Soft-Output Noncoherent Continuous Phase Demodulator Complexity Reduction
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Solution Overview
Problem
Conventional demodulation systems are complex and require significant computational resources, especially when dealing with non-coherent soft-output demodulators, which can be impractical for real-time processing due to the need for numerous correlations and complex calculations.
Innovation Solution
A method and system that simplify the demodulation process by breaking down symbol sequences into subsequences, calculating correlations for possible phase transitions, and determining the largest correlations to approximate the log likelihood of symbols, reducing computational complexity through simplified correlations and approximations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional non-coherent soft-output demodulation is used, then demodulation performance is improved, but computational complexity increases significantly
Solution Approach 1:
The patent segments the symbol sequence into multiple subsequences and processes them separately through parallel demodulation paths. Each subsequence is demodulated independently to produce soft decisions, which are then combined. This segmentation reduces the computational burden on any single processing path while maintaining overall demodulation performance.
Solution Approach 2:
The patent applies partial action by computing correlations only for a subset of possible phase transitions rather than all possible transitions. By identifying and processing only the most likely or relevant phase transitions, the system achieves acceptable demodulation performance with significantly reduced computational complexity compared to exhaustive correlation methods.
2Productivity
If the symbol sequence is broken into subsequences for parallel processing, then processing speed is improved, but system complexity increases
Solution Approach 1:
The symbol sequence is divided into multiple subsequences that can be processed in parallel. Each subsequence undergoes independent correlation calculations and soft decision generation, enabling concurrent processing that improves overall throughput and processing speed.
Solution Approach 2:
After parallel processing of subsequences, the patent merges the results by combining the soft decisions from each subsequence. The correlations and soft decisions from multiple subsequences are integrated to form the final demodulated output, achieving both parallel processing benefits and unified result quality.
Data Source
AI summary
A method and system of demodulating a received transmission is disclosed. The method comprises disassembling a symbol sequence into a before sequence, a current symbol, and an after sequence. The method also comprises calculating correlations for all possible before sequences and determining the largest correlations for the before sequences, and placing into a first group. Further, the method comprises calculating correlations for all possible after sequences and determining the largest correlations for the after sequences, and placing into a second group. Further still, the method comprises piecing together the sequences of the first group, the second group, and the current symbol, to form a third group. Yet further still, the method comprises calculating the correlations for the third group and determining the largest correlation of the third group.