MDCM Signal Demodulation Using Segmented Real and Imaginary Norms
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Solution Overview
Problem
Conventional methods for demodulating modified dual carrier modulation (MDCM) signals in multiband-orthogonal frequency division multiplexing (MB-OFDM) systems face high complexity, which hinders practical application, and fail to generate accurate log likelihood ratios (LLR) necessary for low density parity check (LDPC) channel decoding, especially when using zero-forcing (ZF) or minimum mean square error (MMSE) methods.
Innovation Solution
A method that divides the MDCM signal into real and imaginary parts, generating symbol vector candidates to calculate norms and determine the minimum norm vectors, thereby reducing computational complexity and enabling LLR calculation for soft decision demodulation, using equations to define real and imaginary symbol vector candidates and calculating log likelihood ratios based on these candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maximum likelihood (ML) method is used for MDCM demodulation, then optimal performance is provided, but complexity is so high that it is inappropriate for practical systems
Solution Approach 1:
The patent segments the MDCM demodulation process by dividing the received signal into real and imaginary parts, and separately processing each part through distinct calculation paths. This segmentation reduces the overall computational complexity while maintaining the optimal performance characteristics of ML demodulation.
2Device complexity
If zero-forcing (ZF) or minimum mean square error (MMSE) method is used, then system complexity is decreased, but performance is deteriorated since diversity gain cannot be obtained
Solution Approach 1:
The patent applies segmentation by separating the signal processing into real and imaginary components, each processed independently to preserve diversity gain while reducing complexity compared to conventional unified approaches.
Solution Approach 2:
The patent changes the processing parameters by applying different norm calculations and decision rules to the real and imaginary parts separately, enabling complexity reduction while maintaining performance through parameter optimization.
3Reliability
If soft decision demodulation is performed to increase reception performance, then accurate log likelihood ratio (LLR) is required for LDPC channel decoding, but ML method still has system complexity problem and ZF/MMSE methods cannot generate LLR
Solution Approach 1:
The patent segments the LLR generation process into separate real and imaginary part processing, calculating LLRs for each component independently. This enables accurate soft decision output for LDPC decoding while reducing overall system complexity.
Solution Approach 2:
The patent optimizes the LLR calculation parameters by using simplified norm calculations on segmented signal components, achieving accurate probability information for channel decoding with reduced computational burden.
Data Source
AI summary
A method of demodulating a modified dual carrier modulation (MDCM) signal using hard decision includes generating real symbol vector candidates and imaginary symbol vector candidates which correspond to an MDCM signal pair; calculating a first norm between a real part of the MDCM signal pair and each of the real symbol vector candidates and determining as a real symbol vector a real symbol vector candidate that has the minimum first norm among the real symbol vector candidates; and calculating a second norm between an imaginary part of the MDCM signal pair and each of the imaginary symbol vector candidates and determining as an imaginary symbol vector an imaginary symbol vector candidate that has the minimum second norm among the imaginary symbol vector candidates.