Preemptive Retransmit for Error Recovery in Communications
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Solution Overview
Problem
Existing communication systems face challenges in optimizing error recovery while minimizing bandwidth usage and overhead, as conventional compression/suppression techniques are static, unresponsive, and inefficient, leading to increased costs and delays.
Innovation Solution
A preemptive retransmit method that suppresses static samples and retransmits only changed samples after a configured time interval, reducing unnecessary data transmission and eliminating the need for round-trip delays, thereby enhancing error recovery and conserving bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional compression/suppression techniques are used to reduce bandwidth usage, then bandwidth savings are achieved, but error recovery capability deteriorates due to static and unresponsive protocols
Solution Approach 1:
The patent implements a dynamic suppression protocol that continuously monitors communication patterns and adapts its suppression decisions based on real-time conditions. Unlike static protocols, this dynamic approach can respond to changing traffic patterns and error conditions, maintaining reliability while achieving bandwidth savings through intelligent, adaptive suppression of redundant data.
Solution Approach 2:
The system incorporates feedback mechanisms where the receiver provides information about received data quality and error conditions back to the transmitter. This feedback loop enables the transmitter to adjust its suppression strategy accordingly, retransmitting suppressed data when errors are detected and maintaining optimal error recovery capability while minimizing bandwidth usage during normal operation.
2Device complexity
If static compression protocols are implemented to minimize overhead, then system overhead is reduced, but responsiveness to error conditions worsens due to lack of adaptability
Solution Approach 1:
The protocol transitions from static to dynamic operation, where suppression patterns are continuously adjusted based on observed communication patterns and error conditions. This dynamic behavior allows the system to maintain low overhead during stable conditions while rapidly adapting when errors or pattern changes are detected, achieving both low overhead and high responsiveness.
Solution Approach 2:
The system employs self-service mechanisms where the compression protocol automatically monitors its own performance and error conditions, then autonomously adjusts its suppression strategy without requiring complex external control. This self-adjusting capability maintains simplicity while improving responsiveness to changing conditions.
3Reliability
If round-trip delay protocols are used for error detection and correction, then error recovery accuracy is improved, but communication delay increases significantly
Solution Approach 1:
The system performs preliminary actions by proactively retransmitting suppressed data before errors are detected or at strategically timed intervals rather than waiting for round-trip error reports. This preliminary retransmission approach ensures error recovery capability is maintained while minimizing the actual delay experienced, as corrections are already in transit when errors occur.
Solution Approach 2:
The protocol skips the traditional slow round-trip error detection process by implementing unidirectional retransmission of suppressed data without waiting for acknowledgment. This rushing through the error recovery process eliminates the bidirectional wait time while maintaining recovery accuracy, significantly reducing communication delay.
Data Source
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AI summary
A method for communicating data is provided that includes receiving a plurality of bits associated with a communications flow and determining whether one or more samples included in the flow should be suppressed. The method also includes suppressing a selected one or more of the samples. The method also includes retransmitting certain samples when a given sample has stopped changing, in comparison to a previously received sample, for a configured time interval.