Bi-Directional Syndrome Decoding for Higher-Throughput Data Sharing
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Solution Overview
Problem
In Quantum Key Distribution and other data sharing systems, the throughput rate of error correction is limited by the computational effort required for encoding and decoding, particularly in Slepian-Wolf coding, where the asymmetric usage of computational resources between transmitters and receivers leads to inefficiencies.
Innovation Solution
A bi-directional decoding system is implemented, where both the transmitter and receiver divide and decode signals using a common policy, balancing computational resources and reducing the computational burden by performing syndrome calculation and decoding in parallel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If Slepian-Wolf coding is used for error correction, then the amount of redundant information is minimized, but the computational complexity of encoding increases
Solution Approach 1:
The patent inverts the traditional error correction approach by having the receiver perform encoding operations instead of the transmitter. The receiver generates multiple encoded versions of the transmitted data using different encoding policies, and the transmitter simply sends the original data without encoding. This reversal reduces transmitter computational complexity while maintaining error correction capabilities.
Solution Approach 2:
The patent segments the encoding process into multiple parallel encoding operations performed at the receiver side. Instead of one complex encoding at the transmitter, the receiver performs multiple simpler encoding operations with different policies, selecting the most effective one for error correction.
2Reliability
If traditional forward error correction is used, then error correction capability is achieved, but the throughput rate is limited by computational effort
Solution Approach 1:
By inverting where encoding occurs (from transmitter to receiver), the patent eliminates the encoding computational bottleneck at the transmitter side. The receiver, which already needs to decode and process the data anyway, performs the additional encoding operations as part of its normal processing workflow, thereby improving overall throughput rate while maintaining error correction capability.
Solution Approach 2:
The receiver serves itself by performing the encoding operations that traditionally would be done by the transmitter. This self-service approach eliminates the need for separate encoding computational resources at the transmitter, utilizing the receiver's existing decoding computational infrastructure instead.
3Measurement precision
If computational resources are concentrated at the receiver side, then decoding accuracy is improved, but the system becomes asymmetric and less efficient
Solution Approach 1:
The patent embraces and optimizes the asymmetric architecture by concentrating computational resources at the receiver side. Rather than attempting to balance computational load symmetrically between transmitter and receiver, the invention accepts the asymmetry and designs the system to leverage the receiver's decoding capabilities for both decoding and encoding operations, thereby improving overall system efficiency within the asymmetric constraint.
Solution Approach 2:
The receiver is designed to perform multiple functions: traditional decoding operations and the inverted encoding operations. This multi-functionality allows the receiver to utilize its computational resources efficiently for both error correction decoding and error prevention encoding, improving overall system efficiency despite the asymmetric resource distribution.
Data Source
AI summary
According to one embodiment, a transmitter includes a signal dividing unit, a syndrome sending unit, a syndrome receiving unit and a decoding unit. The signal dividing unit divides an original signal into a first signal and a second signal based on a common dividing policy. The syndrome sending unit sends the first syndrome message calculated based on the first signal through a clear channel. The syndrome receiving unit receives a second syndrome message through the clear channel. The decoding unit decodes the second signal by using the second syndrome message to restore a fourth signal, the fourth signal being corresponding to the second signal received by a receiver through a noisy channel.