Common Gain Value Processing for Signal Accuracy
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Solution Overview
Problem
Communication systems face limitations in data transmission due to channel noise and varying channel conditions, which impair signal reception and decoding, especially in high-speed data transfer scenarios.
Innovation Solution
A method and system that identify a common gain value among data elements representing constellation points of a modulated signal, adjust these elements to include the common gain value, and apply mathematical operations such as folding and factor application to represent the data with reduced precision, thereby enhancing signal processing and decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data elements are processed with individual gain values to maintain signal accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple individual gain values into a single common gain value that represents the entire block of data elements. This merging approach maintains the essential signal characteristics while eliminating the need to process each element separately, thus reducing device complexity while preserving measurement precision.
Solution Approach 2:
The common gain value serves as a universal scaling factor for all data elements in the block, replacing multiple individual gain values. This universal approach simplifies the processing system while maintaining the ability to accurately represent varying signal strengths across different elements.
2Measurement precision
If floating point representation is used for all data elements to maintain precision, then measurement precision is improved, but loss of substance increases due to storage requirements
Solution Approach 1:
The patent applies different precision representations to different parts of the data structure. The common gain value controls the overall precision requirements, allowing most data elements to use reduced precision formats while maintaining accurate representation where needed. This local differentiation optimizes storage efficiency without sacrificing essential precision.
Solution Approach 2:
The system dynamically adjusts the precision parameter based on the common gain value. When signal variations are small (indicated by the common gain), reduced precision formats suffice. When variations are large, the common gain value adjusts to maintain appropriate precision. This parameter adaptation reduces storage requirements while preserving measurement accuracy.
3Reliability
If channel conditions are compensated during reconstruction phases, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent performs gain value determination and data element adjustment as preliminary actions before the main reconstruction and decoding processes. By pre-processing the data to account for channel conditions and establish a common gain value, the subsequent reconstruction phases become simpler while maintaining improved reliability through early compensation of channel effects.
Data Source
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AI summary
A method includes receiving data elements representative of constellation points of a modulated signal. Each data element includes a gain. The method also includes identifying a common gain value among the received data elements, and adjusting the data elements to include the common gain value.