MIMO Symbol Detection Search Tree Thresholding
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Solution Overview
Problem
In MIMO wireless communication systems, especially in complex Beyond 5G and next-generation satellite broadband architectures, symbol detection and search processes become excessively time-consuming due to increasing modulation dimension complexity, requiring more efficient methods to maintain accuracy and speed.
Innovation Solution
A MIMO symbol detection and search method involving a symbol search tree where candidate symbols are sorted and traversed sequentially, with cumulative partial Euclidean distance thresholds to exclude unscanned symbols and update thresholds dynamically, utilizing a decoding circuit with sorting, controlling, distance calculating, and threshold updating units to optimize the search process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exhaustive search is performed on all candidate symbols in the symbol search tree, then detection accuracy is maintained, but search time increases exponentially with modulation dimension
Solution Approach 1:
The patent applies preliminary action by sorting candidate symbols at each layer of the symbol search tree before traversal. This pre-ordering allows the subsequent search process to evaluate symbols in a prioritized sequence, enabling early termination when the cumulative partial Euclidean distance exceeds the threshold, thus reducing search time while maintaining accuracy.
Solution Approach 2:
The patent implements partial action by using a threshold-based early termination strategy. Instead of exhaustively searching all candidate symbols, the algorithm stops searching when the cumulative partial Euclidean distance exceeds a predefined threshold, indicating that no further symbols can improve the detection accuracy. This partial search approach significantly reduces computation time while preserving detection performance.
2Productivity
If dynamic threshold updating is implemented during symbol search, then search efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent applies feedback by dynamically updating the threshold based on the cumulative partial Euclidean distance calculated during the search process. The threshold is adjusted according to the actual search progress and distance metrics, allowing the system to adaptively control the search depth and width. This feedback mechanism improves search efficiency by avoiding unnecessary computations while maintaining manageable computational complexity through iterative updates.
Data Source
AI summary
A MIMO symbol detection and search method, a decoding circuit and a receiving antenna system are provided. The signal detection and search method includes the following steps. A symbol search tree is obtained, and a plurality of candidate symbols at each layer of the symbol search tree are sorted. The candidate symbols are traversed in sequence at each layer of the symbol search tree. At each layer of the symbol search tree, if a cumulative partial Euclidean distance is greater than or equal to a threshold, un-scanned candidate symbols are excluded. If the cumulative partial Euclidean distance is less than the threshold, the threshold is updated by the cumulative partial Euclidean distance. When all of the candidate symbols have been calculated, an estimated symbol combination is outputted, and the scan of the symbol search tree is terminated.