Modulation Adaptation Using Error Pattern Analysis
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Solution Overview
Problem
Conventional modem adaptation methods for channels with complex and non-linear noise, such as low voltage power grids, fail to accurately predict optimal modulation modes due to reliance on general parameters like signal-to-noise ratio, leading to inefficient error coding and reduced channel throughput.
Innovation Solution
A method for choosing optimal modulation modes by analyzing packets with unknown data patterns, where the receiver determines error patterns and adjusts error correction coding on a per-carrier basis, allowing for efficient error correction while maximizing throughput by selecting the least redundancy necessary to correct errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional adaption methods transmit known data patterns for receiver comparison, then modulation mode selection accuracy is improved, but bandwidth utilization deteriorates and latency increases
Solution Approach 1:
The patent extracts only the necessary error pattern information from received packets without requiring transmission of known data patterns. The receiver analyzes error patterns directly from unknown data packets and sends back condensed adaptation information, eliminating the bandwidth waste associated with transmitting known patterns for comparison.
Solution Approach 2:
The patent introduces an intermediary adaptation process where the receiver analyzes error patterns and generates adaptation information that mediates between the channel conditions and modulation mode selection. This intermediary step allows accurate adaptation without requiring the transmitter and receiver to share known patterns.
2Productivity
If general parameters like signal-to-noise ratio are measured for adaption, then bandwidth utilization is improved, but modulation mode selection accuracy deteriorates in non-Gaussian noise channels
Solution Approach 1:
The patent applies local quality by analyzing error patterns specifically in the context of the actual received data rather than relying on general channel parameters. The error pattern analysis is tailored to the specific packet and channel conditions, providing locally optimized adaptation decisions that work accurately in non-Gaussian noise environments.
Solution Approach 2:
The patent changes the adaptation parameter from general measurements like signal-to-noise ratio to specific error patterns observed in received packets. This parameter change enables the system to adapt to non-Gaussian and non-linear noise characteristics that cannot be captured by traditional statistical measures.
3Reliability
If high redundancy error correction coding is used, then communication reliability is improved, but channel throughput deteriorates
Solution Approach 1:
The patent implements dynamic adaptation of error correction coding by continuously analyzing error patterns from received packets and adjusting the coding redundancy accordingly. The system transitions from static high redundancy to dynamic adjustment, using only the necessary amount of redundancy to correct observed errors, thereby optimizing the trade-off between reliability and throughput.
Solution Approach 2:
The patent establishes a feedback loop where the receiver analyzes error patterns in received packets and sends adaptation information back to the transmitter. This feedback enables the transmitter to adjust the error correction coding redundancy to match the actual channel conditions, avoiding excessive redundancy while maintaining communication reliability.
Data Source
AI summary
Systems, methods, and apparatuses are disclosed for choosing the modulation mode using packets transmitted by a sender to a receiver, wherein the packets contain data patterns unknown to the receiver. In some embodiments, the sender sends of a data packet in the most robust mode available, such that the packet can be correctly received by the receiver under even the noisiest conditions. The data contained in the packet is demodulated and decoded. A cyclic redundancy check is performed to ensure that the resultant data is error-free. Once the transmitted payload data is known, the original error coding can be re-applied to the payload data to produce the transmitted bit stream. Comparison of the demodulated bit stream to the regenerated transmitted bit stream yields the pattern of errors. The pattern of errors is analyzed and a higher throughput decoding scheme is chosen based on the results of the analysis.