Predictive Channel Sounding for WLAN Beamforming Throughput Loss
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
As the number of beamformees communicating with a beamformer increases in wireless local area networks (WLAN), the number of received signals also increases, leading to a loss in data throughput due to channel aging, which existing systems struggle to recover.
Innovation Solution
A beamformer proactively triggers a channel sounding process based on an advance prediction of channel aging, using data collection, prediction schemes, and neural networks to determine the probability of channel aging, thereby optimizing beamforming and reducing data loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of beamformees communicating with a beamformer increases, then the communication coverage and connectivity are improved, but the data throughput decreases due to channel aging
Solution Approach 1:
The system performs channel sounding proactively before channel aging significantly degrades beamforming performance. The access point predicts channel aging probability and triggers channel sounding in advance to obtain fresh channel state information, preventing throughput degradation rather than reacting after degradation occurs.
Solution Approach 2:
The system implements a feedback mechanism where the access point receives channel state information from beamformees, predicts channel aging probability based on this feedback, and dynamically decides when to trigger channel sounding. This closed-loop feedback enables adaptive maintenance of beamforming accuracy.
2Productivity
If channel sounding is performed frequently to maintain beamforming accuracy, then data throughput is improved, but system overhead and complexity increase
Solution Approach 1:
The system changes the parameter of channel sounding trigger frequency dynamically based on predicted channel aging probability. Instead of fixed periodic sounding, the access point adjusts sounding occurrence based on environmental conditions, channel stability, and predicted aging rates, optimizing the balance between throughput and overhead.
Solution Approach 2:
The access point autonomously predicts channel aging probability and makes intelligent decisions about when to trigger channel sounding without requiring external control or manual configuration. The system self-manages the timing and frequency of channel sounding based on observed channel characteristics and predictions.
3Device complexity
If channel sounding is delayed until beamforming data loss occurs, then system simplicity is maintained, but data throughput and reliability decrease
Solution Approach 1:
The system proactively triggers channel sounding before beamforming data loss occurs by predicting channel aging probability. This preliminary action prevents reliability degradation rather than reacting after data loss, maintaining both simplicity and reliability through predictive rather than reactive operation.
Solution Approach 2:
The system uses lightweight prediction algorithms and selective channel sounding instead of continuous expensive channel estimation. By using simple prediction models to identify when full channel sounding is necessary, the system maintains reliability while minimizing overhead and complexity.
Data Source
AI summary
In a wireless local area network (WLAN) system including a first device and a second device, an operating method of the first device communicating with the second device via a channel includes collecting data related to a current state of the channel based on a signal received from the second device, predicting a probability of channel aging based on the data, and triggering a channel sounding process based on the prediction.