Internet of Things data security communication device and method based on multiple antennas

Abstract

The invention belongs to the technical field of wireless communication, and discloses an Internet of Things data security communication device and method based on multiple antennae, and the method comprises the following steps: employing visible light as a carrier wave, combining a multiple-input-multiple-output (MIMO) technology and a visible light communication technology, and achieving the high-efficiency and secure communication in a loose missile noise environment; a physical layer safety communication mechanism based on visible light is designed, and high confidentiality of communication is ensured; a signal detection method suitable for the MIMO visible light communication system is developed, and interference between users is effectively reduced; the antenna layout design is optimized by adopting a genetic algorithm, and the communication stability of the system under low power is improved. The method is suitable for scenes with high requirements on communication safety and reliability such as the Internet of Things, the communication quality and safety of the industrial Internet of Things can be improved, and reliable communication guarantee is provided for intelligent manufacturing.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a multi-antenna-based Internet of Things data security communication device and method. Background Art

[0002] With the rapid development of 5G mobile communication technology, the limitations of traditional wireless communication systems have become increasingly prominent, mainly reflected in insufficient transmission stability, weak anti-interference ability and security issues. In order to meet these challenges, researchers and developers around the world are working hard to explore safer and more anti-interference communication technologies. In this context, optical wireless communication (OWC) is widely regarded as a new development direction of connection technology due to its low cost and huge bandwidth advantages. In particular, optical communication (VLC), with its high confidentiality and excellent anti-interference performance, has become a hot research topic.

[0003] Visible light communication technology uses the visible spectrum of light to transmit data. This spectrum resource is abundant and not strictly regulated, providing a broad space for communication. Compared with traditional radio communications, VLC systems are not only low-cost, but also low-power, and are a green communication method. In addition, due to the short wavelength of visible light and easy control, VLC technology has demonstrated excellent confidentiality and anti-interference capabilities in indoor applications, and can effectively prevent eavesdropping and data leakage. Therefore, VLC technology shows great application potential in occasions that require highly confidential and stable communications, such as smart homes, medical facilities, and industrial environments.

[0004] In the existing technology, optical wireless communication systems have been widely studied and applied, especially in indoor communication scenarios. Referring to relevant literature such as "Indoor Optical Wireless Systems-A Review", the current wireless spectrum resources are becoming increasingly crowded, and traditional wireless communication systems face problems such as high equipment costs and insufficient technical maturity under high bandwidth requirements. Although optical wireless communication systems have potential advantages in high bit rate transmission, in practical applications, technical bottlenecks such as physical occlusion in indoor environments, light source power limitations, and system costs still restrict their widespread application.

[0005] In view of the problems in the above-mentioned prior art, the present invention proposes an innovative solution. By optimizing the indoor layout design and adopting advanced visible light communication technology, the present invention achieves efficient data transmission under low power consumption. This technical solution not only effectively overcomes the physical shielding problem, improves the communication reliability and signal coverage of the system, but also can reduce the energy consumption and cost of the system to a certain extent. Therefore, the technical solution of the present invention has certain technical progress and practical value, and can effectively meet the market demand for efficient and low-cost indoor communication systems.

[0006] The novel wireless optical physical layer secure communication device and method based on VLC technology proposed in the present invention are suitable for the IoT factory environment. The device and method can expand the coverage of the optical communication system and improve the data transmission efficiency to a certain extent, while ensuring high security and reliability in the communication process. Through the application of the present invention, it is expected to optimize the communication quality and system stability in the industrial environment to meet the demand for efficient and secure communication solutions in the field of intelligent manufacturing. Under the premise of ensuring data security, further wider communication coverage and more efficient information transmission can be achieved. Summary of the invention

[0007] The present invention provides a multi-antenna-based IoT data security communication device and method, which can achieve low-power, high-security and high-reliability data transmission. By adopting modern optimization algorithms, the system can customize the device installation layout suitable for a specific factory environment. The optical communication equipment installed according to this layout method is expected to provide a low-power and high-efficiency communication solution that is both safe and stable.

[0008] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0009] A multi-antenna-based IoT data security communication device includes the following modules:

[0010] (1) Optimization algorithm module;

[0011] (2) Signal detection module.

[0012] Furthermore, the optimization algorithm module is configured to perform the following steps:

[0013] Step 1: Import the channel information, factory scale and indoor environment layout data of the IoT factory;

[0014] Step 2: Generate a new layout plan from multiple possible layout plans by simulating the crossover and mutation mechanism of biological genetics, and perform crossover and mutation genetic operations. Evaluate the effect of each layout plan according to the fitness function, and optimize through multiple iterations until the performance difference between the new layout plan and the previous plan is small, and find the device layout that best suits the factory environment.

[0015] Furthermore, the channel of Step 1 adopts a Lambert channel suitable for indoor visible light communication, which can accurately describe the channel information of indoor visible light communication. The specific formula is:

[0016]

[0017] Among them A PD is the receiving physical area of ​​the photodetector; is the radiation angle relative to the emission axis, ψ i,j and ψ FoV denote the receiving angle relative to the receiver axis and the half angle of the field of view of the photodetector, T s (ψ i,j ) is the gain of the filter, the specific value is determined by the filter used, d i,j is the Euclidean distance between the transmitting antenna i and the receiving antenna j, is the Lambertian radiation intensity, g(ψ k,j ) is the gain of the light concentrator mounted on the photodetector.

[0018] Furthermore, the execution of Step 2 includes the following specific steps:

[0019] Step 2-1: Initialize the population;

[0020] Step 2-2: Select offspring;

[0021] Step 2-3: crossover mutation operation;

[0022] Step 2-4: Iterative optimization.

[0023] Furthermore, the signal detection module is configured to perform the following steps:

[0024] Step 1: Calculate the likelihood function value of all potential transmission signals;

[0025] Step 2: Compare the likelihood function values ​​and select the signal that maximizes the likelihood function as the estimated signal;

[0026] Step 3: includes a signal analysis and processing unit for demodulating and decrypting the received signal.

[0027] Further, the likelihood function is used to calculate likelihood function values ​​of all possible signals based on the received channel information;

[0028] The expression of the likelihood function is:

[0029]

[0030] Among them, s is a vector of Nt×1, representing the transmitted information, H is the estimated channel matrix, which is a matrix of Nr×Nt, and the number of photons emitted by the LED lamp at the transmitting end is n s , the mean number of noise photons received by the receiver is n b , the actual number of photons received is y.

[0031] The present invention also provides a method for secure data communication of the Internet of Things based on multiple antennas, and the specific implementation steps include:

[0032] Step 1: Collect the indoor layout information of the intended installation site, i.e. the building;

[0033] Step 2: Input the parameters of the transmitting device and receiving device of the optical communication system and the obtained indoor layout information of the building into the optimization algorithm to establish the channel basis of the model;

[0034] Step 3: Apply signal detection methods to ensure that the received signal can be demodulated correctly;

[0035] Step 4: Perform the calculation phase of the optimization algorithm, randomly generate multiple layout schemes, use the bit error rate fitness function to iteratively optimize the optical communication MIMO system, traverse the solution space in the entire building, and finally output a solution close to the optimal solution;

[0036] Step 5: Conduct simulation evaluation on the optimized layout and test different performance indicators of the system to ensure that the installed communication system can operate efficiently and stably.

[0037] Furthermore, in Step 3, a maximum likelihood signal detection algorithm adjusted for optical communication is adopted, and the specific process is as follows:

[0038] Step 3-1: Use the estimated channel matrix pre-calculated in the system and the number of photons received in the current cycle to calculate the maximum likelihood function of all possible signals, where the maximum likelihood function is defined as follows:

[0039]

[0040] In the formula, s represents the symbol vector transmitted by the transmitter; y represents the number of photons received; Nr represents the number of antennas at the receiving end; n s represents the number of photons theoretically emitted by the transmitter in one symbol time; H represents the channel matrix; n b represents the number of photons of background noise; y i Represents the number of photons received by the photodetector numbered i in one symbol time;

[0041] Step 3-2: Find the emission symbol that maximizes the likelihood function, mathematically expressed as:

[0042]

[0043] in It is the estimation of the transmitted signal using the MLE algorithm.

[0044] Furthermore, in Step 4, the specific operation process is as follows:

[0045] Step4-1: Initialization of population;

[0046] Step4-2: Select the parent;

[0047] Step 4-3: Cross operation;

[0048] Step 4-4: mutation operation;

[0049] Step 4-5: Iterate and output the optimal solution.

[0050] Furthermore, in Step 5, the optimal transmitter-receiver layout and its communication performance are comprehensively evaluated. The evaluation process includes:

[0051] Step 5-1: Quantification of channel estimation error;

[0052] Step5-2: Impact analysis;

[0053] Step5-3: Simulation and verification.

[0054] Compared with the prior art, the present invention has the following technical advantages:

[0055] 1. Improved system stability and reliability: Genetic algorithms are used to determine the optimal equipment layout, optimize signal coverage, enhance the system's adaptability to environmental changes, and improve the system's stability and reliability to a certain extent.

[0056] 2. Low-power communication technology: The present invention adopts visible light communication technology and uses single-photon detection instead of traditional continuous light sources, which greatly reduces energy consumption. This low-power communication method reduces the operating cost of the system and meets the environmental protection and economic needs of modern industry.

[0057] 3. High communication security: Visible light communication technology greatly enhances the security of information by utilizing its inherent physical properties, such as the indivisibility of single photons and quantum-level information encoding. This technology is difficult to intercept or tamper with, effectively preventing data leakage and security threats.

[0058] 4. Adaptability and flexibility: The methods and techniques of the present invention are highly adaptable and can be adjusted according to specific factory environments and needs, and are suitable for a variety of industrial occasions.

[0059] 5. Comprehensive performance evaluation: Through detailed system performance evaluation, not only the effectiveness of the proposed layout and communication strategy is verified, but also potential improvement space is identified, further improving the stability and reliability of the communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a schematic diagram of the communication system.

[0061] Figure 1 The overall configuration of the wireless optical physical layer secure communication system involved in the present invention is shown. The diagram includes the equipment layout of the transmitter and receiver, as well as the communication link between them. The diagram also details the main components including the light source, photon detector and other related equipment, providing a visual basis for understanding the working principle of the entire communication system.

[0062] Figure 2 It is the optimization algorithm flow chart.

[0063] Figure 2 A detailed flow chart of the optimization algorithm used in the present invention is provided, which shows in detail the steps from population initialization to parent selection, crossover operation, mutation operation, and finally to outputting the optimal solution. DETAILED DESCRIPTION

[0064] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0065] In the embodiment of the present invention, see Figure 1 , 2 , a multi-antenna based Internet of Things data security communication device and method, involving the following aspects.

[0066] 1. System initialization and parameter setting

[0067] At the beginning of the implementation of the present invention, the system is initialized first, including setting the power, center wavelength, half-radiance half-angle and other parameters of the LED at the transmitting end. At the same time, the physical receiving area, filter gain and refractive index of the light collector at the receiving end also need to be preset. The setting of these parameters is to ensure that the system can achieve the best performance in the subsequent signal transmission process.

[0068] 2. Channel simulation and parameter import

[0069] According to the parameters set in step 1, the channel matrix is ​​generated using computer simulation software. On this basis, the system automatically imports the device parameters of the transmitter and receiver, and then generates the corresponding simulation channel matrix. This step is crucial for subsequent signal detection and analysis.

[0070] 3. Signal detection and maximum likelihood calculation

[0071] The received signal is processed using a maximum likelihood signal detection algorithm adapted for visible light communications, which involves using the estimated channel matrix to calculate the maximum likelihood function of all possible signals, thereby effectively decoding the transmitted signal.

[0072] 4. Layout optimization of the transmitter and receiver

[0073] Genetic algorithms are applied to optimize the layout of the transmitter and receiver. Through genetic operations such as population initialization, selection, crossover, and mutation, the system is able to iterate the equipment layout solution that best suits the current factory environment. This step not only improves the security and stability of communication, but also significantly enhances the overall reliability of the system.

[0074] 5. System performance evaluation

[0075] Finally, a comprehensive evaluation of system performance is conducted, especially the impact of channel estimation errors on communication reliability. By simulating different communication environments and error levels, the effect of the optimal layout solution is evaluated and verified, and the channel estimation and processing algorithms are adjusted based on the evaluation results to further optimize communication performance.

[0076] A more detailed description is given below:

[0077] The multi-antenna-based IoT data security communication device of the present invention comprises the following modules:

[0078] (1) An optimization algorithm module is configured to perform the following steps:

[0079] Step 1: Import the channel information, factory scale and indoor environment layout data of the IoT factory to provide the necessary initial input parameters for the optimization algorithm.

[0080] Step 2: Generate the initial device layout distribution using a genetic algorithm. This step generates a new layout scheme from multiple possible layout schemes by simulating the crossover and mutation mechanism of biological genetics. Genetic operations such as crossover and mutation are performed, and the effect of each layout scheme is evaluated according to the fitness function. Through multiple iterations of optimization, until the performance difference between the new layout scheme and the previous scheme is small, it is ensured that the device layout that best suits the factory environment is found.

[0081] (2) A signal detection module configured to perform the following steps:

[0082] Step 1: Calculate the likelihood function value of all potential transmitted signals. This calculation evaluates the probability of various possible signals based on the received and known signal information.

[0083] Step 2: Compare the likelihood function values ​​and select the signal that maximizes the likelihood function as the estimated signal. This step is to select the estimated value that is most likely to represent the true transmitted signal, thereby improving the accuracy of signal detection.

[0084] Step 3: It includes a signal analysis and processing unit, which is specially used to demodulate and decrypt the received signal. This unit ensures the security of the communication process and fights against any possible security threats.

[0085] The channel of Step 1 in Module 1 uses the Lambert channel suitable for indoor visible light communication. This channel can accurately describe the channel information of indoor visible light communication. The specific formula is:

[0086]

[0087] Among them A PD is the receiving physical area of ​​the photodetector; is the radiation angle relative to the emission axis, ψ i,j and ψ FoV T represents the receiving angle relative to the receiver axis and the half angle of the field of view of the photodetector. s (ψ i,j ) is the gain of the filter, the specific value is determined by the filter used, d i,j is the Euclidean distance between the transmitting antenna i and the receiving antenna j, is the Lambertian radiation intensity, g(ψ k,j ) is the gain of the light concentrator mounted on the photodetector.

[0088] The execution of the second step in the optimization algorithm module of the device includes the following specific steps:

[0089] Step 2-1: Initialize the population. This step generates an initial population set, providing a series of basic candidate solutions for the genetic algorithm.

[0090] Step 2-2: Select offspring. This step selects high-quality offspring to continue to reproduce based on the fitness function. The fitness function is evaluated based on the normalized bit error rate of each candidate solution, thereby encouraging candidate solutions with low bit error rates.

[0091] Step 2-3: Crossover and mutation operation. This step performs crossover and mutation operations on candidate solutions, which enables the algorithm to effectively traverse the solution space by increasing genetic diversity.

[0092] Step 2-4: Iterative optimization. Repeat the above steps until the iteration termination condition is met to determine and select the optimal equipment layout solution.

[0093] The device comprises a signal detection module, wherein the likelihood function of the module is based on the received channel information and is used to calculate the likelihood function values ​​of all possible signals.

[0094] The expression of the likelihood function is:

[0095]

[0096] Among them, s is a vector of Nt×1, representing the transmitted information, H is the estimated channel matrix, which is a matrix of Nr×Nt, and the number of photons emitted by the LED lamp at the transmitting end is ns , the mean number of noise photons received by the receiver is n b , the actual number of photons received is y.

[0097] This module analyzes channel information and generates a likelihood function value for each possible signal, thereby effectively identifying and processing secure transmission signals in indoor visible light communication environments.

[0098] The present invention provides a multi-antenna IoT data security communication method, which adopts an optimization process based on a genetic algorithm. The specific implementation steps include:

[0099] Step 1: Collect indoor layout information of the intended installation location, i.e. the building.

[0100] Step 2: Input the parameters of the transmitting and receiving devices of the optical communication system and the obtained indoor layout information of the building into the optimization algorithm to establish the channel basis of the model.

[0101] Step 3: Apply the unique signal detection method of the present invention, which is particularly suitable for visible light communication MIMO systems, to ensure that the received signal can be correctly demodulated.

[0102] Step 4: In the calculation phase of the optimization algorithm, multiple layout schemes are randomly generated. The bit error rate fitness function is used to iteratively optimize the optical communication MIMO system, traverse the solution space in the entire building, and finally output a solution close to the optimal solution.

[0103] Step 5: Conduct simulation evaluation on the optimized layout and test different performance indicators of the system to ensure that the installed communication system can operate efficiently and stably.

[0104] Through this series of steps, the present invention not only improves the communication efficiency of the system, but also ensures a high degree of security and reliability, and is very suitable for application in a high-demand Internet of Things factory environment.

[0105] Specifically, in Step 1 of the plan, it is necessary to know in advance the length, width, and height of the indoor installation site, as well as the overall interior layout.

[0106] In Step 2 of the present invention, in order to more accurately generate the simulation channel matrix, this step involves importing a variety of equipment parameters. These parameters include: the power of the LED at the transmitting end; the central wavelength of the light emitted by the LED; the half-radiant illumination angle of the LED; the background noise power in the factory environment for the central wavelength of the light emitted by the LED; the physical receiving area of ​​the photodetector at the receiving end; the gain of the filter installed on the photodetector; and the refractive index of the light collector on the photodetector.

[0107] In Step 3 of the present invention, a maximum likelihood signal detection algorithm specially adjusted for optical communication is adopted. The specific process is as follows:

[0108] Step 3-1: Use the estimated channel matrix pre-calculated in the system and the number of photons received in the current cycle to calculate the maximum likelihood function of all possible signals. The maximum likelihood function is defined as follows:

[0109]

[0110] In the formula, s represents the symbol vector transmitted by the transmitter; y represents the number of photons received; Nr represents the number of antennas at the receiving end; n s represents the number of photons theoretically emitted by the transmitter in one symbol time; H represents the channel matrix; n b represents the number of photons of background noise; y i Represents the number of photons received by the photodetector numbered i in one symbol time.

[0111] Step 3-2: Find the emission symbol that maximizes the likelihood function, mathematically expressed as:

[0112]

[0113] in It is the estimation of the transmitted signal using the MLE algorithm.

[0114] In Step 4 of the present invention, based on the contents of the first three steps, a genetic algorithm is used to calculate the installation layout of the transmitter and receiver that is most suitable for the factory environment. This step aims to improve the security, stability and reliability of the communication system. By rationally configuring the positions of the transmitter and receiver, the overall performance of the system can be effectively optimized, and the best communication effect can be achieved for a specific factory environment. The specific operation process is as follows:

[0115] Step 4-1: Initialization of the population - including various possible layout schemes of transmitting and receiving equipment.

[0116] Step 4-2: Select the parent generation - This step uses a bit error rate-based fitness function to evaluate the performance of various transmitter and receiver layout solutions. The design of the fitness function is one of the cores of the present invention. The specific fitness function formula is as follows:

[0117] f(x i ,y i ,z i )=exp[α(1-P e,i )]

[0118] Where P e,iRepresents the bit error rate of the i-th possible solution. This formula reflects that the lower the bit error rate of a layout scheme, the higher its fitness value, that is, the better the performance of the layout scheme.

[0119] According to the calculated fitness, the roulette wheel method (also known as the roulette wheel selection method) is used to select feasible solutions with good performance for subsequent crossover and mutation operations. The specific formula of the roulette wheel method is as follows:

[0120]

[0121] The higher the fitness function of a feasible solution, the higher the probability of being selected.

[0122] Step 4-3: Crossover operation - Through the crossover algorithm, the characteristics of the two parent solutions are combined to generate a new device layout solution in the hope of obtaining a better configuration.

[0123] Step 4-4: Mutation operation - introducing small random changes based on the existing solution, which helps to explore uncovered areas in the solution space and increase diversity.

[0124] Step 4-5: Iterate and output the optimal solution - Repeat the above steps until the set number of iterations is reached or the solution improvement stagnates. Finally, the optimal layout solution for the transmitter and receiver in the current factory environment is output.

[0125] In Step 5 of the present invention, the optimal transmitter-receiver layout and its communication performance obtained through the first four steps are comprehensively evaluated. The main focus is on the specific impact of channel estimation error on the reliability of the communication system. This evaluation process includes:

[0126] Step 5-1: Quantification of channel estimation error - First, the channel estimation error is quantitatively analyzed through simulation and actual measurement data. This step involves comparing the deviation between the real-time feedback of the channel and the pre-simulation estimation results, so as to accurately identify the errors that may occur in the channel estimation process.

[0127] Step 5-2: Impact Analysis - Secondly, analyze how the channel estimation error affects the quality and reliability of communication. This includes evaluating the impact on key indicators such as bit error rate, signal interference, and signal loss, and determining the specific impact of the error on these indicators.

[0128] Step 5-3: Simulate and verify - Use simulation tools to simulate the actual impact of channel estimation errors on the communication system. This step can include creating communication scenarios under different error conditions and evaluating the system performance under various channel conditions.

[0129] Through this meticulous evaluation and analysis, the present invention is not only able to verify the effectiveness of the proposed layout and communication strategy, but also to identify potential room for improvement and further improve the stability and reliability of the communication system in an actual factory environment.

[0130] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-antenna based Internet of Things data security communication device, characterized in that: Includes the following modules: (1) Optimization algorithm module; (2) Signal detection module.

2. The multi-antenna-based IoT data security communication device according to claim 1, characterized in that: The optimization algorithm module is configured to perform the following steps: Step 1: Import the channel information, factory scale and indoor environment layout data of the IoT factory; Step 2: Generate a new layout plan from multiple possible layout plans by simulating the crossover and mutation mechanism of biological genetics, and perform crossover and mutation genetic operations. Evaluate the effect of each layout plan according to the fitness function, and optimize through multiple iterations until the performance difference between the new layout plan and the previous plan is small, and find the device layout that best suits the factory environment.

3. The multi-antenna-based IoT data security communication device according to claim 2, characterized in that: The channel of Step 1 adopts the Lambert channel suitable for indoor visible light communication. This channel can accurately describe the channel information of indoor visible light communication. The specific formula is: Among them A PD is the receiving physical area of ​​the photodetector; is the radiation angle relative to the emission axis, ψ i,j and ψ FoV denote the receiving angle relative to the receiver axis and the half angle of the field of view of the photodetector, T s (ψ i,j ) is the gain of the filter, the specific value is determined by the filter used, d i,j is the Euclidean distance between the transmitting antenna i and the receiving antenna j, is the Lambertian radiation intensity, g(ψ k,j ) is the gain of the light concentrator mounted on the photodetector.

4. The multi-antenna-based IoT data security communication device according to claim 2, characterized in that: The execution of Step 2 includes the following specific steps: Step 2-1: Initialize the population; Step 2-2: Select offspring; Step 2-3: crossover mutation operation; Step 2-4: Iterative optimization.

5. The multi-antenna-based IoT data security communication device according to claim 1, characterized in that: The signal detection module is configured to perform the following steps: Step 1: Calculate the likelihood function value of all potential transmission signals; Step 2: Compare the likelihood function values ​​and select the signal that maximizes the likelihood function as the estimated signal; Step 3: includes a signal analysis and processing unit for demodulating and decrypting the received signal.

6. The multi-antenna-based IoT data security communication device according to claim 5, characterized in that: The likelihood function is based on the received channel information and is used to calculate the likelihood function values ​​of all possible signals; The expression of the likelihood function is: Among them, s is a vector of Nt×1, representing the transmitted information, H is the estimated channel matrix, which is a matrix of Nr×Nt, and the number of photons emitted by the LED lamp at the transmitting end is n s , the mean number of noise photons received by the receiver is n b , the actual number of photons received is y.

7. A method for secure data communication of the Internet of Things based on multiple antennas using the device according to any one of claims 1 to 6, characterized in that: The specific implementation steps include: Step 1: Collect the indoor layout information of the intended installation site, i.e. the building; Step 2: Input the parameters of the transmitting device and receiving device of the optical communication system and the obtained indoor layout information of the building into the optimization algorithm to establish the channel basis of the model; Step 3: Apply signal detection methods to ensure that the received signal can be demodulated correctly; Step 4: Perform the calculation phase of the optimization algorithm, randomly generate multiple layout schemes, use the bit error rate fitness function to iteratively optimize the optical communication MIMO system, traverse the solution space in the entire building, and finally output a solution close to the optimal solution; Step 5: Conduct simulation evaluation on the optimized layout and test different performance indicators of the system to ensure that the installed communication system can operate efficiently and stably.

8. The method for secure data communication of the Internet of Things based on multiple antennas according to claim 7, characterized in that: In Step 3, the maximum likelihood signal detection algorithm adjusted for optical communication is used. The specific process is as follows: Step 3-1: Use the estimated channel matrix pre-calculated in the system and the number of photons received in the current cycle to calculate the maximum likelihood function of all possible signals, where the maximum likelihood function is defined as follows: In the formula, s represents the symbol vector transmitted by the transmitter; y represents the number of photons received; Nr represents the number of antennas at the receiving end; n s represents the number of photons theoretically emitted by the transmitter in one symbol time; H represents the channel matrix; n b represents the number of photons of background noise; y i Represents the number of photons received by the photodetector numbered i in one symbol time; Step 3-2: Find the emission symbol that maximizes the likelihood function, mathematically expressed as: in It is the estimation of the transmitted signal using the MLE algorithm.

9. The method for secure data communication of the Internet of Things based on multiple antennas according to claim 7, characterized in that: In Step 4, the specific operation process is as follows: Step4-1: Initialization of population; Step4-2: Select the parent; Step 4-3: Cross operation; Step 4-4: mutation operation; Step 4-5: Iterate and output the optimal solution.

10. The method for secure data communication of the Internet of Things based on multiple antennas according to claim 7, characterized in that: In Step 5, the optimal transmitter-receiver layout and its communication performance are comprehensively evaluated. This evaluation process includes: Step 5-1: Quantification of channel estimation error; Step5-2: Impact analysis; Step5-3: Simulation and verification.

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