CN117692917A - Relay control system for wireless communication network - Google Patents
Relay control system for wireless communication network Download PDFInfo
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Abstract
The present invention relates to a relay control system for a wireless communication network, comprising: a wireless relay device for providing an access interface of a wireless communication network for passengers inside the closed compartment; and the auxiliary control mechanism is used for starting a standby relay device of the wireless relay device when the difference value between the intelligently predicted average consumption flow rate of the wireless relay device in unit time and the maximum throughput of the wireless relay device in unit time is smaller than or equal to a set difference value threshold value. The invention can intelligently predict the average consumption flow of the wireless relay equipment in the future time in unit time, and when the difference value between the average consumption flow and the maximum throughput of the wireless relay equipment in unit time is smaller than or equal to the set difference value threshold, the standby relay device of the wireless relay equipment is started, so that the wireless communication efficiency in the closed carriage is ensured, and meanwhile, the occupation of excessive relay devices is avoided.
Description
Technical Field
The present invention relates to the field of wireless communications, and in particular, to a relay control system for a wireless communication network.
Background
Electrical communication can generally be divided into two broad categories: one type is called wire radio communication and one type is called radio communication. A communication mode in which information is transmitted by radio waves is called radio communication, and it is capable of transmitting sound, text, data, images, and the like. Compared with wired communication, the wireless communication system does not need to erect a transmission line, has long communication distance, good maneuverability and quick establishment; but the transmission quality is unstable, the signal is easy to interfere or be intercepted, is easy to be influenced by natural factors, and has poor confidentiality.
The wireless routing device is an important relay component for executing wireless communication, in the use scene of the wireless routing device, if more wireless network terminals exist on site and the network data volume required by each wireless network terminal is combined together to be considerable, a standby routing device of the wireless routing device needs to be started for cooperative routing operation, for example, the invention with the application publication number of CN111049934A discloses a wireless Internet of things edge cooperative monitoring method, device and system, and the acquired object access information corresponding to an object state beacon sent by peripheral service object equipment; the cooperative service node performs state monitoring analysis on the object access information; the cooperative service node judges according to the object state identification information: acquiring corresponding event trigger identification information; creating a corresponding new collaborative task item by a collaborative service node which takes on the role of a collaborative routing node in the plurality of collaborative service nodes; and the cooperative routing node performs cooperative monitoring task management on the cooperative task items, and the cooperative service node executes and feeds back the corresponding cooperative task items by inquiring the cooperative processing task identifiers. However, in the prior art, the judgment is performed based on the existing network data volume, and the judgment mechanism is relatively lagged and does not have real-time property, so that the deviation between the use and the provision is easy to exist.
Disclosure of Invention
In order to solve the technical problems in the prior art, the present invention provides a relay control system for a wireless communication network, the system comprising:
the wireless relay device is arranged inside the closed compartment and is used for providing an access interface of a wireless communication network for passengers inside the closed compartment;
the parameter analysis device is connected with the wireless relay device and is used for acquiring a plurality of setting parameters of the wireless relay device, wherein the plurality of setting parameters of the wireless relay device comprise the maximum throughput of unit time of the wireless relay device, the maximum operation amount of an operation core and the number of antennas;
the state acquisition equipment is connected with the control console of the closed carriage and used for acquiring various passenger carrying state information of the closed carriage, wherein the various passenger carrying state information of the closed carriage comprises the current passenger carrying number of the closed carriage, the passenger number of different age groups and the number of network terminals for visual analysis;
a multiple learning mechanism for performing multiple learning on a feedforward neural network to obtain an AI intelligent predictor, the number of learning of the feedforward neural network being positively correlated with a maximum throughput per unit time of the wireless relay device;
the intelligent prediction mechanism is respectively connected with the parameter analysis equipment, the state acquisition equipment and the multiple learning mechanism and is used for intelligently predicting the average consumption flow rate of the wireless relay equipment in unit time by adopting the AI intelligent predictor based on multiple setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage;
the auxiliary control mechanism is respectively connected with the wireless relay equipment and the intelligent prediction mechanism and is used for starting a standby relay device of the wireless relay equipment when the difference value between the received average consumption flow of the wireless relay equipment in unit time and the maximum throughput of the wireless relay equipment in unit time is smaller than or equal to a set difference value threshold;
the auxiliary control mechanism is further used for suspending starting a standby relay device of the wireless relay device when the difference between the received average consumption flow of the wireless relay device in unit time and the maximum throughput of the wireless relay device in unit time is larger than the set difference threshold;
the method for acquiring the passenger carrying state information of the closed carriage comprises the steps of: and the panoramic camera mechanism arranged in the closed carriage is used for identifying the number of network terminals existing in the closed carriage and is used as the number of network terminals for visual analysis.
The invention has the technical effects that: the AI intelligent predictor which is designed in a targeted manner can intelligently predict the average consumption flow rate of the wireless relay equipment in unit time based on a plurality of setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage, and the auxiliary control mechanism is used for starting a standby relay device of the wireless relay equipment when the difference value between the average consumption flow rate of the wireless relay equipment in unit time and the maximum throughput of the wireless relay equipment in unit time which are intelligently predicted is smaller than or equal to a set difference value threshold value, so that the wireless communication efficiency in the closed carriage is ensured, and meanwhile, the occupation of excessive relay devices is avoided.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 1 is a block diagram showing the structure of a relay control system for a wireless communication network according to embodiment 1 of the present invention.
Fig. 2 is a block diagram showing the structure of a relay control system for a wireless communication network according to embodiment 2 of the present invention.
Fig. 3 is a block diagram showing the structure of a relay control system for a wireless communication network according to embodiment 3 of the present invention.
Detailed Description
Embodiments of a relay control system for a wireless communication network according to the present invention will be described in detail with reference to the accompanying drawings.
Example 1
Fig. 1 is a block diagram showing the structure of a relay control system for a wireless communication network according to embodiment 1 of the present invention, the system comprising:
the wireless relay device is arranged inside the closed compartment and is used for providing an access interface of a wireless communication network for passengers inside the closed compartment;
illustratively, the wireless communication network on which the wireless relay device is based is a 5G communication network, a time division duplex communication network, or a frequency division duplex communication network;
the parameter analysis device is connected with the wireless relay device and is used for acquiring a plurality of setting parameters of the wireless relay device, wherein the plurality of setting parameters of the wireless relay device comprise the maximum throughput of unit time of the wireless relay device, the maximum operation amount of an operation core and the number of antennas;
the state acquisition equipment is connected with the control console of the closed carriage and used for acquiring various passenger carrying state information of the closed carriage, wherein the various passenger carrying state information of the closed carriage comprises the current passenger carrying number of the closed carriage, the passenger number of different age groups and the number of network terminals for visual analysis;
a multiple learning mechanism for performing multiple learning on a feedforward neural network to obtain an AI intelligent predictor, the number of learning of the feedforward neural network being positively correlated with a maximum throughput per unit time of the wireless relay device;
the intelligent prediction mechanism is respectively connected with the parameter analysis equipment, the state acquisition equipment and the multiple learning mechanism and is used for intelligently predicting the average consumption flow rate of the wireless relay equipment in unit time by adopting the AI intelligent predictor based on multiple setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage;
for example, the intelligent AI predictor for intelligently predicting the average consumption flow rate of the wireless relay device per unit time based on the various setting parameters of the wireless relay device and the various passenger carrying state information of the closed carriage comprises: the method comprises the steps of respectively performing binary value conversion on various setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage, and then inputting the binary value conversion to the AI intelligent predictor in parallel;
the auxiliary control mechanism is respectively connected with the wireless relay equipment and the intelligent prediction mechanism and is used for starting a standby relay device of the wireless relay equipment when the difference value between the received average consumption flow of the wireless relay equipment in unit time and the maximum throughput of the wireless relay equipment in unit time is smaller than or equal to a set difference value threshold;
the auxiliary control mechanism is further used for suspending starting a standby relay device of the wireless relay device when the difference between the received average consumption flow of the wireless relay device in unit time and the maximum throughput of the wireless relay device in unit time is larger than the set difference threshold;
the method for acquiring the passenger carrying state information of the closed carriage comprises the steps of: the panoramic camera shooting mechanism arranged in the closed carriage is used for identifying the number of network terminals existing in the closed carriage and used as the number of network terminals for visual analysis;
the intelligent AI predictor is used for intelligently predicting the average consumption flow of the wireless relay equipment in unit time based on various setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage, and the intelligent AI predictor comprises the following steps: and inputting a plurality of setting parameters of the wireless relay device and various passenger carrying state information of the closed carriage into the AI intelligent predictor in parallel to execute the AI intelligent predictor, and obtaining the average consumption flow of the wireless relay device per unit time output by the AI intelligent predictor.
Example 2
Fig. 2 is a block diagram showing the structure of a relay control system for a wireless communication network according to embodiment 2 of the present invention.
In comparison with fig. 1, the relay control system for a wireless communication network in fig. 2 may further include:
the current sensing device is respectively connected with the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism and is used for respectively measuring the current real-time current values of the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism;
for example, an SOC chip may be optionally used to implement the current sensing device, for respectively measuring the current real-time current values of the parameter analysis device, the state acquisition device, the multiple learning mechanism, and the intelligent prediction mechanism;
the current sensing device is respectively connected with the parameter analysis device, the state acquisition device, the multiple learning mechanism and the intelligent prediction mechanism, and is used for respectively measuring the current real-time current values of the parameter analysis device, the state acquisition device, the multiple learning mechanism and the intelligent prediction mechanism, wherein the current real-time current values comprise: the current sensing device comprises a plurality of current measuring units which are respectively connected with the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism so as to finish the respective measurement of the current real-time current values of the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism;
the current sensing device comprises a plurality of current measuring units, and the current measuring units are respectively connected with the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism to finish the respective measurement of the current real-time current values of the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism, wherein the respective measurement comprises the following steps: the current measuring units are a plurality of current sensing circuits and are respectively connected with the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism so as to finish the respective measurement of the current real-time current values of the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism;
the plurality of current measurement units are a plurality of current sensing circuits and are used for being respectively connected with the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism, so that the respective measurement of the current real-time current values of the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism is completed, and the respective measurement comprises the following steps: the structures of the plurality of current sensing circuits are the same;
the current measuring units are a plurality of current sensing circuits and are used for being respectively connected with the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism, so that the current real-time current values of the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism are respectively measured, and the current real-time current values of the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism are also: the plurality of current sensing circuits have the same current measurement upper limit value and current measurement lower limit value.
Example 3
Fig. 3 is a block diagram showing the structure of a relay control system for a wireless communication network according to embodiment 3 of the present invention.
In comparison with fig. 1, the relay control system for a wireless communication network in fig. 3 may further include:
the real-time display component is respectively connected with the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the multiple current sensing circuits of the intelligent prediction mechanism and is used for displaying the current real-time current values of the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism in real time;
the real-time display component is respectively connected with the parameter analysis device, the state acquisition device, the multiple learning mechanism and the multiple current sensing circuits of the intelligent prediction mechanism, and is used for displaying the current real-time current values of the parameter analysis device, the state acquisition device, the multiple learning mechanism and the intelligent prediction mechanism in real time, wherein the current real-time current values comprise: the real-time display component is an LED display array formed by a plurality of LED display units;
and wherein the real-time display part is respectively connected with the parameter analysis device, the state acquisition device, the multiple learning mechanism and the multiple current sensing circuits of the intelligent prediction mechanism, and is used for displaying respective current real-time current values of the parameter analysis device, the state acquisition device, the multiple learning mechanism and the intelligent prediction mechanism in real time, and the current real-time current values comprise: the real-time display component is an LCD display array formed by a plurality of LCD display units.
In addition, in the relay control system for a wireless communication network, the intelligent prediction of the average consumption flow rate per unit time of the wireless relay device based on the plurality of setting parameters of the wireless relay device and the various passenger carrying state information of the closed compartment by using the AI intelligent predictor further comprises: and adopting MATLAB tool box simulation to realize the data processing process of intelligently predicting the average consumption flow of the wireless relay equipment in unit time by adopting the AI intelligent predictor based on various setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage.
From this, the outstanding substantial features and significant progress of the technical solution of the invention are shown as follows:
first,: performing multiple times of learning on a feedforward neural network to obtain an AI intelligent predictor, wherein the times of learning of the feedforward neural network are positively correlated with the maximum throughput of the wireless relay equipment in unit time, so that the structure customization of the feedforward neural network of different wireless relay equipment is realized;
secondly: the AI intelligent predictor is used for intelligently predicting the average consumption flow of the wireless relay equipment in unit time based on a plurality of setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage, so that reliable data is provided for the management of the relay equipment in the subsequent closed carriage;
again: and when the difference value between the average consumption flow of the wireless relay equipment in unit time and the maximum throughput of the wireless relay equipment in unit time, which is intelligently predicted by the auxiliary control mechanism, is smaller than or equal to a set difference value threshold, starting a standby relay device of the wireless relay equipment, thereby ensuring the wireless communication efficiency in a closed carriage and simultaneously avoiding occupying excessive relay devices.
The relay control system for the wireless communication network aims at the technical problem that a control mechanism of the opening time of the standby relay device is lagged in the prior art, the average consumption flow of the wireless relay device in unit time of future time is intelligently predicted by adopting the intelligent prediction model with a customized structure, and when the difference value between the average consumption flow and the maximum throughput of the wireless relay device in unit time is smaller than or equal to a set difference value threshold, the standby relay device of the wireless relay device is opened, so that the wireless communication efficiency in a closed carriage is ensured, and meanwhile, the situation that too many relay devices are occupied is avoided.
In addition, the above-described embodiments are described for easy understanding of the present invention, and the present invention is not limited to the above-described embodiments. On the contrary, the invention is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims, which scope is to be accorded the broadest interpretation so as to encompass such modifications and equivalent structures as is permitted under the law.
Claims (9)
1. A relay control system for a wireless communication network, the system comprising:
the wireless relay device is arranged inside the closed compartment and is used for providing an access interface of a wireless communication network for passengers inside the closed compartment;
the parameter analysis device is connected with the wireless relay device and is used for acquiring a plurality of setting parameters of the wireless relay device, wherein the plurality of setting parameters of the wireless relay device comprise the maximum throughput of unit time of the wireless relay device, the maximum operation amount of an operation core and the number of antennas;
the state acquisition equipment is connected with the control console of the closed carriage and used for acquiring various passenger carrying state information of the closed carriage, wherein the various passenger carrying state information of the closed carriage comprises the current passenger carrying number of the closed carriage, the passenger number of different age groups and the number of network terminals for visual analysis;
a multiple learning mechanism for performing multiple learning on a feedforward neural network to obtain an AI intelligent predictor, the number of learning of the feedforward neural network being positively correlated with a maximum throughput per unit time of the wireless relay device;
the intelligent prediction mechanism is respectively connected with the parameter analysis equipment, the state acquisition equipment and the multiple learning mechanism and is used for intelligently predicting the average consumption flow rate of the wireless relay equipment in unit time by adopting the AI intelligent predictor based on multiple setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage;
the auxiliary control mechanism is respectively connected with the wireless relay equipment and the intelligent prediction mechanism and is used for starting a standby relay device of the wireless relay equipment when the difference value between the received average consumption flow of the wireless relay equipment in unit time and the maximum throughput of the wireless relay equipment in unit time is smaller than or equal to a set difference value threshold;
the auxiliary control mechanism is further used for suspending starting a standby relay device of the wireless relay device when the difference between the received average consumption flow of the wireless relay device in unit time and the maximum throughput of the wireless relay device in unit time is larger than the set difference threshold;
the method for acquiring the passenger carrying state information of the closed carriage comprises the steps of: and the panoramic camera mechanism arranged in the closed carriage is used for identifying the number of network terminals existing in the closed carriage and is used as the number of network terminals for visual analysis.
2. The relay control system for a wireless communication network according to claim 1, wherein:
the intelligent AI predictor is used for intelligently predicting the average consumption flow of the wireless relay equipment in unit time based on various setting parameters of the wireless relay equipment and various passenger carrying state information of the closed carriage, and the intelligent AI predictor comprises the following steps: and inputting a plurality of setting parameters of the wireless relay device and various passenger carrying state information of the closed carriage into the AI intelligent predictor in parallel to execute the AI intelligent predictor, and obtaining the average consumption flow of the wireless relay device per unit time output by the AI intelligent predictor.
3. The relay control system for a wireless communication network as claimed in claim 2, wherein the system further comprises:
the current sensing device is respectively connected with the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism and is used for respectively measuring the current real-time current values of the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism;
the current sensing device is respectively connected with the parameter analysis device, the state acquisition device, the multiple learning mechanism and the intelligent prediction mechanism, and is used for respectively measuring the current real-time current values of the parameter analysis device, the state acquisition device, the multiple learning mechanism and the intelligent prediction mechanism, wherein the current real-time current values comprise: the current sensing device comprises a plurality of current measuring units which are respectively connected with the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism so as to finish the respective measurement of the current real-time current values of the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism.
4. A relay control system for a wireless communication network as claimed in claim 3, wherein:
the current sensing device comprises a plurality of current measuring units, which are respectively connected with the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism to finish the respective measurement of the current real-time current values of the parameter analyzing device, the state collecting device, the multiple learning mechanism and the intelligent prediction mechanism, wherein the respective measurement comprises the following steps: the current measuring units are a plurality of current sensing circuits and are used for being respectively connected with the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism so as to finish the respective measurement of the current real-time current values of the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism.
5. The relay control system for a wireless communication network as claimed in claim 4, wherein:
the plurality of current measuring units are a plurality of current sensing circuits and are used for being respectively connected with the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism, so that the current real-time current values of the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism are respectively measured, and the current real-time current values comprise: the plurality of current sensing circuits are identical in structure.
6. The relay control system for a wireless communication network as claimed in claim 5, wherein:
the plurality of current measuring units are a plurality of current sensing circuits and are used for being respectively connected with the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism so as to finish the respective measurement of the current real-time current values of the parameter analyzing equipment, the state collecting equipment, the multiple learning mechanism and the intelligent prediction mechanism, and the method further comprises the following steps: the plurality of current sensing circuits have the same current measurement upper limit value and current measurement lower limit value.
7. A relay control system for a wireless communication network according to any of claims 3-6, wherein the system further comprises:
and the real-time display component is respectively connected with the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the multiple current sensing circuits of the intelligent prediction mechanism and is used for displaying the current real-time current values of the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism in real time.
8. The relay control system for a wireless communication network as claimed in claim 7, wherein:
the real-time display part is respectively connected with the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the multiple current sensing circuits of the intelligent prediction mechanism and is used for displaying the current real-time current values of the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism in real time, wherein the current real-time current values comprise the following components: the real-time display component is an LED display array formed by a plurality of LED display units.
9. The relay control system for a wireless communication network as claimed in claim 7, wherein:
the real-time display part is respectively connected with the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the multiple current sensing circuits of the intelligent prediction mechanism and is used for displaying the current real-time current values of the parameter analysis equipment, the state acquisition equipment, the multiple learning mechanism and the intelligent prediction mechanism in real time, wherein the current real-time current values comprise the following components: the real-time display component is an LCD display array formed by a plurality of LCD display units.
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