CN101257469B - A Method of Using System Information to Suppress Phase Noise in OFDM System - Google Patents

Abstract

The invention relates to a method for suppressing phase noise by using system information in an orthogonal frequency division multiplexing system, belonging to the technical field of digital information transmission. The method includes: at the transmitting end, after the input signal is scrambled and channel coded, symbol mapping is performed to generate data symbols; a frame header is obtained; system information subcarriers are inserted into the data symbols to obtain a frame body; the frame The header and frame body are multiplexed, and the signal frame is obtained after shaping filtering, digital-to-analog conversion, and radio frequency up-conversion processing, and then the signal frame is transmitted to the receiving end; at the receiving end, the signal frame is received, and the system information subcarrier in the signal frame is obtained , take several subcarriers in the middle of the system information subcarriers to estimate the phase noise, solve the LS equation to obtain the frequency domain estimation of the phase noise, and finally perform phase correction on the signal frame in the time domain to obtain the compensated signal frame, and the compensated signal frame Perform demapping and output after decoding.

Description

A Method of Using System Information to Suppress Phase Noise in OFDM System

technical field

The invention relates to the technical field of digital information transmission, in particular to a method for suppressing phase noise by using system information in an Orthogonal Frequency Division Multiplexing (OFDM) system.

Background technique

The main problem in the current digital information transmission technology (such as wireless transmission system) is how to effectively suppress the influence of phase noise on the signal during the signal transmission process. Figure 1 is a system diagram of the radio frequency front end in the wireless transmission system. At the transmitting end, the digital signal passed through the baseband modulator is output to the digital-to-analog conversion (D/A), and the signal passes through the low-pass filter (LPF), up-converter, and radio frequency filter in turn, and then is transmitted through the antenna. In a wireless propagation environment, signals are affected by various interferences and noises. At the receiving end, the signal passes through a radio frequency filter, a down converter, and a baseband filter (BBF) in sequence to obtain a baseband analog signal, which is then output to the baseband receiver after analog-to-digital conversion (A/D). The above RF front-end structure introduces RF front-end distortion problems such as carrier frequency offset, phase noise, and IQ imbalance. Compared with the other two types of interference, phase noise is more difficult to overcome due to its randomness.

Phase noise is caused by random phase changes, phase fluctuations, and frequency fluctuations caused by the oscillators at the receiving end and the transmitting end being affected by thermal noise, and the noise introduced through the external power supply and control circuit. Phase noise can be introduced at both the transmitter at the transmitter and the tuner at the receiver. Using a high-performance oscillator can reduce phase noise, but its price is also more expensive. For broadcast systems, too expensive oscillators cannot be used due to the large number of receivers. Compared with the transmitting end, the phase noise at the receiving end is generally larger. In order to ensure better receiving performance, it is mainly necessary to eliminate the phase noise at the receiving end of the user.

The methods to eliminate phase noise mainly include:

1. CPE (Common Phase Error in Phase Noise) correction technique using pilot. After demapping, scattered pilots and continuous pilots are affected by phase noise, and their subcarrier constellation points no longer fall on the real axis of the constellation diagram, and the average value of each pilot offset is the CPE estimate. The CPE elimination method can only estimate the CPE part in the phase noise, but the scattered part of the phase noise cannot be compensated.

2. Phase noise compensation technology based on DCT quadrature basis. The phase noise is regarded as a set of sine waves, and the least square method (LS) estimation value of the sine wave coefficients is given according to the pilot information of DVB-T. When this method is used to solve the LS equation, the pilot data is large , the computational complexity increases.

3. Phase noise compensation technology based on carrier recovery pilot. Use the guard band to prevent other subcarriers from interfering with the phase reference pilot, and then use a digital filter to complete the extraction of phase noise. The bandwidth of the filter determines the bandwidth of the estimated phase noise, and finally the phase noise is completed by Fourier transform (DFT). compensation. Since this method uses only one carrier recovery pilot for noise estimation, if the pilot is in deep fading under multipath conditions, the estimation performance cannot be guaranteed.

4. ICI (Inter-Carrier Interference) self-cancellation method. The ICI self-cancellation method is another non-data-assisted method to compensate the influence of phase noise without any pilot data. It does not change the symbol form, but reduces the spectrum utilization due to the introduction of a large amount of redundancy.

Contents of the invention

In order to effectively suppress phase noise in an OFDM system, the present invention proposes a method for suppressing phase noise using system information in an OFDM system, including:

Step 101: At the transmitting end, after the input signal is subjected to scrambling processing and channel coding processing, symbol mapping processing is performed to generate data symbols; a frame header is obtained; N system information subcarriers are inserted into the data symbols, where N is a positive integer; then perform inverse discrete Fourier transform on the data symbols inserted with N system information subcarriers to obtain the frame body; multiplex the frame header and frame body into a signal frame, and then pass the signal frame through shaping filtering, digital-analog After conversion and radio frequency up-conversion processing, it is transmitted to the receiving end;

Step 102: Receive the signal frame at the receiving end, obtain the frame body in the signal frame, perform a discrete Fourier transform operation on it to recover N system information subcarriers, and extract several subcarriers among the N system information subcarriers to perform phase noise estimation;

Step 103: Using the received system information subcarrier as the convolution relationship between the phase noise frequency domain response and the transmitting end inserting system information, use the least square method (LS) to obtain the phase noise frequency domain response;

Step 104: Perform discrete Fourier transform on the response of the phase noise to obtain an estimated value of the phase noise, perform phase correction on the received signal frame in the time domain to obtain a compensated signal frame, and demap the compensated signal frame , decoding processing, and then output.

In the present invention, the number N of the system information subcarriers is preferably greater than 8.

In step 102 of the present invention, it is preferable to extract (N-2Bw) subcarriers among the N system information subcarriers for phase noise estimation, where Bw is the phase noise estimation bandwidth.

In the present invention, the least squares method in step 103 adopts a weighted least squares method, or an overall least squares method.

The method in the present invention is simple in calculation, can compensate the scattered part in the phase noise, improves the spectrum utilization rate, can guarantee the performance of the estimation under the condition of multipath, thereby can track the phase transformation of the received signal in time, and suppress the phase noise effectively .

Description of drawings

Fig. 1 is a system diagram of a radio frequency front end of a wireless transmission system in the prior art;

2 is a flowchart of a method for suppressing phase noise using system information in an OFDM system according to an embodiment of the present invention;

FIG. 3 is a system diagram of a transmitting end in a multi-carrier mode in an embodiment of the present invention;

Fig. 4 is a frame header structure diagram in an embodiment of the present invention;

Fig. 5 is a schematic diagram of system information locations in an embodiment of the present invention;

FIG. 6 is a block diagram of using system information to suppress phase noise at the receiving end according to an embodiment of the present invention;

Fig. 7 is the phase noise graph obtained under different phase noise selection bandwidths under the Gaussian channel;

Fig. 8 is a symbol error rate performance curve under different phase noise selection bandwidths under a Gaussian channel;

Fig. 9 is the amplitude-frequency characteristic figure of simulation multipath channel;

Fig. 10 is a graph showing symbol error rate performance curves of the least squares method and the weighted least squares method in a simulated multipath channel.

Detailed ways

In order to make the purpose, content, and advantages of the present invention clearer, the implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

The implementation of the present invention provides a method for suppressing phase noise by using system information in an OFDM system. By using the method, the phase transformation of a received signal can be accurately and timely tracked, and the phase noise in an OFDM system can be effectively suppressed.

As shown in Figure 2, the flow chart of the method for eliminating phase noise using system information provided by the implementation of the present invention specifically includes the following steps:

Step 101: At the transmitting end, after the input signal is subjected to scrambling processing and channel coding processing, symbol mapping processing is performed to generate M data symbols, where M is a positive integer, as shown in Figure 3; to obtain the frame header, the The frame header includes three parts: a pre-guard interval, a PN sequence, and a post-guard interval, as shown in Figure 4; insert N system information subcarriers into the data symbol, where N is a positive integer, and then perform discrete Fourier inversion on it Transform to obtain the frame body; multiplex the frame header and frame body into a signal frame, and then transmit the signal frame to the receiving end after shape filtering, digital-to-analog conversion, and radio frequency up-conversion processing.

System information is information that provides necessary demodulation and decoding for each signal frame, including symbol mapping method, coding rate, interleaving mode information, frame body information mode, etc. Preferably, N>8. As shown in Figure 5, when N=36 and M=3744, 36 system information subcarriers are inserted into the mapped 3744 data symbols to obtain a sequence of N+M=3780 symbols, denoted as Y[3780] , the output sequence Y[3780] is subjected to inverse discrete Fourier transform to obtain a time-domain signal, and the time-domain signal is used as a frame body.

Step 102: Receive the signal frame at the receiving end, obtain the frame body in the signal frame, perform a discrete Fourier transform operation on it to recover N system information subcarriers, and extract several subcarriers among the N system information subcarriers for phase noise estimation.

Since the analog signal corresponding to the sampled signal is a band-limited signal, to obtain completely accurate phase noise at the receiving end, it is not only required that the analog signal corresponding to the sampled signal for DFT operation is a bandwidth smaller than Nyquist (Nyquist) The limit band-limited signal, and requires that the spectrum of the analog signal must be discrete, that is, it can only contain components that are integer multiples of the frequency of the subcarrier. In practice, although the phase noise bandwidth of the oscillator can be guaranteed within a certain range, its power spectrum is generally not discrete, but a continuous distribution. Therefore, by selecting an appropriate bandwidth Bw of the phase noise, the error of the phase noise estimation can be reduced. The larger Bw is, the larger the useful component is, but the guard bandwidth is limited, and the edge subcarriers have been interfered by data subcarriers and become unreliable; in addition, due to noise interference and unsatisfactory channel estimation, Bw The bigger it is, the more disturbed it will be. Generally, Bw selects a length of 1 to 5 subcarriers. The Bw subcarriers on both sides of the system information are used as the frequency guard band in the middle part, and the middle (N-2Bw) system information subcarriers are used as pilots for phase estimation, that is, the middle (N-2Bw) system information subcarriers are taken out for phase estimation. noise estimation.

The frame body signal before the receiver enters the DFT can be expressed as:

⁽ⁿ⁾+w(n)y(n)=(h(n)*x(n))e ^J

⁽ⁿ⁾ +w(n)

(n)表示在第n个采样点处的相位噪声，其带宽为Bw个子载波间隔。从而收端进行离散傅立叶变换(DFT)后的输出可表示为Y(k)：Among them, "*" means linear convolution,

(n) represents the phase noise at the nth sampling point, and its bandwidth is Bw subcarrier intervals. Therefore, the output after discrete Fourier transform (DFT) at the receiving end can be expressed as Y(k):

$\mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; K</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; DFT</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>$

$<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&NotEqual;</span>\mathrm{<span\; class="notranslate">\; k</span>}}{\overset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Bw</span>}}{\underset{\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Bw</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}}\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>$

⁽ⁿ⁾、w(n)的离散傅立叶变换。Where Y(k), X(k), H(k), Q(k), W(k) are y(n), x(n), h(n), e ^J

⁽ⁿ⁾ , the discrete Fourier transform of w(n).

Step 103: Using the convolution relationship between the received system information subcarrier as the phase noise frequency domain response and the transmitting end inserted system information, use the least square method (LS) to obtain the phase noise frequency domain response.

For system information T(p) (where -N/2<p≤N/2) in X(k) (wherein -1890<k≤1890), the signal after passing through the channel is V(p), and V(p )=H(p)T(p). Then there are:

VQ=Y

in:

$\mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; =</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; Bw</span>}<span\; class="notranslate">\; )</span>\\ \mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; Bw</span>}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ \mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&Center\; Dot;</span>\\ \mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Bw</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ \mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Bw</span>}<span\; class="notranslate">\; )</span>\end{array}\right)<span\; class="notranslate">\; ,</span>$

$\mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; =</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ \mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ \mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ <span\; class="notranslate">\; \&CenterDot;</span>\\ \mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ \mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>\end{array}\right)$

VQ=Y is an overdetermined equation, that is, the number of equations is more than the number of unknowns. The least squares method is used to solve the problem, and the problem is expressed as:

${\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; LS</span>}}<span\; class="notranslate">\; =</span>{\underset{\mathrm{<span\; class="notranslate">\; Q</span>}}{\mathrm{<span\; class="notranslate">\; arg</span>}\mathrm{<span\; class="notranslate">\; min</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}$

$<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; V</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; V</span>}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; Y</span>}$

In the multipath channel of wireless communication, frequency selective fading occurs, and the gains of different subcarriers are different. Due to the interference of noise, the signal-to-noise ratio of different subcarriers will be different, so the confidence of different subcarriers is also different. The weighted least square method (WLS) is used to further reduce the error. The weight of the subcarrier with a large gain is large, and the subcarrier The weight with small gain is small, and the weight matrix is defined as a diagonal matrix:

W=diag(|H(-N/2+Bw+1)|, |H(-N/2+Bw+2)|, ..., |H(N/2-Bw)|)

Then the weighted least squares solution is:

Q _WLS ＝(V ^H WV) ^-1 V ^H WY

The total least squares method is the least squares estimation using the singular value decomposition technique when V ^H V is not satisfied with the rank. Reference [V.Huffel, J.Vandewalle, The Total Least Squares Problems: Computation Aspects and Analysis, SIAM, 1991] .

Step 104: Perform discrete Fourier transform on the response estimate of the phase noise to obtain an estimated value of the phase noise, perform phase correction on the received signal frame in the time domain to obtain a compensated signal frame, and decipher the compensated signal frame Mapping, decoding processing, and output.

After estimating the Q value, inverse Fourier transform is performed to obtain q(n), 0≤n<3780, then the phase of q(n) is the estimated phase noise, and the input signal is compensated in the time domain. The compensated signal is:

r'(n)=r(n)·e ^{-J·angle(q(n))} .

The compensated signal frame r'(n) is used to replace the uncompensated signal frame r(n), thereby suppressing the influence of phase noise on the signal, and then the compensated signal frame r'(n) is decomposed Mapping, decoding and other processing, and then output.

Combining steps 102, 103, and 104, Fig. 6 shows a block diagram of eliminating phase noise at the receiving end according to an embodiment of the present invention.

In order to make the beneficial effects of the embodiments of the present invention more obvious, a computer simulation is performed on the method for eliminating phase noise based on system information proposed in the embodiments of the present invention below, and the effects of the embodiments of the present invention can be compared from the simulation data;

The main simulation parameters are shown in Table 1.

Table 1 Main simulation parameters

symbol rate 7.56M symbols/second Subcarrier Constellation Diagram 64QAM Number of OFDM subcarriers 3780 Subcarrier spacing 2KHz training sequence length 420 System information length 36

The phase noise generation method adopts the phase noise simulation method recommended by the IEEE 802.11g standard, and the steps are as follows:

(1) Generate an independent and identically distributed Gaussian random sequence;

(2) design a Butterworth low-pass filter, its 3dB bandwidth is Bw _3dB ;

(3) Filter the random sequence generated in (1) with the filter designed in (2), and the output is the required phase noise, and its variance is σ ² .

The simulation parameters are set as Bw _3dB =1 kHz, σ ² =3°.

Figure 7 shows the phase noise estimates obtained by using different estimated bandwidths at the receiving end in a Gaussian channel, and the symbol error rate performance curves obtained by using different estimated bandwidths at the receiving end are shown in Figure 8. From the figure, It can be seen that when Bw=3, the symbol error rate is the lowest, and compared with no phase noise compensation, there is about 2.5dB improvement in signal-to-noise ratio (SNR).

The multipath channel model adopts the channel model shown in Table 2. The multipath channel is a test channel proposed by the State Administration of Radio Film and Television (SARFT) in the digital TV test report. Its amplitude-frequency characteristics are as follows: Figure 9 shows. Select the phase noise bandwidth Bw = 3 subcarrier intervals, and use the least squares method and weighted least squares method respectively to obtain the symbol error rate performance curve shown in Figure 10. It can be seen from the figure that the performance of the least squares method and the weighted least squares method is close to , compared with no phase noise compensation, there is about 1.5dB SNR improvement.

Table 2 Impulse response of simulated channel

tap Delay (μs) Power(dB) 1 0 0 2 0.2 -10 3 1.9 -14 4 3.9 -18 5 8.2 -20 6 15 -20

The specific examples of the present invention have been described in detail above, but the present invention is not limited to the above examples. Within the spirit and principles of the claims of the present invention, any modifications, equivalent replacements, improvements, etc., should be included in the protection scope of the present invention.

Claims (4)

1. utilize system information to suppress the method for phase noise in an ofdm system, it is characterized in that described method comprises:

Step 101: at transmitting terminal, the signal of input is handled, after chnnel coding handles, carried out sign map and handle through scrambler, generate data symbol; Obtain frame head; N system information subcarrier inserted in the described data symbol, and wherein N is a positive integer; Then the data symbol that has inserted N system information subcarrier is carried out inverse discrete Fourier transformer inverse-discrete, obtain frame; Frame head and frame multiple connection are become signal frame, will be transmitted into receiving terminal after this signal frame process shaping filter, digital to analog conversion, the radio frequency up-conversion process then;

Step 102: at receiving terminal received signal frame, obtain the frame in the signal frame, it is carried out discrete Fourier transform operations recover N system information subcarrier, take out the middle experimental process carrier wave of N system information subcarrier and carry out the phase noise estimation;

Step 103: utilize the system information subcarrier that receives to be the convolution relation of phase noise frequency domain response, use least square method to try to achieve the frequency domain response of phase noise with the insertion system information of making a start;

Step 104: the frequency domain response to described phase noise carries out discrete Fourier transform (DFT), tries to achieve the estimated value of phase noise, time domain to received signal frame carry out phasing, the signal frame that is compensated, signal frame to described compensation is separated mapping, and decoding is handled, then output.

2. utilize system information to suppress the method for phase noise in the ofdm system according to claim 1, it is characterized in that the number N of described system information subcarrier is greater than 8.

3. utilize system information to suppress the method for phase noise in the ofdm system according to claim 1, it is characterized in that, in described step 102, (N-2Bw) individual subcarrier carries out the phase noise estimation in the middle of taking out N system information subcarrier, wherein, Bw is the phase noise estimated bandwidth.

4. utilize system information to suppress the method for phase noise in the ofdm system according to claim 1, it is characterized in that least square method comprises weighted least-squares method described in the described step 103, or total least square method.

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