Probabilistic Symbol Encoding for Higher-Capacity Data Transmission
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current transmission capacity per transmission line, such as optical fiber, is insufficient for efficiently transmitting large volumes of data in a short time, particularly for applications like video streaming or electronic sports.
Innovation Solution
A communication system that includes an encoding unit transforming input symbol sequences into output symbol sequences based on encoding-side transformation destination candidate information and transformation probabilities, and a decoding unit transforming the output sequences back, using predefined probability distributions to increase transmission capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional transmission methods are used, then the transmission line can operate with standard capacity, but the transmission capacity is insufficient for large volume data in short time
Solution Approach 1:
The patent applies parameter changes by transforming symbol sequences using probability distributions. The encoding unit transforms input symbol sequences into output symbol sequences according to a first probability distribution, while the decoding unit transforms received symbol sequences according to a second probability distribution. This probabilistic transformation approach changes the statistical parameters of the transmitted data, enabling higher transmission capacity by optimizing how data is mapped to transmission symbols, thereby increasing productivity while maintaining acceptable transmission time
2Productivity
If transmission capacity is increased using probability distribution transformation, then data transmission efficiency is enhanced, but the system complexity increases due to encoding and decoding units
Solution Approach 1:
The patent uses parameter changes through probabilistic symbol transformation. Instead of increasing physical transmission infrastructure, the system changes the statistical parameters of the transmitted symbols using predefined probability distributions. The encoding unit applies a first probability distribution to transform input symbols, and the decoding unit applies a second probability distribution to recover original data. This approach increases transmission capacity without proportionally increasing device complexity, as the complexity is confined to software-based probability transformation algorithms rather than hardware expansion
Data Source
AI summary
An aspect of the present invention is a communication system including: an encoding unit configured to transform an input symbol sequence into an output symbol sequence, the input symbol sequence being a sequence of first symbols, the output symbol sequence being a sequence of second symbols; and a decoding unit configured to transform the output symbol sequence into the input symbol sequence in accordance with a decoding-side transformation mapping for transforming the output symbol sequence into the input symbol sequence that is a transformation source for the output symbol sequence, wherein the encoding unit transforms the input symbol sequence into the output symbol sequence in accordance with encoding-side transformation destination candidate information, the input symbol sequence, and a transformation probability, the encoding-side transformation destination candidate information being information indicating candidates of a transformation destination for the input symbol sequence, the transformation probability being a probability of transformation into the transformation destination indicated by the encoding-side transformation destination candidate information, and a probability of appearance of the second symbol conforms to a predefined prescribed probability distribution.