USRP satellite communication simulation system based on communication state iteration stability prediction

Abstract

The invention discloses a USRP satellite communication simulation system based on communication state iteration stability prediction, and belongs to the technical field of mobile communication. The system comprises an analogue simulation system and a semi-physical access system, the analogue simulation system comprises USRP equipment, a channel simulator and ground gateway station equipment, and simulation software runs in the channel simulator; the USRP equipment is used for simulating communication behaviors of a satellite and a load; the channel simulator is used for simulating a real channel environment and electromagnetic interference; the analogue simulation system is used for modeling and simulating behaviors of a satellite, a load, a communication link, a core network and a ground gateway station to generate experimental data, performance indexes and statistical results; and the semi-physical access system displays the communication state of the semi-physical according to the channel environment and the satellite data provided by the analogue simulation system. According to the invention, the user can truly feel the use experience of the satellite internet through the communication and data service of the simulation terminal.

Description

Technical Field

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

[0002] The development and practice of carrier aggregation technology can achieve more efficient spectrum utilization and improve spectrum efficiency. Carrier aggregation technology can support larger transmission bandwidth and meet the needs of high peak rate and system capacity by aggregating multiple discrete available carrier units at the same time. In the scenario where the spectrum availability status is real-time and dynamically available, carrier aggregation technology can flexibly aggregate adjacent or non-adjacent idle available spectrum to provide larger transmission bandwidth. This aggregation method can more effectively utilize limited spectrum resources and provide higher practical value.

[0003] In order to achieve efficient spectrum resource development and testing, the Universal Software Radio Peripheral (USRP) is widely used in communication system design. USRP combines open source software-defined radio platforms such as GNU Radio to form a complete software and hardware communication system design platform. Through software definition, combined with open source modules and user-defined modules, low-cost and high-efficiency communication system development and testing can be achieved. Using tools such as USRP and GNU Radio, a semi-physical simulation platform for dynamic spectrum management can be developed. The platform uses cognitive users to detect the available status of the spectrum and dynamically allocate working frequency bands to cognitive users. This can achieve dynamic management of the spectrum and provide a more flexible spectrum utilization method.

[0004] However, the existing technology has the problem of insufficient accuracy in 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, which 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.

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

[0007] A USRP satellite communication simulation system based on iterative stable prediction of communication status includes a simulation system and a semi-physical access system. The simulation system includes a USRP device, a channel simulator and a ground gateway device. Simulation software runs in the channel simulator.

[0008] The USRP device is configured as a radio signal transmitter and receiver of the satellite and the payload through software-defined radio operations, and transmits data through wireless signals to simulate the communication behavior of the satellite and the payload;

[0009] The channel simulator simulates the 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;

[0010] 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;

[0011] The semi-physical access system displays the communication status of the semi-physical according to the channel environment and satellite data provided by the simulation system;

[0012] The system works as follows:

[0013] S1: Get the positions of satellites, payloads and semi-physical objects, and calculate the average distances between satellites, payloads and semi-physical objects:

[0014]

[0015] In the formula, D represents the average distance, x i ,y i ,z i 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, and n is the number of visible satellites and payloads;

[0016] 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 multipath interference, and calculate the interference factor:

[0017]

[0018] In the formula, I represents the interference factor in the channel environment, k is the weight, and F d is the fading depth of the channel fading, F T is the fading duration, U P is the interference power of multipath interference, represents the interference signal-to-noise ratio, where N P represents the noise power;

[0019] 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 to calculate the signal quality:

[0020]

[0021] Where M i is the signal quality of the ith simulation, g represents the signal quality coefficient of the simulation experimental data, P i is the power of the ith simulation experimental data, N P represents the noise power, represents the signal-to-noise ratio, e represents the bit error rate, V represents the throughput of the simulation experiment data, and C represents the delay of the simulation experiment data;

[0022] S4: Using the average distance, interference factor and signal quality obtained by S1, S2 and S3, iteratively predict the communication status of the semi-physical object, where the input parameter of the i-th simulation experiment is represented by IN i =(D,I,M) i The average value of the parameters in the previous i simulation experiments is The offset of the input parameters of the ith simulation experiment is:

[0023]

[0024] In the formula, E i is the offset of the input parameters of the ith simulation experiment, μ1, μ2, and μ3 are weights;

[0025] When the absolute value of the offset between the input parameters of the ith and i-1th simulation experiments is less than the threshold, the simulation experiment is terminated.

[0026] The beneficial effects of the present invention are:

[0027] 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.

[0028] 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.

[0029] 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, and enables users to truly experience the use of satellite Internet by specifying "soft" satellites or terminal mappings.

[0030] In summary, 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

[0031] Figure 1The structure diagram of a USRP satellite communication simulation system based on iterative stable prediction of communication status in an embodiment of the present invention.

[0032] Figure 2 The schematic diagram is a principle diagram of a USRP satellite communication simulation system based on iterative stable prediction of communication status in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The technical solution of the present invention is described in detail below with reference to the accompanying drawings.

[0034] A USRP satellite communication simulation system based on iterative stable prediction of communication status, such as Figure 1 As shown, it includes a simulation system and a semi-physical access system. The simulation system includes a USRP device, a channel simulator and a ground gateway device. The channel simulator runs simulation software.

[0035] The USRP device is configured as a radio signal transmitter and receiver of the satellite and the payload through software defined radio (Software Defined Radio, SDR) operation, and transmits data through wireless signals to simulate the communication behavior of the satellite and the payload;

[0036] The channel simulator simulates the real channel environment and electromagnetic interference, including phenomena such as channel fading, multipath propagation, and multipath interference, and simulates and evaluates the performance of the satellite communication system under various channel conditions;

[0037] 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;

[0038] The semi-physical access system allows users to have a real usage experience in a simulation environment. According to the channel environment and satellite data provided by the simulation system, the semi-physical communication status is displayed, and "soft" satellite or terminal mapping can be specified.

[0039] like Figure 2 As shown, the working steps of the simulation system are as follows:

[0040] S1: Get the positions of satellites, payloads and semi-physical objects, and calculate the average distances between satellites, payloads and semi-physical objects:

[0041]

[0042] In the formula, D represents the average distance, x i ,y i ,z iare 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, and n is the number of visible satellites and payloads;

[0043] 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 multipath interference, and calculate the interference factor:

[0044]

[0045] In the formula, I represents the interference factor in the channel environment, k is the weight, and F d is the fading depth of the channel fading, F T is the fading duration, U P is the interference power of multipath interference, represents the interference signal-to-noise ratio, where N P represents the noise power;

[0046] 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 to calculate the signal quality:

[0047]

[0048] Where M i is the signal quality of the ith simulation, g represents the signal quality coefficient of the simulation experimental data, P i is the power of the ith simulation experimental data, N P represents the noise power, represents the signal-to-noise ratio, e represents the bit error rate, V represents the throughput of the simulation experiment data, and C represents the delay of the simulation experiment data;

[0049] S4: Using the average distance, interference factor and signal quality obtained by S1, S2 and S3, iteratively predict the communication status of the semi-physical object, where the input parameter of the i-th simulation experiment is represented by IN i =(D,I,M) i The average value of the parameters in the previous i simulation experiments is The offset of the input parameters of the ith simulation experiment is:

[0050]

[0051] In the formula, E i is the offset of the input parameters of the ith simulation experiment, μ1, μ2, and μ3 are weights;

[0052] When the absolute value of the offset between the input parameters of the i-th and i-1-th simulation experiments is less than the threshold, the simulation experiment ends.

[0053] In this example, we will take The average value of the experimental inputs is used as the actual input to predict the communication status of the semi-physical object (if 53 experiments are conducted, the average value of the experimental inputs from 47 to 53 is taken):

[0054]

[0055] The S value is obtained by the above formula. It is stipulated that when S is greater than 0.5, it means that stable and reliable communication can be carried out. On the contrary, it means that stable and reliable communication cannot be carried out. Based on this, the semi-physical communication state can be obtained.

[0056] The embodiments of the present application are described above, but the present application is not limited to the above specific implementations. The above specific implementations are merely illustrative and not restrictive. Under the enlightenment of the present 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 belong to the protection of the present application.

Claims

1. A USRP satellite communication simulation system based on iterative stable prediction of communication status, characterized in that: It includes a simulation system and a semi-physical 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 is configured as a radio signal transmitter and receiver of the satellite and the payload through software-defined radio operations, and transmits data through wireless signals to simulate the communication behavior of the satellite and the payload; The channel simulator simulates the 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; 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 according to the channel environment and satellite data provided by the simulation system; The system works as follows: S1: Get the positions of satellites, payloads and semi-physical objects, and calculate the average distances between satellites, payloads and semi-physical objects: In the formula, D represents the average distance, x i ,y i ,z i 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, and n is the number of visible satellites and payloads; 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 multipath interference, and calculate the interference factor: In the formula, I represents the interference factor in the channel environment, k is the weight, and F d is the fading depth of the channel fading, F T is the fading duration, U P is the interference power of multipath interference, represents the interference signal-to-noise ratio, where N P represents the noise power; 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 to calculate the signal quality: Where M i is the signal quality of the ith simulation, g represents the signal quality coefficient of the simulation experimental data, P i is the power of the ith simulation experimental data, N P represents the noise power, represents the signal-to-noise ratio, e represents the bit error rate, V represents the throughput of the simulation experiment data, and C represents the delay of the simulation experiment data; S4: Using the average distance, interference factor and signal quality obtained by S1, S2 and S3, iteratively predict the communication status of the semi-physical object, where the input parameter of the i-th simulation experiment is represented by IN i =(D,I,M) i The average value of the parameters in the previous i simulation experiments is The offset of the input parameters of the ith simulation experiment is: In the formula, E i is the offset of the input parameters of the ith simulation experiment, μ1, μ2, and μ3 are weights; When the absolute value of the offset between the input parameters of the ith and i-1th simulation experiments is less than the threshold, the simulation experiment is terminated.

Images