CN107592174A - A kind of high-efficiency frequency spectrum cognitive method in intelligent grid communication - Google Patents
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Abstract
High-efficiency frequency spectrum cognitive method and system in being communicated the invention discloses a kind of intelligent grid, the system is made up of intelligent electric meter terminal, Substation control center, dynamically realizes the two-way communication between terminal and control centre using the idle frequency spectrum of TV band using cognitive radio technology；Methods described includes：Data detect according to the history of storage in control centre, and the degree of different television channels is made prediction using Three-exponential Smoothing model, and preferably go out one group of relatively low channel of degree according to prediction result, form a less channel set to be detected.The characteristics of intelligent electric meter terminal is using known to digital television signal PN sequence codes, using correlation detection principle, only this less channel set is detected, compared with traditional frequency spectrum sensing method, not only accuracy of detection is high, detection time is short for methods described, and the probability for detecting idle channel can be improved, improve the frequency spectrum perception efficiency in intelligent grid communication.
Description
Technical Field
The invention relates to the field of intelligent power grid communication, mainly solves the problem of efficient spectrum detection during wireless access of an intelligent power grid, and particularly relates to a prediction-based efficient spectrum sensing method in intelligent power grid communication.
Background
The intelligent power grid is based on a traditional power grid framework, adopts advanced sensing, measuring and equipment and an efficient control method, and utilizes a high-speed, bidirectional and integrated communication network and a computer information network as a platform to realize high fusion of electric power, information and service, so that the power grid becomes more reliable and safer. Compared with the traditional power grid, the high-speed operation of the network structure is guaranteed in the transmission process of the intelligent power grid, the interaction with users can be realized, the diversified requirements of the users are met, value-added services are provided for the users, and therefore the comprehensive functions of the intelligent power grid are exerted. In the construction of the smart grid, the role of the communication technology is crucial, and the establishment of an efficient, real-time and integrated communication system is the basis for realizing the smart grid.
In a smart grid system, the user terminal meters have access to the communication portion of the local control center, commonly referred to as last mile access. Compared with other existing wireless communication systems, the last kilometer of wireless access of the smart grid has the characteristics of the smart grid. First, the transmitter and receiver are fixed, which alleviates problems in many mobile communications such as fast channel changes, frequent handovers, etc.; secondly, the smart grid needs to enable more end-user interactions, such as real-time meter monitoring. The above requirements are met with the following challenges: and (1) the time delay requirement is high. If the control center does not receive the message input from the terminal sensor due to excessive time delay, the control center may send an incorrect control message to the terminal of the smart meter. And (2) the transmission information quantity is large. Because of the huge number of terminal users and the necessarily large amount of information transmission, the communication network should be able to carry the message transmission with large data volume. When designing the last kilometer access system of the smart grid, the above factors must be considered to realize reliable and efficient communication.
The invention considers the condition that the communication link between the user terminal electric meter and the local control center adopts a wireless link, and the first task of accessing the last kilometer at the moment is to solve the problem of selecting the wireless spectrum. According to the prior art development, there are currently three alternative spectrum schemes: (1) The power grid system applies for a special authorized frequency spectrum to a frequency spectrum management department; (2) using a public spectrum without authorization; (3) Licensed spectrum is dynamically utilized using cognitive radio techniques. Due to the fact that the problem of shortage of spectrum resources is prominent at present, it is not practical to allocate a special spectrum to a power grid system, and a plurality of application technologies exist in public unauthorized frequency bands at present, so that spectrum interference is large, and the requirement of the power grid system for reliable and efficient communication cannot be met. Therefore, the method mainly focuses on the communication problem when the cognitive radio technology is used for realizing the access of the smart grid in the last kilometer. Cognitive radio is an intelligent software-defined radio technology that, based on radio environment detection, adjusts portions of its configured radio spectrum to facilitate efficient, reliable, and dynamic use of underutilized licensed spectrum. IEEE802.22 is the first standardization project for cognitive radio based on opportunistic utilization of the tv spectrum band. The IEEE802.22 is utilized to realize the last kilometer access scheme of the smart grid, and the following advantages are achieved: (1) The cognitive radio makes full use of unused television frequency bands, so that insufficient frequency spectrum resources can be greatly relieved, and the frequency spectrum requirement of the smart power grid on wireless access is met. And (2) transmission rates up to tens of Mbps can be achieved. (3) Due to the long-term propagation characteristic band of the supported television, the coverage area can reach 100 kilometers. (4) The cognitive radio is a self-adaptive, programmable and flexible technology, and can realize dynamic utilization of the idle frequency spectrum of the television frequency band.
According to an application mode of a cognitive radio technology, when the last kilometer of smart grid communication is accessed by flexibly utilizing the video band white space, each cognitive device (including a smart meter terminal and a grid control center) firstly detects the use condition of the television band at the geographic position, and then the communication parties access the unused television channel through a servo after negotiation. In the cognitive radio-based smart grid communication system, the efficient spectrum sensing method based on television channel occupancy prediction is provided for improving the spectrum sensing efficiency of the electric meter terminal by considering that the storage and calculation capabilities of a wireless module of the smart electric meter terminal are limited, and a grid control center has the characteristic of strong storage and calculation capabilities.
Disclosure of Invention
Based on the analysis, in order to improve the spectrum sensing efficiency of the electric meter terminal in the smart grid communication system, the invention provides the following efficient spectrum sensing method and system:
the method only considers the problem of accessing the last kilometer of the smart grid communication by using cognitive radio, the system consists of a smart meter terminal, a terminal substation control center and a regional substation control center, the cognitive radio technology is adopted to dynamically utilize the idle frequency spectrum of a video frequency band, the smart meter terminal and the terminal substation control center are cognitive devices, the cognitive devices firstly detect television channels before the communication, an available channel list is obtained, and two communication parties select a common available channel for communication after negotiation.
The method comprises a correlation detection method based on a PN sequence code of a digital television signal and a channel occupancy rate prediction and selection method based on a cubic exponential smoothing model.
A basic idea of a correlation detection method based on a PN sequence code of a digital television signal is as follows: according to a known digital television signal frame header PN sequence mode, the intelligent electric meter terminal locally generates a PN sequence, and performs correlation operation on a received signal and the local PN sequence to obtain a correlation signal; and comparing the peak value of the relevant signal with a judgment threshold to obtain a judgment result of idle or occupied television signals. The method is characterized in that the known characteristics of the PN sequence code of the digital television signal are utilized, and a correlation detection method is adopted.
The basic thought of a channel occupancy prediction and selection method based on a cubic exponential smoothing model is as follows: and the terminal substation control center predicts the occupancy rates of the television channels of different electric meter terminals by adopting a cubic exponential smoothing model according to the stored historical detection data, and preferably selects a group of channels with lower occupancy rates according to the prediction results to form a smaller channel set to be detected. The method is characterized in that the characteristics of strong storage and calculation capabilities of the intelligent power grid control center are utilized, the intelligent power grid control center predicts the occupancy rate of the television channel according to the historical detection result of the intelligent electric meter terminal, and then the intelligent electric meter terminal only executes spectrum detection on the channel with the lower occupancy rate based on the prediction result, so that the spectrum sensing time is saved, and the probability of detecting the idle spectrum is improved.
Specifically, the efficient spectrum sensing method based on correlation detection and prediction comprises the following steps:
step 101) dividing all intelligent electric meter terminals in a management range of a terminal substation control center into a plurality of clusters according to geographical positions;
step 102) after the system is started, detecting the television channel occupation condition of the position of the intelligent electric meter terminal of the ith cluster by adopting a correlation detection method, and setting a television channel set as A, wherein the television channel set comprises N channels. The intelligent electric meter terminal selects a channel j, and the occupation condition of the channel j is detected by adopting a correlation detection method, wherein the correlation detection method is specifically realized as follows: assuming that the received signal is r (n) and the PN sequence length of the channel j is L, the correlation calculation result is recorded as:
will correlate the signal R j (n) peak value R j-max (n) comparing with a judgment threshold lambda if R j-max (n)&And gt, lambda, determining that the television channel occupies, otherwise, determining that the television channel is idle.
Step 103) the intelligent electric meter terminal in the ith cluster sends the detection results of the N channels to the control center;
step 104) the control center predicts and sorts the occupancy rates of the N channels in the set A according to the stored historical detection data of the ith cluster, wherein the specific prediction and sorting method comprises the following steps:
step 104-1) the control center carries out statistical analysis on historical detection data aiming at a certain channel in the television channel set to be detected to obtain a time sequence of the occupancy rate of the channel, and the occupancy rate sequence of the channel is set as { s } t }；
Step 104-2) using a cubic exponential smoothing model for the occupancy time series s t Predicting to obtain a prediction result y of the channel occupancy rate t . The cubic exponential smoothing prediction is re-smoothing based on the quadratic smoothing, and the basic idea is as follows:the predicted value is a weighted sum of the previous observations and different data is given different weight, new data is given greater weight and old data is given lesser weight. The prediction formula is as follows:
the prediction model of the cubic exponential smoothing method is as follows:
wherein,
and step 104-3) the control center sorts the channels from low to high according to the predicted spectrum occupancy rate, and the channels arranged in the front are combined into a smaller channel subset to be detected. Sorting according to the occupancy rate from low to high, taking out the first M (M < N) channels to form a new channel subset A1 to be detected, wherein A1 belongs to A;
step 105) the control center broadcasts the channel subset A1 to be detected to the ith cluster terminal;
and 106) the ith intra-cluster terminal only carries out spectrum detection on the channels in the channel subset A1 to be detected to obtain detection results, and reports the detection results of the M channels to the control center. The next step is to step 104.
Drawings
Fig. 1 is a structural diagram of a cognitive radio-based smart grid communication system according to the present invention.
Fig. 2 shows a high efficiency spectrum sensing method based on correlation detection and prediction.
Detailed Description
The solution proposed by the present invention is described in detail below with reference to fig. 1 and 2.
Fig. 1 is a structural diagram of a cognitive radio-based smart grid communication system, which is composed of a smart meter terminal, a terminal substation control center and a regional substation control center, and the invention only considers the problem of wireless access of the last kilometer of smart grid communication, and adopts a cognitive radio technology to dynamically utilize idle frequency spectrum of a video band, wherein the smart meter terminal and the terminal substation control center are cognitive devices, the cognitive devices firstly detect television channels before communication to obtain an available channel list, and two communication parties select a common available channel for communication after negotiation. The present invention only considers the problem of efficient spectrum detection of the system shown in fig. 1, and performs spectrum detection by using the method shown in fig. 2.
The efficient spectrum sensing method based on correlation detection and prediction shown in fig. 2 comprises the following steps:
step 101) dividing all intelligent electric meter terminals in the management range of a terminal substation control center into a plurality of clusters according to geographical positions in the system shown in FIG. 1;
step 102) after the system is started, detecting the television channel occupation condition of the position of the intelligent electric meter terminal of the ith cluster by adopting a correlation detection method, and setting a television channel set as A, wherein the television channel set comprises N channels. The intelligent electric meter terminal selects a channel j, and detects the occupation condition of the channel j by adopting a correlation detection method, wherein the correlation detection method is specifically realized as follows: assuming that the received signal is r (n) and the PN sequence length of the channel j is L, the correlation calculation result is recorded as:
carrying out peak value search on the calculation result of the formula and taking out the highest peak value R j-max (n) comparing with a decision threshold gamma, if R j-max (n)&And gt, gamma, judging that the television channel is occupied, otherwise, judging that the television channel is idle. Wherein the value of the decision threshold gamma is determined by the false alarm probability P f Determining the relation between the two:
wherein,in order to be the average power of the noise,is the average power of the PN sequence.
Step 103) the intelligent electric meter terminal in the ith cluster sends the detection results of the N channels to the control center;
step 104) the control center predicts and sorts the occupancy rates of the N channels in the set A according to the stored historical detection data of the ith cluster, wherein the specific prediction and sorting method comprises the following steps:
step 104-1) the control center carries out statistical analysis on the historical detection data aiming at a certain channel in the television channel set to be detected to obtain a time sequence of the occupancy rate of the channel, and the occupancy rate sequence of the channel is set as { s } t }；
Step 104-2) using a cubic exponential smoothing model for the occupancy time series s t Predicting to obtain a prediction result y of the occupancy rate of the channel t . The cubic exponential smoothing prediction is re-smoothing based on the quadratic smoothing, and the basic idea is as follows: the predicted value is a weighted sum of the previous observations and different data is given different weight, new data is given greater weight and old data is given lesser weight. The prediction formula is as follows:
the prediction model of the cubic exponential smoothing method is as follows:
wherein,
and step 104-3) the control center sorts the channels from low to high according to the predicted spectrum occupancy rate, and the channels in the front row form a smaller channel subset to be detected. Taking out the front M (M) according to the sequence of the occupancy degree from low to high<, N) channels to form a new subset A1, A1 of channels to be detected ∈ A；
Step 105) the control center broadcasts the channel subset A1 to be detected to the ith cluster terminal;
and 106) the ith intra-cluster terminal only carries out spectrum detection on the channels in the channel subset A1 to be detected to obtain detection results, and reports the detection results of the M channels to the control center. The next step is to step 104 to continue execution.
Claims (3)
1. An effective spectrum sensing method in smart grid communication is characterized by comprising the following operation steps:
step 101) dividing all intelligent electric meter terminals in a terminal substation management range into a plurality of clusters according to geographical positions;
step 102), after the system is started, detecting the television channel occupation condition of the position of the intelligent electric meter terminal of the ith cluster by adopting a correlation detection method, and setting a television channel set as A, wherein the television channel set comprises N channels;
step 103) the intelligent electric meter terminal in the ith cluster sends the detection results of the N channels to the control center;
step 104) the control center performs data mining and prediction on the occupancy rates of the N channels in the set A according to the stored historical detection data of the ith cluster, the occupancy rates are sorted from low to high, the front M (M < N) channels are taken out to form a new channel subset A1 to be detected, and A1 belongs to A;
step 105) the control center broadcasts the channel subset A1 to be detected to the ith cluster terminal;
and 106) the ith intra-cluster terminal only carries out spectrum detection on the channels in the channel subset A1 to be detected to obtain detection results, and reports the detection results of the M channels to the control center. The next step is to step 104 to continue execution.
2. The method for spectrum sensing for television signal correlation detection as claimed in claim 1, wherein said step 102) further comprises:
step 102-1), according to a known PN sequence mode of a digital television signal frame header, the intelligent electric meter terminal locally generates a PN sequence, and performs correlation operation on the received signal and the local PN sequence to obtain a correlation signal. Assuming that the received signal is r (n) and the PN sequence length of the channel j is L, the formula of the correlation calculation is:
step 102-2) correlating the signal R j (n) peak value R j-max (n) comparing with a judgment threshold lambda if R j-max (n)&And gt, lambda, determining that the television channel occupies, otherwise, determining that the television channel is idle.
3. The occupancy rate data mining and prediction method according to claim 1, wherein the step 104) comprises the following specific steps:
step 104-1) the control center carries out statistical analysis on historical detection data aiming at a certain channel in the television channel set to be detected to obtain a time sequence { s ] of the occupancy rate of the channel t }；
Step 104-2) using a cubic exponential smoothing model for the occupancy time series s t Predicting to obtain a prediction result y of the occupancy rate of the channel t . The prediction formula is as follows:
the prediction model of the cubic exponential smoothing method is as follows:
wherein,
and step 104-3) the control center sorts the channels from low to high according to the predicted spectrum occupancy rate, and the channels arranged in the front are combined into a smaller channel subset to be detected.
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