shift can be estimated by the synchronization tracking, and the phase of the terminal sampling clock can be adjusted in real time, so that the PN code at the receiving end tracks the change of the PN code at the transmitting end, i.e. the difference between the phases is kept less than a fraction of a chip.

The commonly used synchronous tracking methods are both delay locked loops and tau-jitter loops based on early-late gate timing error detectors. They all belong to the advance-retard type of phase-locked loops. The phase-locked loop functions by correlating the received signal with two locally generated phase-shifted (early and late) signals. The delay-locked loop uses two independent correlators, while the tau-dither loop uses a single correlator for time division. The disadvantage of this conventional synchronous tracking method is that the speed and phase jitter are a contradictory quantity. If the adjustment speed is required to be high, large phase jitter exists; if less phase jitter is required, the corresponding speed of adjustment will also be slower. Therefore, it is necessary to provide a synchronous tracking device having a high speed, a small jitter, and the like.

Disclosure of Invention

In view of the above-described drawbacks, it is an object of the present invention to provide a timing tracking apparatus, a receiving apparatus, a timing tracking and adjusting method, which are fast and have small phase jitter.

An aspect of the present invention is to provide a timing tracking apparatus for calculating a timing error using data of an early sampling point and a late sampling point, comprising a data separator for separating data of the early sampling point and the late sampling point of a training sequence from received data, respectively

A calculator for calculating the time of the measurement,

P_efor early sampling of the power of the data, P_lFor the power of the late sample data, for estimating the power of the early sample point data and the power of the late sample point data, respectively, based on the training sequence data of the early sample point data and the late sample point data separated by the data separator, and calculatingA mean value for calculating n sub-frames

And a timing error calculator for calculating a timing error based on the mean value output by the averager.

Another aspect of the present invention is to provide a receiving apparatus having the timing tracking apparatus as described above, which adjusts timing using a timing error calculated by the timing tracking apparatus.

Another aspect of the present invention is to provide a timing tracking method, which includes a training sequence data separating step of separating early sample point data and late sample point data of a training sequence from received data, respectively, using a data separator,

a calculation step of using

A calculator for estimating power of the early sample point data and power of the late sample point data respectively according to the training sequence data of the early sample point data and the late sample point data separated by the data separator, and calculating

A value of (b), wherein P_eFor early sampling of the power of the data, P_lIs the power of the late sampled data; averaging step, using an averager to calculate n sub-frames

And a timing error calculation step of calculating a timing error based on a result of the averaging step using a timing error calculator.

Another aspect of the present invention is to provide a timing adjustment method including a step of adjusting a timing using a timing error calculated by the timing tracking method as described above.

According to the invention, because the early sampling point and the late sampling point have different power/amplitude when the timing error is not 0, once the timing tracking loop converges within the allowable range of timing precision, that is, the timing error is smaller than the required precision, the power/amplitude difference between the early sampling point and the late sampling point is smaller than a fixed threshold value. Therefore, the method has the advantages of high speed, small phase jitter and the like, and can effectively keep the downlink synchronization within the requirement of a precision range, thereby effectively avoiding the system communication quality reduction and even communication interruption caused by the synchronization adjustment and tracking failure of the receiver.

Drawings

Fig. 1 is a power-time delay diagram for a multipath channel.

Fig. 2 is a block diagram of a receiving apparatus according to the present invention.

Fig. 3 is a block diagram of a timing tracking device.

Fig. 4 is a structure diagram of TD-SCDMA subframe.

Fig. 5 is a structure diagram of TD-SCDMA time slot.

FIG. 6 is a structural diagram of DwPTS.

FIG. 7 is an FFT-based implementationMethod of

Structural block diagram of the calculator.

FIG. 8 is a diagram of a correlation-based implementation methodStructural block diagram of the calculator.

Detailed Description

As shown in fig. 2, the receiving apparatus according to the present invention includes an rf front end 21, an automatic gain controller 22, an analog-to-digital converter 23, a cosine transform filter 24, a receiver 26 and a timing tracking apparatus 25. The structure and function of the rf front-end 21, the agc 22, the adc 23, the radiconic cosine filter 24 and the receiver 26 are the same as in the prior art and their construction will not be described in detail here. The timing tracking means 25 receives the two paths of data of the late and early sampling points from the root cosine filter 24, and estimates a timing error based on the received data. Here, the late and early sampling points are for the ideal sampling point. The timing error obtained by the timing tracking means 25 is inputted to the analog-to-digital converter 23 to adjust the timing. The estimation of timing error needs two paths of over-sampled data, and the receiver receives normal data demodulation and needs one path of sampled data, so the receiving device in the invention at least needs three times of over-sampled data.

The principle of timing tracking in the present invention is that when the timing error is not 0, the early and late sampling points have different powers/amplitudes, so that the different powers/amplitudes of the early and late sampling points can be used to estimate the timing error. Once the timing tracking loop converges within the timing accuracy tolerance, i.e. the timing error is less than the required accuracy, the power/amplitude difference between the early and late sampling points will be less than a fixed threshold. The estimated timing error is for the sample that is intermediate the late sample and the early sample.

In an actual communication system, signals reach a receiving end from a transmitting end through different reflection paths to form multipath signals. Different propagation paths of a multipath signal cause different propagation delays, i.e., multipath effects. Fig. 1 shows a power-delay diagram of a multipath channel, wherein the multipath signal includes three significantly different paths, hereinafter referred to as effective path components. The timing tracking method can track any effective path, but preferably tracks the first effective path, so that the receiver can apply the effective path information as much as possible during data demodulation, and the data demodulation performance of the receiver is improved. In the following, only the tracking of the first effective path will be described.

Fig. 3 shows a block diagram of the timing tracking device 25 according to the present invention. As shown in FIG. 3, the timing estimation device 25 includes a data separator 251, a

A calculator 252, an averager 253, and a timing error calculator 254.

The data separator 251 separates the data of the early sampling point and the data of the late sampling point of the training sequence from the received data of the whole sub-frame, and obtains training sequence data of the early sampling point and training sequence data of the late sampling point. Since in most digital mobile communication systems, channel estimation can be performed by a training sequence, in TD-SCDMA systems (subframe structure is shown in fig. 4), the training sequence for downlink data can include midamble or SYNC-DL data of DwPTS portion. Therefore, the midamble or the early and late sampling data of SYNC-DL can be directly applied to perform timing error estimation in the TD-SCDMA system. Fig. 5 shows the time slot structure of TD-SCDMA, midamble is 144 chips in the TD-SCDMA time slot. SYNC-DL is located in DwPTS shown in fig. 6.

Therefore, the training sequence data obtained by the data separator 251 may be midamble data or SYNC-DL data. The preferred embodiment of the present invention is that the data separator 251 separates the last 128 chips of midamble of 144 chips in the time slot. In the following, an implementation of separating midamble by the data separator 251 will be described as an example, which is also applicable to the implementation of SYNC-DL.

The calculator 252 estimates powers of the early and late sample data based on the early and late sample data of the midamble part input from the data separator 251, and calculates the power based on the estimated powers

The early and late sampling data of the midamble part are respectively marked as e_{mid_e}(n), n-1, 2, …, 128 and e_{mid_l}(n)，n＝1，2，…，128。

Can be formulated as:

here, T_cAnd τ are the chip period and timing error, respectively. Delta is the same time difference between the ideal sample point and the late sample point, respectively, the early sample point.Is the result of the estimation of R (tau). For the root-raised cosine filter, when a is 0.22,

there are two ways to implement calculator 252. Implementation method 1 is based on FFT implementation method to calculate

The method is called as an FFT-Based timing tracking (FFT-Based timing tracking) method, and a structural block diagram Based on the method is shown in FIG. 7. The implementation method 2 is based on the calculation of the related implementation method

This is called Correlation-Based Timing Tracking (Correlation-Based Tracking) method in the present invention, and FIG. 8 shows a structural block Based on this methodFigure (a). These two implementations will be described separately in detail below.

As shown in fig. 7, the FFT-based implementation is calculated

Is/are as follows

The calculator 252 includes a channel estimator 71 for calculating the power of the early-sampled data, a first effective path decimator 72 and a power calculator 73, a channel estimator 71 for calculating the power of the late-sampled data, a first effective path decimator 72 and a power calculator 73, an adder 75, a subtractor 74, and a divider 76.

When the early-sampled data is input to the channel estimator 71, the channel estimator 71 calculates a channel impulse response from the received midamble and the local midamble. In the channel estimator 71, the channel impulse response h_eCan be calculated by the following formula,

h_e＝IFFT[FFT(e_{mid_e})./FFT(_mid)] (3)

here, h_e＝[h_e(1)，h_e(2)，...，h_e(128)]Is the estimated channel impulse response, e_{mid_e}＝[e_{mid_e}(1)，e_{mid_e}(2)，...，e_{mid_e}(128)]Is the early sampled data portion, L, of the received midamble data_{mid_e}＝[l_mid(1)，l_mid(2)，...，l_mid(128)]Is the local midamble data. FFT (), IFFT () respectively represent fast fourier transform and inverse transform of the data sequence in brackets.

The channel impulse response calculated by the channel estimator 71 is input to a first effective path decimator 72. A first effective path extractor 72 extracts a first effective path in the channel profile window (the first value in the channel profile window is defaulted to the first effective path) based on the known user code information (i.e., any code in the user slot). In the present invention, the default value of the code channel number used is the smallest code channel of the user in the user time slot. The extracted position can be calculated by:

N_extact＝112-(K-k_user)*W (4)

here, K is the number of the largest midamble shift values in one cell. W is the shift value of two adjacent miambles. k is a radical of_userIndicating the sequence number of the smallest code channel in the user time slot. When the number of the largest midamble shift values is K,

(

represents the largest integer less than ·). If we consider using the beacon code track of TSO to implement FFT-based timing tracking, N_extact0 is a fixed value.

The power calculator 73 calculates the power value of the extracted first effective diameter:

P_e＝|h_e(N_extact)|² (5)

similarly, the power of the late sampled data is also calculated by a channel estimator 71, a first effective path decimator 72 and a power calculator 73, in the same configuration as that used for the calculation of the power of the early sampled data. The difference is that the received data used in the calculation is late sampled midamble data. The late sample data power is noted as:

P_l＝|h_l(N_extact)|² (6)

the adder 75, the subtractor 75 and the divider 76 calculate based on the power of the early sampled data and the power of the late sampled dataIs formulated as:

as shown in fig. 8, the calculation is based on the implementation of correlation

Of

The calculator 252' includes a correlator 81 and a power calculator 82 for calculating the power of early-sampled data, a correlator 81 and a power calculator 82 for calculating the power of late-sampled data, a shift enable generator 86, an adder 84, a subtractor 83, and a divider 85.

The shifted midamble generator 86 generates shifted midamble codes from the basic midamble codes and the code channel information of the user. The generation process comprises the generation of a complex midamble and the generation of a shifted midamble.

The generation of complex midambles is a process of converting a basic midamble into a complex midamble code, which is described as:

m(n)＝jⁿ*m(n)；n＝1，2，...，128 (8)

here, m (n) is a binary representation of the basic midamble.

Displacement of

Can be expressed as:

<math> <mrow> <msub> <mi>m</mi> <mi>l</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <munder> <mi>m</mi> <mo>&OverBar;</mo> </munder> <mrow> <mo>(</mo> <mi>n</mi> <mo>+</mo> <mrow> <mo>(</mo> <mi>K</mi> <mo>-</mo> <msub> <mi>k</mi> <mi>user</mi> </msub> <mo>)</mo> </mrow> <mo>*</mo> <mi>W</mi> <mo>)</mo> </mrow> <mo>;</mo> <mi>whenn</mi> <mo>+</mo> <mrow> <mo>(</mo> <mi>K</mi> <mo>-</mo> <msub> <mi>k</mi> <mi>user</mi> </msub> <mo>)</mo> </mrow> <mo>*</mo> <mi>W</mi> <mo>≤</mo> <mn>128</mn> </mtd> </mtr> <mtr> <mtd> <munder> <mi>m</mi> <mo>&OverBar;</mo> </munder> <mrow> <mo>(</mo> <mi>n</mi> <mo>+</mo> <mrow> <mo>(</mo> <mi>K</mi> <mo>-</mo> <msub> <mi>k</mi> <mi>user</mi> </msub> <mo>)</mo> </mrow> <mo>*</mo> <mi>W</mi> <mo>-</mo> <mn>128</mn> <mo>)</mo> </mrow> <mo>;</mo> <mi>whenn</mi> <mo>+</mo> <mrow> <mo>(</mo> <mi>K</mi> <mo>-</mo> <msub> <mi>k</mi> <mi>user</mi> </msub> <mo>)</mo> </mrow> <mo>*</mo> <mi>W</mi> <mo>></mo> <mn>128</mn> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> </mrow> </math>

here, n is 1, 2, …, 128. K is the number of the largest midamble shift values in a cell. W is the shift value of two adjacent midambles. k is a radical of_userIndicating the sequence number of the smallest code channel in the user time slot. When the number of the largest midamble shift values is K,

(

represents the largest integer less than ·). If we consider using the beacon code track of TSO to realize the timing tracking based on correlation, (K-K)_user) W-112 is a fixed value.

The shifted midamble code generated by the shifted midamble generator 86 is input to the correlator 81. The correlator 81 calculates the correlation result of the shifted midamble and the received early sampled midamble. Correlation result R of early sampled data_eCan be expressed as:

the correlation result R_eInto the power calculator 82. The power calculator 82 calculates the power value of the extracted first effective diameter from the input correlation result:

P_e＝|R_e|² (11)

the late sampled data power is also calculated by a correlator 81 and a power calculator 82, which are the same in structure as those employed for the calculation of the early sampled data power. The difference is that the received data used in the calculation is late sampled midamble data.

Correlation result R of late sampled data_lCan be expressed as:

the power of the late sampled data is noted as:

P_l＝|R_l|² (13)

the adder 84, the subtractor 83 and the divider 85 calculate based on the power of the early sampled data and the power of the late sampled dataIs formulated as:

calculated by calculator 252

And input to the averager 253. The averager 253 calculates n sub-frames

The result can be expressed as:

where n is a number

Number of subframes of the mean. The minimum value of n may be 1. When the timing variation is within the allowable accuracy requirement (e.g., 1/8 chips), the larger the value of n,

the closer the mean is to the statistical mean.

The timing error calculator 254 calculates a timing error from the result of the averager 253. There are two ways to implement this calculation:

a first way to implement this is for the tracking loop to make a fixed step adjustment of the timing. Here, the adjusted timing error value is calculated based on the threshold value T and the adjustment step value α. Timing error adjustment value

Can be calculated using the following equation:

<math> <mrow> <msub> <mover> <mi>T</mi> <mo>^</mo> </mover> <mi>offset</mi> </msub> <mo>=</mo> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <mo>-</mo> <mi>α</mi> <mo>,</mo> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>τ</mi> <mo>/</mo> <msub> <mi>T</mi> <mi>c</mi> </msub> <mo>)</mo> </mrow> <mo><</mo> <mo>-</mo> <mi>T</mi> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> <mo>,</mo> <mo>-</mo> <mi>T</mi> <mo>≤</mo> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>τ</mi> <mo>/</mo> <msub> <mi>T</mi> <mi>c</mi> </msub> <mo>)</mo> </mrow> <mo>≤</mo> <mi>T</mi> </mtd> </mtr> <mtr> <mtd> <mi>α</mi> <mo>,</mo> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>τ</mi> <mo>/</mo> <msub> <mi>T</mi> <mi>c</mi> </msub> <mo>)</mo> </mrow> <mo>></mo> <mi>T</mi> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>16</mn> <mo>)</mo> </mrow> </mrow> </math>

here, ,

the unit of (a) is a chip. This estimate is used to adjust the timing of the next subframe.

A second way to implement this is for the tracking loop to make a non-fixed step adjustment of the timing.

Here, the timing error adjustment value is based on the threshold value T, the adjustment step value alpha and the oversampling multiple S_n(i.e., the sampling clock frequency) are calculated jointly.

Here, ,

maximum integer representing absolute value smaller than · sign [ ·]The symbol of. T is a threshold value, which can be defined by two of the above-mentionedA method for determining; k is

The slope of the function curve, as described above.

When the relation between the oversampling multiple of the system and the required precision is 1/S_nThe second implementation is fully equivalent to the first implementation when α.

When the relation between the oversampling multiple of the system and the required precision is 1/S_nWhen the value is less than alpha, the convergence effect of the timing error of the second implementation method is better than that of the first implementation method.

For the two methods, the threshold value and the adjustment step value may be determined according to the accuracy requirement of the timing, and taking 1/8 chips as an example, the adjustment step may be set to α -1/8.

There are two calculation methods for the threshold value T.

The first method can be directly based on the precision requirement

The slope of the function curve at 0 point is set, for example, in TD-SCDMA system, the filter is root raised cosine filter, so

The slope of the function curve is K1.402, and if 1/8 chips of accuracy are required, the threshold T is equal to:

the second method can be directly obtained by using a formula:

T＝G(T_required/T_c) (19)

here, T_requiredIs the required progress accuracy of the synchronization tracking,

taking a root raised cosine filter with a being 0.22 as an example, R (τ) is shown in formula (2), and the calculation method of the present invention is also suitable for other filters.

In the following, a timing tracking method according to the present invention is described. The timing tracking method comprises the following steps:

a training sequence data separating step of separating early sample point data and late sample point data of the training sequence from the received data by using a data separator 251,

calculation step of using

A calculator 252 for calculating training sequence data according to the training sequence data separated by the data separator

An averaging step of calculating n sub-frames using the averager 253And a timing error calculation step of calculating a timing error based on the result of the averaging step using the timing error calculator 254.

In the training sequence data separation step, the separated training sequence data is midamble data or SYNC-DL data.

There are two implementation methods for the calculation step of (a) and (b), namely an FFT-based implementation method and a correlation-based implementation method.

The FFT-based implementation method comprises calculating the power of the early sampled data according to the training sequence data of the early sampled point, the local training sequence and the user code channel informationStep of calculating power of late sampling data according to training sequence data of late sampling point, local training sequence and user code channel information, and calculating power of early sampling data and power of late sampling data according to calculated power of early sampling data

In the step (2) of (a),

P_efor early sampling of the power of the data, P_lIs the power of the late sampled data.

The related realization method comprises a step of calculating the power of early sampling data according to the training sequence data of the early sampling point and the shifting training sequence, a step of calculating the power of late sampling data according to the training sequence data of the late sampling point and the shifting training sequence, and a step of calculating the power of the early sampling data and the power of the late sampling data according to the calculated power of the early sampling data and the calculated power of the late sampling dataIn the step (2) of (a),

The timing error adjustment value calculation step has two implementation methods. The first method for realizing the timing error adjustment value calculation step is to calculate the timing error adjustment value according to the threshold value T and the adjustment step value alpha

<math> <mrow> <msub> <mover> <mi>T</mi> <mo>^</mo> </mover> <mi>offset</mi> </msub> <mo>=</mo> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <mo>-</mo> <mi>α</mi> <mo>,</mo> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>τ</mi> <mo>/</mo> <msub> <mi>T</mi> <mi>c</mi> </msub> <mo>)</mo> </mrow> <mo><</mo> <mo>-</mo> <mi>T</mi> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> <mo>,</mo> <mo>-</mo> <mi>T</mi> <mo>≤</mo> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>τ</mi> <mo>/</mo> <msub> <mi>T</mi> <mi>c</mi> </msub> <mo>)</mo> </mrow> <mo>≤</mo> <mi>T</mi> </mtd> </mtr> <mtr> <mtd> <mi>α</mi> <mo>,</mo> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>τ</mi> <mo>/</mo> <msub> <mi>T</mi> <mi>c</mi> </msub> <mo>)</mo> </mrow> <mo>></mo> <mi>T</mi> </mtd> </mtr> </mtable> </mfenced> </mrow> </math>

Wherein,

the result obtained in the averaging step.

The second method for realizing the timing error adjustment value calculation step is to calculate the adjustment step value alpha and the oversampling multiple S according to the threshold value T_nCalculating a timing error adjustment value

Here, ,

as a result of the averaging step, the average value,maximum integer representing absolute value smaller than · sign [ ·]The symbol of.

In both implementations of the timing error calculation step described above, the threshold value T is equal to

The slope of the function curve at point 0 is multiplied by the required accuracy value, or by the formula T ═ G (T)_required/T_c) And (4) calculating. Here, T_requiredIs the required accuracy of the synchronous tracking progress,

T_cand τ is the chip period and timing error, respectively, and Δ is the same time difference between the ideal sample and the late and early samples, respectively.

The timing adjustment method according to the present invention adjusts the timing using the timing error calculated by the above-described timing tracking method.

Additional advantages and modifications will readily appear to those skilled in the art. Therefore, the present invention is not limited to the embodiments described in the specification. Accordingly, various modifications may be made without departing from the spirit or scope of the invention as defined by the appended claims and their equivalents.

Claims

1. A timing tracking apparatus for calculating a timing error using data at an early sample point and a late sample point, comprising

A data separator for separating the early sampling point and late sampling point data of the training sequence from the received data,

a

A calculator for calculating the time of the measurement,

P_efor early sampling of the power of the data, P_lFor late sampling of the power of the data, said

The calculator is used for respectively estimating the power of the early sampling point data and the power of the late sampling point data according to the training sequence data of the early sampling point data and the late sampling point data separated by the data separator, and calculating

The value of (a) is,

an averager for calculating n sub-frames

Is a mean value of

And the timing error calculator is used for calculating the timing error according to the average value output by the averager.

2. The timing tracking device of claim 1,

the training sequence data separated by the data separator is midamble data or SYNC-DL data.

3. The timing tracking device of claim 1,

the calculator being based on FFTA calculator comprising

A channel estimator for calculating power of the early sampled data based on the training sequence data of the early sampled point, the local training sequence and the user code channel information, an effective path extractor and a power calculator,

a channel estimator for calculating power of late sampled data in accordance with training sequence data of late sampled points, local training sequence and user code channel information, an effective path extractor and a power calculator, and a power calculator for calculating power P of early sampled data in accordance with calculated power P of late sampled data_eAnd power P of the late sampled data_lComputing

The computing unit of (1).

4. The timing tracking device of claim 1,

the calculator being based on a correlation-based implementation

A calculator comprising

A correlator and a power calculator for calculating the power of the early sample data in accordance with the training sequence data of the early sample point, the shifted training sequence,

a correlator and a power calculator for calculating the power of the late sampled data in accordance with the training sequence data of the late samples, the shifted training sequence, and

power P for early sampled data according to computation_eAnd power P of the late sampled data_lComputing

The computing unit of (1).

5. The timing tracking device of claim 1,

the timing error calculator calculates a timing error adjustment value according to the threshold value T and the adjustment step value alpha

Wherein,

is the output of the averager.

6. The timing tracking device of claim 1,

the timing error calculator adjusts the step value alpha and the oversampling multiple S according to the threshold value T_nCalculating a timing error adjustment value

Here, ,is the output of the averaging device and is,

maximum integer representing absolute value less than · sign[·]Symbol of, K is

The slope of the function curve.

7. The timing tracking device of claim 5,

threshold value T is equal to

The slope at point 0 is multiplied by the precision value of the demand.

8. The timing tracking device of claim 6,

threshold value T is equal to

The slope at point 0 is multiplied by the precision value of the demand.

9. The timing tracking device of claim 5,

T＝G(T_required/T_c)

here, T_requiredIs the required accuracy of the synchronous tracking progress,

T_eand τ is the chip period and timing error, respectively, and Δ is the same time difference between the ideal sample and the late and early samples, respectively.

10. The timing tracking device of claim 6,

T＝G(T_required/T_c)

here, T_requiredIs the required accuracy of the synchronous tracking progress,

11. A receiving device having a timing tracking device according to any one of claims 1 to 10 which adjusts the timing using the timing error calculated by the timing tracking device.

12. A timing tracking method, comprising

A training sequence data separation step, wherein a data separator is used to separate the early sampling point data and the late sampling point data of the training sequence from the received data respectively,

calculating stepProcedure of using

A value of (b), wherein P_cFor early sampling of the power of the data, P_lIn order to late-sample the power of the data,

averaging step, using an averager to calculate n sub-framesIs a mean value of

And a timing error calculation step of calculating a timing error according to the result of the averaging step by using a timing error calculator.

13. The timing tracking method of claim 12, wherein

The separated training sequence data is midamble data or SYNC-DL data.

14. The timing tracking method of claim 12,

the calculation step of (a) is based on an FFT implementation method, comprising,

calculating the power of the early sampling data according to the training sequence data of the early sampling point, the local training sequence and the user code channel information,

calculating the power of the late sampled data based on the training sequence data of the late samples, the local training sequence and the user code channel information, an

According to the calculated power P of the early sampling data_eAnd power P of the late sampled data_lComputingThe step (2).

15. The timing tracking method of claim 12,

based on the correlation, comprises

Calculating the power of the early sample data by shifting the training sequence according to the training sequence data of the early sample point,

calculating the power of the late sampled data by shifting the training sequence in accordance with the training sequence data of the late sampled points, an

According to the calculated power P of the early sampling data_eAnd power P of the late sampled data_lComputing

The step (2).

16. The timing tracking method of claim 12,

the timing error calculation step is to calculate the timing according to the threshold value T and the adjustment step value alphaTime error adjustment value

Wherein,the result obtained in the averaging step.

17. The timing tracking method of claim 12,

the timing error calculation step is based on the threshold value T, the adjustment step value alpha and the oversampling multiple S_nCalculating a timing error adjustment value