Soft Demapping in Rotated QAM Systems
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Solution Overview
Problem
In rotated quadrature amplitude modulation (QAM) based communication systems, the complexity of soft demapping at the receiver is high, necessitating methods to reduce structural and functional complexity while addressing signal fading issues.
Innovation Solution
A method and apparatus for soft demapping that pre-process symbols based on a priori information, dividing them into I and Q channel symbols using MMSE or MMSE-IC methods, and performing one-dimensional log-likelihood ratio calculations to reduce operational complexity and enhance receiver performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If rotated QAM is used to implement signal-space diversity and combat fading, then reliability is improved, but device complexity increases due to the need for complex soft demapping at the receiver
Solution Approach 1:
The patent segments the complex 2D soft demapping process into two independent 1D soft demapping processes by separating the I and Q channel symbols. This segmentation is achieved by dividing the rotated QAM constellation into independent I and Q components, allowing each to be processed separately through 1D demapping operations, thereby reducing receiver complexity while maintaining reliability
Solution Approach 2:
The patent transforms the problem from a two-dimensional soft demapping operation to two separate one-dimensional operations. By changing the dimensionality of the demapping process and processing I and Q channels independently in 1D space, the computational complexity is significantly reduced while preserving the diversity benefits of rotated QAM
2Measurement precision
If conventional soft demapping is used for rotated QAM, then measurement precision is maintained, but productivity decreases due to high operational complexity
Solution Approach 1:
The patent segments the complex 2D soft demapping calculation into two independent 1D calculations for I and Q channels. This segmentation maintains measurement precision by preserving the statistical independence of the channels while dramatically improving processing efficiency through simpler 1D log-likelihood ratio computations
Solution Approach 2:
The patent transitions from 2D soft demapping to two separate 1D soft demapping operations. This dimensional reduction maintains the precision of LLR calculation by treating each channel independently while significantly improving productivity through reduced computational operations
Data Source
AI summary
A method and apparatus to perform a soft demapping in a rotated quadrature amplitude modulation (QAM) based communication system is described. The method and the apparatus include pre-processing a symbol based on a priori information and performing a one-dimensional (1D) soft demapping on the pre-processed symbol, continuously.