Channel prediction system and method for short-wave broadcast
By using a channel prediction system to conduct all-weather, all-time ionospheric detection and data analysis, the channel perception and link prediction problems of shortwave broadcasting have been solved, enabling accurate coverage of shortwave broadcasting and effective blocking of illegal broadcasts.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-22
- Publication Date
- 2026-03-13
AI Technical Summary
Existing technologies lack effective channel sensing and link prediction capabilities, resulting in insufficient accurate coverage of shortwave broadcasts and inadequate ability to block illegal broadcasts globally.
A channel prediction system is adopted, including a channel prediction front-end subsystem and a channel prediction back-end subsystem. It utilizes ionospheric transceiver equipment, ionospheric measurement and reception equipment, and ionospheric transmission equipment to conduct all-weather, all-time ionospheric detection. Combined with subsystems such as coverage prediction, short-term and long-term channel prediction, quality assessment and intelligent early warning, it realizes the inversion and calculation of ionospheric characteristic parameters and data analysis.
It has improved the accuracy of shortwave broadcasting coverage and the ability to block illegal broadcasts, providing strong technical support for national shortwave broadcasting and ensuring the rights to high-quality broadcasting and listening.
Smart Images
Figure CN121664334A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of shortwave broadcasting, and specifically relates to a channel prediction system and method for shortwave broadcasting, which can be used for accurate shortwave broadcast coverage and blocking of illegal broadcasts. Background Technology
[0002] With economic development, shortwave channels and electromagnetic background environments have become increasingly complex, seriously affecting the scheduling accuracy, listening quality, and ability to suppress interference from illegal broadcasts. This is mainly manifested in the following ways: (1) Currently, due to the lack of ionospheric environmental data, the shortwave broadcasting system relies solely on the International Reference Ionospheric (IRI) model or the ITU-533 model, resulting in low coverage prediction and quality assessment capabilities. On the one hand, this seriously affects the safe broadcasting management and high-quality broadcasting guarantee of shortwave broadcasting globally. On the other hand, shortwave broadcasting suffers from spillover effects in various experimental tasks.
[0003] (2) The realization of shortwave broadcast quality early warning and suppression capabilities is based on multi-source data such as frequency, station, equipment, antenna and ionospheric environment. At present, due to the serious lack of ability to acquire and master ionospheric characteristics, there is a lack of real-time and effective channel perception and link prediction capabilities.
[0004] Currently, there is no effective channel sensing and link prediction system for shortwave broadcasting, making it difficult to guarantee the accurate global coverage of my country's shortwave broadcasting and the ability to block illegal broadcasts. Summary of the Invention
[0005] The technical problem to be solved by this invention is to address the gap in channel sensing and link prediction technology for shortwave broadcasting, and to provide an effective channel prediction system and method for shortwave broadcasting, which can improve the accurate coverage capability of shortwave broadcasting and the ability to block illegal broadcasts.
[0006] The present invention adopts the following technical solution: An improved channel prediction system for shortwave broadcasting includes a channel prediction front-end subsystem and a channel prediction back-end subsystem. The channel prediction front-end subsystem includes ionospheric transceiver equipment, ionospheric measurement and reception equipment, and ionospheric transmission equipment. The channel prediction back-end subsystem includes a coverage prediction subsystem, a short-term channel prediction subsystem, a long-term channel prediction subsystem, a channel link prediction subsystem, a channel quality assessment and intelligent early warning subsystem, a channel area optimization and reconstruction subsystem, a planning and task inversion subsystem, a channel situation display subsystem, a channel auxiliary decision-making subsystem, and a data management subsystem.
[0007] Furthermore, the data management subsystem receives and stores the ionospheric sounding data acquired by the channel prediction front-end subsystem, and distributes the ionospheric sounding data to the short-term channel prediction subsystem and the long-term channel prediction subsystem. The short-term channel prediction subsystem generates short-term channel prediction data, and the long-term channel prediction subsystem generates long-term channel prediction data.
[0008] Furthermore, the coverage prediction subsystem completes coverage effect prediction based on short-term and long-term channel prediction data, generating coverage prediction and analysis data. The channel link prediction subsystem completes channel link prediction based on short-term and long-term channel prediction data, generating link prediction data; the channel quality assessment and intelligent early warning subsystem completes quality assessment and link early warning based on link prediction data, generating quality assessment and link early warning data. The channel region optimization and reconstruction subsystem optimizes the broadcast region based on short-term and long-term channel prediction data, and generates broadcast region optimization data. The planning and task inversion subsystem and the channel-aided decision-making subsystem complete frequency planning and task inversion based on short-term channel prediction data and long-term channel prediction data, and generate frequency planning and task inversion data. The data management subsystem receives and stores status data, ionospheric detection commands, coverage prediction and analysis data, quality assessment and link early warning data, broadcast area optimization data, and frequency planning and task inversion data from each device in the channel prediction front-end subsystem. It then distributes this data to the channel situation display subsystem for display. The channel situation display subsystem sends ionospheric detection commands to the channel prediction front-end subsystem. The data management subsystem uploads ionospheric detection data, status data of each device in the channel prediction front-end subsystem, ionospheric detection commands, coverage prediction and analysis data, quality assessment and link early warning data, broadcast area optimization data, and frequency planning and task inversion data to external systems.
[0009] Furthermore, the channel prediction front-end subsystem has n1 sets of ionospheric transceiver equipment, n1≥3, n2 sets of ionospheric receiver equipment, n2≥4, and n3 sets of ionospheric transmitter equipment, n3≥1. The channel prediction front-end subsystem is deployed at n stations, n=n1+n2+n3, to complete all-weather, all-time vertical and oblique ionospheric detection of the area of interest.
[0010] Furthermore, the ionospheric detection data includes vertical ionograph data, oblique ionograph data, vertical ionograph characteristic parameter data, oblique ionograph characteristic parameter data, and electron concentration profile data.
[0011] Furthermore, the channel prediction front-end subsystem communicates with the data management subsystem and the channel situation display subsystem via a dedicated line, which is a bidirectional transmission network.
[0012] Furthermore, the short-term channel prediction data consists of the 1-hour quasi-real-time prediction values and 72-hour short-term prediction values of the channel ionospheric parameters and the shortwave coverage area, while the long-term channel prediction data consists of the 1-month long-term prediction values of the channel ionospheric parameters and the shortwave coverage area.
[0013] Furthermore, the data management subsystem is a database, and it communicates with external systems via TCP or UDP protocols.
[0014] A channel prediction method for shortwave broadcasting, using the aforementioned channel prediction system, is improved by including the following steps: Step 1, Data Generation and Collection: The channel prediction front-end subsystem utilizes ionospheric transceiver equipment, ionospheric measurement and reception equipment, and ionospheric transmission equipment deployed at n stations to detect and obtain ionospheric detection data, and also generates status data for each device; Step 2, Data transmission and storage: The channel prediction front-end subsystem stores the acquired ionospheric detection data and device status data locally, then transmits them to the channel prediction back-end subsystem via a dedicated line, and stores them in the data management subsystem; the ionospheric detection commands generated by the channel prediction back-end subsystem are also transmitted to the channel prediction front-end subsystem via a dedicated line. Step 3, Data Processing and Analysis: The short-term channel prediction subsystem and the long-term channel prediction subsystem obtain the predicted values of the highest available frequency, median field strength, basic circuit reliability, and signal-to-noise ratio for the next 72 hours and the next month, respectively, and generate short-term channel prediction data and long-term channel prediction data. The coverage prediction subsystem obtains near real-time, short-term, and long-term coverage parameter prediction results for shortwave broadcast coverage and generates coverage effect prediction data. The channel link prediction subsystem plans and predicts broadcast links that meet specific requirements based on the input or specified transmission location or area, coverage area or point. The channel quality assessment and intelligent early warning subsystem obtains the link field pattern data and ionospheric parameter data for the current time period and generates quality assessment and link early warning data. The channel region optimization and reconstruction subsystem performs region optimization for routine tasks and region optimization for temporary tasks, and generates broadcast region optimization data. The planning and task inversion subsystem realizes frequency planning, task broadcast status inversion or reproduction, transmission link planning and transmit power inversion, while the channel-aided decision-making subsystem realizes overall frequency planning for frequency switching tasks and related task inversion comparison, and generates frequency planning and task inversion data. Step 4, Data Presentation and Application: The ionospheric detection data obtained by the channel prediction front-end subsystem, the ionospheric sensing and propagation effect data, coverage effect prediction data, quality assessment and link early warning data, broadcast area optimization data, frequency planning and task inversion data generated by the channel prediction back-end subsystem, are visualized by the channel situation display subsystem based on GIS, and simultaneously sent to external systems via TCP or UDP protocols.
[0015] Furthermore, in step 1, the detection period is set to half an hour by default.
[0016] The beneficial effects of this invention are: The channel prediction system disclosed in this invention utilizes ionospheric transceiver equipment, ionospheric measurement equipment, and ionospheric transmission equipment for distributed station deployment and network observation, enabling all-weather, all-time detection of the ionospheric state in areas of interest. The detected ionospheric data is transmitted and aggregated to the channel prediction back-end subsystem via a transmission network. Based on the acquired ionospheric detection data, the channel prediction back-end subsystem performs inversion and inference analysis of ionospheric characteristic parameters, predicts nonlinear ionospheric shortwave propagation effect parameters, and provides 1-hour quasi-real-time predictions, 72-hour short-term predictions, and 1-month long-term predictions of channel ionospheric parameters and shortwave coverage areas. Furthermore, it realizes functions such as coverage prediction, quality assessment and link early warning, area optimization, frequency planning and task inversion, situation display, and ionospheric propagation effect analysis.
[0017] The channel prediction system disclosed in this invention can improve the accuracy of my country's shortwave broadcasting coverage globally and the ability to block illegal broadcasts, providing strong technical support for the high-quality broadcasting of China's shortwave broadcasting globally, the protection of listener rights, and international radio coordination. Attached Figure Description
[0018] Figure 1 This is a schematic diagram of the composition of the channel prediction system disclosed in this invention; Figure 2 This is a schematic diagram of the service process of the channel prediction system disclosed in this invention; Figure 3 This is a flowchart illustrating the channel prediction method disclosed in this invention. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0020] Example 1: This example discloses a channel prediction system for shortwave broadcasting, such as... Figure 1 As shown, it includes a channel prediction front-end subsystem and a channel prediction back-end subsystem. The channel prediction front-end subsystem includes ionospheric transceiver equipment, ionospheric measurement and reception equipment, and ionospheric transmission equipment. The channel prediction back-end subsystem consists of 10 subsystems, including a coverage prediction subsystem, a short-term channel prediction subsystem, a long-term channel prediction subsystem, a channel link prediction subsystem, a channel quality assessment and intelligent early warning subsystem, a channel area optimization and reconstruction subsystem, a planning and task inversion subsystem, a channel situation display subsystem, a channel auxiliary decision-making subsystem, and a data management subsystem.
[0021] like Figure 2 As shown, the service flow of the channel prediction system is divided into four parts: data detection, data transmission, data processing, and result reporting. (1) Data Probe: The channel prediction front-end subsystem has n1 sets of ionospheric transceiver equipment, n1≥3; n2 sets of ionospheric receiving equipment, n2≥4; and n3 sets of ionospheric transmitting equipment, n3≥1. The channel prediction front-end subsystem is deployed at n stations, n=n1+n2+n3, to complete all-weather, all-time vertical and oblique ionospheric sounding of the area of interest, acquire vertical and oblique ionospheric sounding data, and obtain ionospheric sounding data and store it locally by interpreting and inverting the vertical and oblique ionospheric sounding maps.
[0022] Ionospheric detection data includes vertical ionograph data, oblique ionograph data, characteristic parameter data of vertical ionograph, characteristic parameter data of oblique ionograph, and electron concentration profile data.
[0023] (2) Data transmission: Using the transmission network, the channel prediction front-end subsystem transmits the acquired ionospheric detection data and status data of each device to the data management subsystem of the channel prediction back-end subsystem. When it is necessary to change the operating parameters, the channel situation display subsystem of the channel prediction back-end subsystem can use the transmission network to send ionospheric detection commands to the channel prediction front-end subsystem.
[0024] The channel prediction front-end subsystem communicates with the data management subsystem and the channel situation display subsystem via a dedicated line, which is a bidirectional transmission network.
[0025] (3) Data processing: The data management subsystem receives and stores the ionospheric detection data acquired by the channel prediction front-end subsystem, distributes the ionospheric detection data to the short-term channel prediction subsystem and the long-term channel prediction subsystem, completes ionospheric sensing and ionospheric propagation effect analysis, generates short-term channel prediction data by the short-term channel prediction subsystem, and generates long-term channel prediction data by the long-term channel prediction subsystem.
[0026] The short-term channel prediction data consists of the 1-hour quasi-real-time prediction of the channel ionospheric parameters and the shortwave coverage area, and the 72-hour short-term prediction. The long-term channel prediction data consists of the 1-month long-term prediction of the channel ionospheric parameters and the shortwave coverage area.
[0027] The coverage prediction subsystem predicts coverage effect based on short-term and long-term channel prediction data, and generates coverage prediction and analysis data. The channel link prediction subsystem completes channel link prediction based on short-term and long-term channel prediction data, generating link prediction data; the channel quality assessment and intelligent early warning subsystem completes quality assessment and link early warning based on link prediction data, generating quality assessment and link early warning data. The channel region optimization and reconstruction subsystem optimizes the broadcast region based on short-term and long-term channel prediction data, and generates broadcast region optimization data. The planning and task inversion subsystem and the channel-aided decision-making subsystem complete frequency planning and task inversion based on short-term channel prediction data and long-term channel prediction data, and generate frequency planning and task inversion data. The data management subsystem receives and stores status data, ionospheric detection commands, coverage prediction and analysis data, quality assessment and link early warning data, broadcast area optimization data, and frequency planning and task inversion data from each device in the channel prediction front-end subsystem. It then distributes this data to the channel situation display subsystem for display (visual presentation).
[0028] (4) Result reporting: The data management subsystem uploads ionospheric detection data, status data of various devices in the channel prediction front-end subsystem, ionospheric detection commands, coverage prediction and analysis data, quality assessment and link early warning data, broadcast area optimization data, and frequency planning and task inversion data to external systems (such as the operation management system) to provide support for precise suppression analysis and judgment, and precise coverage scheduling.
[0029] The data management subsystem is a database, and it communicates with external systems via TCP or UDP protocols.
[0030] like Figure 3As shown, this embodiment also discloses a channel prediction method for shortwave broadcasting, which uses the above-described channel prediction system and includes the following steps: Step 1, Data Generation and Collection: The channel prediction front-end subsystem utilizes ionospheric transceiver equipment, ionospheric measurement and reception equipment, and ionospheric transmission equipment deployed at n stations to detect and obtain ionospheric detection data. The detection period is half an hour by default, and the status data of each device is also generated. Step 2, Data transmission and storage: The channel prediction front-end subsystem stores the acquired ionospheric detection data and device status data locally, then transmits them to the channel prediction back-end subsystem via a dedicated line, and stores them in the data management subsystem; the ionospheric detection commands generated by the channel prediction back-end subsystem are also transmitted to the channel prediction front-end subsystem via a dedicated line. Step 3, Data Processing and Analysis: The short-term channel prediction subsystem and the long-term channel prediction subsystem obtain relevant ionospheric state parameters such as the highest available frequency, median field strength, basic circuit reliability, and signal-to-noise ratio prediction values for the next 72 hours and the next month, respectively, and generate short-term channel prediction data and long-term channel prediction data. The coverage prediction subsystem obtains near real-time, short-term, and long-term coverage parameter prediction results for shortwave broadcast coverage and generates coverage effect prediction data. The channel link prediction subsystem plans and predicts broadcast links that meet specific requirements based on the input or specified transmission location / area, coverage area / point and other link parameters. The channel quality assessment and intelligent early warning subsystem obtains the link field pattern data and ionospheric parameter data (field strength, signal-to-noise ratio, highest available frequency, critical frequency, etc.) for the current time period and generates quality assessment and link early warning data. The channel region optimization and reconstruction subsystem performs region optimization for routine tasks and region optimization for temporary tasks, and generates broadcast region optimization data. The planning and task inversion subsystem realizes frequency planning, task broadcast status inversion or reproduction, transmission link planning and transmit power inversion, while the channel-aided decision-making subsystem realizes overall frequency planning for frequency switching tasks and related task inversion comparison, and generates frequency planning and task inversion data. Step 4, Data Presentation and Application: The ionospheric detection data obtained by the channel prediction front-end subsystem, and the ionospheric sensing and propagation effect data, coverage effect prediction data, quality assessment and link early warning data, broadcast area optimization data, frequency planning and task inversion data generated by the channel prediction back-end subsystem, are visualized by the channel situation display subsystem based on GIS, and simultaneously sent to external systems (such as operation management systems) via TCP or UDP protocols to realize the application of corresponding business scenarios.
Claims
1. A channel prediction system for shortwave broadcasting, characterized in that: It includes a channel prediction front-end subsystem and a channel prediction back-end subsystem. The channel prediction front-end subsystem includes ionospheric transceiver equipment, ionospheric measurement and reception equipment, and ionospheric transmission equipment. The channel prediction back-end subsystem includes a coverage prediction subsystem, a short-term channel prediction subsystem, a long-term channel prediction subsystem, a channel link prediction subsystem, a channel quality assessment and intelligent early warning subsystem, a channel area optimization and reconstruction subsystem, a planning and task inversion subsystem, a channel situation display subsystem, a channel auxiliary decision-making subsystem, and a data management subsystem.
2. The channel prediction system for shortwave broadcasting according to claim 1, characterized in that: The data management subsystem receives and stores the ionospheric sounding data acquired by the channel prediction front-end subsystem, and distributes the ionospheric sounding data to the short-term channel prediction subsystem and the long-term channel prediction subsystem. The short-term channel prediction subsystem generates short-term channel prediction data, and the long-term channel prediction subsystem generates long-term channel prediction data.
3. The channel prediction system for shortwave broadcasting according to claim 2, characterized in that: The coverage prediction subsystem predicts coverage effect based on short-term and long-term channel prediction data, and generates coverage prediction and analysis data. The channel link prediction subsystem performs channel link prediction based on short-term and long-term channel prediction data, and generates link prediction data. The channel quality assessment and intelligent early warning subsystem completes quality assessment and link early warning based on link prediction data, and generates quality assessment and link early warning data. The channel region optimization and reconstruction subsystem optimizes the broadcast region based on short-term and long-term channel prediction data, and generates broadcast region optimization data. The planning and task inversion subsystem and the channel-aided decision-making subsystem complete frequency planning and task inversion based on short-term channel prediction data and long-term channel prediction data, and generate frequency planning and task inversion data. The data management subsystem receives and stores status data, ionospheric detection commands, coverage prediction and analysis data, quality assessment and link early warning data, broadcast area optimization data, and frequency planning and task inversion data from each device in the channel prediction front-end subsystem, and distributes these data to the channel situation display subsystem for display. The channel situation display subsystem sends ionospheric detection commands to the channel prediction front-end subsystem; The data management subsystem uploads ionospheric detection data, status data of each device in the channel prediction front-end subsystem, ionospheric detection commands, coverage prediction and analysis data, quality assessment and link early warning data, broadcast area optimization data, and frequency planning and task inversion data to external systems.
4. The channel prediction system for shortwave broadcasting according to claim 1, characterized in that: The channel prediction front-end subsystem has n1 sets of ionospheric transceiver equipment, n1≥3; n2 sets of ionospheric receiver equipment, n2≥4; and n3 sets of ionospheric transmitter equipment, n3≥1. The channel prediction front-end subsystem is deployed at n stations, n=n1+n2+n3, to complete all-weather, all-time vertical and oblique ionospheric detection of the area of interest.
5. The channel prediction system for shortwave broadcasting according to claim 2, characterized in that: Ionospheric detection data includes vertical ionograph data, oblique ionograph data, characteristic parameter data of vertical ionograph, characteristic parameter data of oblique ionograph, and electron concentration profile data.
6. The channel prediction system for shortwave broadcasting according to claim 3, characterized in that: The channel prediction front-end subsystem communicates with the data management subsystem and the channel situation display subsystem via a dedicated line, which is a bidirectional transmission network.
7. The channel prediction system for shortwave broadcasting according to claim 2, characterized in that: The short-term channel prediction data consists of the 1-hour quasi-real-time prediction of the channel ionospheric parameters and the shortwave coverage area, and the 72-hour short-term prediction. The long-term channel prediction data consists of the 1-month long-term prediction of the channel ionospheric parameters and the shortwave coverage area.
8. The channel prediction system for shortwave broadcasting according to claim 3, characterized in that: The data management subsystem is a database, and it communicates with external systems via TCP or UDP protocols.
9. A channel prediction method for shortwave broadcasting, using the channel prediction system of claim 3, characterized in that, Includes the following steps: Step 1, Data generation and collection: The channel prediction front-end subsystem utilizes ionospheric transceiver equipment, ionospheric measurement and reception equipment, and ionospheric transmission equipment deployed at n stations to detect and obtain ionospheric detection data, and also generates status data for each device; Step 2, Data transmission and storage: The channel prediction front-end subsystem stores the acquired ionospheric detection data and device status data locally, then transmits them to the channel prediction back-end subsystem via a dedicated line, and stores them in the data management subsystem; the ionospheric detection commands generated by the channel prediction back-end subsystem are also transmitted to the channel prediction front-end subsystem via a dedicated line. Step 3, Data Processing and Analysis: The short-term channel prediction subsystem and the long-term channel prediction subsystem obtain the predicted values of the highest available frequency, median field strength, basic circuit reliability, and signal-to-noise ratio for the next 72 hours and the next month, respectively, and generate short-term channel prediction data and long-term channel prediction data. The coverage prediction subsystem obtains near real-time, short-term, and long-term coverage parameter prediction results for shortwave broadcast coverage and generates coverage effect prediction data. The channel link prediction subsystem plans and predicts broadcast links that meet specific requirements based on the input or specified transmission location or area, coverage area or point. The channel quality assessment and intelligent early warning subsystem obtains the link field pattern data and ionospheric parameter data for the current time period and generates quality assessment and link early warning data. The channel region optimization and reconstruction subsystem performs region optimization for routine tasks and region optimization for temporary tasks, and generates broadcast region optimization data. The planning and task inversion subsystem realizes frequency planning, task broadcast status inversion or reproduction, transmission link planning and transmit power inversion, while the channel-aided decision-making subsystem realizes overall frequency planning for frequency switching tasks and related task inversion comparison, and generates frequency planning and task inversion data. Step 4, Data Presentation and Application: The ionospheric detection data obtained by the channel prediction front-end subsystem, the ionospheric sensing and propagation effect data, coverage effect prediction data, quality assessment and link early warning data, broadcast area optimization data, frequency planning and task inversion data generated by the channel prediction back-end subsystem, are visualized by the channel situation display subsystem based on GIS, and simultaneously sent to external systems via TCP or UDP protocols.
10. The channel prediction method for shortwave broadcasting according to claim 9, characterized in that, In step 1, the detection period is set to half an hour by default.