Mixed Metrics Generator for Multi-Format Signal Processing
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Solution Overview
Problem
Current communication receivers face challenges in efficiently processing quadrature modulated symbols, particularly in handling multiple symbol modulation formats, which affects processing speed and efficiency, especially when dealing with increasing data volumes and diverse modulation formats.
Innovation Solution
The implementation of a mixed metrics generator within the communication receiver that processes digital samples from quadrature modulated signals, utilizing a metrics calculator and selector to generate log-likelihood ratios (LLR) and support metrics, allowing for flexible operation across different modulation formats and modes, thereby enhancing processing efficiency and throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a communication receiver processes multiple symbol modulation formats, then the adaptability and versatility of the receiver is improved, but the device complexity and processing difficulty increase
Solution Approach 1:
The patent implements a universal metrics generator that can handle multiple modulation formats (QPSK, 16-QAM, 64-QAM, 256-QAM) through a single integrated architecture. The system uses a unified LLR calculation framework that adapts to different formats by adjusting parameters rather than requiring separate processing paths for each format, thereby achieving multi-functionality without proportionally increasing complexity.
Solution Approach 2:
The patent employs parameter-based adaptation where the same metrics generator uses different configurable parameters to support various modulation formats. By changing parameters such as constellation points, metric thresholds, and calculation coefficients rather than restructuring the entire processing pipeline, the system maintains simplicity while achieving versatility across multiple formats.
2Productivity
If data processing speed is increased to handle larger data volumes, then productivity is improved, but measurement precision and metric accuracy may deteriorate
Solution Approach 1:
The patent segments the metrics generation process into distinct modular stages: signal sampling, LLR calculation, metric computation, and decision-making. This segmentation allows parallel processing of different signal components and formats simultaneously, increasing throughput while maintaining accuracy through dedicated processing paths for each stage that can be optimized independently.
Solution Approach 2:
The system performs preliminary signal conditioning and pre-calculation of metrics before the main processing pipeline. By pre-computing certain parameters and preparing data structures in advance, the system reduces the computational burden during critical processing stages, enabling faster overall processing without sacrificing the precision of final metric calculations.
Data Source
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AI summary
Metric values are estimated from digital samples of received symbols modulated in selected first and second modulation formats. The first format can be selected from among multiple modulation formats. The system can receive the digital samples in sample blocks arranged as a data frame. Each sample block can comprise a first region that contains first samples of the first format or overhead samples, a second region that contains second samples of the second modulation format regardless, and a third region which includes the first samples or the second samples. The system estimates first metrics according to the first modulation format for the first samples and second metrics according to the second modulation format for the second samples. The system also estimates both first metrics and second metrics for the third samples and selects valid metrics for the third samples accordance to the first modulation format or a sample index.