Dynamic MIMO Antenna Configuration for Portable Systems
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Solution Overview
Problem
Portable information handling systems face challenges in optimizing antenna configurations due to changes in physical configuration and environment, which affect communication performance, leading to suboptimal antenna usage and potential interference.
Innovation Solution
Incorporating an antenna control module that detects changes in the physical configuration and environment, updating the MIMO antenna list and retraining antennas to ensure optimal communication by adjusting active and inactive states, and modifying the MIMO configuration to maintain reliable and efficient wireless communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system uses a fixed MIMO antenna configuration, then the antenna setup is simple and stable, but communication performance degrades when physical configuration or environment changes
Solution Approach 1:
The patent implements dynamic antenna configuration by continuously monitoring physical configuration changes (via sensors detecting chassis state, hinge angle, etc.) and environmental conditions, then automatically updating the MIMO antenna list and retraining antennas. This transforms the static antenna system into a dynamic one that adapts to changing conditions, resolving the contradiction between fixed configuration stability and adaptability to changes.
2Reliability
If the system continuously monitors and updates antenna configurations, then communication performance is optimized, but power consumption increases
Solution Approach 1:
The system employs periodic monitoring of physical configuration changes using sensors, rather than continuous active scanning. The antenna configuration is updated periodically when changes are detected, and retraining is performed at scheduled intervals or triggered by specific events. This periodic approach maintains communication performance while significantly reducing power consumption compared to continuous optimization.
Solution Approach 2:
The system uses feedback mechanisms where sensors detect physical configuration changes and environmental conditions, which then trigger conditional updates to the MIMO antenna list. This feedback-driven approach ensures antenna optimization only occurs when necessary, balancing communication performance with power consumption by avoiding unnecessary updates during stable conditions.
3Productivity
If more antennas are kept active in MIMO configuration, then communication throughput increases, but interference and power consumption increase
Solution Approach 1:
The system dynamically changes the parameter of active antenna count based on detected physical configuration and environmental conditions. By analyzing signal quality metrics, interference levels, and chassis state, the system optimizes the number of active antennas in the MIMO list, keeping more antennas active when conditions favor higher throughput and fewer antennas when interference or power constraints exist.
Data Source
AI summary
Systems and methods are disclosed for antenna optimization in an information handling system. A portable information handling system includes a chassis and a plurality of antennas coupled to the chassis. The plurality of antennas is capable of communicating in a multiple-input and multiple-output (MIMO) antenna configuration with a wireless-enabled device. The system includes an antenna control module communicatively coupled to the plurality of antennas. The antenna control module is configured to detect a change in at least one of a physical configuration of the chassis and an environment surrounding the portable information handling system, the change affecting a performance one or more of the plurality of antennas. The antenna control module is also configured to, based on the change, update a MIMO antenna list from the plurality of antennas. The MIMO antenna list represents active antennas for communicating with the wireless-enabled device.