AI-Assisted UE Switching in Adverse Wireless Conditions
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Solution Overview
Problem
User equipment (UE) performance is degraded in adverse environmental conditions, leading to issues such as latency and loss of connectivity in wireless communications networks, particularly in environments like high-speed movement or areas with reduced coverage.
Innovation Solution
An AI engine on the UE detects adverse conditions and switches between different technologies, such as UL MIMO and UL CA, to optimize performance by balancing throughput gain and spectrum efficiency, using a database to determine the most effective strategy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional communication technologies are used in adverse environmental conditions, then device simplicity is maintained, but UE performance degrades with latency and connectivity loss
Solution Approach 1:
The system dynamically changes communication parameters by switching between different uplink technologies (MIMO and CA) based on environmental conditions. The AI engine monitors conditions and adjusts the communication mode to optimize reliability without permanently increasing device complexity
Solution Approach 2:
The UE equips itself with an AI engine that autonomously detects adverse conditions and switches between communication technologies without external intervention. This self-service capability improves reliability while keeping the system architecture relatively simple
2Productivity
If AI-driven dynamic switching is implemented, then UE performance and connectivity are improved, but device complexity increases
Solution Approach 1:
The AI engine serves multiple functions: detecting adverse conditions, determining optimal communication technologies, and controlling switching between modes. This multi-functionality consolidates complexity into a single component rather than distributing it across multiple separate systems
Solution Approach 2:
The system implements dynamic switching between MIMO and CA technologies based on real-time environmental conditions. This dynamic adaptation improves communication efficiency while keeping the base architecture flexible rather than requiring multiple fixed systems
3Reliability
If single technology is used for uplink communication, then device complexity is reduced, but performance in adverse conditions deteriorates
Solution Approach 1:
The patent extracts the intelligence required for technology selection into a separate AI engine component. This allows the core communication system to remain relatively simple while adding the capability to switch between MIMO and CA only when needed, rather than permanently maintaining both systems
Solution Approach 2:
The system performs preliminary detection of adverse conditions and proactively switches to the appropriate communication technology before performance degradation occurs. This preliminary action maintains reliability without requiring complex real-time reaction mechanisms
Data Source
AI summary
Aspects of the subject disclosure may include, for example, detecting conditions of an operating environment of a user equipment device (UE); determining that the operating environment is an adverse environment; and providing a signal to an artificial intelligence (AI) engine on the UE regarding the adverse environment; the AI engine, responsive to the signal, obtains from a database on the UE a list of procedures for improving the performance of the UE and creates a strategy that specifies one or more of the listed procedures to be performed; one of the specified procedures comprises switching between a use of a first technology for improving the performance of the UE and a use of a second technology for improving the performance of the UE. Other embodiments are disclosed.