CN115149982A - Resource optimization method, system and storage medium for multi-user indoor power line communication - Google Patents

Resource optimization method, system and storage medium for multi-user indoor power line communication Download PDF

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CN115149982A
CN115149982A CN202210540784.1A CN202210540784A CN115149982A CN 115149982 A CN115149982 A CN 115149982A CN 202210540784 A CN202210540784 A CN 202210540784A CN 115149982 A CN115149982 A CN 115149982A
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optimal
network configuration
user equipment
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CN115149982B (en
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王祥
李铮
洪海敏
逄林
汤志颖
袁望星
李祥
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Beijing Smartchip Microelectronics Technology Co Ltd
China Gridcom Co Ltd
Shenzhen Zhixin Microelectronics Technology Co Ltd
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Beijing Smartchip Microelectronics Technology Co Ltd
China Gridcom Co Ltd
Shenzhen Zhixin Microelectronics Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B3/00—Line transmission systems
    • H04B3/54—Systems for transmission via power distribution lines
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/08—Configuration management of networks or network elements
    • H04L41/0803—Configuration setting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/142—Network analysis or design using statistical or mathematical methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a resource optimization method, a resource optimization system and a storage medium for multi-user indoor power line communication, wherein the method comprises the following steps: randomly distributing sub-channels for each user equipment, and determining the network configuration of each sub-channel; calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, and searching the optimal network configuration according to the optimal value of the transmitting power under the current network configuration; acquiring an optimal value of transmitting power of each user equipment under the optimal network configuration; and determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value. The method can ensure that each user equipment uses the optimal sub-channel for transmission in most of time, thereby ensuring that the power line communication system is close to the optimal effect, reducing the signaling overhead of the system and enhancing the expandability of the system.

Description

Resource optimization method, system and storage medium for multi-user indoor power line communication
Technical Field
The present invention relates to the field of power line communication technologies, and in particular, to a resource optimization method for multi-user indoor power line communication, a computer-readable storage medium, a resource optimization system for multi-user indoor power line communication, and a power line communication system.
Background
With the development of emerging technologies such as the internet of things, power line communication is used as an infrastructure without rewiring, and the power line communication technology has the advantages of simple networking, low cost, high safety, easiness in implementation and the like, can be used for low-speed control such as remote meter reading and home automation, and is also suitable for high-speed information transmission such as data, the internet, audio and video multimedia and the like. The power line is utilized to transmit data information, so that not only can the operation cost be reduced, but also the cost for constructing a new communication network can be reduced.
In the related art, for a multi-user power line communication system, a centralized deployment of user equipment is generally adopted for deployment. Centralized deployment, however, requires the use of a centralized server, which is very costly. In addition, with the increase of traffic volume in a centralized architecture, when the system needs to be expanded, the expansion can be performed only by expanding the servers of the same architecture horizontally. Therefore, the centrally deployed power line communication system generates a large signaling overhead and is poorly scalable.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art. Therefore, a first objective of the present invention is to provide a resource optimization method for multi-user indoor power line communication, which enables each user equipment to use an optimal sub-channel for transmission most of the time, thereby enabling the power line communication system to be close to optimal utility, reducing signaling overhead of the system, and enhancing scalability of the system.
A second object of the invention is to propose a computer-readable storage medium.
A third objective of the present invention is to provide a resource optimization system for multi-user indoor power line communication.
A fourth object of the present invention is to provide a power line communication system.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides a resource optimization method for multi-user indoor power line communication, including: randomly distributing sub-channels for each user equipment, and determining the network configuration of each sub-channel; calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, and searching the optimal network configuration according to the optimal value of the transmitting power under the current network configuration; acquiring an optimal value of the transmitting power of each user equipment under the optimal network configuration; and determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value.
According to the resource optimization method of the multi-user indoor power line communication, sub-channels are randomly distributed to each user equipment, and the network configuration of each sub-channel is determined; calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, and searching the optimal network configuration according to the optimal value of the transmitting power under the current network configuration; acquiring an optimal value of transmitting power of each user equipment under the optimal network configuration; and determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value. Therefore, the method can ensure that each user equipment uses the optimal sub-channel for transmission in most of time, thereby ensuring that the power line communication system is close to the optimal utility, reducing the signaling overhead of the system and enhancing the expandability of the system.
In addition, the resource optimization method for multi-user indoor power line communication according to the above embodiment of the present invention may further have the following additional technical features:
according to an embodiment of the present invention, calculating an optimal value of the transmit power of each ue in its corresponding current network configuration includes: establishing a mixed integer nonlinear programming model based on a network utility function; determining a power distribution model according to the mixed integer nonlinear programming model; keeping the current network configuration unchanged, converting a power distribution model into an unconstrained optimization problem by adopting a Lagrangian function, and determining an optimal value of a Lagrangian multiplier; adopting Karush-Kuhn-Tucker according to the optimal value of the Lagrange multiplier the conditions determine the optimum value of the transmit power under the current network configuration.
According to one embodiment of the present invention, determining an optimal network configuration according to an optimal value of transmit power under a current network configuration comprises: keeping the optimal value of the transmitting power under the current network configuration unchanged, and adding a weighted entropy item to the optimal system network utility value under the current network configuration to obtain a network configuration model; and solving the network configuration model by adopting Karush-Kuhn-Tucker conditions to determine the optimal network configuration.
According to one embodiment of the invention, the mixed integer nonlinear programming model is as follows:
Figure BDA0003648205080000021
Figure BDA0003648205080000022
Figure BDA0003648205080000023
Figure BDA0003648205080000024
wherein NU (-) represents a system network utility value; alpha represents weight, and alpha is more than or equal to 0 and less than or equal to 1; r is n,k Representing the transmission rate of device n on subchannel k; x is a radical of a fluorine atom n,k Representing a binary variable, x when device n selects subchannel k n,k =1, otherwise x n,k ＝0；p n,k Indicating the allocated transmit power;
Figure BDA0003648205080000031
represents the circuit consumed power;
Figure BDA0003648205080000032
representing the quality of service requirement of device n;
Figure BDA0003648205080000033
representing the maximum value of the device n transmit power.
According to one embodiment of the invention, the power allocation model type is converted into an unconstrained optimization problem by the following formula:
Figure BDA0003648205080000034
wherein λ is n And mu n Representing the Lagrange multiplier, alpha representing the weight, 0 ≦ alpha ≦ 1 n,k Representing the transmission rate of device n on subchannel k; p is a radical of n,k Indicating the allocated transmit power;
Figure BDA0003648205080000035
represents the power consumed by the circuit;
Figure BDA0003648205080000036
representing the quality of service requirement of device n;
Figure BDA0003648205080000037
representing the maximum value of the device n transmit power.
According to one embodiment of the invention, the network configuration model is obtained by the following formula:
Figure BDA0003648205080000038
Figure BDA0003648205080000039
wherein NU (c) represents a weight of the network configuration c,
Figure BDA00036482050800000310
representing a weighted entropy term, beta representing a weight of the entropy term, pr c Representing the percentage of time the system is in network configuration C, which represents the set of network configurations.
According to an embodiment of the present invention, determining whether to update the subchannel set of the user equipment according to the optimal system network utility value includes: generating an exponential distribution timer according to the optimal system network utility value and the subchannel set selected by the current user equipment; when the exponential distribution timer of the current user equipment finishes timing, determining the release probability of the sub-channel in the sub-channel set selected by the current user equipment; and when the release probability of the sub-channel is greater than a preset threshold value, releasing the sub-channel from the sub-channel set, updating the sub-channel set of the current user equipment, randomly allocating a new sub-channel for the current user equipment from the idle sub-channels, and adding the new sub-channel into the sub-channel set selected by the current user equipment.
According to one embodiment of the invention, the exponential distribution timer is generated by the following formula:
Figure BDA00036482050800000311
wherein, the timer represents an exponential distribution timer,
Figure BDA00036482050800000312
representing an optimal system network utility value of a current sub-channel of current user equipment; σ denotes a constant, β denotes a weight of the entropy term, k i Any one of the set of sub-channels, K, representing the current user equipment selection n Represents the set of subchannels selected by the user equipment n, i being a positive integer less than or equal to K, K representing the number of available subchannels.
According to one embodiment of the present invention, the release probability of a sub-channel in the set of sub-channels selected by the current user equipment is determined by the following formula:
Figure BDA0003648205080000041
wherein, pr n,k Representing the probability of release of subchannel k in the set of subchannels selected by user equipment n.
To achieve the above object, a second aspect of the present invention provides a computer-readable storage medium, on which a resource optimization program for multi-user indoor power line communication is stored, and when executed by a processor, the resource optimization program for multi-user indoor power line communication implements the resource optimization method for multi-user indoor power line communication.
According to the computer-readable storage medium of the embodiment of the invention, by executing the resource optimization method of multi-user indoor power line communication, the power line communication system can be close to the optimal effect, the signaling overhead of the system is reduced, and the expandability of the system is enhanced.
In order to achieve the above object, a third embodiment of the present invention provides a resource optimization system for multi-user indoor power line communication, where a first determining module is configured to randomly allocate sub-channels to each user equipment, and determine a network configuration of each sub-channel; the calculation module is used for calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment; the second determining module is used for searching the optimal network configuration according to the optimal value of the transmitting power under the current network configuration; the acquisition module is used for acquiring the optimal value of the transmitting power of each user equipment under the optimal network configuration; and the third determining module is used for determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value.
According to the resource optimization system for multi-user indoor power line communication, a first determining module randomly allocates sub-channels to each user equipment and determines the network configuration of each sub-channel, a calculating module calculates the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, a second determining module searches for the optimal network configuration according to the optimal value of the transmitting power under the current network configuration, an obtaining module obtains the optimal value of the transmitting power of each user equipment under the optimal network configuration, a third determining module determines the optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and whether the sub-channel set of the user equipment is updated or not is determined according to the optimal system network utility value. Therefore, the system can enable each user equipment to use the optimal sub-channel for transmission most of the time, thereby enabling the power line communication system to be close to the optimal effect, reducing the signaling overhead of the system and enhancing the expandability of the system.
In order to achieve the above object, a fourth aspect of the present invention provides a power line communication system, which includes a memory, a processor, and a resource optimization program for multi-user indoor power line communication stored in the memory and executable on the processor, where when the processor executes the resource optimization program for multi-user indoor power line communication, the resource optimization method for multi-user indoor power line communication is implemented.
According to the power line communication system disclosed by the embodiment of the invention, by executing the resource optimization method of multi-user indoor power line communication, each user equipment can use the optimal sub-channel for transmission in most of time, so that the power line communication system is close to the optimal effect, the signaling overhead of the system is reduced, and the expandability of the system is enhanced.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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Fig. 1 is a flowchart of a resource optimization method for multi-user indoor power line communication according to an embodiment of the present invention;
FIG. 2 is a flow chart of calculating an optimal value of user equipment transmit power according to one embodiment of the present invention;
FIG. 3 is a flow diagram of determining an optimal network configuration according to one embodiment of the invention;
fig. 4 is a flowchart for determining whether to replace a current sub-channel of a user equipment according to one embodiment of the present invention;
fig. 5 is a block diagram illustrating a resource optimization system for multi-user indoor power line communication according to an embodiment of the present invention;
fig. 6 is a block diagram of a power line communication system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
A resource optimization method for multi-user indoor power line communication, a computer-readable storage medium, a resource optimization system for multi-user indoor power line communication, and a power line communication system according to embodiments of the present invention are described below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a resource optimization method for multi-user indoor power line communication according to an embodiment of the present invention.
As shown in fig. 1, a resource optimization method for multi-user indoor power line communication according to an embodiment of the present invention may include the following steps:
step S101, randomly distributing sub-channels for each user equipment, and determining the network configuration of each sub-channel.
Step S102, calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, and searching the optimal network configuration according to the optimal value of the transmitting power under the current network configuration.
Step S103, obtaining an optimal value of the transmission power of each ue in the optimal network configuration.
And step S104, determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value.
Specifically, in the multi-user indoor power line communication system according to the embodiment of the present invention, assuming that there are N user equipments, distributed deployment is adopted, the number of available subchannels is K, and the number of subchannels is greater than the number of devices, that is, K > N. To avoid interference between different devices, each subchannel can only be used by one device. For example, in an initial state, the user equipment N randomly selects a subchannel K, where N ∈ N, K ∈ K, and may determine the network configuration of the subchannel K. When all the ues in the system select the sub-channel, the set of sub-channels of the ue n is Kn.
Further, according to the current network configuration of the user equipment n, calculating the optimal value of the transmission power of the user equipment n. And then searching the optimal network configuration of the user equipment n in the subchannel k according to the optimal value of the transmitting power of the user equipment n. After finding the optimal network configuration of the user equipment n in the sub-channel k, the optimal value of the transmission power of the user equipment n in the optimal network configuration can be obtained. Based on the same principle, the optimal value of the transmission power of each user equipment in the system under the optimal network configuration can be obtained.
After the optimal value of the transmission power of each user equipment under the optimal network configuration is obtained, the optimal system network utility value can be determined according to the optimal value of the transmission power of each user equipment under the optimal network configuration, and the release probability of the sub-channel in the sub-channel set Kn selected by the current user is calculated according to the optimal system network utility value. And when the releasing probability of the sub-channel is larger than a certain value, updating the sub-channel set of the current user equipment.
Therefore, by calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, searching for the optimal network configuration according to the optimal value of the transmitting power under the current network configuration, acquiring the optimal value of the transmitting power of each user equipment under the optimal network configuration, determining the optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value, each user equipment can use the optimal subchannel for transmission in most of time, so that the power line communication system is close to the optimal utility, the signaling cost of the system is reduced, and the expandability of the system is enhanced.
The following describes a specific process of the resource optimization method of the present invention in detail.
According to an embodiment of the present invention, as shown in fig. 2, calculating an optimal value of the transmit power of each ue in its corresponding current network configuration may include the following steps:
step S201, a mixed integer nonlinear programming model is established based on a network utility function.
According to one embodiment of the invention, the mixed integer nonlinear programming model is as follows:
Figure BDA0003648205080000071
Figure BDA0003648205080000072
Figure BDA0003648205080000073
Figure BDA0003648205080000074
wherein NU (-) represents a system network utility value; alpha represents weight, and alpha is more than or equal to 0 and less than or equal to 1; r n,k Representing the transmission rate of device n on subchannel k; x is the number of n,k Representing a binary variable, x when device n selects subchannel k n,k =1, otherwise x n,k ＝0；p n,k Indicating the allocated transmit power;
Figure BDA0003648205080000075
represents the power consumed by the circuit;
Figure BDA0003648205080000076
representing the quality of service requirement of device n;
Figure BDA0003648205080000077
representing the maximum value of the device n transmit power.
In particular, although energy supply is sufficient in a power line communication network, it is still important to improve energy efficiency of the network in order to avoid wasting energy. In an embodiment of the present invention, the energy efficiency of the whole system can be reflected by a network utility function (NU), the set C is used to represent the set of the whole possible network configurations of the powerline communication system, and a certain assignment x of a sub-channel in the system is used as a network configuration C, so that C ∈ C. When device n selects subchannel k, i.e. x n,k =1, the mixed integer nonlinear programming model described above can be converted into:
Figure BDA0003648205080000078
Figure BDA0003648205080000079
Figure BDA00036482050800000710
c∈C.
wherein,
Figure BDA00036482050800000711
representing the set of active sub-channels selected by device n under network configuration c.
Step S202, determining a power distribution model according to the mixed integer nonlinear programming model.
And step S203, keeping the current network configuration unchanged, converting the power distribution model into an unconstrained optimization problem by adopting a Lagrangian function, and determining the optimal value of a Lagrangian multiplier.
According to one embodiment of the invention, the power allocation model is converted into an unconstrained optimization problem by the following formula:
Figure BDA00036482050800000712
wherein λ is n And mu n Representing the Lagrange multiplier, alpha representing the weight, 0 ≦ alpha ≦ 1 n,k Representing the transmission rate of device n on subchannel k; p is a radical of n,k Indicating the allocated transmit power;
Figure BDA0003648205080000081
represents the power consumed by the circuit;
Figure BDA0003648205080000082
representing the quality of service requirement of device n;
Figure BDA0003648205080000083
representing the maximum value of the device n transmit power.
Specifically, the user equipment n keeps the current network configuration c unchanged, and adopts the formulaThe power allocation model will be transformed into an unconstrained optimization problem. The optimal value of the transmission power of the user equipment n under the current network configuration c and the Lagrange multiplier lambda n 、μ n Is related to the value of (a), it is therefore necessary to first find the optimum value of the lagrange multiplier
Figure BDA0003648205080000084
And
Figure BDA0003648205080000085
in an embodiment of the present invention, the optimal value of the lagrangian multiplier can be solved by the steepest descent method, and the specific formula is as follows:
Figure BDA0003648205080000086
Figure BDA0003648205080000087
where κ and γ are positive steps small enough, and t is the iteration index value. Since the lagrange function of the unconstrained optimization problem described above is a convex function, the above formula pairs
Figure BDA0003648205080000088
Convergence is carried out to obtain the optimal value of the Lagrange multiplier
Figure BDA0003648205080000089
And
Figure BDA00036482050800000810
and S204, determining the optimal value of the transmitting power under the current network configuration by adopting a Karush-Kuhn-Tucker condition according to the optimal value of the Lagrange multiplier.
The optimal value of the Lagrangian multiplier is found in the above step S203
Figure BDA00036482050800000811
And
Figure BDA00036482050800000812
then, the optimal value of the Lagrange multiplier is obtained by adopting the Karush-Kuhn-Tucker condition
Figure BDA00036482050800000813
And
Figure BDA00036482050800000814
substituting the following formula, the optimal value of the transmitting power of the device n under the current network configuration can be obtained
Figure BDA00036482050800000815
The concrete formula is as follows:
Figure BDA00036482050800000816
wherein epsilon n Is the network efficiency value, g n,k Is the signal-to-noise ratio of device n at channel k.
According to an embodiment of the present invention, as shown in fig. 3, determining the optimal network configuration according to the optimal value of the transmission power under the current network configuration may include the following steps:
step S301, keeping the optimal value of the transmitting power under the current network configuration unchanged, and adding a weighted entropy item to the optimal system network utility value under the current network configuration to obtain a network configuration model.
According to one embodiment of the invention, the network configuration model is obtained by the following formula:
Figure BDA0003648205080000091
Figure BDA0003648205080000092
wherein NU (c) represents a weight of the network configuration c,
Figure BDA0003648205080000093
representing a weighted entropy term, beta representing a weight of the entropy term, pr c Representing the percentage of time the system is in network configuration C, which represents the set of network configurations.
And step S302, solving the network configuration model by adopting a Karush-Kuhn-Tucker condition, and determining the optimal network configuration.
Specifically, the network configuration model in step S301 is solved by using the Karush-Kuhn-Tucker condition, so that the optimal solution of the time percentage of the system in the network configuration c can be obtained
Figure BDA0003648205080000094
The expression is specifically as follows:
Figure BDA0003648205080000095
where C' is an element of C, the product form of the optimal solution can be abstracted as the smooth distribution of the Markov chain at a certain time. Thus, the optimal network configuration for the system can be determined by the optimal solution for the percentage of time the system is in network configuration c.
Further, the optimal value of the transmission power of each user equipment under the optimal network configuration of the system can be respectively obtained.
According to an embodiment of the present invention, as shown in fig. 4, determining whether to update the subchannel set of the user equipment according to the optimal system network utility value may include the following steps:
step S401, an exponential distribution timer is generated according to the optimal system network utility value and the subchannel set selected by the current user equipment.
According to one embodiment of the invention, the exponential distribution timer is generated by the following formula:
Figure BDA0003648205080000096
wherein,the timer represents an exponential distribution timer which is,
Figure BDA0003648205080000097
representing an optimal system network utility value of a current sub-channel of current user equipment; σ denotes a constant, β denotes a weight of the entropy term, k i Representing any one of a set of sub-channels, K, currently selected by the user equipment n Represents the set of subchannels selected by the user equipment n, i being a positive integer less than or equal to K, K representing the number of available subchannels.
Specifically, in the initial state, the user equipment n randomly selects one subchannel K to join the set K n And generates a current configuration c when the network utility of user equipment n is z n,k ，k∈K n . After obtaining the optimal value of the transmit power in the optimal network configuration, the user equipment n may determine the optimal system network utility value in the current sub-channel according to the optimal value of the transmit power in the optimal network configuration
Figure BDA0003648205080000101
Will be provided with
Figure BDA0003648205080000102
Substituting the above formula, an exponential distribution timer for the ue n can be generated and the countdown can be started.
Step S402, when the exponential distribution timer of the current user equipment finishes timing, determining the release probability of the sub-channel in the sub-channel set selected by the current user equipment.
According to one embodiment of the present invention, the release probability of a sub-channel in the set of sub-channels selected by the current user equipment is determined by the following formula:
Figure BDA0003648205080000103
wherein, pr n,k Representing the probability of release of subchannel k in the set of subchannels selected by user equipment n. Through the formula, the sub-letter selected by the user equipment n can be determinedProbability of release of track k.
Step S403, when the release probability of the sub-channel is greater than the preset threshold, releasing the sub-channel from the sub-channel set, updating the sub-channel set of the current user equipment, randomly allocating a new sub-channel for the current user equipment from the idle sub-channels, and adding the new sub-channel into the sub-channel set selected by the current user equipment.
That is, when the release probability of the subchannel k selected by the user equipment n is greater than the preset threshold, the subchannel k is released from the subchannel set Kn, and the subchannel set Kn of the user equipment n is updated. The user equipment n releases the current sub-channel k to enter a hopping state, a new sub-channel can be randomly selected from the idle sub-channels kept active for the user equipment n to be added into the sub-channel set Kn, and then a reset message is broadcasted to the power line communication system. After the power line communication system receives the reset message and other devices complete the current timing process, the network utility value of the power line communication system is calculated in the new network configuration, a new timing variable is generated, and then the power line communication system enters a waiting state. And when the release probability of the sub-channel k selected by the user equipment n is smaller than a preset threshold value, the user equipment n keeps unchanged at the current sub-channel k. Therefore, the user equipment in the system can use the optimal sub-channel for transmission.
Therefore, the resource optimization method of the embodiment can be deployed in a large-scale power line communication system without causing reduction of the utility performance of many networks, and the generated network approximation error is lower in upper bound under the large-scale network configuration.
In summary, according to the resource optimization method for multi-user indoor power line communication in the embodiment of the present invention, sub-channels are randomly allocated to each user equipment, and the network configuration of each sub-channel is determined; calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, and determining the optimal network configuration according to the optimal value of the transmitting power under the current network configuration; acquiring an optimal value of transmitting power of each user equipment under the optimal network configuration; and determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determining whether to replace the current sub-channel of the user equipment according to the optimal system network utility value. Therefore, the method can enable each user equipment to use the optimal sub-channel for transmission most of time, thereby enabling the power line communication system to be close to the optimal effect, reducing the signaling overhead of the system and enhancing the expandability of the system.
The invention further provides a computer readable storage medium corresponding to the above embodiment.
The computer readable storage medium of the embodiment of the present invention stores thereon a resource optimization program for multi-user indoor power line communication, which when executed by a processor implements the above-described resource optimization method for multi-user indoor power line communication.
According to the computer-readable storage medium of the embodiment of the invention, by executing the resource optimization method of multi-user indoor power line communication, the power line communication system can be close to the optimal effect, the signaling overhead of the system is reduced, and the expandability of the system is enhanced.
Corresponding to the embodiment, the invention further provides a resource optimization system for multi-user indoor power line communication.
Fig. 5 is a block diagram illustrating a resource optimization system for multi-user indoor power line communication according to an embodiment of the present invention.
As shown in fig. 5, a resource optimization system 500 for multi-user indoor power line communication according to an embodiment of the present invention may include: a first determination module 510, a calculation module 520, a second determination module 530, an acquisition module 540, and a third determination module 550.
The first determining module 510 is configured to randomly allocate a sub-channel to each ue, and determine a network configuration of each sub-channel. The calculating module 520 is configured to calculate an optimal value of the transmit power of each ue under its corresponding current network configuration. The second determining module 530 is configured to find an optimal network configuration according to the optimal value of the transmit power under the current network configuration. The obtaining module 540 is configured to obtain an optimal value of the transmit power of each ue in the optimal network configuration. The third determining module 550 is configured to determine an optimal system network utility value according to the optimal value of the transmit power under the optimal network configuration, and determine whether to update the subchannel set of the user equipment according to the optimal system network utility value.
According to an embodiment of the present invention, the calculating module 520 calculates an optimal value of the transmit power of each ue in its corresponding current network configuration, specifically, for establishing a mixed integer nonlinear programming model based on a network utility function; determining a power distribution model according to the mixed integer nonlinear programming model; keeping the current network configuration unchanged, converting a power distribution model into an unconstrained optimization problem by adopting a Lagrangian function, and determining an optimal value of a Lagrangian multiplier; and determining the optimal value of the transmitting power under the current network configuration by adopting a Karush-Kuhn-Tucker condition according to the optimal value of the Lagrange multiplier.
According to an embodiment of the present invention, the second determining module 530 determines an optimal network configuration according to the optimal value of the transmit power under the current network configuration, and is specifically configured to keep the optimal value of the transmit power under the current network configuration unchanged, and add a weighted entropy term to the optimal system network utility value under the current network configuration to obtain a network configuration model; and solving the network configuration model by adopting a Karush-Kuhn-Tucker condition to determine the optimal network configuration.
According to one embodiment of the invention, the mixed integer nonlinear programming model is as follows:
Figure BDA0003648205080000121
Figure BDA0003648205080000122
Figure BDA0003648205080000123
Figure BDA0003648205080000124
wherein NU (-) represents a system network utility value; alpha represents weight, and alpha is more than or equal to 0 and less than or equal to 1; r n,k Representing the transmission rate of device n on subchannel k; x is the number of n,k Representing a binary variable, x when device n selects subchannel k n,k =1, otherwise x n,k ＝0；p n,k Indicating the allocated transmit power;
Figure BDA0003648205080000125
represents the power consumed by the circuit;
Figure BDA0003648205080000126
representing the quality of service requirement of device n;
Figure BDA0003648205080000127
representing the maximum value of the device n transmit power.
According to one embodiment of the invention, the calculation module 520 converts the power allocation model into an unconstrained optimization problem by the following formula:
Figure BDA0003648205080000128
wherein λ is n And mu n Representing the Lagrange multiplier, alpha representing the weight, 0 ≦ alpha ≦ 1 n,k Representing the transmission rate of device n on subchannel k; p is a radical of n,k Indicating the allocated transmit power;
Figure BDA0003648205080000129
represents the power consumed by the circuit;
Figure BDA00036482050800001210
representing the quality of service requirement of device n;
Figure BDA00036482050800001211
representing the maximum value of the device n transmit power.
According to one embodiment of the invention, the second determining module 530 obtains the network configuration model by the following formula:
Figure BDA00036482050800001212
Figure BDA00036482050800001213
wherein NU (c) represents a weight of the network configuration c,
Figure BDA00036482050800001214
representing a weighted entropy term, beta representing a weight of the entropy term, pr c Representing the percentage of time the system is in network configuration C, which represents the set of network configurations.
According to an embodiment of the present invention, the third determining module 550 determines whether to update the subchannel set of the user equipment according to the optimal system network utility value, and is specifically configured to generate an exponential distribution timer according to the optimal system network utility value and the subchannel set selected by the current user equipment; when the exponential distribution timer of the current user equipment finishes timing, determining the release probability of the sub-channel in the sub-channel set selected by the current user equipment; and when the release probability of the sub-channel is greater than a preset threshold value, releasing the sub-channel from the sub-channel set, randomly allocating a new sub-channel for the current user equipment from the idle sub-channel in the sub-channel set of the current user equipment, and adding the new sub-channel into the sub-channel set selected by the current user equipment.
According to one embodiment of the invention, the third determining module 550 generates the exponential distribution timer by:
Figure BDA0003648205080000131
wherein, the timer represents an index distribution timer,
Figure BDA0003648205080000132
representing an optimal system network utility value of a current sub-channel of current user equipment; σ denotes a constant, β denotes a weight of the entropy term, k i Representing any one of a set of sub-channels, K, currently selected by the user equipment n Represents a set of subchannels selected by the user equipment n, i is a positive integer equal to or less than K, K represents the number of available subchannels.
According to an embodiment of the present invention, the third determining module 550 determines the releasing probability of the sub-channel in the sub-channel set selected by the current user equipment by the following formula:
Figure BDA0003648205080000133
wherein, pr n,k Representing the probability of release of subchannel k in the set of subchannels selected by user equipment n.
It should be noted that, for details not disclosed in the resource optimization system for multi-user indoor power line communication according to the embodiment of the present invention, please refer to details disclosed in the resource optimization method for multi-user indoor power line communication according to the embodiment of the present invention, and details are not repeated herein.
According to the resource optimization system for multi-user indoor power line communication, a first determining module randomly allocates sub-channels to each user device, determines the network configuration of each sub-channel, a calculating module calculates the optimal value of the transmitting power of each user device under the current network configuration corresponding to each user device, a second determining module determines the optimal network configuration according to the optimal value of the transmitting power under the current network configuration, an obtaining module obtains the optimal value of the transmitting power of each user device under the optimal network configuration, a third determining module determines the optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determines whether to replace the current sub-channels of the user devices according to the optimal system network utility value. Therefore, the system can enable each user equipment to use the optimal sub-channel for transmission most of the time, thereby enabling the power line communication system to be close to the optimal effect, reducing the signaling overhead of the system and enhancing the expandability of the system.
Corresponding to the above embodiment, the present invention further provides a power line communication system.
Fig. 6 is a block diagram of a power line communication system according to an embodiment of the present invention.
As shown in fig. 6, the power line communication system 600 according to the embodiment of the present invention includes a memory 610, a processor 620, and a resource optimization program for multi-user indoor power line communication stored in the memory 610 and executable on the processor 620, where when the processor 620 executes the resource optimization program for multi-user indoor power line communication, the resource optimization method for multi-user indoor power line communication is implemented.
According to the power line communication system disclosed by the embodiment of the invention, by executing the resource optimization method of multi-user indoor power line communication, each user equipment can use the optimal sub-channel for transmission in most of time, so that the power line communication system is close to the optimal effect, the signaling overhead of the system is reduced, and the expandability of the system is enhanced.
It should be noted that the logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise explicitly stated or limited, the terms "mounted," "connected," "fixed," and the like are to be construed broadly, e.g., as being permanently connected, detachably connected, or integral; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (12)

1. A resource optimization method for multi-user indoor power line communication is characterized by comprising the following steps:
randomly distributing sub-channels for each user equipment, and determining the network configuration of each sub-channel;
calculating the optimal value of the transmitting power of each user equipment under the current network configuration corresponding to the user equipment, and searching for the optimal network configuration according to the optimal value of the transmitting power under the current network configuration;
acquiring an optimal value of the transmitting power of each user equipment under the optimal network configuration;
and determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration, and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value.
2. The method of claim 1, wherein calculating the optimal value of the transmit power of each UE in its corresponding current network configuration comprises:
establishing a mixed integer nonlinear programming model based on a network utility function;
determining a power distribution model according to the mixed integer nonlinear programming model;
keeping the current network configuration unchanged, converting the power distribution model into an unconstrained optimization problem by adopting a Lagrangian function, and determining an optimal value of a Lagrangian multiplier;
and determining the optimal value of the transmitting power under the current network configuration by adopting a Karush-Kuhn-Tucker condition according to the optimal value of the Lagrange multiplier.
3. The method of claim 1, wherein determining the optimal network configuration according to the optimal value of the transmit power in the current network configuration comprises:
keeping the optimal value of the transmitting power under the current network configuration unchanged, and adding a weighted entropy item to the optimal system network utility value under the current network configuration to obtain a network configuration model;
and solving the network configuration model by adopting a Karush-Kuhn-Tucker condition to determine the optimal network configuration.
4. The resource optimization method for multi-user indoor power line communication according to claim 2, wherein the mixed integer nonlinear programming model is as follows:
Figure FDA0003648205070000011
Figure FDA0003648205070000012
Figure FDA0003648205070000013
Figure FDA0003648205070000014
wherein NU (-) represents a system network utility value; alpha represents weight, and alpha is more than or equal to 0 and less than or equal to 1; r n,k Representing the transmission rate of device n on subchannel k; x is the number of n,k Representing a binary variable, x when device n selects subchannel k n,k =1, otherwise x n,k ＝0；p n,k Indicating the allocated transmit power;
Figure FDA0003648205070000021
represents the circuit consumed power;
Figure FDA0003648205070000022
representing the quality of service requirements of device n;
Figure FDA0003648205070000023
representing the maximum value of the device n transmit power.
5. The method of resource optimization for multi-user indoor power line communication according to claim 2, wherein the power allocation model is converted into an unconstrained optimization problem by the following formula:
Figure FDA0003648205070000024
wherein λ is n And mu n Representing Lagrange multipliers, alpha represents weight, alpha is more than or equal to 0 and less than or equal to 1 n,k Representing the transmission rate of device n on subchannel k; p is a radical of formula n,k Indicating the allocated transmit power;
Figure FDA0003648205070000025
represents the power consumed by the circuit;
Figure FDA0003648205070000026
representing the quality of service requirements of device n;
Figure FDA0003648205070000027
representing the maximum value of the device n transmit power.
6. The method of resource optimization for multi-user indoor power line communication according to claim 3, wherein the network configuration model is obtained by the following formula:
Figure FDA0003648205070000028
Figure FDA0003648205070000029
wherein NU (c) represents a weight of the network configuration c,
Figure FDA00036482050700000210
representing a weighted entropy term, beta representing a weight of the entropy term, pr c Representing the percentage of time the system is in network configuration C, which represents the set of network configurations.
7. The method of claim 1, wherein determining whether to update the set of subchannels of the user equipment based on the optimal system network utility value comprises:
generating an exponential distribution timer according to the optimal system network utility value and the subchannel set selected by the current user equipment;
when the exponential distribution timer of the current user equipment finishes timing, determining the release probability of the sub-channel in the sub-channel set selected by the current user equipment;
and when the release probability of the sub-channel is greater than a preset threshold value, releasing the sub-channel from the sub-channel set, updating the sub-channel set of the current user equipment, randomly allocating a new sub-channel for the current user equipment from the idle sub-channels, and adding the new sub-channel into the sub-channel set selected by the current user equipment.
8. The method for resource optimization of multi-user indoor power line communication according to claim 7, wherein the exponential distribution timer is generated by the following formula:
Figure FDA0003648205070000031
wherein, the timer represents the exponential distribution timer,
Figure FDA0003648205070000032
representing an optimal system network utility value of a current sub-channel of current user equipment; σ denotes a constant, β denotes a weight of the entropy term, k i Any one of the set of sub-channels, K, representing the current user equipment selection n Represents the set of subchannels selected by the user equipment n, i being a positive integer less than or equal to K, K representing the number of available subchannels.
9. The method of claim 8, wherein the probability of releasing a subchannel in the set of subchannels selected by the current ue is determined according to the following formula:
Figure FDA0003648205070000033
wherein, pr n,k Representing the probability of release of subchannel k in the set of subchannels selected by user equipment n.
10. A computer-readable storage medium, having stored thereon a resource optimization program for multi-user indoor power line communication, which when executed by a processor, implements the resource optimization method for multi-user indoor power line communication according to any one of claims 1 to 9.
11. A resource optimization system for multi-user indoor power line communication is characterized in that,
a first determining module, configured to randomly allocate sub-channels to each user equipment, and determine a network configuration of each sub-channel;
a calculating module, configured to calculate an optimal value of transmit power of each ue in a current network configuration corresponding to the ue;
the second determining module is used for searching the optimal network configuration according to the optimal value of the transmitting power under the current network configuration;
an obtaining module, configured to obtain an optimal value of transmit power of each user equipment in the optimal network configuration;
and the third determining module is used for determining an optimal system network utility value according to the optimal value of the transmitting power under the optimal network configuration and determining whether to update the subchannel set of the user equipment according to the optimal system network utility value.
12. A power line communication system, comprising a memory, a processor and a resource optimization program for multi-user indoor power line communication stored in the memory and executable on the processor, wherein the processor implements the resource optimization method for multi-user indoor power line communication according to any one of claims 1 to 9 when executing the resource optimization program for multi-user indoor power line communication.
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