Adjustable Throughput Estimation Threshold for Wireless Modems
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Solution Overview
Problem
Fixed thresholds for switching between throughput estimation techniques in wireless communication systems lead to inaccurate estimates, causing underutilization of network resources, delays, and failure to meet quality of service parameters due to variations in scheduling rates unrelated to data transfer.
Innovation Solution
Implementing an adjustable threshold based on the scheduling rate and its moving average to dynamically select appropriate throughput estimation techniques, ensuring accurate estimation and efficient resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed threshold is used for switching between throughput estimation techniques, then the switching decision is simple and fast, but the throughput estimation accuracy deteriorates due to variations in scheduling rates unrelated to data transfer
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed threshold to a dynamic threshold that adapts to changing network conditions. The threshold is adjusted based on historical scheduling rate data and moving averages, allowing the system to respond to variations in scheduling rates while maintaining accurate throughput estimation. This resolves the contradiction by making the switching criterion flexible rather than static.
Solution Approach 2:
The patent changes the parameter used for threshold determination from a fixed value to a dynamically calculated value based on scheduling rate statistics. By introducing parameters such as historical scheduling rates, moving averages, and standard deviations, the system can distinguish between scheduling rate variations caused by data transfer versus those caused by other factors, thereby improving throughput estimation accuracy without sacrificing switching speed.
2Device complexity
If a fixed threshold is used for switching between throughput estimation techniques, then the system complexity is low, but network resource utilization deteriorates due to inaccurate throughput estimates
Solution Approach 1:
The system introduces dynamic threshold adjustment mechanisms that adapt to network conditions while maintaining manageable complexity. By using moving averages and statistical parameters of scheduling rates, the system achieves accurate throughput estimation without requiring overly complex algorithms, thus improving network resource utilization without excessive complexity increase.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors scheduling rates and adjusts the threshold based on observed patterns. This feedback loop enables the system to learn from historical data and improve its throughput estimation accuracy over time, leading to better network resource utilization while keeping the complexity increase moderate through iterative adaptation rather than complex upfront design.
3Ease of manufacture
If a fixed threshold is used for switching between throughput estimation techniques, then the implementation is simple, but communication delays increase due to inaccurate throughput estimates
Solution Approach 1:
The patent modifies the threshold parameter from a fixed value to a dynamically calculated value based on scheduling rate statistics. This change enables more accurate throughput estimation, which in turn allows for better optimization of communication parameters and reduction of delays, while the implementation remains relatively straightforward by building upon existing threshold-based switching mechanisms.
Solution Approach 2:
The system performs preliminary analysis of scheduling rate patterns and calculates appropriate thresholds in advance, before actual throughput estimation is needed. By pre-computing moving averages and statistical parameters, the system prepares optimized switching criteria that reduce communication delays without adding complex real-time processing requirements during critical estimation periods.
Data Source
AI summary
Some techniques described herein provide identification of a throughput estimate using a throughput estimation technique that is selected in accordance with an adjustable threshold. For example, the adjustable threshold may be based at least in part on a scheduling rate of a user equipment. In some aspects, the threshold may be adjustable based at least in part on a scheduling rate and a moving average derived from the scheduling rate. For example, the threshold may change over time based at least in part on a moving average derived from a past value of the scheduling rate and/or a current value of the scheduling rate. Thus, the threshold may decrease over time when the scheduling rate is relatively low (e.g., lower than the threshold), and may increase over time when the scheduling rate is relatively high (e.g., higher than the threshold).