Frequency Scanning Order Optimization for Wireless Devices
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Solution Overview
Problem
Wireless communication devices face high power consumption and time inefficiency during frequency scanning due to the large number of frequency bands and channels they need to search through, especially in wideband communication systems like 4G LTE and 5G NR, which can lead to prolonged battery drain in battery-operated equipment.
Innovation Solution
Implementing an intelligent frequency scanning algorithm that determines an efficient order for scanning frequency channels based on the likelihood of a successful connection, prioritizing channels with stronger signal power and lower power consumption, using a processor to configure antennas and LNAs to minimize the number of scans required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a wireless communication device scans through all frequency bands and channels systematically, then it ensures comprehensive signal detection, but the power consumption and time required increase significantly
Solution Approach 1:
The device performs preliminary actions by scanning lower frequency bands first (which have better propagation characteristics and higher likelihood of successful connection) before scanning higher frequency bands. This preliminary scanning of more promising channels reduces the need to exhaustively scan all bands, thereby lowering power consumption while maintaining reliable signal detection.
Solution Approach 2:
The frequency scanning process is made dynamic by adjusting the scanning order based on frequency band characteristics and connection probability. Instead of a static sequential scan, the system dynamically prioritizes lower frequency bands (e.g., Band 3, Band 7) over higher frequency bands (e.g., Band 255, Band 47), adapting the scan strategy to maximize connection success while minimizing power consumption.
2Reliability
If a wireless communication device scans through all frequency bands and channels systematically, then it ensures comprehensive signal detection, but the time required increases significantly
Solution Approach 1:
The device performs preliminary actions by scanning lower frequency bands first (which have better propagation characteristics and higher likelihood of successful connection) before scanning higher frequency bands. This preliminary scanning of more promising channels reduces the time needed to find a suitable network while maintaining comprehensive detection capability.
Solution Approach 2:
The frequency scanning process is made dynamic by adjusting the scanning order based on frequency band characteristics and connection probability. Instead of a static sequential scan, the system dynamically prioritizes lower frequency bands (e.g., Band 3, Band 7) over higher frequency bands (e.g., Band 255, Band 47), adapting the scan strategy to maximize connection success while minimizing time consumption.
3Adaptability or versatility
If a wireless communication device supports multiple frequency bands for global roaming, then it increases network compatibility, but the complexity of frequency scanning increases
Solution Approach 1:
The device segments the frequency scanning process into distinct phases: first scanning lower frequency bands (e.g., Bands 3, 7, 13, 18, 28) that are more likely to provide successful connections, and only if needed, scanning higher frequency bands (e.g., Bands 255, 47). This segmentation reduces the complexity of managing multiple bands by establishing a clear scanning hierarchy.
Solution Approach 2:
The frequency scanning process is made dynamic by adjusting the scanning order based on frequency band characteristics and connection probability. Instead of a static sequential scan, the system dynamically prioritizes lower frequency bands (e.g., Band 3, Band 7) over higher frequency bands (e.g., Band 255, Band 47), adapting the scan strategy to maximize connection success while minimizing time consumption.
Data Source
AI summary
The disclosed technology provides a system for scanning frequency channels that reduces the number of frequency channels scanned from among all the possible frequency channels that a wireless communication device can operate on. The wireless communication device uses historical data on last successful connection together with device data metrics from the last successful connection to determine a probability of successful connection for each of the potential frequency channels. The wireless communication device then ranks the probability associated with each frequency channel to determine a frequency scanning order that results in fewer frequencies being scanned before an appropriate channel is identified.


