A smart metering communication channel modeling method for a basement environment

Abstract

The application relates to a smart metering communication channel modeling method for a basement environment, which comprises the following steps: obtaining smart metering communication system channel information through a joint ray tracing method and a channel measurement method; obtaining channel parameters of multipath propagation based on channel data, and establishing a corresponding wireless channel model; obtaining typical channel characteristics of the smart metering communication system based on the established wireless channel model; and realizing system optimization and network deployment in the smart metering system transmission by analyzing the typical channel characteristics. The application provides a reference for the deployment and optimization of the receiving and sending ends in the smart metering communication by analyzing the channel propagation characteristics and adjusting the sending end position to optimize signal transmission.

Description

TECHNICAL FIELD

[0001] The application relates to a smart metering communication channel modeling method for a basement environment and belongs to the field of new-generation electronic information technology. BACKGROUND

[0002] New-generation smart grid transmission will adopt a mode of integration of wired communication and wireless communication to realize communication of power user power consumption information aggregation, transmission and interaction, and further realize functions such as automatic acquisition of power consumption information, measurement anomaly detection and power consumption analysis. Considering the complex and changeable communication environment between a transmitter (Tx) and a receiver (Rx), the signal of a smart metering system is prone to unstable transmission. Therefore, in order to better deploy the transmitter and the receiver and further optimize the power transmission grid, it is urgent to accurately model and analyze the corresponding channel. This will help to understand the possible obstacles and attenuation of the signal in the propagation process, so as to take corresponding technical means to enhance the stability and reliability of the system. Such modeling can provide a more accurate basis for the design and optimization of the system and provide guidance for the implementation of future smart metering power transmission systems.

[0003] In the field of channel measurement and modeling of smart metering communication systems, both domestic and foreign have carried out work. Masood et al. gave a channel model for the smart metering communication system under three conditions of low voltage, medium voltage and high voltage. The performances of various channel models are compared, and the related channel characteristics are evaluated. Panchascharam et al. carried out wired communication channel modeling and noise analysis. Padhan et al. analyzed the three-hop hybrid wired communication channel in the wide area network of the smart metering system. For wireless transmission, Li Sichao et al. carried out wideband micro-power channel measurement. Based on the collected channel data, the channel characteristics of large-scale fading (LSF) and small-scale fading (SSF) are analyzed, and the influence of different positions of Tx and Rx on the channel characteristics is studied. Aloui et al. evaluated the wireless communication and proved that wireless transmission is the preferred way of smart meter communication under the condition of high signal-to-noise ratio. At the same time, smart grid wireless transmission is widely used due to its own advantages, such as the basement scene, to provide low-cost, flexible and high-reliable information transmission for power users.

[0004] The typical basement scene is rarely studied as a frequently deployed communication environment. Unlike other application scenarios, the basement communication scene has the characteristics of large shadow attenuation, poor penetration effect and shielding influence. It is well known that the development, verification and evaluation of wireless communication networks rely on accurate channel models. Corresponding channel modeling and characterization that can describe the unique characteristics of the scene are crucial for future smart metering systems. Therefore, based on the above research and background, the present application proposes an accurate and effective smart metering communication channel modeling method for basement environment. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a smart metering communication channel modeling method for basement environment;

[0006] The present application applies channel modeling to a smart metering communication for basement environment, and adopts a joint ray tracing method and channel measurement method. By placing the transmitting end and the receiving end at different positions, the channel parameters of multipath propagation are obtained, and a corresponding wireless channel model is established. Based on the proposed model, the channel characteristics of some typical smart metering systems are studied, and a channel characteristic analysis method and theory are established. Through analysis of the channel characteristic results, system optimization and network deployment in the transmission of the smart metering system are realized. The present application can provide an important reference for the deployment and optimization of the smart metering transmitting and receiving end position in the typical smart grid application scenario, especially in the basement scenario.

[0007] Terminology explanation:

[0008] GNU Radio: GNU Radio is a software that combines hardware devices with a rich set of signal modules such as filters, modems, Fourier transformers, etc. It builds a communication system through software, defines the transmission and reception of radio waves. GNU Radio combines external hardware devices and uses UHD for driving, and realizes the transmission and reception of probe signals in measurement based on the constructed communication flow graph.

[0009] Ray tracing method: Ray tracing is a widely used simulation method in the field of wireless communication, which is used to simulate the propagation of electromagnetic waves in complex environments. This method traces the rays of electromagnetic waves, considering reflection, refraction, diffraction and other phenomena, to simulate the signal propagation in the real world. In simulation, rays usually start from wireless transmitting antennas. These rays can propagate in different directions according to the principles of geometric optics. Each ray interacts with objects in the scene, affecting its propagation path. The advantage of ray tracing simulation method is its high simulation accuracy for complex scenes and multipath effects, making it a powerful tool for wireless communication system design and optimization.

[0010] The technical scheme of the present application is:

[0011] The basement environment-oriented intelligent meter reading communication channel modeling method comprises:

[0012] The first step is to obtain the intelligent meter reading communication system channel data by a joint ray tracing method and a channel measurement method;

[0013] The second step is to obtain the channel parameters of multipath propagation based on the channel data, and establish a corresponding wireless channel model;

[0014] The third step is to obtain the typical channel characteristics of the intelligent meter reading communication system based on the established wireless channel model;

[0015] The fourth step is to realize the system optimization and network deployment in the intelligent meter reading system transmission by analyzing the typical channel characteristics.

[0016] According to the application, the wireless channel measurement system based on USRP (Universal Software Radio Peripheral) is used to obtain the intelligent meter reading communication system channel data.

[0017] According to the application, the ray tracing method is used to obtain the intelligent meter reading communication system channel data.

[0018] According to the application, the channel parameters of multipath propagation are obtained based on the channel data, and the channel parameters comprise:

[0019] The transmission signal adopts a pseudo-noise (PN) sequence signal; the response of the direct connection calibration elimination device, the transmission and the receiving side cable is eliminated to obtain the calibration signal y th (t), that is:

[0020] y th (t) = s(t) * m(t)

[0021] Wherein, * represents convolution operation, s(t) represents the transmission signal, and m(t) represents the response of the intelligent meter reading communication system and the cable;

[0022] The calibration signal y th (t) is transmitted through a specific environment, and the probe signal received by the wireless channel is represented as y rx (t), that is:

[0023] y rx (t) = s(t) * m(t) * γ(t) = y th (t) * γ(t)

[0024] Wherein, γ(t) represents the channel impulse response;

[0025] The frequency domain response is obtained by fast Fourier transform (FFT) of the time domain response, and the calibrated channel impulse response γ(t) is obtained from inverse fast Fourier transform (IFFT) of the frequency domain, that is:

[0026]

[0027] Y rx (f) and Y th (f) are the frequency domain responses of the calibrated signal y th (t) and the received signal y rx (t), respectively;

[0028] Based on γ(t), the channel parameters of channel multipath propagation are obtained by using a peak detection algorithm, including:

[0029] The maximum received power P max of the amplitude value of γ(t) and the average noise floor N aver of the received signal are calculated, both in dB;

[0030] The power value (dB) of each receiving point is calculated, the noise reduction processing is completed, the peak signal is taken down by 30-40 dB, and the average noise floor is taken up by 5-10 dB, as two threshold values, and the maximum value of the two threshold values is taken as the signal threshold value, and the received signal not within the signal threshold value range is discarded;

[0031] According to the application, a corresponding wireless channel model is established, including:

[0032] By using the joint ray tracing method and the channel measurement method, the channel parameters including time delay, power and angle are obtained, a corresponding wireless channel model is established, and the channel impulse response (CIR) under different positions is obtained, which is expressed as:

[0033]

[0034] Wherein, τ i (t), α i (t) and φ i (t) represent the delay, amplitude and phase of the i-th path between the transmitting end and the receiving end, and L(t) represents the total number of multipaths; h(t, τ) represents the CIR in the time delay domain, and τ represents the time delay variable.

[0035] According to the application, based on the established wireless channel model, the typical channel characteristics of the intelligent meter reading communication system are obtained, including:

[0036] The typical channel characteristics of the intelligent meter reading communication system include power delay profile (PDP), power angle profile (PAP), root mean square delay spread, path loss and channel capacity.

[0037] Typical channel characteristics of the smart metering communication system include the channel characteristics of the typical smart metering system in different locations of the same basement, different basements, different floors.

[0038] According to the application, the propagation characteristics of the metering system in different locations of the same basement are modeled based on the obtained channel data of the smart metering communication system, and the modeling includes:

[0039] Typical channel characteristics of the smart metering communication system are obtained according to the obtained CIR, and the obtaining includes:

[0040] According to the obtained CIR, a power delay spectrum Ψ(t,τ) is obtained to describe the power variation along the delay axis, and the specific expression is as follows:

[0041]

[0042] Similarly, a power angle spectrum Υ(t,θ) is obtained to describe the power variation along the angle axis, and the specific expression is as follows:

[0043]

[0044] h(t,θ) represents the CIR in the angle domain, and θ represents the angle variable;

[0045] The received power κ at each receiving end is calculated by superimposing the received power of each path, and is expressed as:

[0046]

[0047] wherein L is the number of multipath components in channel propagation, P i is the received power of the i-th path;

[0048] The path loss is defined as the received power minus the transmitted power minus the antenna gain; the floating intercept (FI) model fits the path loss data in dB is expressed as:

[0049]

[0050] wherein n is the path loss exponent (PLE), ξ is the intercept, d is the three-dimensional distance from the transmitting end to the receiving end, and X s is the shadow fading; is the path loss variable with the distance d as the parameter;

[0051] The root mean square delay spread σ τ is expressed as:

[0052]

[0053] where τ i and P(τ i ) are the delay and power of the i-th multipath component (MPC) ray, respectively.

[0054] Channel capacity C refers to the maximum amount of data transmitted on each time and frequency resource; it is expressed as:

[0055]

[0056] where ρ is the signal-to-noise ratio, and C is the unit bps / Hz.

[0057] After obtaining the typical channel characteristics of the intelligent meter reading communication system at different positions in the same basement, a certain optimal position of the basement corresponding to the maximum received power, the minimum root mean square delay spread, the maximum channel capacity, and the minimum path loss is selected.

[0058] According to the preferred embodiment of the present application, the propagation characteristics of different basements of the same building are modeled based on the obtained channel data of the intelligent meter reading communication system, including:

[0059] After obtaining the typical channel characteristics of the intelligent meter reading communication system at different basements of the same building, a basement corresponding to the maximum received power, the minimum root mean square delay spread, the maximum channel capacity, and the minimum path loss is selected.

[0060] According to the preferred embodiment of the present application, the propagation characteristics of different floors at the same horizontal position are modeled based on the obtained channel data of the intelligent meter reading communication system, including:

[0061] After obtaining the typical channel characteristics of the intelligent meter reading communication system at different floors at the same horizontal position, a floor corresponding to the maximum received power, the minimum root mean square delay spread, the maximum channel capacity, and the minimum path loss is selected.

[0062] The present application has the following advantages:

[0063] 1. The present application constructs an intelligent meter reading communication network system for a basement environment. The intelligent meter reading communication network data is obtained by combining ray tracing and channel measurement methods, and the channel multipath parameters, including delay, angle, and power, are obtained. Based on the collected channel data, the typical channel characteristics are modeled and analyzed. The typical channel characteristics, including power delay distribution, power angle distribution, delay spread, angle spread, and channel capacity, are calculated and analyzed.

[0064] 2. According to the collected channel data, the application models and analyzes typical channel characteristics. The channel propagation characteristics such as received power, root mean square delay spread, path loss, channel capacity, power delay profile, and power angle profile of different positions in the same basement, different basements in the same building, and different floors in the same building are analyzed and compared. By analyzing the channel propagation characteristics, the sending end position is adjusted to optimize signal transmission, which provides a reference for the deployment and optimization of the receiving and sending ends in smart metering communication.

[0065] 3. The application establishes a smart metering communication channel model for the corresponding basement environment by combining simulation and measurement data for analysis. The application solves the deployment problem of the receiving and sending ends of the smart metering system and gives comparative results of the corresponding indicators. The application can provide an important reference for the deployment and optimization of the receiving and sending ends of smart metering in typical application scenarios, especially in community scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0066] Figure 1 is a schematic diagram of different Tx positions in the same basement;

[0067] Figure 2 is a schematic diagram of the cumulative distribution function of the received power of different Tx positions in the same basement;

[0068] Figure 3 is a schematic diagram of the cumulative distribution function of the channel capacity of Tx placed in different basements;

[0069] Figure 4 is a schematic diagram of the time-varying delay power spectrum of Tx placed in the basement;

[0070] Figure 5 is a schematic diagram of the time-varying angle power spectrum of Tx placed in the basement. DETAILED DESCRIPTION

[0071] The application is further limited by the description and examples in the specification and the accompanying drawings, but is not limited thereto.

[0072] Example 1

[0073] A smart metering communication channel modeling method for a basement environment includes:

[0074] Step 1: Obtain smart metering communication system channel information by combining ray tracing and channel measurement methods;

[0075] Step 2: Based on the channel data, obtain the channel parameters of multipath propagation and establish a corresponding wireless channel model;

[0076] Step 3: Based on the established wireless channel model, obtain typical channel characteristics of the smart metering communication system;

[0077] Fourth step: through the analysis of typical channel characteristics, the system optimization and network deployment in the intelligent meter reading system transmission are realized.

[0078] The application applies channel modeling to an intelligent meter reading communication facing a basement environment, adopts a joint ray tracing method and a channel measurement method. By placing a transmitting end and a receiving end at different positions, the application can provide an important reference for the deployment and optimization of the intelligent meter reading transmitting and receiving end positions in typical smart grid application scenarios, especially in a basement scenario.

[0079] Embodiment 2

[0080] The basement environment-oriented intelligent meter reading communication channel modeling method according to Embodiment 1 is different in that:

[0081] A wireless channel measurement system based on USRP (Universal Software Radio Peripheral) is adopted to obtain intelligent meter reading communication system channel data.

[0082] According to measurement requirements, a lightweight and portable wireless channel measurement system is independently built. The wireless channel measurement system based on USRP is a system for radio signal processing using software-defined radio technology. The USRP hardware device and the GNU Radio software radio (Software Defined Radio, SDR) on the PC side are used to process radio signals, and flexible radio signal transmission, reception and processing can be realized. The following is a detailed description and acquisition process of the wireless channel measurement system:

[0083] First, the wireless channel measurement system based on USRP is built. The wireless channel measurement system includes a transmitting end and a receiving end, and specifically as follows:

[0084] The transmitting end includes USRP, an antenna, a portable power supply and a microcomputer; the signal transmission platform uses USRP to transmit and modulate the transmitted signal, such as a pseudo-noise PN sequence signal. After the transmitted signal is transmitted through the wireless channel, the signal receiving platform completes the real-time reception and saving of the detected signal; the USRP X300 of the ettus company is used as the core device for signal transmission, and is connected with the external antenna through the transmitting port. Among them, the antenna needs to be matched with the measurement frequency band. The portable power supply provides power for the USRP and other devices. The computer host runs GNU Radio, which is used to build and control the signal transmission process.

[0085] Receiving end: including USRP, antenna, computer host, display, outdoor power supply and transmission line; using USRP to receive signals, and storing signals in computer host; high-power outdoor power supply is responsible for the power supply of computer host, display and USRP. The signal receiving platform is connected with the signal transmitting platform in real time. USRP X310 is used as the core equipment of signal receiving, and the receiving port is connected with the external antenna. Among them, the antenna needs to be matched with the measurement frequency band. The computer host runs GNU Radio, which is used to build and control the signal receiving process, store and process the received data, and monitor the signal receiving situation in real time. The outdoor power supply supplies power for high-power equipment such as computer host, display and USRP. In addition, the clock of the sending end and the receiving end is synchronized to avoid phase error in signal processing.

[0086] Secondly, channel measurement activities are carried out and channel data is obtained, as follows:

[0087] Sending end: GNU Radio is used to build signal flow chart, set signal type (such as pseudo-noise PN sequence signal), sampling rate, center frequency, transmission gain and other parameters. The modulated signal is transmitted through USRP.

[0088] Receiving end: GNU Radio Companion is used on computer host to build signal receiving flow chart, set parameters matched with sending end. Wireless signal is received through USRP, and data is stored in computer host. Finally, the received data (such as pseudo-noise PN sequence signal) is properly post-processed, such as denoising and demodulation, to extract useful channel information.

[0089] After the hardware equipment of the wireless channel measurement system is built, GNU Radio is used to build the sending and receiving flow charts of the probe signal at the sending end and the receiving end respectively, set the corresponding measurement parameters, and realize the sending and receiving of the probe signal. During measurement, the measurement parameters are set according to the measurement requirements, such as sampling rate, center frequency, transmission gain. In order to ensure the effective coverage range of the probe signal and ensure the effective extraction of the probe signal at the receiving end, the transmission gain can be set to adjust the range of 0-31.5dB. During the measurement activity, whether the received signal is normally received is judged by observing the time domain waveform of the received signal of the signal receiving platform. The measurement data is saved in the folder preset in the hardware equipment after being processed by USRP internally.

[0090] Ray tracing method is used to obtain channel data of intelligent meter reading communication system, including:

[0091] The scene is reconstructed by using ray tracing software to obtain relevant scene map and real structure diagram; and the size, material and electromagnetic parameters of all objects in the scene are obtained;

[0092] Wireless Insite is a set of complete simulation software launched by REMCOM company, which uses ray tracing simulation algorithm to model complex scenes. At the same time, the software has powerful functions and can meet the needs of scene reconstruction.

[0093] In scene reconstruction, the electromagnetic parameters of building materials, reflection times, center frequency, bandwidth, antenna type and polarization mode are set to simulate real signal propagation, and then wireless channel data such as received power, amplitude, time delay and angle are obtained.

[0094] The more detailed process is as follows:

[0095] First, collect the geographic information of the deployment area of the smart metering system, including the data of buildings, terrain, vegetation, etc. Based on the geographic information, a three-dimensional model is established, which conforms to the real communication environment.

[0096] Then, set the material properties, assign appropriate electromagnetic properties such as dielectric constant and conductivity to different materials in the environment model (such as concrete, glass, ground, wall, vegetation, trees, etc.).

[0097] Finally, complete the ray emission and tracking. Define the emission source position and receiving point position of the smart metering device in the model. From the emission source, a group of rays are emitted to simulate the propagation of wireless signals. Finally, the propagation path of the rays in the environment is calculated, considering reflection, refraction, scattering and diffraction, etc. The multipath propagation signal is obtained at the receiving end.

[0098] The advantages of combining ray tracing method and channel measurement method for obtaining channel data of smart metering communication system are that they can provide detailed and accurate information about wireless signal propagation. Smart metering system usually involves a large number of devices deployed in complex environments, such as homes, building interiors or urban areas, and the signal propagation in these environments is affected by factors such as multipath effect, obstacle shielding and interference. Channel measurement method and ray tracing complement each other. By jointly using ray tracing and channel measurement method, comprehensive and accurate channel information can be obtained.

[0099] Based on the channel data, the channel parameters of multipath propagation are obtained, including:

[0100] The transmitted signal uses a pseudo-noise (PN) sequence signal; although the pseudo-noise (PN) sequence signal has certain anti-interference performance, in order to better remove the interference of hardware devices and accurately obtain the propagation channel information, the present application further eliminates the response of the device, the transmission and reception side cable through direct connection calibration, and obtains the calibration signal y th(t), that is:

[0101] y th (t) = s(t) * m(t)

[0102] Wherein, * represents convolution operation, s(t) represents transmitting signal, and m(t) represents response of smart meter communication system and cable;

[0103] Calibration signal y th (t) is transmitted through specific environment, and the received probe signal of wireless channel is represented as y rx (t), that is:

[0104] y rx (t) = s(t) * m(t) * γ(t) = y th (t) * γ(t)

[0105] Wherein, γ(t) represents channel impulse response;

[0106] The frequency domain response is obtained through fast Fourier transform (FFT) of time domain response, and the calibrated channel impulse response γ(t) is obtained from inverse fast Fourier transform (IFFT) of frequency domain, that is:

[0107]

[0108] Wherein, Y rx (f) and Y th (f) are frequency domain responses of calibration signal y th (t) and received signal y rx (t) respectively;

[0109] Based on γ(t), the peak detection algorithm is adopted to obtain channel parameters of channel multipath propagation; including:

[0110] The maximum received power P max of amplitude value of γ(t) is calculated, and the average noise floor N aver of received signal is calculated, and the units are both dB;

[0111] The power value (dB) of each receiving point is calculated, the noise reduction processing is completed, the peak signal is taken down by 30-40 dB, the average noise floor is taken up by 5-10 dB, as two threshold values, the maximum value of two threshold values is taken as a signal threshold value, and the received signal not in the signal threshold value range is discarded;

[0112] Thus, the channel parameters of multipath propagation based on channel measurement can be obtained.

[0113] Based on the ray tracing method, the channel parameters are obtained: after the ray tracing is completed, a txt or p2m ending document can be obtained, which directly gives the channel related parameters of multipath propagation. Using matlab or python language to read the document and arrange the format, the channel parameters of multipath propagation based on ray tracing can be obtained.

[0114] The corresponding wireless channel model is established, including:

[0115] By combining the ray tracing method and the channel measurement method, the channel parameters including time delay, power and angle are obtained, and the corresponding wireless channel model is established to obtain the channel impulse response CIR (channel impulse response, CIR) under different positions, which is expressed as:

[0116]

[0117] Where τ i (t), α i (t) and φ i (t) represent the delay, amplitude and phase of the i-th path between the transmitting end and the receiving end, and L(t) represents the total number of multipaths; note that these parameters vary with time. h(t, τ) represents the CIR in the time delay domain, and τ represents the time delay variable.

[0118] Based on the established wireless channel model, the typical channel characteristics of the smart metering communication system are obtained, including:

[0119] The typical channel characteristics of the smart metering communication system include power delay profile PDP, power angle profile PAP, root mean square delay spread, path loss and channel capacity.

[0120] The typical channel characteristics of the smart metering communication system include the typical channel characteristics of the smart metering system in the same basement, different basements and different floors.

[0121] Based on the obtained channel data of the smart metering communication system, the propagation characteristics of the metering system in the same basement are modeled, including:

[0122] Placing smart metering systems at different positions in the same basement will have different effects on the entire communication environment. It is necessary to deeply study the influence of different positions in the same basement on the channel. The structure inside the basement is complex and diverse, which may include support columns, walls, partitions and other structures. These elements will cause scattering, attenuation and reflection of signals, thus forming complex propagation paths. When studying different positions in the same basement, these factors need to be considered comprehensively, and the propagation characteristics of each position need to be modeled. This helps to optimize the layout of the smart metering system to improve the performance and reliability of the smart metering system.

[0123] Explore the impact of different positions,

[0124] According to the CIR obtained, the typical channel characteristics of the intelligent meter reading communication system are obtained; including:

[0125] According to the obtained CIR, the power delay spectrum Ψ(t,τ) is obtained, which is used to describe the power change along the delay axis, and the specific expression is as follows:

[0126]

[0127] Similarly, the power angle spectrum Υ(t,θ) is obtained, which is used to describe the power change along the angle axis, and the specific expression is as follows:

[0128]

[0129] h(t,θ) represents the CIR in the angle domain, and θ represents the angle variable;

[0130] Due to the difference between different paths and the delay dispersion of the signal, the power delay spectrum may exhibit different characteristics at different positions in the same basement. Different clusters of birth and death phenomena are observed at different locations, and these locations have different effects on the channel. Specifically, compared to positions close to the inner wall, positions close to the window often exhibit less delay dispersion. This is because positions close to the window often have a more direct path to the outside, resulting in fewer obstacles and reflections.

[0131] The signal from the sending end is reflected multiple times by the scatterer and reaches the receiving end. The received power of each path can be tracked. The received power κ at each receiving end is calculated by superimposing the received power of each path, which is represented as:

[0132]

[0133] Where L is the number of multipath components in channel propagation, P i is the received power of the i-th path;

[0134] In the communication scenario of the intelligent meter reading system in the basement, the sending end can be deployed at different positions in the same basement, and the receiving end is set outdoors. The pros and cons of the sending end position are analyzed by analyzing the value of the cumulative distribution function (CDF) of the received power when the proportion is 80%. The sending end near the window position usually has the strongest received power. Windows are usually made of thin glass, while interior walls can be thicker and have different compositions. Therefore, the thinness of the glass and its low signal attenuation characteristics enable the signal to easily pass through the window, making it easier for the signal to propagate outdoors. When the signal is transmitted from a position close to the interior wall, it is absorbed, attenuated, or reflected by the wall material, resulting in a decrease in received power.

[0135] Path loss is defined as the received power minus the transmitted power minus the antenna gain; it is an important channel characteristic in communication system design. In addition, the floating intercept (FI) model fits the path loss data in dB is expressed as:

[0136]

[0137] where n is the path loss exponent (PLE), ξ is the intercept, d is the three-dimensional distance from the sending end to the receiving end in meters; X s is shadow fading; is the path loss variable with distance d as the parameter;

[0138] Root mean square delay spread is one of the typical channel characteristics used to represent the delay of multipath effect. It can be obtained by calculating the square root of the second order central moment, and the root mean square delay spread σ τ is expressed as:

[0139]

[0140] where τ i and P(τ i ) are the delay and power of the i-th multipath component (MPC) ray, respectively;

[0141] Channel capacity C refers to the maximum amount of data transmitted per time and frequency resource; it has typical practical significance in intelligent meter reading system communication, which can be expressed as:

[0142]

[0143] where ρ is the signal-to-noise ratio, and C is the unit bps / Hz;

[0144] The merits of the sending end position are analyzed by analyzing the value of the cumulative distribution function of the channel capacity at 80%. Generally, the channel capacity of the near-window position is the strongest. In the basement communication, the window position is closer to the outdoor environment than other indoor positions, and there are relatively fewer obstacles in the radio propagation path. The window material is usually glass, which has small attenuation. In other positions, obstacles will cause scattering, refraction and diffraction, thereby weakening the signal and reducing the channel capacity.

[0145] After obtaining the typical channel characteristics of the intelligent meter reading communication system at different positions in the same basement, the corresponding best position of the basement is selected, which has the most concentrated power delay spectrum, the most concentrated power angle spectrum, the maximum received power, the minimum root mean square delay spread, the maximum channel capacity and the minimum path loss.

[0146] The power delay spectrum can well reflect the change of power with time delay in the transmission process. In the present application, the merits are mainly determined by observing the power delay spectrum. If the power delay spectrum is more concentrated, the effect is better. If the power delay spectrum is more dispersed, it is greatly affected by the surrounding environment, the time delay domain multipath is rich, and it is easy to produce error code phenomenon in the process of communication transmission.

[0147] The height of the received power directly affects the quality and reliability of the communication. The higher the received power, the better the signal-to-noise ratio. Higher signal-to-noise ratio means that the signal is clearer and easier to distinguish from the background noise, thereby reducing the error rate and improving the communication reliability. Higher received power can maintain sufficient strength to ensure the communication quality. In addition, in the wireless communication environment, the signal will be disturbed by other electronic equipment. Higher received power can improve the anti-interference ability of the signal, so that the communication system is more stable.

[0148] In the communication system, the root mean square delay spread measures the time delay spread of multipath signals arriving at the receiver. Lower root mean square delay spread means that the time delay difference of multipath signals arriving at the receiver is smaller, which is usually beneficial to the communication system. Lower root mean square delay spread means that the signal is more concentrated in the time domain, which can reduce the inter-symbol interference. Because the signal experiences less time delay spread in the transmission process, the duration of each symbol overlaps less, so that the receiver can more easily correctly identify and decode each symbol. In addition, when the root mean square delay spread is low, the design of the receiver can be simpler, and a complex equalizer is not needed to compensate for the multipath effect.

[0149] A higher channel capacity is considered better because channel capacity is directly related to the data transmission rate and communication quality that the system can support. A high channel capacity means that the system can transmit more data in a unit of time. Higher channel capacity can allocate more resources to each user, such as higher modulation order and more frequency bandwidth, thereby providing better signal quality and lower bit error rate. In addition, high channel capacity can provide more space for error correction coding, increasing the robustness of the system, making communication more reliable, especially in the presence of interference and noise.

[0150] Based on the acquired smart metering communication system channel data, the propagation characteristics of different basements of the same building are modeled; including:

[0151] After obtaining the typical channel characteristics of the smart metering communication system for different basements of the same building, the corresponding basement with the most concentrated power delay spectrum, the most concentrated power angle spectrum, the maximum received power, the smallest root mean square delay spread, the maximum channel capacity, and the minimum path loss is selected.

[0152] One of the requirements for in-depth optimization of the smart metering system is not only to determine the best position in the basement, but also to continue to study the impact of different basement positions on the signal to achieve overall optimization of the system. When analyzing the impact of the signal at different basement positions, the differences caused by environmental elements need to be considered. By modeling the propagation characteristics of different basements of the same building, the performance of the signal at each basement position can be better predicted to comprehensively understand the signal transmission characteristics at different positions and then select the optimal deployment strategy. This technology can ensure efficient and stable signal transmission of the system in various practical application scenarios, while taking appropriate technical means to deal with potential interference problems.

[0153] To explore the impact of different positions, the typical channel characteristics calculation method of the smart metering system communication channel is needed, including power delay spectrum, power angle spectrum, root mean square delay spread, path loss, and channel capacity. Specifically:

[0154] The received power characteristics of the channel can be obtained through equation (3). The advantages and disadvantages of the sending end position are analyzed by analyzing the cumulative distribution function of its received power.

[0155] In the basement position close to the trajectory of the receiving end, the characteristics of the received power tend to be the strongest. Different basement positions have different sensitivities to these influences, resulting in differences in received power.

[0156] The root mean square delay spread characteristics of the channel can be obtained through equation (6). Analysis is performed through the cumulative distribution function of the root mean square delay spread. Different basement positions have different sensitivities to multipath propagation, resulting in certain differences.

[0157] The basement locations close to the receiver trajectory exhibit smaller root mean square delay spread. The basement locations close to the receiver trajectory have fewer multiple reflections and scatterings. Reflections and scatterings of signals from walls and obstacles can cause delay elongation and increase the root mean square delay spread.

[0158] The channel capacity characteristics of the channel can be obtained by equation (7). Analysis is performed through the cumulative distribution function of the channel capacity.

[0159] The basement locations close to the receiver trajectory exhibit stronger channel capacity trends. This is mainly due to less fading and multipath interference compared to other basement locations. In the basement locations close to the receiver, the channel capacity is enhanced because the propagation path is more direct and the signal is subjected to minimal interference and attenuation.

[0160] The path loss characteristics of the channel can be obtained by equation (5). Correlation analysis is performed based on the FI model. This model can well adapt to different environmental conditions. This model is commonly used in the planning and design of wireless communication systems, which can more accurately predict the power attenuation of signals in different distances and environments, thereby better optimizing the performance of the system.

[0161] The smallest path loss trend can be observed in the basement locations close to the receiver trajectory. The closer the transmission end and the receiver are to the receiver trajectory, the shorter the signal propagation path, and the smaller the path loss. Basement locations away from the receiver trajectory have more interference from walls, obstacles, and the propagation environment, which can cause additional attenuation and scattering.

[0162] Based on the obtained smart metering communication system channel data, the propagation characteristics of different floors at the same horizontal position are modeled; including:

[0163] After obtaining the typical channel characteristics of the smart metering communication system for different floors at the same horizontal position, the corresponding floor with the most concentrated power delay spectrum, the most concentrated power angle spectrum, the maximum received power, the smallest root mean square delay spread, the largest channel capacity, and the smallest path loss is selected.

[0164] In the optimization process of the smart metering system, in addition to considering the relevant positions of the basement, the characteristics of different floors need to be analyzed in depth to fully understand the propagation of the channel. The structural differences between different floors can lead to changes in the signal propagation path. By deeply studying the structure of different floors, the propagation characteristics of signals between floors can be better understood, and the optimal signal transmission position can be more accurately determined to improve the performance of the communication system.

[0165] The root mean square delay spread characteristics of the channel can be obtained by equation (6). Analysis is performed through the cumulative distribution function of the root mean square delay spread.

[0166] The receiving end is set outdoors, and the transmitting end is set in the basement and different floors. The minimum root mean square delay spread occurs at the location of the basement. In addition, due to the existence of relatively few interference paths, the influence of other buildings is small, so the delay spread caused by multipath propagation is reduced. Close to the ground, the signal does not need to pass through multiple floors of the building, reducing the influence of fading and attenuation, which helps to reduce the root mean square delay spread.

[0167] The power delay spectrum characteristics of the channel can be obtained by formula (2). The change of clusters can be observed by the dispersion diagram of the power delay spectrum, such as power and delay, and the birth and death phenomenon.

[0168] The different trends of the power delay spectrum are consistent with the motion characteristics of the receiving end trajectory. Since the signal emitted from the basement needs to pass through the basement and the ground, it has less shielding and interference compared to other floors. In addition, the signal emitted from the basement passes through fewer multipath propagation paths, and the delay is smaller when propagating to the outdoor. Therefore, the power delay spectrum is more concentrated in dispersion. With the increase of height, the signal propagation path of different floors becomes more complex, and more buildings and obstacles are passed through. This leads to a more obvious dispersion of the power delay spectrum.

[0169] The power angle spectrum is used to describe the power distribution in the angle domain of the channel. Inside the building, the signal may experience multiple reflections, scattering and refraction, resulting in different powers in different directions. Through the analysis of the angle spectrum, the spatial diversity can be better utilized to improve the reliability and coverage of the signal. In the deployment of the smart meter reading system, by fully utilizing the information of the channel power angle spectrum, the data can be effectively transmitted, and the overall efficiency of the smart meter reading system can be improved.

[0170] The best power angle spectrum is when Tx is located in the basement. Compared with other floors, the basement can transmit signals through fewer buildings and obstacles because it is located underground. The propagation path is more direct, reducing the influence of multipath propagation. Therefore, the angle domain dispersion of the signal emitted from the basement is small, and better signal transmission effect can be obtained. With the increase of height, the signal transmission path becomes more complex. The signal needs to pass through more buildings and is more easily affected by buildings and obstacles. This will increase the effect of multipath propagation, making the received signal have a large angle domain dispersion.

[0171] By analyzing the typical channel characteristics, system optimization and network deployment in the transmission of the smart meter reading system are realized; including:

[0172] Based on the propagation characteristics of the meter reading system in the same basement at different positions, different basements of the same building, and different floors at the same horizontal position, optimization and deployment are carried out.

[0173] Firstly, by analyzing the channel characteristics, the required transmission power at different locations and different times can be determined. This helps to reduce energy consumption, prolong the battery life of smart metering devices, and reduce interference to other devices.

[0174] Secondly, in the smart metering system, understanding the channel characteristics helps to determine the optimal data transmission path and network topology, thereby reducing delay and improving the efficiency of data collection. Channel characteristic analysis helps to determine the coverage and capacity requirements of the network, thereby making reasonable network deployment and resource allocation.

[0175] Finally, based on the channel characteristics, the optimal location for smart metering system deployment can be obtained. Specifically, based on the modeling results of the metering system at different positions in the same basement, the optimal position of the basement can be obtained. Based on the obtained optimal position, different basement transmitters are deployed, and the optimal basement position can be selected. Based on the obtained optimal position, different floor transmitters are deployed, and the final optimal position can be selected. This position can be used as the final smart metering system deployment position.

[0176] Through in-depth analysis of the channel characteristic results, the smart metering system can achieve more efficient and reliable data transmission, improve the overall performance of the network, and meet the needs of smart grid and power internet of things applications.

[0177] By analyzing the channel characteristics at different positions in the same basement, including multipath effects, attenuation and interference factors, the optimal position is selected. The optimal transmitter position in the same basement is accurately selected, which has good transmission performance in the channel environment. After selecting the optimal position, further analysis of the characteristics of different basement positions can identify the best basement area with signal quality. Through optimization in this stage, the selected basement area has the best signal quality, which helps to improve the performance and reliability of data transmission of the system. Finally, in order to achieve more comprehensive modeling purposes, it is necessary to conduct in-depth analysis of the relationship between the basement and different floors. This includes the differences in signal propagation characteristics between the basement and the ground floor and different floors. Through the study of these characteristics, the optimal position of the basement in the entire building can be determined, thereby realizing more efficient signal coverage and data transmission.

[0178] Such comprehensive modeling process helps to ensure that the complexity of the channel environment is fully considered in the modeling of the smart system, improves the performance and stability of the system, and provides a strong reference for future system design and optimization.

[0179] Embodiment 3

[0180] The difference between the smart metering communication channel modeling method for basement environment according to embodiment 2 is:

[0181] Based on the previous research, a certain place was selected as the experimental address. A wireless channel measurement system was built, and related channel measurement activities were carried out in the base. Scene reconstruction was carried out based on the ray tracing method. The reconstructed scene includes vegetation, ground, glass, etc. The electromagnetic parameters of all materials in the scene are obtained by using the specific material parameters provided by the Wireless Insite software and the International Telecommunication Union (ITU). The sending end is placed in the basement environment of a certain place. The receiving end is placed in the open space outside a certain place to collect instrument data. Among them, the measurement and simulation center frequency is 490 MHz, and the bandwidth is 40 MHz. This configuration meets the real scene smart grid communication system. Smart metering data can be transmitted between the sending end and the receiving end.

[0182] Based on the channel data, the channel parameters of multipath propagation are obtained, and the corresponding wireless channel model is established. In the underground smart metering communication system, the sending end can be deployed in different positions in the same basement, and the receiving end is set outdoors. The specific analysis positions are shown in Figure 1 , that is, close to the window (Tx1), close to the left wall (Tx2), in the middle of the room (Tx3), close to the right wall (Tx4), and close to the door (Tx5). The characteristics of the received power, channel capacity, and power delay spectrum are analyzed. Figure 2 The cumulative distribution function of the received power along the Rx path at different Tx positions in the same basement is shown. When the received power share is 80%, the values from Tx1 to Tx5 are -49.74 dBm, -53.60 dBm, -54.85 dBm, -52.19 dBm, and -51.98 dBm, respectively. The results show that the received power is the strongest near the window position (Tx1). The thinness of the window glass and its low signal attenuation characteristics enable the signal to easily pass through the window, thus facilitating the successful propagation of the signal to the outdoor. When the signal is transmitted from a position close to the indoor wall, it can be absorbed, attenuated, or reflected by the wall material, resulting in a decrease in received power. Combined with the relevant characteristics, it is finally determined that it can be deployed at position 1.

[0183] Channel models for different basement positions are established. According to the distance from the trajectory of the receiving end, Tx1, Tx2, Tx3, Tx4, Tx5, and Tx6 are set. The received power, root mean square delay spread, channel capacity, and path loss characteristics are analyzed. The cumulative distribution function of the channel capacity along the Rx path at different basement Tx positions is shown in Figure 3 . It can be clearly observed that the basement positions close to the Rx path (Tx1) exhibit a stronger channel capacity trend. This is mainly due to the reduced fading and multipath interference compared to other basement positions. In the basement positions close to the Rx route, the channel capacity is enhanced because the propagation path is more direct, and the signal is subjected to minimal interference and attenuation. Combined with the relevant characteristics, it is finally determined that it can be deployed at position 1.

[0184] Channel models for different floor locations are established. Specifically, Tx1 is placed in the basement; Tx2 is placed on the third floor; Tx3 is placed on the fifth floor; and Tx4 is placed on the eleventh floor (top floor). The root mean square delay spread, power delay profile, and power angle profile characteristics are analyzed. Figure 4 The time-varying delay power spectrum diagram for the Tx placed in the basement; the different trends of the power delay profile are consistent with the motion characteristics of the receiving end trajectory. Since the signal emitted from the basement needs to pass through the basement and the ground, there is less obstruction and interference compared to other floors. In addition, the signal emitted from the basement passes through fewer multipath propagation paths and has a smaller delay when propagating outdoors. Therefore, the power delay profile is more concentrated in dispersion. As the height increases, the signal propagation path becomes more complex and passes through more buildings and obstacles. This leads to more obvious power delay profile dispersion. Figure 5 The time-varying angle power spectrum diagram for the Tx placed in the basement. It can be noted that the time-varying angle power spectrum is optimal when the transmitting end is placed in the basement. Compared to other floors, the basement is located underground and can transmit signals through fewer buildings and obstacles. This means that the propagation path is more direct, reducing the impact of multipath propagation. Therefore, the angle dispersion of the signal emitted from the basement is smaller, and better signal transmission effects can be achieved. As the floor height increases, the signal transmission path becomes more complex. The signal needs to pass through more buildings and is more susceptible to obstruction by buildings and obstacles. This will increase the effect of multipath propagation, making the received signal have a larger angle domain dispersion. In combination with the relevant characteristics, it is ultimately decided that it can be deployed in location 1.

[0185] Deploy the optimal location. In combination with the relevant characteristics in the above three cases, it is ultimately decided that it can be deployed in location 1.

Claims

1. A smart meter reading communication channel modeling method for basement environment, characterized by: include: Step 1: Acquire the channel information of the smart meter reading communication system by combining ray tracing and channel measurement methods; Step 2: Based on the channel data, obtain the channel parameters of multipath propagation and establish the corresponding wireless channel model; Step 3: Based on the established wireless channel model, obtain the typical channel characteristics of the smart meter reading communication system; Step 4: Analyze typical channel characteristics to achieve system optimization and network deployment in smart meter reading system transmission; Based on the established wireless channel model, the typical channel characteristics of the intelligent meter reading communication system are obtained, including: Typical channel characteristics of smart meter reading communication systems; including: power delay spectrum, power angle spectrum, square root delay spread, path loss, and channel capacity; Typical channel characteristics of smart meter reading communication systems include channel characteristics of typical smart meter reading systems at different locations in the same basement, different basements, and different floors; Based on the acquired channel data of the smart meter reading communication system, the propagation characteristics of the meter reading system at different locations in the same basement are modeled. This includes: Based on the obtained CIR, the typical channel characteristics of the intelligent meter reading communication system are obtained, including: According to the obtained CIR, the power delay spectrum Ψ(t,τ) is obtained to describe the power variation along the delay axis. The specific expression is as follows: Similarly, the power angle spectrum Υ(t,θ) is obtained to describe the power variation along the angle axis. The specific expression is as follows: h(t,θ) represents the CIR in the angle domain; θ represents the angle variable; The received power of each path is added to calculate the received power κ at each receiving end, which is expressed as: Where L is the number of multipath components in channel propagation, P i is the received power of the i-th path; Path loss is defined as received power minus transmitted power minus antenna gain; the floating intercept model fits path loss data in dB. Expressed as: Where n is the path loss exponent, ξ is the intercept, and d is the three-dimensional distance from the transmitter to the receiver in meters; X s It is the shadow that fades; is the path loss variable with distance d as parameter; RMS delay spread σ τ Expressed as: Among them, τ i and P(τ i ) are respectively the delay and power of the i-th multipath component ray; Channel capacity C refers to the maximum amount of data transmitted in each time and spectrum resource; it is expressed as: Where ρ is the signal-to-noise ratio and the unit of C is bps / Hz; After obtaining the typical channel characteristics of the smart meter reading communication system at different locations in the same basement, the optimal location in the basement corresponding to the most concentrated power delay spectrum, the most concentrated power angle spectrum, the maximum received power, the minimum root mean square delay spread, the maximum channel capacity, and the minimum path loss is selected.

2. The intelligent meter reading communication channel modeling method for basement environment according to claim 1 is characterized in that: A USRP-based wireless channel measurement system is used to obtain channel data of the smart meter reading communication system.

3. The intelligent meter reading communication channel modeling method for basement environment according to claim 1 is characterized in that: The ray tracing method is used to obtain the channel data of the smart meter reading communication system.

4. The method for modeling a communication channel for intelligent meter reading in a basement environment according to claim 1, characterized in that: Based on the channel data, the channel parameters of multipath propagation are obtained, including: The sending signal uses a pseudo-noise PN sequence signal; through direct calibration, the response of the device, the sending and receiving side cables is eliminated to obtain the calibration signal y th (t), that is: y th (t)=s(t)*m(t) Where * represents the convolution operation, s(t) represents the transmitted signal, and m(t) represents the response of the smart meter communication system and the cable. Calibration signal y th (t) After transmission in a specific environment, the detection signal received by the wireless channel is expressed as y rx (t), that is: y rx (t)=s(t)*m(t)*γ(t)=y th (t)*γ(t) Where γ(t) represents the channel impulse response; The frequency domain response is obtained by the fast Fourier transform FFT of the time domain response, and the calibrated channel impulse response γ(t) is obtained from the inverse fast Fourier transform IFFT in the frequency domain, that is: Among them, Y rx (f) and Y th (f) are the calibration signals y th (t) and the received signal y rx Frequency domain response of (t); Based on γ(t), a peak detection algorithm is used to obtain the channel parameters of channel multipath propagation; including: Calculate the maximum received power P of the amplitude value of γ(t) max and the average noise floor N of the received signal aver , the unit is dB; The power value of each receiving point is calculated to complete the noise reduction processing. The peak signal is taken down by 30-40dB, and the average noise floor is taken up by 5-10dB as the two thresholds. The maximum value of the two thresholds is used as the signal threshold. The received signal outside this signal threshold range is discarded.

5. The method for modeling a communication channel for intelligent meter reading in a basement environment according to claim 4, characterized in that: The power value of each receiving point is calculated to complete the noise reduction processing. The peak signal is taken down 40dB and the average noise floor is taken up 10dB as the two thresholds. The maximum value of the two thresholds is used as the signal threshold. The received signal outside this signal threshold range is discarded.

6. The method for modeling a communication channel for intelligent meter reading in a basement environment according to claim 1, characterized in that: Establish the corresponding wireless channel model; including: By combining ray tracing and channel measurement methods, we can obtain channel parameters, including delay, power, and angle. We can also establish a corresponding wireless channel model and obtain the channel impulse response (CIR) at different locations, which can be expressed as: Among them, τ i (t), α i (t) and φ i (t) represents the delay, amplitude, and phase of the i-th path between the transmitter and the receiver, L(t) represents the total number of multipaths; h(t,τ) represents the CIR in the delay domain; τ represents the delay variable.

7. The method for modeling a communication channel for intelligent meter reading in a basement environment according to claim 1, characterized in that: Based on the acquired channel data of the smart meter reading communication system, the propagation characteristics of different basements in the same building are modeled. This includes: After obtaining the typical channel characteristics of the smart meter reading communication system in different basements of the same building, the basement with the most concentrated power delay spectrum, the most concentrated power angle spectrum, the maximum received power, the minimum root mean square delay spread, the maximum channel capacity, and the minimum path loss is selected.

8. A method for modeling a communication channel for intelligent meter reading in a basement environment according to any one of claims 1 to 7, characterized in that: Based on the acquired channel data of the smart meter reading communication system, the propagation characteristics of different floors at the same horizontal position are modeled; including: After obtaining the typical channel characteristics of the intelligent meter reading communication system for different floors at the same horizontal position, the corresponding floor with the most concentrated power delay spectrum, the most concentrated power angle spectrum, the maximum received power, the minimum root mean square delay spread, the maximum channel capacity, and the minimum path loss is selected.

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