Wireless Device Throughput Estimation via Active Node Counting
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Solution Overview
Problem
Wireless communication systems face challenges in estimating network load and throughput, particularly in varying device densities, which affects performance and resource utilization, making it difficult for devices to select the best network for connection.
Innovation Solution
A method where wireless devices determine the number of active nodes in uplink and downlink communication, channel utilization, and estimate data rates to calculate throughput, using either access point signals or autonomous monitoring, allowing them to choose the network with the highest throughput before association.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wireless devices connect to networks with higher device density, then network coverage and connectivity are improved, but throughput and performance deteriorate due to limited network resources
Solution Approach 1:
The patent applies preliminary action by enabling wireless devices to estimate network load and available throughput before actually associating with a network. Devices perform measurements of beacon intervals, channel utilization, and active node counts during the scanning phase, calculate expected throughput using these metrics, and select networks based on these pre-calculated estimates. This allows devices to avoid connecting to overloaded networks in the first place, ensuring both connectivity reliability and acceptable throughput performance.
2Measurement precision
If wireless devices autonomously monitor the wireless medium to estimate network load, then measurement accuracy is improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent applies universality by designing the autonomous monitoring mechanism to serve multiple functions simultaneously. The same monitoring infrastructure that collects data for throughput estimation is also used for basic channel assessment and network discovery. By making the monitoring system multi-functional, the patent reduces overall device complexity compared to having separate specialized systems for each function, while still maintaining measurement precision through continuous observation of beacon intervals and channel conditions.
3Measurement precision
If wireless devices use detailed network load information for throughput estimation, then throughput prediction accuracy is improved, but information processing requirements increase
Solution Approach 1:
The patent applies the extraction principle by identifying and utilizing only the most critical parameters for throughput estimation: beacon interval, channel utilization percentage, and count of active nodes. Rather than processing all available network information, the device extracts these specific key metrics that have the highest impact on throughput prediction. This selective extraction approach maintains estimation accuracy while significantly reducing the computational burden and energy consumption associated with processing comprehensive network data.
Data Source
AI summary
This disclosure relates to determining load and estimating throughput of wireless networks by a wireless device. According to some embodiments, the numbers of active downlink and uplink nodes in a wireless network may be determined. Channel utilization of the wireless network may also be determined. An uplink data rate and a downlink data rate of the wireless device in the wireless network may be estimated. Based on the numbers of active downlink and uplink nodes, channel utilization, and the uplink data rate and a downlink data rate of the wireless device, the maximum possible uplink throughput and downlink throughput of the wireless device in the wireless network may be estimated. Such throughput estimates may be used to select a wireless network to join from among multiple available wireless networks.