Wireless Receiver Signal Quality Processing Routine Selection
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Solution Overview
Problem
In wireless communication systems, particularly in CDMA technology, there is a challenge in optimizing signal processing performance while minimizing computing resources and power consumption, especially when the transmitter has reached its minimum power level and the receiver experiences excess signal quality, leading to inefficient power control and potential degradation in service quality.
Innovation Solution
A method and system that compare target signal quality with estimated received signal quality, allowing for the selection of processing routines of varying sensitivities to adjust transmit power and optimize processing, including options like reducing complexity in algorithms, discarding data, or lowering channel estimation rates, to maintain quality of service without excessive resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high-sensitivity processing routines are used to maintain signal quality, then service quality is improved, but power consumption and computational resources increase
Solution Approach 1:
The system dynamically adapts the sensitivity of processing routines based on real-time signal quality conditions. When signal quality exceeds the target threshold, the system switches to lower-sensitivity processing modes, and when signal quality approaches the threshold, it transitions to higher-sensitivity modes. This dynamic adaptation allows the system to maintain service quality while minimizing power consumption and computational resource usage under varying channel conditions.
Solution Approach 2:
The system changes key processing parameters such as channel estimation rate, data discarding thresholds, and algorithm complexity based on signal quality measurements. By adjusting these parameters dynamically, the system can reduce computational load and power consumption when signal conditions are good, while maintaining high processing sensitivity when signal quality degrades, thus resolving the contradiction between reliability and energy consumption.
2Measurement precision
If high-sensitivity processing routines are used, then signal detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The system employs dynamic selection of processing routine sensitivity levels based on measured signal quality. When the estimated signal quality exceeds the target quality threshold, the system automatically selects lower-sensitivity processing routines with reduced computational complexity. Conversely, when signal quality approaches the threshold, it switches to higher-sensitivity routines. This dynamic behavior maintains detection accuracy when needed while reducing computational burden during favorable conditions.
Solution Approach 2:
The system adjusts processing parameters including channel estimation intervals, despreading algorithm complexity, and equalization sophistication based on signal quality conditions. By changing these parameters dynamically, the system achieves adaptive computational complexity that matches the actual signal conditions, maintaining high detection accuracy only when necessary and reducing complexity during good signal conditions.
3Loss of energy
If transmit power is reduced to minimum level, then power efficiency is improved, but signal quality may degrade under poor channel conditions
Solution Approach 1:
The system implements a feedback mechanism where the estimated signal quality is continuously monitored and compared against a target quality threshold. Based on this feedback, the system dynamically adjusts the sensitivity of processing routines. This feedback loop enables the system to maintain adequate signal quality even at minimum transmit power by adapting processing sensitivity to current channel conditions, thus resolving the contradiction between power efficiency and signal quality.
Solution Approach 2:
The receiver system performs self-adjustment of processing sensitivity based on its own measurements of signal quality. By monitoring its received signal conditions and autonomously selecting appropriate processing routines, the system compensates for reduced transmit power through optimized signal processing, maintaining service quality without requiring additional power expenditure.
Data Source
AI summary
A system and method for processing digital samples from a signal received via a wireless transmission channel in a wireless communications system. The method comprises: comparing a target signal quality value with an estimated received signal quality value; detecting if the estimated received signal quality value exceeds the target signal quality value for a period; and selecting one of a plurality of processing routines of differing sensitivities for processing the digital samples.