A method and system for optimizing throughput in wireless power supply networks

Abstract

This invention proposes a method and system for optimizing the throughput of wireless power supply networks, comprising: constructing a wireless power supply communication system model with energy and delay constraints; constructing a throughput maximization problem P0; S3, based on the throughput maximization problem P0, constructing a charging energy maximization sub-problem P1 under constraints of total energy and energy collection duration, and solving it under two cases: low and high total available energy of the wireless power supply base station; based on the throughput maximization problem P0, constructing and solving a throughput maximization sub-problem P2 for energy collection users with a given energy collection strategy and wireless communication duration as the variable; and transforming the throughput maximization problem P0 into a single-variable optimization problem P3 based on the characteristics of the optimal wireless energy transmission strategy and the optimal wireless communication duration strategy, and solving it. This invention improves the actual throughput performance of wireless power supply communication networks and meets the high-efficiency communication requirements in complex dynamic network environments.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of wireless communication, and particularly relates to a wireless power supply network throughput optimization method and system. BACKGROUND

[0002] With the rapid development of wireless communication technology and wireless power transfer (WPT) technology, the traditional communication mode relying on battery power supply is facing problems such as inconvenient energy supply and limited device life. Therefore, a wireless power communication network (WPCN) emerges as the times require. The network relies on the wireless power transfer technology to realize that the terminal device continuously obtains energy without manual battery replacement, and then supports its communication task, and is widely used in the fields of Internet of Things, sensor network and remote monitoring. In a typical WPCN system, the energy-limited user first obtains wireless energy from the base station, and then transmits data to the target receiver using the collected energy. However, due to the limited energy and delay resources, how to optimize the system throughput under the limited energy budget and system delay constraint becomes a key problem to realize efficient wireless power communication. The traditional research assumes that the energy collection process has linear characteristics, that is, the collected energy is proportional to the received radio frequency power, but the actual energy collection circuit has nonlinear characteristics, especially in the low power and high power areas, the energy collection efficiency is not monotonous, and ignoring this characteristic will lead to deviation of the system optimization result from the actual situation.

[0003] In addition, in order to further improve the system performance, the existing research begins to explore the dynamic control strategy of the base station transmission power, and adjusts the power distribution in the energy supply stage to adapt to different energy demands and channel conditions. However, considering the dynamic power control under the nonlinear energy collection model, the non-convexity of the optimization problem is enhanced, and the variable dimension is increased, so that the traditional convex optimization or iterative algorithm is difficult to obtain the global optimal solution. Especially in the case of time-varying function of the base station transmission power, how to realize the optimal design of the system throughput under the premise of guaranteeing the energy budget and delay constraint, there is still a lack of perfect solution.

[0004] Therefore, an optimal resource allocation method considering the nonlinear energy collection characteristics, energy and delay constraints, and supporting the time-varying transmission power control of the base station is needed to improve the actual throughput performance of the wireless power communication network and meet the efficient communication demand in complex dynamic network environment. SUMMARY

[0005] The present application aims at the above-mentioned problems existing in the prior art, and provides a wireless power supply communication network throughput optimization method and system based on a nonlinear energy collection model.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] A method for optimizing throughput in a wireless power supply network includes the following steps:

[0008] S1. Construct a wireless power supply and communication system model with energy constraints and time delay constraints, divide it into energy harvesting stage and wireless information transmission stage, and calculate the total charging energy of energy harvesting users and the wireless communication signal-to-noise ratio;

[0009] S2. Based on the total charging energy and the wireless communication signal-to-noise ratio, construct the throughput maximization problem P0;

[0010] S3. Based on the throughput maximization problem P0, construct the charging energy maximization sub-problem P1 under the constraints of total energy and energy collection time, and solve it in two cases: when the total available energy of the wireless power supply base station is less and when it is more, to obtain the optimal wireless energy transmission strategy considering the energy budget and maximum power limit.

[0011] S4. Based on the throughput maximization problem P0, construct and solve the throughput maximization subproblem P2 for energy harvesting users under a given energy harvesting strategy, with wireless communication duration as the variable; obtain the optimal wireless communication duration strategy under a given energy harvesting strategy.

[0012] S5. Based on the characteristics of the optimal wireless energy transmission strategy and the optimal wireless communication duration strategy, the throughput maximization problem P0 is transformed into a single-variable optimization problem P3 and solved to obtain the optimal base station wireless energy transmission strategy, wireless energy transmission duration, and wireless communication duration strategy.

[0013] Further, S1 includes:

[0014] S11. During the energy harvesting phase, the wireless power supply base station sends radio frequency signals to the energy harvesting user. The energy harvesting user converts the radio frequency signals into direct current through a nonlinear energy harvesting device. The total charging energy of the energy harvesting user is:

[0015]

[0016] in, The total charging energy for energy harvesting users, This represents the nonlinear relationship between charging power and received RF signal power. For wireless power base stations RF signal power at any given time For the duration of energy harvesting, For path loss between wireless power supply base stations and energy harvesting users;

[0017] S12. In the information transmission phase, the energy harvesting user transmits communication data to the wireless power base station in the wireless information transmission phase, and the wireless communication signal-to-noise ratio of the energy harvesting user is:

[0018]

[0019] wherein, is the wireless communication signal-to-noise ratio of the energy harvesting user, denotes the wireless communication duration, is the path loss between the energy harvesting user and the information receiver, is the communication noise power.

[0020] Further, the throughput maximization problem P0 in S2 is:

[0021]

[0022] wherein, is the upper limit of the total energy budget of the wireless power base station, is the upper limit of the instantaneous transmit power of the wireless power base station, is the upper limit of the total latency of the energy harvesting phase and the wireless information transmission phase, is the throughput of the wireless power network; denotes the maximization of the throughput of the wireless power network by jointly optimizing the instantaneous transmit power of the wireless power base station , the energy harvesting collection time and the wireless communication duration .

[0023] Further, the throughput of the wireless power network is:

[0024] .

[0025] Further, the charging energy maximization sub-problem P1 under the existence of total energy and energy harvesting duration constraints constructed in S3 is:

[0026]

[0027] wherein, denotes the upper limit of the energy harvesting phase duration; denotes the maximization of the total charging amount of the energy harvesting user by jointly optimizing the instantaneous transmit power of the wireless power base station and the energy harvesting time .

[0028] Further, the optimal wireless energy transmission strategy under the conditions of energy budget and maximum power limitation in S3 is:

[0029]

[0030]

[0031] in, To achieve the maximum energy conversion efficiency power level for wireless power base station transmission; The optimal constant power for transmission by wireless power base stations. The optimal wireless power transmission duration.

[0032] Furthermore, the throughput maximization subproblem P2 in S4, which uses wireless communication duration as a variable, is:

[0033]

[0034] Optimal wireless communication duration Represented as:

[0035]

[0036] in, To obtain the optimal total charging amount for energy harvesting users by solving the subproblem P1 that maximizes charging amount; This indicates that by optimizing the duration of wireless communication Maximize system throughput.

[0037] Furthermore, in step S5, the throughput maximization problem P0 is transformed into a single-variable optimization problem P3:

[0038]

[0039] in, , These represent the maximum duration of the energy harvesting phase. Optimal charging power and optimal energy collection duration for users under the optimal wireless energy transfer strategy; This indicates that by optimizing the energy harvesting duration Maximize system throughput.

[0040] Furthermore, the global optimal solution of the single-variable optimization problem P3 using the one-dimensional search method in S5 includes:

[0041] For any Substituting the closed-form solutions of the optimal wireless power transfer strategy in S3 and the optimal wireless communication duration strategy in S4 respectively, the corresponding system throughput is obtained; by traversing... By comparing the corresponding system throughput values, the optimal transmit power can be obtained. Optimal wireless power transfer duration and optimal wireless communication duration .

[0042] On the other hand, the present invention provides a wireless power network throughput optimization system, comprising:

[0043] The wireless power supply communication system model building module is used to construct a wireless power supply communication system model with energy constraints and time delay constraints, divide the energy harvesting stage and the wireless information transmission stage, and calculate the total charging energy of the energy harvesting user and the wireless communication signal-to-noise ratio.

[0044] A throughput maximization problem P0 construction module is used to construct the throughput maximization problem P0 based on the total charging energy and the wireless communication signal-to-noise ratio;

[0045] The module for constructing the subproblem P1 is used to construct the subproblem P1 for maximizing charging energy under the constraints of total energy and energy collection time, based on the throughput maximization problem P0. It solves the subproblem P1 for maximizing charging energy under the constraints of total energy and energy collection time, and solves the subproblem P1 for the two cases of low and high total available energy of the wireless power supply base station, respectively, to obtain the optimal wireless energy transmission strategy considering energy budget and maximum power limit.

[0046] The module for constructing the subproblem P2 is used to construct and solve the subproblem P2 for maximizing throughput of the energy harvesting user under a given energy harvesting strategy, with wireless communication duration as the variable, based on the throughput maximization problem P0; and to obtain the optimal wireless communication duration strategy under the given energy harvesting strategy.

[0047] The solution module is used to transform the throughput maximization problem P0 into a single-variable optimization problem P3 based on the characteristics of the optimal wireless energy transmission strategy and the optimal wireless communication duration strategy, and then solve it to obtain the optimal base station wireless energy transmission strategy, wireless energy transmission duration, and wireless communication duration strategy.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] This invention, through mathematical analytical analysis, derives and rigorously proves the closed-form analytical solution of the optimal charging strategy in scenarios where the base station's power can be dynamically adjusted, effectively solving the problem of unoptimizable performance due to the infinite dimensionality of variables. Through in-depth analysis of the system's monotonicity, the originally complex dynamic power and time joint optimization problem is transformed into a single-variable, one-dimensional, low-complexity search problem. Compared to existing suboptimal strategies relying on relaxation, approximation, and interior-point methods, this invention not only boasts extremely low computational complexity but also achieves optimal throughput, possessing both theoretical value and promising practical applications. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0051] Figure 1 This is an overall flowchart of the method described in the embodiments of the present invention.

[0052] Figure 2 This is a structural diagram of the wireless power supply communication network architecture according to an embodiment of the present invention.

[0053] Figure 3 This is a schematic diagram illustrating the maximum throughput of the system under different total system latency in embodiments of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0055] Example 1

[0056] like Figure 1 The diagram shown is a flowchart of a method according to an embodiment of the present invention. The implementation process includes the following steps:

[0057] S1, such as Figure 2 As shown, a wireless power supply and communication system model with energy and time delay constraints is constructed, dividing the system into an energy harvesting stage and a wireless information transmission stage, and calculating the total charging energy of the energy harvesting user and the wireless communication signal-to-noise ratio.

[0058] Specifically, S1 includes:

[0059] S11, Energy Harvesting Phase: The wireless power supply base station sends radio frequency signals to the energy harvesting users, who then convert the radio frequency signals into DC signals through their energy harvesting devices to charge the energy harvesting users.

[0060] The total charging energy of the energy harvesting user is:

[0061]

[0062] In the above formula, The total charging energy for energy harvesting users, This represents the nonlinear relationship between charging power and received RF signal power. For wireless power base stations RF signal power at any given time For the duration of energy harvesting, For path loss between wireless power supply base stations and energy harvesting users;

[0063] S12. Utilizing the energy obtained during the energy harvesting phase, the energy harvesting user transmits communication data to the wireless power supply base station during the wireless information transmission phase. The wireless communication signal-to-noise ratio of the energy harvesting user is:

[0064]

[0065] In the above formula, For energy harvesting users' wireless communication signal-to-noise ratio, Indicates the duration of wireless communication. For path loss between energy harvesting users and information receivers, This represents the communication noise power.

[0066] S2. Based on the total charging energy and the wireless communication signal-to-noise ratio, construct the throughput maximization problem P0;

[0067] Specifically, S2 includes:

[0068] S21. The throughput of the wireless power supply network is calculated using the following formula:

[0069]

[0070] In the above formula, This refers to the throughput of the wireless power supply network.

[0071] S22. Based on the throughput formula of the wireless power supply network derived in S2, the joint optimization problem of dynamic transmit power, energy harvesting time, and communication time of the wireless power supply base station with the objective of maximizing the throughput of the wireless power supply network is constructed as follows:

[0072]

[0073] In the above formula, The upper limit of the total energy budget for wireless power supply base stations. The instantaneous transmit power limit for wireless power base stations. This is the upper limit of the total latency for the energy harvesting phase and the wireless information transmission phase. This indicates that by jointly optimizing the instantaneous transmit power of wireless power supply base stations... Energy collection time and duration of wireless communication This maximizes the throughput of the wireless power supply network.

[0074] S3. Based on the throughput maximization problem P0, construct the charging energy maximization sub-problem P1 under the constraints of total energy and energy collection time, and solve it in two cases: when the total available energy of the wireless power supply base station is less and when it is more, to obtain the optimal wireless energy transmission strategy considering the energy budget and maximum power limit.

[0075] Specifically, S3 includes:

[0076] S31. From the throughput expression of the wireless power supply network in S2, it can be seen that the throughput is related to the total charging energy of the energy harvesting users. It exhibits a monotonically increasing relationship, meaning more... This is beneficial for increasing throughput. Therefore, to maximize throughput, the first step is to solve the problem of maximizing the total charging energy of energy harvesting users. There exists a subproblem P1 for maximizing charging energy under constraints of total energy and energy harvesting duration:

[0077]

[0078] in The upper limit of the total energy budget for wireless power supply base stations. The instantaneous transmit power limit for wireless power base stations. This is the upper limit for the delay during the energy harvesting phase; This indicates that by jointly optimizing the instantaneous transmit power of wireless power supply base stations... and energy harvesting time This maximizes the total charging amount for users who collect energy.

[0079] S32. Set the power level of the wireless power supply base station to achieve maximum energy conversion efficiency. ,Right now

[0080]

[0081] Where P represents any transmit power level of the wireless power supply base station. This indicates finding the transmit power. This enables the energy harvesting efficiency of energy harvesting users when the wireless power base station performs wireless power transmission at this power level. Reach the maximum.

[0082] S32, When the total available energy of the wireless power supply base station In rare cases, that is At that time, the optimal strategy for wireless power transmission is: the wireless power supply base station operates at a constant power. Transmission is carried out, and the energy harvesting time is To maximize user energy collection, among which This indicates the optimal transmit power level for wireless power supply base stations. This indicates the optimal energy harvesting time.

[0083] This optimal strategy can be proven by contradiction: Assume there exists another wireless power supply strategy. The strategy includes Each sub-time slot has a different transmission power at the wireless power base station within each sub-time slot. Provide energy. Indicates the wireless power supply base station in the 1st Transmit power in each energy harvesting sub-slot. This wireless power supply strategy. To meet the total power supply duration constraint: ,in Indicates the first The duration of each energy harvesting sub-slot satisfies the total energy constraint of the wireless power supply base station: ,in Indicates the wireless power supply base station in the 1st The total energy consumption in each energy harvesting sub-slot. If, under this strategy, the total harvested energy of the energy harvesting user is higher than that under the constant power strategy, i.e. Then there must be

[0084]

[0085] in Indicates wireless power supply strategy Below, the total energy collected by the energy harvesting user. However, due to the defined... Right now Already made Reaching the maximum, for any All have Therefore, the assumed wireless power supply strategy Under these conditions, the total energy collected by the energy harvesting user meets the following requirements. .because ,so And because , Therefore, we get This contradicts the assumption, proving that the constant power strategy is optimal.

[0086] S33, When the total available energy of the wireless power supply base station In most cases, that is At that time, the optimal strategy for wireless power transmission is: the wireless power supply base station operates at a constant power. Transmission is carried out, and the energy harvesting time is This is to maximize user energy harvesting. The proof is as follows:

[0087] when For any wireless power transmission scheme involving multiple energy harvesting sub-slots with different transmit powers in each sub-slot, the transmit power of all sub-slots should satisfy the following condition: ,in Indicates the wireless power supply base station in the 1st The transmit power in each energy harvesting sub-slot This indicates the number of sub-time slots. The reason is that for a base station with a given energy budget... In the case of using a lower Transmission power It would take longer to supply the same amount of energy, and its energy harvesting efficiency would be lower than that of other methods. ,Right now Therefore, in order to maximize user energy harvesting within a limited energy budget and energy harvesting duration constraints, methods lower than [a certain limit] should be avoided. This is an inefficient power supply strategy. Specifically, the transmit power of all power supply sub-slots must be greater than or equal to... This is to improve overall energy harvesting efficiency and reduce power supply delay.

[0088] Furthermore, for any continuous, differentiable, and monotonically increasing function... If it is in the interval The above is a convex function, and in The above is a concave function. It is the turning point of the concave-convex interval, and satisfies Then the function The independent variable corresponding to the maximum value satisfies: Based on this property, a nonlinear energy harvesting function is considered. The function is convex in the low-power region and concave in the high-power region. The inflection point of concavity / convexity is defined as follows: Then it satisfies That is, optimal transmission power lie in The concave interval. Combined with the previously discussed... For any wireless power transmission scheme involving multiple energy harvesting sub-slots with different transmit powers in each sub-slot, the transmit power of all sub-slots should satisfy the following condition: , can be appropriate In any wireless power transmission scheme involving multiple energy harvesting sub-time slots with different transmit powers in each sub-time slot, the transmit power of the wireless power supply base station is located at... The concave interval of the function.

[0089] Furthermore, based on the properties of concave functions, for any two energy harvesting sub-slots... and The durations of the two energy harvesting sub-slots are respectively and The combined constant-power emission scheme can achieve higher energy harvesting efficiency, namely:

[0090]

[0091] in Indicates the first The proportion factor of each time slot is defined as follows: , Indicates the first The proportion factor of each time slot is defined as follows: And satisfy This indicates that any multi-slot scheme can ultimately be equivalent to a single constant-power transmission scheme, providing... , .

[0092] Based on the above conclusions, the optimal wireless power transfer strategy considering energy budget and maximum power constraints is as follows:

[0093]

[0094]

[0095] in, To achieve the maximum energy conversion efficiency power level for wireless power base station transmission; The optimal constant power for transmission by wireless power base stations. The optimal wireless power transmission duration.

[0096] S4. Based on the throughput maximization problem P0, construct and solve the throughput maximization subproblem P2 for energy harvesting users under a given energy harvesting strategy, with wireless communication duration as the variable; obtain the optimal wireless communication duration strategy under a given energy harvesting strategy.

[0097] Specifically, S4 includes:

[0098] S41. Given an energy harvesting user and a specific energy harvesting strategy, the optimization problem P2, which maximizes throughput with wireless communication duration as the variable, is as follows:

[0099]

[0100] in This indicates the upper limit of the total system latency. This indicates the optimal energy harvesting phase duration. This indicates that by optimizing the duration of wireless communication To maximize system throughput, this embodiment proposes the following mathematical lemma to solve optimization problem P2:

[0101] set up It is a concave and monotonically increasing function that satisfies Then for any constant ,function In the interval It increases monotonically.

[0102] According to this lemma, the system throughput function in P2 about It is monotonically increasing. Therefore, the optimal information transmission duration is... It can be represented as:

[0103] .

[0104] S5. Based on the characteristics of the optimal wireless energy transmission strategy and the optimal wireless communication duration strategy, the throughput maximization problem P0 is transformed into a single-variable optimization problem P3 and solved to obtain the optimal base station wireless energy transmission strategy, wireless energy transmission duration, and wireless communication duration strategy.

[0105] Specifically, based on the characteristics of the optimal wireless energy transfer scheme and the optimal wireless communication duration strategy in S3 and S4, the optimization problem model P0 is transformed into a single-variable optimization problem P3:

[0106]

[0107] in This indicates that by optimizing the energy harvesting duration Maximize system throughput; a one-dimensional search method can be used to efficiently find the global optimum of P3. Specifically, for any... By selecting and substituting the optimal wireless energy transfer strategy from step S3 and the optimal wireless communication duration strategy from step S4 into their closed-form solutions, the corresponding system throughput is obtained. This is achieved by iterating through... By comparing the corresponding system throughput values, the optimal transmit power can be obtained. Optimal wireless power transfer duration and optimal information transmission duration This achieves the optimal resource allocation design for system throughput, as shown in the following figure. Figure 3 As shown in the figure. The method in this embodiment has the advantages of low computational complexity and guaranteed global optimality, and is suitable for resource allocation optimization needs in various wireless power supply communication scenarios.

[0108] Example 2

[0109] This embodiment provides a wireless power network throughput optimization system, including:

[0110] The wireless power supply communication system model building module is used to construct a wireless power supply communication system model with energy constraints and time delay constraints, divide the energy harvesting stage and the wireless information transmission stage, and calculate the total charging energy of the energy harvesting user and the wireless communication signal-to-noise ratio.

[0111] A throughput maximization problem P0 construction module is used to construct the throughput maximization problem P0 based on the total charging energy and the wireless communication signal-to-noise ratio;

[0112] The module for constructing the subproblem P1 is used to construct the subproblem P1 for maximizing charging energy under the constraints of total energy and energy collection time, based on the throughput maximization problem P0. It solves the subproblem P1 for maximizing charging energy under the constraints of total energy and energy collection time, and solves the subproblem P1 for the two cases of low and high total available energy of the wireless power supply base station, respectively, to obtain the optimal wireless energy transmission strategy considering energy budget and maximum power limit.

[0113] The module for constructing the subproblem P2 is used to construct and solve the subproblem P2 for maximizing throughput of the energy harvesting user under a given energy harvesting strategy, with wireless communication duration as the variable, based on the throughput maximization problem P0; and to obtain the optimal wireless communication duration strategy under the given energy harvesting strategy.

[0114] The solution module is used to transform the throughput maximization problem P0 into a single-variable optimization problem P3 based on the characteristics of the optimal wireless energy transmission strategy and the optimal wireless communication duration strategy, and then solve it to obtain the optimal base station wireless energy transmission strategy, wireless energy transmission duration, and wireless communication duration strategy.

[0115] It should be understood that any parts not described in detail in this specification belong to the prior art.

[0116] It should be understood that the above description of the preferred embodiments is quite detailed, but this should not be construed as limiting the scope of protection of this invention. It is neither necessary nor possible to exhaustively describe all possible implementations. Those skilled in the art, guided by this invention, can make substitutions or modifications without departing from the scope of the claims, all of which fall within the scope of protection of this invention. The scope of protection of this invention should be determined by the appended claims.

Claims

1. A method for optimizing throughput in wireless power supply networks, characterized in that, The method comprises the following steps: S1, constructing a wireless power supply communication system model with energy constraints and time delay constraints, dividing energy collection stage and wireless information transmission stage, calculating total charging energy of energy collection user and wireless communication signal-to-noise ratio; S2, based on the total charging energy and the wireless communication signal-to-noise ratio, constructing a throughput maximization problem P0; S3, based on the throughput maximization problem P0, constructing a charging energy maximization sub-problem P1 under the constraint of total energy and energy collection time length, and solving under the conditions of less and more total available energy of the wireless power supply base station respectively, to obtain an optimal wireless energy transmission strategy under the conditions of energy budget and maximum power limit; S4, based on the throughput maximization problem P0, constructing a throughput maximization sub-problem P2 with wireless communication time length as a variable under the given energy collection strategy and solving; obtaining the optimal wireless communication time length strategy under the given energy collection strategy; S5, based on the characteristics of the optimal wireless energy transmission strategy and the optimal wireless communication time length strategy, converting the throughput maximization problem P0 into a single variable optimization problem P3 and solving, to obtain the optimal base station wireless energy transmission strategy, wireless energy transmission time length and wireless communication time length strategy.

2. The wireless power network throughput optimization method of claim 1, wherein, The S1 comprises: S11. In the energy collection stage, the wireless power supply base station sends radio frequency signals to the energy collection user, and the energy collection user converts the radio frequency signals into direct current through a non-linear energy collection device. The total charging energy of the energy collection user is: in, The total charging energy for energy harvesting users, This represents the nonlinear relationship between charging power and received RF signal power. For wireless power base stations RF signal power at any given time For the duration of energy harvesting, For path loss between wireless power supply base stations and energy harvesting users; S12. In the information transmission stage, the energy collection user sends communication data to the wireless power supply base station in the wireless information transmission stage. The wireless communication signal-to-noise ratio of the energy collection user is: wherein, is the wireless communication signal-to-noise ratio for the energy harvesting user, denotes the wireless communication duration, is the path loss between the energy harvesting user and the information receiver, is the communication noise power.

3. The wireless power network throughput optimization method of claim 2, wherein, The throughput maximization problem P0 in the S2 is: wherein, is an upper bound on the total energy budget of the wireless powered base station, is an upper bound on the instantaneous transmit power of the wireless powered base station, is an upper bound on the total latency of the energy harvesting phase and the wireless information transfer phase, is the throughput of the wireless powered network; denotes maximizing the throughput of the wireless powered network by jointly optimizing the instantaneous transmit power of the wireless powered base station, the energy harvesting collection time and the wireless communication duration.

4. The wireless power network throughput optimization method of claim 3, wherein, Throughput of a wireless power network To: 。 5. The wireless power network throughput optimization method of claim 3, wherein, The charging energy maximization sub-problem P1 constructed in the S3 under the constraint of total energy and energy collection time length is: wherein, denotes an upper bound on the length of the energy harvesting phase; denotes maximizing the total charge of the energy harvesting users by jointly optimizing the instantaneous transmit power of the wireless power base station and the energy harvesting time .

6. The wireless power network throughput optimization method of claim 5, wherein, The optimal wireless energy transmission strategy under the conditions of energy budget and maximum power limit in the S3 is: wherein, a maximum energy conversion efficiency power level for the wireless powered base station transmission to be achieved, an optimal constant power for the wireless powered base station to transmit at, an optimal wireless energy transmission duration.

7. The wireless power network throughput optimization method of claim 6, wherein, The throughput maximization sub-problem P2 with wireless communication time length as a variable in the S4 is: Optimal wireless communication duration is represented as: wherein, the optimal total charging amount of the energy harvesting users obtained for solving the charging amount maximization subproblem P1 ; denotes the optimization of the wireless communication duration maximizes the system throughput.

8. The wireless power network throughput optimization method of claim 7, wherein, The conversion of the throughput maximization problem P0 into a single variable optimization problem P3 in the S5 is: wherein, , respectively represent the optimal charging power and the optimal energy harvesting duration of the energy harvesting user under the optimal wireless energy transfer strategy when the upper limit of the energy harvesting duration is maximize the system throughput.​​ 9. The wireless power network throughput optimization method of claim 8, wherein, The global optimal solution of the single variable optimization problem P3 in the S5 by using one-dimensional search method comprises: For any , respectively, the closed-form solution of the optimal wireless energy transfer strategy in S3 and the optimal wireless communication duration strategy in S4 are substituted to obtain the corresponding system throughput; by traversing and comparing the corresponding system throughput values, the optimal transmit power , the optimal wireless energy transfer duration and the optimal wireless communication duration can be obtained.

10. A wireless power network throughput optimization system, comprising: It comprises: A wireless power supply communication system model construction module is configured to construct a wireless power supply communication system model with energy constraints and time delay constraints, divide energy collection stage and wireless information transmission stage, and calculate total charging energy of energy collection user and wireless communication signal-to-noise ratio; A throughput maximization problem P0 construction module is configured to construct a throughput maximization problem P0 based on the total charging energy and the wireless communication signal-to-noise ratio; A maximization sub-problem P1 construction module is configured to construct a charging energy maximization sub-problem P1 under the constraint of total energy and energy collection time length based on the throughput maximization problem P0, and solve under the conditions of less and more total available energy of the wireless power supply base station respectively, to obtain an optimal wireless energy transmission strategy under the conditions of energy budget and maximum power limit; a maximization sub-problem P2 construction module, configured to construct and solve a throughput maximization sub-problem P2 with wireless communication duration as a variable for energy harvesting users under a given energy harvesting policy based on the throughput maximization problem P0; obtain an optimal wireless communication duration strategy under the given energy harvesting policy; a solving module, configured to transform the throughput maximization problem P0 into a single variable optimization problem P3 and solve the single variable optimization problem P3 to obtain an optimal base station wireless energy transmission strategy, a wireless energy transmission duration and a wireless communication duration strategy based on characteristics of the optimal wireless energy transmission strategy and the optimal wireless communication duration strategy; the wireless powered network throughput optimization system is configured to perform the steps of the wireless powered network throughput optimization method of any one of claims 1-9.

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