WO2020215801A1 - Procédé et dispositif de distribution optimisée d'efficacité énergétique de réseau de relais, terminal, et support de stockage - Google Patents

Procédé et dispositif de distribution optimisée d'efficacité énergétique de réseau de relais, terminal, et support de stockage Download PDF

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WO2020215801A1
WO2020215801A1 PCT/CN2019/130584 CN2019130584W WO2020215801A1 WO 2020215801 A1 WO2020215801 A1 WO 2020215801A1 CN 2019130584 W CN2019130584 W CN 2019130584W WO 2020215801 A1 WO2020215801 A1 WO 2020215801A1
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source
information
energy
receiving end
channel gain
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PCT/CN2019/130584
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English (en)
Chinese (zh)
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罗蔚然
申妍燕
龚世民
朱国普
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深圳先进技术研究院
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • 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

Definitions

  • the present invention relates to the technical field of resource optimization of wireless energy-carrying relay networks, and in particular to a method, device, terminal and storage medium for optimal allocation of energy efficiency of a relay network.
  • Wireless energy-carrying communication combines communication technology and wireless energy harvesting technology. The purpose is to realize the simultaneous transmission of information and energy, which can bring huge benefits in terms of spectrum efficiency, energy consumption, and interference management.
  • nodes in wireless networks can Use wireless energy-carrying communication to collect energy to extend its service life.
  • the concept of green communication is increasingly accepted by people. While ensuring that the communication network can provide users with high-speed communication services, the energy consumption of the network is reduced as much as possible, and the operation cost and energy consumption of the communication network are reduced, which is beneficial to the protection of the environment and the realization of green development.
  • the energy efficiency of the system is optimized only by using a simple linear energy receiving model, and the obtained results have a large deviation from the actual situation.
  • eavesdropping is not considered.
  • the existing problems of the user reduce the security of the communication network.
  • the present invention provides a relay network energy efficiency optimal distribution method, device, terminal and storage medium, so as to solve the problem that the maximum energy efficiency optimization scheme of the existing relay communication network has large actual deviation and low safety.
  • the present invention provides a method for optimal distribution of energy efficiency in a relay network, which is applied to the relay of a relay network system.
  • the relay network system further includes a source end, a receiver end and an eavesdropping section; the method includes:
  • the non-convex optimization problem is transformed into a D.C. optimization problem, and the optimal solution is calculated.
  • the preset allocation method includes a time allocation method or a power allocation method.
  • the steps of receiving the information and energy sent by the source terminal based on the preset distribution mode and forwarding the information to the receiving terminal include:
  • the steps of obtaining the information sent by the receiving source and the related power parameters, related channel gain parameters, related circuit loss parameters, and additive white Gaussian noise parameters of the receiving end and the eavesdropping end when forwarding the information to the receiving end include:
  • n ⁇ N N is the number of subcarriers
  • the steps of receiving the information and energy sent by the source end based on the preset allocation method and forwarding the information to the receiving end include:
  • the steps of obtaining the information sent by the receiving source and the related power parameters, related channel gain parameters, related circuit loss parameters, and additive white Gaussian noise parameters of the receiving end and the eavesdropping end when forwarding the information to the receiving end include:
  • the transmit power of the source on the nth subcarrier when obtaining the information and energy sent by the source The transmit power of the source end on the nth subcarrier when it forwards information to the receiving end n ⁇ N, N is the number of subcarriers;
  • the present invention also provides a relay network energy efficiency optimal distribution device, which includes:
  • the dividing module is used to receive the information and energy sent by the source terminal based on a preset distribution method and forward the information to the receiving terminal;
  • the parameter acquisition module is used to acquire relevant power parameters, relevant channel gain parameters, relevant circuit loss parameters, and additive white Gaussian noise parameters of itself, the receiving end and the eavesdropping end during information transmission from the source end to the receiving end;
  • the collected energy calculation module is used to calculate the collected energy E according to related power parameters and related channel gain parameters;
  • the transmission rate calculation module is used to calculate the transmission rate R from the source end to the receiving end according to the relevant power parameters, the relevant channel gain parameters and the additive white Gaussian noise parameters;
  • the energy consumption calculation module is used to calculate the total energy consumption E tot according to related power parameters, related circuit loss parameters and energy E;
  • the building module is used to construct a non-convex optimization problem with the maximum energy efficiency maxEE as the goal according to the transmission rate R and the total energy consumption E tot ;
  • the transformation module is used to transform the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to the nonlinear fractional programming theory, and calculate the optimal solution.
  • the preset allocation method includes a time allocation method or a power allocation method.
  • the parameter acquisition module includes:
  • the first power parameter obtaining unit is used to obtain the transmission power of the source on the nth subcarrier when the energy sent by the source is collected
  • the transmit power on the nth subcarrier when the receiving source sends information
  • the transmit power of the source on the nth subcarrier when forwarding information to the receiving end Where n ⁇ N, N is the number of subcarriers;
  • the first channel gain parameter obtaining unit is used to obtain the channel gain of the nth subcarrier from the source to itself Channel gain from self to receiver And the channel gain from itself to the eavesdropper
  • the first circuit loss parameter acquisition unit is used to acquire the circuit loss when the source sends energy to itself The circuit loss when the source sends information to itself Circuit loss when transmitting information And the circuit loss of the receiving end when receiving information
  • the first noise parameter obtaining unit is used to obtain the variance of its own additive white Gaussian noise Variance of additive white Gaussian noise at the receiving end And the variance of the additive white Gaussian noise
  • the dividing module is used to set the power distribution ratio of the source to send information and energy to ⁇ , and within the first T/2 time, the source Send information and energy to itself, and forward the information to the receiving end within the next T/2, where T is the total transmission time;
  • the parameter acquisition module includes:
  • the second power parameter obtaining unit is used to obtain the transmission power of the source end on the nth subcarrier when the information and energy sent by the source end are received by itself
  • the transmit power of the source end on the nth subcarrier when it forwards information to the receiving end n ⁇ N, N is the number of subcarriers;
  • the second channel gain parameter obtaining unit is used to obtain the channel gain of the nth subcarrier from the source to itself Channel gain from self to receiver And the channel gain from itself to the eavesdropper
  • the second circuit loss parameter acquisition unit is used to acquire the circuit loss when the source sends information and energy Circuit loss when transmitting information Circuit loss at the receiving end when receiving information
  • the second noise parameter acquisition unit is used to acquire additive white Gaussian noise parameters
  • the additive white Gaussian noise parameters include: the variance of its own additive white Gaussian noise Variance of additive white Gaussian noise at the receiving end And the variance of the additive white Gaussian noise
  • the present invention also provides a terminal, which includes a memory and a processor, the processor is coupled to the memory, and a computer program that can run on the processor is stored in the memory;
  • the processor executes the computer program, it implements the steps in any one of the above-mentioned methods for optimal distribution of energy efficiency in a relay network.
  • the present invention also provides a storage medium on which a computer program is stored.
  • the computer program is executed by a processor, the steps in any one of the above-mentioned methods for optimal distribution of energy efficiency of a relay network are realized.
  • the invention obtains the relevant power parameters, relevant channel gain parameters, relevant circuit loss parameters in the process of transmitting information and energy from the source end to the relay and relaying the information to the receiving end, as well as the additivity of the relay itself, the receiving end and the eavesdropping end.
  • Gaussian white noise parameters calculate the energy collected by the relay itself, the transmission rate of information sent from the source to the receiving end, and the total energy consumption in the process of sending information from the source to the receiving end based on the above parameters, and then construct a The non-convex optimization problem with maximum energy efficiency as the goal, and then through the introduction of variables and based on the nonlinear fractional programming theory, the non-convex optimization problem is transformed into a DC optimization problem, that is, a more realistic nonlinear energy receiving model is obtained.
  • the eavesdropping end is also taken into consideration, while optimizing the energy efficiency of the system from the source end to the receiving end, the security performance in the information transmission process is improved.
  • Figure 1 is a schematic block diagram of an embodiment of a relay network system according to the present invention.
  • FIG. 2 is a schematic flowchart of a first embodiment of a method for optimal distribution of energy efficiency in a relay network according to the present invention
  • FIG. 3 is a schematic flowchart of a second embodiment of a method for optimal distribution of energy efficiency in a relay network according to the present invention
  • FIG. 4 is a schematic flowchart of a third embodiment of a method for optimal distribution of energy efficiency in a relay network according to the present invention.
  • FIG. 5 is a schematic diagram of functional modules of a first embodiment of a device for optimally assigning energy efficiency to a relay network according to the present invention
  • FIG. 6 is a schematic diagram of functional modules of a second embodiment of a device for optimal distribution of energy efficiency in a relay network according to the present invention.
  • FIG. 7 is a schematic diagram of functional modules of a third embodiment of a device for optimal distribution of energy efficiency in a relay network according to the present invention.
  • Fig. 8 is a schematic block diagram of an embodiment of a terminal of the present invention.
  • the method for optimal distribution of energy efficiency in a relay network relates to a relay network system, which includes a source terminal 10, a relay terminal 11, a receiving terminal 12, and an eavesdropping terminal 13.
  • the relay 11 has the ability to collect energy.
  • the source 10 sends a signal to the relay 11, and the relay 11 performs energy harvesting.
  • the source 10 sends information to the relay 11, and finally the relay 11 uses the collected energy to forward
  • the information from the source end 10 arrives at the receiving end 12, and the eavesdropping end 13 can steal information from the relay 11 during the information transmission process.
  • the relay 11 has no initial available energy
  • the channels from the source 10 to the relay 11, the relay 11 to the receiving end 12, and the relay 11 to the eavesdropping end 13 are all multi-carrier transmission, and the number of available subcarriers is N.
  • Fig. 2 shows the first embodiment of the optimal distribution method for energy efficiency of the relay network of the present invention.
  • the optimal distribution method for energy efficiency of the relay network includes:
  • Step S1 receiving the information and energy sent by the source terminal based on a preset distribution method and forwarding the information to the receiving terminal.
  • the preset allocation method includes a time allocation method or a power allocation method.
  • Step S2 Obtain related power parameters, related channel gain parameters, related circuit loss parameters, and additive white Gaussian noise parameters of the source end to the receiving end during information transmission.
  • the relevant power parameters include the transmission power between the source, relay and the receiver
  • the relevant channel gain parameters include the channel gains from the source to the relay, from the relay to the receiver, and from the relay to the eavesdropping section.
  • Related circuit loss parameters include the circuit loss when the source sends information and energy, the circuit loss when relaying and forwarding information, the circuit loss when the receiving end receives information
  • the additive white Gaussian noise parameters include relay, receiving, and wiretapping. The variance of the additive white Gaussian noise with the mean value of the segment being 0.
  • Step S3 Calculate the collected energy E according to the relevant power parameter and the relevant channel gain parameter.
  • the relay has the ability to collect energy from the surrounding environment.
  • the energy E collected by the relay can be calculated.
  • Step S4 Calculate the transmission rate R from the source end to the receiving end according to the relevant power parameter, the relevant channel gain parameter and the additive white Gaussian noise parameter.
  • the achievable transmission rate when the source terminal sends information to the relay and the achievable transmission rate when the relay transmits information to the receiving terminal are calculated through the relevant power parameters, the relevant channel gain parameters and the additive white Gaussian noise parameters, and Taking into account the interference of the eavesdropping channel, combined with the additive white Gaussian noise parameter of the eavesdropping end, the achievable transmission rate R from the source end to the receiving end under security conditions can be obtained.
  • Step S5 Calculate the total energy consumption E tot according to the relevant power parameters, the relevant circuit loss parameters and the energy E.
  • both the source and the relay need to send information, so they are equivalent to the transmitter.
  • the transmitter sends signals not only because of the transmission power consumption, but also the actual The consumption of the circuit, including frequency modulation and amplitude modulation, AD/DA conversion, filtering and power amplification, etc.
  • P C,on ⁇ 0, P C,off ⁇ 0 respectively represent the actual circuit losses in the "on” and “off” states, so the actual power consumption model for the wireless transmitter can be expressed as Among them, ⁇ is a multiplicative constant used to reflect the low efficiency of the radio frequency circuit.
  • P total represents the total energy consumed by the transmitter.
  • Step S6 construct a non-convex optimization problem with the maximum energy efficiency maxEE as the target according to the transmission rate R and the total energy consumption E tot .
  • a non-convex optimization problem targeting the maximum energy efficiency maxEE can be expressed as:
  • step S7 the non-convex optimization problem is transformed into a D.C. optimization problem by introducing variables and according to the nonlinear fractional programming theory, and the optimal solution is calculated.
  • the above non-convex optimization problem with the maximum energy efficiency maxEE as the goal is transformed into a DC optimization problem, and then it is approximated at each feasible point to obtain a convex Optimize the problem, and then solve the convex optimization problem to get the optimal solution.
  • the related power parameters, related channel gain parameters, related circuit loss parameters in the process of acquiring the source end sending information and energy to the relay and relaying the information to the receiving end, as well as the increase of the relay itself, the receiving end and the eavesdropping end Gaussian white noise parameters, and calculate the energy collected by the relay itself, the transmission rate of information sent from the source to the receiving end, and the total energy consumption in the process of sending information from the source to the receiving end based on the above parameters, and then construct a The non-convex optimization problem with maximum energy efficiency as the goal, and then through the introduction of variables and based on the nonlinear fractional programming theory, the non-convex optimization problem is transformed into a DC optimization problem, that is, a more realistic nonlinear energy receiving model is obtained
  • the eavesdropping terminal is also taken into consideration to optimize the energy efficiency of the system from the source terminal to the receiving terminal while improving the security performance in the information transmission process.
  • Fig. 3 shows a second embodiment of the optimal distribution method for energy efficiency of a relay network of the present invention.
  • the mode under the preset conditions is the mode of time distribution
  • the method for optimal distribution of energy efficiency of the relay network includes the following steps:
  • step S10 the transmission time from the source end to the receiving end is divided into three time periods ⁇ 1 T, ⁇ 2 T, and ⁇ 3 T.
  • T is the total transmission time
  • the energy sent by the source is collected during the period ⁇ 1 T
  • the information sent by the source is received during the period ⁇ 2 T, ⁇ 3
  • the information is forwarded to the receiving end within T time period.
  • Step S11 Obtain the transmit power of the source on the nth subcarrier when the energy sent by the source is collected The transmit power on the nth subcarrier when the receiving source sends information The transmit power of the source on the nth subcarrier when forwarding information to the receiving end
  • the channels from the source end to the relay, the relay to the receiving end, and the relay to the eavesdropping end are all multi-carrier transmissions, and the number of available subcarriers is N, where n represents the first subcarrier, n ⁇ N.
  • Step S12 Obtain the channel gain of the nth subcarrier from the source to itself Channel gain from self to receiver And the channel gain from itself to the eavesdropper
  • Step S13 Obtain the circuit loss when the source sends energy to itself The circuit loss when the source sends information to itself Circuit loss when transmitting information And the circuit loss of the receiving end when receiving information
  • Step S14 obtain the variance of its own additive white Gaussian noise Variance of additive white Gaussian noise at the receiving end And the variance of the additive white Gaussian noise
  • Step S15 Calculate the collected energy E according to the relevant power parameter and the relevant channel gain parameter.
  • Step S16 Calculate the transmission rate R from the source end to the receiver end according to the relevant power parameter, the relevant channel gain parameter and the additive white Gaussian noise parameter.
  • the information sent by the source is received, and the transmission power on the nth subcarrier when the information is sent by the receiving source is The channel gain of the nth subcarrier from the source to itself Variance of repeating additive white Gaussian noise Calculate the achievable transmission rate from the source to the relay among them,
  • Step S17 Calculate the total energy consumption E tot according to the relevant power parameters, the relevant circuit loss parameters and the energy E.
  • the energy consumed by the source to send information and energy is
  • the energy consumed by the relay is the
  • the receiving end only needs to receive information, but does not need to send information. Therefore, the energy consumed by the receiving end is
  • Step S18 construct a non-convex optimization problem with the maximum energy efficiency maxEE as the target according to the transmission rate R and the total energy consumption E tot .
  • Constraints (1) and (2) indicate that the transmission power of energy and information sent by the source must not exceed its maximum available power threshold P MAX , and constraint (3) indicates not considering In order to ensure that the communication is not interrupted, the relay must meet the requirement that the collected energy is greater than or equal to the energy consumed when forwarding information. Constraint (4) indicates that in order to ensure communication quality, the safe transmission rate must be higher than the set Threshold R Q.
  • step S19 the non-convex optimization problem is transformed into a D.C. optimization problem by introducing variables and according to the nonlinear fractional programming theory, and the optimal solution is calculated.
  • the objective function of the transformed optimization problem is It is a DC function for a given value of q.
  • the 4th, 5th, 6th, 7th, 11th and 12th constraint conditions in the constraint conditions also belong to the DC function, that is, the form is f(x)-g(x), where x Is a vector composed of all variables, f(x) and g(x) are convex functions, so the problem belongs to the DC optimization problem, and the idea of solving the DC optimization problem is to approximate it at each feasible point to obtain a convex Optimize the problem, and then solve the convex optimization problem to get the optimal solution. This iterative step continues until convergence.
  • the specific solution process is as follows:
  • step 6 Judge whether the absolute value of the difference between the objective function values of steps k and k-1 is less than or equal to the set accuracy, if less than or equal, proceed to step 7, otherwise skip to step 4;
  • FIG. 4 shows a third embodiment of the method for optimal distribution of energy efficiency in a relay network of the present invention.
  • the way under the preset conditions is the way of power distribution
  • the method for optimal distribution of energy efficiency of the relay network includes the following steps:
  • Step S20 Set the power distribution ratio of the source to send information and energy to ⁇ , and within the first T/2, the source sends information and energy to itself, and within the next T/2, it forwards the information to the receiver. end.
  • T is the total transmission time
  • Step S21 Obtain the transmit power of the source on the nth subcarrier when the information and energy sent by the source are received by itself The transmit power of the source end on the nth subcarrier when it forwards information to the receiving end
  • the channels from the source end to the relay, the relay to the receiving end, and the relay to the eavesdropping end are all multi-carrier transmissions, and the number of available subcarriers is N, where n represents the first subcarrier, n ⁇ N.
  • Step S22 Obtain the channel gain of the nth subcarrier from the source to itself Channel gain from self to receiver And the channel gain from itself to the eavesdropper
  • Step S23 Obtain the circuit loss when the source sends information and energy Circuit loss when transmitting information Circuit loss at the receiving end when receiving information
  • Step S24 obtain the variance of its own additive white Gaussian noise Variance of additive white Gaussian noise at the receiving end And the variance of the additive white Gaussian noise
  • Step S25 Calculate the collected energy E sent by the source end according to the relevant power parameter and the relevant channel gain parameter.
  • the source sends information and energy to itself, and relays the received energy among them, a, b, and M are preset constants, which can be obtained by data fitting of actual measurement data.
  • Step S26 Calculate the transmission rate R from the source end to the receiver end according to the relevant power parameter, the relevant channel gain parameter and the additive white Gaussian noise parameter.
  • the source sends a signal to the relay, and the transmission rate from the source to the relay at this time is among them,
  • the relay uses the collected energy to send the received information to the receiving end.
  • the transmission rate from the relay to the receiving end is among them,
  • Step S27 Calculate the total energy consumption E tot according to the relevant power parameters, the relevant circuit loss parameters and the energy E.
  • the energy consumed by the source to send information and energy is
  • the energy consumed by the relay is the
  • the receiving end only needs to receive information, but does not need to send information. Therefore, the energy consumed by the receiving end is
  • Step S28 construct a non-convex optimization problem with the maximum energy efficiency maxEE as the target according to the transmission rate R and the total energy consumption E tot .
  • Constraint (1) means that the transmission power of the source and information must not exceed its maximum available power threshold P MAX
  • constraint (2) means that the initial energy of the relay is not considered In order to ensure uninterrupted communication, the relay must satisfy that the collected energy is greater than or equal to the energy consumed when forwarding information.
  • Constraint (3) indicates that in order to ensure communication quality, the safe transmission rate must be higher than the set threshold R Q.
  • step S29 the non-convex optimization problem is transformed into a D.C. optimization problem by introducing variables and according to the nonlinear fractional programming theory, and the optimal solution is calculated.
  • Fig. 5 shows an embodiment of the optimal distribution device for energy efficiency of the relay network of the present invention.
  • the relay network energy efficiency optimal distribution device includes a dividing module 10, a parameter obtaining module 11, a collected energy calculation module 12, a transmission rate calculation module 13, an energy consumption calculation module 14, a construction module 15 and a conversion module 16.
  • the dividing module 10 is used to receive the information and energy sent by the source end based on a preset allocation method and forward the information to the receiving end;
  • the parameter obtaining module 11 is used to obtain related power parameters, Related channel gain parameters, related circuit loss parameters, and additive white Gaussian noise parameters of itself, the receiving end and the eavesdropping end;
  • the collected energy calculation module 12 is used to calculate the collected energy E according to the related power parameters and the related channel gain parameters;
  • transmission The rate calculation module 13 is used to calculate the transmission rate R from the source end to the receiving end according to the relevant power parameters, the relevant channel gain parameters and the additive white Gaussian noise parameters;
  • the energy consumption calculation module 14 is used to calculate the relevant power parameters and the relevant circuit loss parameters And energy E to calculate the total energy consumption E tot ;
  • the construction module 15 is used to construct a non-convex optimization problem with the maximum energy efficiency maxEE as the goal according to the transmission rate R and the total energy consumption E tot ;
  • the transformation module 16 is used to introduce variables According to
  • the preset allocation method includes a time allocation method or a power allocation method.
  • the parameter acquisition module 11 includes a first power parameter acquisition unit 1100, a first channel gain parameter acquisition unit 1101, a first circuit loss parameter acquisition unit 1102, and a first noise parameter acquisition unit 1103.
  • the first power parameter obtaining unit 1100 is configured to obtain the transmit power of the source on the nth subcarrier when the energy sent by the source is collected The transmit power on the nth subcarrier when the receiving source sends information The transmit power of the source on the nth subcarrier when forwarding information to the receiving end
  • n ⁇ N, N is the number of subcarriers
  • the first channel gain parameter acquisition unit 1101 is used to acquire the channel gain of the nth subcarrier from the source to itself Channel gain from self to receiver And the channel gain from itself to the eavesdropper
  • the first circuit loss parameter acquisition unit 1102 is used to acquire the circuit loss when the source sends energy to itself The circuit loss when the source sends information to itself Circuit loss when transmitting information
  • the first noise parameter obtaining unit 1103 is configured to obtain the variance of its own additive white Gaussian noise Variance of additive white Gaussian noise at the receiving end And the variance of the additive white Gaussian noise
  • the dividing module is used to set the power allocation ratio of the source to send information and energy to ⁇ , And in the first T/2, the source sends information and energy to itself, and in the latter T/2, it forwards the information to the receiving end, and T is the total transmission time;
  • the parameter acquisition module 11 includes a second power parameter acquisition unit 1110, a second channel gain parameter acquisition unit 1111, a second circuit loss parameter acquisition unit 1112, and a second noise parameter acquisition unit 1113.
  • the second power parameter obtaining unit 1110 is used to obtain the transmit power of the source end on the nth subcarrier when it receives the information and energy sent by the source end.
  • the transmit power of the source end on the nth subcarrier when it forwards information to the receiving end n ⁇ N, N is the number of subcarriers;
  • the second channel gain parameter obtaining unit 1111 is used to obtain the channel gain of the nth subcarrier from the source to itself Channel gain from self to receiver And the channel gain from itself to the eavesdropper
  • the second circuit loss parameter acquisition unit 1112 is used to acquire the circuit loss when the source sends information and energy Circuit loss when transmitting information Circuit loss at the receiving end when receiving information
  • the second noise parameter obtaining unit 1113 is configured to obtain additive white Gaussian noise parameters, and the additive white Gaussian noise parameters include: the variance of its own additive white Gaussian noise Variance of additive white Gaussian noise at the receiving end And the variance of the additive white Gaussian noise
  • FIG. 8 shows a schematic block diagram of a terminal provided by another embodiment of the present invention.
  • the terminal in this embodiment includes: one or at least two processors 80, a memory 81, and the A computer program 810 running on the processor 80.
  • the processor 80 executes the computer program 810, it implements the steps in the method for optimal distribution of energy efficiency of the relay network described in the foregoing embodiment, for example: step S1-step S7 shown in FIG. 2.
  • the processor 80 executes the computer program 810, it realizes the functions of the modules/units in the above-mentioned embodiment of the device for optimal distribution of energy efficiency in a relay network based on multi-mode integration, for example: the functions of module 10-module 16 shown in FIG. 5 .
  • the computer program 810 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 81 and executed by the processor 80 to complete the application.
  • One or more modules/units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 810 in the terminal.
  • the terminal includes but is not limited to a processor 80 and a memory 81.
  • FIG. 8 is only an example of the terminal, and does not constitute a limitation on the terminal. It may include more or less components than shown in the figure, or combine some components, or different components, such as a terminal. It can also include input devices, output devices, network access devices, buses, and so on.
  • the processor 80 may be a central processing unit (Central Processing Unit, CPU), other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), ready-made Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
  • the memory 81 can be a read-only memory, a static storage device that can store static information and instructions, a random access memory, or a dynamic storage device that can store information and instructions, or it can be an electrically erasable programmable read-only memory or a read-only optical disk. , Or other optical disk storage, optical disk storage, magnetic disk storage media or other magnetic storage devices.
  • the memory 81 and the processor 80 may be connected through a communication bus, or may be integrated with the processor 80.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only illustrative, for example, the division of modules or units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or It can be integrated into another device, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • each unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • An embodiment of the present application also provides a storage medium for storing a computer program, which contains program data designed for executing the foregoing embodiment of the method for optimal distribution of energy efficiency in a relay network of the present application.
  • a storage medium for storing a computer program, which contains program data designed for executing the foregoing embodiment of the method for optimal distribution of energy efficiency in a relay network of the present application.
  • the integrated module/unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • this application implements all or part of the processes in the above-mentioned embodiment methods, and can also be completed by instructing relevant hardware through a computer program 810.
  • the computer program 810 can be stored in a computer-readable storage medium. When executed by the processor 80, 810 may implement the steps of the foregoing method embodiments.
  • the computer program 810 includes computer program code, and the computer program code may be in the form of source code, object code, executable file, or some intermediate forms.
  • Computer-readable media may include: any entity or device capable of carrying computer program code, recording media, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access Memory (RAM, Random Access Memory), electric carrier signal, telecommunications signal, software distribution medium, etc. It should be noted that the content contained in computer-readable media can be appropriately added or deleted according to the requirements of the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to the legislation and patent practice, computer-readable media does not include It is electric carrier signal and telecommunication signal.

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Abstract

La présente invention concerne un procédé et un dispositif de distribution optimisée d'efficacité énergétique de réseau de relais, un terminal, et un support de stockage. Le procédé comprend : la division d'un processus de transmission d'informations d'une extrémité de source à une extrémité de réception sur la base d'un schéma de distribution prédéfini ; l'acquisition d'un paramètre de puissance pertinent, d'un paramètre de gain de canal pertinent, d'un paramètre de perte de circuit pertinent dans un processus de transmission d'informations, et de paramètres de bruit blanc gaussien additif d'un relais, de l'extrémité de réception, et d'une extrémité de tapotement ; puis le calcul respectif de l'énergie collectée par le relais, du débit de transmission de l'extrémité source à l'extrémité de réception, et de la consommation énergétique totale ; la construction et la résolution d'un problème d'optimisation non convexe pour une efficacité énergétique maximale sur la base du débit de transmission et de la consommation d'énergie totale, et la conversion du problème en un problème d'optimisation CC, ce qui permet de calculer une solution optimale. La présente invention, par l'acquisition des paramètres pertinents dans le processus de transmission d'informations, la construction et la résolution du problème d'optimisation non convexe pour une efficacité énergétique maximale, puis par la conversion du problème en un problème d'optimisation CC, ce qui permet de produire la solution optimale, est en outre conforme aux applications pratiques et, en prenant en considération le problème de tapotement, renforce la sécurité.
PCT/CN2019/130584 2019-04-26 2019-12-31 Procédé et dispositif de distribution optimisée d'efficacité énergétique de réseau de relais, terminal, et support de stockage WO2020215801A1 (fr)

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