A USRP satellite communication simulation system based on iterative stable prediction of communication status

Abstract

The present invention discloses a USRP satellite communication simulation system based on iterative and stable prediction of communication states, belonging to the field of mobile communication technology. The system comprises a simulation system and a hardware-in-the-loop access system. The simulation system includes a USRP device, a channel simulator, and a ground gateway device. The channel simulator runs simulation software. The USRP device simulates the communication behavior of the satellite and payload. The channel simulator simulates the actual channel environment and electromagnetic interference. The simulation system models and simulates the behavior of the satellite, payload, communication link, core network, and ground gateway, generating experimental data, performance indicators, and statistical results. The hardware-in-the-loop access system displays the hardware-in-the-loop communication status based on the channel environment and satellite data provided by the simulation system. This system allows users to experience the true experience of satellite internet through simulated terminal communications and data services.

Description

Technical Field

[0001] The present invention relates to the field of mobile communication technology, in particular to a USRP satellite communication simulation system based on iterative stable prediction of communication states. Background Art

[0002] The development and implementation of carrier aggregation technology has enabled more efficient spectrum utilization and improved spectrum efficiency. By simultaneously aggregating multiple discrete available carriers, carrier aggregation supports greater transmission bandwidth, meeting the demands for high peak rates and system capacity. In scenarios where spectrum availability is dynamically changing, carrier aggregation can flexibly aggregate adjacent or non-adjacent unused spectrum to provide greater transmission bandwidth. This aggregation approach more effectively utilizes limited spectrum resources and delivers greater practical value.

[0003] To enable efficient spectrum resource development and testing, the Universal Software Radio Peripheral (USRP) is widely used in communication system design. The USRP, combined with open-source software-defined radio platforms such as GNU Radio, forms a complete hardware and software platform for communication system design. This software-defined approach, combining open-source and user-defined modules, enables cost-effective, high-efficiency communication system development and testing. Leveraging tools such as the USRP and GNU Radio, a hardware-in-the-loop simulation platform for dynamic spectrum management can be developed. This platform utilizes cognitive users to detect spectrum availability and dynamically allocate operating frequency bands to them. This enables dynamic spectrum management and provides more flexible spectrum utilization.

[0004] However, existing technologies have problems with the accuracy of predicting the communication status of semi-physical access simulation software systems. The simulation software cannot display the semi-physical communication status or specify "soft" satellite or terminal mapping, and the adaptability and flexibility of communication scenarios are insufficient. Summary of the Invention

[0005] In view of this, the present invention discloses a USRP satellite communication simulation system based on iterative stable prediction of communication status. By combining USRP devices, channel simulators, simulation software and semi-physical access systems, comprehensive simulation of a small number of satellites, payloads and related communication links is achieved.

[0006] The technical solution adopted in the present invention is:

[0007] A USRP satellite communication simulation system based on iterative stable prediction of communication status, including a simulation system and a semi-physical access system;

[0008] The simulation system models and simulates the behavior of satellites, payloads and communication links, core networks and ground gateways, generates experimental data, performance indicators and statistical results, and provides adjustment and configuration of various parameters and scenarios;

[0009] The semi-physical access system displays the communication status of the semi-physical device according to the channel environment and satellite data provided by the simulation system.

[0010] Furthermore, the simulation system includes a USRP device, a channel simulator and a ground gateway device, and the channel simulator runs simulation software;

[0011] The USRP device is configured as a radio signal transmitter and receiver for the satellite and payload respectively through software-defined radio operations, and transmits data through wireless signals to simulate the communication behavior of the satellite and payload;

[0012] The channel simulator simulates real channel environment and electromagnetic interference, including channel fading, multipath propagation, and multipath interference, and simulates and evaluates the performance of the satellite communication system under various channel conditions.

[0013] Furthermore, the system works as follows:

[0014] Step S1: Obtain the positions of the satellite, payload, and HIL, and calculate the average distance between the satellite, payload, and HIL:

[0015] ,

[0016] Where D represents the average distance, , , are the x-axis, y-axis, and z-axis coordinates of each visible satellite and payload, respectively. X, Y, and Z represent the x-axis, y-axis, and z-axis coordinates of the semi-physical object. i is the number of the visible satellite and payload, and n is the number of visible satellites and payloads.

[0017] Step S2: Obtain the interference in the channel environment, including the fading depth and fading duration of the channel fading, as well as the interference power and interference signal-to-noise ratio of the multipath interference, and calculate the interference factor:

[0018] ,

[0019] Where, Represents the interference factor in the channel environment, k is the weight, is the fading depth of the channel fading, is the fading duration, T is the communication time, represents the time proportion of channel fading, is the interference power of multipath interference, represents the noise power, represents the interference signal-to-noise ratio;

[0020] Step S3: Obtain the signal quality of the simulation experiment data, including the signal-to-noise ratio and bit error rate, and obtain the throughput and delay of the simulation experiment data, and calculate the signal quality:

[0021] ,

[0022] Where, is the simulated signal quality, represents the signal quality coefficient of the simulation experimental data, is the power of the simulated experimental data, represents the noise power, represents the signal-to-noise ratio, is the bit error rate, is the throughput of the simulation experimental data, Represents the delay of simulation experimental data;

[0023] Step S4: Iterate the simulation experiment. In each iteration, the average distance, interference factor and signal quality are calculated once through steps S1, S2 and S3. The average distance, interference factor and signal quality of the j-th simulation experiment are expressed as The average distance, interference factor and signal quality of the first j simulation experiments are , the offset of the jth simulation experiment is:

[0024] ,

[0025] Where, is the offset of the j-th simulation experiment, 、 、 is the weight;

[0026] When the absolute value of the difference between the offsets of the j-th and j-1-th simulation experiments is less than the threshold, the simulation experiment ends, otherwise the iteration continues;

[0027] Step S5: Calculate the communication status judgment value S of the semi-physical object according to the number N of iterative simulation experiments in step S4:

[0028] ,

[0029] in, Indicates rounding down;

[0030] If S is greater than 0.5, it indicates that the communication state is stable, otherwise it indicates that the communication state is unstable.

[0031] The beneficial effects of the present invention are:

[0032] 1. The present invention realizes comprehensive simulation of a small number of satellites, payloads and related communication links by combining USRP devices, channel simulators, simulation software and semi-physical access systems.

[0033] 2. The present invention can not only simulate the communication behavior of satellites and payloads, but also simulate the real channel environment and electromagnetic interference.

[0034] 3. The present invention uses the satellite data and channel environment and simulation data provided by the simulation system to iteratively and stably predict the semi-physical communication status. By specifying "soft" satellite or terminal mapping, users can truly experience the use of satellite Internet.

[0035] In short, the present invention can predict the communication status of the semi-physical access simulation software system through the channel environment and simulation data, meet the growing communication needs, and allow users to truly experience the use of satellite Internet through the communication and data services of the simulated terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The figure is a structural diagram of a USRP satellite communication simulation system based on iterative stable prediction of communication status in an embodiment of the present invention.

[0037] Figure 2 The figure is a schematic diagram of the principle of a USRP satellite communication simulation system based on iterative stable prediction of communication status in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The technical solution of the present invention is described in detail below with reference to the accompanying drawings.

[0039] A USRP satellite communication simulation system based on iterative stable prediction of communication status, such as Figure 1 As shown, it includes simulation system and semi-physical access system;

[0040] The simulation system models and simulates the behavior of satellites, payloads and communication links, core networks and ground gateways, generates experimental data, performance indicators and statistical results, and provides adjustment and configuration of various parameters and scenarios;

[0041] The semi-physical access system displays the communication status of the semi-physical device according to the channel environment and satellite data provided by the simulation system.

[0042] This system utilizes USRP devices for Software Defined Radio (SDR) operations to simulate satellite and payload communication behavior. USRP devices are configured as radio signal transmitters and receivers for the satellite and payload, respectively, enabling simulation of real-world communication processes and data transmission via wireless signals. A channel simulator simulates the actual satellite and payload channels, along with realistic channel environments and electromagnetic interference, including channel fading, multipath propagation, and multipath interference. This allows for a more realistic assessment of communication link performance and reliability, simulating and evaluating the performance of satellite communication systems under various channel conditions. The simulation system models and simulates the behavior of satellites, payloads, communication links, core networks, and ground gateways, generating experimental data, performance metrics, and statistical results, providing adjustments and configurations for various parameters and scenarios. The hardware-in-the-loop access system allows users to experience real-world usage in a simulated environment. Based on the satellite data and channel environment provided by the simulation system and the iterations of the simulated data, the system can stably predict hardware-in-the-loop communication states and specify "soft" satellite or terminal mappings. This system allows users to experience the true experience of satellite internet through simulated terminal communications and data services.

[0043] like Figure 2 As shown, the working process of the system is as follows:

[0044] S1: Get the positions of the satellite, payload and HIL, and calculate the average distance between the satellite, payload and HIL:

[0045] ,

[0046] Where D represents the average distance, , , are the x-axis, y-axis, and z-axis coordinates of each visible satellite and payload, respectively. X, Y, and Z represent the x-axis, y-axis, and z-axis coordinates of the semi-physical object. i is the number of the visible satellite and payload, and n is the number of visible satellites and payloads.

[0047] S2: Obtain the interference in the channel environment, including the fading depth and fading duration of the channel fading, the interference power and interference signal-to-noise ratio of multipath interference, and calculate the interference factor:

[0048] ,

[0049] Where, represents the interference factor in the channel environment, is the fading depth of the channel fading, is the fading duration, is the interference power of multipath interference, represents its interference signal-to-noise ratio, where represents the noise power. k is the weight, which is determined as follows:

[0050] In urban high-interference environments, the value range is 1.2-1.5;

[0051] In the suburban area, the interference environment is in the range of 0.8-1.2;

[0052] In an open and low-interference environment, the value range is 0.5-0.8.

[0053] S3: Obtain the signal quality of the simulation data, including the signal-to-noise ratio and bit error rate, and obtain the throughput and delay of the simulation data to calculate the signal quality:

[0054] ,

[0055] Where, is the simulated signal quality, represents the signal quality coefficient of the simulation experimental data, is the power of the simulated experimental data, represents the noise power, represents the signal-to-noise ratio, is the bit error rate, is the throughput of the simulation experimental data, Represents the delay of simulation experimental data.

[0056] S4: Iterate the simulation experiment. In each iteration, the average distance, interference factor and signal quality are calculated once through steps S1, S2 and S3; the average distance, interference factor and signal quality of the j-th simulation experiment can be expressed as The average distance, interference factor and signal quality of the first j simulation experiments are recorded as , calculate the offset of the jth simulation experiment for:

[0057] ,

[0058] In the formula, the weight Adjust according to communication requirements, and the sum is 1. Specifically:

[0059] For long distance communication: The values ​​are 0.6, 0.2, and 0.2, respectively. At this time, the satellite is far away and the distance factor is dominant;

[0060] For high-interference environments: The values ​​are 0.2, 0.5, and 0.3 respectively. In this case, it is a city or an area with severe multipath interference, where the interference factor is dominant.

[0061] For high quality requirements: The values ​​are 0.3, 0.2, and 0.5 respectively. This is suitable for applications with high requirements on communication quality, where signal quality takes precedence.

[0062] When the absolute value of the difference between the offset of the j-th and j-1-th simulation experiments is less than the threshold , that is, when the following conditions are met:

[0063] ,

[0064] The simulation experiment ends.

[0065] In addition, the iteration stops when the maximum number of iterations is reached.

[0066] Generally speaking, It can be set to 0.03, and the maximum number of times is set to 300.

[0067] S5: Predict the communication status of the semi-physical hardware. Assume that a total of N simulation experiments are performed, calculate The average value of the experiments is taken as the communication status judgment value S (for example, if 53 experiments are performed, the average value of experiments 47 to 53 is taken):

[0068] ,

[0069] in, Indicates rounding down.

[0070] The S value is calculated using the above formula. If S is greater than 0.5, stable and reliable communication is possible. Otherwise, stable and reliable communication is not possible. Based on this, the communication status of the semi-physical hardware can be obtained.

[0071] In summary, this invention combines USRP devices, a channel simulator, simulation software, and a hardware-in-the-loop access system to achieve comprehensive simulation of a small number of satellites, payloads, and related communication links. This system simulates not only the communication behavior of satellites and payloads, but also the actual channel environment and electromagnetic interference. By using the satellite data and channel environment provided by the simulation system, and by iteratively predicting hardware-in-the-loop communication states, users can specify "soft" satellite or terminal mappings, providing a realistic satellite internet experience.

[0072] The embodiments of the present application have been described above, but the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the guidance of this application, those skilled in the art can also make many forms without departing from the scope of protection of the present application and the claims, all of which fall within the protection of this application.

Claims

1. A USRP satellite communication simulation system based on iterative stable prediction of communication status, characterized in that: Including simulation system and semi-physical access system; The simulation system models and simulates the behavior of satellites, payloads and communication links, core networks and ground gateways, generates experimental data, performance indicators and statistical results, and provides adjustment and configuration of various parameters and scenarios; The semi-physical access system displays the communication status of the semi-physical device according to the channel environment and satellite data provided by the simulation system; The simulation system includes a USRP device, a channel simulator and a ground gateway device, and the channel simulator runs simulation software; The USRP device is configured as a radio signal transmitter and receiver for the satellite and payload respectively through software-defined radio operations, and transmits data through wireless signals to simulate the communication behavior of the satellite and payload; The channel simulator simulates real channel environments and electromagnetic interference, including channel fading, multipath propagation, and multipath interference, to simulate and evaluate the performance of satellite communication systems under various channel conditions; The system works as follows: Step S1: Obtain the positions of the satellite, payload, and HIL, and calculate the average distance between the satellite, payload, and HIL: ， Where D represents the average distance, , , are the x-axis, y-axis, and z-axis coordinates of each visible satellite and payload, respectively. X, Y, and Z represent the x-axis, y-axis, and z-axis coordinates of the semi-physical object. i is the number of the visible satellite and payload, and n is the number of visible satellites and payloads. Step S2: Obtain the interference in the channel environment, including the fading depth and fading duration of the channel fading, as well as the interference power and interference signal-to-noise ratio of the multipath interference, and calculate the interference factor: ， Where, Represents the interference factor in the channel environment, k is the weight, is the fading depth of the channel fading, is the fading duration, T is the communication time, represents the time proportion of channel fading, is the interference power of multipath interference, represents the noise power, represents the interference signal-to-noise ratio; Step S3: Obtain the signal quality of the simulation experiment data, including the signal-to-noise ratio and bit error rate, and obtain the throughput and delay of the simulation experiment data, and calculate the signal quality: ， Where, is the simulated signal quality, represents the signal quality coefficient of the simulation experimental data, is the power of the simulated experimental data, represents the noise power, represents the signal-to-noise ratio, is the bit error rate, is the throughput of the simulation experimental data, Represents the delay of simulation experimental data; Step S4: Iterate the simulation experiment. In each iteration, the average distance, interference factor and signal quality are calculated once through steps S1, S2 and S3. The input parameters of the j-th simulation experiment are expressed as The average value of the parameters of the first j simulation experiments is , the offset of the input parameters of the jth simulation experiment is: ， Where, is the offset of the input parameters for the jth simulation experiment, 、 、 is the weight; When the absolute value of the difference between the offset of the input parameters of the j-th and j-1-th simulation experiments is less than the threshold, the simulation experiment ends, otherwise the iteration continues; Step S5: Calculate the communication status judgment value S of the semi-physical object according to the number N of iterative simulation experiments in step S4: ， in, Indicates rounding down, with subscript j They represent the j-th simulation experiment value; If S is greater than 0.5, it indicates that the communication state is stable, otherwise it indicates that the communication state is unstable.

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