MIMO Antenna Diversity Mode Selection
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Solution Overview
Problem
In high-order MIMO systems, selecting the optimal antenna for improving wireless link quality between a base station and user equipment is not straightforward, leading to suboptimal network performance due to overlooked UE antenna behavior and increased correlation in radio channels.
Innovation Solution
The system determines the operational mode by evaluating the number and power levels of multipath components for each antenna, considering eigenvalues and angles of arrival, and dynamically selects between antennas based on channel richness and load conditions to optimize antenna diversity and channel efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the order of MIMO system increases to use more antennas, then the potential for improving wireless link quality increases, but it becomes more difficult to select the optimal antenna configuration
Solution Approach 1:
The patent replaces manual or simple antenna selection mechanisms with an automated system that uses signal processing and mathematical analysis (eigenvalue computation) to determine optimal antenna configurations. The base station automatically evaluates channel conditions and computes eigenvalues to select the best antenna subset, substituting complex manual optimization with computational algorithms.
Solution Approach 2:
The system dynamically changes operational parameters (antenna selection, mode selection) based on computed eigenvalues and channel conditions. By monitoring eigenvalue ratios and comparing them against thresholds, the system adapts antenna configurations in real-time to maintain optimal wireless link quality as channel conditions vary.
2Productivity
If conventional antenna selection methods are used in high-order MIMO, then implementation is simpler, but network performance deteriorates due to suboptimal antenna selection
Solution Approach 1:
The system implements feedback by having the UE report channel state information and eigenvalue measurements back to the base station. The base station uses this feedback to continuously refine antenna selections and adjust operational modes, creating a closed-loop system that optimizes performance based on actual channel conditions rather than static configurations.
Solution Approach 2:
The system performs preliminary eigenvalue computations and channel assessments before finalizing antenna selections. By pre-evaluating channel conditions and computing eigenvalues in advance, the system prepares optimal antenna configurations ahead of actual data transmission, ensuring peak performance without real-time delays.
3Reliability
If UE antenna behavior is not considered in antenna selection, then the selection process is simpler, but wireless link quality deteriorates
Solution Approach 1:
The patent segments the antenna selection process into distinct evaluation stages: individual antenna channel assessment, eigenvalue computation for each antenna, ratio calculation, and threshold-based decision making. This segmentation allows the system to systematically evaluate UE antenna behavior for each antenna independently before making holistic selection decisions, ensuring comprehensive consideration of UE characteristics.
Data Source
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AI summary
Systems, methods and computer program products for determining an operational mode for a device in a network are disclosed. An exemplary method comprises determining a device (201) has a first antenna (210) and a second antenna (220); determining a first number of multipath components and associated power levels for the first antenna (210); determining a second number of multipath components and associated power levels for the second antenna (220); and determining an operational mode for the device (201) based on the first number of multipath components and its associated power levels for the first antenna (210) and the second number of multipath components and its associated power levels for the second antenna (220).