Nested Source Coding for Unknown Active Encoder Sets
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Solution Overview
Problem
Current lossless source coding technologies face challenges in achieving optimal performance, especially in finite-blocklength scenarios with non-vanishing error probabilities, particularly in point-to-point, multiple access, and random access communication regimes, where achieving third-order optimal performance is difficult due to sub-optimal decoder designs and lack of knowledge about the distribution of sources.
Innovation Solution
The development of systems and methods that utilize random codes with maximum likelihood decoding and threshold decoding to achieve near-optimal performance in point-to-point communication, and extend this to multiple access and random access scenarios by employing a nested code structure and single deterministic codes that can handle unknown or varying sets of active encoders, allowing for reliable source reconstruction with limited feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Shannon's theory is used for lossless source coding, then the information-theoretic limit is achieved, but an arbitrarily long encoding blocklength is required which is not suitable for delay-sensitive applications
Solution Approach 1:
The patent changes the parameter of blocklength from arbitrary/long to finite/specified, and adjusts the error probability parameter from vanishing to non-vanishing but controlled, to achieve practical coding performance for delay-sensitive applications while maintaining theoretical optimality
2Reliability
If optimal codes are designed to achieve fundamental limits, then coding performance is maximized, but the device complexity increases due to the need for complex decoder designs and knowledge of source distribution
Solution Approach 1:
The patent employs random codebooks that are simple to generate and use, sacrificing the need for complex optimal code designs. The random codes achieve near-optimal performance without requiring complex decoders or knowledge of source distribution, making the system practically implementable
Solution Approach 2:
The system uses the received codewords themselves to directly determine the most likely source sequence through maximum likelihood decoding, without requiring external knowledge of source distribution or complex processing. The decoder serves itself by using the code structure and received signals to achieve optimal reconstruction
3Reliability
If separate optimal codes are designed for each communication scenario, then each scenario achieves its fundamental limit, but the adaptability decreases when dealing with unknown or time-varying encoder sets
Solution Approach 1:
The patent designs a universal random codebook that can serve multiple communication scenarios (point-to-point, multiple access, random access) simultaneously. The same codebook structure and maximum likelihood decoding rule achieve near-optimal performance across all scenarios, providing both scenario-specific optimality and adaptability to unknown encoder configurations
Data Source
AI summary
Systems and methods in accordance with various embodiments of the invention perform lossless source coding. Nested code structures are utilized to perform Random Access Source Coding (RASC), where the number of active encoders is initially unknown. Decoders can attempt to source decode using a number of Slepian-Wolf decoders corresponding to an estimated number of sources. Multiple source encoders are configured to receive start messages and transmit portions of codewords, selected by source encoding data from sources to remove redundancy, until an end of epoch message is received.