Packet loss probability prediction method and device and computer equipment

Abstract

The invention relates to a packet loss probability prediction method and device and computer equipment. The method comprises the following steps: acquiring a modulation parameter of a Bluetooth chip and a path loss model of the Bluetooth chip in an environment; determining the number of target signals received by the Bluetooth chip; the signal intensity of the target signal is within a target range, and the target range is determined according to the receiving sensitivity of the Bluetooth chip; drawing a packet error rate curve of the Bluetooth chip in the target range based on the number of the target signals received by the Bluetooth chip and the signal strength of the target signals; and importing a simulation packet error rate curve corresponding to the packet error rate curve, the modulation parameters and the path loss model into a Mesh layer for Mesh simulation prediction to obtain a packet loss rate prediction result. By adopting the method, the efficiency and the accuracy can be improved.

Description

Technical Field

[0001] The present application relates to the field of network communication technology, and in particular to a packet loss rate prediction method, apparatus, and computer equipment. Background Art

[0002] Mesh networking, as a low-power, self-organizing, and self-healing wireless communication architecture, has been widely adopted in scenarios such as smart lighting, smart buildings, industrial automation, and the Internet of Things. The fundamental principle of mesh networking is to flexibly forward data between nodes within the network through multi-hop routing, thereby expanding communication range and enhancing reliability.

[0003] However, in the actual deployment of mesh networks, network communication quality is affected by a variety of factors. To achieve ideal communication performance, repeated adjustments to node locations and network topology are often required, along with extensive field testing to determine deployment effectiveness. Mesh network communication quality is determined by packet loss rate. Existing technologies for packet loss rate simulation often consider a limited range of factors, making it difficult to accurately predict packet loss rates. Furthermore, packet loss rate prediction efficiency is low. Summary of the Invention

[0004] Based on this, it is necessary to provide a packet loss rate prediction method, device and computer equipment that can improve efficiency and accuracy in order to address the above technical problems.

[0005] A packet loss rate prediction method, characterized in that the method comprises:

[0006] Obtaining modulation parameters of a Bluetooth chip and a path loss model of the Bluetooth chip in the environment in which it is located;

[0007] Determining the number of target signals received by the Bluetooth chip; wherein the signal strength of the target signal is within a target range, and the target range is determined according to the receiving sensitivity of the Bluetooth chip;

[0008] Drawing a packet error rate curve of the Bluetooth chip within a target range based on the number of target signals received by the Bluetooth chip and the signal strength of the target signals;

[0009] The simulated packet error rate curve corresponding to the packet error rate curve, the modulation parameters and the path loss model are imported into the Mesh layer to perform Mesh simulation prediction to obtain a packet loss rate prediction result.

[0010] A packet loss rate prediction device, comprising:

[0011] An information acquisition module, configured to acquire modulation parameters of a Bluetooth chip and a path loss model of the Bluetooth chip in its environment;

[0012] a quantity acquisition module, configured to determine the number of target signals received by the Bluetooth chip; the signal strength of the target signal is within a target range, and the target range is determined according to the receiving sensitivity of the Bluetooth chip;

[0013] a curve acquisition module, configured to draw a packet error rate curve of the Bluetooth chip within a target range based on the number of target signals received by the Bluetooth chip and the signal strength of the target signals;

[0014] The simulation prediction module is used to import the simulated packet error rate curve corresponding to the packet error rate curve, the modulation parameters and the path loss model into the Mesh layer to perform Mesh simulation prediction and obtain a packet loss rate prediction result.

[0015] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0016] The packet loss rate prediction method, apparatus, and computer device described above determine the number of target signals received by the Bluetooth chip by obtaining the modulation parameters of the Bluetooth chip and the path loss model of the Bluetooth chip's environment. The target signal strength is within a target range. Based on the number of target signals received by the Bluetooth chip and the target signal strength, a packet error rate curve for the Bluetooth chip within the target range is plotted. The simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve are then imported into the Mesh layer for mesh simulation prediction, resulting in a packet loss rate prediction result. This method, while more realistically reflecting the behavior of the Bluetooth chip during communication during simulation, also focuses on valid signals, avoiding counting signals with signal strengths outside the target range, and eliminating invalid interference to produce a more accurate packet error rate curve. Furthermore, the simulated packet error rate curve, modulation parameters, and path loss model involved in the RF physical layer can be directly combined with the Mesh layer to simulate the multi-hop transmission process in the simulation, thereby simplifying the simulation process while ensuring simulation integrity and improving the efficiency and accuracy of packet loss rate prediction results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A diagram illustrating an application environment of a packet loss rate prediction method according to an embodiment;

[0018] Figure 2 1 is a flow chart of a packet loss rate prediction method according to an embodiment;

[0019] Figure 3 is a schematic diagram of a packet error rate curve in one embodiment;

[0020] Figure 4 is a schematic diagram of calculating a first frequency offset in one embodiment;

[0021] Figure 5 is a schematic diagram of calculating the second frequency offset in one embodiment;

[0022] Figure 6 is a schematic diagram of calculating a first frequency deviation average value in one embodiment;

[0023] Figure 7 is a schematic diagram of calculating the second frequency deviation average value in one embodiment;

[0024] Figure 8 is a schematic diagram of calculating the frequency difference in one embodiment;

[0025] Figure 9 is a schematic diagram of a path loss model in one embodiment;

[0026] Figure 10 is a schematic diagram of a simulated packet error rate curve in one embodiment;

[0027] Figure 11 Schematic diagram of node distribution in one embodiment;

[0028] Figure 12 is a structural block diagram of a packet loss rate prediction device in one embodiment;

[0029] Figure 13 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0031] The packet loss rate prediction method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, the terminal 102 interacts with the server 104 via a wired / wireless channel. The data storage system can store data that the server 104 needs to process. The server 104 obtains the modulation parameters of the Bluetooth chip and the path loss model of the Bluetooth chip in the environment in which it is located; the server 104 determines the number of target signals received by the Bluetooth chip; the signal strength of the target signal is within the target range, which is determined by the receiving sensitivity of the Bluetooth chip; the server 104 draws a packet error rate curve of the Bluetooth chip within the target range based on the number of target signals received by the Bluetooth chip and the signal strength of the target signal; the server 104 imports the simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve into the Mesh layer for Mesh simulation prediction to obtain a packet loss rate prediction result. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablet computers, IoT devices, etc. The server 104 can be a single server, a server cluster consisting of multiple servers, or a cloud computing center consisting of multiple servers.

[0032] In one embodiment, Figure 2 As shown, a packet loss rate prediction method is provided, which is applied to Figure 1 Taking the server 104 in the example as an example, the following steps are included:

[0033] S202: Acquire modulation parameters of the Bluetooth chip and a path loss model of the Bluetooth chip in the environment in which it is located.

[0034] The Bluetooth chip may be any model of Bluetooth chip that has the function of transmitting and receiving signals.

[0035] The modulation parameters are inherent properties of Bluetooth chips. Bluetooth chips of the same model all have the same modulation parameters, while different models may have the same or different modulation parameters.

[0036] The path loss model describes the phenomenon of signal strength attenuation as transmission distance increases. The path loss model is dependent on the environment in which the Bluetooth chip is currently located. The path loss models of the same Bluetooth chip model may be the same or different in different environments. Different Bluetooth chip models may have the same or different path loss models in the same environment.

[0037] S204, determining the number of target signals received by the Bluetooth chip; the signal strength of the target signal is within a target range, and the target range is determined according to the receiving sensitivity of the Bluetooth chip.

[0038] When determining the number of target signals received by the Bluetooth chip, only the number of target signals whose signal strengths are within the target range is counted. For example, if the Bluetooth chip receives n signals, but only m signals have signal strengths within the target range, the number of target signals received by the Bluetooth chip is determined to be m.

[0039] The Bluetooth chip's receiving sensitivity refers to the weakest signal strength the Bluetooth chip can receive. The receiving sensitivity is fixed and can be obtained from the factory information or the chip manual.

[0040] The target range is the range after adjusting the preset value up or down based on the receiving sensitivity. For example, if the receiving sensitivity is -96dB and the preset value is ±6dB, the target range is (-96dB, -84dB). The target signal can be understood as a signal strength between (-96dB, -84dB).

[0041] S206 , drawing a packet error rate curve of the Bluetooth chip within the target range based on the number of target signals received by the Bluetooth chip and the signal strength of the target signals.

[0042] Among them, the packet error rate curve within the target range refers to the ratio of data packets that the Bluetooth chip fails to receive correctly or loses when sending a target signal with a signal strength within the target range. For example, continuing with the above example, if the signal is sent to the Bluetooth chip 1000 times per dB, if the Bluetooth chip can successfully receive 900 times, the PER (Packet Error Ratio, PER) is 0.1, and if the Bluetooth chip can successfully receive 800 times, the PER is 0.2. Finally, the packet error rate curve is drawn according to the absolute value of the signal strength near ±6dB of the horizontal axis receiving sensitivity and the vertical axis PER. The packet error rate curve is as follows Figure 3 As shown, the horizontal axis is the absolute value of signal strength, the vertical axis is the packet error rate, and Rx represents the receiving sensitivity.

[0043] S208 , importing the simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve into the Mesh layer to perform Mesh simulation prediction to obtain a packet loss rate prediction result.

[0044] The simulated packet error rate curve corresponding to the packet error rate curve is obtained by adjusting the simulated background noise parameters and fitting the trend of the packet error rate curve. The trend of the packet error rate curve is similar to that of the simulated packet error rate curve.

[0045] The Mesh layer is the network layer in the Bluetooth Mesh protocol, which is mainly responsible for managing the routing of messages in the network and ensuring that messages can reach the target node from the source node.

[0046] Importing the simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve into the Mesh layer for mesh simulation prediction is a systematic process that combines physical layer communication characteristics with network layer behavior modeling. This allows the simulated packet error rate curve, modulation parameters, and path loss model involved in the RF physical layer to be directly combined with the Mesh layer to simulate the multi-hop transmission process in the simulation. This simplifies the simulation process while ensuring simulation integrity, improving the efficiency and accuracy of packet loss rate prediction results.

[0047] In some embodiments, the packet error rate curve, modulation parameters and path loss model can also be imported into the Mesh layer for Mesh simulation prediction to obtain the packet loss rate prediction result. This can save the steps of obtaining the simulation packet error rate curve and simplify the process of packet loss rate prediction.

[0048] In the above-mentioned packet loss rate prediction method, the number of target signals received by the Bluetooth chip is determined by obtaining the modulation parameters of the Bluetooth chip and the path loss model of the Bluetooth chip's environment. The signal strength of the target signal is within the target range. Based on the number of target signals received by the Bluetooth chip and the signal strength of the target signal, a packet error rate curve for the Bluetooth chip within the target range is plotted. The simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve are then imported into the Mesh layer for mesh simulation prediction, resulting in a packet loss rate prediction result. This method not only more realistically reflects the behavior of the Bluetooth chip during communication during simulation, but also focuses on valid signals, avoiding counting signals with signal strength outside the target range, and eliminating invalid interference, thereby plotting a more accurate packet error rate curve. Furthermore, the simulated packet error rate curve, modulation parameters, and path loss model involved in the RF physical layer can be directly combined with the Mesh layer to simulate the multi-hop transmission process in the simulation, thereby simplifying the simulation process while ensuring simulation integrity and improving the efficiency and accuracy of packet loss rate prediction results.

[0049] In one embodiment, obtaining the modulation parameters of the Bluetooth chip includes:

[0050] When the Bluetooth chip sends a signal, a first frequency of a leading portion of a data packet carried by the sent signal and a preset second frequency are obtained, and a difference between the first frequency and the second frequency is determined as a first frequency offset; when the sent signal is received, a third frequency of the leading portion is obtained, and a difference between the third frequency and the first frequency is determined as a second frequency offset;

[0051] When the Bluetooth chip sends a signal carrying a first sequence, obtaining a first frequency deviation average value between a plurality of bits in the first sequence;

[0052] When the Bluetooth chip sends a signal carrying a second sequence, obtaining a second frequency deviation average value between a plurality of bits in the second sequence; the first sequence and the second sequence are inconsistent binary sequences;

[0053] Obtaining a frequency difference between any two third sequences separated by a preset time in a payload portion of a data packet; the third sequence includes a plurality of bits;

[0054] The first frequency deviation, the second frequency deviation, the first frequency deviation average value, the second frequency deviation average value, and the frequency difference are determined as modulation parameters.

[0055] The data packet mainly includes a preamble and an access address, i.e., a payload, which is the effective load of the data packet.

[0056] The first frequency is the frequency of the leading part of the data packet when the signal is generated or sent, and the second frequency is the preset ideal frequency. The first frequency offset can also be understood as the absolute value of the result of subtracting the second frequency from the first frequency. For example, if the preset second frequency is 2402MHz and the first frequency of the leading part of the data packet when the signal is generated and sent is 2403MHz, then the first frequency offset is |2403MHz-2402MHz|=1MHz. Figure 4 FIG. 1 is a schematic diagram of calculating the first frequency offset, wherein 10101010 is a sequence in a data packet, the horizontal axis is time, and the vertical axis is frequency.

[0057] The third frequency is the frequency of the leading part of the data packet when the signal is received. The second frequency offset can also be understood as the absolute value of the result of subtracting the first frequency from the third frequency. For example, continuing with the above example, if the third frequency of the leading part of the data packet when the signal is received is 2406MHz, then the second frequency offset is |2406MHz-2403MHz|=3MHz. Figure 5 FIG. 1 is a schematic diagram of calculating the second frequency offset, wherein 10101010 is a sequence in a data packet, the horizontal axis is time, and the vertical axis is frequency.

[0058] The first sequence is located in the payload of the data packet. The second sequence is also located in the payload of the data packet. The first and second sequences have the same length but different bit values. For example, the first sequence is 11110000, and the second sequence is 10101010.

[0059] The first frequency deviation average value is the average value of the difference between the actual carrier frequency and the ideal carrier frequency for each bit in the first sequence. For example, if there are 3 bits in the first sequence, for the first bit, the difference between the actual carrier frequency and the ideal carrier frequency is x1, for the second bit, the difference between the actual carrier frequency and the ideal carrier frequency is x2, and for the third bit, the difference between the actual carrier frequency and the ideal carrier frequency is x3, then the first frequency deviation average value is (x1+x2+x3) / 3. Specifically, the schematic diagram of calculating the first frequency deviation average value of the first sequence 11110000 is as follows Figure 6 As shown, 11110000 is the first sequence in the data packet, the horizontal axis is time, the vertical axis is frequency, Δf1, Δf2, Δf3, Δf4, Δf5, Δf6, Δf7, and Δf8 are the differences between the actual carrier frequency and the ideal carrier frequency of each bit in the first sequence 11110000, and ΔF1 is the first frequency deviation average value.

[0060] The second frequency deviation average value is the average value of the difference between the actual carrier frequency and the ideal carrier frequency of each bit in the second sequence. Specifically, the schematic diagram of calculating the second frequency deviation average value of the second sequence 10101010 is as follows: Figure 7 As shown, 10101010 is the second sequence in the data packet, the horizontal axis is time, the vertical axis is frequency, Δf9, Δf 10 , Δf 11 , Δf 12 , Δf 13 , Δf 14 , Δf 15 , Δf 16 are the differences between the actual carrier frequency and the ideal carrier frequency of each bit in the second sequence 10101010, and ΔF2 is the second frequency deviation average value.

[0061] The third sequence is located in the payload of the data packet. The preset time is a pre-set time interval. The frequency difference is the frequency difference between two third sequences. The number of bits between the two third sequences is the same, and the specific bit values may be the same or different. For example, the frequency difference is the frequency difference between any two 10-bit sequences separated by 50 microseconds in the payload of the data packet. 10 bits constitute the third sequence, and 50 microseconds is the preset time. Specifically, the schematic diagram for calculating the frequency difference is as follows Figure 8 As shown, where f1, f2, f3, f4, f5, f6, ..., f n It indicates that for each 10-bit group, that is, for each third sequence, the interval between f6 and f1 is 50 microseconds, and the interval between f7 and f2 is 50 microseconds.

[0062] Specifically, the modulation parameters of the module under different transmit powers are shown in Table 1.

[0063] Table 1 Modulation parameters (unit: KHz)

[0064]

[0065] In Table 1, F n represents the frequency difference, ΔF1 represents the first frequency deviation average value, and ΔF2 represents the second frequency deviation average value.

[0066] In this embodiment, by determining the first frequency deviation, the second frequency deviation, the average value of the first frequency deviation, the average value of the second frequency deviation and the frequency difference as modulation parameters, the adjustment signal used in the Mesh layer simulation process can be accurately adjusted during the Mesh layer simulation, thereby improving the accuracy of the packet loss rate prediction result.

[0067] In one embodiment, the process of obtaining the path loss model of the Bluetooth chip in the environment includes:

[0068] In the vicinity of the Bluetooth chip, multiple points are evenly arranged at preset intervals;

[0069] When the Bluetooth chip sends a signal, obtain the signal strength at each point;

[0070] Based on the signal strength of each point and the distance between each point and the Bluetooth chip, a path loss model of the Bluetooth chip in the environment is obtained.

[0071] The adjacent area refers to the area around the current location of the Bluetooth chip. The preset spacing can be understood as the distance between two adjacent points. Adjacent can be front-to-back or left-to-right.

[0072] When the Bluetooth chip sends a signal, it will be sent to multiple points. Since the distance between each point and the Bluetooth chip is different, the strength of the signal received by each point is also different.

[0073] The path loss model is Where d is the distance between the point and the Bluetooth chip; d0 is the reference distance, which is a multiple of the signal wavelength; d f is the starting distance of the far field; [P L (d0)] dB is the path loss at a standard distance of 1m; χ is a Gaussian distribution random variable with a mean of zero and a standard deviation of σ; n is the path loss index under a specific environment. The variables that need to be fitted based on the signal strength of each point and the distance between each point and the Bluetooth chip are [P L (d0)] dB , n, χ. After fitting, we get [P L(d0)] dB The specific values of , n, and χ are used to obtain the path loss model of the Bluetooth chip in the environment.

[0074] In different environments, the path loss models fitted by the same Bluetooth chip may be the same or different. Specifically, in different environments, the fitting variables in the path loss models fitted by the same Bluetooth chip may be the same or different.

[0075] In this embodiment, by obtaining the signal strength of each point when the Bluetooth chip sends a signal, fitting is performed based on the signal strength of each point and the distance between each point and the Bluetooth chip to obtain a path loss model of the Bluetooth chip in the environment. This can provide accurate physical layer support for subsequent packet loss rate prediction, thereby obtaining an accurate packet loss rate prediction result.

[0076] In one embodiment, within the vicinity of the Bluetooth chip, multiple points are evenly arranged at preset intervals, including:

[0077] If there is an obstacle in the vicinity of the Bluetooth chip, multiple points are arranged in the vicinity according to the preset distance and the position of the obstacle.

[0078] Obstacles refer to objects that can block, reflect, or absorb signals, such as walls, doors, windows, furniture, and plants.

[0079] The specific steps for arranging multiple points in the adjacent area based on the preset spacing and the location of the obstacle are: evenly arranging multiple points in the adjacent area at the preset spacing, and arranging points at the location of the obstacle; and combining the evenly arranged multiple points with the points arranged at the location of the obstacle to determine the final points arranged in the adjacent area. In some embodiments, at least one point is arranged at the location of the obstacle. For example, if the obstacle is a wall, one point is arranged on both sides of the wall.

[0080] In this embodiment, when there is an obstacle in the vicinity of the Bluetooth chip, multiple points are arranged in the vicinity according to the preset spacing and the position of the obstacle. This can fully consider the impact of obstacles in the environment on the signal strength, thereby obtaining a more accurate path loss model.

[0081] In one embodiment, a path loss model of the Bluetooth chip in the environment is obtained by fitting based on the signal strength of each point and the distance between each point and the Bluetooth chip, including:

[0082] Determine the number of obstacles and the path loss exponent of the obstacles;

[0083] Based on the number of obstacles, the path loss index of the obstacles, the signal strength of each point, and the distance between each point and the Bluetooth chip, a path loss model of the Bluetooth chip in the environment is obtained.

[0084] The path loss exponent describes how quickly a signal attenuates as distance increases when propagating through an obstacle. The path loss exponents for different types of obstacles may be the same or different. For example, walls, doors, and windows each have different path loss exponents.

[0085] The path loss model of the Bluetooth chip in its environment is: Where d is the distance between the point and the Bluetooth chip; d0 is the reference distance, which is a multiple of the signal wavelength; d f is the starting distance of the far field; [P L (d0)] dB is the path loss at a standard distance of 1m; χ is a Gaussian random variable with a mean of zero and a standard deviation of σ; n is the path loss index under a specific environment; m is the path loss index of the signal passing through obstacles, and ω is the number of obstacles the signal passes through when it reaches the point. In some embodiments, if the types of obstacles the signal passes through when it reaches the point are at least two, and the path loss indexes of each type of obstacle are different, then the path loss model Among them, m i represents the path loss index of the i-th obstacle, ω i represents the number of obstacles of type i, and N represents the number of obstacles.

[0086] The variables that need to be fitted based on the signal strength of each point and the distance between each point and the Bluetooth chip are [P L (d0)] dB , n, m, χ. After fitting, we get [P L (d0)] dB , n, m, and χ, and the path loss model of the Bluetooth chip in the environment is obtained.

[0087] In this embodiment, by determining the number of obstacles and the path loss index of the obstacles, fitting is performed based on the number of obstacles, the path loss index of the obstacles, the signal strength of each point, and the distance between each point and the Bluetooth chip. This can fully consider the impact of obstacles in the environment on the signal strength, thereby obtaining a more accurate path loss model.

[0088] In one embodiment, a path loss model of the Bluetooth chip in the environment is obtained by fitting based on the signal strength of each point and the distance between each point and the Bluetooth chip, including:

[0089] Based on the signal strength of each point and the distance between each point and the Bluetooth chip, the initial path loss model of the Bluetooth chip in the environment is obtained;

[0090] Based on the signal strength of each point and the distance between each point and the Bluetooth chip, the initial path loss model of the Bluetooth chip in the environment is obtained;

[0091] Obtain the fitted signal strength at each point based on the initial path loss model;

[0092] When the difference between the fitted signal strength at multiple points and the actual signal strength is greater than a preset difference, the fitting variables in the initial path loss model are adjusted until the difference between the fitted signal strength at multiple points and the actual signal strength is less than the preset difference, thereby obtaining the path loss model of the Bluetooth chip in the environment in which it is located.

[0093] The initial path loss model represents the relationship between the fitted signal strength and the target distance, which is the distance between the location and the Bluetooth chip. Therefore, once the distance between the location and the Bluetooth chip is determined, the fitted signal strength at that location can be determined using the initial path loss model.

[0094] There are at least two situations in the fitted initial path loss model: one is that the difference between the fitted signal strength and the actual signal strength at most points is less than a preset difference, and the other is that the difference between the fitted signal strength and the actual signal strength at most points is greater than the preset difference. When the difference between the fitted signal strength and the actual signal strength at most points is less than the preset difference, the initial path loss model can be directly determined as the path loss model. When the difference between the fitted signal strength and the actual signal strength at most points is greater than the preset difference, the fitting variables in the initial path loss model need to be adjusted until the difference between the fitted signal strength and the actual signal strength at multiple points is less than the preset difference. For example, a total of 100 points are arranged for the Bluetooth chip. If the difference between the fitted signal strength and the actual signal strength of 90 points is determined to be less than the preset difference according to the fitted initial path loss model, the fitted initial path loss model can be directly determined as the final path loss model. If the difference between the fitted signal strength and the actual signal strength of 90 points is determined to be greater than the preset difference according to the fitted initial path loss model, the fitting variables in the initial path loss model need to be adjusted until the difference between the fitted signal strength and the actual signal strength of multiple points is less than the preset difference.

[0095] In some embodiments, the preset difference may be twice the standard deviation, wherein twice the standard deviation is determined based on the actual signal strength of each signal.

[0096] Specifically, the fitted path loss model is shown in the following figure: Figure 9 As shown. The horizontal axis node spacing represents the distance between the point and the Bluetooth chip, the vertical axis represents the absolute value of the signal strength at the point, the data point represents each point, the path loss curve is the fitted path loss model, the path loss curve of one standard deviation is based on the path loss curve, the curve is obtained by moving up and down by one standard deviation, and the path loss curve of two times the standard deviation is based on the path loss curve, the curve is obtained by moving up and down by two standard deviations. The path loss curve is specifically Among them, 18 is the path loss at the reference distance, and the reference distance d0 is 1 meter; 51 is the path loss exponent n multiplied by 10; d is the distance between the point and the Bluetooth chip; ω is the number of obstacles between the point and the Bluetooth chip; σ is a random number with a standard deviation of 3.7.

[0097] In this embodiment, when the difference between the fitted signal strength at multiple points and the actual signal strength is greater than a preset difference, the fitting variables in the initial path loss model are adjusted until the difference between the fitted signal strength at multiple points and the actual signal strength is less than the preset difference, thereby obtaining a path loss model of the Bluetooth chip in the environment in which it is located. This ensures that the path loss model can more accurately reflect the signal propagation characteristics in the actual environment, provide high-quality input parameters for Mesh simulation, and make the packet loss rate prediction results more realistic.

[0098] In one embodiment, the simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve are imported into the Mesh layer to perform Mesh simulation prediction. After obtaining the packet loss rate prediction result, the following steps are included:

[0099] Determining a plurality of signals to be sent, and adding noise to the plurality of signals to be sent to obtain a plurality of mixed signals;

[0100] Controlling the first simulation node to send multiple mixed signals to the second simulation node, controlling the second simulation node to receive the signals and demodulate each received signal, and counting the number of signals successfully demodulated by the second simulation node;

[0101] Based on the number of signals successfully demodulated by the second simulation node, a simulation packet error rate curve is drawn, and parameters in the simulation packet error rate curve are adjusted based on the packet error rate curve until the simulation packet error rate curve matches the packet error rate curve, so as to perform Mesh simulation based on the simulation packet error rate curve.

[0102] The first simulation node and the second simulation node may be simulation nodes corresponding to any model of a Bluetooth chip having a signal receiving and transmitting function.

[0103] The signal strength of the mixed signal transmitted by the first simulated node is within the target range corresponding to the second simulated node. The target range corresponding to the second simulated node can be determined based on the receiving sensitivity of the Bluetooth chip corresponding to the second simulated node. For example, if the second simulated node is a simulated node of Bluetooth chip A, and the receiving sensitivity of Bluetooth chip A is -90dB, then the target range corresponding to the second simulated node is (-90dB-X, -90dB+X), where X is an adjustable preset value.

[0104] When the second simulation node receives a signal, it demodulates the received signal to obtain valid information from the signal. Specifically, when the second simulation node demodulates the received signal, if the relay and retransmission information in the signal is obtained through demodulation, it is determined that the signal demodulation is successful. When counting the number of signals successfully demodulated by the second simulation node, only the number of mixed signals whose signal strength is within the target range is counted. For example, if the second simulation node successfully demodulates n mixed signals, but only the signal strength of m mixed signals is within the target range, then the number of signals successfully demodulated by the second simulation node is determined to be m.

[0105] The manner in which the first simulation node sends the mixed signal includes but is not limited to continuously sending multiple mixed signals to the first simulation node and sending a mixed signal at intervals of a preset time.

[0106] The formula for simulated background noise is:

[0107] noiseFloor=10log 10 (k·T·BW)+NF,

[0108] Where k is the Boltzmann constant; T is the ambient temperature; BW is the bandwidth; and NF is the noise factor. By adjusting the two parameters T and NF in the simulated background noise, the simulated packet error rate curve can be made to have a similar trend to the actual packet error rate curve, that is, the simulated packet error rate curve can match the actual packet error rate curve. Specifically, the simulated packet error rate curve is as follows: Figure 10 As shown, Figure 10 The horizontal axis represents the absolute value of the transmitted signal strength, and the vertical axis represents the packet error rate.

[0109] In this embodiment, a simulated packet error rate curve is drawn based on the number of mixed signals received by the second simulation node, and the parameters in the simulated packet error rate curve are adjusted based on the packet error rate curve until the simulated packet error rate curve matches the packet error rate curve, so as to perform Mesh simulation based on the simulated packet error rate curve. This ensures that the simulated packet error rate curve input to the Mesh layer is reliable, so that accurate packet loss rate prediction results can be output when performing Mesh simulation.

[0110] In one embodiment, the simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve are imported into the Mesh layer for Mesh simulation prediction to obtain a packet loss rate prediction result, including:

[0111] Import the simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve into the Mesh layer, and control the simulated sending node to generate the signal to be adjusted;

[0112] The signal to be adjusted is sampled according to a preset sampling rate to obtain a sampled signal, the frequency of the sampled signal is adjusted according to the modulation parameter, and the signal strength of the sampled signal is adjusted according to the waveform propagation distance and the path loss model to obtain an adjusted signal to be sent;

[0113] According to the simulated packet error rate curve, it is judged whether the signal to be sent can be received by the simulated receiving node; the waveform propagation distance is the distance between the simulated sending node and the simulated receiving node;

[0114] When the signal to be sent is received by the simulated receiving node, the received signal to be sent is demodulated to obtain demodulated data;

[0115] When the demodulated data includes target information indicating whether to relay and the number of retransmissions, a Mesh simulation prediction is performed to obtain a packet loss rate prediction result.

[0116] The simulated receiving node and the simulated transmitting node are simulation models of a Bluetooth chip with signal transceiver capabilities. The generated signal to be adjusted is an ideal signal. For example, an ideal 2.4G Bluetooth waveform is generated by the simulated node of the Bluetooth chip. The signal to be adjusted is a simulated signal.

[0117] The sampling rate is preset. The sampled signal is a digital signal.

[0118] Frequency adjustment refers to changing the frequency of the sampled signal when it is transmitted. For example, if the ideal frequency of the signal to be adjusted is 2402 MHz, and the sampling signal frequency is also 2402 MHz, the signal to be adjusted is adjusted based on the first frequency offset of 1 kHz in the modulation parameters and the second frequency offset of 3 kHz during the propagation process, so that the frequency of the adjusted signal to be transmitted is consistent with the frequency of the signal received by the chip in the actual scenario. Specifically, the sampling signal frequency is offset from 2402 MHz to 2402 MHz + 1 kHz + 3 kHz = 2402.004 MHz.

[0119] Signal strength adjustment refers to changing the signal strength of the sampled signal. For example, if the signal strength of the simulated signal to be adjusted is M, and the signal strength of the sampled signal is also M, then the signal strength obtained by substituting the waveform propagation distance into the path loss model is N, and N and M are not equal, the signal strength of the sampled signal is adjusted to MN so that the signal strength of the adjusted signal to be transmitted is consistent with the signal strength transmitted in the actual scenario.

[0120] In some embodiments, if the signal strength of the to-be-transmitted signal is greater than the receiving sensitivity of the simulated receiving node, it can be directly determined that the to-be-transmitted signal can be received by the simulated receiving node. Furthermore, if the signal strength of the to-be-transmitted signal is less than the receiving sensitivity of the simulated receiving node, whether the to-be-transmitted signal can be received by the simulated receiving node is determined based on the simulated packet error rate curve.

[0121] The number of simulated receiving nodes is at least one. Among the at least one simulated receiving node, there may be a node that can receive and demodulate the signal to be sent, and there may also be a node that cannot receive and / or demodulate the signal to be sent.

[0122] Mesh simulation means that the simulated receiving node relays and retransmits according to the relay and retransmission times in the target information. If the target information cannot be demodulated, the simulated receiving node will not perform Mesh simulation.

[0123] In this embodiment, the simulated packet error rate curve, modulation parameters, and path loss model corresponding to the packet error rate curve are imported into the Mesh layer, and the simulated sending node is controlled to generate a signal to be adjusted. The signal to be adjusted is sampled at a preset sampling rate to obtain a sampled signal. The sampled signal is frequency-adjusted according to the modulation parameters. The signal strength of the sampled signal is adjusted according to the waveform propagation distance and the path loss model to obtain an adjusted signal to be transmitted. Based on the simulated packet error rate curve, it is determined whether the signal to be transmitted can be received by the simulated receiving node. The waveform propagation distance is the distance between the simulated sending node and the simulated receiving node. When the signal to be transmitted is received by the simulated receiving node, the received signal to be transmitted is demodulated to obtain demodulated data. When the demodulated data includes target information indicating whether to relay and the number of retransmissions, a Mesh simulation prediction is performed to obtain a packet loss rate prediction result. In this way, the simulated packet error rate curve, modulation parameters, and path loss model involved in the RF physical layer can be directly combined with the Mesh layer to simulate the multi-hop transmission process in the simulation, thereby simplifying the simulation process while ensuring the integrity of the simulation and improving the efficiency and accuracy of obtaining the packet loss rate prediction result.

[0124] In some embodiments, by importing the simulated packet error rate curve, modulation parameters and path loss model corresponding to the packet error rate curve into the Mesh layer for Mesh simulation prediction, the predicted signal receiving node can also be output. The distribution of the output signal receiving and sending nodes is as follows: Figure 11 As shown in the figure, the horizontal and vertical axes represent the location of signal receiving nodes in the actual environment, the triangles represent signal transceiver nodes, and the rectangles represent gateways. Specifically, in the simulation, the signal transceiver nodes send two data packets each time. The gateway can receive the data sent by the signal transceiver nodes, but may lose one data packet. Table 2 shows the mesh network simulation results.

[0125] Table 2 Mesh network simulation results

[0126]

[0127] Table 3 shows the packet loss rate test results in a real-world environment. In Table 3, each node in the mesh network sent two data items 288 times, for a total of 576 data items. The gateway received data 288 times, but the total number of data items was not 576. This indicates that one of the two data items sent by the node may be lost, which is consistent with the simulation results.

[0128] Table 3 Packet loss rate test results

[0129]

[0130] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0131] Based on the same inventive concept, embodiments of the present application also provide a packet loss rate prediction device for implementing the aforementioned packet loss rate prediction method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more packet loss rate prediction device embodiments provided below can be found in the above-described limitations of the packet loss rate prediction method and will not be further elaborated here.

[0132] In one embodiment, Figure 12As shown, a packet loss rate prediction device is provided, comprising:

[0133] The information acquisition module 1202 is used to obtain the modulation parameters of the Bluetooth chip and the path loss model of the Bluetooth chip in the environment in which it is located;

[0134] The number acquisition module 1204 is used to determine the number of target signals received by the Bluetooth chip; the signal strength of the target signal is within the target range, and the target range is determined according to the receiving sensitivity of the Bluetooth chip;

[0135] A curve acquisition module 1206 is configured to draw a packet error rate curve of the Bluetooth chip within a target range based on the number of target signals received by the Bluetooth chip and the signal strength of the target signals;

[0136] The simulation prediction module 1208 is used to import the simulated packet error rate curve, modulation parameters and path loss model corresponding to the packet error rate curve into the Mesh layer to perform Mesh simulation prediction and obtain a packet loss rate prediction result.

[0137] Each module in the packet loss rate prediction device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0138] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 13 As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store modulation parameters, path loss models, the number of target signals, target range, receiving sensitivity, packet error rate curves, and packet loss rate prediction results. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a packet loss rate prediction method is implemented.

[0139] Those skilled in the art will understand that Figure 13 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0140] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0141] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0142] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0143] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0144] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0145] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0146] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A packet loss rate prediction method, characterized in that: The method comprises: Obtaining modulation parameters of a Bluetooth chip and a path loss model of the Bluetooth chip in the environment in which it is located; Determining the number of target signals received by the Bluetooth chip; wherein the signal strength of the target signal is within a target range, and the target range is determined according to the receiving sensitivity of the Bluetooth chip; Drawing a packet error rate curve of the Bluetooth chip within a target range based on the number of target signals received by the Bluetooth chip and the signal strength of the target signals; The simulated packet error rate curve corresponding to the packet error rate curve, the modulation parameters and the path loss model are imported into the Mesh layer to perform Mesh simulation prediction to obtain a packet loss rate prediction result.

2. The method according to claim 1, characterized in that The obtaining of the modulation parameters of the Bluetooth chip includes: When the Bluetooth chip sends a signal, obtaining a first frequency of a leading portion of a data packet carried by the sent signal and a preset second frequency, and determining a difference between the first frequency and the second frequency as a first frequency offset; when the sent signal is received, obtaining a third frequency of the leading portion, and determining a difference between the third frequency and the first frequency as a second frequency offset; When the Bluetooth chip sends a signal carrying a first sequence, obtaining a first frequency deviation average value between a plurality of bits in the first sequence; When the Bluetooth chip sends a signal carrying a second sequence, obtaining a second frequency deviation average value between a plurality of bits in the second sequence; the first sequence and the second sequence are inconsistent binary sequences; Obtaining a frequency difference between any two third sequences separated by a preset time in the payload portion of the data packet; The first frequency offset, the second frequency offset, the first frequency offset average value, the second frequency offset average value, and the frequency difference are determined as modulation parameters.

3. The method according to claim 1, characterized in that The process of obtaining the path loss model of the Bluetooth chip in the environment includes: In the vicinity of the Bluetooth chip, multiple points are evenly arranged at preset intervals; When the Bluetooth chip sends a signal, obtaining the signal strength of each of the points; Fitting is performed based on the signal strength of each of the points and the distance between each of the points and the Bluetooth chip to obtain a path loss model of the Bluetooth chip in the environment in which it is located.

4. The method according to claim 3, characterized in that The method further comprises: evenly arranging a plurality of points in a vicinity of the Bluetooth chip at preset intervals, including: If there is an obstacle in the vicinity of the Bluetooth chip, multiple points are arranged in the vicinity according to a preset distance and the position of the obstacle.

5. The method according to claim 4, characterized in that The fitting based on the signal strength of each point and the distance between each point and the Bluetooth chip to obtain a path loss model of the Bluetooth chip in the environment includes: determining the number of obstacles and the path loss index of the obstacles; Fitting is performed based on the number of obstacles, the path loss index of the obstacles, the signal strength of each point, and the distance between each point and the Bluetooth chip to obtain a path loss model of the Bluetooth chip in the environment.

6. The method according to claim 3, characterized in that The fitting based on the signal strength of each point and the distance between each point and the Bluetooth chip to obtain a path loss model of the Bluetooth chip in the environment includes: Performing fitting based on the signal strength of each point and the distance between each point and the Bluetooth chip to obtain an initial path loss model of the Bluetooth chip in the environment in which it is located; Obtaining a fitted signal strength at each of the points based on the initial path loss model; When the difference between the fitted signal strength at multiple points and the actual signal strength is greater than a preset difference, the fitting variables in the initial path loss model are adjusted until the difference between the fitted signal strength at multiple points and the actual signal strength is less than the preset difference, thereby obtaining the path loss model of the Bluetooth chip in the environment in which it is located.

7. The method according to claim 1, characterized in that After importing the simulated packet error rate curve corresponding to the packet error rate curve, the modulation parameters, and the path loss model into the Mesh layer to perform Mesh simulation prediction and obtain the packet loss rate prediction result, the method includes: Determining a plurality of signals to be sent, and adding noise to the plurality of signals to be sent to obtain a plurality of mixed signals; Controlling the first simulation node to send the plurality of mixed signals to the second simulation node, controlling the second simulation node to receive signals and demodulate each received signal, and counting the number of signals successfully demodulated by the second simulation node; Based on the number of signals successfully demodulated by the second simulation node, a simulation packet error rate curve is drawn, and parameters in the simulation packet error rate curve are adjusted based on the packet error rate curve until the simulation packet error rate curve matches the packet error rate curve, so as to perform Mesh simulation based on the simulation packet error rate curve.

8. The method according to claim 1, characterized in that The step of importing the simulated packet error rate curve corresponding to the packet error rate curve, the modulation parameters, and the path loss model into the Mesh layer to perform Mesh simulation prediction to obtain a packet loss rate prediction result includes: Importing the simulated packet error rate curve corresponding to the packet error rate curve, the modulation parameters, and the path loss model into the Mesh layer, and controlling the simulated sending node to generate a signal to be adjusted; Sampling the signal to be adjusted according to a preset sampling rate to obtain a sampled signal, frequency-adjusting the sampled signal according to the modulation parameter, and adjusting the signal strength of the sampled signal according to the waveform propagation distance and the path loss model to obtain an adjusted signal to be transmitted; According to the simulated packet error rate curve, it is determined whether the signal to be sent can be received by the simulated receiving node; the waveform propagation distance is the distance between the simulated sending node and the simulated receiving node; When the signal to be sent is received by the simulated receiving node, demodulating the received signal to be sent to obtain demodulated data; When the demodulated data includes target information indicating whether to relay and the number of retransmissions, a Mesh simulation prediction is performed to obtain a packet loss rate prediction result.

9. A packet loss rate prediction device, characterized in that: The device comprises: An information acquisition module, configured to acquire modulation parameters of a Bluetooth chip and a path loss model of the Bluetooth chip in its environment; a quantity acquisition module, configured to determine the number of target signals received by the Bluetooth chip; the signal strength of the target signal is within a target range, and the target range is determined according to the receiving sensitivity of the Bluetooth chip; a curve acquisition module, configured to draw a packet error rate curve of the Bluetooth chip within a target range based on the number of target signals received by the Bluetooth chip and the signal strength of the target signals; The simulation prediction module is used to import the simulated packet error rate curve corresponding to the packet error rate curve, the modulation parameters and the path loss model into the Mesh layer to perform Mesh simulation prediction and obtain a packet loss rate prediction result.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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