Soft Decision LLR Correction for Low-Complexity QAM Demodulation
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Solution Overview
Problem
Conventional soft decision value generating apparatuses face challenges in calculating log-likelihood ratios (LLRs) with high accuracy due to high computational complexity, especially for modulation schemes like gray-mapped QAM and differential encoding schemes, which require large amounts of computation.
Innovation Solution
A soft decision value generating apparatus comprising a hard decision value calculator, an approximate value calculator, and an approximate value corrector that calculates hard decision values and approximate LLRs, and inverts the sign bit of the approximate values when conflicting with hard decision values to produce accurate soft decision values, reducing computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the exact LLR calculation formula is used, then calculation accuracy is improved, but the amount of computation becomes enormous
Solution Approach 1:
The patent segments the LLR calculation by separating the exact formula into two parts: an approximate calculation using only the maximum value term (reducing computation) and a correction term (adding back accuracy). This segmentation allows the system to achieve both low computational complexity and high accuracy by handling each part separately rather than computing the entire exact formula.
Solution Approach 2:
The patent introduces an intermediary correction mechanism. The approximate calculator provides a quick but slightly inaccurate result, and the correction unit acts as an intermediary to adjust this result using a simplified correction term. This intermediary step bridges the gap between the simple approximate calculation and the exact calculation, achieving high accuracy without the full computational burden.
2Device complexity
If approximate calculation methods are used, then the amount of computation is reduced, but calculation accuracy deteriorates
Solution Approach 1:
The patent changes the parameters of the calculation by introducing a correction term that adjusts the approximate LLR value. Instead of using the raw approximate calculation result, the system modifies the parameters by adding a correction component derived from the difference between the maximum value term and other terms in the exact formula. This parameter change restores accuracy while maintaining the low computational complexity of the approximate method.
3Ease of manufacture
If gray-mapped QAM is used, then LLR calculation is simplified, but it is not applicable to QAM with odd power of 2 modulation levels
Solution Approach 1:
The patent creates a universal LLR calculation method that works for all QAM modulation schemes regardless of whether they have even or odd power of 2 levels. By using the approximation-calculation-correction framework, the system achieves gray-mapping-like simplicity for all QAM types, not just traditional even-power QAM. This makes the method universally applicable to 16QAM, 32QAM, 64QAM, 128QAM, and other variants.
Data Source
AI summary
There are provided a hard decision value calculator that calculates hard decision values from I-ch and Q-ch coordinates of a received symbol having been subjected to multilevel modulation, and an LLR calculator that approximately calculates LLRs from the I-ch and Q-ch coordinates of the received symbol. In a case where a sign bit of an LLR calculated by the LLR calculator conflicts with a hard decision value calculated by the hard decision value calculator, an LLR corrector inverts the sign bit of the LLR and outputs the sign-bit-inverted LLR as a soft decision value to an error correction decoder.