Beam forming optimization system based on energy efficiency priority

Abstract

The invention relates to the field of energy efficiency priority beam forming optimization, in particular to an energy efficiency priority-based beam forming optimization system, which comprises a signal transmitting module, a data acquisition module, a signal estimation module, an energy efficiency evaluation module and an adaptive optimization module, and is characterized in that the channel estimation module is used for receiving a user terminal according to a specific pilot signal value transmitted by a base station transmitting end; after a receiving user terminal receives a pilot signal, channel estimation is performed on the pilot signal, an energy efficiency evaluation module analyzes a beam forming signal according to each parameter value of a received data acquisition module, a signal emission module matches a corresponding antenna unit according to the signal, a high-gain beam is formed in a target direction, and the energy efficiency of the beam forming signal is improved. The invention aims to improve the energy efficiency of the system to the greatest extent on the premise of meeting certain communication quality requirements by optimizing beam forming.

Description

Technical Field

[0001] The present invention relates to the field of beamforming optimization based on energy efficiency priority, and specifically to a beamforming optimization system based on energy efficiency priority. Background Technique

[0002] In the current era of rapid technological development, audio technology, as a core part of the audio field, is constantly pursuing higher performance and efficiency. With the growing demand for high-quality audio experiences among people, the functions of audio equipment are becoming increasingly complex; Beamforming technology originally plays an important role in the field of wireless communication. By precisely adjusting the amplitudes and phases of each antenna element in an antenna array, it forms a high-gain antenna beam in a specific direction and suppresses signals in other directions, thereby effectively improving the signal transmission quality and coverage range and reducing interference. A similar principle can be borrowed and applied in the audio field, including in multi-channel audio systems or large-scale amplification equipment. By performing beamforming-like processing on the audio signals of multiple speaker units, it is possible to achieve the focusing and enhancement of sound in a specific area, enabling listeners to obtain a clearer and louder audio experience at a specific position, while reducing the diffusion of sound energy in unnecessary directions and lowering the overall power consumption; In mobile communication, a base station can use beamforming technology to concentrate signals on mobile users, improving signal strength and data transmission rate. With the development of large-scale antenna array technology, through a large number of antenna elements, multiple independent beams can be formed simultaneously to serve multiple users, greatly improving the system capacity and performance. Summary of the Invention

[0003] To solve the technical problems raised in the above background technique, the present invention provides a beamforming optimization system based on energy efficiency priority.

[0004] The object of the present invention can be achieved through the following technical solutions: If the present invention is a beamforming optimization system based on energy efficiency priority, it includes a signal transmission module, a data acquisition module, a signal estimation module, an energy efficiency evaluation module, an adaptive optimization module, a data center, and a cloud server.

[0005] The signal transmission module matches the corresponding antenna elements according to the signal and forms a high-gain beam in the target direction. The specific acquisition method is as follows: Build a wireless communication system model, including a base station equipped with multiple antennas and multiple user terminals. Each user terminal has a corresponding antenna, obtains the signal generated by the base station signal source, marked as the original signal, preprocesses the original signal, and the preprocessing includes amplification, filtering and digitization operations to obtain each digital processed signal. Compare the obtained signals with adjacent digital processed signals in sequence. When the value of the digital processed signal is larger than the values of its adjacent digital processed signals before and after, mark it as a local peak. When the value of the digital processed signal is smaller than the values of its adjacent digital processed signals before and after, mark it as a local valley. The transmitting end distributes the digital processed signals to be transmitted to each antenna unit of the antenna array in parallel. Each processed signal matches the corresponding antenna unit, and each processed signal is transmitted through the antenna and propagates in the form of electromagnetic waves in space. When the electromagnetic waves emitted by each antenna unit are in-phase superimposed in the target direction, the peaks are added to the peaks and the valleys are added to the valleys, so that the amplitude of the synthesized wave in the same direction increases, and a high-gain beam is formed in the target direction.

[0006] The data acquisition module collects the corresponding parameter values according to each sensor and sends the collected parameter values to each module for analysis. The specific acquisition method is as follows: The output end of the data acquisition module is connected to the output end of the signal estimation module, and the output end of the data acquisition module is connected to the input end of the energy efficiency evaluation module. The operating parameters of each transmitter are collected in real time through a voltmeter, and the operating parameters of each transmitter are obtained in real time.

[0007] By installing a network traffic monitor at the receiving end, the network data volume of beamforming within a specific time is collected in real time, and the network data volumes of beamforming within a specific time period are obtained. Similarly, the network data volumes of each beamforming are collected to obtain the network data volumes of each beamforming.

[0008] Extract the known power signal of the antenna in the data center, input a signal with known power to the antenna, and collect the power of the received signal in real time through a vector network analyzer within a specific time to obtain the signal powers of each antenna in real time.

[0009] Connect the spectrum analyzer to the signal receiving port, collect the signal power and noise power of the receiving port in real time to obtain the signal power parameter and noise power parameter, and then collect the signal transmission frequency of the receiving port in a specific time period to obtain the signal frequency parameters in a specific time period.

[0010] The channel estimation module analyzes and calculates the actual estimated value of the signal according to the determined signal model. The specific acquisition method is as follows: The base station transmitting end sends a specific pilot signal value to the receiving user terminal. After the receiving user terminal receives the pilot signal, it performs channel estimation on the pilot signal. Specifically: A1: Determine the channel model and set the transmitted signal as . After transmission through the channel, the actual received signal . There is the following relationship between the transmitted signal and the channel parameters: , where \(t\) represents that the value of the signal changes with time, are the channel parameters, is the additive noise; A2: Extract the estimated value of the channel parameters at the data center, marked as . Calculate according to the estimated value of the channel parameters and the transmitted signal using the formula to obtain the estimated received signal ; A3: Calculate using the obtained estimated received signal and the actual received signal, and use the formula to obtain the error value \(E\) between the estimated value and the true value; A4: Calculate the actual estimated value of the channel parameters according to the obtained error value, and use the formula = 1 to obtain the actual estimated value with the minimum error .

[0011] After the receiving end completes channel estimation in the transmission stage, the actual estimated value is processed and quantized through the feedback information to generate the corresponding feedback information. The feedback information includes key parameters such as the amplitude of the channel, the channel quality indicator, and the precoding matrix indicator. The receiving end sends the feedback information to the transmitting end through the feedback channel. After receiving the feedback information from the receiving end, the transmitting end extracts the historical data of the data center and adjusts the beamforming according to the historical data. The historical data includes the prediction of the channel change trend by the transmitting end, the historical channel information, the system model, and the constraint conditions. The transmitting end recomputes the weighting coefficients of the antenna array through the beamforming algorithm according to the feedback information and the historical data, and adjusts the direction, shape, and power distribution of the beam to optimize the signal transmission. After the transmitting end completes the beamforming adjustment in the iterative optimization stage, it sends the signal again. After the receiving end receives the new signal, it performs channel estimation and feedback again, and the transmitting end adjusts it according to the feedback information, resulting in a continuously iterative optimization process. As the number of iterations increases, the beamforming gradually approaches the optimal, and the system performance also continuously improves.

[0012] The energy efficiency evaluation module analyzes the beamforming signal according to the parameter values of the received data acquisition module. The specific acquisition method is as follows: The output end of the energy efficiency evaluation module is connected to the input end of the optimization module. The signal power parameter, noise power parameter, each signal frequency parameter, and each network data volume in each specific period of beamforming obtained through the data acquisition module are analyzed. Specifically: S1: Based on the obtained signal power parameter and noise power parameter, label them as DC and DF respectively, and use the formula to obtain the signal-to-noise ratio KC at the receiving end; S2: According to the network data volume of each beamforming specific period obtained, extract the duration of the specific period, and obtain the average data transmission rate TH through average calculation; S3: According to the signal frequency parameters of the specific period obtained, extract the highest frequency and the lowest frequency among the signal frequency parameters, and perform a difference calculation on the highest frequency and the lowest frequency to obtain the channel bandwidth value TY of beamforming; S4: By obtaining the signal-to-noise ratio, average data transmission rate and channel bandwidth value obtained, use the formula to calculate to obtain the effective transmission value CH; S5: Extract the preset effective transmission threshold of the data center, compare the obtained current effective transmission value with the preset effective transmission threshold. If the current effective transmission value is greater than or equal to the preset effective transmission threshold, it indicates that the transmission rate is normal. On the contrary, it indicates that the transmission rate is slow; Obtain and analyze the operating parameters of each transmitter through the data acquisition module. Specifically: Z1: Extract the power consumption of multiple circuit blocks, and then sum the extracted power consumption to obtain the circuit power consumption CV at the transmitting end; Z2: Obtain the positions of the transmitting end and the receiving end, and label them to obtain marked points. Connect the two marked points linearly to obtain the communication distance. Then extract the standard path energy consumption and signal frequency of the data center, and analyze through the obtained communication distance, standard path energy consumption and signal frequency to obtain the transmission base value of the base station, and label the transmission base value of the base station as CX; Z3: Substitute the transmission base value of the base station, the circuit power consumption at the transmitting end and the effective transmission value into the formula to calculate to obtain the transmission power consumption value, where C1, C2 and C3 are preset proportionality coefficients; Z4: Extract the preset transmission power consumption threshold of the data center, compare the transmission power consumption value with the preset transmission power consumption threshold. If the transmission power consumption value is greater than the preset transmission power consumption threshold, it indicates that the transmission power consumption efficiency is normal. On the contrary, it indicates that the transmission power consumption is large, and generate a high-power consumption signal to send to the adaptive optimization module.

[0013] The adaptive optimization module adjusts the transmission power in real time according to the channel conditions and communication distance to reduce the transmission power consumption. The specific acquisition method is as follows: The adaptive optimization module receives a high-power signal, obtains the distance positions of the transmitting end and the receiving end in real time through the cloud server, connects the two points linearly to obtain the transmission distance of the signal, extracts the standard communication distance of the data center. If the actual communication distance is less than the standard communication distance, the cloud server sends a short-distance signal to the transmitting end. The transmitting end receives the short-distance signal and reduces the transmission power of the corresponding antenna. If the actual communication distance is greater than the standard communication distance, the transmission power is increased. This can avoid unnecessary high-power transmission while ensuring communication quality and reduce power consumption.

[0014] Collect the operating conditions of the channel in real time, and select the corresponding modulation method and coding rate according to the real-time condition of the channel. When the channel quality is good, high-order modulation and high coding rate are adopted to improve the transmission efficiency. When the channel quality is poor, switch to low-order modulation and low coding rate, and at the same time reduce the bit error rate and the number of retransmissions to reduce power consumption.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: By optimizing the beamforming parameters, the system can more accurately control the transmitting and receiving directions of signals, reduce unnecessary signal radiation and power waste. After adopting the optimized beamforming, the energy can be concentrated in a specific direction with user terminals, reducing the power output in other directions, thereby significantly reducing the overall power consumption of the base station. For mobile terminal devices, the beamforming optimization with energy efficiency priority can also reduce their transmission power and extend the battery life. When a mobile phone communicates with a base station, through the optimized beamforming, reliable data transmission can be achieved with lower power, reducing the consumption of battery energy. The system can dynamically adjust the beamforming strategy according to the real-time channel conditions and user requirements, enabling more reasonable distribution of energy in different time and space dimensions.

[0016] The wide application of the beamforming optimization system based on energy efficiency priority can significantly reduce energy consumption in the entire communication field, thereby reducing the dependence on traditional energy and the corresponding carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. The following drawings are not deliberately drawn to scale in actual size, and the focus is on showing the gist of the present invention.

[0018] Figure 1 It is a principle block diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts also belong to the scope of protection of the present invention.

[0020] If the present invention is an energy efficiency - priority - based beamforming optimization system, it includes a signal transmission module, a data acquisition module, a signal estimation module, an energy efficiency evaluation module, an adaptive optimization module, a data center, and a cloud server.

[0021] The signal transmission module matches the corresponding antenna units according to the signal and forms a high - gain beam in the target direction. The specific acquisition method is as follows: Build a wireless communication system model, including a base station equipped with multiple antennas and multiple user terminals. Each user terminal has a corresponding antenna. Obtain the signal generated by the base station signal source, marked as the original signal. Pre - process the original signal, including amplification, filtering, and digitization operations, to obtain each digital - processed signal. Compare the obtained signals with adjacent digital - processed signals in sequence. When the value of a digital - processed signal is larger than the values of its adjacent digital - processed signals before and after, mark it as a local peak. When the value of a digital - processed signal is smaller than the values of its adjacent digital - processed signals before and after, mark it as a local valley. The transmitting end distributes the digital - processed signals to be transmitted to each antenna unit of the antenna array in parallel. Each processed signal matches the corresponding antenna unit, and each processed signal is transmitted through the antenna and propagates in the form of electromagnetic waves in space. When the electromagnetic waves emitted by each antenna unit are in - phase superposed in the target direction, the peaks are added to the peaks and the valleys are added to the valleys, increasing the amplitude of the synthesized wave in the same direction and forming a high - gain beam in the target direction.

[0022] The data acquisition module acquires the corresponding parameter values according to each sensor and sends the acquired parameter values to each module for analysis. The specific acquisition method is as follows: Connect the output end of the data acquisition module to the output end of the signal estimation module and connect the output end of the data acquisition module to the input end of the energy efficiency evaluation module. Real - time collect the operating parameters of each transmitter through a voltmeter and obtain the operating parameters of each transmitter in real - time.

[0023] By installing a network traffic monitor at the receiving end, real - time collect the network data volume of beamforming within a specific time, obtain the network data volumes of beamforming within a specific time period, and similarly collect the network data volumes of each beamforming to obtain the network data volumes of each beamforming.

[0024] Extract the known power signals of the antennas in the data center. Input signals with known power to the antennas, and use a vector network analyzer to collect the power of the received signals in real time within a specific time, and obtain the power of each signal of the antennas in real time.

[0025] Connect a spectrum analyzer to the signal receiving port, collect the signal power and noise power of the receiving port in real time, obtain the signal power parameters and noise power parameters, and then collect the signal transmission frequencies of the receiving port in a specific time period in real time to obtain the signal frequency parameters of each signal in the specific time period.

[0026] The channel estimation module analyzes and calculates the actual estimated values of the signals according to the determined signal model. The specific acquisition method is as follows: The base station transmitter sends specific pilot signal values to the receiving user terminal. After the receiving user terminal receives the pilot signal, it performs channel estimation on the pilot signal. Specifically: A1: Determine the channel model, and set the transmitted signal as , after transmission through the channel, the actual received signal There is the following relationship between the transmitted signal and the channel parameters: , where t represents that the value of the signal changes with time, is the channel parameter, is the additive noise; A2: Extract the estimated values of the channel parameters in the data center, marked as , and calculate according to the estimated values of the channel parameters and the transmitted signal using the formula to obtain the estimated received signal ; A3: Calculate through the obtained estimated received signal and the actual received signal, and use the formula to obtain the error value E between the estimated value and the true value; A4: Calculate the actual estimated values of the channel parameters according to the obtained error value, and use the formula =1 to obtain the actual estimated value with the minimum error .

[0027] After the receiving end completes channel estimation during the feedback information generation and transmission phase, it processes and quantifies the actual estimation values to generate corresponding feedback information. The feedback information includes key parameters such as the amplitude of the channel, channel quality indication, and precoding matrix indication. The receiving end sends the feedback information to the transmitting end through the feedback channel. After the transmitting end receives the feedback information from the receiving end, it extracts the historical data in the data center and adjusts the beamforming according to the historical data. The historical data includes the prediction of the channel change trend by the transmitting end, historical channel information, system models, and constraint conditions. The transmitting end recomputes the weighting coefficients of the antenna array through the beamforming algorithm based on the feedback information and historical data, and adjusts the direction, shape, and power distribution of the beam to optimize signal transmission. After the transmitting end completes the beamforming adjustment in the iterative optimization phase, it sends the signal again. After the receiving end receives the new signal, it performs channel estimation and feedback again, and the transmitting end adjusts it according to the feedback information, resulting in a continuously iteratively optimized process. As the number of iterations increases, the beamforming gradually approaches the optimal state, and the system performance also continuously improves.

[0028] The energy efficiency evaluation module analyzes the beamforming signal based on the parameter values of the received data acquisition module. The specific acquisition method is as follows: The output end of the energy efficiency evaluation module is connected to the input end of the adaptive optimization module. It analyzes the signal power parameter, noise power parameter, each signal frequency parameter, and each network data volume at specific time periods of each beamforming obtained through the data acquisition module. Specifically: S1: Based on the obtained signal power parameter and noise power parameter, mark them as DC and DF respectively, and use the formula to obtain the signal-to-noise ratio KC at the receiving end; S2: Based on the obtained network data volumes at specific time periods of each beamforming, extract the duration of the specific time period, and obtain the average data transmission rate TH through mean calculation; S3: Based on the obtained signal frequency parameters at specific time periods, extract the highest frequency and the lowest frequency among the signal frequency parameters, and perform a difference calculation on the highest frequency and the lowest frequency to obtain the channel bandwidth value TY of the beamforming; S4: Through the obtained signal-to-noise ratio, average data transmission rate, and channel bandwidth value, use the formula to calculate to obtain the effective transmission value CH; where L1, L2, and L3 are preset proportionality coefficients; S5: Extract the preset effective transmission threshold in the data center, and compare the obtained current effective transmission value with the preset effective transmission threshold. If the current effective transmission value is greater than or equal to the preset effective transmission threshold, it indicates that the transmission rate is normal; otherwise, it indicates that the transmission rate is slow; Analyze the operating parameters of each transmitter obtained through the data acquisition module. Specifically: Z1: Extract the power consumption of multiple circuit blocks, and then sum up the extracted power consumption to obtain the circuit power consumption CV of the transmitting end; the multiple circuit blocks include the power consumption of circuit blocks such as mixers, frequency synchronizers, analog filters, and digital-to-analog converters.

[0029] Z2: Obtain the positions of the transmitting end and the receiving end, and mark them to get marked points. Connect the two marked points linearly to obtain the communication distance and mark its value as d. Then extract the standard path energy consumption and signal frequency of the data center, mark the value of the signal frequency as HK, and set the value of the path energy consumption as ; Use the formula to obtain the transmission base value CX of the base station, where c is the value of the speed of light, represents the value of the propagation loss at a distance and per unit frequency, where ε1, ε2, and ε3 are all preset proportionality coefficients.

[0030] Z3: Substitute the transmission base value of the base station, the circuit power consumption of the transmitting end, and the effective transmission value into the formula to calculate to obtain the transmission power consumption value, where C1, C2, and C3 are preset proportionality coefficients; Z4: Extract the preset transmission power consumption threshold of the data center, and compare the transmission power consumption value with the preset transmission power consumption threshold. If the transmission power consumption value is greater than the preset transmission power consumption threshold, it means that the transmission power consumption efficiency is normal. On the contrary, it means that the transmission power consumption is large, and a high-power consumption signal is generated and sent to the adaptive optimization module.

[0031] The adaptive optimization module adjusts the transmission power in real time according to the channel conditions and communication distance to reduce the transmission power consumption. The specific acquisition method is as follows: The adaptive optimization module receives the high-power consumption signal, obtains the distance positions of the transmitting end and the receiving end in real time through the cloud server, linearly connects the two points to obtain the transmission distance of the signal, extracts the standard communication distance of the data center. If the actual communication distance is less than the standard communication distance, the cloud server sends a short-distance signal to the transmitting end. The transmitting end receives the short-distance signal and reduces the transmission power of the corresponding antenna. If the actual communication distance is greater than the standard communication distance, the transmission power is increased. This can avoid unnecessary high-power transmission while ensuring communication quality and reduce power consumption.

[0032] Collect the operating conditions of the channel in real time, and select the corresponding modulation method and coding rate according to the real-time status of the channel. When the channel quality is good, adopt high-order modulation and high coding rate to improve the transmission efficiency. When the channel quality is poor, switch to low-order modulation and low coding rate to ensure the reliable transmission of the signal, and at the same time reduce the error rate and the number of retransmissions to reduce power consumption.

[0033] The foregoing is a description of the invention and should not be construed as limiting thereof. Although several exemplary embodiments of the invention have been described, those skilled in the art will readily appreciate that many modifications can be made to the exemplary embodiments without departing from the novel teachings and advantages of the invention. Accordingly, all such modifications are intended to be included within the scope of the invention as defined by the claims. It should be understood that the foregoing is a description of the invention and should not be considered limited to the particular embodiments disclosed, and modifications to the disclosed embodiments as well as other embodiments are intended to be included within the scope of the appended claims. The invention is defined by the claims and their equivalents.

Claims

1. A beamforming optimization system based on energy efficiency priority, including a signal transmission module, a data acquisition module, an energy efficiency evaluation module, an adaptive optimization module, a data center and a cloud server, characterized in that: Also included is a signal estimation module; The channel estimation module receives the user terminal according to the specific pilot signal value sent by the base station transmitter. After the receiving user terminal receives the pilot signal, it performs channel estimation on the pilot signal, specifically: A1: Determine the channel model and set the transmit signal to , after transmission through the channel, the actual received signal , the following relationship exists between the transmitted signal and the channel parameters: , where t means the value of the signal changes with time. is the channel parameter, is additive noise; A2: Extract the channel parameter estimate of the data center, marked as , calculated using the formula based on the channel parameter estimate and the transmitted signal Get the estimated received signal ; A3: Calculate the estimated received signal and the actual received signal using the formula Get the error value E between the estimated value and the true value; A4: Calculate the actual estimated value of the channel parameter based on the obtained error value, using the formula =1 to get the actual estimate with the smallest error ; After the receiving end completes channel estimation in the feedback information generation and transmission stage, the actual estimated value is processed and quantified to generate corresponding feedback information. The receiving end sends the feedback information to the transmitting end through the feedback channel. After receiving the feedback information from the receiving end, the transmitting end extracts the historical data of the data center and adjusts the beamforming according to the historical data. The transmitting end adjusts the direction, shape and power distribution of the beam according to the feedback information and historical data to optimize the signal transmission. In the iterative optimization stage, the transmitting end completes the beamforming adjustment and sends the signal again. After receiving the new signal, the receiving end re-estimates the channel and gives feedback. The transmitting end adjusts it according to the feedback information, thus obtaining a process of continuous iterative optimization.

2. The beamforming optimization system based on energy efficiency priority according to claim 1, characterized in that: The energy efficiency evaluation module analyzes the beamforming signal according to the parameter values ​​of the receiving data acquisition module. The specific method is as follows: The output end of the energy efficiency evaluation module is connected to the input end of the adaptive optimization module. The signal power parameters, noise power parameters, frequency parameters of each signal and the amount of network data in each specific period of beamforming obtained by the data acquisition module are analyzed, specifically: S1: According to the obtained signal power parameter and noise power parameter, they are marked as DC and DF respectively, using the formula Get the signal-to-noise ratio KC of the receiving end; S2: extract the duration of the specific time period according to the obtained network data volume of each beamforming specific time period, and obtain the average data transmission rate TH by average calculation; S3: extracting the highest frequency and the lowest frequency from the signal frequency parameters obtained in the specific time period, performing difference calculation on the highest frequency and the lowest frequency, and obtaining the channel bandwidth value TY of the beamforming; S4: Calculate the signal-to-noise ratio, average data transmission rate and channel bandwidth using the formula Get the effective transmission value CH; S5: extracting a preset effective transmission threshold of the data center, and comparing the obtained current effective transmission value with the preset effective transmission threshold. If the current effective transmission value is greater than or equal to the preset effective transmission threshold, it indicates that the transmission rate is normal. Otherwise, it indicates that the transmission rate is slow. The operating parameters of each transmitter are obtained through the data acquisition module for analysis, specifically: Z1: extract the power consumption of multiple circuit blocks, and then sum the extracted power consumption to obtain the circuit power consumption CV of the transmitter; Z2: Get the location of the transmitter and the location of the receiver, mark them, get the marking point, connect the two marking points with a straight line to get the communication distance, then extract the standard path energy consumption and signal frequency of the data center, analyze the acquired communication distance, standard path energy consumption and signal frequency to get the base value of the base station, and mark the base value of the base station as CX; Z3: Substitute the base station's transmission base value, the transmitter's circuit power consumption, and the effective transmission value into the formula to calculate Obtaining a transmission power consumption value, wherein C1, C2 and C3 are preset proportional coefficients; Z4: Extract the preset transmission power consumption threshold of the data center, and compare the transmission power consumption value with the preset transmission power consumption threshold. If the transmission power consumption value is greater than the preset transmission power consumption threshold, it means that the transmission power consumption efficiency is normal. On the contrary, it means that the transmission power consumption is large, and a high power consumption signal is generated and sent to the adaptive optimization module.

3. The beamforming optimization system based on energy efficiency priority according to claim 1, characterized in that: The adaptive optimization module adjusts the transmission power in real time according to the channel conditions and communication distance to reduce transmission power consumption. The specific methods are as follows: The optimization module receives the high-power consumption signal, obtains the distance between the transmitter and the receiver in real time through the cloud server, connects the two points in a straight line, obtains the transmission distance of the signal, and extracts the standard communication distance of the data center. If the actual communication distance is less than the standard communication distance, the cloud server sends a short-distance signal to the transmitter. The transmitter receives the short-distance signal and reduces the transmission power of the corresponding antenna. If the actual communication distance is greater than the standard communication distance, the transmission power is increased. Real-time acquisition of channel operating conditions, selection of corresponding modulation mode and coding rate according to the real-time status of the channel, use of high-order modulation and high coding rate to improve transmission efficiency when channel quality is good, switch to low-order modulation and low coding rate when channel quality is poor to ensure reliable signal transmission, while reducing bit error rate and retransmission times to reduce power consumption.

4. The beamforming optimization system based on energy efficiency priority according to claim 1, characterized in that: The signal transmission module matches the corresponding antenna unit according to the signal and forms a high-gain beam in the target direction. The specific method is as follows: A wireless communication system model is constructed, including a base station equipped with multiple antennas and multiple user terminals; each user terminal has a corresponding antenna, and a signal generated by a base station signal source is obtained and marked as an original signal. The original signal is preprocessed, and the preprocessing includes amplification, filtering and digitization operations to obtain each digital processing signal. The obtained signal is compared with adjacent digital processing signals in turn. When the value of the digital processing signal is larger than the values ​​of the adjacent digital processing signals before and after it, it is marked as a local peak. When the value of the digital processing signal is smaller than the values ​​of the adjacent digital processing signals before and after it, it is marked as a local trough. The transmitting end distributes the digital processing signal to be transmitted in parallel to each antenna unit of the antenna array, and each processing signal matches the corresponding antenna unit. Each processing signal is transmitted through the antenna and propagates in the space in the form of electromagnetic waves. When the electromagnetic waves emitted by each antenna unit are superimposed in phase in the target direction, the peaks are added and the troughs are added, so that the amplitude of the synthetic wave in the same direction is increased, and a high-gain beam is formed in the target direction.

5. The beamforming optimization system based on energy efficiency priority according to claim 1, characterized in that: The data acquisition module collects the corresponding parameter values ​​according to each sensor and sends the collected parameter values ​​to each module for analysis. The specific method is as follows: The output end of the data acquisition module is connected to the output end of the signal estimation module, and the output end of the data acquisition module is connected to the input end of the energy efficiency evaluation module. The operating parameters of each transmitter are collected in real time through a voltmeter to obtain the operating parameters of each transmitter in real time; By installing a network traffic monitor at the receiving end, the network data volume of beamforming in a specific time period is collected in real time, and the network data volume of each beamforming in the specific time period is obtained. Similarly, the network data volume of each beamforming is collected to obtain the network data volume of each beamforming; Extract the known power signal of the antenna in the data center, input the known power signal to the antenna, collect the power of the received signal in real time within a specific time through the vector network analyzer, and obtain the power of each signal of the antenna in real time; Connect a spectrum analyzer to the signal receiving port, collect the signal power and noise power of the receiving port in real time, obtain the signal power parameters and noise power parameters, and then collect the signal transmission frequency of the receiving port in a specific period of time in real time to obtain the frequency parameters of each signal in the specific period of time.

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