CN104243371A - Channel estimation method and device of broadband power line communication system - Google Patents

Abstract

The present invention relates to broadband power line communication technology, in particular to a channel estimation method and device for a broadband power line communication system. The modulation method selects the number of sampling points, and according to the number of sampling points, uniformly selects the interpolation point in the pilot symbol period, determines the value of the self-similarity factor according to the value of the sampling point, uses the affine transformation to estimate the channel, and obtains the channel estimation value, and The estimated value is sent to subsequent links such as a channel equalizer in the receiver. The channel estimation device based on the method includes a sampling point number selection unit, a uniform sampling unit, a self-similar factor calculation unit and an affine transformation calculation unit. The invention realizes the channel estimation of the broadband power line communication system, has simple algorithm, small calculation amount and low bit error rate.

Description

Channel Estimation Method and Device for Broadband Power Line Communication System

technical field

The invention relates to broadband power line communication technology, in particular to a channel estimation method and device for a broadband power line communication system.

Background technique

In recent years, the medium and low voltage power line high-speed communication system (PLC) has been widely used and recognized in the smart grid, and the modulation technology is one of the key supporting technologies of the PLC system. Cross-Frequency Division Multiplexing (OFDM) has become the designated modulation technology of the current PLC system because of its good performance in combating multipath fading.

The multipath propagation in the medium and low voltage power distribution network will cause the delay extension of the signal, cause the signal to produce frequency selective fading, and at the same time seriously destroy the orthogonality between the subcarriers in the OFDM system, resulting in adjacent channel interference (ICI) between carriers. ), leading to a decrease in the performance of the communication system. Channel estimation is a key technology to reduce the influence of OFDM channel frequency selectivity and time selectivity fading.

The current OFDM system channel estimation technology is mainly divided into two categories: 1) channel estimation algorithm based on pilot signal (pilot technology); 2) blind (or semi-blind) channel estimation technology. Blind (or semi-blind) technology improves spectrum utilization to a certain extent, but the complexity of the algorithm is high, and it is not as widely used as the pilot algorithm. For slow time-varying medium and low-voltage power line channels, the pilot technology is often used, and the least square (LS) algorithm based on the training sequence is used to realize it, but the anti-noise performance of this technology is poor.

According to the existing research results, the wideband PLC-OFDM signal has self-similarity: the signal shows similarity on different time scales. The self-similarity of OFDM signals provides a powerful analysis and processing tool for channel estimation. According to the self-similarity of the broadband PLC-OFDM signal, the present invention utilizes the affine transformation summarized by the fractal theory to estimate the channel, and the calculation is simple and fast, and the precision is high.

Contents of the invention

The purpose of the present invention is to propose a method and device for channel estimation of broadband power line communication system based on self-similarity theory and fractal theory.

The method for channel estimation of a broadband power line communication system includes the following steps:

Step 1: After the received signal in the power line communication channel passes through the radio frequency receiver, it first needs to carry out routine processing of the broadband power line communication system receiver. The conventional processing includes analog-to-digital conversion, removal of the cyclic prefix of the OFDM signal, and serial-to-parallel conversion in sequence. P/S and Fast Fourier Transform (FFT);

Step 2: Select the number of sampling points according to the modulation mode of the broadband power line communication system. The selection basis is: 4QAM requires 4 points, 16QAM requires 6-8 points, and 64QAM requires 8-10 points;

Step 3: According to the number of sampling points, uniformly select interpolation points within the pilot symbol period;

Step 4: Determine the value of the self-similarity factor according to the value of the sampling point ${\mathrm{\Δy}}_0={\mathrm{the\; y}}_0^1-{\mathrm{the\; y}}_0^0,{\mathrm{\Δy}}_{\mathrm{no}}={\mathrm{the\; y}}_{\mathrm{no}}^1-{\mathrm{the\; y}}_{\mathrm{no}}^0,\mathrm{no}=\mathrm{0,1},\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;,N-1,$ Among them: N is the number of sampling points, Indicates the value of point t _n before the affine transformation (the value at t _n before the radio frequency signal enters the channel), Indicates the value of point t _n after affine transformation (the value after the radio frequency signal is output from the channel, corresponding to t _n on the time axis).

Step five, use the affine transformation to estimate the channel:

${\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; t</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right]<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}& {\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\end{array}\right]\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; t</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right]<span\; class="notranslate">\; +</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\\ {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\end{array}\right]$

${\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

${\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

${\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\frac{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

Among them, a _n , e _n , c _n and f _n are parameters used in affine transformation, and have no specific physical meaning.

Where y is the estimated value of the channel at time t.

After the channel estimation value y is obtained, the estimated value is sent to the channel equalizer in the receiver and other subsequent links.

A channel estimation device for a broadband power line communication system based on the above channel estimation method includes a sampling point number selection unit, a uniform sampling unit, a self-similarity factor calculation unit, and an affine transformation calculation unit, wherein:

The selection unit for the number of sampling points is used to complete the selection and determination of the number of sampling points under different modulation modes;

The uniform sampling unit, according to the setting of the sampling point number selection unit, uniformly selects the interpolation points in the pilot symbol period, and is used to complete the uniform sampling of the signal in the symbol period;

The self-similarity factor calculation unit receives the value of the sampling point transmitted by the uniform sampling unit, and completes the calculation of the self-similarity factor in the affine transformation;

The radial transformation calculation unit receives the value of the self-similarity factor transmitted by the self-similarity factor calculation unit, completes the affine transformation, and obtains the channel estimation value.

The beneficial effect of the present invention is that the algorithm is extremely simple to realize, and the required calculation amount is extremely small, and the calculation amount is ο(N), wherein N is the number of sampling points. The interpolation precision is high, and the relative error is about 5%. Compared with other wired communication methods (such as optical fiber communication systems), the communication bandwidth of the broadband power line communication system is narrow (about 500Mbps now), and the receiver cannot be designed too complicated, so the invented channel estimator can be compared in hardware design. It is simple, and the precision also meets actual needs, and is suitable for the needs of broadband power line communication systems. One way to measure the performance of a channel estimator is to evaluate the bit error rate of the communication system.

Description of drawings

Figure 1: Schematic diagram of the channel estimator method

Figure 2: Schematic diagram of channel estimator setup

Figure 3: BER performance of different channel estimators

Detailed ways

The present invention relates to a broadband power line communication system OFDM signal interpolation method based on self-similarity theory. The present invention will be described in detail below in conjunction with specific embodiments of broadband power line communication system PLC-OFDM channel estimation, but the content of the present invention is not limited thereby .

FIG. 1 is a schematic diagram of a channel estimator method. The signal in the power line communication channel enters the radio frequency receiver, and then undergoes routine processing by the broadband power line communication system receiver, followed by analog-to-digital conversion, removal of the cyclic prefix of the OFDM signal, serial-to-parallel conversion P/S and fast Fourier transform (FFT) ;

The first step is to select the number of sampling points: select according to the modulation method. The basis for selection is: 4QAM requires 4 points, 16QAM requires 6-8 points, and 64QAM requires 8-10 points. The commonly used modulation method of broadband power line communication system is 64QAM modulation, so the number of sampling points is selected as 8 points;

The second step of sampling point selection: according to the aforementioned number of sampling points, uniformly select sampling points within the symbol period of 40.96 microseconds;

The third step is to calculate the value of the self-similarity factor according to the number of sampling points;

The calculation formula is:

${\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Delta;y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}{{\mathrm{<span\; class="notranslate">\; \&Delta;y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0,1,2</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>$

Wherein N is the number of sampling points, where the value of N is the same as the number of sampling points determined in the first step;

n is a natural number,

${\mathrm{<span\; class="notranslate">\; \&Delta;y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>$

Indicates the value of point t _n before the affine transformation (the value at t _n before the radio frequency signal enters the channel), Indicates the value of point t _n after affine transformation (the value after the radio frequency signal is output from the channel, corresponding to t _n on the time axis)

The value of d _n is the value of the self-similarity factor;

The fourth step is to use affine transformation to estimate the channel, and the calculation formula used is as follows:

${\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right]<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}& {\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\end{array}\right]\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right]<span\; class="notranslate">\; +</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\\ {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\end{array}\right]$

${\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

${\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

${\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\frac{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}}{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

in:

a _n , e _n , c _n and f _n are the parameters used in affine transformation and have no specific physical meaning.

y is the estimated value of the channel at time t.

After the channel estimation value y is obtained, the estimated value is sent to the channel equalizer in the receiver and other subsequent links.

As shown in Figure 2, it is a schematic diagram of a channel estimator device, including a sampling point number selection unit, a uniform sampling unit, a self-similar factor calculation unit and an affine transformation calculation unit, wherein:

The selection unit for the number of sampling points is used to complete the selection and determination of the number of sampling points under different modulation modes; the uniform sampling unit selects the interpolation points evenly in the pilot symbol period according to the setting of the selection unit for the number of sampling points, and uses To complete the uniform sampling of the signal within the symbol period; the self-similarity factor calculation unit receives the value of the sampling point transmitted by the uniform sampling unit, and completes the calculation of the self-similarity factor in the affine transformation; the affine transformation calculation unit receives the self-similarity factor calculation unit The value of the transmitted self-similarity factor is affine transformed to obtain the channel estimation value.

The present invention also provides another preferred embodiment of the channel estimator. In this embodiment, the channel estimator includes: a processor, wherein the processor is configured to execute the following program units stored in the memory:

The selection unit for the number of sampling points is used to complete the selection and determination of the number of sampling points under different modulation modes; the uniform sampling unit selects the interpolation points evenly in the pilot symbol period according to the setting of the selection unit for the number of sampling points, and uses To complete the uniform sampling of the signal within the symbol period; the self-similarity factor calculation unit receives the value of the sampling point transmitted by the uniform sampling unit, and completes the calculation of the self-similarity factor in the affine transformation; the affine transformation calculation unit receives the self-similarity factor calculation unit The value of the transmitted self-similarity factor is affine transformed to obtain the channel estimation value.

Fig. 3 is a performance comparison between the channel estimator of the present invention and the channel estimator commonly used at present, it can be seen from the figure that the present invention has better channel estimation performance, and the bit error rate of the system is greatly reduced.

The invention provides a new method and a new device for channel estimation in a broadband power line communication receiver, which are used for calculating channel estimation values simply, quickly and effectively. The technical solution proposed by the implementation example of the present invention is suitable for channel estimation in substation automation communication, has low complexity of the solution, and can effectively improve the performance of the communication system.

Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be realized by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is a better embodiment . Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art can be embodied in the form of a software product, the computer software product is stored in a storage medium, and includes several instructions to make a A computer device executes the methods described in various embodiments of the present invention.

Claims (4)

1. A method for channel estimation of a broadband power line communication system, characterized in that the method comprises the following steps: Step 1: After the received signal in the power line communication channel passes through the radio frequency receiver, perform routine processing by the receiver of the broadband power line communication system; Step 2: Select the number of sampling points according to the modulation mode of the broadband power line communication system; Step 3: According to the number of sampling points, uniformly select interpolation points within the pilot symbol period; Step 4: Determine the value of the self-similarity factor d _n according to the value of the sampling point, ${\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Delta;y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}{{\mathrm{<span\; class="notranslate">\; \&Delta;y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0,1,2</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>$ ${\mathrm{<span\; class="notranslate">\; \&Delta;y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>$ ${\mathrm{<span\; class="notranslate">\; \&Delta;y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0,1</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ;</span>$ Among them: n is a natural number, N is the number of sampling points, Indicates the value at t _n before the RF signal enters the channel, that is, the value at point t _n before the affine transformation, Indicates the value at t _n after the radio frequency signal is output from the channel, that is, the value at point t _n after the affine transformation; Step five, use affine transformation to estimate the channel: ${\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; t</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right]<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}& {\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\end{array}\right]\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; t</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right]<span\; class="notranslate">\; +</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\\ {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\end{array}\right]$ ${\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$ ${\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$ ${\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\frac{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$ ${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\frac{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}}{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; ,</span>$ in: a _n , e _n , c _n and f _n are parameters used for affine transformation; y is the estimated value of the channel at time t; Step six, after obtaining the estimated channel value, send the estimated value to the channel equalizer in the receiver. 2. the channel estimation method of broadband power line communication system according to claim 1, is characterized in that, described conventional processing comprises successively analog-to-digital conversion, removes the cyclic prefix of OFDM signal, serial-to-parallel transformation P/S and fast Fourier transform transform. 3. the channel estimation method of broadband power line communication system according to claim 1, it is characterized in that, the selection method of sampling point in step 2 is specifically: the required sampling point number of 4QAM modulation mode is 4, and 16QAM modulation mode needs The number of sampling points is 6-8, and the number of sampling points required by the 64QAM modulation mode is 8-10. 4. A channel estimation device based on the broadband power line communication system of the method according to claim 1, characterized in that the device comprises, The selection unit for the number of sampling points is used to complete the selection and determination of the number of sampling points under different modulation modes; The uniform sampling unit, according to the setting of the sampling point number selection unit, uniformly selects the interpolation points in the pilot symbol period, and is used to complete the uniform sampling of the signal in the symbol period; The self-similarity factor calculation unit receives the value of the sampling point transmitted by the uniform sampling unit, and completes the calculation of the self-similarity factor in the affine transformation; The affine transformation calculation unit receives the value of the self-similarity factor transmitted by the self-similarity factor calculation unit, completes the affine transformation, and obtains the channel estimation value.