Graph-Based Iterative Decoding for Unordered Mesh Network Copies
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Solution Overview
Problem
Existing error correcting decoders are not adapted to the topology of mesh networks, where relay nodes create additional copies of messages, leading to variable arrival times and potential loss of copies, making it impossible to recover the initial message due to unordered reception and possible data loss.
Innovation Solution
A system comprising soft decision decoders and a graph-based decoder that separately decodes multiple copies of a data word, using an algorithm to propagate messages within a graph-based decoder to determine a decoding value, adapting to the number of copies received and accounting for additional redundancy information generated by relay nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If relay nodes duplicate and re-transmit messages in mesh networks, then message delivery reliability is improved, but copy arrival order becomes variable and decoding becomes impossible with prior art
Solution Approach 1:
The decoding process is segmented into multiple independent stages: soft decision decoding of individual copies, graph construction from decoded copies, and iterative belief propagation on the graph. This segmentation allows the system to handle variable arrival orders and copy losses by processing each copy independently and combining results through the graph structure.
Solution Approach 2:
A graph structure serves as an intermediary between received copies and final decoding. The graph nodes represent decoded copies and edges represent relationships between them, enabling the system to process copies in any order and combine information from multiple paths to achieve reliable decoding despite variable arrival times and potential copy losses.
2Loss of information
If multiple copies of messages are transmitted through different paths, then redundancy information is increased, but copies may be lost and reception order becomes unpredictable
Solution Approach 1:
The system performs soft decision decoding on each received copy immediately upon arrival, before knowing whether other copies will arrive. This preliminary action converts received copies into decoded form that can be immediately incorporated into the graph structure, allowing the system to utilize available redundancy information progressively as copies arrive in unpredictable orders.
Solution Approach 2:
The iterative belief propagation algorithm provides feedback loops where decoded information from the graph is used to refine soft decisions on received copies, which in turn updates the graph. This feedback mechanism allows the system to progressively improve decoding reliability by utilizing redundancy information from multiple copies even when some copies are lost or arrive late.
3Measurement precision
If prior art decoders require all copies to be received in order, then decoding accuracy is maintained, but decoding fails when copies are lost or arrive out of order
Solution Approach 1:
The graph structure dynamically adapts to the actual set of received copies regardless of arrival order or which specific copies were lost. The graph is constructed from whichever copies are available, and the belief propagation algorithm iteratively refines decoding based on the current graph state. This dynamic adaptation maintains decoding accuracy while providing versatility for mesh network topology variations.
Data Source
AI summary
In the field of coding/decoding in telecommunications networks, an error correcting decoder and associated decoding method are adapted to a mesh network.In particular, the system for the decoding of a plurality of coded copies of a data word includes at least a first decoding stage with:a plurality of soft decision decoders, each decoder being arranged for decoding a coded copy received as decoder input, anda graph-based decoder comprising a plurality of nodes, each node of said graph-based decoder receiving the soft output value from a corresponding decoder and the graph-based decoder determining a decoding value of said data word on the basis of said soft output values.