DCM Demapper Noise Amplification Reduction
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Solution Overview
Problem
Conventional Dual Carrier Modulation (DCM) demappers face issues with noise amplification and degraded reception performance due to the noise amplification effect, especially when using Zero-Forcing Equalization (ZFE) and Linear Combination (LC) methods, and the complexity of calculating theoretical log-likelihood ratios (LLR) in CSI methods.
Innovation Solution
A DCM demapper is designed with a basic signal generation unit, soft decision generation units, and selection units that generate and select soft decisions based on power differences and channel information between subcarriers, reducing noise amplification and simplifying hardware configuration by approximating exponential/log function calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If Zero-Forcing Equalization (ZFE) and Linear Combination (LC) methods are used, then the demapper is simple to embody, but noise amplification occurs causing degraded reception performance
Solution Approach 1:
The patent introduces an intermediary weighting factor (alpha) that balances between ZFE-LC simplicity and MMSEE-LC noise suppression. This weighting factor acts as a mediator parameter that allows the system to operate at an optimal point between the two extreme methods, reducing noise amplification while maintaining implementation simplicity.
Solution Approach 2:
The patent changes the parameter space by introducing a weighting factor (alpha) that controls the trade-off between noise suppression and implementation complexity. By adjusting this parameter, the system can adapt to different channel conditions and achieve optimal reception performance without requiring complex MMSEE calculations.
2Reliability
If Minimum Mean Square Error Equalizer (MMSEE) is used instead of ZFE, then noise amplification effect is supplemented, but there is a defect in estimating average power of noise
Solution Approach 1:
The weighting factor (alpha) serves as an intermediary that allows the system to achieve noise suppression benefits without requiring precise noise power estimation. By using this intermediate parameter, the system can operate effectively with simplified noise estimation, avoiding the defects of MMSEE while maintaining noise suppression capabilities.
3Measurement precision
If CSI (LLR) method is used, then the most accurate soft decision is generated, but the embodiment is difficult to realize due to exponential/log function calculations and quantizing errors
Solution Approach 1:
The patent replaces the complex exponential/log function calculations with simpler algebraic operations involving a weighting factor. This substitution uses computationally inexpensive operations that achieve near-optimal soft decision accuracy without requiring complex hardware, effectively replacing the theoretical LLR method with a practical approximation.
Solution Approach 2:
The patent transforms the complex LLR calculation into a simplified parameter-based computation using the weighting factor (alpha). This parameter change converts an exponentially complex calculation into a linear algebraic operation, dramatically reducing hardware complexity while maintaining accuracy.
4Reliability
If CSI (BAL) method is used, then noise amplification effect is remarkably reduced, but reception performance degrades more than CSI (LLR) method due to soft decision far from theoretical LLR
Solution Approach 1:
The patent introduces a new parameter (weighting factor alpha) that optimizes the balance between noise suppression and soft decision accuracy. By carefully selecting this parameter, the system achieves better soft decision accuracy than BAL method while maintaining the noise amplification reduction benefit, effectively finding an optimal operating point between BAL and LLR methods.
Data Source
AI summary
A DCM demapper and a DCM demapping method are provided. The DCM demapper includes: a basic signal generation unit generating a plurality of basic signals using a signal and channel information of two subcarriers; a soft decision generation unit generating a plurality of soft decisions using the plurality of basic signals; and a soft decision selection unit selecting a soft decision corresponding to each bit of the two subcarriers among the generated soft decisions.