Communication System Data Transmission with Predictive Redundancy
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Solution Overview
Problem
Current communication systems face challenges in maintaining high-quality multimedia services due to data packet loss and congestion issues during data transmission, particularly in wireless IP networks, where existing methods like FEC codes and congestion avoidance methods are limited in recovery performance and delay, leading to degraded service quality.
Innovation Solution
The proposed solution involves an apparatus and method that includes a depacketizer, frame assembler, redundancy controller, and packetizer to predict data packet loss and congestion, adding redundant data to packets without delay, and aggregating data to avoid channel congestion, allowing for fast and normal data transmission and reception.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If forward error correction (FEC) code is used to recover lost data packets, then data recovery capability is improved, but transmission delay increases and service quality degrades
Solution Approach 1:
The patent applies preliminary action by predicting packet loss and congestion situations before they occur, and proactively generating redundant data and adjusting transmission parameters in advance. The system predicts packet loss probability based on historical data and network conditions, then pre-generates forward error correction codes and adjusts transmission rates before actual loss or congestion occurs, eliminating the need for reactive recovery that causes delay.
Solution Approach 2:
The patent implements dynamics by making the transmission system adaptive and variable. The forward error correction rate, redundancy data generation amount, and transmission parameters are dynamically adjusted based on real-time network conditions, packet loss probability predictions, and congestion situations. This allows the system to optimize between reliability and delay by varying correction rates and redundancy levels according to actual needs rather than using fixed parameters.
2Object-affected harmful factors
If congestion avoidance methods are implemented during data transmission, then channel congestion is reduced, but data transmission rate and service quality are limited
Solution Approach 1:
The patent applies feedback by continuously monitoring network conditions, packet loss situations, and transmission performance, then using this information to adjust transmission parameters. The system collects feedback on actual packet loss rates, congestion levels, and recovery effectiveness, and uses this feedback to dynamically adjust forward error correction rates, redundancy generation, and transmission scheduling, optimizing both congestion avoidance and transmission rate.
Solution Approach 2:
The patent implements parameter changes by varying transmission parameters such as forward error correction rate, packet size, transmission interval, and redundancy level based on network conditions. The system changes these parameters dynamically to balance congestion avoidance with maintaining high transmission rates, rather than using conservative fixed parameters that limit productivity.
3Quantity of substance
If large-capacity data packets are transmitted to provide multimedia services, then service quality is improved, but packet loss probability increases and recovery performance deteriorates
Solution Approach 1:
The patent applies segmentation by dividing large-capacity data into smaller packets or data units. This segmentation allows for more granular application of forward error correction and redundancy mechanisms. Instead of protecting entire large packets, the system segments data and applies correction codes to smaller units, improving recovery performance while maintaining overall data capacity for multimedia services.
4Reliability
If traditional loss recovery methods are used in IP networks, then some packet loss is recovered, but the intrinsic inability of IP networks to guarantee QoS remains and service quality degrades
Solution Approach 1:
The patent applies preliminary action by predicting packet loss and congestion before they occur, and proactively adjusting transmission parameters and generating redundancy in advance. This predictive approach addresses the intrinsic QoS guarantee limitation of IP networks by preventing loss rather than merely recovering it, thereby maintaining service quality that traditional reactive methods cannot achieve.
Data Source
AI summary
Disclosed is an apparatus for transmitting data in a communication system, including: a depacketizer configured to receive loss information on a data packet and congestion information on the channel from a terminal receiving the data packet through the channel; a frame assembly configured to confirm a congestion situation predictor from the congestion information and frame-aggregate data transmitted to the terminal according to the congestion situation predictor; a redundancy controller configured to confirm a data packet loss predictor from the loss information and generate redundancy data of the data according to the data packet loss predictor; and a packetizer configured to transmit the frame aggregated data and the redundancy data, with being included in the data packet.