Beamforming Precoding Optimization via Feedback Quality Scores
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Solution Overview
Problem
Existing beamforming technologies face inefficiencies and incomplete understanding of beamformed signal performance due to inadequate tracking and analysis of beamforming metrics, leading to suboptimal communication outcomes.
Innovation Solution
A method and system for determining and analyzing precoding techniques by sending sounding signals and obtaining feedback, allowing for the selection of superior precoding techniques based on quality scores, thereby optimizing beamforming and steering in digital communication systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional beamforming is used without comprehensive metric tracking, then device complexity is reduced, but beamforming performance and communication efficiency deteriorate
Solution Approach 1:
The patent implements comprehensive beamforming metric tracking that captures feedback from beamformee devices including feedback matrices, signal-to-noise ratios, and quality scores. This feedback mechanism enables the beamformer to continuously monitor and analyze beamforming performance metrics, resolving the contradiction by providing the necessary data for performance optimization without requiring fundamental changes to the beamforming architecture.
Solution Approach 2:
The patent replaces traditional mechanical or hardware-based beamforming adjustment mechanisms with software-based metric tracking and analysis systems. By using digital processing to capture, analyze, and optimize beamforming metrics, the system achieves comprehensive performance monitoring without proportionally increasing hardware complexity, thus resolving the contradiction between reliability improvement and device complexity.
2Productivity
If multiple precoding techniques are tested and analyzed, then communication efficiency and signal strength improve, but power consumption and processing overhead increase
Solution Approach 1:
The patent implements quality score-based precoding selection that evaluates multiple precoding techniques but selects only the optimal subset for actual transmission. By using quality scores to rank precoding techniques and selecting only the top performers, the system achieves high communication efficiency without the need to continuously process and transmit using all possible precoding variations, thus reducing power consumption while maintaining productivity.
Solution Approach 2:
The patent changes the operational parameters of precoding techniques by evaluating them under different quality metrics and selecting precoding methods based on quality scores derived from beamforming feedback. This parameter-based selection approach allows the system to optimize communication efficiency by adapting precoding parameters to current channel conditions while avoiding the excessive power consumption that would result from testing all precoding configurations continuously.
3Measurement precision
If comprehensive beamforming metric tracking is implemented, then precision of beamforming optimization improves, but system complexity and processing requirements worsen
Solution Approach 1:
The patent extracts specific critical metrics from comprehensive beamforming data including feedback matrices, signal-to-noise ratios, and quality scores. By focusing on these key extracted metrics rather than processing all raw beamforming data, the system achieves high measurement precision for optimization decisions while reducing the complexity of the analysis and processing system. This selective extraction approach resolves the contradiction between precision and complexity.
4Reliability
If optimal precoding techniques are selected based on quality scores, then signal strength and throughput improve, but processing time and computational overhead increase
Solution Approach 1:
The patent performs preliminary quality score calculations and precoding technique evaluations during idle periods or using previously captured beamforming metrics. By pre-computing quality scores and ranking precoding techniques before actual transmission is needed, the system minimizes processing time during critical communication windows while maintaining high signal strength through optimized precoding selection. This preliminary action approach resolves the contradiction between reliability and time loss.
Data Source
AI summary
An example method may include determining a first precoding processing for communication between a beamformer and a beamformee, and transmitting a first sounding signal precoded according to the first precoding processing. The method also includes obtaining first beamforming feedback from the beamformee in response to the first sounding signal, and selecting a second precoding processing for communication between the beamformer and the beamformee. The method also includes obtaining second beamforming feedback from the beamformee based on a second sounding signal from the beamformer preprocessed according to the second precoding processing, and analyzing the first beamforming feedback and the second beamforming feedback. The method additionally includes deriving a quality score of the second precoding processing based on the analysis of the first beamforming feedback and the second beamforming feedback, and selecting the second precoding processing instead of the first precoding processing based on the quality score of the second precoding processing.