QAM Demodulation via Rotated Constellation Candidate Selection
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Solution Overview
Problem
Current QAM demodulation methods are inefficient, especially with high modulation orders like 64-QAM and 256-QAM, due to increased calculation complexity and distortion in fading channels, which affects data communication under limited frequency resources.
Innovation Solution
A method for demodulating QAM signals by selecting a subset of candidate points based on distances and channel responses, calculating log-likelihood ratios only for these points, rather than all reference points, to reduce computational load and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If QAM modulation order increases (e.g., 64-QAM, 256-QAM) to transfer more data bits per symbol, then data transmission efficiency is improved, but calculation complexity for demodulation is significantly increased
Solution Approach 1:
The patent segments the demodulation process into two stages: first identifying candidate points from the rotated constellation based on received signal characteristics, then calculating log-likelihood ratios only for these candidate points. This segmentation reduces the number of calculations required compared to evaluating all constellation points, thereby resolving the contradiction between high-order modulation efficiency and demodulation complexity.
Solution Approach 2:
The patent applies partial action by calculating log-likelihood ratios for only a subset of candidate points rather than all reference points in the constellation. This selective calculation approach maintains sufficient demodulation accuracy while significantly reducing computational load, enabling practical implementation of high-order QAM schemes.
2Productivity
If QAM signal is transmitted through fading channel, then data communication capability is improved, but signal distortion increases making demodulation more difficult
Solution Approach 1:
The patent performs preliminary identification of candidate points from the rotated constellation before calculating log-likelihood ratios. This preliminary action filters out unlikely candidates based on received signal characteristics, making the subsequent demodulation more robust against fading channel distortion and improving reliability.
Solution Approach 2:
The patent uses channel response information as feedback to guide the candidate point selection process. By incorporating channel state into the demodulation algorithm, the system adapts to fading conditions and maintains reliable communication despite signal distortion.
Data Source
AI summary
To demodulate a quadrature amplitude modulation (QAM) signal, a reception point is determined corresponding to a symbol in the QAM signal that is received where the symbol is mapped to one reference point of a plurality of reference points in a rotated constellation and the plurality of reference points are represented by an in-phase (I) coordinate and a quadrature-phase (Q) coordinate. A plurality of candidate points corresponding to a portion of the plurality of reference points are selected based on distances between the reception point and the respective reference points. The reception point is demapped by calculating a plurality of log-likelihood ratios based on the plurality of candidate points, the plurality of log-likelihood ratios corresponding to bits of data represented by the reception point.