BLE Pattern Detection for WLAN Channel Avoidance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless local area networks (WLANs) often experience interference between WLAN transmissions and Bluetooth Low Energy (BLE) signals, particularly since both may use the same frequency range, leading to potential disruptions in communication.
Innovation Solution
A system and method that utilize known BLE signal patterns to determine when and which channels are occupied by BLE signals, allowing WLAN transmissions to be adjusted and scheduled to avoid interference by selecting channels not in use by BLE signals, thereby ensuring simultaneous operation without interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If WLAN and BLE operate simultaneously in the same frequency range, then wireless communication coverage is extended, but interference between transmissions increases
Solution Approach 1:
The system performs preliminary detection of BLE signal patterns and predicts future channel occupancy before WLAN transmissions occur. By identifying upcoming BLE activity in advance, the WLAN scheduler can proactively select alternative channels or adjust transmission timing, preventing interference before it happens rather than reacting after interference occurs.
Solution Approach 2:
The WLAN transmission parameters are made dynamic rather than static. The system continuously monitors BLE signal patterns and adjusts WLAN channel selection, transmission power, and timing in real-time based on predicted BLE activity. This dynamic adaptation allows both systems to coexist by constantly optimizing WLAN operations around BLE signal patterns.
2Object-affected harmful factors
If WLAN channel selection is adjusted to avoid BLE signals, then interference is reduced, but channel utilization efficiency decreases
Solution Approach 1:
By predicting BLE signal patterns in advance, the system identifies future idle channels before they become occupied. This allows WLAN to proactively schedule transmissions on channels that will be free, maximizing channel utilization while avoiding interference. The preliminary prediction enables optimal channel selection rather than reactive avoidance.
Solution Approach 2:
The system changes multiple transmission parameters simultaneously including channel frequency, transmission timing, and power levels. By adjusting these parameters based on predicted BLE patterns, the system finds optimal operating points that maintain high channel utilization while avoiding interference periods, rather than simply avoiding channels entirely.
3Reliability
If BLE signal patterns are predicted to avoid interference, then transmission reliability improves, but system complexity increases
Solution Approach 1:
Instead of complex real-time analysis of actual BLE signals, the system creates a simplified predictive model or copy of expected BLE signal patterns. This model replicates the essential timing and channel occupancy characteristics of BLE signals, enabling interference avoidance through pattern matching rather than complex signal analysis, thus maintaining reliability while reducing complexity.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
An example computing device, comprising: a processing resource; and a memory resource storing machine readable instructions to cause the processing resource to: determine when known pattern indicates a pattern of a Bluetooth low energy (BLE) signal in relation to a channel to be occupied by the BLE signal; and adjust a channel for a wireless local area network (WLAN) transmission based on the determination.