CN110312269B - Wireless energy-carrying communication system and method based on energy-information balance transmission - Google Patents
Wireless energy-carrying communication system and method based on energy-information balance transmission Download PDFInfo
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Abstract
The invention discloses a wireless energy-carrying communication system based on energy-information balance transmission and a method thereof, which mainly solve the problem that the existing energy-carrying communication system cannot realize optimal energy distribution. The system of the invention comprises a base station end part and a user end part, wherein the base station end part consists of a baseband communication module and a transmitting antenna module; the user end part consists of a receiving antenna module, a storage battery module, an electric quantity detection module, an energy distribution module, an information receiving module and an energy acquisition module. The method comprises the following implementation steps: (1) a base station end sends a signal; (2) receiving signals by a user terminal antenna; (3) detecting the electric quantity of the storage battery; (4) an energy distribution module; (5) receiving information; and (6) energy collection. The invention realizes optimal allocation of information transmission and energy collection, and is suitable for energy-carrying communication of a straight-chain link.
Description
Technical Field
The invention relates to a wireless energy-carrying communication system based on energy-information balance transmission and a method thereof, belonging to the technical field of wireless communication.
Background
In recent years, the popularization of mobile internet and intelligent terminals makes the requirements on wireless communication quality and transmission rate higher and higher, and new challenges are continuously provided for wireless communication technology. With the development of a new generation of mobile communication technology and the appearance of wearable equipment, the hardware configuration of a communication terminal is higher and higher, the energy consumption is higher and higher, and how to effectively provide energy for an intelligent terminal for a long time is a very critical problem for realizing green communication and is a difficult problem for restricting the further development of a communication system.
Current research addresses the increasing energy demand of mobile terminals, mainly from both "open source" and "throttling". On the one hand, throttling is to improve the energy efficiency of the communication system and reduce the energy consumption. On the other hand, "open source" refers to a method of increasing energy supply of a communication terminal by using techniques such as wireless energy transmission and energy harvesting. Radio energy transmission utilizes radio means to convert power generated by a power plant into radio waves to be transmitted, and the radio waves are collected by a specific receiving device and converted into power for people to use. In 2010, hail introduced a "tailless tv" without power, signal and network lines, which marked that the remote efficient wireless power transmission technology has been successfully applied in daily life.
Among the solutions to the energy demand, wireless energy-carrying communication technology (SWIPT) is considered as a convenient, safe and "green" energy collection technology, which is a product of combining Wireless Power Transfer (WPT) and Wireless Information Transfer (WIT), and therefore, the advantages of both "sourcing" and "throttling" are considered. In the wireless energy-carrying communication technology, a base station end equipped with Power towers (PBs) transmits energy or information to a mobile terminal wirelessly, so that the mobile terminal can be free from the limitation of battery service time, chargers and charging cables can be eliminated, and the development requirement of 'green communication' is met. Based on the remarkable characteristic of information and energy parallel transmission, the wireless energy-carrying communication technology is expected to be widely applied to information exchange and energy transmission among a high-speed Radio Frequency Identification (RFID), an Internet of things, a sensor network under a severe working environment and various mobile terminals, and is expected to effectively provide energy for various terminal devices by extracting energy in received signals while realizing high-speed information exchange, so that the inconvenience of layout or the inconvenience of frequent replacement caused by battery power supply in the traditional wired mode is avoided, and the standby time of the wireless energy-carrying communication technology is greatly prolonged. Therefore, the research on the wireless energy-carrying communication technology has practical significance.
The current wireless energy-carrying communication technology has 3 challenges: how to establish a direct-view link between an energy tower and a mobile terminal, how to form an energy beam on the energy tower that can resist fading loss, how to improve the energy reception efficiency of the terminal, and how to reduce energy loss. Corresponding 3-aspect techniques can address these challenges: energy towers are deployed individually, at low cost and intensively, or in combination with a relay network, at convenient locations where the grid can be connected; a large-scale array antenna technology with tens or hundreds of antenna elements, which is actively developing, can form an energy beam facing a terminal, so that the wireless energy transmission efficiency approaches 1; due to the continuous deployment of the micro cells, the energy receiving efficiency of the terminal can be effectively improved by the energy distribution technology. Therefore, the energy tower with enough density can be deployed in the future to effectively realize the energy supplement for the mobile terminal.
The present invention is a research on how to improve the energy receiving efficiency and reduce the energy consumption of a terminal in wireless energy-carrying communication, and is intended to "how to improve the energy receiving efficiency and reduce the energy consumption of a terminal by achieving a tradeoff between the data transmission rate and the energy transmission? "a breakthrough is made on this critical issue. The receiver models in various wireless energy-carrying communication scenes are researched, and a mathematical relation between data transmission and energy transmission is established, so that the problem is solved; an alternative to the above problem is presented by studying a passto optimal solution that optimizes both data transmission and energy transmission.
As wireless communication becomes more popular, there is a great breakthrough in the research on wireless energy transmission. It is not satisfactory to transmit information by radio waves alone, but it is desirable to transmit information while fully utilizing valuable transmitted power to transmit energy. Under the promotion of the demand, it is particularly important to research key technologies such as an energy relay mode, a system architecture, an information modulation mode and the like of a wireless energy-carrying communication system based on simultaneous transmission of information and energy.
Varshney first published an article on "IEEE International Symposium on Information Theory,2008: the "transmission information and energy simultaneouslly" raises the problem of wireless energy-carrying communication, and on the basis of giving the definition of "capacity energy function", the problem of how to compromise between channel capacity and energy transmission efficiency in an amplitude-limited additive white gaussian noise channel is studied. Liang Liu published in "IEEE International Symposium on Information Theory, 2008. Then, the Liang Liu et al studied the optimal switching criteria of the receiver operation mode, and the criteria is used to realize the balance between information transmission and energy transfer. On the basis of these contents, the problems of jointly optimizing receiver operation mode switching, information and energy transmission scheduling, and transmission energy control are discussed. Omurozel et al published in "IEEE Journal on Selected Areas in Communications, 29-1743" by Omurozel et al, an article "Transmission with Transmission and Transmission harnessing nodes in signaling wireless channels: optimal policies", and optimized the energy storage capacity and time series energy Transmission problem for direct link data Transmission in fading channels with the maximization of information Transmission rate and the minimization of Transmission time as optimization objectives.
In particular, zhou X et al published in "IEEE Global Communications Conference,2012, 3982-3987" the article "Wireless information and power transfer: architecture design and rate-energy handoff" proposed an overall receiver scheme of "dynamic power allocation", i.e., allocating received signals in a certain proportion, dividing received radio signals into two parts, energy collection and information reception, in real time. Thereby the energy ratio of the energy receiver and the information receiver can be dynamically adjusted. On this basis, xun Zhou et al give both a split and a combined receiver structure. Then, the error rate performance of the two receivers when M-QAM modulation is adopted is compared, and the influence of energy loss in a circuit on the data transmission rate and the energy efficiency of the two receivers is respectively researched.
There is an increasing amount of research on the trade-off between data transmission rate and energy transmission, which can be roughly divided into two categories: the first type mainly studies the relationship between the data transmission rate and the energy transmission, but because only the relationship between the data transmission rate and the energy transmission or only the iterative algorithm is given, but no global optimal closed expression solution is given, a direct theoretical basis cannot be provided for a system designer; the second type is to optimize the energy transmission optimization problem under the condition that the data transmission rate is a constraint condition, but when optimizing the energy transmission, the data transmission rate is regarded as a constraint condition to be inflexible, the performance of the data transmission rate is limited, and the energy configuration is not flexible enough.
Disclosure of Invention
The present invention is directed to solve the above-mentioned problems of the prior art, and an object of the present invention is to provide a wireless energy-carrying communication system and a method thereof based on energy-information tradeoff transmission.
The technical scheme of the invention is as follows: a wireless energy-carrying communication system based on energy-information weighted transmission is characterized by comprising a base station end part and a user end part, wherein the base station end part consists of a baseband communication module and a transmitting antenna module; the user end part consists of a receiving antenna module, a storage battery module, an electric quantity detection module, an energy distribution module, an information receiving module and an energy acquisition module;
the base band communication module is electrically connected with the transmitting antenna module, the energy distribution module is respectively electrically connected with the receiving antenna module, the information receiving module and the energy acquisition module, the storage battery module is electrically connected with the energy acquisition module, and the electric quantity detection module is electrically connected with the storage battery module; wherein:
the baseband communication module is used for encoding and modulating data to be transmitted into a baseband signal;
the transmitting antenna module is used for transmitting the baseband signal in the form of electromagnetic wave;
the receiving antenna module is used for converting electromagnetic waves transmitted by a receiving base station end into electric signals;
the energy distribution module is used for receiving the electric signals received by the antenna module and distributing the electric signals into information electric signals and energy electric signals;
the information receiving module is used for restoring the information electric signal distributed by the energy distribution module into original transmission data;
the energy acquisition module is used for storing the energy electric signals distributed by the energy distribution module into the storage battery module;
the storage battery module is used for storing energy and supplying energy to the receiving antenna module, the electric quantity detection module, the energy distribution module, the information receiving module and the energy acquisition module at the user end part;
and the electric quantity detection module is used for detecting the real-time residual electric quantity proportion of the storage battery module and feeding back the real-time residual electric quantity proportion to the energy distribution module.
A wireless energy-carrying communication method based on energy-information tradeoff transmission is characterized by comprising the following implementation steps:
(1) Base station end transmitting signal
1a) A baseband communication module at the end part of the base station encodes and modulates data to be transmitted into a baseband signal;
1b) The antenna module of the base station end part transmits the baseband signal in the step 1 a) in the form of electromagnetic waves;
(2) User terminal antenna receiving signal
The receiving antenna module is used for converting the electromagnetic waves transmitted by the receiving base station end into electric signals and sending the electric signals to the energy distribution module;
(3) Battery capacity detection
The electric quantity detection module detects the electric quantity of the current storage battery and compares the real-time residual electric quantity with a ratio Q C Feeding back to the energy distribution module;
(4) Energy distribution module
4a) Calculating information rate weights w
The energy distribution module is used for distributing the real-time electric quantity Q of the storage battery C The information rate weight w is calculated corresponding to the importance of the transmitted data as follows:
| information rate weight w | Control frame data | Data frame data |
| Q C ≤ |
1 | 0 |
| Q C ≥Q thre | 1 | Q C |
4b) Calculating the power of the normalized energy collection;
the energy collection power of the energy collection module is calculated by the following formula:
E＝ρηP
wherein, P is the total energy of the received signal, eta belongs to (0,1) is the energy transfer efficiency, and rho is the energy distribution factor;
the normalized energy collection power is:
wherein E max For the energy harvesting power when all energy is allocated to energy harvesting, it is possible to pass E max = η P calculation;
4c) Calculating the maximum information rate of the data transmission of the normalized system;
the maximum information rate of data transmission of the data transmission module is calculated by the following formula:
wherein N is rec Is additive white Gaussian noise in the channel, N cov For noise processing, P is the total energy of the received signal, and ρ is the energy allocation factor;
the normalized maximum information rate of data transmission is:
wherein the content of the first and second substances,
the maximum information rate for data transmission when all the energy is allocated to data transmission can be calculated by formula
Calculating to obtain;
4d) Constructing a trade-off value of information rate-energy collection;
trade-off value U of information rate-energy collection R-E Can be calculated by the following formula:
where w is the information rate weight, p is the energy allocation factor,
for the maximum information rate of the data transmission when all the energy is allocated to the data transmission, P is the total energy of the received signal, N rec As additive white Gaussian noise, N, in the channel cov To deal with noise.
4e) Calculating an optimal energy distribution factor rho * ；
Optimal energy distribution factor ρ * Obtained by the following formula:
where P is the total energy of the received signal,
for the maximum information rate, N, of the data transmission with all energy allocated to the data transmission cov To handle noise, w is the information rate weight, N rec Is additive white gaussian noise in the channel.
When N is present rec ＞＞N cov Time, optimal energy distribution factor ρ * Can be obtained by the following formula:
where w is the information rate weight and,
for the maximum information rate, N, of the data transmission with all energy allocated to the data transmission cov To handle noise, P is the total energy of the received signal.
4f) The energy distribution module distributes the electric signal received by the receiving antenna module into two parts, and the ratio of the two parts is the optimal energy distribution factor rho * Is distributed to the energy collection module and the remaining 1-rho is distributed to the energy collection module * Is distributed to the energy harvesting module.
(5) Information reception
The information receiving module demodulates and decodes the distributed information electric signal into original transmission data;
(6) Energy harvesting
The energy acquisition module is used for converting the energy of the received signals and storing the converted energy into the storage battery module.
The encoding in the step 1 a) can be completed by any one of a linear block code, a convolutional code, a Turbo code, a low density check code LDPC code and a non-encoding mode; the modulation in the step 1 a) can adopt any one modulation mode of MPSK, MFSK and MASK; the decoding in the step (5) adopts a coding mode corresponding to the coding mode in the step 1 a); the demodulation in the step (5) corresponds to the modulation mode in the step 1 a).
Optimal energy distribution factor rho of step 4 e) * Is the optimal solution of the following optimization problem:
wherein U is R-E A trade-off value for information rate-energy collection, p is an energy allocation factor,
expression U under the premise of unknown rho R-E S.t. is a constraint.
The battery electric quantity detection in the step (3) can be completed by any one of a voltage detection method, a battery modeling method and a coulometer method.
The energy collection in the step (6) can adopt an electromagnetic wave energy transmission technology, and the received electromagnetic wave energy is converted into direct current electric energy at a receiving end through a rectifying antenna.
Aiming at the defects of the existing work, the invention researches how to simply and efficiently realize the balance between the data transmission rate and the energy transmission in the wireless energy-carrying communication system, and can realize the pareto optimality of the terminals through flexibly configuring the information rate weight according to the data transmission characteristics of the terminals of different types. Firstly, an optimized power distribution problem based on statistical channel state information is established by taking a relation matrix of joint optimization data transmission rate and energy transmission as an objective function based on the statistical channel state information, and then a pareto-type optimal solution for realizing balance of the optimal solution is found out according to a Lagrange solution and by utilizing proper approximation. The configuration of the information rate weights and the optimal solution with a closed form make the distribution of the transmission energy more flexible and practical.
According to the invention, under the scene of a direct link, fig. 1 is a system model of energy-carrying transmission, and a receiver is divided into two parts, namely an information receiving module and an energy collecting module, which respectively correspond to two signal streams, namely an information stream and an energy stream, received by a receiving antenna.
The power collected by the receiver energy is then:
E＝ρηP (0-1)
wherein P is the total energy of the received signal, η ∈ (0,1) is the energy transfer efficiency, and the received signal at the information receiving module is
y rec ＝(1-ρ)(y r +n rec )+n cov (0-2)
Wherein n is rec And n cov Respectively, zero mean variance of N rec And N cov White additive gaussian noise and process noise. According to the theory related to wireless relay, the signal-to-noise ratio during information reception can be derived from the received signal expression of the information receiving module as follows:
substituting the shannon formula to obtain the maximum information rate of system data transmission as follows:
therefore, a mathematical model, namely an information rate-energy collection matrix, is established according to a wireless relay correlation theory and random signal analysis:
wherein
E max ＝ηP。
Trade-off function optimization scheme
It is difficult to directly solve the multi-objective optimization problem, so it is necessary to define w as the information rate weight for representing the importance of information transmission in the whole system. The weight is determined by the type of terminal: when the terminal has higher requirement on the data transmission rate, such as a video transmission scene, the weight w is higher; when data traffic of the terminal is not frequent and the data amount is not high, if only control information is transmitted, the weight w is low. The selection of w needs to be determined according to the actual application scenario, and generally, information transmission and energy transmission in the system are considered to be equally important, where w =0.5.
Converting the multi-objective optimization problem into a single-objective optimization problem by an objective weighting method, and defining an information rate-energy collection equilibrium value as follows:
for a given information rate weight w, there is a very critical problem: how to obtain an energy ratio ρ? Thus, a rate-energy optimization problem is constructed:
the optimal solution can be calculated by applying the KKT condition of lagrangian optimization:
the rho value for achieving rate-energy equalization is obtained by this calculation. When N is present rec ＞＞N cov Time, i.e. when the antenna noise is much larger than the processing noise, ρ * → 1. This indicates that the system achieves optimal rate-energy equalization when the receiver is primarily used to receive energy, consistent with the conclusions in the literature "Wireless information and power transfer: architecture design and rate-energy handoff".
Meanwhile, since the optimal solution form is complicated and inconvenient for practical application, a pareto optimal solution of an approximate form is obtained using an approximation related in wireless communication:
from the above equation, ρ is an increasing function with respect to the variable w.
And (3) simulation results: the invention verifies the correctness of the analysis result through computer simulation. Without loss of generality, let N in simulation rec ＝N cov ＝1，P＝10dB。
Normalized information rate
Energy harvesting power E norm With their trade-off function U R-E The relationship of (a) is shown in FIG. 2. Since w is a weight parameter of the information rate, the information rate
Is a non-increasing function of w, the energy harvesting power E norm A non-decreasing function with respect to w. This means that it is valuable to select the appropriate w in a real system, and the trade-off is facilitated by the trade-off function. The three curves are converged at the same point, which shows that the information rate-energy collection power matrix can show the direct relation between the information rate and the energy collection power.
Drawings
Fig. 1 shows a receiver model in wireless energy-carrying communication technology.
Fig. 2 is a diagram illustrating the relationship between energy distribution factor and energy efficiency, transmission efficiency and information rate-energy collection matrix in wireless energy-carrying communication technology.
Fig. 3 shows the optimal energy distribution coefficient under different transmission rate requirements.
Fig. 4 is a diagram illustrating the relationship between energy efficiency and transmission efficiency in wireless energy-carrying communication technology.
Fig. 5 is a schematic structural diagram of the present invention.
FIG. 6 is a flow chart of the present invention.
Detailed Description
The present invention will be described in further detail in order to make the objects, technical solutions and advantages of the present invention more apparent.
A wireless energy-carrying communication system based on energy-information weighted transmission is characterized by comprising a base station end part and a user end part, wherein the base station end part consists of a baseband communication module and a transmitting antenna module; the user end part consists of a receiving antenna module, a storage battery module, an electric quantity detection module, an energy distribution module, an information receiving module and an energy acquisition module;
the base band communication module is electrically connected with the transmitting antenna module, the energy distribution module is respectively electrically connected with the receiving antenna module, the information receiving module and the energy acquisition module, the storage battery module is electrically connected with the energy acquisition module, and the electric quantity detection module is electrically connected with the storage battery module; wherein:
the baseband communication module is used for encoding and modulating data to be transmitted into baseband signals;
the transmitting antenna module is used for transmitting the baseband signal in the form of electromagnetic wave;
the receiving antenna module is used for converting electromagnetic waves transmitted by the receiving base station end into electric signals;
the energy distribution module is used for receiving the electric signals received by the antenna module and distributing the electric signals into information electric signals and energy electric signals;
the information receiving module is used for restoring the information electric signal distributed by the energy distribution module into original transmission data;
the energy acquisition module is used for storing the energy electric signals distributed by the energy distribution module into the storage battery module;
the storage battery module is used for storing energy and supplying energy to the receiving antenna module, the electric quantity detection module, the energy distribution module, the information receiving module and the energy acquisition module at the user end part;
and the electric quantity detection module is used for detecting the real-time residual electric quantity proportion of the storage battery module and feeding back the real-time residual electric quantity proportion to the energy distribution module.
A wireless energy-carrying communication method based on energy-information tradeoff transmission is realized by the following steps:
(1) Base station end transmitting signal
1a) A baseband communication module at the end part of the base station encodes and modulates data to be transmitted into a baseband signal;
1b) The antenna module of the base station end part transmits the baseband signal in the step 1 a) in the form of electromagnetic waves;
(2) Receiving signal by user terminal antenna
The receiving antenna module is used for converting the electromagnetic waves transmitted by the receiving base station end into electric signals and sending the electric signals to the energy distribution module;
(3) Battery capacity detection
The electric quantity detection module detects the electric quantity of the current storage battery and compares the real-time residual electric quantity with a ratio Q C Feeding back to the energy distribution module;
(4) Energy distribution module
4a) Calculating information rate weights w
The energy distribution module is used for distributing the real-time electric quantity Q of the storage battery C The information rate weight w is calculated corresponding to the importance of the transmitted data as follows:
| information rate weight w | Control frame data | Data frame data |
| Q C ≤ |
1 | 0 |
| Q C ≥Q thre | 1 | Q C |
4b) Calculating the power of the normalized energy collection;
the energy collection power of the energy collection module is calculated by the following formula:
E＝ρηP
wherein, P is the total energy of the received signal, eta belongs to (0,1) is the energy transfer efficiency, and rho is the energy distribution factor;
the normalized energy collection power is:
wherein E max For the energy harvesting power when all energy is allocated to energy harvesting, it is possible to pass E max = η P calculated;
4c) Calculating the maximum information rate of the data transmission of the normalized system;
the maximum information rate of data transmission of the data transmission module is calculated by the following formula:
wherein N is rec Is additive white Gaussian noise in the channel, N cov For noise processing, P is the total energy of the received signal, and ρ is the energy allocation factor;
the normalized maximum information rate of data transmission is:
wherein the content of the first and second substances,
for all energy to beThe maximum information rate allocated to data transmission during data transmission can be determined by a formula
Calculating to obtain;
4d) Constructing a trade-off value of information rate-energy collection;
information rate-energy harvesting trade-off U R-E Can be calculated by the following formula:
where w is the information rate weight, p is the energy allocation factor,
for the maximum information rate of the data transmission when all the energy is allocated to the data transmission, P is the total energy of the received signal, N rec As additive white Gaussian noise, N, in the channel cov To deal with noise.
4e) Calculating an optimal energy distribution factor rho * ；
Optimal energy allocation factor ρ * Obtained by the following formula:
where P is the total energy of the received signal,
for the maximum information rate, N, of the data transmission with all energy allocated to the data transmission cov To handle noise, w is the information rate weight, N rec Is additive white gaussian noise in the channel.
When N is present rec ＞＞N cov Time, optimal energy distribution factor ρ * Can be obtained by the following formula:
where w is the information rate weight and,
maximum information rate, N, of data transmission when all energy is allocated to data transmission cov To handle noise, P is the total energy of the received signal.
4f) The energy distribution module distributes the electric signal received by the receiving antenna module into two parts, and the ratio of the two parts is the optimal energy distribution factor rho * Is distributed to the energy collection module and the remaining 1-rho is distributed to the energy collection module * Is distributed to the energy harvesting module.
(5) Information reception
The information receiving module demodulates and decodes the distributed information electric signal into original transmission data;
(6) Energy harvesting
The energy acquisition module carries out energy conversion on the received signals and stores the received signals into the storage battery module.
The encoding in the step 1 a) can be completed by any one of a linear block code, a convolutional code, a Turbo code, a low density check code LDPC code and a non-encoding mode; the modulation in the step 1 a) can adopt any one modulation mode of MPSK, MFSK and MASK; the decoding in the step (5) adopts a coding mode corresponding to the coding mode in the step 1 a); the demodulation in the step (5) corresponds to the modulation mode in the step 1 a).
Optimal energy distribution factor rho of step 4 e) * Is the optimal solution of the following optimization problem:
wherein U is R-E A trade-off value for information rate-energy collection, p is an energy allocation factor,
expression U under the premise of unknown rho R-E S.t. is a constraint.
The battery electric quantity detection in the step (3) can be completed by any one of a voltage detection method, a battery modeling method and a coulometer method.
The energy collection in the step (6) can adopt an electromagnetic wave energy transmission technology, and the received electromagnetic wave energy is converted into direct current electric energy at a receiving end through a rectifying antenna.
Fig. 3 is a diagram illustrating the relationship between the energy scale factor ρ and the weight parameter w, where P =0,5, 10, 15, 20, 25dB. The energy scale factor p is given in relation to a weight parameter w, and can be determined from the weight parameter w. The transmission rate versus energy is shown in fig. 4. It is apparent that the information rate is an increasing function of the energy harvesting power. These simulations clearly show the information rate versus energy harvesting trade-off.
According to the invention, how to simply and efficiently realize the balance between the data transmission rate and the energy transmission in the wireless energy-carrying communication system is researched, and the pareto optimal of the terminals can be realized by flexibly configuring the information rate weight according to the data transmission characteristics of different types of terminals. The optimal solution is then calculated by the lagrangian solution in nonlinear programming:
the first step is as follows: and calculating a corresponding Lagrange function according to the optimization problem, introducing a parameter, and converting a constrained extreme value problem into an unconstrained extreme value problem.
The second step is that: and solving a first-order condition of the Lagrangian function. First order partial derivatives of the lagrangian function pair selection variable and the lagrangian multiplier are respectively solved, and at the optimal solution, the group of partial derivatives are equal to 0.
The third step: and simultaneously establishing a first-order conditional equation set and solving.
The solution required is the optimal solution to the trade-off problem to be studied by the subject.
Since the direct calculation of the optimal solution is complex in form and needs further simplification, the form of the optimal solution can be simplified by using series expansion or large signal-to-noise ratio approximation and the like which are often used in relay communication. And finally, performing simulation verification.
Claims (6)
1. A wireless energy-carrying communication method based on energy-information tradeoff transmission is characterized by comprising the following implementation steps:
(1) Base station end transmitting signal
1a) A baseband communication module at the end part of the base station encodes and modulates data to be transmitted into a baseband signal;
1b) The antenna module of the base station end part transmits the baseband signal in the step 1 a) in the form of electromagnetic waves;
(2) Receiving signal by user terminal antenna
The receiving antenna module is used for converting the electromagnetic waves transmitted by the receiving base station end into electric signals and sending the electric signals to the energy distribution module;
(3) Battery capacity detection
The electric quantity detection module detects the electric quantity of the current storage battery and compares the real-time residual electric quantity with a ratio Q C Feeding back to the energy distribution module;
(4) Energy distribution module
4a) Calculating information rate weights w
The energy distribution module is used for distributing the energy according to the real-time residual electric quantity proportion Q of the storage battery C The information rate weight w is calculated with the frame type of the transmission data,
when the transmission data is control frame data, the information rate weight w is equal to 1; when the transmission data is data frame data and Q C ≤Q thre Then the information rate weight w is equal to 0; when the transmission data is data frame data and Q C ≥Q thre When the information rate weight w is equal to Q C ；
4b) Calculating the power of the normalized energy collection;
the energy collection power of the energy collection module is calculated by the following formula:
E＝ρηP
wherein, P is the total energy of the received signal, eta (0,1) is the energy conversion efficiency, and rho is the energy distribution factor;
the normalized energy collection power is:
wherein E max For the energy harvesting power when all energy is allocated to energy harvesting, it is possible to pass E max = η P calculated;
4c) Calculating the maximum information rate of the data transmission of the normalized system;
the maximum information rate of data transmission of the data transmission module is calculated by the following formula:
wherein N is rec Is additive white Gaussian noise in the channel, N cov For noise processing, P is the total energy of the received signal, and ρ is the energy allocation factor;
the normalized maximum information rate of data transmission is:
wherein, the first and the second end of the pipe are connected with each other,
the maximum information rate for data transmission when all the energy is allocated to data transmission can be calculated by formula
Calculating to obtain;
4d) Constructing a trade-off value of information rate-energy collection;
information rate-energy harvesting trade-off U R-E Can be calculated by the following formula:
4e) Calculating an optimal energy distribution factor rho * ；
Optimal energy distribution factor ρ * Obtained by the following formula:
when N is present rec ＞＞N cov Time, optimal energy distribution factor ρ * Can be obtained by the following formula:
4f) The energy distribution module distributes the electric signal received by the receiving antenna module into two parts, and the ratio of the two parts is the optimal energy distribution factor rho * Is distributed to the energy collection module and the remaining 1-rho is distributed to the energy collection module * The electric signal is distributed to the energy acquisition module;
(5) Information reception
The information receiving module demodulates and decodes the distributed information electric signal into original transmission data;
(6) Energy harvesting
The energy acquisition module carries out energy conversion on the received signals and stores the received signals into the storage battery module.
2. The wireless energy-carrying communication method based on energy-information tradeoff transmission according to claim 1, wherein the encoding in step 1 a) can be performed by any one of linear block code, convolutional code, turbo code, low density check code LDPC code, and non-encoding; the modulation in the step 1 a) can adopt any one modulation mode of MPSK, MFSK and MASK; the decoding in the step (5) adopts a coding mode corresponding to the coding mode in the step 1 a); the demodulation in the step (5) corresponds to the modulation mode in the step 1 a).
3. The method as claimed in claim 1, wherein the optimal energy allocation factor p in step 4 e) is the same as the optimal energy-carrying capacity factor p * Is the optimal solution of the following optimization problem:
wherein U is R-E A trade-off value for information rate-energy collection, p is an energy allocation factor,
expression U under the premise of unknown rho R-E S.t. is a constraint.
4. The method of claim 1, wherein the battery power detection in step (3) can be performed by any one of voltage detection, battery modeling, and coulometry.
5. The wireless energy-carrying communication method based on energy-information tradeoff transmission as claimed in claim 1, wherein the energy collection in step (6) can be electromagnetic wave energy transmission technology, and the received electromagnetic wave energy is converted into direct current electric energy at the receiving end through a rectifying antenna.
6. A wireless energy-carrying communication system for implementing the wireless energy-carrying communication method based on energy-information tradeoff transmission of claim 1, comprising a base station part and a user terminal part, wherein the base station part is composed of a baseband communication module and a transmitting antenna module; the user end part consists of a receiving antenna module, a storage battery module, an electric quantity detection module, an energy distribution module, an information receiving module and an energy acquisition module;
the base band communication module is electrically connected with the transmitting antenna module, the energy distribution module is respectively electrically connected with the receiving antenna module, the information receiving module and the energy acquisition module, the storage battery module is electrically connected with the energy acquisition module, and the electric quantity detection module is electrically connected with the storage battery module; wherein:
the baseband communication module is used for encoding and modulating data to be transmitted into baseband signals;
the transmitting antenna module is used for transmitting the baseband signal in the form of electromagnetic wave;
the receiving antenna module is used for converting electromagnetic waves transmitted by a receiving base station end into electric signals;
the energy distribution module is used for receiving the electric signals received by the antenna module and distributing the electric signals into information electric signals and energy electric signals;
the information receiving module is used for restoring the information electric signal distributed by the energy distribution module into original transmission data;
the energy acquisition module is used for storing the energy electric signals distributed by the energy distribution module into the storage battery module;
the storage battery module is used for storing energy and supplying energy to the receiving antenna module, the electric quantity detection module, the energy distribution module, the information receiving module and the energy acquisition module at the user end part;
and the electric quantity detection module is used for detecting the real-time residual electric quantity proportion of the storage battery module and feeding back the real-time residual electric quantity proportion to the energy distribution module.
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