WLAN Receiving Antenna Selection via RSSI and CRC Testing
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Solution Overview
Problem
Conventional beamforming techniques in WLANs, such as those specified in the 802.11n protocol, require support from client stations and rely on selecting a specific antenna from an antenna array, which may not always optimize signal reception quality due to interference and varying environmental conditions.
Innovation Solution
A method and apparatus for selecting an optimal receiving antenna from an antenna array in a WLAN by testing each antenna for parameters like Error Vector Magnitude (EVM), Cyclic Redundancy Check (CRC) errors, transmission quality, and Received Signal Strength Indication (RSSI), and performing intersecting computations to determine the best antenna for improved reception quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a specific antenna is selected from an antenna array using conventional beamforming techniques, then the signal transmission can be directed to a target user, but the signal reception quality may not be optimized due to interference and varying environmental conditions
Solution Approach 1:
The patent implements dynamic antenna selection by continuously monitoring signal quality parameters (RSSI, SINR, CRC error rate) and adapting the receiving antenna choice based on real-time channel conditions. The system transitions from static conventional beamforming to dynamic adaptation, allowing the receiving end to switch between antennas according to varying environmental conditions and interference levels.
Solution Approach 2:
The system employs feedback mechanisms where the receiving station reports signal quality metrics (RSSI, SINR, CRC error rate) back to the transmitting access point. Based on this feedback, the access point dynamically adjusts antenna selection and beamforming parameters to optimize reception quality, creating a closed-loop control system that adapts to changing conditions.
2Measurement precision
If conventional beamforming is used to concentrate energy to a target user, then the demodulating signal-to-noise ratio increases, but the technique requires support from client stations and complex software algorithms
Solution Approach 1:
The patent inverts the conventional beamforming approach by implementing antenna selection and signal processing primarily at the receiving end rather than requiring complex client station support. The receiving station independently selects optimal antennas based on local signal quality measurements, reducing the computational burden and algorithmic complexity at both transmitting and receiving ends while maintaining improved signal-to-noise ratio performance.
3Reliability
If multiple antenna quality parameters are tested and intersecting computations are performed, then the optimal receiving antenna can be determined, but the testing and computation process becomes more complex
Solution Approach 1:
The system implements a tiered antenna selection approach where it first evaluates a subset of key parameters (primarily RSSI and SINR) to identify candidate antennas, then performs more comprehensive testing including CRC error rates only for the narrowed-down candidates. This partial action approach achieves high selection accuracy without the excessive computational burden of testing all parameters for all antennas simultaneously.
Data Source
Figure 1~2
AI summary
The disclosure involves selecting a receiving antenna in a wireless local area network, comprises: testing each antenna in an antenna array to obtain an antenna quality parameter of each antenna corresponding to a client Station, and determining an optimal receiving antenna corresponding to said Station according to the antenna quality parameter of each antenna corresponding to the Station; setting the optimal receiving antenna corresponding to said Station as the receiving antenna upon receiving a notification transmission message transmitted by said Station.