RF Rate Determination via Entropy Signal Characterization
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Solution Overview
Problem
The increasing demand for wireless data services and the growing congestion in the radio spectrum require techniques to enable reliable operation in crowded RF environments, where interference is tolerated or even invited, necessitating methods for efficient co-occupation of RF bands and effective interference mitigation.
Innovation Solution
A machine-implemented method for determining data rates and selecting transmit parameter combinations in wireless systems, involving monitoring RF energy, characterizing signals, estimating maximum sum rates, and using multi-user detection receivers to mitigate interference, allowing multiple users to share RF bands without detrimental effects on existing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple users co-occupy the same RF band to increase spectrum utilization, then throughput and spectral efficiency are improved, but interference between users increases and reliability deteriorates
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting transmit power levels, modulation schemes, and coding rates based on detected interference conditions. The system monitors RF energy and characterizes signals to determine optimal parameters that maximize throughput while maintaining reliable performance in co-occupied bands.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring RF energy, characterizing received signals, and using this information to adapt transmit parameters. The entropy-based signal characterization provides feedback about channel conditions that drives parameter optimization for reliable multi-user operation.
2Reliability
If advanced interference mitigation techniques are implemented to enable reliable operation in crowded RF environments, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical or algorithmic interference mitigation systems with an entropy-based signal characterization approach. By using entropy calculations on I/Q histograms to identify structured signals versus noise, the system achieves reliable operation without requiring sophisticated multi-user detection algorithms or complex interference cancellation mechanisms.
Solution Approach 2:
The system introduces entropy-based signal characterization as an intermediary between raw RF measurements and interference mitigation decisions. This intermediary layer simplifies the detection process by providing a clear metric for distinguishing structured signals from noise, enabling reliable operation without complex direct interference mitigation techniques.
3Measurement precision
If entropy-based signal characterization is used to detect structured signals in noisy environments, then measurement precision is improved, but computational requirements increase
Solution Approach 1:
The system applies partial action by calculating entropy only on binned I/Q histogram data rather than on raw sample streams. This approach achieves sufficient measurement precision for signal detection while significantly reducing computational energy requirements compared to processing every individual sample through complex entropy calculations.
Data Source
AI summary
Techniques are described for determining rates and other parameters for users associated with a multiple access channel (MAC). In at least one embodiment, a rate determination tool having a GUI interface is provided.