CN104410508A - Power line network topology sensing method and device based on power line communication - Google Patents

Abstract

The invention provides a power line network topology sensing method based on power line communication. The method comprises the following steps: S1, under the coordination of a main node, transmitting a signal frame m from a node A of a power line network to a node B, which receives a signal frame m'; S2, acquiring channel frequency response estimation Hest between the node A and the node B through channel estimation; S3, calculating an estimated value t of the arrival time of the signal frame m from the node A to the node B; S4, calculating the distance between the node A and the node B; S5, performing the steps S1 to S4 on any two nodes in the power line network to obtain distance information between any two nodes; and S6, acquiring the topological structure of the power line network according to a tree estimation method. The method provided by the invention has the advantages of high sensing accuracy and low complexity.

Description

Based on power line network topology perception method and the device of power line communication

Technical field

The present invention relates to communication technical field, be specifically related to a kind of power line network topology perception method based on power line communication and device.

Background technology

The full name of power line communication (Power Line Communication is called for short PLC) technology is power-line carrier communication, and it is that medium transmits data with power line.Convert information is on the electric current that is modulated in power line of high-frequency signal at transmitting terminal by PLC technology, signal extraction is out sent to the enterprising row relax of computer to realize information transmission with this at receiving terminal by demodulation.

In recent years, along with rise and the development of electronic telecommunication technology, the application of power line communication technology in electrical network is also more and more extensive, organically combines gradually with electric power networks, become the key technology of electric power networks, this greatly facilitates automation and the informationization of electric power networks.A novel intelligent grid is arisen spontaneously under the leading of these technology, intelligent grid passes through the transmission between electric energy and power supply, distribution, control and management, not only change the mode of electric power development, also improve the intelligent level of electrical network, be the important selection of merging flow of power, information flow and Business Stream simultaneously.

Among the development of intelligent grid, in the urgent need to knowing power line network topological model:

1, the Geographic routing of PLC often needs to use relevant positional information, therefore needs power line network topological model.

2, can be inferred by range measurement and neighbours after obtaining powerline networks topological structure and carry out online monitoring and diagnosis thus the operation of intelligent grid is provided support.

But at present, very not enough to the topological structure cognition of power line network, low-pressure field sometimes even Utilities Electric Co. also do not know, in power distribution network, power line network topology information is lacked very much, and the topological structure cognitive approach of existing power line network, not only perceived accuracy is low but also complexity is high, is not suitable for practical application.

Summary of the invention

For defect of the prior art, the invention provides a kind of power line network topology perception method based on power line communication, with solve at present to the topological structure of power line network cognitive not enough or to the topological structure perceived accuracy of power line network the low and problem that complexity is high.

First aspect, the invention provides a kind of power line network topology perception method based on power line communication, described method comprises:

S1., under the coordination of host node, the node A of power line network sends signal frame m to Node B, and described Node-B receiver is to signal frame m ';

S2. according to described signal frame m and described signal frame m ', the channel frequency response obtained between described node A and described Node B by channel estimating estimates H _est;

S3. H is estimated according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used;

S4. according to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B;

S5. step S1 to S4 is all performed to two nodes any in described power line network, obtain the range information between any two nodes, the range information between described any two nodes is sent to the host node in power line network;

S6. described host node is according to the range information between described any two nodes, utilizes tree method of estimation to obtain the topological structure of described power line network.

Preferably, in step sl, described host node communicates between coordinator node for being responsible for, and adds up the Centroid of the distance between any two nodes.

Preferably, in described step S1, described signal frame m comprises frame head and frame, and described frame head comprises two sections of identical training sequences, and length is 2N _f; Described frame comprises orthogonal frequency division multiplex OFDM data block, and length is N, and described training sequence is the inverse discrete Fourier transform of frequency domain pseudo random sequence, wherein N _fbe positive integer with N.

Preferably, according to described signal frame m and described signal frame m ' in described step S2, estimate to comprise by the channel estimating channel frequency response obtained between described node A and described Node B:

If the second segment training sequence of signal frame m is the second segment training sequence of signal frame m ' is ${\left\{c_1\left(k\right)\right\}}_{k=0}^{N_f-1},$

Described c ₀(k) and c ₁k () has following relation:

$c_1\left(k\right)=c_0\left(k\right)\⊗h\left(k\right)$

The channel frequency response adopting Fourier transform domain phase division to obtain between described node A and described Node B estimates H _est:

$H_{\mathrm{est}}\left(k\right)=\frac{\mathrm{FFT}\left[c_1\left(k\right)\right]}{\mathrm{FFT}\left[c_0\left(k\right)\right]}$

Wherein, h (k) is that channel time domain impact is corresponding, N _ffor the length of second segment training sequence, the value of k is [0, N _f-1].

Preferably, H is estimated according to the channel frequency response between described node A and described Node B in described step S3 _est, calculate described signal frame m and comprise from described node A to the estimated value t of described Node B time of advent used:

If $x\left(t\right)={[H_t,H_{t+1},......,H_{N_f-l+t-1}]}^T,$ Structural matrix:

X ₀＝[x _l-1,x _l-2,......,x ₀]

X ₁＝[x _l,x _l-1,......,x ₁]

If V ₀and U ₀x respectively ₀left and right singular vector matrix, A is X ₀the diagonal matrix of singular value composition, then pass through formula calculate V ₀, U ₀and A, wherein u ₀transpose conjugate matrix; A ^-1it is the inverse matrix of A;

According to described matrix V ₀, U ₀and A, compute matrix characteristic value z0 _s, s value is 1,2 ..., n ₁, n ₁value be matrix the number of characteristic value;

According to z0 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{0}_1\right\}}{2\mathrm{\π\Δf}}$

Wherein, z0 ₁for matrix characteristic value z0 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

Preferably, H is estimated according to the channel frequency response between described node A and described Node B in described step S3 _est, calculate described signal frame m and comprise from described node A to the estimated value t of described Node B time of advent used:

Definition $x\left(t\right)={[H_t,H_{t+1},......,H_{N_f-l+t-1}]}^T,$

Structural matrix:

X ₀＝[x _l-1,x _l-2,......,x ₀]

X ₁＝[x _l,x _l-1,......,x ₁]

According to matrix X ₀and X ₁compute matrix characteristic value z1 _s, s value is 1,2 ..., n ₂, n ₂value be matrix the number of characteristic value;

According to z1 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{1}_1\right\}}{2\mathrm{\π\Δf}}$

Wherein, z1 ₁for matrix characteristic value z1 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

Preferably, H is estimated according to the channel frequency response between described node A and described Node B in described step S3 _est, calculate described signal frame m and comprise from described node A to the estimated value t of described Node B time of advent used:

The channel frequency response between node A and described Node B is utilized to estimate H _estgenerate a M × (N _f-M) matrix H ', wherein M<N _f;

$H^{\&prime;}=\left[\begin{array}{cccc}{H}_0& H_1& ...& H_{N_f-M-1}\\ H_1& H_2& ...& H_{N_f-M}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ H_{M-1}& H_M& ...& H_{N_f-1}\end{array}\right]$

By singular value decomposition H '=USV ^hcompute matrix U, wherein, U and V is the left and right singular vector matrix of H ' respectively, and S is the inverse matrix of the diagonal matrix of H ' singular value composition, V ^hfor the transpose conjugate matrix of matrix V;

According to matrix U compute matrix characteristic value z2 _s, s value is 1,2 ..., n ₃, n ₃value be matrix the number of characteristic value;

Wherein, represent matrix u ^p pseudoinverse, the operation that before deleting matrix U, p is capable, u ^p it is the operation that after deleting matrix U, p is capable;

According to z2 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{2}_1\right\}}{2\mathrm{p\&pi;\&Delta;f}}$

Wherein, p is positive integer, z2 ₁for matrix characteristic value z2 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

Preferably, in described step S6, host node is according to the range information between described any two nodes, and the topological structure utilizing tree method of estimation to obtain described power line network comprises:

Host node, according to the range information between described any two nodes, utilizes the tree method of estimation of dynamic reconstruction to obtain the topological structure of described power line network:

(1) preset a root node, preset the leaf node set that comprises two leaf nodes, in described leaf node set, also store the distance of leaf node relative to described root node;

Preset an out-tree node set and the set of out-tree limit, other nodes removing described root node and two described leaf nodes are formed a node set to be added in power line network;

(2) one by one using the node in described node set to be added as destination node, and described destination node to be proceeded as follows:

A. the intersection point that leaf node in described leaf node set and described destination node extend to root node is determined;

Leaf node in leaf node set described in the Distance geometry of b. more described intersection point and described root node, relative to the distance of described root node, judges whether the father node of described destination node is root node or leaf node;

If c. determine, the father node of described destination node is root node or leaf node, then described destination node is added in described leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, add out-tree node set to by destination node, the limit that the father node of destination node and destination node forms is added to during out-tree limit gathers;

If d. determine, the father node of described destination node is not root node or leaf node, be then judged as one of following three kinds of situations:

D1. destination node non-leaf nodes;

D2. destination node is leaf node, and its father node is the known node of non-root node;

D3. destination node is leaf node, and the non-known node of its father node.

If e. described intersection point overlaps with destination node, then judge destination node non-leaf nodes, upgrade out-tree node set and the set of out-tree limit, add out-tree node set to by destination node; Add two limits that the child node of the father node of destination node and destination node, destination node and destination node forms to out-tree limit to gather, from the set of out-tree limit, delete the limit of the child node composition of destination node father node and destination node;

If f. described intersection point is known node, then judge that destination node is leaf node, and its father node is the known node of non-root node, described destination node is added in leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, add out-tree node set to by destination node, the limit of the father node of destination node and destination node composition is added in the set of out-tree limit;

If g. described intersection point is unknown node, then judge that destination node is leaf node, and the non-known node of its father node, described destination node is added in leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, out-tree node set is added to by destination node and described intersection point, add the limit of the child node of described intersection point and the father node of described intersection point, described intersection point composition the set of to out-tree limit, from the set of out-tree limit, delete the limit of the father node of described intersection point and the child node composition of described intersection point;

(3) obtain the tree structure rebuild after execution of step (2), namely obtain the topological structure of described power line network.

Preferably, in described step S6, host node is according to the range information between described any two nodes, and the topological structure utilizing tree method of estimation to obtain described power line network comprises:

Host node is according to the range information between described any two nodes, and the tree method of estimation utilizing root to adjoin obtains the topological structure of described power line network:

(1) preset a root node, preset a leaf node set, described leaf node set comprises all nodes except described root node; Preset an out-tree node set and the set of out-tree limit;

(2) two leaf nodes are determined according to mode below:

If root node is r, the distance between any two leaf node i and j is q _ij, for described two leaf node i and j, calculate the distance q of i and j and root node r respectively _irand q _jr, get and make formula (q _ir+ q _jr-q _ijleaf node i and j of maximum is got in)/2;

(3) father node of described leaf node i and j of determining step (2), upgrade out-tree node set and the set of out-tree limit, be stored in out-tree node set by leaf node i and j, the limit that the father node of leaf node i, j and described leaf node i and j forms is stored in during out-tree limit gathers, described father node is increased in described leaf node set simultaneously, deletes leaf node i and j in described leaf node set;

(4) repeated execution of steps (2) ~ (3), until only remain next leaf node in described leaf node set, thus obtain the tree structure of reconstruction, namely obtain the topological structure of described power line network.

Second aspect, the present invention also provides a kind of power line network topology ambiguity device based on power line communication, and described device comprises:

Signal transmitting module, under the coordination of host node, sends signal frame m from the node A of power line network to Node B;

Signal receiving module, for the Node-B receiver signal frame m ' from power line network;

Channel frequency response estimation module, for according to described signal frame m and described signal frame m ', obtains the channel frequency response estimation H between described node A and described Node B by channel estimating _est;

Euclidean distance between node pair estimation module, for estimating H according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used; According to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B;

Topological structure estimation module, for according to the range information between any two nodes of described euclidean distance between node pair estimation module transmission, utilizes tree method of estimation to obtain the topological structure of described power line network.

As shown from the above technical solution, power line network topology perception method based on power line communication of the present invention, by the communication between power line node, complete the perception of power line topological structure, solve at present to the topological structure of power line network cognitive not enough or cannot be cognitive problem, method of the present invention has the advantage that perceived accuracy is high and complexity is low.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

Fig. 1 is the flow chart of the power line network topology perception method based on power line communication that the embodiment of the present invention one provides;

Fig. 2 is the frequency response estimated result schematic diagram of a certain certain power line channel that the embodiment of the present invention two provides;

Fig. 3 is the efficiency comparison figure of two kinds of tree methods of estimation that the embodiment of the present invention three provides;

Fig. 4 is the structural representation of the power line network topology ambiguity device based on power line communication that the embodiment of the present invention four provides.

Embodiment

For making the object of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, clear, complete description is carried out to the technical scheme in the embodiment of the present invention, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.

Embodiment one

Fig. 1 shows the flow chart of the power line network topology perception method based on power line communication that the embodiment of the present invention one provides, and as shown in Figure 1, the power line network topology perception method based on power line communication of the present embodiment is as described below.

Step 101: under the coordination of host node, the node A of power line network sends signal frame m to Node B, and described Node-B receiver is to signal frame m '.

Step 102: according to described signal frame m and described signal frame m ', the channel frequency response obtained between described node A and described Node B by channel estimating estimates H _est.

Step 103: estimate H according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used.

Step 104: according to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B.

Step 105: step 101 is all performed to 104 to two nodes any in described power line network, obtains the range information between any two nodes, the range information between described any two nodes is sent to the host node in power line network.

Step 106: described host node, according to the range information between described any two nodes, utilizes tree method of estimation to obtain the topological structure of described power line network.

Thus, the power line network topology perception method based on power line communication of the present embodiment, by the communication between power line node, complete the perception of power line topological structure, solve at present to the topological structure of power line network cognitive not enough or cannot be cognitive problem, the method described in the present embodiment has the advantage that perceived accuracy is high and complexity is low.

Embodiment two

The present embodiment two is mainly for the perception of the power line communication network topological structure of multinode.For the perception of the more power line communication network topological structure of node, the tree method of estimation of dynamic reconstruction shows good characteristic, the present embodiment, for 300 nodes, describes the process of the power line network topology perception method based on power line communication in detail.

Step 201: under the coordination of host node, the node A of power line network sends signal frame m to Node B, and described Node-B receiver is to signal frame m '.

In this step, described host node is the Centroid of the distance be responsible between any two nodes of statistics.Described signal frame m comprises frame head and frame, and wherein, described frame head comprises two sections of identical training sequences, and length is 2N _f; Described frame comprises orthogonal frequency division multiplex OFDM data block, and length is N, and described training sequence is the inverse discrete Fourier transform of frequency domain pseudo random sequence, wherein N _fbe positive integer with N.The present embodiment N _fvalue 255, N value 3780.

Step 202: according to described signal frame m and described signal frame m ', the channel frequency response obtained between described node A and described Node B by channel estimating estimates H _est.

In this step, if the second segment training sequence of signal frame m is the second segment training sequence of signal frame m ' is

Described c ₀(k) and c ₁k () has following relation:

$c_1\left(k\right)=c_0\left(k\right)\&CircleTimes;h\left(k\right)$

The channel frequency response adopting Fourier transform domain phase division to obtain between described node A and described Node B estimates H _est:

$H_{\mathrm{est}}\left(k\right)=\frac{\mathrm{FFT}\left[c_1\left(k\right)\right]}{\mathrm{FFT}\left[c_0\left(k\right)\right]}$

Wherein, h (k) is that channel time domain impact is corresponding, N _ffor the length of second segment training sequence, the value of k is [0, N _f-1].Fig. 2 shows the frequency response estimated result schematic diagram of a certain certain power line channel.

Step 203: estimate H according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used.

In this step, calculate described signal frame m to comprise from described node A to the estimated value t of described Node B time of advent used:

If $x\left(t\right)={[H_t,H_{t+1},......,H_{N_f-l+t-1}]}^T,$ Structural matrix:

X ₀＝[x _l-1,x _l-2,......,x ₀]

X ₁＝[x _l,x _l-1,......,x ₁]

If V ₀and U ₀x respectively ₀left and right singular vector matrix, A is X ₀the diagonal matrix of singular value composition, then pass through formula calculate V ₀, U ₀and A, wherein u ₀transpose conjugate matrix; A ^-1it is the inverse matrix of A;

According to described matrix V ₀, U ₀and A, compute matrix characteristic value z0 _s, s value is 1,2 ..., n ₁, n ₁value be matrix the number of characteristic value;

According to z0 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{0}_1\right\}}{2\mathrm{\&pi;\&Delta;f}}$

Wherein, z0 ₁for matrix characteristic value z0 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

Above-mentioned described method just calculates a kind of mode of the estimated value t of the time of advent, certainly can also calculate in the following method:

Definition $x\left(t\right)={[H_t,H_{t+1},......,H_{N_f-l+t-1}]}^T,$

Structural matrix:

X ₀＝[x _l-1,x _l-2,......,x ₀]

X ₁＝[x _l,x _l-1,......,x ₁]

According to matrix X ₀and X ₁compute matrix characteristic value z1 _s, s value is 1,2 ..., n ₂, n ₂value be matrix the number of characteristic value;

According to z1 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{1}_1\right\}}{2\mathrm{\&pi;\&Delta;f}}$

Wherein, z1 ₁for matrix characteristic value z1 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

In addition, can also in another way to the calculating of the estimated value t of the time of advent:

The channel frequency response between node A and described Node B is utilized to estimate H _estgenerate a M × (N _f-M) matrix H ', wherein M<N _f;

$H^{\&prime;}=\left[\begin{array}{cccc}{H}_0& H_1& ...& H_{N_f-M-1}\\ H_1& H_2& ...& H_{N_f-M}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ H_{M-1}& H_M& ...& H_{N_f-1}\end{array}\right]$

By singular value decomposition H '=USV ^hcompute matrix U, wherein, U and V is the left and right singular vector matrix of H ' respectively, and S is the inverse matrix of the diagonal matrix of H ' singular value composition, V ^hfor the transpose conjugate matrix of matrix V;

According to matrix U compute matrix characteristic value z2 _s, s value is 1,2 ..., n ₃, n ₃value be matrix the number of characteristic value;

Wherein, represent matrix u ^p pseudoinverse, the operation that before deleting matrix U, p is capable, u ^p it is the operation that after deleting matrix U, p is capable;

According to z2 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{2}_1\right\}}{2\mathrm{p\&pi;\&Delta;f}}$

Wherein, p is positive integer, z2 ₁for matrix characteristic value z2 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

Here, the value of p is generally no more than 10% of matrix U line number, so both fully can retain the information in matrix, also can obtain higher accuracy.The value of p=5, p depends on the length (both become positive correlation) of training sequence herein.

Step 204: according to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B.

In this step, utilize the signal velocity in power line, distance between described node A and described Node B can be calculated from the t time of advent of two nodes.

Step 205: step 101 is all performed to 104 to two nodes any in described power line network, obtains the range information between any two nodes, the range information between described any two nodes is sent to the host node in power line network.

In this step, described host node is the Centroid of the distance be responsible between any two nodes of statistics.

Step 206: described host node, according to the range information between described any two nodes, utilizes tree method of estimation to obtain the topological structure of described power line network.

In this step, the topological structure utilizing the tree method of estimation of dynamic reconstruction to obtain described power line network comprises:

(1) preset a root node, preset the leaf node set that comprises two leaf nodes, in described leaf node set, also store the distance of leaf node relative to described root node;

Preset an out-tree node set and the set of out-tree limit, other nodes removing described root node and two described leaf nodes are formed a node set to be added in power line network;

(2) one by one using the node in described node set to be added as destination node, and described destination node to be proceeded as follows:

A. the intersection point that leaf node in described leaf node set and described destination node extend to root node is determined;

Leaf node in leaf node set described in the Distance geometry of b. more described intersection point and described root node, relative to the distance of described root node, judges whether the father node of described destination node is root node or leaf node;

If c. determine, the father node of described destination node is root node or leaf node, then described destination node is added in described leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, add out-tree node set to by destination node, the limit that the father node of destination node and destination node forms is added to during out-tree limit gathers;

If d. determine, the father node of described destination node is not root node or leaf node, be then judged as one of following three kinds of situations:

D1. destination node non-leaf nodes;

D2. destination node is leaf node, and its father node is the known node of non-root node;

D3. destination node is leaf node, and the non-known node of its father node.

If e. described intersection point overlaps with destination node, then judge destination node non-leaf nodes, upgrade out-tree node set and the set of out-tree limit, add out-tree node set to by destination node; Add two limits that the child node of the father node of destination node and destination node, destination node and destination node forms to out-tree limit to gather, from the set of out-tree limit, delete the limit of the child node composition of destination node father node and destination node;

If f. described intersection point is known node, then judge that destination node is leaf node, and its father node is the known node of non-root node, described destination node is added in leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, add out-tree node set to by destination node, the limit of the father node of destination node and destination node composition is added in the set of out-tree limit;

If g. described intersection point is unknown node, then judge that destination node is leaf node, and the non-known node of its father node, described destination node is added in leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, out-tree node set is added to by destination node and described intersection point, add the limit of the child node of described intersection point and the father node of described intersection point, described intersection point composition the set of to out-tree limit, from the set of out-tree limit, delete the limit of the father node of described intersection point and the child node composition of described intersection point;

(3) obtain the tree structure rebuild after execution of step (2), namely obtain the topological structure of described power line network.

Embodiment three

The present embodiment three is mainly for the perception of the power line communication network topological structure of few node.For the perception of the less power line communication network topological structure of node, the adjacent tree method of estimation of root shows good characteristic.The present embodiment, for 50 nodes, describes the process of the power line network topology perception method based on power line communication in detail.

Step 301: under the coordination of host node, the node A of power line network sends signal frame m to Node B, and described Node-B receiver is to signal frame m '.

In this step, described signal frame m comprises frame head and frame, and wherein, described frame head comprises two sections of identical training sequences, and length is 2N _f; Described frame comprises orthogonal frequency division multiplex OFDM data block, and length is N, and described training sequence is the inverse discrete Fourier transform of frequency domain pseudo random sequence, wherein N _fbe positive integer with N.The present embodiment N _fvalue 511, N value 4096.

Step 302: according to described signal frame m and described signal frame m ', the channel frequency response obtained between described node A and described Node B by channel estimating estimates H _est.

In this step, if the second segment training sequence of signal frame m is the second segment training sequence of signal frame m ' is

Described c ₀(k) and c ₁k () has following relation:

$c_1\left(k\right)=c_0\left(k\right)\&CircleTimes;h\left(k\right)$

The channel frequency response adopting Fourier transform domain phase division to obtain between described node A and described Node B estimates H _est:

$H_{\mathrm{est}}\left(k\right)=\frac{\mathrm{FFT}\left[c_1\left(k\right)\right]}{\mathrm{FFT}\left[c_0\left(k\right)\right]}$

Wherein, h (k) is that channel time domain impact is corresponding, N _ffor the length of second segment training sequence, the value of k is [0, N _f-1].Fig. 2 shows the frequency response estimated result schematic diagram of a certain certain power line channel.

Step 303: estimate H according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used.

In this step, calculate described signal frame m and can adopt the first two mode as described in embodiment two from described node A to the estimated value t of described Node B time of advent used, also can adopt the third mode as described in embodiment two, the present embodiment adopts the third mode as described in embodiment two:

The channel frequency response between node A and described Node B is utilized to estimate H _estgenerate a M × (N _f-M) matrix H ', wherein M<N _f;

$H^{\&prime;}=\left[\begin{array}{cccc}{H}_0& H_1& ...& H_{N_f-M-1}\\ H_1& H_2& ...& H_{N_f-M}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ H_{M-1}& H_M& ...& H_{N_f-1}\end{array}\right]$

By singular value decomposition H '=USV ^hcompute matrix U, wherein, U and V is the left and right singular vector matrix of H ' respectively, and S is the inverse matrix of the diagonal matrix of H ' singular value composition, V ^hfor the transpose conjugate matrix of matrix V;

According to matrix U compute matrix characteristic value z2 _s, s value is 1,2 ..., n ₃, n ₃value be matrix the number of characteristic value;

Wherein, represent matrix u ^p pseudoinverse, the operation that before deleting matrix U, p is capable, u ^p it is the operation that after deleting matrix U, p is capable;

According to z2 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{2}_1\right\}}{2\mathrm{p\&pi;\&Delta;f}}$

Wherein, p is positive integer, z2 ₁for matrix characteristic value z2 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

Due to the N of this enforcement _fvalue 511, herein p value 10 (value of p depends on the length of training sequence, and both become positive correlation).

Step 304: according to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B.

In this step, utilize the signal velocity in power line, distance between described node A and described Node B can be calculated from the t time of advent of two nodes.

Step 305: step 301 is all performed to 304 to two nodes any in described power line network, obtains the range information between any two nodes, the range information between described any two nodes is sent to the host node in power line network.

In this step, described host node is the Centroid of the distance be responsible between any two nodes of statistics.

Step 306: described host node, according to the range information between described any two nodes, utilizes tree method of estimation to obtain the topological structure of described power line network.

In this step, the topological structure that the tree method of estimation utilizing root to adjoin obtains described power line network comprises:

(1) preset a root node, preset a leaf node set, described leaf node set comprises all nodes except described root node; Preset an out-tree node set and the set of out-tree limit;

(2) two leaf nodes are determined according to mode below:

If root node is r, the distance between any two leaf node i and j is q _ij, for described two leaf node i and j, calculate the distance q of i and j and root node r respectively _irand q _jr, get and make formula (q _ir+ q _jr-q _ijleaf node i and j of maximum is got in)/2;

(3) father node of described leaf node i and j of determining step (2), upgrade out-tree node set and the set of out-tree limit, be stored in out-tree node set by leaf node i and j, the limit that the father node of leaf node i, j and described leaf node i and j forms is stored in during out-tree limit gathers, described father node is increased in described leaf node set simultaneously, deletes leaf node i and j in described leaf node set;

(4) repeated execution of steps (2) ~ (3), until only remain next leaf node in described leaf node set, thus obtain the tree structure of reconstruction, namely obtain the topological structure of described power line network.

The present embodiment three is relative to embodiment two, its difference is to utilize different tree methods of estimation to obtain the topological structure of described power line network, for the power line network that nodes is more, relatively be applicable to adopt dynamic reconstruction method, for the power line network that nodes is less, compare and be applicable to adopt root adjacent method.Wherein, the efficiency comparison of dynamic reconstruction method and root adjacent method as shown in Figure 3.

Embodiment four

Fig. 4 shows the structural representation of the power line network topology ambiguity device based on power line communication that the present embodiment four provides, and as shown in Figure 4, the described power line network topology ambiguity device based on power line communication comprises:

Signal transmitting module 41, under the coordination of host node, sends signal frame m from the node A of power line network to Node B;

Signal receiving module 42, for the Node-B receiver signal frame m ' from power line network;

Channel frequency response estimation module 43, for according to described signal frame m and described signal frame m ', obtains the channel frequency response estimation H between described node A and described Node B by channel estimating _est;

Euclidean distance between node pair estimation module 44, for estimating H according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used; According to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B;

Topological structure estimation module 45, for according to the range information between any two nodes of described euclidean distance between node pair estimation module 44 transmission, utilizes tree method of estimation to obtain the topological structure of described power line network.

The power line network topology ambiguity device based on power line communication described in the present embodiment, may be used for the technical scheme performing embodiment of the method shown in Fig. 1, it realizes principle and technique effect is similar, repeats no more herein.

Above embodiment only for illustration of technical scheme of the present invention, is not intended to limit; Although with reference to previous embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein portion of techniques feature; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.

Claims (10)

1. based on a power line network topology perception method for power line communication, it is characterized in that, described method comprises:

S1., under the coordination of host node, the node A of power line network sends signal frame m to Node B, and described Node-B receiver is to signal frame m ';

S2. according to described signal frame m and described signal frame m ', the channel frequency response obtained between described node A and described Node B by channel estimating estimates H _est;

S3. H is estimated according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used;

S4. according to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B;

S5. step S1 to S4 is all performed to two nodes any in described power line network, obtain the range information between any two nodes, the range information between described any two nodes is sent to the host node in power line network;

S6. described host node is according to the range information between described any two nodes, utilizes tree method of estimation to obtain the topological structure of described power line network.

2. method according to claim 1, is characterized in that, in step sl, described host node communicates between coordinator node for being responsible for, and adds up the Centroid of the distance between any two nodes.

3. method according to claim 1, is characterized in that, in described step S1, described signal frame m comprises frame head and frame, and described frame head comprises two sections of identical training sequences, and length is 2N _f; Described frame comprises orthogonal frequency division multiplex OFDM data block, and length is N, and described training sequence is the inverse discrete Fourier transform of frequency domain pseudo random sequence, wherein N _fbe positive integer with N.

4. method according to claim 3, is characterized in that, according to described signal frame m and described signal frame m ' in described step S2, estimates to comprise by the channel estimating channel frequency response obtained between described node A and described Node B:

If the second segment training sequence of signal frame m is the second segment training sequence of signal frame m ' is ${\left\{c_1\left(k\right)\right\}}_{k=0}^{N_f-1},$

Described c ₀(k) and c ₁k () has following relation:

$c_1\left(k\right)=c_0\left(k\right)\&CircleTimes;h\left(k\right)$

The channel frequency response adopting Fourier transform domain phase division to obtain between described node A and described Node B estimates H _est:

$H_{\mathrm{est}}\left(k\right)=\frac{\mathrm{FFT}\left[c_1\left(k\right)\right]}{\mathrm{FFT}\left[c_0\left(k\right)\right]}$

Wherein, h (k) is that channel time domain impact is corresponding, N _ffor the length of second segment training sequence, the value of k is [0, N _f-1].

5. method according to claim 4, is characterized in that, estimates H in described step S3 according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m and comprise from described node A to the estimated value t of described Node B time of advent used:

If $x\left(t\right)={[H_t,H_{t+1},......,H_{N_f-l+t-1}]}^T,$ Structural matrix:

X ₀＝[x _l-1,x _l-2,......,x ₀]

X ₁＝[x _l,x _l-1,......,x ₁]

If V ₀and U ₀x respectively ₀left and right singular vector matrix, A is X ₀the diagonal matrix of singular value composition, then pass through formula calculate V ₀, U ₀and A, wherein u ₀transpose conjugate matrix; A ^-1it is the inverse matrix of A;

According to described matrix V ₀, U ₀and A, compute matrix characteristic value z0 _s, s value is 1,2 ..., n ₁, n ₁value be matrix the number of characteristic value;

According to z0 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{0}_1\right\}}{2\mathrm{\&pi;\&Delta;f}}$

Wherein, z0 ₁for matrix characteristic value z0 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

6. method according to claim 4, is characterized in that, estimates H in described step S3 according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m and comprise from described node A to the estimated value t of described Node B time of advent used:

Definition $x\left(t\right)={[H_t,H_{t+1},......,H_{N_f-l+t-1}]}^T,$

Structural matrix:

X ₀＝[x _l-1,x _l-2,......,x ₀]

X ₁＝[x _l,x _l-1,......,x ₁]

According to matrix X ₀and X ₁compute matrix characteristic value z1 _s, s value is 1,2 ..., n ₂, n ₂value be matrix the number of characteristic value;

According to z1 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{1}_1\right\}}{2\mathrm{\&pi;\&Delta;f}}$

Wherein, z1 ₁for matrix characteristic value z1 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

7. method according to claim 4, is characterized in that, estimates H in described step S3 according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m and comprise from described node A to the estimated value t of described Node B time of advent used:

The channel frequency response between node A and described Node B is utilized to estimate H _estgenerate a M × (N _f-M) matrix H ', wherein M<N _f;

$H^{\&prime;}=\left[\begin{array}{cccc}{H}_0& H_1& ...& H_{N_f-M-1}\\ H_1& H_2& ...& H_{N_f-M}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ H_{M-1}& H_M& ...& H_{N_f-1}\end{array}\right]$

By singular value decomposition H '=USV ^hcompute matrix U, wherein, U and V is the left and right singular vector matrix of H ' respectively, and S is the inverse matrix of the diagonal matrix of H ' singular value composition, V ^hfor the transpose conjugate matrix of matrix V;

According to matrix U compute matrix characteristic value z2 _s, s value is 1,2 ..., n ₃, n ₃value be matrix the number of characteristic value;

Wherein, represent matrix u ^p pseudoinverse, the operation that before deleting matrix U, p is capable, u ^p it is the operation that after deleting matrix U, p is capable;

According to z2 _sthe estimated value t calculated from described node A to described Node B time of advent used is:

$t=\frac{\arg \left\{z{2}_1\right\}}{2\mathrm{p\&pi;\&Delta;f}}$

Wherein, p is positive integer, z2 ₁for matrix characteristic value z2 _sin first characteristic value, Δ f is the subcarrier spacing of body section OFDM.

8. method according to claim 1, is characterized in that, in described step S6, host node is according to the range information between described any two nodes, and the topological structure utilizing tree method of estimation to obtain described power line network comprises:

Host node, according to the range information between described any two nodes, utilizes the tree method of estimation of dynamic reconstruction to obtain the topological structure of described power line network:

(1) preset a root node, preset the leaf node set that comprises two leaf nodes, in described leaf node set, also store the distance of leaf node relative to described root node;

Preset an out-tree node set and the set of out-tree limit, other nodes removing described root node and two described leaf nodes are formed a node set to be added in power line network;

(2) one by one using the node in described node set to be added as destination node, and described destination node to be proceeded as follows:

A. the intersection point that leaf node in described leaf node set and described destination node extend to root node is determined;

Leaf node in leaf node set described in the Distance geometry of b. more described intersection point and described root node, relative to the distance of described root node, judges whether the father node of described destination node is root node or leaf node;

If c. determine, the father node of described destination node is root node or leaf node, then described destination node is added in described leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, add out-tree node set to by destination node, the limit that the father node of destination node and destination node forms is added to during out-tree limit gathers;

If d. determine, the father node of described destination node is not root node or leaf node, be then judged as one of following three kinds of situations:

D1. destination node non-leaf nodes;

D2. destination node is leaf node, and its father node is the known node of non-root node;

D3. destination node is leaf node, and the non-known node of its father node.

If e. described intersection point overlaps with destination node, then judge destination node non-leaf nodes, upgrade out-tree node set and the set of out-tree limit, add out-tree node set to by destination node; Add two limits that the child node of the father node of destination node and destination node, destination node and destination node forms to out-tree limit to gather, from the set of out-tree limit, delete the limit of the child node composition of destination node father node and destination node;

If f. described intersection point is known node, then judge that destination node is leaf node, and its father node is the known node of non-root node, described destination node is added in leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, add out-tree node set to by destination node, the limit of the father node of destination node and destination node composition is added in the set of out-tree limit;

If g. described intersection point is unknown node, then judge that destination node is leaf node, and the non-known node of its father node, described destination node is added in leaf node set, upgrade out-tree node set and the set of out-tree limit simultaneously, out-tree node set is added to by destination node and described intersection point, add the limit of the child node of described intersection point and the father node of described intersection point, described intersection point composition the set of to out-tree limit, from the set of out-tree limit, delete the limit of the father node of described intersection point and the child node composition of described intersection point;

(3) obtain the tree structure rebuild after execution of step (2), namely obtain the topological structure of described power line network.

9. method according to claim 1, is characterized in that, in described step S6, host node is according to the range information between described any two nodes, and the topological structure utilizing tree method of estimation to obtain described power line network comprises:

Host node is according to the range information between described any two nodes, and the tree method of estimation utilizing root to adjoin obtains the topological structure of described power line network:

(1) preset a root node, preset a leaf node set, described leaf node set comprises all nodes except described root node; Preset an out-tree node set and the set of out-tree limit;

(2) two leaf nodes are determined according to mode below:

If root node is r, the distance between any two leaf node i and j is q _ij, for described two leaf node i and j, calculate the distance q of i and j and root node r respectively _irand q _jr, get and make formula (q _ir+ q _jr-q _ijleaf node i and j of maximum is got in)/2;

(3) father node of described leaf node i and j of determining step (2), upgrade out-tree node set and the set of out-tree limit, be stored in out-tree node set by leaf node i and j, the limit that the father node of leaf node i, j and described leaf node i and j forms is stored in during out-tree limit gathers, described father node is increased in described leaf node set simultaneously, deletes leaf node i and j in described leaf node set;

(4) repeated execution of steps (2) ~ (3), until only remain next leaf node in described leaf node set, thus obtain the tree structure of reconstruction, namely obtain the topological structure of described power line network.

10., based on a power line network topology ambiguity device for power line communication, it is characterized in that, described device comprises:

Signal transmitting module, under the coordination of host node, sends signal frame m from the node A of power line network to Node B;

Signal receiving module, for the Node-B receiver signal frame m ' from power line network;

Channel frequency response estimation module, for according to described signal frame m and described signal frame m ', obtains the channel frequency response estimation H between described node A and described Node B by channel estimating _est;

Euclidean distance between node pair estimation module, for estimating H according to the channel frequency response between described node A and described Node B _est, calculate described signal frame m from described node A to the estimated value t of described Node B time of advent used; According to described signal frame m from described node A to the estimated value t of described Node B time of advent used, calculate the distance between described node A and described Node B;

Topological structure estimation module, for according to the range information between any two nodes of described euclidean distance between node pair estimation module transmission, utilizes tree method of estimation to obtain the topological structure of described power line network.