Communication Quality Mapping for Mobile Fading Prediction
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Solution Overview
Problem
Existing communication quality prediction methods fail to accurately predict communication quality during fading periods in mobile object communication control, leading to inadequate control strategies.
Innovation Solution
A method and apparatus that divide a target space into regions based on a mobile object's movement speed, generate a spectrum of received radio wave power for each frequency in these regions, and calculate the variation in communication quality between them, enabling accurate prediction and display of communication quality changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If communication quality is measured during fading periods in mobile object communication, then communication quality prediction accuracy is improved, but measurement complexity and processing time increase
Solution Approach 1:
The patent divides the measurement process into distinct segments: acquiring spatial map information, generating spectrum data for each frequency, calculating degree of variation, and predicting communication quality. This segmentation allows the system to handle complex fading period measurements through structured, manageable steps, improving accuracy without overwhelming complexity.
Solution Approach 2:
The patent performs preliminary actions by acquiring spatial map information and pre-calculating spectrum data for multiple frequencies before actual communication quality measurement. This preliminary preparation enables the system to efficiently analyze fading periods and predict communication quality without increasing real-time processing complexity.
2Measurement precision
If spectrum analysis is performed for each frequency in multiple regions, then communication quality prediction accuracy is improved, but calculation time and processing resources increase
Solution Approach 1:
The patent segments the spatial area into multiple regions and analyzes each region's spectrum at multiple frequencies independently. This segmentation allows parallel processing and efficient calculation of degree of variation between regions, improving prediction accuracy while managing calculation time through structured analysis.
Solution Approach 2:
The patent applies local quality analysis by generating spectrum data specific to each frequency and each spatial region, then calculating the degree of variation locally between adjacent regions. This localized approach improves prediction accuracy for specific areas without requiring exhaustive global analysis, thereby reducing overall processing time.
3Measurement precision
If spatial map is divided into smaller regions corresponding to movement speed, then communication quality prediction accuracy is improved, but the number of regions and data processing volume increase
Solution Approach 1:
The patent segments the spatial map into regions based on mobile object movement characteristics, creating a manageable number of zones that balance prediction accuracy with data processing volume. This segmentation strategy ensures sufficient spatial resolution for accurate fading analysis while avoiding excessive data processing requirements.
Solution Approach 2:
The patent dynamically adjusts the spatial map division based on mobile object movement speed, creating regions that adapt to the object's motion characteristics. This dynamic approach improves prediction accuracy for moving objects while controlling data processing volume by adjusting region count according to actual movement patterns rather than using fixed high-resolution grids.
Data Source
AI summary
A communication quality calculation apparatus of the present disclosure includes: an acquiring unit that acquires a spatial map having a plurality of regions obtained by dividing a target space in which a mobile object will move by a size corresponding to a movement speed of the mobile object; a spectrum calculating unit that generates a spectrum representing electric power for each frequency of received radio waves in each of the regions within the spatial map based on preset information; and a variation calculating unit that calculates, based on a change in the spectrum between the regions within the spatial map, a degree of variation in communication quality between the regions.