CN111866904A - Relay network energy efficiency optimal allocation method, device, terminal and storage medium - Google Patents
Relay network energy efficiency optimal allocation method, device, terminal and storage medium Download PDFInfo
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- H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
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Abstract
本发明公开了一种中继网络能量效率最优分配方法、装置、终端和存储介质，该方法包括：根据预设分配方式划分源端至接收端的信息传输过程；并获取信息传输过程中的相关功率参数、相关信道增益参数、相关电路损耗参数，以及中继、接收端和窃听端的加性高斯白噪声参数；再分别计算出中继收集到的能量、源端到接收端的传输速率、总能量消耗；根据传输速率和总能量消耗构建求解最大能量效率的非凸优化问题，并将其转化为一个D.C.优化问题，进而计算最优解。本发明通过获取信息传输过程中的相关参数，构建求解最大能量效率的非凸优化问题，再将其转化为一个D.C.优化问题，从而得出最优解，更符合实际应用，并考虑到窃听的问题，提高了安全性。
The invention discloses a method, device, terminal and storage medium for optimal allocation of energy efficiency of a relay network. The method includes: dividing an information transmission process from a source end to a receiving end according to a preset allocation method; and obtaining relevant information in the information transmission process. Power parameters, related channel gain parameters, related circuit loss parameters, and the additive white Gaussian noise parameters of the relay, receiver and eavesdropper; then calculate the energy collected by the relay, the transmission rate from the source to the receiver, and the total energy. Consumption; construct a non-convex optimization problem to solve the maximum energy efficiency according to the transmission rate and total energy consumption, and convert it into a DC optimization problem, and then calculate the optimal solution. The present invention constructs a non-convex optimization problem to solve the maximum energy efficiency by acquiring the relevant parameters in the information transmission process, and then converts it into a DC optimization problem, so as to obtain the optimal solution, which is more in line with practical applications, and takes into account the possibility of eavesdropping. problem and improve security.
Description
Technical Field
The invention relates to the technical field of resource optimization of wireless energy-carrying relay networks, in particular to a method, a device, a terminal and a storage medium for optimal distribution of energy efficiency of a relay network.
Background
With the continuous development of wireless communication networks and communication technologies and the continuous consumption of limited resources such as energy, communication devices with energy harvesting function are considered as a promising alternative to provide self-sustainable development for energy-limited communication systems. The wireless energy-carrying communication combines a communication technology and a wireless energy collection technology, and aims to realize the simultaneous transmission of information and energy, so that huge benefits can be brought in the aspects of spectral efficiency, energy consumption, interference management and the like.
At present, with the increasing attention of people to energy and environmental problems, the concept of green communication is more and more accepted by people. The method and the device have the advantages that the communication network can provide high-speed communication services for users, meanwhile, the energy consumption of the network is reduced as much as possible, the operation cost and the energy consumption of the communication network are reduced, the environmental protection is facilitated, and the green development is realized. However, in the optimal configuration of the communication network resources, the energy efficiency of the system is optimized only by adopting a simple linear energy receiving model, the obtained result has a large deviation from the actual result, and in the existing energy efficiency optimization scheme, the problem of an eavesdropper is not considered, so that the safety of the communication network is reduced.
Disclosure of Invention
The invention provides a method, a device, a terminal and a storage medium for optimal distribution of energy efficiency of a relay network, which aim to solve the problems of larger deviation and lower safety of the maximum energy efficiency optimization scheme of the conventional relay communication network from the actual scheme.
In order to solve the above problems, the present invention provides a method for optimally allocating energy efficiency of a relay network, which is applied to a relay of a relay network system, wherein the relay network system further comprises a source end, a receiving end and an eavesdropping section; the method comprises the following steps:
receiving information and energy sent by a source end based on a preset distribution mode and transmitting the information to a receiving end;
acquiring a related power parameter, a related channel gain parameter and a related circuit loss parameter when information is transmitted from a source end to a receiving end, and additive white Gaussian noise parameters of the receiving end and an eavesdropping end;
calculating the collected energy E according to the relevant power parameter and the relevant channel gain parameter;
calculating the transmission rate R from the source end to the receiving end according to the related power parameter, the related channel gain parameter and the additive white Gaussian noise parameter;
calculating the total energy consumption E from the related power parameter, the related circuit loss parameter and the energy Etot；
According to the transmission rate R and the total energy consumption E totConstructing a non-convex optimization problem with the maximum energy efficiency maxEE as a target;
the non-convex optimization problem is converted into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, and an optimal solution is calculated.
As a further improvement of the present invention, the preset allocation manner includes a time allocation manner or a power allocation manner.
As a further improvement of the present invention, when the preset allocation manner is a time allocation manner, the step of receiving information and energy sent by the source end and forwarding the information to the receiver end based on the preset allocation manner includes:
dividing the transmission time of the source end sending information to the receiving end into alpha1T、α2T、α3T three time periods, wherein1+α2+α3T is the total transmission time, α1Collecting energy alpha sent by a source end in a T time period2Receiving information, alpha, sent by a source end in a time period of T3Transmitting the information to a receiving end in the T time period;
the steps of obtaining the information sent by the receiving source end and the relevant power parameter, the relevant channel gain parameter, the relevant circuit loss parameter when the information is forwarded to the receiving end, and the additive white Gaussian noise parameters of the receiving end, the receiving end and the eavesdropping end comprise:
acquiring the transmitting power of the source end on the nth subcarrier when the energy transmitted by the source end is collected 
Transmitting power on nth subcarrier when receiving source end transmitting information
Transmitting power of source end on nth subcarrier when information is forwarded to receiving end
Wherein N belongs to N, and N is the number of subcarriers;
obtaining the channel gain of the nth sub-carrier from the source end to the nth sub-carrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
Obtaining circuit loss when source end sends energy to itself
Circuit loss when source sends information to itself
Circuit loss in forwarding information
And circuit loss of the receiving end in receiving information
Obtaining the variance of the additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
As a further improvement of the present invention, when the preset allocation manner is a power allocation manner, the step of receiving information and energy sent by the source end and forwarding the information to the receiver end based on the preset allocation manner includes:
setting a power distribution proportion theta for sending information and energy by a source end, sending the information and the energy to the source end by the source end within the former T/2 time, and forwarding the information to a receiving end by the source end within the later T/2 time, wherein T is total transmission time;
The steps of obtaining the information sent by the receiving source end and the relevant power parameter, the relevant channel gain parameter, the relevant circuit loss parameter when the information is forwarded to the receiving end, and the additive white Gaussian noise parameters of the receiving end, the receiving end and the eavesdropping end comprise:
obtaining the transmitting power of the source end on the nth subcarrier when the source end receives the information and the energy sent by the source end
Transmitting power of source end on nth subcarrier when self-transmitting information to receiving end
N belongs to N, and N is the number of subcarriers;
obtaining the channel gain of the nth sub-carrier from the source end to the nth sub-carrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
Circuit loss in obtaining source end transmission information and energy
Circuit loss in forwarding information
Circuit loss of receiving end in receiving information
Obtaining the variance of the additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
In order to solve the above problem, the present invention further provides a relay network energy efficiency optimal allocation apparatus, including:
the dividing module is used for receiving the information and the energy sent by the source end based on a preset distribution mode and forwarding the information to the receiving end;
The parameter acquisition module is used for acquiring related power parameters, related channel gain parameters and related circuit loss parameters when information is transmitted from the source end to the receiving end, and additive white Gaussian noise parameters of the receiving end and the eavesdropping end;
the collected energy calculation module is used for calculating the collected energy E according to the relevant power parameter and the relevant channel gain parameter;
the transmission rate calculation module is used for calculating 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;
an energy consumption calculation module for calculating total energy consumption E according to the related power parameter, the related circuit loss parameter and the energy Etot；
A building block for determining the total energy consumption E from the transmission rate RtotConstructing a non-convex optimization problem with the maximum energy efficiency maxEE as a target;
and the conversion module is used for converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory and calculating an optimal solution.
As a further improvement of the present invention, the preset allocation manner includes a time allocation manner or a power allocation manner.
As a further improvement of the present invention, when the preset allocation mode is a time allocation mode, the dividing module is configured to divide the transmission time of the source sending the information to the sink into α 1T、α2T、α3T three time periods, wherein1+α2+α3T is the total transmission time, α1Collecting energy alpha sent by a source end in a T time period2Receiving information, alpha, sent by a source end in a time period of T3Transmitting the information to a receiving end in the T time period;
the parameter acquisition module comprises:
a first power parameter obtaining unit, configured to obtain the transmission power of the source end on the nth subcarrier when the energy sent by the source end is collected
Transmitting power on nth subcarrier when receiving source end transmitting information
Transmitting power of source end on nth subcarrier when information is forwarded to receiving end
Wherein N belongs to N, and N is the number of subcarriers;
a first channel gain parameter obtaining unit, configured to obtain a channel gain from a source end to the nth subcarrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
A first circuit loss parameter obtaining unit, configured to obtain a circuit loss when a source end sends energy to the first circuit loss parameter obtaining unit
Circuit loss when source sends information to itself
Circuit loss in forwarding information
And circuit loss of the receiving end in receiving information
A first noise parameter obtaining unit for obtaining variance of self additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end 
And variance of additive white Gaussian noise at eavesdropping end
As a further improvement of the present invention, when the preset distribution mode is a power distribution mode, the dividing module is configured to set a power distribution ratio of information and energy sent by the source end to be θ, and the source end sends the information and the energy to itself within a former T/2 time, and within a latter T/2 time, the source end itself forwards the information to the receiving end, where T is total transmission time;
the parameter acquisition module comprises:
a second power parameter obtaining unit for obtaining the transmission power of the source end on the nth subcarrier when the source end receives the information and energy sent by the source end
Transmitting power of source end on nth subcarrier when self-transmitting information to receiving end
N belongs to N, and N is the number of subcarriers;
a second channel gain parameter obtaining unit for obtaining the channel gain of the nth sub-carrier from the source end to the nth sub-carrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
A second circuit loss parameter obtaining unit for obtaining the circuit loss when the source end sends information and energy
Circuit loss in forwarding information
Circuit loss of receiving end in receiving information
A second noise parameter obtaining unit, configured to obtain an additive white gaussian noise parameter, where the additive white gaussian noise parameter includes: variance of additive white Gaussian noise 
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
In order to solve the above problem, the present invention further provides a terminal, which includes a memory and a processor, wherein the processor is coupled to the memory, and the memory stores a computer program that can be executed on the processor;
and when the processor executes the computer program, the steps of any relay network energy efficiency optimal distribution method are realized.
In order to solve the above problem, the present invention further provides a storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the steps of any one of the above methods for optimally allocating relay network energy efficiency.
The invention constructs a non-convex optimization problem taking maximum energy efficiency as a target by acquiring related power parameters, related channel gain parameters, related circuit loss parameters and additive white Gaussian noise parameters of a relay, a receiving terminal and an eavesdropping terminal in the process of sending information and energy to the relay by a source terminal and forwarding information to the receiving terminal by the relay, calculating the energy collected by the relay, the transmission rate of the information sent from the source terminal to the receiving terminal and the total energy consumption in the process of sending the information from the source terminal to the receiving terminal according to the parameters, and converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, namely obtaining a nonlinear energy receiving model which is more accordant with the reality, and considering the eavesdropping terminal, when optimizing the system energy efficiency from the source terminal to the receiving terminal, the safety performance in the information transmission process is improved.
Drawings
Fig. 1 is a schematic block diagram of an embodiment of a relay network system of the present invention;
fig. 2 is a schematic flow chart of a method for optimally allocating energy efficiency of a relay network according to a first embodiment of the present invention;
fig. 3 is a flowchart illustrating a second embodiment of the method for optimally allocating energy efficiency of a relay network according to the present invention;
fig. 4 is a flowchart illustrating a method for optimally allocating energy efficiency of a relay network according to a third embodiment of the present invention;
fig. 5 is a functional block diagram of a first embodiment of the optimal energy efficiency distribution device for the relay network according to the present invention;
fig. 6 is a functional block diagram of a second embodiment of the optimal distribution device for energy efficiency of a relay network according to the present invention;
fig. 7 is a functional block diagram of a third embodiment of the optimal distribution device for energy efficiency of a relay network according to the present invention;
fig. 8 is a schematic block diagram of an embodiment of the terminal of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Firstly, as shown in fig. 1, the method for optimally allocating energy efficiency of a relay network provided by the present invention relates to a relay network system, which includes a source end 10, a relay 11, a receiving end 12 and an eavesdropping end 13, wherein the relay 11 has an energy collection capability, the source end 10 sends a signal to the relay 11, the relay 11 performs energy collection, the source end 10 sends information to the relay 11, the relay 11 forwards information of the source end 10 to the receiving end 12 by using the collected energy, and the eavesdropping end 13 can steal information from the relay 11 in an information transmission process. Assuming that the relay 11 has no initial available energy, considering that the channels from the source end 10 to the relay 11, from the relay 11 to the receiving end 12 and from the relay 11 to the eavesdropping end 13 are all multi-carrier transmissions, and the number of available subcarriers is N.
Fig. 2 shows a first embodiment of the energy efficiency optimal allocation method of the relay network of the present invention. As shown in fig. 2, in this embodiment, the method for optimally allocating energy efficiency of a relay network includes:
step S1, receiving the information and energy sent by the source end based on the preset distribution mode and forwarding the information to the sink end.
The preset allocation method includes a time allocation method and a power allocation method.
Step S2, obtaining the relevant power parameter, the relevant channel gain parameter, the relevant circuit loss parameter when the information from the source end to the receiving end is transmitted, and the additive white Gaussian noise parameter of the receiving end, the interception end and the interception end.
Specifically, in the process that the relay transmits information and energy sent by a receiving source end to the receiving end and forwards the information to the receiving end, a relevant power parameter, a relevant channel gain parameter, a relevant circuit loss parameter and additive white gaussian noise parameters of the relay, the receiving end and an eavesdropping end are obtained, wherein the relevant power parameter comprises the transmitting power among the source end, the relay and the receiving end, the relevant channel gain parameter comprises channel gains from the source end to the relay, from the relay to the receiving end and from the relay to the eavesdropping section, the relevant circuit loss parameter comprises the circuit loss when the source end transmits the information and the energy, the circuit loss when the relay forwards the information and the circuit loss when the receiving end receives the information, and the additive white gaussian noise parameter comprises the variance of the additive white gaussian noise with the average value of 0 among the relay, the receiving end and the eavesdropping section.
Step S3, the collected energy E is calculated according to the correlated power parameter and the correlated channel gain parameter.
Specifically, the relay has the capability of collecting energy from the surrounding environment, and in this embodiment, after the relevant power parameter and the relevant channel gain parameter are obtained, the energy E collected by the relay can be calculated.
Step S4, calculating the transmission rate R from the source end to the receiving end according to the related power parameter, the related channel gain parameter and the additive white Gaussian noise parameter.
Specifically, the transmission rate which can be realized when the source end sends information to the relay and the transmission rate which can be realized when the relay forwards information to the receiving end are obtained through calculation of a related power parameter, a related channel gain parameter and an additive white gaussian noise parameter, and the transmission rate R which can be realized from the source end to the receiving end based on the safety condition can be obtained by combining the additive white gaussian noise parameter of the eavesdropping end in consideration of the interference of the eavesdropping channel.
Step S5, calculating total energy consumption E according to the related power parameter, the related circuit loss parameter and the energy Etot。
Specifically, in this embodiment, both the source end and the relay need to transmit information, and therefore they are equivalent to a transmitter, and in an actual wireless network, there is not only transmission power consumption but also consumption of actual circuits, including fm, am, AD/DA conversion, filtering, power amplification, etc., for signal transmission by the transmitter, and when the transmission power P > 0 of the transmitter, we consider that the transmitter is in the "on" state, and when P is 0, the transmitter is in the "off" state, and P is in the "on" state C，on≥0，PC，off≧ 0 represents the actual circuit loss in the "on" and "off" states, respectively, so the actual power consumption model for the wireless transmitter can be expressed as
Wherein, is a multiplication constant, which is used to reflect the low efficiency of the radio frequency circuit, PtotalRepresents the total energy consumed by the transmitter, and in fact PC，offRatio PC，onMuch smaller, so for simplicity, P can be consideredC，on> 0, and PC，off0, so that the actual power consumption model of the wireless transmitter can be expressed as Ptotal＝P+PC，onThereby calculating the total energy consumption E in the process of sending information from the source end to the receiving endtot。
Step S6, according to the transmission rate R and the total energy consumption EtotA non-convex optimization problem is constructed with the maximum energy efficiency maxEE as the target.
Specifically, the transmission rate R from the source end to the receiving end and the total consumption energy E of the source end, the relay and the receiving end are obtained according to calculationtotThen, the limitation of transmission power, time allocation, and the requirement of communication quality are considered comprehensively, and a non-convex optimization problem with the maximum energy efficiency maxEE as the target is constructed, which can be expressed as:
and step S7, converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, and calculating an optimal solution.
Specifically, the non-convex optimization problem which takes the maximum energy efficiency maxEE as the target is converted into a d.c. optimization problem by introducing variables and combining a nonlinear fractional programming theory, the d.c. optimization problem is approximated at each feasible point to obtain a convex optimization problem, and then the convex optimization problem is solved to obtain an optimal solution.
In the embodiment, by obtaining the relevant power parameter, the relevant channel gain parameter, the relevant circuit loss parameter and the additive white gaussian noise parameter of the relay, the receiving terminal and the eavesdropping terminal in the process of sending information and energy to the relay by the source terminal and forwarding information to the receiving terminal by the relay, and calculating the energy collected by the relay, the transmission rate of the information sent from the source terminal to the receiving terminal and the total energy consumption in the process of sending the information from the source terminal to the receiving terminal according to the parameters, a non-convex optimization problem which takes the maximum energy efficiency as a target is further constructed, and then the non-convex optimization problem is converted into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, namely, a nonlinear energy receiving model which is more in line with the reality is obtained, and the eavesdropping terminal is also taken into consideration, so that while the system energy efficiency from the source terminal to the receiving terminal is optimized, the safety performance in the information transmission process is improved.
Further, as shown in fig. 3, fig. 3 shows a second embodiment of the energy efficiency optimal allocation method of the relay network of the present invention. In this embodiment, the method under the preset condition is a time allocation method, and the method for optimally allocating the energy efficiency of the relay network includes the following steps:
step S10, dividing the transmission time of the source end sending information to the receiving end into alpha1T、α2T、α3T three time periods.
In addition, α is1+α2+α3T is the total transmission time, α1Collecting energy alpha sent by a source end in a T time period2Receiving information, alpha, sent by a source end in a time period of T3And transmitting the information to a receiving end in the T time period.
Step S11, obtaining the transmitting power of the source end on the nth sub-carrier when collecting the energy transmitted by the source end
Transmitting power on nth subcarrier when receiving source end transmitting information
Transmitting power of source end on nth subcarrier when information is forwarded to receiving end
It should be noted that channels from the source end to the relay, from the relay to the receiving end, and from the relay to the eavesdropping end are all multi-carrier transmissions, the number of available subcarriers is N, N represents the first subcarrier, and N belongs to N.
Step S12, obtaining the channel gain of the nth sub-carrier from the source end to itself
Channel gain from self to receiving end 
And channel gain from itself to the eavesdropping end
Step S13, obtaining the circuit loss when the source end sends energy to itself
Circuit loss when source sends information to itself
Circuit loss in forwarding information
And circuit loss of the receiving end in receiving information
Step S14, obtaining variance of self additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
Step S15, the collected energy E is calculated according to the correlated power parameter and the correlated channel gain parameter.
In particular, at α1Collecting energy sent by a source end in a T time period, specifically according to energy sent by the source endTransmitting power of source end on nth subcarrier during energy
And channel gain of nth subcarrier from source end to relay
And calculating the energy E-alpha according to the time distribution mode1T phi, wherein,
a. and b and M are preset constants which can be obtained by performing data fitting on actual measured data.
Step S16, calculating the transmission rate R from the source end to the receiving end according to the related power parameter, the related channel gain parameter and the additive white Gaussian noise parameter.
In particular, at α2Receiving information sent by a source end in a T time period, and sending power on the nth subcarrier when the source end sends the information 
Channel gain of nth subcarrier from source end to nth subcarrier
Variance of additive white gaussian noise of relay
Calculating to obtain the transmission rate which can be realized by the source end to the relay transmission information
Wherein,
at α3The information is transmitted to the receiving end in the T time period,transmitting power of source end on nth subcarrier when transmitting information to receiving end
Channel gain from relay to receiving end
Variance of additive white Gaussian noise at receiving end
Calculating the transmission rate which can be realized by the relay to forward the information to the receiving end
Wherein,
at this time, the interference of the eavesdropping channel is considered, so that the transmission rate which can be finally realized from the source end to the receiving end is considered
Wherein,
step S17, calculating total energy consumption E according to the related power parameter, the related circuit loss parameter and the energy Etot。
Specifically, as can be seen from the above embodiments, the actual power consumption model can be represented as Ptotal＝P+PC，onIn this embodiment, when there is circuit loss at the source end, the relay, and the receiving end, it can be known from the consumption model that:
the source end transmits information and energy with the energy consumption of
The energy consumed by the relay is
The receiving end only needs to receive information and does not need to transmit information, so the energy consumed by the receiving end is 
Therefore, in combination with the energy E collected by the relay, the total energy consumption in the process of sending information from the source end to the receiving end
Step S18, according to the transmission rate R and the total energy consumption EtotA non-convex optimization problem is constructed with the maximum energy efficiency maxEE as the target.
In particular, the transmission power limit, the time allocation and the communication quality requirement are considered together, so that the transmission rate R and the total energy consumption E are taken into accounttotConstructing a non-convex optimization problem with maximum energy efficiency maxEE as a target, which can be expressed as:
wherein s.t. is a constraint condition of the maximum energy efficiency maxEE expression, and the constraints (1) and (2) represent that the transmission power of the source end transmission energy and information must not exceed the maximum available power threshold value P thereofMAXConstraint (3) indicates that the relay must collect energy equal to or greater than the energy consumed in forwarding information in order to ensure uninterrupted communication without considering the initial energy of the relay, and constraint (4) indicates that the relay must guarantee communication qualityThe full transmission rate must be higher than the set threshold RQ。
And step S19, converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, and calculating an optimal solution.
Specifically, as can be seen from equation 1, all optimization variables are divided into two categories, so we have a variable set a ═ { α ═ α1，α2，α3}，
Moreover, it can be known that the optimization problem belongs to a non-convex optimization problem and is difficult to solve, so this embodiment proves that
And
introducing variables y and z, planning theory according to nonlinear components, and defining new variables
Thereby converting the non-convex optimization problem into a D.C. optimization problem, wherein the variable y satisfies
Thereby obtaining
The variable z satisfies
And alpha1T phi is more than or equal to z, thereby obtaining
Thus, the above problem of maximizing energy efficiency can be described as:
the objective function of the transformed optimization problem is
For a given q value, the d.c. function is a constraint, and the 4 th, 5 th, 6 th, 7 th, 11 th and 12 th constraints in the constraint also belong to the d.c. function, namely, the form is f (x) -g (x), wherein x is a vector composed of all variables, and f (x) and g (x) both belong to convex functions, so that the problem belongs to the d.c. optimization problem, and the idea of solving the d.c. optimization problem is to approximate the constraint at each feasible point to obtain a convex optimization problem, and then solve the convex optimization problem to obtain an optimal solution. This iteration step continues until convergence. The specific solving process is as follows:
1: setting the calculation precision delta of the algorithm, setting the initial value of q to be 0, and enabling the iteration number i to be 0;
2: giving an initial value X (0, 0) meeting a variable constraint condition, and enabling the iteration number k to be 0, wherein X represents a vector formed by all variables in the optimization problem;
3: let i equal i + 1;
4: let k be k + 1:
5: solving the approximate convex optimization problem and obtaining an optimal solution X (i, k);
6: judging whether the absolute value of the difference between the objective function values of the k step and the k-1 step is smaller than or equal to the set precision, if so, performing the step 7, otherwise, jumping to the step 4;
7: the value of q is updated and,
8: and judging whether the difference between the q values of the i-th step and the i-1-th step is smaller than or equal to the set precision, if so, judging that the solution obtained in the i-th step is the final solution of the algorithm, applying the q value obtained in the i-th step to a formula 2 for solving to obtain the optimal solution, and otherwise, jumping to the 3-rd step for continuous execution.
Further, as shown in fig. 4, fig. 4 shows a third embodiment of the energy efficiency optimal allocation method of the relay network in the present invention. In this embodiment, the method under the preset condition is a power distribution method, and the method for optimally distributing the energy efficiency of the relay network includes the following steps:
And step S20, setting the power distribution proportion of the information and energy sent by the source end to theta, sending the information and energy to the source end by the source end within the former T/2 time, and forwarding the information to the receiving end by the source end within the later T/2 time.
Specifically, 0 < theta < 1, and T is the total transmission time.
Step S21, obtaining the sending power of the source end on the nth sub-carrier when the source end receives the information and energy sent by the source end
Transmitting power of source end on nth subcarrier when self-transmitting information to receiving end
It should be noted that channels from the source end to the relay, from the relay to the receiving end, and from the relay to the eavesdropping end are all multi-carrier transmissions, the number of available subcarriers is N, N represents the first subcarrier, and N belongs to N.
Step S22, obtaining the channel gain of the nth sub-carrier from the source end to itself
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
Step S23, obtaining source end sending informationCircuit loss with energy
Circuit loss in forwarding information
Circuit loss of receiving end in receiving information
Step S24, obtaining variance of self additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end 
Step S25, calculating the collected energy E sent by the source according to the relevant power parameter and the relevant channel gain parameter.
Specifically, in the previous T/2 time, the source end sends information and energy to the source end, and relays the received energy
Wherein,
a. and b and M are preset constants which can be obtained by performing data fitting on actual measured data.
Step S26, calculating the transmission rate R from the source end to the receiving end according to the related power parameter, the related channel gain parameter and the additive white Gaussian noise parameter.
Specifically, in the previous T/2 time, the source end sends a signal to the relay, and the transmission rate from the source end to the relay is at this time
Wherein,
in the later T/2 time, the relay sends the received information to the receiving end by using the collected energy, and the transmission rate of the relay to the receiving end is
Wherein,
at this time, the interference of the eavesdropping channel is considered, so that the transmission rate which can be finally realized from the source end to the receiving end is considered
Wherein,
step S27, calculating total energy consumption E according to the related power parameter, the related circuit loss parameter and the energy Etot。
Specifically, as can be seen from the above embodiments, the actual power consumption model can be represented as Ptotal＝P+PC，onIn this embodiment, when there is circuit loss at the source end, the relay, and the receiving end, it can be known from the consumption model that:
The source end transmits information and energy with the energy consumption of
The energy consumed by the relay is
And the receiving endOnly information reception is needed, and no information transmission is needed, so that the energy consumed by the receiving end is
Therefore, in combination with the energy E collected by the relay, the total energy consumption in the process of sending information from the source end to the receiving end
Step S28, according to the transmission rate R and the total energy consumption EtotA non-convex optimization problem is constructed with the maximum energy efficiency maxEE as the target.
In particular, the transmission power limit, the time allocation and the communication quality requirement are considered together, so that the transmission rate R and the total energy consumption E are taken into accounttotConstructing a non-convex optimization problem with maximum energy efficiency maxEE as a target, which can be expressed as:
wherein s.t. is a constraint condition of the maximum energy efficiency maxEE expression, and the constraint (1) indicates that the transmission power of the source end transmission energy and information does not exceed the maximum available power threshold value P of the source end transmission energy and informationMAXConstraint (2) indicates that the relay must collect energy equal to or greater than the energy consumed in forwarding information in order to ensure that communication is not interrupted, regardless of the initial energy of the relay, and constraint (3) indicates that the safe transmission rate must be higher than a set threshold R in order to ensure communication quality Q。
And step S29, converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, and calculating an optimal solution.
Specifically, according to the above formula 3, by proving
And introducing variables y and z, and defining a new variable θ PSn ═ PS, θ n according to a nonlinear fractional programming theory, so as to convert the non-convex optimization problem into a d.c. optimization problem, so that the problem of maximizing energy efficiency can be described as follows:
refer to the process of solving the d.c. optimization problem in the second embodiment to obtain the optimal solution, and refer to the process of solving the d.c. optimization problem in the second embodiment for details, which are not described herein again.
Fig. 5 shows an embodiment of the optimal energy efficiency distribution device for the relay network of the present invention. In this embodiment, the optimal energy efficiency distribution device for the relay network includes a dividing module 10, a parameter obtaining module 11, a collected energy calculating module 12, a transmission rate calculating module 13, an energy consumption calculating module 14, a constructing module 15, and a converting module 16.
The dividing module 10 is configured to receive information and energy sent by a source end based on a preset allocation manner and forward the information to a receiving end; the parameter acquisition module 11 is configured to acquire a relevant power parameter, a relevant channel gain parameter, a relevant circuit loss parameter when information is transmitted from the source end to the receiving end, and additive white gaussian noise parameters of the receiving end, and the eavesdropping end; a collected energy calculating module 12, configured to calculate the collected energy E according to the relevant power parameter and the relevant channel gain parameter; a transmission rate calculation module 13, configured to calculate a 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; energy consumption calculation module 14 for calculating a total energy consumption E based on the associated power parameter, the associated circuit loss parameter and the energy Etot(ii) a A building block 15 for determining the transmission rate R and the total energy consumption EtotConstructing a non-convex optimization problem with the maximum energy efficiency maxEE as a target; and the conversion module 16 is used for converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, and calculating an optimal solution.
On the basis of the above embodiment, in other embodiments, the preset allocation manner includes a time allocation manner or a power allocation manner.
Based on the foregoing embodiment, in other embodiments, as shown in fig. 6, when the preset allocation manner is a time allocation manner, the dividing module is configured to divide transmission time of the source sending the information to the receiver into α1T、α2T、α3T three time periods, wherein1+α2+α3T is the total transmission time, α1Collecting energy alpha sent by a source end in a T time period2Receiving information, alpha, sent by a source end in a time period of T3Transmitting the information to a receiving end in the T time period;
the parameter obtaining module 11 includes a first power parameter obtaining unit 1100, a first channel gain parameter obtaining unit 1101, a first circuit loss parameter obtaining unit 1102, and a first noise parameter obtaining unit 1103.
The first power parameter obtaining unit 1100 is configured to obtain the transmission power of the source end on the nth subcarrier when the energy sent by the source end is collected
Transmitting power on nth subcarrier when receiving source end transmitting information
Transmitting power of source end on nth subcarrier when information is forwarded to receiving end
Wherein N belongs to N, and N is a subcarrierThe number of waves; a first channel gain parameter obtaining unit 1101 for obtaining the channel gain of the nth sub-carrier from the source end to itself
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
A first circuit loss parameter obtaining unit 1102, configured to obtain a circuit loss when a source end sends energy to itself
Circuit loss when source sends information to itself
Circuit loss in forwarding information
And circuit loss of the receiving end in receiving information
A first noise parameter obtaining unit 1103 for obtaining variance of the additive white gaussian noise of itself
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
On the basis of the foregoing embodiment, in other embodiments, as shown in fig. 7, when the preset allocation manner is a power allocation manner, the dividing module is configured to set a power allocation ratio of information and energy sent by the source end to be θ, and in a former T/2 time, the source end sends information and energy to itself, and in a latter T/2 time, itself forwards the information to the receiving end, where T is 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 configured to obtain the transmission power of the source end on the nth subcarrier when the source end receives the information and the energy sent by the source end
Transmitting power of source end on nth subcarrier when self-transmitting information to receiving end
N belongs to N, and N is the number of subcarriers; a second channel gain parameter obtaining unit 1111, configured to obtain a channel gain from a source end to the nth subcarrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
A second circuit loss parameter obtaining unit 1112, configured to obtain circuit loss when the source end sends information and energy
Circuit loss in forwarding information
Circuit loss of receiving end in receiving information
A second noise parameter obtaining unit 1113, configured to obtain an additive white gaussian noise parameter, where the additive white gaussian noise parameter includes: variance of additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end 
For other details of the technical solution for implementing each module of the optimal distribution device for energy efficiency of the relay network in the foregoing embodiment, reference may be made to the description of the optimal distribution method for energy efficiency of the relay network in the foregoing embodiment, and details are not described here again.
Fig. 8 shows a schematic block diagram of a terminal according to another embodiment of the present invention, and referring to fig. 8, the terminal in this embodiment includes: one or at least two processors 80, a memory 81, and a computer program 810 stored in the memory 81 and executable on the processors 80. The processor 80, when executing the computer program 810, implements the steps in the relay network energy efficiency optimal allocation method described in the above embodiments, for example: step S1-step S7 shown in fig. 2. Alternatively, when the processor 80 executes the computer program 810, the functions of the modules/units in the above-mentioned relay network energy efficiency optimal distribution apparatus embodiment based on multi-mode integration are implemented, for example: the functionality of the modules 10-16 shown in fig. 5.
The computer program 810 may be divided into one or more modules/units, which are stored in the memory 81 and executed by the processor 80 to accomplish the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 810 in the terminal.
The terminal includes, but is not limited to, a processor 80, a memory 81. Those skilled in the art will appreciate that fig. 8 is only one example of a terminal and is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or different components, e.g., a terminal may also include input devices, output devices, network access devices, buses, etc.
The Processor 80 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 81 may be a read-only memory, a static storage device that may store static information and instructions, a random access memory, or a dynamic storage device that may store information and instructions, or may be an electrically erasable programmable read-only memory, a read-only optical disk, or other optical disk storage, magnetic disk storage media, or other magnetic storage devices. The memory 81 may be connected to the processor 80 via a communication bus or may be integrated with the processor 80.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The embodiment of the present application further provides a storage medium for storing a computer program, which contains program data for executing the embodiment of the optimal energy efficiency distribution method for a relay network described above. By executing the computer program stored in the storage medium, the optimal distribution method of energy efficiency of the relay network provided by the application can be realized.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by the computer program 810, and the computer program 810 can be stored in a computer-readable storage medium, where the computer program 810 can implement the steps of the methods described above when being executed by the processor 80. The computer program 810 comprises, inter alia, computer program code, which may be in the form of source code, object code, an executable file or some intermediate form. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. It should be noted that the computer readable medium may include any suitable increase or decrease as required by legislation and patent practice in the jurisdiction, for example, in some jurisdictions, computer readable media may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the device-like embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The embodiments of the present invention have been described in detail, but the present invention is only exemplary and is not limited to the embodiments described above. It will be apparent to those skilled in the art that any equivalent modifications or substitutions can be made within the scope of the present invention, and thus, equivalent changes and modifications, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the scope of the present invention.
Claims (10)
1. The optimal distribution method of the energy efficiency of the relay network is characterized in that the optimal distribution method is applied to the relay of a relay network system, and the relay network system also comprises a source end, a receiving end and an interception segment; the method comprises the following steps:
receiving information and energy sent by a source end based on a preset distribution mode and transmitting the information to a receiving end;
Acquiring a related power parameter, a related channel gain parameter and a related circuit loss parameter when information is transmitted from a source end to a receiving end, and additive white Gaussian noise parameters of the receiving end and an eavesdropping end;
calculating the collected energy E according to the related power parameter and the related channel gain parameter;
calculating the transmission rate R from the source end to the receiving end according to the related power parameter, the related channel gain parameter and the additive white Gaussian noise parameter;
calculating a total energy consumption E from the correlated power parameter, the correlated circuit loss parameter and the energy Etot；
According to the transmission rate R and the total energy consumption EtotConstructing a non-convex optimization problem with the maximum energy efficiency maxEE as a target;
and converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory, and calculating an optimal solution.
2. The optimal distribution method for energy efficiency of relay network according to claim 1, wherein the preset distribution mode comprises a time distribution mode or a power distribution mode.
3. The method according to claim 2, wherein when the preset allocation manner is a time allocation manner, the step of receiving information and energy transmitted by a source end and forwarding the information to a receiver end based on the preset allocation manner comprises:
Dividing the transmission time of the source end sending information to the receiving end into alpha1T、α2T、α3T three time periods, wherein1+α2+α3T is the total transmission time, α1Collecting energy sent by a source end in a T time period, wherein the alpha is2Receiving information sent by a source end in a T time period, wherein the alpha is3Transmitting the information to a receiving end in the T time period;
the step of acquiring the information sent by the receiving source end, the related power parameter, the related channel gain parameter and the related circuit loss parameter when the information is forwarded to the receiving end, and the additive white gaussian noise parameters of the receiving end, the receiving end and the eavesdropping end comprises the following steps:
acquiring the transmitting power of the source end on the nth subcarrier when the energy transmitted by the source end is collected
Transmitting power on nth subcarrier when receiving source end transmitting information
Transmitting power of source end on nth subcarrier when information is forwarded to receiving end
Wherein N belongs to N, and N is the number of subcarriers;
obtaining the channel gain of the nth sub-carrier from the source end to the nth sub-carrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
Obtaining circuit loss when source end sends energy to itself
Circuit loss when source sends information to itself
Circuit loss in forwarding information
And circuit loss of the receiving end in receiving information 
Obtaining the variance of the additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
4. The method according to claim 2, wherein when the preset allocation manner is a power allocation manner, the step of receiving information and energy transmitted by a source end and forwarding the information to a receiver end based on the preset allocation manner comprises:
setting a power distribution proportion theta for sending information and energy by a source end, sending the information and the energy to the source end by the source end within the former T/2 time, and forwarding the information to a receiving end by the source end within the later T/2 time, wherein T is total transmission time;
the step of acquiring the information sent by the receiving source end, the related power parameter, the related channel gain parameter and the related circuit loss parameter when the information is forwarded to the receiving end, and the additive white gaussian noise parameters of the receiving end, the receiving end and the eavesdropping end comprises the following steps:
obtaining the transmitting power of the source end on the nth subcarrier when the source end receives the information and the energy sent by the source end
Transmitting power of source end on nth subcarrier when self-transmitting information to receiving end
N belongs to N, and N is the number of subcarriers;
Obtaining the channel gain of the nth sub-carrier from the source end to the nth sub-carrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
Circuit loss in obtaining source end transmission information and energy
Circuit loss in forwarding information
Circuit loss of receiving end in receiving information
Obtaining the variance of the additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
5. An apparatus for optimally allocating energy efficiency of a relay network, comprising:
the dividing module is used for receiving the information and the energy sent by the source end based on a preset distribution mode and forwarding the information to the receiving end;
the parameter acquisition module is used for acquiring related power parameters, related channel gain parameters and related circuit loss parameters when information is transmitted from the source end to the receiving end, and additive white Gaussian noise parameters of the receiving end and the eavesdropping end;
the collected energy calculation module is used for calculating the collected energy E according to the relevant power parameter and the relevant channel gain parameter;
a transmission rate calculation module, configured to calculate a transmission rate R from the source end to the receiver end according to the correlated power parameter, the correlated channel gain parameter, and the additive white gaussian noise parameter;
An energy consumption calculation module for calculating a total energy consumption E based on the correlated power parameter, the correlated circuit loss parameter and the energy Etot；
A construction module for constructing a total energy consumption E based on the transmission rate R and the total energy consumptiontotConstructing a non-convex optimization problem with the maximum energy efficiency maxEE as a target;
and the conversion module is used for converting the non-convex optimization problem into a D.C. optimization problem by introducing variables and according to a nonlinear fractional programming theory and calculating an optimal solution.
6. The optimal distribution device for energy efficiency of relay network according to claim 5, wherein the preset distribution mode comprises a time distribution mode or a power distribution mode.
7. The device of claim 6, wherein when the preset allocation manner is a time allocation manner, the dividing module is configured to divide the transmission time of the source sending the message to the sink into α1T、α2T、α3T three time periodsIn which α is1+α2+α3T is the total transmission time, α1Collecting energy sent by a source end in a T time period, wherein the alpha is2Receiving information sent by a source end in a T time period, wherein the alpha is3Transmitting the information to a receiving end in the T time period;
The parameter acquisition module comprises:
a first power parameter obtaining unit, configured to obtain the transmission power of the source end on the nth subcarrier when the energy sent by the source end is collected
Transmitting power on nth subcarrier when receiving source end transmitting information
Transmitting power of source end on nth subcarrier when information is forwarded to receiving end
Wherein N belongs to N, and N is the number of subcarriers;
a first channel gain parameter obtaining unit, configured to obtain a channel gain from a source end to the nth subcarrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
A first circuit loss parameter obtaining unit, configured to obtain a circuit loss when a source end sends energy to the first circuit loss parameter obtaining unit
Circuit loss when source sends information to itself
Circuit loss in forwarding information
And circuit loss of the receiving end in receiving information
A first noise parameter obtaining unit for obtaining variance of self additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And variance of additive white Gaussian noise at eavesdropping end
8. The optimal distribution device of energy efficiency of the relay network according to claim 6, wherein when the preset distribution mode is a power distribution mode, the dividing module is configured to set a power distribution ratio of information and energy sent by the source end to θ, and the source end sends information and energy to itself within a former T/2 time, and forwards information to the receiving end by itself within a latter T/2 time, where T is a total transmission time;
The parameter acquisition module comprises:
a second power parameter obtaining unit for obtaining the transmission power of the source end on the nth subcarrier when the source end receives the information and energy sent by the source end
Source end on nth subcarrier when self-transmitting information to receiving endTransmit power of
N belongs to N, and N is the number of subcarriers;
a second channel gain parameter obtaining unit for obtaining the channel gain of the nth sub-carrier from the source end to the nth sub-carrier
Channel gain from self to receiving end
And channel gain from itself to the eavesdropping end
A second circuit loss parameter obtaining unit for obtaining the circuit loss when the source end sends information and energy
Circuit loss in forwarding information
Circuit loss of receiving end in receiving information
A second noise parameter obtaining unit, configured to obtain the additive white gaussian noise parameter, where the additive white gaussian noise parameter includes: variance of additive white Gaussian noise
Variance of additive white Gaussian noise at receiving end
And additive white Gaussian noise at eavesdropping endVariance (variance)
9. A terminal comprising a memory and a processor, the processor coupled to the memory, the memory having stored thereon a computer program operable on the processor;
The processor, when executing the computer program, performs the steps in the method for energy efficiency optimized distribution of a relay network according to any of claims 1-4.
10. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps in the method for energy efficient optimal distribution of relay networks according to any of claims 1-4.
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