Sequential Decoder Stack Reordering for Bounded Node Search
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Solution Overview
Problem
Existing wireless communication systems face challenges in managing computational complexity and stack size limitations during sequential decoding, particularly in high-dimensional constellations and real-time applications, leading to inefficiencies in decoding processes.
Innovation Solution
A decoder system that includes a symbol estimation unit and a stack reordering activation monitoring unit, which reduces and reorders node metrics to maintain a manageable stack size, allowing for efficient decoding by favoring nodes with lower metrics and enabling early termination or adaptive stack management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If stack decoding technique is used to reduce computational complexity, then decoding complexity is reduced, but stack size increases excessively for high-dimensional constellations
Solution Approach 1:
The patent changes the ordering parameter of the stack from metric-only sorting to a hierarchical ordering where nodes are first sorted by tree level (depth) and then by metric within each level. This parameter change in the sorting criterion allows the decoder to process nodes level-by-level, significantly reducing the maximum stack size required while maintaining decoding performance for high-dimensional constellations
Solution Approach 2:
The patent segments the stack processing into multiple levels corresponding to tree depths. Instead of maintaining a single large stack with all candidate nodes, the decoder processes nodes level-by-level, where each level contains only nodes at that specific depth. This segmentation divides the large stack into smaller level-specific stacks, reducing memory requirements while preserving the search capability
2Reliability
If exhaustive search ML decoding is used to achieve optimal performance, then decoding performance is optimized, but computational complexity increases prohibitively
Solution Approach 1:
The patent implements a dynamic decoding approach where the search strategy adapts based on the received signal and channel conditions. The hierarchical stack decoder dynamically explores the decoding tree level-by-level, expanding only the most promising nodes at each level rather than exhaustively searching all nodes. This dynamic adaptation maintains near-optimal performance while significantly reducing computational complexity for practical implementation
3Productivity
If constellation size or number of antennas increases to improve communication capacity, then system capacity increases, but decoding complexity and stack size increase prohibitively
Solution Approach 1:
The patent introduces a new dimension to the decoding process by organizing the search space hierarchically across multiple tree levels. Instead of treating all candidate nodes equally in a flat stack structure, the invention adds the tree level dimension, creating a multi-dimensional search organization. This allows the decoder to handle high-dimensional constellations and multiple antennas by processing the search space level-by-level, reducing the effective dimensionality at each processing step while maintaining overall system capacity
Data Source
AI summary
There is provided a decoder (310) for sequentially decoding a data signal received through a transmission channel in a communication system, the received data signal carrying transmitted symbols, the decoder comprising a symbol estimation unit (311) configured to determine estimated symbols representative of the transmitted symbols carried by the received signal from information stored in a stack, the stack being filled by iteratively expanding child nodes of a selected node of a decoding tree comprising a plurality of nodes, each node of the decoding tree corresponding to a candidate component of a symbol of the received data signal and each node being associated with a predetermined metric, the stack being filled at each iteration with at least some of the expanded child nodes and being ordered by increasing values of the metrics associated with the nodes, the selected node for each iteration corresponding to the node having the lowest metric in the stack. The decoder further comprises a stack reordering activation monitoring unit (313) configured to monitor at least one stack reordering activation condition and, in response to a stack reordering activation condition being verified, to cause the symbol estimation unit to:reduce the metric associated with each node stored in the stack by a quantity,reorder the stack by increasing value of the reduced metric, andremove a set of nodes from the reordered stack so as to maintain a number N of nodes in the reordered stack, the maintained nodes corresponding to the N nodes having the lowest metrics in the reordered stack.