Dynamic Context Resource Module for Wireless Signal Compression
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Solution Overview
Problem
Current compression techniques in wireless communication systems struggle to achieve an average compression ratio with reasonable signal degradation and low latency jitter, especially when dealing with rapidly changing signal behavior, and are not adaptable to the unique characteristics of individual signal streams in carrier aggregation systems.
Innovation Solution
A dynamic context resource module adjusts compression parameters for each signal stream based on its performance level, using a compression parameter estimation module to determine if the desired performance is met, and adjusting parameters accordingly to ensure efficient compression with low latency and jitter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If predetermined compression parameters are used, then the compression process is simple and fast, but the compression ratio deteriorates when signal behavior changes rapidly
Solution Approach 1:
The patent implements dynamic compression parameter adjustment by continuously monitoring signal characteristics (variance, correlation coefficient) and adapting compression parameters in real-time. The system transitions from static predetermined parameters to dynamic parameters that evolve with signal behavior, resolving the contradiction between compression speed and adaptability.
Solution Approach 2:
The patent employs feedback mechanisms where compression performance is continuously evaluated and used to adjust compression parameters. The system measures signal characteristics before and after compression, and uses this feedback to optimize parameters dynamically, maintaining high compression ratios despite signal variations.
2Quantity of substance
If higher compression ratios are achieved, then bandwidth requirements are reduced, but latency jitter increases
Solution Approach 1:
The patent changes compression parameters dynamically based on signal characteristics to optimize the balance between compression ratio and latency jitter. By adjusting parameters like quantization precision and prediction order according to signal variance, the system achieves high compression ratios while maintaining acceptable latency performance.
3Productivity
If compression techniques are applied to carrier aggregation with 8×8 MIMO and CoMP, then spectral efficiency is improved, but the number of optical or wireless links increases
Solution Approach 1:
The patent extracts and removes redundancy from the large volume of data generated by carrier aggregation with 8×8 MIMO and CoMP techniques. By applying sophisticated compression algorithms that identify and eliminate redundant information across multiple streams, the system reduces the amount of data requiring transmission over optical or wireless links, thereby reducing infrastructure complexity while maintaining high spectral efficiency.
4Adaptability or versatility
If compression parameters are adjusted dynamically, then compression performance improves with changing signals, but the complexity of the compression system increases
Solution Approach 1:
The patent segments the compression system into distinct functional modules: signal characteristic analysis, parameter selection, compression execution, and performance evaluation. This modular segmentation allows dynamic adaptation to signal changes while managing system complexity through organized, independent components that can be developed and optimized separately.
Data Source
AI summary
A dynamic context resource module measures a compression performance level of a most recent compressed data packet of each of a plurality of compressed signal streams to generate a signal stream compression performance level for each signal stream. Dynamic compression performance indicators are calculated from the measured signal stream compression performance levels and are stored in a dynamic context resource table. A compression parameter estimation module reads the dynamic compression performance indicators and determines if each signal stream exhibits a desired performance level. If a signal stream does not exhibit the desired performance level, the compression parameters for the signal stream are adjusted. A compressed packet generator compresses a next data packet of the signal stream based upon the adjusted compression parameters for the signal stream or the unadjusted compression parameters for the signal stream.