An analytical energy conversion system for a smart metasurface-assisted passive environment system

Abstract

This invention discloses an analytical energy conversion system for a passive environmental system assisted by an intelligent metasurface, relating to an energy storage system. The system includes: an end-to-end passive environmental system transmission model, constructed based on a transmission environment consisting of an intelligent metasurface, a transmitter, an integrated terminal, and an environmental reverse receiver. This transmission environment includes two transmission modes: common transmission of downlink signals and reverse transmission of environmental signals. The end-to-end passive environmental system transmission model encompasses both the common transmission mode and the reverse transmission mode. A nonlinear energy conversion model with waveform analytical characteristics is also included. Finally, a nonlinear energy conversion model combining the end-to-end model and the nonlinear energy conversion model is constructed. This invention provides a solution strategy for constructing solutions for practical deployment scenarios by effectively combining an analytical system model with hardware physical effects and a nonlinear energy conversion model.

Description

Technical Field

[0001] This invention relates to energy storage system technology, and more particularly to an analytical energy conversion system for a passive system with intelligent metasurface-assisted environment. Background Technology

[0002] The Internet of Things (IoT) is projected to witness a significant increase in device connectivity over the next decade, from 27 billion in 2020 to over 500 billion in 2030. The limitations of 5G technology have made 6G technology crucial for IoT development, particularly in improving system energy efficiency. With the broad prospects of IoT applications and the requirements of the "dual-carbon" strategy, green communication concepts have become paramount. Passive IoT technology and smart metasurface technology, as key to achieving green communication, are receiving increasing attention.

[0003] Passive IoT technology aims to achieve ultra-low power operation of terminal devices, eliminating the limitations of power cords or batteries. Smart metasurface technology, due to its superior channel control capabilities, significantly improves system performance and is expected to be widely used in 6G commercial applications. This technology will ensure the transmission stability of passive systems in the environment and achieve ultra-low power consumption in 6G networks at a lower cost, driving breakthroughs in multiple aspects of network development.

[0004] To analyze passive environmental systems assisted by intelligent metasurfaces, a comprehensive system model needs to be constructed, and system modeling and optimization should be coordinated. While core subsystems of intelligent metasurface systems and passive environmental systems have already seen practical applications, cases of integration into complete systems are rare. Summary of the Invention

[0005] The technical problem to be solved by this invention is to address the shortcomings of existing technologies. The purpose is to provide an analytical energy conversion system for an intelligent metasurface-assisted passive environment system. This system extends the end-to-end model of scattering parameters, introduces an environmental reverse communication transmission link, integrates the information and energy transmission system with the environmental reverse system, constructs a complete passive environment system, and proposes a hybrid transmission mechanism to meet the needs of ultra-low power terminals.

[0006] The analytical energy conversion system of the intelligent metasurface-assisted passive environment system described in this invention includes:

[0007] An end-to-end passive system transmission model is constructed based on a transmission environment consisting of a smart metasurface, a transmitter, an integrated terminal, and an environmental reverse receiver. The transmission environment has two transmission modes: common transmission of downlink signals and environmental reverse transmission. The end-to-end passive system transmission model covers both the common transmission mode and the environmental reverse transmission mode of the downlink signals.

[0008] A nonlinear energy conversion model with waveform analytical properties;

[0009] The nonlinear energy conversion model, which combines the end-to-end model with the passive system transmission model and the nonlinear energy conversion model, is constructed.

[0010] This invention constructs an end-to-end model of a passive system in a typical environment, focusing on key hardware effects and emphasizing the nonlinear transmission characteristics of energy conversion circuits. By effectively combining an analytical system model with hardware physical effects with a nonlinear energy conversion model, it provides a solution strategy for constructing solutions for practical deployment scenarios. Furthermore, this model extends the end-to-end model of scattering parameters by incorporating an environmental reverse communication transmission link, effectively integrating it with the main transmission link and demonstrating the scalability advantages of the scattering parameter model.

[0011] Preferably, the transmitter is connected to the smart metasurface via a smart metasurface auxiliary link, and the transmitter is connected to the integrated terminal via a direct link to form a common transmission mode for downlink signals; the integrated terminal is connected to the environmental reverse receiver via an environmental reverse link to form an environmental reverse transmission mode.

[0012] Preferably, the method for constructing the end-to-end passive system transmission model is as follows:

[0013] The number of integrated terminals is set to N. B The number of environmental reverse receivers is N. R A method based on scattering parameters is used to treat the transmission path as an N-port network in order to solve the relationship between the transmitted waves b and a.

[0014] Based on the relationship between the system transmitted waves b and a obtained from the solution, the transmission model from the transmitter to the integrated terminal is derived. And the transmission model from transmitter to environmental reverse receiver

[0015] Calculate the power values ​​of the corresponding ports of the integrated terminal under load matching and load mismatch conditions;

[0016] The formula for calculating the power value is simplified to obtain a transmission model that characterizes the maximum received power value at the integrated terminal and the environmental reverse receiver location. and

[0017] Preferably, the end-to-end passive system transmission model is as follows:

[0018]

[0019] in, This represents the transmission model under integrated terminal load matching conditions. S represents the transmission model under the conditions of total reflection at the integrated terminal load and load matching of the environmental reverse receiver. BT S is the scattering transmission matrix from transmitter to integrated terminal. BI S is the scattering transfer matrix from the smart metasurface to the integrated terminal. II For the self-scattering transfer matrix of the intelligent metasurface, S IT S is the scattering transfer matrix from the transmitter to the smart metasurface. RB To integrate the scattering transmission matrix from the terminal to the environmental reverse receiver, Θ -1 It is the inverse of the reflectance coefficient of the smart metasurface.

[0020] Preferably, the nonlinear energy conversion model is as follows:

[0021]

[0022] in, To analyze the output current of the rectifier circuit in the energy conversion system, k2 and k4 are both circuit constant factors, and ρ is the power distribution coefficient. In the transmission model The nth f A transmission channel with multiple subcarriers In the transmission model The nth f Beamforming vectors of N subcarriers, F This represents the total number of carriers.

[0023] The analytical energy conversion system of the intelligent metasurface-assisted passive environment system described in this invention has the following advantages:

[0024] This paper constructs an end-to-end model of a passive system in a typical environment, focusing on key hardware effects and emphasizing the nonlinear transmission characteristics of energy conversion circuits. By effectively combining an analytical system model with hardware physical effects with a nonlinear energy conversion model, it provides a solution strategy for constructing solutions to problems in practical deployment scenarios. Furthermore, this model extends the end-to-end model of scattering parameters by incorporating an environmental reverse communication transmission link, effectively integrating it with the main transmission link and demonstrating the scalability advantages of the scattering parameter model. Attached Figure Description

[0025] Figure 1 This is a schematic diagram illustrating the analytical energy conversion system construction process of an intelligent metasurface-assisted passive environment system described in this invention.

[0026] Figure 2 This is a schematic diagram of the transmission scenario of the intelligent metasurface-assisted passive system in this invention.

[0027] Figure 3This is a schematic diagram of the equivalent circuit transmission of the analytical energy conversion system described in this invention.

[0028] Figure 4 This is a schematic diagram of the overall iterative optimization algorithm framework described in this invention.

[0029] Figure 5 This is a schematic diagram of the output current of the energy conversion circuit under different bandwidth levels described in this invention.

[0030] Figure 6 This is a schematic diagram of the output current of the energy conversion circuit under different numbers of transmitting energy storage systems as described in this invention. Detailed Implementation

[0031] The present invention will be further described below with reference to embodiments, but this does not constitute any limitation on the present invention. Any limited modifications made by any person within the scope of the claims of the present invention are still within the scope of the claims of the present invention.

[0032] See Figure 1 The analytical energy conversion system of the intelligent metasurface-assisted passive environment system described in this invention includes the following steps:

[0033] S1. Construct an end-to-end passive system transmission model.

[0034] Construct an end-to-end transmission model, i.e., an end-to-end passive system transmission model, suitable for applications such as... Figure 2 The transmission environment shown can be considered a simplified version of the hybrid passive IoT model, covering two core transmission modes: downlink signal co-transmission and environmental reverse transmission.

[0035] Generally speaking, the number of integrated terminals should be set to N. B The number of environmental reverse receivers is set to N. R A method based on scattering parameters is employed, treating the transmission path as an N-port network, to solve for the system's transmitted wave b = [b...]. T b B b I b R ] and a=[a T ;a B ;a I ;a R The relationship between them is as follows:

[0036]

[0037] The model of each end path can be written as:

[0038] a T =b s,T +ΓT b T ,

[0039] a R =Γ R b R ,

[0040] a I =Θb I ,

[0041] a B =Γ B b B .

[0042] Further derive the transmission model from transmitter to integrated terminal for:

[0043]

[0044] The transmission model from the transmitter to the environmental reverse receiver can be obtained. for:

[0045]

[0046] This model covers most of the physical characteristics of the transmitter, smart metasurface, integrated terminal, and environmental reverse receiver in a multi-unit configuration, including mismatch and coupling effects.

[0047] In addition, such as Figure 2 As shown, the integrated terminal needs to perform two tasks: first, to collect and demodulate the downlink signal emitted by the transmitter; and second, to complete environmental inversion using existing signals. The integrated terminal is assumed to have two states: matched and mismatched. Under the condition of matched terminal load, i.e., Γ... B =0, the corresponding port power value is:

[0048] P B =|b B | 2 -|a B | 2 =|(S BT +S BI (Θ -1 -S II ) -1 S IT (S) TT +I) -1 v T | 2 ,

[0049] P R =|b R | 2 -|a R| 2 =0.

[0050] Similarly, when the load is totally reflected, i.e., Γ B =I, and the environmental reverse receiver are perfectly matched Γ R When = 0, the corresponding port power value is:

[0051] P B =|b B | 2 -|a B | 2 =0,

[0052] P R =|b R | 2 -|a R | 2 =|(S RB (IS BB ) -1 (S BT +S BI (Θ -1 -S II ) -1 S IT ))(S TT +I) -1 v T | 2 .

[0053] The proposed formula reveals the power performance of a specific architecture under different application environments. Specifically, when the integrated terminal load is mismatched, the terminal cannot acquire signals, while the environmental reverse receiver can detect the corresponding reflected signals; conversely, when the load is matched, the terminal has signal acquisition capabilities, and the power received by the environmental reverse receiver is zero. The detection difference caused by load mismatch constitutes the basis for the environmental reverse receiver's signal decision. In subsequent analyses, only the physical effects related to the smart metasurface will be considered, while the physical influence of other ports will be ignored. and They can be simplified as follows:

[0054]

[0055] here, Represents Γ B =0; Represents Γ B =I and Γ R The case where = 0. Both describe the transmission models that achieve the maximum received power value at the integrated terminal and the environmental reverse receiver location.

[0056] S2. Construct a nonlinear energy conversion model with waveform analytical characteristics.

[0057] Under integrated terminal matching conditions, signal demodulation and energy harvesting functions will be further developed. Therefore, the energy conversion circuit, which is crucial in the energy harvesting process, must be accurately and reasonably represented. Typically, refer to... Figure 3 The circuit diagram shown illustrates a standard energy conversion circuit comprised of core modules such as a front-end matching circuit, energy conversion diodes, and a filter module. Among these components, the energy conversion diode plays a crucial role, and its nonlinear characteristics are a key factor affecting circuit performance. The following section will focus on modeling and analyzing its nonlinear characteristics.

[0058] observe Figure 3 In the equivalent circuit of the energy conversion circuit, the relationship between the voltage drop across the diode and the current flowing through it can be expressed as:

[0059] v d (t)=v in (t)-v out (t),

[0060]

[0061] Among them, v t Let v represent the thermal voltage, and n represent the ideality factor. To further investigate its nonlinear eigenvalues ​​and the influence of the input waveform on the output current, v can be... d (t) is set to a constant value v a Then, a Taylor series expansion is performed around this value, which takes the following form:

[0062]

[0063] in, and In the formula, v in (t) and v B There is a close correlation between (t).

[0064] Assume the integrated terminal is configured as a single energy storage system and has N F Each carrier frequency operates independently and without interference during transmission. Based on this assumption, the voltage value of one port of the integrated terminal can be derived as follows:

[0065]

[0066] in, This comes from the transmission model. It pertains to the transmitted voltage (signal). Its nth t The energy storage system generates a carrier frequency of nf The signal can be described as:

[0067]

[0068] Among them, the mean of the signal Integrated weights and These represent the subcarrier frequencies respectively. The waveform amplitude and beamforming phase parameters are set. The aforementioned carrier frequencies can be set to a uniform distribution. Δ f It is a frequency gap. Therefore, it can be defined as follows: in

[0069] To clearly illustrate the relationship between the two, we can further assume that the energy conversion circuit reaches a steady-state response, i.e., the output voltage v out (t) no longer jitters highly over time, therefore i out (t) will also remain in a steady state. Based on this, a reasonable fixed value of voltage drop v can be selected. a and set it to v a =E{v in (t)-v out}=-v out .

[0070] Assuming the integrated terminal uses a lossless power allocation scheme to separate information and energy, and the power allocation coefficient is ρ, then the input voltage value of the actual energy conversion circuit is... Therefore, i d (t) can be converted to:

[0071]

[0072] The above formula organically integrates the end-to-end transmission model with the diode model. Crucially, this formula possesses waveform analysis capabilities, thus introducing new degrees of freedom for system optimization. In engineering practice, system deployment focuses more on considering the average output power, i.e., ii E =E{i d (t)},i E It can be represented as:

[0073]

[0074] Further analysis, taking i = 2, 3, 4 as an example, leads to the following conclusions:

[0075]

[0076] in, And such as and The expression is a simplified representation of the relationship between carrier frequency and phase. Similarly, Other similar statements will not be repeated here.

[0077] Further i E The approximation is as follows:

[0078]

[0079] The above formula includes the case where n terms are even. Since odd-numbered terms contribute relatively little to the DC current output, a DC term is only generated when the number of inter-frequency "+" and "-" terms is equal. Furthermore, when n = 2, it is observed to be basically consistent with the standard linear model form, but in practical applications, it should satisfy n > 2, which is the root of the nonlinear effect. Let n = 4, and let i... E After back-end filtering, only the DC component is retained for in-depth analysis of nonlinear characteristics. Based on the above settings, the simplified i E The specific form can be expressed as

[0080] i E ≈k2ρ(E{A{v B (t) 2}})+k4ρ 2 (E{A{v B (t) 4}}),

[0081] When expanded, it can be represented as:

[0082]

[0083] The mean of the second-order signal is The mean of the fourth-order signal is Therefore, the average output current i E It can be represented as:

[0084]

[0085] S3. Construct a nonlinear energy conversion model that combines an end-to-end model.

[0086] Based on the aforementioned transmission and nonlinear models, we will first explore the signal-to-noise ratio (SNR) expression in downlink transmission with simultaneous signal and power transmission. We assume that the reflection coefficient reaches an ideal matching state, i.e., Γ. B =0, and external noise is taken into account. Due to the influence of power division, the signal after power division is used for information demodulation, and its expression is:

[0087]

[0088] in, Represents the beamforming vector. This represents the transmission waveform. Therefore, the signal-to-noise ratio (SNR) of the integrated terminal under simultaneous signal and power transmission can be expressed as:

[0089]

[0090] Similarly, for reverse transmission of the environment, set Γ B =I, considering external noise The received signal of the environmental reverse receiver can be represented as:

[0091]

[0092] In the formula, Represents the nth f Transmission channels for each sub-transmission frequency band.

[0093] The environmental inverse signal-to-noise ratio can be expressed as:

[0094]

[0095] Based on the aforementioned model, the problem of maximizing output current is defined, and the following system model is constructed under the constraints of downlink integrated terminal signal-to-noise ratio requirements, environmental reverse signal-to-noise ratio requirements, total power level, and physical limitations of the smart metasurface:

[0096]

[0097] 0≤ρ≤1.

[0098] in, For beamforming vectors, For transmitting waveforms, For the signal-to-noise ratio of the integrated terminal under simultaneous transmission and reception, The signal-to-interference-plus-noise ratio of the integrated terminal. For environmental inverse signal-to-noise ratio. For the signal-to-interference-plus-noise ratio of the environmental reverse receiver, ||x|| F Represents the norm, P Max At maximum transmission power, For the nth i The scattering coefficient of a smart metasurface.

[0099] The above formulas respectively reflect the maximization of output current, the minimum requirement of downlink signal-to-noise ratio of integrated terminal, the minimum requirement of environmental reverse transmission signal-to-noise ratio, the limitation of total power, the constraint of intelligent metasurface back-end reflection phase, and the limitation of power division factor.

[0100] In the nonlinear energy conversion model combining end-to-end models as described above, multiple variables are coupled, resulting in a complex form. To effectively solve this model, this invention employs the following... Figure 4 The iterative decoupling method shown divides the variables into three sub-problems for step-by-step solution. Sub-problem one is based on beamforming vectors. Sub-problem 2: Based on multi-carrier waveforms and power division factors And ρ, subproblem three is based on the reflection coefficient Θ of the back-end load of the smart metasurface. After constructing a nonlinear energy conversion model combining an end-to-end model, the beamforming vector is first initialized. Based on multicarrier waveform and power segmentation factor And ρ, based on the intelligent metasurface back-end load reflection coefficient Θ, and then using as... Figure 4 The process shown iteratively processes these four variables to obtain the optimized four variables, which are then returned to the nonlinear energy conversion model combining the end-to-end model as the optimal parameters of the nonlinear energy conversion model combining the end-to-end model.

[0101] Figure 5 The output current of the rectifier circuit at different bandwidth levels is shown. Figure 6 The output current of the rectifier circuit under different numbers of antennas is given, and the settings for each case are the same as those for the previous case. Figure 5 The performance differences remained consistent across all cases, and the order of performance gaps remained unchanged. This indicates that the hardware characteristics of the intelligent metasurface and rectifier circuit significantly impact the actual system performance. Their output currents all tend to increase with the number of transmitting antennas. This consistent performance demonstrates that a larger number of transmitting antennas provides greater freedom in beamforming, resulting in more significant gains for system optimization. Furthermore, the performance differences in output current across the control cases gradually increase with the number of transmitting antennas, suggesting that performance deviations become more pronounced when hardware effects are not considered or certain parameters are not optimized.

[0102] Based on the foregoing analysis, this invention proposes an intelligent metasurface-assisted passive environmental system, whose analytical energy conversion model is an extension of the end-to-end scattering parameter model. This model integrates an environmental reverse communication transmission link, effectively consolidating the main transmission link and demonstrating the scalability advantages of the scattering parameter model. Furthermore, this model combines a signal-energy simultaneous transmission system with an environmental reverse system to construct a complete passive environmental system, and designs a hybrid transmission mechanism that balances performance and efficiency, ensuring the self-replenishment capability of the terminal equipment.

[0103] For those skilled in the art, various other corresponding changes and modifications can be made based on the technical solutions and concepts described above, and all such changes and modifications should fall within the protection scope of the claims of this invention.

Claims

1. An analytical energy conversion system for a passive environment assisted by an intelligent metasurface, characterized in that, include: An end-to-end passive system transmission model is constructed based on a transmission environment consisting of a smart metasurface, a transmitter, an integrated terminal, and an environmental reverse receiver. The transmission environment has two transmission modes: common transmission of downlink signals and environmental reverse transmission. The end-to-end passive system transmission model covers both the common transmission mode and the environmental reverse transmission mode of the downlink signals. A nonlinear energy conversion model with waveform analytical properties; The nonlinear energy conversion model, which combines the end-to-end model with the passive system transmission model and the nonlinear energy conversion model, is constructed. The method for constructing the end-to-end passive system transmission model is as follows: The number of the integrated terminals is set to The number of the environmental reverse receivers is A method based on scattering parameters is used to treat the transmission path as an N-port network in order to solve the relationship between the transmitted waves b and a. Based on the relationship between the system transmitted waves b and a obtained from the solution, the transmission model from the transmitter to the integrated terminal is derived. And the transmission model from transmitter to environmental reverse receiver ; Calculate the power values ​​of the corresponding ports of the integrated terminal under load matching and load mismatch conditions; The formula for calculating the power value is simplified to obtain a transmission model that characterizes the maximum received power value at the integrated terminal and the environmental reverse receiver location. and ; The end-to-end passive system transmission model is as follows: in, This represents the transmission model under integrated terminal load matching conditions. S represents the transmission model under the conditions of total reflection at the integrated terminal load and load matching of the environmental reverse receiver. BT S is the scattering transmission matrix from transmitter to integrated terminal. BI S is the scattering transfer matrix from the smart metasurface to the integrated terminal. II For the self-scattering transfer matrix of the intelligent metasurface, S IT S is the scattering transfer matrix from the transmitter to the smart metasurface. RB To integrate the scattering transmission matrix from the terminal to the environmental reverse receiver, Θ -1 This is the inverse of the reflection coefficient matrix of the intelligent metasurface; The nonlinear energy conversion model is as follows: ； in, To analyze the output current of the rectifier circuit in the energy conversion system, k 2 and k 4 are all circuit constant factors. ρ The power allocation factor, In the transmission model The n f A transmission channel with multiple subcarriers In the transmission model The n f Beamforming vectors for each subcarrier, N F This represents the total number of carriers.

2. The analytical energy conversion system of the intelligent metasurface-assisted passive environment system according to claim 1, characterized in that, The transmitter is connected to the intelligent metasurface via an auxiliary link and to the integrated terminal via a direct link, forming a common transmission mode for downlink signals; the integrated terminal is connected to the environmental reverse receiver via an environmental reverse link, forming an environmental reverse transmission mode.

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