TW201926939A - Phase recovery device and phase recovery method - Google Patents

Abstract

A phase recovery device includes a phase estimation module receiving a plurality of received signals, where the plurality of received signals includes a plurality of pilot signals and a plurality of data signals, the phase detection module comprising a pilot phase estimation unit calculating a plurality of pilot phase errors according to the plurality of pilot signals; a weighting unit calculating a plurality of weighting values corresponding to the plurality of pilot phase errors; and a combining unit calculating a plurality of phase errors corresponding to the data signals according to the plurality of pilot signals and the plurality of weighting values; and a phase compensating module compensating a plurality of phases of the plurality of received signals according to the phase errors.

Description

Phase recovery device and phase recovery method

The invention relates to a phase recovery device and a phase recovery method, in particular to a phase recovery device and a phase recovery method capable of accurately estimating a phase error.

Phase recovery (Phase Recovery) at the receiving end of the digital communication system can compensate the phase error of the signal to effectively reduce the system's Symbol Error Rate (SER) or Bit Error Rate (Bit Error Rate, BER), while improving system performance.

In general, phase recovery requires phase error detection (PED) on the received signal, and phase compensation is performed based on the estimated phase error. In the prior art, the phase error estimator in the phase recovery device is an open loop phase error estimator (Open Loop PED), and the circuit structure and calculation amount of the open loop phase error estimator are simple, but the estimated The accuracy of the phase error is also poor.

Therefore, how to provide a phase recovery device and a phase recovery method for accurately estimating the phase error has become one of the goals of the industry.

Accordingly, it is a primary object of the present invention to provide a phase recovery device and a phase recovery method that accurately estimate phase errors to improve the shortcomings of the prior art.

The present invention discloses a phase recovery device including a phase estimation module for receiving a plurality of received signals, wherein the plurality of received signals includes a plurality of pilot signals and a plurality of data signals, and the phase estimation module includes a pilot a phase estimating unit, configured to calculate a plurality of pilot phase errors according to the plurality of pilot signals; a weighting unit configured to calculate, according to the at least one received signal of the plurality of received signals, corresponding to the plurality of pilot phases a plurality of weight values; and a combining unit configured to calculate a plurality of phase errors corresponding to the plurality of data signals based on the plurality of pilot phase errors and the plurality of weight values, wherein the plurality of phase errors are a linear combination of a plurality of pilot phases; and a phase compensation module for compensating for a plurality of phases of the plurality of received signals based on the plurality of phase errors.

The present invention further discloses a phase recovery method, including receiving a plurality of received signals, wherein the plurality of received signals includes a plurality of pilot signals and a plurality of data signals; and calculating a plurality of pilot phase errors according to the plurality of pilot signals; Calculating, according to at least one of the plurality of received signals, a plurality of weight values corresponding to the plurality of pilot phases; calculating, according to the plurality of pilot phase errors and the plurality of weight values, corresponding to the plurality of data signals a plurality of phase errors, wherein the plurality of phase errors are linear combinations of the plurality of pilot phases; and compensating for a plurality of phases of the plurality of received signals based on the plurality of phase errors.

FIG. 1 is a block diagram of a Phase Recovery device 1 according to an embodiment of the present invention. The phase recovery device 1 is used to phase restore a plurality of received signals r. The phase recovery device 1 includes a phase estimation module 10 and a phase compensation module 20. The phase estimation module 10 receives a plurality of received signals r and calculates/estimates a plurality of phases corresponding to the plurality of received signals r. Error x. The phase compensation module 20 compensates a plurality of phases of the plurality of received signals r based on the plurality of phase errors x. The phase estimation module 10 includes a pilot phase estimation unit 12, a weight unit 14, and a combining unit 16. FIG. 2 is a flow chart of a phase recovery method 22 according to an embodiment of the present invention.

Referring to FIG. 1 and FIG. 2 together, the phase estimation module 10 receives a plurality of received signals r, wherein the plurality of received signals r includes a plurality of pilot signals (Pilot Signal) and a plurality of data signals (Data Signal). (Step 200), the pilot phase estimation unit 12 is configured to calculate a plurality of pilot phase errors based on the plurality of pilot signals of the plurality of received signals r (step 202). On the other hand, the weighting unit 14 calculates a plurality of weight values corresponding to the pilot phase error based on at least one of the plurality of received signals r (step 204). The combining unit 16 calculates a plurality of phase errors x corresponding to the plurality of data signals according to the plurality of pilot phase errors and the plurality of weight values, wherein each of the plurality of phase errors x is linear of the plurality of pilot phases Linear Combination (step 206). In this way, the phase compensation module 20 can compensate a plurality of phases of the plurality of received signals according to the plurality of phase errors x (step 208).

In detail, please refer to FIG. 3, which is a schematic diagram of a plurality of pilot signals r _P1 , r _P2 , r _P3 , r _P4 and a plurality of data signals r _{D in} a plurality of received signals r, and a plurality of data signals. r _D is a data signal to be compensated by the phase recovery device 1 at a first time, a plurality of pilot signals r _P2 and a plurality of data signals r _D form a frame F _i , wherein a plurality of data signals r _{D are} located The data interval T _D in the frame F _i , the plurality of pilot signals r _{P2 are} located in the pilot interval T _P in the frame F _i . The plurality of pilot signals r _P1 , r _P3 , and r _P4 are pilot signals corresponding to the frames F _i-1 , F _i+1 , and F _i+2 . In an embodiment, the pilot interval T _P may include 36 pilot signals, and the data interval T _D may include 1440 data signals.

In step 202, the pilot phase estimation unit 12 can calculate corresponding to the frames F _i-1 , F _i , F _i+1 , F _i according to the plurality of pilot signals r _P1 , r _P2 , r _P3 , r _P4 . ₊₂ (or pilot phase errors θ ₁ , θ ₂ , θ ₃ , θ ₄ corresponding to pilot signals r _P1 , r _P2 , r _P3 , r _P4 ), wherein pilot phase estimation unit 12 is based on a plurality of derivatives The technical details of calculating the pilot phase errors θ ₁ to θ ₄ from the frequency signals r _P1 to r _P4 are known to those skilled in the art and will not be described herein.

In step 204, the weighting unit 14 calculates a plurality of weight values w ₁ to w ₄ corresponding to the pilot phase errors θ ₁ to θ ₄ based on the at least one received signal. Please refer to FIG. 3 , which is a block diagram of a weight unit 14 according to an embodiment of the present invention. The weight unit 14 includes a cross correlation calculation unit 140, an autocorrelation calculation unit 142, a weight calculation unit 144, and a measurement error calculation. Unit 146. The cross correlation calculation unit 140 is configured to calculate a plurality of cross-correlation values k _yx1 ～ k _yx4 corresponding to the pilot phase errors θ ₁ θ θ ₄ with respect to the time t according to a time t, wherein the plurality of cross-correlation values k _yx1 ～ k _yx4 is a cross-correlation of a first phase error θ _t and the plurality of pilot phase errors θ ₁ ～ θ ₄ , respectively, and the first phase error θ _t may be a plurality of data signals r _D in time The phase error of the data signal r _{D,t of t} . The cross-correlation values k _yx1 ～ k _yx4 can form a cross-correlation vector K _yx , that is, K _yx =[k _yx1 , k _yx2 , k _yx3 , k _yx4 ] ^T =E{[θ ₁ , θ ₂ , θ ₃ , θ ₄ ] ^T θ _t } (where E{} represents the expected value operator). On the other hand, the measurement error calculation unit 146 is configured to calculate a measurement error ε according to the at least one received signal r, and the autocorrelation calculation unit 142 is configured to calculate a plurality of autocorrelation values according to the measurement error ε, where multiple The autocorrelation value is an autocorrelation of a plurality of pilot phase errors θ ₁ ～ θ ₄ , and the plurality of autocorrelation values may form an autocorrelation matrix K _yy which is K _yy = E{[θ ₁ , θ ₂ , θ ₃ , θ ₄ ] ^T [θ ₁ , θ ₂ , θ ₃ , θ ₄ ]}. The weight calculation unit 144 calculates a plurality of weight values w ₁ to w ₄ based on the cross-correlation vector K _yx (cross-correlation values k _yx1 to k _yx4 ) and the autocorrelation matrix K _yy (a plurality of autocorrelation values).

In detail, assuming that the trajectory motion of the phase error in the received signal r is Brownian Motion (BM) (ie, it is assumed that the time function of the phase error in the received signal r changes with time is proportional to / proportional to a Brownian motion program (BM Process)), the cross-correlation vector K _yx can be expressed as Equation 1, and the autocorrelation matrix K _yy can be expressed as Equation 2, where the constant c is an arbitrary constant. (Formula 1) (Formula 2)

After the cross-correlation calculation unit 140 calculates the cross-correlation vector K _yx and the autocorrelation calculation unit 142 calculates the autocorrelation matrix K _yy , the weight calculation unit 144 may calculate the weight vector w= according to the cross-correlation vector K _yx and the autocorrelation matrix K _yy . [w ₁ , w ₂ , w ₃ , w ₄ ] ^T (where the weight values w ₁ to w ₄ form a weight vector w). The weight calculation unit 144 may calculate the calculation weight vector w as w = [w ₁ , w ₂ , w ₃ , w ₄ ] ^T = (K _yy ) ^-1 K _yx (Equation 3). In other words, the weight calculation unit 144 calculates an inverse matrix K _yy is the autocorrelation matrix and autocorrelation matrix K _yy multiplied by the inverse matrix of the cross-correlation vector K _yx, to output a weight vector w (i.e., weight values w ₁ ~ w ₄ ).

In addition, the measurement error calculation unit 146 may calculate a Signal-to-Noise Ratio (SNR) according to the at least one received signal, and calculate the measurement according to the signal-to-noise ratio and the Phase Noise Intensity (αT). The error ε is ε = σ ² / (1476αT), and σ ^{2 is} related to the Signal-to-Noise Ratio (SNR), which can be proportional to the reciprocal of the signal-to-noise ratio. In one embodiment, the measurement error calculation unit 146 can calculate σ ² as σ ² =N ₀ /(72E _S ), where E _S is the symbol energy (Symbol Energy), and N ₀ is the noise spectral density (Noise) Power Density), where E _S , N ₀ , αT can be adjusted according to actual conditions. In another embodiment, the measurement error calculation unit 146 may calculate a signal-to-noise ratio according to at least one of the plurality of received signals r, and calculate σ ² according to the signal-to-noise ratio. In addition, the technical details of calculating the signal-to-noise ratio according to the at least one received signal by the measurement error calculation unit 146 are known to those skilled in the art, and thus are not described herein.

In step 206, the combining unit 16 calculates a plurality of data signals r _D corresponding to the pilot phase errors θ ₁ , θ ₂ , θ ₃ , θ ₄ and the weight values w ₁ , w ₂ , w ₃ , and w ₄ . The phase error x, any of which is generally expressed as x = w ₁ θ ₁ + w ₂ θ ₂ + w ₃ θ ₃ + w ₄ θ ₄ (Equation 4). Since the weight vector w is calculated by Equation 3, the phase error x calculated/estimated by the combining unit 16/phase estimation module 10 is a Maximum Likelihood (ML) estimation of the phase error x. .

In an embodiment, the cross-correlation calculation unit 140 may divide the data interval T _D into N time points t ₀ ～t _N (N may be equal to 1440), and the cross-correlation calculation unit 140 may calculate from the formula 1 corresponding to the time point t _{0 .} The N cross-correlation vectors K _{yx, 0} ～ K _{yx, N-1 of} ～t _N-1 , the weight calculation unit 144 can be calculated by the formula 3 according to the N cross-correlation vectors K _{yx, 0} ～ K _{yx, N-1} respectively. Weight values corresponding to time points t ₀ to t _N-1 (w _1,0 , w _2,0 , w _3,0 , w _4,0 ) to (w _1,N-1 , w _2,N-1 , w _{3, N-1} , w _{4, N-1} ) (which involves N inverse matrix operations), the combining unit 16 can calculate from the formula 4 that the phase error x _n corresponding to the data signal r _{D, n} is x _n = w _1,n θ ₁ + w _2,n θ ₂ + w _3,n θ ₃ + w _4,n θ ₄ , wherein the data signal r _D,n is a plurality of data signals r _D corresponding to the time point t _n The data signal, the time point t _n may be a time point in the time points t ₀ to t _N .

In an embodiment, the cross-correlation calculation unit 140 may calculate one cross-correlation vector K _yx,0 corresponding to the time point t ₀ from the formula 1 _, and the re-calculation unit 144 may be calculated by the formula 3 according to the cross-correlation vector K _yx,0 . Corresponding to the weight value (w _1,0 , w _2,0 , w _3,0 , w _4,0 ) at the time point t ₀ (which involves only one inverse matrix operation), the combining unit 16 can be calculated by the formula 4 In addition to the phase error x _{0 of the} data signal r _D,0 (which may be regarded as the initial value LW), the combining unit 16 may further calculate an update value LRA such that the phase error x _n corresponding to the data signal r _{D, n} is x _n = LW–n* LRA.

Specifically, please refer to FIG. 5, which is a block diagram of the combining unit 16 according to an embodiment of the present invention. As shown in FIG. 5, the combining unit 16 may include an initial unit 160, an updating unit 162, and a accumulating unit 164. The initial unit 160 may calculate the initial value LW as LW = w ₁ θ ₁ + w ₂ θ according to the weight values w ₁ , w ₂ , w ₃ , w ₄ and the pilot phase errors θ ₁ , θ ₂ , θ ₃ , θ ₄ . ₂ + w ₃ θ ₃ + w ₄ θ ₄ , that is, a product term sum between the calculated weight values w ₁ , w ₂ , w ₃ , w ₄ and the pilot phase errors θ ₁ , θ ₂ , θ ₃ , θ ₄ (Sum-of-Product), in addition, the weight value (w ₁ , w ₂ , w ₃ , w ₄ ) at this time may be a weight value corresponding to the time point t ₀ (w _1,0 , w _2,0 , w _3,0 , w _4,0 ), and the calculated initial value LW is LW = w _1,0 θ ₁ + w _2,0 θ ₂ + w _3,0 θ ₃ + w _4,0 θ ₄ . The update unit 162 may calculate the update value LRA according to the weight values w ₁ , w ₂ , w ₃ , w ₄ and the pilot phase errors θ ₁ , θ ₂ , θ ₃ , θ ₄ , wherein the update value LRA may be proportional to ( w ₁ -w ₄ ) θ ₁ + (w ₂ - w ₃ ) θ ₂ + (w ₃ - w ₂ ) θ ₃ + (w ₄ - w ₁ ) θ ₄ . The accumulating unit 164 can calculate the phase error x _n corresponding to the data signal r _D,n (at the time point t _n ) as x _n = LW - n * LRA based on the initial value LW and the updated value LRA.

The initial unit 160, the update unit 162, and the accumulation unit 164 are not limited to being implemented in a specific circuit configuration. For example, please refer to FIG. 6 to FIG. 8 , and FIG. 6 to FIG. 8 are respectively an initial embodiment of the present invention. A schematic diagram of unit 160, update unit 162, and accumulation unit 164. As can be seen from FIG. 6, the initial unit 160 includes a multiplier MP1 and an accumulator ACC1. The accumulator ACC1 includes an adder AD1 and a register Q1. The initial unit 160 receives the pilot phase errors θ ₁ , θ ₂ , θ ₃ , θ _{4 in} a time sequence. For example, the initial unit 160 receives the pilot phase error θ ₁ at times s ₁ , s ₂ , s ₃ , s _{4 ,} respectively. , θ ₂ , θ ₃ , θ ₄ . At time s ₁ , the multiplier MP1 multiplies the weight value w ₁ by the pilot phase error θ ₁ to generate a multiplication result w ₁ θ ₁ , and the initial unit 160 stores the multiplication result w ₁ θ ₁ in the register Q1. . At time s ₂ , the multiplier MP1 multiplies the weight value w ₂ by the pilot phase error θ ₂ to generate a multiplication result w ₂ θ ₂ , and the adder AD1 multiplies the multiplication result w ₂ θ ₂ and the multiplication result w ₁ θ _{1 is} added to generate an accumulated result w ₁ θ ₁ + w ₂ θ ₂ , and the initial unit 160 stores the accumulated result w ₁ θ ₁ + w ₂ θ ₂ in the register Q1. By analogy, at time s ₄ , the multiplier MP1 multiplies the weight value w ₄ by the pilot phase error θ ₄ , and the adder AD1 multiplies the multiplication result w ₄ θ ₄ with the accumulated result w ₁ θ _{1 of the} corresponding time s ₃ + w ₂ θ ₂ + w ₃ θ ₃ are added to produce an accumulated result w ₁ θ ₁ + w ₂ θ ₂ + w ₃ θ ₃ + w ₄ θ ₄ , and the initial unit 160 will accumulate the result w ₁ θ ₁ + w ₂ θ ₂ + w ₃ θ ₃ + w ₄ θ _{4 is} stored in the register Q1, and the initial value LW is output as LW = w ₁ θ ₁ + w ₂ θ ₂ + w ₃ θ ₃ + w ₄ θ ₄ .

As can be seen from FIG. 7, the updating unit 162 can include a multiplying unit 70, a summing unit 72, and an adjusting unit 74. The multiplying unit 70 multiplies the pilot phase errors θ ₁ , θ ₂ , θ ₃ , and θ ₄ by the subtraction results ( w ₁ - w ₄ ), (w ₂ - w ₃ ), (w ₃ - w ₂ ), w ₄ - w ₁ ) to produce multiplication results ( w ₁ -w ₄ ) θ ₁ , (w ₂ – w ₃ ) θ ₂ , (w ₃ – w ₂ ) θ ₃ , (w ₄ – w ₁ ) θ ₄ . The summing unit 72 is used to add the multiplication results ( w ₁ -w ₄ ) θ ₁ , (w ₂ - w ₃ ) θ ₂ , (w ₃ - w ₂ ) θ ₃ , (w ₄ - w ₁ ) θ ₄ In total, to produce a total result I is I = ( w ₁ - w ₄ ) θ ₁ + (w ₂ - w ₃ ) θ ₂ + (w ₃ - w ₂ ) θ ₃ + (w ₄ – w ₁ ) θ ₄ . The adjusting unit 74 is configured to multiply the total result by an adjustment coefficient h to generate an updated value LRA as LRA=h*I=h*[( w ₁ —w ₄ ) θ ₁ +(w ₂ – w ₃ ) θ ₂ + (w ₃ - w ₂ ) θ ₃ + (w ₄ - w ₁ ) θ ₄ ], the adjustment unit 74 can be implemented by a multiplier. In an embodiment, the adjustment factor h may be equal to or proportional to (1/N), and N may be 1440.

As can be seen from FIG. 8, the accumulation unit 164 includes a register Q2, a subtractor SB, and a multiplexer MUX. At time t ₀ , the multiplexer MUX can output the initial value LW to the register Q2, and the accumulation unit 164 stores the initial value LW in the register Q2, and the temporary storage content RC of the register Q2 is the initial value. LW. At time point t ₁ , the subtractor SB subtracts the temporary value RC (ie, the initial value LW) from the updated value LRA to generate the updated temporary content RC', ie RC'= RC – LRA= LW– LRA, The multiplexer MUX can output the temporary content RC of the temporary storage content RC' to the temporary storage device Q2 as LW-LRA. At time point t ₂ , the subtractor SB subtracts the updated value LRA from the temporary content RC (ie LW - LRA) to produce the updated temporary content RC', ie RC' = RC - LRA = LW - 2 * LRA In addition, the multiplexer MUX can output the temporary content RC of the temporary storage content RC' to the temporary storage device Q2 as LW-2*LRA. By analogy, at time t _n , the subtractor SB subtracts the temporary value RC (ie LW - (n - 1) * LRA) from the updated value LRA to generate the updated temporary content RC ', ie RC' = RC - LRA = LW - n * LRA, and the output temporary content RC' is the phase error x _n corresponding to the data signal r _D,n (at time point t _n ).

In step 208, the phase compensation module 20 compensates a plurality of phases of the plurality of received signals according to the plurality of phase errors x. The technical details are known to those skilled in the art, and thus are not described herein.

In general, the maximum likelihood estimation has better performance, but its computational cost is quite high. Even if the weight vector w can be calculated using Equation 3, the cross-correlation vector K _yx and the autocorrelation matrix K _yy need to be utilized in the prior art. It is implemented in a statistical manner, which requires a lot of computational effort and the latency required to perform statistics. In contrast, the present invention assumes that the cross-correlation calculation unit 140 and the autocorrelation calculation unit 142 can simply calculate the cross-correlation vector from Equation 1 and Equation 2, assuming that the trajectory motion of the phase error in the received signal r is Brownian motion. K _yx and the autocorrelation matrix K _yy provide an easy way to achieve maximum likelihood estimation.

Further, since the cross-correlation vector K _{yx is} Time Varying (please refer to Formula 1), in order to omit the N-th inverse matrix operation, the present invention calculates the initial value LW using the initial unit 160, and uses the update unit 162. The update value LRA is calculated, and the phase error x _n (n=1, . . . , N corresponding to the data signal r _D,n (at time point t _n ) is calculated by means of the accumulation unit 164 in a stepwise update manner. ), it only needs to perform one inverse matrix operation, which greatly reduces the computational complexity.

In addition, the pilot signals r _P1 , r _P2 , r _P3 , and r _{P4 are} temporally distributed before and after the plurality of data signals r _D , and the calculated phase error x can be regarded as based on the pilot phase errors θ ₁ , θ _{2 .} , θ _3, the fourth-order interpolation performed by [theta] ₄ (4 ^th order interpolation), the estimated increase its accuracy. The above are only the preferred embodiments of the present invention, and all changes and modifications made to the scope of the present invention should be within the scope of the present invention.

1‧‧‧ phase recovery device

10‧‧‧ Phase Estimation Module

12‧‧‧Pilot Phase Estimation Unit

14‧‧‧weight unit

140‧‧‧Related correlation unit

142‧‧‧Autocorrelation calculation unit

144‧‧‧weight calculation unit

146‧‧‧Measurement error calculation unit

16‧‧‧Combination unit

160‧‧‧ initial unit

162‧‧‧Update unit

164‧‧‧Accumulating unit

20‧‧‧ phase compensation module

22‧‧‧ Phase recovery method

200-208‧‧‧ steps

70‧‧‧Multiplication unit

72‧‧‧Additional unit

74‧‧‧Adjustment unit

F _i-1 , F _i , F _i+1 , F _i+2 ‧‧‧ frame

ACC1‧‧‧ accumulator

AD1‧‧‧Adder

H‧‧‧adjustment factor

I‧‧‧ total results

K _yx ‧‧‧ cross correlation vector

K _yy ‧‧‧autocorrelation matrix

LRA‧‧‧ updated value

LW‧‧‧ initial value

MP1‧‧‧ Multiplier

MUX‧‧‧Multiplexer

Q1, Q2‧‧‧ register

R‧‧‧ receiving signal

r _D ‧‧‧Information signal

r _P1 , r _P2 , r _P3 , r _P4 ‧‧‧ pilot signals

RC, RC’‧‧‧ temporary content

SB‧‧‧Subtractor

T _D ‧‧‧ data interval

T _P ‧‧‧Pilot interval

w ₁ ~ w ₄ ‧ ‧ weight value

X‧‧‧ phase error

αT‧‧‧ phase error strength

ε‧‧‧Measurement error

θ ₁ ～ θ ₄ ‧‧ ‧ pilot phase error

1 is a block diagram of a phase return device according to an embodiment of the present invention. FIG. 2 is a flowchart of a phase recovery method according to an embodiment of the present invention. Figure 3 is a schematic diagram of a plurality of pilot signals and a plurality of data signals in a plurality of received signals. Figure 4 is a block diagram of a weight unit according to an embodiment of the present invention. FIG. 5 is a block diagram of a combination unit according to an embodiment of the present invention. Figure 6 is a block diagram of an initial unit of the embodiment of the present invention. FIG. 7 is a block diagram of an update unit according to an embodiment of the present invention. Figure 8 is a block diagram of an accumulation unit in accordance with an embodiment of the present invention.

Claims (18)

A phase recovery device includes: a phase estimation module that receives a plurality of received signals, wherein the plurality of received signals includes a plurality of pilot signals and a plurality of data signals, the phase estimation module comprising: a pilot phase An estimating unit, configured to calculate a plurality of pilot phase errors according to the plurality of pilot signals; a weighting unit configured to calculate, according to at least one of the plurality of received signals, a phase corresponding to the plurality of pilot phases a plurality of weight values; and a combining unit configured to calculate a plurality of phase errors corresponding to the plurality of data signals according to the plurality of pilot phase errors and the plurality of weight values, wherein the plurality of phase errors are more a linear combination of pilot phases; and a phase compensation module for compensating for multiple phases of the plurality of received signals based on the plurality of phase errors. The phase recovery module of claim 1, wherein the weighting unit comprises: a measurement error calculation unit configured to calculate a measurement error according to the at least one received signal; and a cross correlation calculation unit for Time, calculating a plurality of cross-correlation values related to the time, wherein the plurality of cross-correlation values are related to a first phase error of the first data signal at the time of the plurality of data signals and the plurality of pilot phases a cross-correlation of errors; an autocorrelation calculation unit for calculating a plurality of autocorrelation values of the plurality of pilot phase errors according to the measurement error; and a weight calculation unit for using the plurality of cross-correlation values and The plurality of autocorrelation values, the plurality of weight values are calculated. The phase response module of claim 2, wherein the plurality of cross-correlation values form a cross-correlation vector, the plurality of autocorrelation values forming an autocorrelation matrix, the weight calculation unit according to the plurality of cross-correlation values and the The plurality of autocorrelation values, the step of calculating the plurality of weight values includes: calculating an inverse matrix of the autocorrelation matrix; and multiplying the inverse matrix by the cross correlation vector to output the plurality of weight values. The phase response module of claim 2, wherein the measuring error calculating unit calculates the measurement error according to the at least one received signal, comprising: calculating a signal to noise ratio according to the at least one received signal; The measurement error is calculated by the signal-to-noise ratio and the phase noise strength. The phase recovery module of claim 1, wherein the combining unit comprises: an initial unit, configured to calculate an initial value according to the plurality of pilot phase errors and the plurality of weight values, wherein the multiple weight values Corresponding to a first time; an updating unit, configured to calculate an updated value according to the plurality of pilot phase errors and the plurality of weight values; and an accumulating unit configured to calculate the initial value or the updated value a first phase error of the plurality of phase errors; wherein the first phase error corresponds to a second time, the second time is not earlier than the first time. The phase recovery module of claim 5, wherein the initial unit calculates an integral term between the plurality of pilot phase errors and the plurality of weight values as the initial value. The phase recovery module of claim 5, wherein the initial unit receives the plurality of pilot phase errors according to a time sequence, the initial unit comprising: a multiplier, the plurality of pilot phase errors according to the time sequence Multiplying the plurality of weight values to generate a plurality of first multiplication results; and a first accumulator for accumulating the plurality of first multiplication results to generate the initial value. The phase recovery module of claim 7, wherein the first accumulator comprises: a first register for storing a first accumulated result; and a first adder for accumulating the first The result is added to a first multiplication result of the plurality of first multiplication results to generate a second accumulation result. The phase recovery module of claim 5, wherein the updating unit comprises: a multiplying unit for multiplying the plurality of pilot phase errors by a plurality of subtraction results to generate a plurality of second multiplication results And a first subtraction result of the plurality of subtraction results is a subtraction result of a first weight value and a second weight value of the plurality of weight values; The second multiplied result is summed to produce a summed result; and an adjustment unit is used to multiply the summed result by an adjustment factor to generate the updated value. The phase recovery module of claim 5, wherein the accumulation unit comprises: a second temporary register for storing a first temporary storage content; a subtractor for subtracting the first temporary storage content Updating the value to generate a second temporary storage content; and a multiplexer for outputting the initial value or the second temporary storage content to the second temporary storage device and outputting the second temporary storage content as the first A phase error. A phase recovery method includes: receiving a plurality of received signals, wherein the plurality of received signals includes a plurality of pilot signals and a plurality of data signals; calculating a plurality of pilot phase errors according to the plurality of pilot signals; Computing at least one of the received signals, calculating a plurality of weight values corresponding to the plurality of pilot phases; calculating a plurality of the plurality of data signals corresponding to the plurality of pilot phase errors and the plurality of weight values a phase error, wherein the plurality of phase errors is a linear combination of the plurality of pilot phases; and compensating for a plurality of phases of the plurality of received signals based on the plurality of phase errors. The phase recovery method of claim 11, wherein the calculating the plurality of weight values corresponding to the plurality of pilot phases comprises: calculating a measurement error according to the at least one received signal; a plurality of cross-correlation values at the time, wherein the plurality of cross-correlation values are related to a cross-correlation of a first phase error of the first data signal at the time of the plurality of data signals with the plurality of pilot phase errors; Calculating, according to the measurement error, a plurality of autocorrelation values of the plurality of pilot phase errors, wherein the plurality of autocorrelation values are related to autocorrelation of the plurality of pilot phase errors; and according to the plurality of cross correlation values and The plurality of autocorrelation values, the plurality of weight values are calculated. The phase recovery method of claim 12, wherein the plurality of cross-correlation values form a cross-correlation vector, the plurality of autocorrelation values forming an autocorrelation matrix, according to the plurality of cross-correlation values and the plurality of autocorrelation values The step of calculating the plurality of weight values includes: calculating an inverse matrix of the autocorrelation matrix; and calculating the plurality of weight values, wherein the plurality of weight values are related to a multiplication result of the inverse matrix and the cross correlation vector. The phase recovery method of claim 11, wherein the calculating the plurality of phase errors corresponding to the plurality of data signals according to the plurality of pilot phase errors and the plurality of weight values comprises: according to the plurality of pilots Calculating an initial value, wherein the plurality of weight values correspond to a first time; calculating an updated value according to the plurality of pilot phase errors and the plurality of weight values; and according to the initial And a value of the first phase error of the plurality of phase errors; wherein the first phase error corresponds to a second time, the second time is not earlier than the first time. The phase recovery method of claim 14, wherein the calculating the initial value comprises: calculating an product term sum between the plurality of pilot phase errors and the plurality of weight values to generate the initial value. The phase recovery method of claim 14, wherein the step of calculating the initial value according to the plurality of pilot phase errors and the plurality of weight values comprises: the initial unit receiving the plurality of pilot phase errors in a time sequence; Multiplying the plurality of pilot phase errors by the plurality of weight values in accordance with the chronological order to generate a plurality of first multiplication results; and accumulating the first multiplication results to generate the initial values. The phase recovery method of claim 14, wherein the calculating the updated value according to the plurality of pilot phase errors and the plurality of weight values comprises: multiplying the plurality of pilot phase errors by a plurality of subtractions As a result, a plurality of second multiplication results are generated, wherein a first subtraction result of the plurality of subtraction results is a subtraction result of a first weight value and a second weight value of the plurality of weight values; The plurality of second multiplied results are summed to produce a summation result; and the summed result is multiplied by an adjustment factor to generate the updated value. The phase recovery method of claim 14, wherein the generating the first phase error of the plurality of phase errors according to the initial value or the updated value comprises: calculating the first phase error as the initial value plus Update the result of the value at least once.