CN111865474A - Wireless communication anti-interference decision method and system based on edge calculation - Google Patents
Wireless communication anti-interference decision method and system based on edge calculation Download PDFInfo
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- CN111865474A CN111865474A CN202010681536.XA CN202010681536A CN111865474A CN 111865474 A CN111865474 A CN 111865474A CN 202010681536 A CN202010681536 A CN 202010681536A CN 111865474 A CN111865474 A CN 111865474A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H—ELECTRICITY
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- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
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Abstract
The invention discloses a wireless communication anti-interference decision method and a wireless communication anti-interference decision system based on edge calculation, which have low requirement on wireless communication node capability, wide application range and high decision precision. The invention discloses a wireless communication anti-interference decision method, which comprises the following steps: (10) constructing an anti-interference strategy library: the edge computing node determines an anti-interference strategy under each scene, and an anti-interference strategy library is constructed; (20) and (3) perception data collection: the edge computing node stores self perception and perception data from two wireless communication nodes; (30) and (3) generating an anti-interference strategy: the edge computing node selects an anti-interference strategy for the wireless communication node from the anti-interference strategy library according to the sensing data; (40) distributing anti-interference strategies: the edge computing node distributes the anti-interference decision to the two wireless communication nodes; (50) policy application and feedback: the wireless communication node applies the received anti-interference strategy and feeds back the effect after the strategy is applied to the edge computing node through a control channel.
Description
Technical Field
The invention belongs to the technical field of network data communication, and particularly relates to a wireless communication anti-interference decision method and system based on edge calculation.
Background
The interference attack is an attack behavior that a legal user uses a wireless channel to receive and transmit a message by sending useless interference signals to the wireless communication channel or destroying the operation process of a wireless network link layer access protocol. The anti-interference decision is a process of selecting a targeted anti-interference strategy according to the type of the interference attack so as to cope with the interference attack, so that the influence of the interference attack can be effectively reduced or eliminated, and the wireless communication service is recovered.
After the interference attack is triggered, the two wireless communication nodes of the two communication parties need to respectively execute the selected anti-interference decision methods to generate respective anti-interference strategies. The anti-interference decision method mainly comprises a genetic algorithm, a particle swarm algorithm, a simulated annealing algorithm, an artificial bee colony algorithm, a reinforcement learning method and the like. However, the computation, storage and energy supply required for continuously executing the decision methods are high, which exceed the capability of the wireless communication node based on the embedded platform, and the application range of the methods is severely limited. In addition, the complex calculation process may lead to a long decision time, and may not be suitable for a dynamically changing wireless communication environment.
Edge computing potentially provides computational resources needed for anti-interference decisions by placing computational, storage, and transmission resources at the data generation source, thereby providing a computing infrastructure of computing services in the near vicinity.
However, the prior art has problems that: the method for using the edge computing architecture for the anti-interference decision making is lacked, so that the requirement on the wireless communication node capacity is high, the anti-interference strategy decision making is accurate and low, and the method is narrow in application range.
Disclosure of Invention
The invention aims to provide a wireless communication anti-interference decision method and a wireless communication anti-interference decision system based on edge calculation, which have low requirements on wireless communication node capability, wide application range and high decision precision.
The technical solution for realizing the purpose of the invention is as follows:
an edge calculation-based wireless communication anti-interference decision method comprises the following steps:
(10) constructing an anti-interference strategy library: for various given interference attack scenes, the edge computing nodes determine an anti-interference strategy under each scene, and an anti-interference strategy library is constructed;
(20) and (3) perception data collection: the edge computing node stores self-perceived edge computing node perception data and perception data from two wireless communication nodes;
(30) and (3) generating an anti-interference strategy: the edge computing node selects an anti-interference strategy for the wireless communication node from the anti-interference strategy library according to the sensing data;
(40) distributing anti-interference strategies: the edge computing node distributes the anti-interference decision to the two wireless communication nodes;
(50) Policy application and feedback: the wireless communication node applies the received anti-interference strategy and feeds back the effect after the strategy is applied to the edge computing node through a control channel.
The technical solution for realizing another purpose of the invention is as follows:
an edge-computing-based wireless communication anti-interference decision making system, comprising:
the anti-interference strategy library construction unit (1) is used for determining an anti-interference strategy under each scene by the edge computing node for a plurality of given interference attack scenes and constructing an anti-interference strategy library;
the sensing data collection unit (2) is used for storing self-sensed edge computing node sensing data and wireless communication node sensing data from both wireless communication parties by the edge computing node;
the anti-interference strategy generating unit (3) is used for selecting an anti-interference strategy for the wireless communication node from the anti-interference strategy library by the edge computing node according to the sensing data;
the anti-interference strategy distribution unit (4) is used for distributing the anti-interference decision to the two wireless communication nodes by the edge computing node;
and the strategy application and feedback unit (5) is used for applying the received anti-interference strategy by the wireless communication node and feeding back the effect after the strategy is applied to the edge computing node through a control channel.
Compared with the prior art, the invention has the following remarkable advantages:
1. the requirement on the capability of the wireless communication node is very low, and the application range is wide: according to the wireless communication anti-interference decision method and system based on edge computing, the edge computing node completes anti-interference decision, the requirements on computing, transmission and storage capacities of wireless communication equipment are low, and the method and system can be widely applied to wireless communication equipment with limited capacity.
2. The decision result is more accurate: the edge computing node has sufficient resources so that various anti-interference decision algorithms can be operated, an optimal anti-interference strategy is determined by selecting probability, and then a feedback mechanism is used for evaluating the application of the anti-interference strategy, so that the anti-interference decision result is more accurate.
The invention is described in further detail below with reference to the figures and the detailed description.
Drawings
Fig. 1 is a main flow chart of the wireless communication anti-interference decision method based on edge calculation according to the present invention.
Fig. 2 is a flowchart of the interference avoidance policy library construction step in fig. 1.
Fig. 3 is an exemplary diagram of a wireless communication scenario in the presence of an interference attack.
Fig. 4 is a flowchart of the interference avoidance strategy generation step of fig. 1.
FIG. 5 is a flow chart of the strategy application and feedback steps of FIG. 1.
Detailed Description
As shown in fig. 1, the method for deciding the interference resistance of the wireless communication based on the edge calculation of the present invention includes the following steps:
(10) constructing an anti-interference strategy library: for various given interference attack scenes, the edge computing nodes determine an anti-interference strategy under each scene, and an anti-interference strategy library is constructed;
as shown in fig. 2, the step of constructing (10) the immunity policy library includes:
(11) and (3) determining constraint conditions: the edge computing node determines anti-interference decision constraint conditions of two wireless communication nodes, wherein the anti-interference decision constraint conditions comprise capability configuration, a wireless propagation environment and wireless communication service quality;
(12) determining an anti-interference strategy: for various given interference attack scenes, the edge computing node determines the anti-interference strategy of the wireless communication node in each scene according to constraint conditions and domain expert knowledge;
optionally, the capability configurations of the two wireless communication parties include a modulation and demodulation mode, a coding mode, transmission power, and the like;
optionally, the wireless propagation environment includes a channel propagation model, a channel attenuation index, environmental noise, and the like;
optionally, the wireless communication service quality includes a transmission rate and a bit error rate;
optionally, the domain expert knowledge may include a knowledge graph or expert system;
Optionally, the anti-interference policy includes configuring a communication frequency, a modulation and demodulation scheme, a coding scheme, and a transmission power parameter.
(13) And (3) forming an anti-interference strategy library: and collecting the anti-interference strategies corresponding to each scene to obtain an anti-interference strategy library.
(20) And (3) perception data collection: the edge computing node stores self-perceived edge computing node perception data and perception data from two wireless communication nodes; in the step (20) of collecting perception data, the perception data of the edge computing node is the perception data collected by the edge computing node through a self perception module;
the perception data of the two wireless communication nodes are the perception data which are received by the edge computing node through a control channel and come from the two wireless communication nodes which are communicated with each other;
in a wireless communication scenario when there is an interference attack, as shown in fig. 3, the wireless communication node 1 and the wireless communication node 2 transmit their respective sensing data to the edge computing node through the wireless control channel.
Optionally, the sensing data includes received signal power, noise power, signal-to-noise ratio, transmission rate, bit error rate, and the like.
(30) And (3) generating an anti-interference strategy: the edge computing node selects an anti-interference strategy for the wireless communication node from the anti-interference strategy library according to the sensing data;
As shown in fig. 4, the (30) anti-interference policy generating step includes:
(31) selecting an anti-interference strategy: the edge computing node simultaneously operates a plurality of anti-interference algorithms, and each algorithm selects a corresponding anti-interference strategy from an anti-interference strategy library according to the sensing data;
the multiple anti-interference algorithms comprise an artificial bee colony algorithm, a genetic algorithm, a reinforcement learning method, an association diagram method and a decision tree method;
(32) and (3) selecting probability calculation: for each anti-interference strategy, the edge computing node calculates the times of the strategy selected by the anti-interference algorithms, and then multiplies the times by the weight of the strategy to be used as the selection probability of the strategy;
(33) determining an anti-interference strategy: and the edge computing node takes the anti-interference strategy with the maximum selection probability as the anti-interference strategies of the two wireless communication nodes.
(40) Distributing anti-interference strategies: the edge computing node distributes the anti-interference decision to the two wireless communication nodes;
in the wireless communication scenario when there is an interference attack, as shown in fig. 3, the edge computing node transmits the interference rejection policy to the wireless communication node 1 and the wireless communication node 2 through the wireless control channel.
(50) Policy application and feedback: the wireless communication node applies the received anti-interference strategy and feeds back the effect after the strategy is applied to the edge computing node through a control channel.
As shown in fig. 5, the policy applying and feedback step (50) includes:
(51) communication parameter configuration: the wireless communication node configures own communication parameters according to the received anti-interference strategy;
(52) and (3) strategy feedback calculation: the wireless communication node calculates strategy feedback according to the communication speed and the error rate change before and after the strategy is applied;
(53) and (3) strategy feedback transmission: the wireless communication node transmits the strategy feedback to the edge computing node through a control channel;
(54) updating the anti-interference strategy weight: and the edge computing node updates the weight of the anti-interference strategy according to the received strategy feedback.
The invention relates to a wireless communication anti-interference decision system based on edge calculation, which comprises:
the anti-interference strategy library construction unit (1) is used for determining an anti-interference strategy under each scene by the edge computing node for a plurality of given interference attack scenes and constructing an anti-interference strategy library;
the anti-interference strategy library construction unit (1) comprises:
the constraint condition determining module (101) is used for determining anti-interference decision constraint conditions of the two wireless communication nodes by the edge computing node, wherein the anti-interference decision constraint conditions comprise capability configuration, a wireless propagation environment and wireless communication service quality;
the anti-interference strategy determining module (102) is used for determining the anti-interference strategy of the wireless communication node in each scene according to constraint conditions and domain expert knowledge for a plurality of given interference attack scenes;
And an anti-interference strategy library forming module (103) for collecting the anti-interference strategies corresponding to each scene to obtain an anti-interference strategy library.
The sensing data collection unit (2) is used for storing self-sensed edge computing node sensing data and wireless communication node sensing data from both wireless communication parties by the edge computing node;
the anti-interference strategy generating unit (3) is used for selecting an anti-interference strategy for the wireless communication node from the anti-interference strategy library by the edge computing node according to the sensing data;
the anti-interference strategy generation unit (3) comprises:
the anti-interference strategy selection module (301) is used for simultaneously operating multiple anti-interference algorithms by the edge computing node, and each algorithm selects a corresponding anti-interference strategy from the anti-interference strategy library according to the sensing data;
the multiple anti-interference algorithms comprise an artificial bee colony algorithm, a genetic algorithm, a reinforcement learning method, an association diagram method and a decision tree method;
a selection probability calculation module (302) used for calculating the times of the strategy selected by the multiple anti-interference algorithms by the edge calculation node for each anti-interference strategy, and then multiplying the times by the weight of the strategy to be used as the selection probability of the strategy;
and the anti-interference strategy selection module (303) is used for the edge computing node to use the anti-interference strategy with the maximum selection probability as the anti-interference strategies of the two wireless communication nodes.
The anti-interference strategy distribution unit (4) is used for distributing the anti-interference decision to the two wireless communication nodes by the edge computing node;
and the strategy application and feedback unit (5) is used for applying the received anti-interference strategy by the wireless communication node and feeding back the effect after the strategy is applied to the edge computing node through a control channel.
The policy application and feedback unit (5) comprises:
a communication parameter configuration module (501) for configuring the communication parameters of the wireless communication node according to the received anti-interference strategy;
the strategy feedback calculation module (502) is used for calculating strategy feedback by the wireless communication node according to changes of communication speed, bit error rate and the like before and after strategy application;
a policy feedback transmission module (503) for the wireless communication node to transmit the policy feedback to the edge computing node over the control channel;
and the anti-interference strategy weight value updating module (504) is used for updating the weight value of the anti-interference strategy by the edge computing node according to the received strategy feedback.
Claims (9)
1. An edge calculation-based wireless communication anti-interference decision method is characterized by comprising the following steps:
(10) constructing an anti-interference strategy library: for various given interference attack scenes, the edge computing nodes determine an anti-interference strategy under each scene, and an anti-interference strategy library is constructed;
(20) And (3) perception data collection: the edge computing node stores self-perceived edge computing node perception data and perception data from two wireless communication nodes;
(30) and (3) generating an anti-interference strategy: the edge computing node selects an anti-interference strategy for the wireless communication node from the anti-interference strategy library according to the sensing data;
(40) distributing anti-interference strategies: the edge computing node distributes the anti-interference decision to the two wireless communication nodes;
(50) policy application and feedback: the wireless communication node applies the received anti-interference strategy and feeds back the effect after the strategy is applied to the edge computing node through a control channel.
2. The method for decision-making for wireless communication based on edge computing interference avoidance of claim 1, wherein the step of constructing (10) the interference avoidance policy library comprises:
(11) and (3) determining constraint conditions: the edge computing node determines anti-interference decision constraint conditions of two wireless communication nodes, wherein the anti-interference decision constraint conditions comprise capability configuration, a wireless propagation environment and wireless communication service quality;
(12) determining an anti-interference strategy: for various given interference attack scenes, the edge computing node determines the anti-interference strategy of the wireless communication node in each scene according to constraint conditions and domain expert knowledge;
(13) And (3) forming an anti-interference strategy library: and collecting the anti-interference strategies corresponding to each scene to obtain an anti-interference strategy library.
3. The method of claim 1, wherein the method comprises:
in the step (20) of collecting perception data, the perception data of the edge computing node is the perception data collected by the edge computing node through a self perception module;
the perception data of the wireless communication node is the perception data received by the edge computing node through the control channel from two wireless communication nodes which are communicated with each other.
4. The method of claim 1, wherein the step of generating (30) the immunity policy comprises:
(31) selecting an anti-interference strategy: the edge computing node simultaneously operates a plurality of anti-interference algorithms, and each algorithm selects a corresponding anti-interference strategy from an anti-interference strategy library according to the sensing data;
the multiple anti-interference algorithms comprise an artificial bee colony algorithm, a genetic algorithm, a reinforcement learning method, an association diagram method and a decision tree method;
(32) and (3) selecting probability calculation: for each anti-interference strategy, the edge computing node calculates the times of the strategy selected by the anti-interference algorithms, and then multiplies the times by the weight of the strategy to be used as the selection probability of the strategy;
(33) Determining an anti-interference strategy: and the edge computing node takes the anti-interference strategy with the maximum selection probability as the anti-interference strategies of the two wireless communication nodes.
5. The method of claim 1, wherein the policy applying and feedback step comprises (50):
(51) communication parameter configuration: the wireless communication node configures own communication parameters according to the received anti-interference strategy;
(52) and (3) strategy feedback calculation: the wireless communication node calculates strategy feedback according to the communication speed and the error rate change before and after the strategy is applied;
(53) and (3) strategy feedback transmission: the wireless communication node transmits the strategy feedback to the edge computing node through a control channel;
(54) updating the anti-interference strategy weight: and the edge computing node updates the weight of the anti-interference strategy according to the received strategy feedback.
6. An edge-computing-based wireless communication anti-interference decision making system, comprising:
the anti-interference strategy library construction unit (1) is used for determining an anti-interference strategy under each scene by the edge computing node for a plurality of given interference attack scenes and constructing an anti-interference strategy library;
the sensing data collection unit (2) is used for storing self-sensed edge computing node sensing data and wireless communication node sensing data from both wireless communication parties by the edge computing node;
The anti-interference strategy generating unit (3) is used for selecting an anti-interference strategy for the wireless communication node from the anti-interference strategy library by the edge computing node according to the sensing data;
the anti-interference strategy distribution unit (4) is used for distributing the anti-interference decision to the two wireless communication nodes by the edge computing node;
and the strategy application and feedback unit (5) is used for applying the received anti-interference strategy by the wireless communication node and feeding back the effect after the strategy is applied to the edge computing node through a control channel.
7. The system according to claim 6, wherein the antijam policy library construction unit (1) comprises:
the constraint condition determining module (101) is used for determining anti-interference decision constraint conditions of the two wireless communication nodes by the edge computing node, wherein the anti-interference decision constraint conditions comprise capability configuration, a wireless propagation environment and wireless communication service quality;
the method comprises the steps that an anti-interference strategy is determined (102), and for various given interference attack scenes, the edge computing node determines the anti-interference strategy of the wireless communication node under each scene according to constraint conditions and domain expert knowledge;
and forming (103) an anti-interference strategy library, and collecting anti-interference strategies corresponding to each scene to obtain the anti-interference strategy library.
8. The system according to claim 6, wherein the immunity policy generation unit (3) comprises:
the anti-interference strategy selection module (301) is used for simultaneously operating multiple anti-interference algorithms by the edge computing node, and each algorithm selects a corresponding anti-interference strategy from the anti-interference strategy library according to the sensing data;
the multiple anti-interference algorithms comprise an artificial bee colony algorithm, a genetic algorithm, a reinforcement learning method, an association diagram method and a decision tree method;
a selection probability calculation module (302) used for calculating the times of the strategy selected by the multiple anti-interference algorithms by the edge calculation node for each anti-interference strategy, and then multiplying the times by the weight of the strategy to be used as the selection probability of the strategy;
and the anti-interference strategy selection module (303) is used for the edge computing node to use the anti-interference strategy with the maximum selection probability as the anti-interference strategies of the two wireless communication nodes.
9. The system according to claim 6, wherein the policy application and feedback unit (5) comprises:
a communication parameter configuration module (501) for configuring the communication parameters of the wireless communication node according to the received anti-interference strategy;
The strategy feedback calculation module (502) is used for calculating strategy feedback by the wireless communication node according to changes of communication speed, bit error rate and the like before and after strategy application;
a policy feedback transmission module (503) for the wireless communication node to transmit the policy feedback to the edge computing node over the control channel;
and the anti-interference strategy weight value updating module (504) is used for updating the weight value of the anti-interference strategy by the edge computing node according to the received strategy feedback.
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