Multi-Antenna Receiver Cross-Technology Interference Cancellation
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Solution Overview
Problem
802.11n networks experience complete loss of connectivity or significant throughput reduction due to high-power cross-technology interference from devices like baby monitors and cordless phones, which current technologies struggle to mitigate effectively, especially in scenarios with multiple interferers and changing interference patterns.
Innovation Solution
A method using a multi-antenna receiver to estimate the relationship between interfering signals, filter and combine signals to reduce interference, and update estimates based on decoded data, allowing for effective discrimination and decoding of desired signals even in the presence of unknown interfering signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If frequency-based isolation techniques are used to mitigate interference, then interference reduction is achieved, but device complexity increases and adaptability to changing interference patterns deteriorates
Solution Approach 1:
The system dynamically changes parameters including channel width, frequency selection, and transmission power based on detected interference characteristics. The receiver adapts by adjusting equalization filters and decoding parameters according to the estimated interfering signal properties, allowing flexible response without complex hardware modifications.
Solution Approach 2:
The interference mitigation system operates dynamically by continuously monitoring the wireless medium for interfering signals, estimating their characteristics in real-time, and adapting transmission and reception parameters accordingly. This dynamic approach replaces static frequency isolation with agile, condition-based parameter adjustment.
2Object-affected harmful factors
If directional antennas are used for spatial isolation, then interference reduction is achieved, but ease of operation deteriorates in indoor scenarios
Solution Approach 1:
The patent replaces mechanical directional antenna systems with signal processing-based interference mitigation. Instead of physically orienting antennas or using complex beamforming hardware, the system uses digital signal processing including equalization, filtering, and interference estimation to achieve spatial selectivity and interference rejection.
3Device complexity
If mitigation schemes assume transient interference are used, then device complexity is reduced, but reliability deteriorates when facing persistent high-power interferers
Solution Approach 1:
The system implements continuous feedback loops where the receiver estimates interfering signal characteristics, feeds this information back to adjust transmission parameters, and re-estimates to verify effectiveness. This closed-loop approach maintains reliability against persistent interferers by continuously adapting to their presence rather than assuming transient conditions.
4Object-affected harmful factors
If frequency-based isolation with OFDM subcarrier suppression is used, then interference reduction is achieved, but productivity deteriorates due to reduced bandwidth utilization
Solution Approach 1:
Instead of suppressing entire subcarriers or channels, the system applies localized interference mitigation only to the specific frequency regions and time intervals where interfering signals are detected. This allows uninterrupted transmission on clean frequencies and maintains high bandwidth utilization while providing targeted interference reduction.
Data Source
AI summary
In one aspect, a method for mitigating an effect of an interfering radio signal at a multiple antenna receiver includes forming an estimate of a relationship of the interfering signal among signals received from the multiple antennas. In general, the interfering signal does not share the same communication technology as a desired signal. The signals received from the multiple antennas filtered and combined according to the estimate of the relationship of the interfering channels to reduce an effect of the interfering signal. Desired data present in the desired signal represented in the filtered and combined signals is decoded and the estimate of the relationship of the interfering signals is updated according to the decoding of the desired signal.