Multi-Stage Symbol Block Detection for Reduced Complexity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current symbol block detection methods in DS-CDMA and MIMO systems face high computational complexity due to intersymbol interference (ISI) and large number of possible symbol combinations, especially at higher data rates, making existing approaches impractical for efficient processing.
Innovation Solution
A demodulator with multiple stages of detection assistance is used to reduce the number of candidate symbol combinations by identifying the most likely symbol values and groups, progressively reducing the complexity of symbol block detection through assisting detectors and a final assisting detector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If maximum likelihood sequence estimation (MLSE) is used to detect all possible symbol combinations, then detection accuracy is improved, but computational complexity increases exponentially with the number of symbols in each block
Solution Approach 1:
The patent segments the detection process into multiple stages: first detecting individual symbols or small groups of symbols, then progressively combining them into larger groups. This segmentation transforms the exponential complexity of detecting all N symbols simultaneously into a manageable multi-stage process where each stage handles fewer combinations, thereby resolving the contradiction between detection accuracy and computational complexity.
Solution Approach 2:
The patent performs preliminary detection of individual symbols or small groups before proceeding to detect larger symbol blocks. By establishing initial detection results and using them to constrain subsequent detection stages, the system reduces the search space exponentially while maintaining accuracy, thus resolving the complexity-accuracy tradeoff.
2Productivity
If the number of symbols in each symbol block is increased to achieve higher data rates, then productivity is improved, but the number of possible symbol combinations increases exponentially
Solution Approach 1:
The patent divides the detection of large symbol blocks into multiple smaller detection stages. Instead of attempting to detect all symbols in a large block simultaneously (which would require examining M^N combinations), the system segments the block into smaller groups detected in sequence, reducing complexity from exponential to polynomial in the number of symbols.
Solution Approach 2:
The patent employs dynamic programming techniques where the detection process adapts based on intermediate results. Each detection stage uses the results from previous stages to dynamically constrain the search space for subsequent stages, allowing the system to handle larger symbol blocks at higher data rates without exponential complexity growth.
3Device complexity
If single-stage detection assistance is used to reduce complexity by identifying K most likely symbol values, then computational complexity is reduced, but it remains overly complicated for symbol blocks with many symbols
Solution Approach 1:
The patent extends single-stage detection assistance into multiple sequential stages. Each stage applies detection assistance to a subset of symbols or a refined search space based on previous stage results. This multi-stage approach progressively reduces complexity to a level practical for high data rate applications with many symbols per block, whereas single-stage assistance would still require managing K^N combinations.
Solution Approach 2:
The patent performs preliminary detection assistance in multiple stages rather than relying on a single stage. Each preliminary stage narrows the search space for the next stage, creating a cascade of constrained searches that collectively reduce the overall complexity to a practically manageable level for high data rate symbol blocks.
Data Source
Figure 1
Figure 2A~2B
Figure 2C~2D
AI summary
Teachings presented herein offer reduced computational complexity for detecting a plurality of symbol blocks, even for symbol blocks that comprise the combination of a relatively large number of symbols. The teachings perform two or more stages of detection assistance to successively reduce the number of candidate combinations of symbols to be considered for a symbol block when detecting the plurality of symbol blocks. In particular, the teachings identify a reduced set of candidate symbol combinations for at least one symbol block in the plurality of symbol blocks, and then jointly detect each of one or more distinct groups of symbols in the symbol block to determine from that reduced set a final reduced set of candidate symbol combinations. Detection of the plurality of symbol blocks limits the candidate combinations of symbols considered for a symbol block to the final reduced set of candidate symbol combinations identified for that symbol block.