Wireless Feedback Metric Profiles for Spectrum Efficiency
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Solution Overview
Problem
Current mobile communication systems face inefficiencies in resource allocation and feedback mechanisms between Base Station Apparatus and Mobile Station Apparatus, particularly in advanced air interface scenarios, leading to suboptimal transmission resource utilization and spectrum efficiency.
Innovation Solution
A system where the Mobile Station Apparatus determines a metric profile based on physical parameters of resource blocks, using a predetermined rule to calculate a metric value, which is then provided to the Base Station Apparatus for structuring transmission resources, incorporating Channel Quality Indicator (CQI) and Preferred Matrix Index (PMI) feedback to optimize resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional feedback mechanisms are used between Base Station and Mobile Station, then the system maintains simplicity in resource allocation, but spectrum efficiency and transmission resource utilization deteriorate
Solution Approach 1:
The patent segments the feedback information into multiple distinct metrics including Channel Quality Indicator (CQI), Preferred Matrix Index (PMI), and Rank Indicator (RI), each serving specific functions in resource allocation. This segmentation allows the system to optimize different aspects of transmission independently, improving spectrum efficiency without creating a monolithic complex feedback structure
Solution Approach 2:
The feedback mechanism is made dynamic by allowing the Mobile Station to adaptively select and report only the most relevant metrics based on current channel conditions and transmission requirements. The system dynamically adjusts which metrics to report and at what frequency, optimizing spectrum efficiency while avoiding unnecessary signaling overhead that would increase complexity
2Productivity
If resource allocation is optimized for specific tasks using metric profiles, then transmission resource utilization improves, but the complexity of determining and applying metrics increases
Solution Approach 1:
The patent implements preliminary action by pre-defining metric profiles that correspond to different task types (e.g., voice communication, data transmission, video streaming). These profiles contain pre-configured weightings and thresholds for various channel parameters, allowing the Mobile Station to quickly match current tasks to appropriate profiles without performing complex real-time calculations, thus improving resource utilization while limiting complexity growth
Solution Approach 2:
The system changes parameters by allowing flexible adjustment of metric weightings within defined ranges based on task requirements. Instead of fixed complex algorithms, the system modifies parameter weightings (e.g., importance of CQI vs. PMI) according to the selected metric profile, achieving task-specific optimization through parameter adjustment rather than structural complexity
3Measurement precision
If detailed physical parameters are gathered from all resource blocks, then measurement precision improves, but signaling overhead increases
Solution Approach 1:
The patent extracts only the most essential and task-relevant physical parameters from the full set of available measurements. Based on the selected metric profile, the system identifies and reports only critical parameters (such as CQI for throughput optimization or PMI for MIMO configuration), discarding redundant information. This extraction maintains measurement precision for essential parameters while dramatically reducing signaling overhead by eliminating unnecessary data transmission
Data Source
AI summary
For using best M method in a mixed subband/miniband environment a Mobile Station Apparatus calculates a metric for sending information corresponding to the metric to a base station.