MIMO Decoding via Quadrant-Based Tree Search
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Solution Overview
Problem
Conventional MIMO decoding techniques are computation-intensive, leading to high power consumption and resource utilization in receivers due to the need to process multiple interfering data streams, complicating the identification and decoding of data in communication networks.
Innovation Solution
The proposed solution employs a tree search method that selects a subset of decoding constellation points based on the sign value of nodes, reducing the number of calculations required for each tree level by expanding only the selected subset of candidate constellation points, rather than the entire set, thereby conserving system resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional MIMO decoding techniques are used to process multiple interfering data streams, then accurate decoding of data streams is achieved, but computational load and power consumption increase significantly
Solution Approach 1:
The patent segments the constellation points into different quadrants based on sign patterns, and processes only relevant quadrants instead of evaluating all constellation points. This segmentation reduces the computational search space while maintaining decoding accuracy by focusing resources on the most probable signal regions.
Solution Approach 2:
The patent applies partial action by evaluating only a subset of constellation points (those in relevant quadrants) rather than all possible points. This partial evaluation suffices for accurate decoding in MIMO systems, significantly reducing computational load and power consumption while maintaining reliability.
2Reliability
If conventional MIMO decoding techniques process all constellation points, then complete data stream identification is achieved, but device complexity and resource utilization increase
Solution Approach 1:
The receiver complexity is reduced by segmenting the constellation space into quadrants and selectively processing only those quadrants that contain relevant signal information. This segmentation approach maintains complete data stream identification while avoiding unnecessary computational operations on irrelevant constellation points.
Solution Approach 2:
The patent extracts and processes only the essential subset of constellation points (those in relevant quadrants) needed for accurate decoding, eliminating the need to process the entire constellation space. This extraction principle reduces device complexity while preserving decoding reliability.
3Reliability
If tree search expands all candidate constellation points at each level, then thorough search coverage is achieved, but computational load increases
Solution Approach 1:
The tree search process is optimized by segmenting the candidate constellation points into quadrants and expanding only those nodes corresponding to relevant quadrants. This segmentation maintains thorough search coverage within the relevant signal space while dramatically improving decoding efficiency by avoiding expansion of irrelevant nodes.
Solution Approach 2:
The patent applies partial action in the tree search by expanding only a subset of candidate nodes (those in relevant quadrants) rather than all nodes at each tree level. This partial expansion maintains decoding reliability by covering all probable signal paths while improving productivity through reduced computational load.
Data Source
AI summary
A decoder decodes a set of data streams received at a receiver based on a tree search that employs a subset of decoding constellation points. The decoder can form a tree wherein each level of the tree corresponds to one of the set of data streams. Each level of the tree includes a plurality of nodes corresponding to a set of candidate constellation points, wherein the set of candidate constellation points indicating possible values of data received via the set of data streams. For tree levels beyond an initial tree level, the decoder expands each node (that is, calculates the metrics for nodes of the next tree level) for only a subset of candidate constellation points, wherein the subset of candidate constellation points is based on a sign value of the node.