5G multi-frequency antenna and signal adjusting method

Abstract

The invention relates to the technical field of multi-frequency antennas, in particular to a 5G multi-frequency antenna and a signal adjusting method, and the antenna comprises a reconfigurable metasurface antenna array, an intelligent signal adjusting module and an environment perception and control module. By dynamically adjusting the electromagnetic characteristics of the metasurface unit and adopting a self-adaptive signal processing algorithm based on reinforcement learning, dynamic frequency band coverage, intelligent signal adjustment and high energy efficiency ratio can be realized, and the system can be widely applied to the field of 5G communication; the defects of multi-band coverage, signal adjusting capability, hardware complexity and energy efficiency ratio in the prior art are effectively overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of multi - frequency antennas, and more specifically, it relates to a 5G multi - frequency antenna and a signal adjustment method. Background Technique

[0002] With the rapid development of 5G communication technology, the performance requirements for antennas are getting higher and higher. Traditional multi - frequency antennas are usually designed to cover fixed frequency bands (such as Sub - 6GHz or millimeter - wave), and it is difficult to dynamically adapt to the needs of different 5G frequency bands. At the same time, existing signal adjustment technologies mainly rely on fixed algorithms and cannot optimize signal processing strategies in real - time according to environmental changes. In complex urban environments, signal interference sources and user distributions change dynamically, and traditional methods are difficult to adjust beamforming and interference suppression strategies in real - time, resulting in a decline in communication quality. Therefore, in response to the above - mentioned problems, a 5G multi - frequency antenna and a signal adjustment method are proposed, which improve and solve the above problems in terms of multi - band coverage and signal adjustment capabilities. Summary of the Invention

[0003] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a 5G multi - frequency antenna and a signal adjustment method to solve the problems existing in the above - mentioned background technique.

[0004] The above - mentioned technical purpose of the present invention is achieved through the following technical solutions: A 5G multi - frequency antenna includes a multi - frequency antenna body; on the multi - frequency antenna body, there are provided: a reconfigurable metasurface antenna array, an intelligent signal adjustment module for adjusting the reconfigurable metasurface antenna array according to the received signal strength, and an environment perception and control module for adjusting the reconfigurable metasurface antenna array according to environmental perception data; the reconfigurable metasurface antenna array is detachably connected to the multi - frequency antenna body; the intelligent signal adjustment module and the environment perception and control module are respectively detachably connected to the multi - frequency antenna body; the intelligent signal adjustment module and the environment perception and control module are respectively electrically connected to the reconfigurable metasurface antenna array.

[0005] Optionally, the reconfigurable metasurface antenna array includes a number of metasurface units; a number of the metasurface units are all detachably connected to the multi - frequency antenna body; a number of the metasurface units are arranged at equal distances on the multi - frequency antenna body; a number of the metasurface units are respectively electrically connected to the intelligent signal adjustment module and the environment perception and control module.

[0006] Optionally, the metasurface unit includes a metal patch, a dielectric substrate, and a tunable element for changing the resonant frequency and phase response; the dielectric substrate is detachably connected to the multi - frequency antenna body; the metal patch is arranged on the upper surface of the dielectric substrate; the tunable element is embedded in the dielectric substrate.

[0007] Optionally, the intelligent signal adjustment module includes: a signal receiving unit for receiving the signal transmitted by the reconfigurable metasurface antenna array and performing preliminary processing and transmission, an intelligent signal processing unit for processing the data transmitted by the signal receiving unit and outputting an adjustment strategy, and a signal transmitting unit for amplifying the power and adjusting the phase of the signal according to the adjustment strategy output by the intelligent signal processing unit; the receiving end of the signal receiving unit is electrically connected to the reconfigurable metasurface antenna array, and the transmission end of the signal receiving unit is electrically connected to the receiving end of the intelligent signal processing unit; the transmission end of the intelligent signal processing unit is electrically connected to the signal transmitting unit; the signal transmitting unit is electrically connected to the reconfigurable metasurface antenna array.

[0008] Optionally, the environment perception and control module includes several environment sensors for identifying and acquiring external information and a dynamic adjustment unit for dynamically adjusting according to the acquired external information; several of the environment sensors are respectively arranged on the multi-frequency antenna body; the input end of the dynamic adjustment unit is electrically connected to several of the environment sensors respectively, and the output end of the dynamic adjustment unit is electrically connected to the reconfigurable metasurface antenna array.

[0009] A signal adjustment method for a 5G multi-frequency antenna based on the above, including,

[0010] Step A, receiving a signal: receiving a signal through the reconfigurable metasurface antenna array and transmitting the signal data to the intelligent signal adjustment module;

[0011] Step B, signal preprocessing: the signal receiving unit preprocesses the received signal to obtain signal data after removing noise;

[0012] Step C, signal feature extraction: the intelligent signal processing unit extracts features from the signal data after removing noise to obtain corresponding feature vectors;

[0013] Step D, constructing a signal adjustment model and inputting the characteristic vector to obtain an adjustment strategy: the intelligent processing unit constructs a signal adjustment model and inputs the corresponding feature vector into the constructed signal adjustment model to obtain the corresponding adjustment strategy;

[0014] Step E, signal adjustment enhancement based on the adjustment strategy: the signal transmitting unit processes and enhances the signal based on the obtained adjustment strategy and then transmits it.

[0015] Optionally, the intelligent signal processing unit in step C extracts features from the signal data after removing noise to obtain corresponding feature vectors, and the specific implementation process is as follows,

[0016] C1. The received multi-band signal is expressed as where s i(t) represents the signal of the i-th frequency band;

[0017] C2. Normalize the received signal where μ y represents the mean of the signal, and σ y represents the standard deviation of the signal;

[0018] C3. Perform short-time Fourier transform on the normalized signal to extract time-frequency features, where, represents the wavelet basis function, a is the scale parameter, and b is the translation parameter;

[0019] C4. Convert the extracted time-frequency features into a feature vector X as the model input quantity for step D.

[0020] Optionally, in step D, a signal adjustment model is constructed, the characteristic vector is input, and an adjustment strategy is obtained: The intelligent processing unit constructs a signal adjustment model, inputs the corresponding feature vector into the constructed signal adjustment model, and obtains the corresponding adjustment strategy. The specific implementation process is as follows.

[0021] D1. Define the state space S of the signal adjustment model, including the current signal strength, interference source location, and user distribution information, denoted as s t ={x, I, U}, where I is the interference source location matrix and U is the user distribution matrix;

[0022] D2. Define the action space A of the signal adjustment model, including the configuration of the metasurface unit, signal separation parameters, and beamforming parameters, denoted as a t ={C, P, B}, where C is the metasurface unit configuration matrix, P is the signal separation parameter matrix, and B is the beamforming parameter matrix;

[0023] D3. Design the reward function R of the signal adjustment model to evaluate the signal processing effect, denoted as R(s t , a t ) = α·SINR + β·EnergyEfficiency + γ·UserSatisfaction, where SINR is the signal-to-interference-plus-noise ratio, EnergyEfficiency is the energy efficiency ratio, UserSatisfaction is the user satisfaction, and α, β, and γ are the weight coefficients of each item respectively;

[0024] D4. Optimize the strategy of the signal adjustment model, use the deep reinforcement learning algorithm, and obtain the optimal signal processing strategy through interaction with the environment, denoted as where γ is the discount factor and T is the time step;

[0025] D5. Input the feature vector X of the corresponding signal obtained into the signal conditioning model after adjustment to obtain the adjustment strategy a. t .

[0026] Optionally, in the signal conditioning enhancement based on the adjustment strategy in step E: The signal transmitting unit processes and enhances the signal based on the obtained adjustment strategy and then transmits it. The specific implementation process is as follows.

[0027] E1. According to the adjustment strategy a obtained in step D t , separate the received signal, expressed as where f i represents the signal separation function, and θ i is the separation parameter;

[0028] E2. Perform enhancement processing on the separated signal to improve the signal-to-noise ratio and anti-interference ability of the signal, expressed as where g i represents the signal enhancement function, and φ i is the enhancement parameter;

[0029] E3. Transmit the signal after enhancement processing through the signal transmitting unit.

[0030] Optionally, the signal separation function in step E1 is a signal separation model based on a deep neural network, and its expression is f i (y(t); θ i ) = NN i (y(t); θ i ), where NN i represents the deep neural network, and θ i is the network parameter.

[0031] In summary, the present invention has the following beneficial effects:

[0032] 1. The multi-frequency antenna body adopts the reconfigurable metasurface technology, which can dynamically adjust the working frequency band of the antenna to meet the requirements of different 5G frequency bands; in the wide-area coverage scenario, the antenna can be switched to the Sub-6GHz frequency band; in the high-density hotspot area, the antenna can be switched to the millimeter-wave frequency band; the dynamic switching ability significantly improves the flexibility and resource utilization rate of the antenna.

[0033] 2. During the operation of the antenna, the antenna can intelligently adjust the signal, adopt the adaptive signal processing algorithm based on reinforcement learning, and can optimize the signal processing strategy in real time according to environmental changes; in the complex urban environment, the system can adjust the beamforming and interference suppression strategies in real time, significantly improving the communication quality and user experience.

[0034] 3. Through intelligent signal regulation and environmental perception, the energy consumption of the system is reduced and the energy efficiency ratio is improved; the antenna system can dynamically adjust the transmission power according to the user distribution and signal strength, reducing unnecessary energy consumption. Brief Description of the Drawings

[0035] Figure 1 It is a schematic flow chart of the steps of the signal regulation method of the present invention. Detailed Embodiments

[0036] To make the objectives, features, and advantages of the present invention more obvious and understandable, the following provides a detailed description of the specific embodiments of the present invention with reference to the accompanying drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0037] In the present invention, unless otherwise clearly specified and defined, terms such as "installed", "connected", "connected to", "fixed", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features.

[0038] In the present invention, unless otherwise clearly specified and defined, the first feature being "above" or "below" the second feature may include the direct contact of the first and second features, or may include the non-direct contact of the first and second features but through other features between them. Moreover, the first feature being "above", "over", and "on" the second feature includes the first feature being directly above and obliquely above the second feature, or simply indicating that the first feature has a higher horizontal height than the second feature. The first feature being "below", "beneath", and "under" the second feature includes the first feature being directly below and obliquely below the second feature, or simply indicating that the first feature has a lower horizontal height than the second feature. Terms such as "vertical", "horizontal", "left", "right", "up", "down", and similar expressions are only for the purpose of illustration and do not indicate or imply that the indicated device or element must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the present invention.

[0039] The following describes the present invention in detail with reference to the drawings and embodiments.

[0040] The present invention provides a 5G multi - frequency antenna and a signal adjustment method, as Figure 1 shown, which includes a multi - frequency antenna body; on the multi - frequency antenna body, there are provided: a reconfigurable metasurface antenna array, an intelligent signal adjustment module for adjusting the reconfigurable metasurface antenna array according to the received signal strength, and an environment perception and control module for adjusting the reconfigurable metasurface antenna array according to the environmental perception data; the reconfigurable metasurface antenna array is detachably connected to the multi - frequency antenna body; the intelligent signal adjustment module and the environment perception and control module are respectively detachably connected to the multi - frequency antenna body; the intelligent signal adjustment module and the environment perception and control module are respectively electrically connected to the reconfigurable metasurface antenna array.

[0041] In the specific implementation process, when receiving signals, different frequency bands are adjusted through the reconfigurable metasurface antenna array to receive signals of different frequency bands. After receiving the signals, they are analyzed by the intelligent signal adjustment module, enhanced after analysis and then transmitted to achieve better communication quality; during the daily operation process, the working frequency of the reconfigurable metasurface antenna array is dynamically adjusted through the environment perception and control module to achieve better energy - saving effects.

[0042] Furthermore, the reconfigurable metasurface antenna array includes several metasurface units; several of the metasurface units are all detachably connected to the multi - frequency antenna body; several of the metasurface units are arranged at equal intervals on the multi - frequency antenna body; several of the metasurface units are respectively electrically connected to the intelligent signal adjustment module and the environment perception and control module.

[0043] In the first embodiment, the size of each metasurface unit is λ / 4, where λ is the working wavelength. During the arrangement process, several metasurface units are arranged at equal intervals to form a rectangular grid structure, and the unit spacing is λ / 2 to ensure the radiation characteristics of the antenna array;

[0044] In the working mode, in the Sub - 6GHz frequency band, the resonant frequency of the metasurface unit is adjusted to 3.5GHz to achieve wide - area coverage; in the millimeter - wave frequency band, the resonant frequency of the metasurface unit is adjusted to 28GHz to achieve high - density hot - spot area coverage; by adjusting the phase distribution of the metasurface units, dynamic beamforming is achieved to improve the signal coverage range and anti - interference ability.

[0045] Furthermore, the metasurface unit includes a metal patch, a dielectric substrate, and a tunable element for changing the resonant frequency and phase response; the dielectric substrate is detachably connected to the multi - frequency antenna body; the metal patch is arranged on the upper surface of the dielectric substrate; the tunable element is embedded in the dielectric substrate.

[0046] In the second embodiment, the tunable element uses a varactor diode, and its capacitance value is adjusted by an external control voltage, so as to change the resonant frequency and phase response of the metasurface unit, so as to receive signals of different frequencies and frequency bands.

[0047] Further, the intelligent signal adjustment module includes: a signal receiving unit for receiving the signal transmitted by the reconfigurable metasurface antenna array and performing preliminary processing and transmission, an intelligent signal processing unit for processing the data transmitted by the signal receiving unit and outputting an adjustment strategy, and a signal transmitting unit for amplifying the power and adjusting the phase of the signal according to the adjustment strategy output by the intelligent signal processing unit; the receiving end of the signal receiving unit is electrically connected to the reconfigurable metasurface antenna array, and the transmission end of the signal receiving unit is electrically connected to the receiving end of the intelligent signal processing unit; the transmission end of the intelligent signal processing unit is electrically connected to the signal transmitting unit; the signal transmitting unit is electrically connected to the reconfigurable metasurface antenna array.

[0048] In the third embodiment, the signal receiving unit performs preliminary filtering, amplification, and normalization processing on the received signal, where the filtering process is expressed as Perform band-pass filtering on the received signal to remove out-of-band noise, where h(t) represents the impulse response of the band-pass filter. After the filtering process, further amplify the filtered signal, which is expressed as y amplified (t) = G·y filtered (t), where G represents the amplification gain; after preprocessing the signal, it is convenient for subsequent analysis and adjustment.

[0049] Further, the environment perception and control module includes several environment sensors for identifying and acquiring external information and a dynamic adjustment unit for dynamically adjusting according to the acquired external information; several of the environment sensors are respectively arranged on the multi-frequency antenna body; the input end of the dynamic adjustment unit is electrically connected to several of the environment sensors respectively, and the output end of the dynamic adjustment unit is electrically connected to the reconfigurable metasurface antenna array.

[0050] In the fourth embodiment, the environment sensor includes a signal strength sensor for real-time measurement of the strength of the received signal, which is expressed as An interference source positioning sensor for positioning the position of the interference source through the Doppler effect, which is expressed as I = (x i ,y i ,z i ); a user distribution sensor for determining the user distribution position range by receiving the signal strength indication of the user equipment, which is expressed as U = {(x u ,y u ,z u)}; It also obtains network load through external network feedback: the number of users and data traffic of the current network, interference source information: the location and intensity of interference sources of other base stations or devices, and user location: the precise location of the user equipment obtained through GPS or base station triangulation;

[0051] According to the obtained data, the dynamic adjustment unit performs dynamic adjustment, including the following: metasurface unit configuration adjustment: calculating the phase distribution of metasurface units according to the location of interference sources and the range of user distribution locations where H u represents the channel matrix of user u, and D u represents the desired beamforming direction. By adjusting the phase distribution of metasurface units, dynamic beamforming is achieved to avoid interference sources and cover target users;

[0052] According to the signal strength P r and the interference source strength P i , calculate the signal-to-interference-plus-noise ratio, denoted as where P n represents the noise power. According to the calculated signal-to-interference-plus-noise ratio, dynamically adjust the signal separation parameter P and the beamforming parameter B, P = f sep (SINR), B = f beam (SINR), where f sep and f beam are preset adjustment functions, which can be automatically generated by the system or adjusted manually;

[0053] According to the user distribution U and network load, dynamically adjust the transmit power P t , denoted as where P max represents the maximum transmit power, and P req represents the user demand power.

[0054] A signal adjustment method based on the above 5G multi-band antenna includes,

[0055] Step A, receive signals: receive signals through a reconfigurable metasurface antenna array and transmit the signal data to the intelligent signal adjustment module;

[0056] Step B, signal preprocessing: the signal receiving unit preprocesses the received signals to obtain signal data after removing noise;

[0057] Step C, signal feature extraction: the intelligent signal processing unit extracts features from the signal data after removing noise to obtain the corresponding feature vectors;

[0058] Step D: Construct a signal regulation model, input the characteristic vector, and obtain the regulation strategy: The intelligent processing unit constructs a signal regulation model, inputs the corresponding feature vector into the constructed signal regulation model, and obtains the corresponding adjustment strategy;

[0059] Step E: Perform signal regulation enhancement based on the regulation strategy: The signal transmitting unit processes and enhances the signal based on the obtained adjustment strategy and then transmits it.

[0060] Optionally, the intelligent signal processing unit in step C extracts feature vectors from the signal data after noise removal. The specific implementation process is as follows.

[0061] C1: The received multi-band signal is expressed as where s i (t) represents the signal of the i-th frequency band;

[0062] C2: Normalize the received signal where μ y represents the mean of the signal, and σ y represents the standard deviation of the signal;

[0063] C3: Perform short-time Fourier transform on the normalized signal to extract time-frequency features. where, represents the wavelet basis function, a is the scale parameter, and b is the translation parameter;

[0064] C4: Convert the extracted time-frequency features into a feature vector X, which is used as the model input quantity for step D.

[0065] Optionally, for the construction of the signal regulation model in step D, input the characteristic vector and obtain the regulation strategy: The intelligent processing unit constructs a signal regulation model, inputs the corresponding feature vector into the constructed signal regulation model, and obtains the corresponding adjustment strategy. The specific implementation process is as follows.

[0066] D1: Define the state space S of the signal regulation model, including the current signal strength, interference source location, and user distribution information, expressed as s t = {x, I, U}, where I is the interference source location matrix and U is the user distribution matrix;

[0067] D2: Define the action space A of the signal regulation model, including the configuration of the metasurface unit, signal separation parameters, and beamforming parameters, expressed as a t = {C, P, B}, where C is the metasurface unit configuration matrix, P is the signal separation parameter matrix, and B is the beamforming parameter matrix;

[0068] D3. Design the reward function R of the signal adjustment model to evaluate the signal processing effect, expressed as R(s t , a t ) = α·SINR + β·EnergyEfficiency + γ·UserSatisfaction, where SINR is the signal-to-interference-plus-noise ratio, EnergyEfficiency is the energy efficiency ratio, UserSatisfaction is the user satisfaction, and α, β, and γ are the weight coefficients of each item respectively;

[0069] D4. Optimize the strategy of the signal adjustment model. Using the deep reinforcement learning algorithm, through interaction with the environment, obtain the optimal signal processing strategy, expressed as where γ is the discount factor and T is the time step;

[0070] D5. Input the obtained feature vector X of the corresponding signal into the adjusted signal adjustment model to obtain the adjustment strategy a t .

[0071] Optionally, in the signal adjustment enhancement based on the adjustment strategy in step E: The signal transmitting unit processes and enhances the signal based on the obtained adjustment strategy and then transmits it. The specific implementation process is as follows.

[0072] E1. According to the adjustment strategy a obtained in step D t , separate the received signal, expressed as θ i ), where f i represents the signal separation function and θ i is the separation parameter;

[0073] E2. Perform enhancement processing on the separated signal to improve the signal-to-noise ratio and anti-interference ability of the signal, expressed as where g i represents the signal enhancement function and φ i is the enhancement parameter;

[0074] E3. Transmit the enhanced signal through the signal transmitting unit.

[0075] Optionally, the signal separation function in step E1 is a signal separation model based on a deep neural network, and its expression is f i (y(t); θ i ) = NN i (y(t); θ i ), where NN i represents the deep neural network and θ i is the network parameter.

[0076] Optionally, the signal enhancement function in step E2 is a filter-based signal enhancement model, and its expression is: where h i (t) represents the impulse response of the filter, and φ i represents the filter parameter.

[0077] A 5G multi-band antenna and signal adjustment method of the present invention. The multi-band antenna body adopts the reconfigurable metasurface technology, which can dynamically adjust the operating frequency band of the antenna to meet the requirements of different 5G frequency bands. In the wide-area coverage scenario, the antenna can be switched to the Sub-6GHz frequency band. In the high-density hot spot area, the antenna can be switched to the millimeter wave frequency band. The dynamic switching ability significantly improves the flexibility and resource utilization rate of the antenna. During the operation of the antenna, the antenna can intelligently adjust the signal, adopt an adaptive signal processing algorithm based on reinforcement learning, and can optimize the signal processing strategy in real time according to environmental changes. In a complex urban environment, the system can adjust the beamforming and interference suppression strategies in real time, significantly improving the communication quality and user experience. Through intelligent signal adjustment and environmental perception, the energy consumption of the system is reduced and the energy efficiency ratio is improved. The antenna system can dynamically adjust the transmission power according to the user distribution and signal strength, reducing unnecessary energy consumption.

[0078] The above are only the preferred embodiments of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A 5G multi-band antenna, characterized in that, It includes a multi - frequency antenna body; on the multi - frequency antenna body, there are provided: a reconfigurable metasurface antenna array, an intelligent signal adjustment module for adjusting the reconfigurable metasurface antenna array according to the received signal strength, and an environment perception and control module for adjusting the reconfigurable metasurface antenna array according to the environment perception data; The reconfigurable metasurface antenna array is detachably connected to the multi - frequency antenna body; the intelligent signal adjustment module and the environment perception and control module are respectively detachably connected to the multi - frequency antenna body; the intelligent signal adjustment module and the environment perception and control module are respectively electrically connected to the reconfigurable metasurface antenna array.

2. The 5G multi-band antenna according to claim 1, characterized in that The reconfigurable metasurface antenna array includes a number of metasurface units; a number of the metasurface units are all detachably connected to the multi - frequency antenna body; A number of the metasurface units are arranged equidistantly on the multi - frequency antenna body; a number of the metasurface units are respectively electrically connected to the intelligent signal adjustment module and the environment perception and control module.

3. The 5G multi-band antenna according to claim 2, characterized in that The metasurface unit includes a metal patch, a dielectric substrate, and a tunable element for changing the resonant frequency and phase response; The dielectric substrate is detachably connected to the multi - frequency antenna body; the metal patch is arranged on the upper surface of the dielectric substrate; The tunable element is embedded in the dielectric substrate.

4. A 5G multi-band antenna according to claim 1, characterized in that, The intelligent signal adjustment module includes: a signal receiving unit for receiving the signal transmitted by the reconfigurable metasurface antenna array and performing preliminary processing and transmission, an intelligent signal processing unit for processing the data transmitted by the signal receiving unit and outputting an adjustment strategy, and a signal transmitting unit for amplifying the power and adjusting the phase of the signal according to the adjustment strategy output by the intelligent signal processing unit; The receiving end of the signal receiving unit is electrically connected to the reconfigurable metasurface antenna array, the transmission end of the signal receiving unit is electrically connected to the receiving end of the intelligent signal processing unit; the transmission end of the intelligent signal processing unit is electrically connected to the signal transmitting unit; the signal transmitting unit is electrically connected to the reconfigurable metasurface antenna array.

5. A 5G multi-band antenna according to claim 1, characterized in that, The environment perception and control module includes a number of environment sensors for identifying and acquiring external information and a dynamic adjustment unit for performing dynamic adjustment according to the acquired external information; A number of the environment sensors are respectively arranged on the multi - frequency antenna body; the input end of the dynamic adjustment unit is respectively electrically connected to a number of the environment sensors, and the output end of the dynamic adjustment unit is electrically connected to the reconfigurable metasurface antenna array.

6. A signal adjustment method for a 5G multi-band antenna according to any one of claims 1-5, characterized in that, Including, Step A, receiving a signal: receiving a signal through the reconfigurable metasurface antenna array and transmitting the signal data to the intelligent signal adjustment module; Step B, signal pre - processing: the signal receiving unit pre - processes the received signal to obtain signal data after noise removal; Step C, signal feature extraction: the intelligent signal processing unit extracts features from the signal data after noise removal to obtain the corresponding feature vector; Step D: Construct a signal regulation model, input the characteristic vector, and obtain the regulation strategy: The intelligent processing unit constructs a signal regulation model, inputs the corresponding feature vector into the constructed signal regulation model, and obtains the corresponding adjustment strategy; Step E: Perform signal regulation enhancement based on the regulation strategy: The signal transmitting unit processes and enhances the signal based on the obtained adjustment strategy and then transmits it.

7. A signal adjustment method for a 5G multi-band antenna according to claim 6, characterized in that, The intelligent signal processing unit in step C extracts features from the signal data after noise removal to obtain the corresponding feature vector. The specific implementation process is as follows: C1. The received multi-band signal is represented as where s i (t) represents the signal of the i-th frequency band; C2. Normalize the received signal where μ y represents the mean of the signal, and σ y represents the standard deviation of the signal; C3. Perform short-time Fourier transform on the normalized signal to extract time-frequency features. Among them, is expressed as a wavelet basis function, a is the scale parameter, and b is the translation parameter; C4: Convert the extracted time-frequency features into a feature vector X as the model input quantity for step D.

8. A signal adjustment method for a 5G multi-band antenna according to claim 6, characterized in that, In step D, for constructing the signal regulation model and inputting the characteristic vector to obtain the regulation strategy: The intelligent processing unit constructs a signal regulation model, inputs the corresponding feature vector into the constructed signal regulation model, and obtains the corresponding adjustment strategy. The specific implementation process is as follows: D1. Define the state space S of the signal regulation model, including the current signal strength, the position of the interference source, and the user distribution information, denoted as s t = {x, I, U}, where I is the interference source position matrix and U is the user distribution matrix; D2. Define the action space A of the signal adjustment model, including the configuration of the metasurface units, signal separation parameters, and beamforming parameters, denoted as a t ={C, P, B}, where C is the metasurface unit configuration matrix, P is the signal separation parameter matrix, and B is the beamforming parameter matrix; D3. Design the reward function R of the signal adjustment model to evaluate the signal processing effect, expressed as R(s t , a t ) = α·SINR + β·EnergyEfficiency + γ·UserSatisfaction, where SINR is the signal-to-interference-plus-noise ratio, EnergyEfficiency is the energy efficiency ratio, UserSatisfaction is the user satisfaction, and α, β, and γ are the weight coefficients of each item respectively; D4. Optimize the strategy of the signal adjustment model. Using the deep reinforcement learning algorithm, through interacting with the environment, obtain the optimal signal processing strategy, expressed as where γ is the discount factor and T is the time step; D5. Input the feature vector X of the corresponding signal obtained into the signal conditioning model after adjustment to obtain the adjustment strategy a t .

9. A signal adjustment method for a 5G multi-band antenna according to claim 6, characterized in that, In step E, for performing signal regulation enhancement based on the regulation strategy: The signal transmitting unit processes and enhances the signal based on the obtained adjustment strategy and then transmits it. The specific implementation process is as follows: E1. The adjustment strategy a obtained according to step D t , separate the received signal, expressed as where f i represents the signal separation function, and θ i is the separation parameter; E2. Enhance the separated signal to improve the signal-to-noise ratio and anti-interference ability of the signal, expressed as where g i is expressed as the signal enhancement function, and φ i is expressed as the enhancement parameter; E3: Transmit the signal after enhancement processing through the signal transmitting unit.

10. A signal adjustment method for a 5G multi-band antenna according to claim 8, characterized in that, The signal separation function in the step E1 is a signal separation model based on a deep neural network, and its expression is f i (y(t); θ i ) = NN i (y(t); θ i ), where NN i is represented as a deep neural network, and θ i is represented as network parameters.

Images