Beamforming Weight Adjustment for Inter-Cell Interference Mitigation
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Solution Overview
Problem
Existing beamforming systems face challenges in mitigating inter-cell interference caused by azimuth changes in antennas at cell sites, leading to potential signal quality degradation due to increased weighting loss.
Innovation Solution
The system dynamically adjusts beamforming weights based on potential or measured inter-cell interference, either proactively analyzing interference before an azimuth change or reactively adjusting weights after the change, to balance signal quality and interference levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If beamforming weights are adjusted to reduce inter-cell interference, then interference levels decrease, but weighting loss increases causing signal quality degradation
Solution Approach 1:
The system dynamically changes beamforming weight parameters based on detected interference conditions. When inter-cell interference is detected, the system adjusts the beamforming weights to redirect signal energy away from interfering cells, thereby reducing interference while managing the associated weighting loss through adaptive parameter optimization
Solution Approach 2:
The system implements a feedback mechanism where interference levels are continuously monitored and measured. Based on this feedback, the beamforming weights are dynamically adjusted in subsequent transmission cycles, creating a closed-loop control system that balances interference reduction with signal quality maintenance
2Area of stationary object
If remote azimuth steering is used to change beam coverage, then coverage area is optimized, but inter-cell interference increases
Solution Approach 1:
The system applies different beamforming strategies to different spatial regions. By analyzing the azimuthal direction and identifying which neighboring cells are affected, the system selectively adjusts beamforming weights only in the directions where interference occurs, maintaining optimal coverage in non-interfering directions
Solution Approach 2:
The beam coverage area and direction are made dynamically adjustable through remote azimuth steering. The system can change the beam's azimuthal orientation in real-time based on traffic conditions and interference measurements, allowing flexible optimization of coverage while minimizing interference with neighboring cells
3Object-affected harmful factors
If beamforming weights are altered to mitigate interference, then weighting loss increases, but inter-cell interference decreases
Solution Approach 1:
The system applies partial beamforming weight adjustments rather than maximum adjustments. By applying just enough weight modification to reduce interference to acceptable levels, the system avoids excessive weighting loss while still achieving the goal of inter-cell interference mitigation
Solution Approach 2:
The system dynamically optimizes beamforming weight parameters to find the optimal balance point where interference is reduced to acceptable levels while minimizing weighting loss. This involves adjusting multiple parameters including weight magnitude, phase, and azimuthal direction to achieve optimal performance
Data Source
AI summary
Methods and systems are provided for dynamically adjusting beamforming weights based on an azimuthal change request. A proposed azimuth change of an antenna is received, such as at a base station, where the proposed azimuth change is from remote azimuth steering of the antenna. A potential inter-cell interference is determined based on the proposed azimuth change. Based on the potential inter-cell interference, it can be predicted whether the proposed azimuth change can be made. The response, as to whether or not the proposed azimuth change can be made or not, is communicated to the base station.