AI Receiver Switching for Variable Wireless Channel Conditions
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Solution Overview
Problem
Existing wireless communication systems lack efficient methods for switching between general receivers and artificial intelligence receivers based on pre-determined criteria, necessitating improved switching determination models for optimal receiver selection in varying wireless environments.
Innovation Solution
A method and device for user equipment (UE) that dynamically select between a general receiver and an AI receiver based on wireless communication environment information, utilizing SNR, frequency variation, and delay spread, and adjust AI-related model information for optimal switching through measurement and relearning processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a general receiver is used for signal reception, then device complexity is reduced and ease of operation is improved, but reception performance deteriorates in complex wireless environments
Solution Approach 1:
The patent implements dynamic switching between general receiver and AI receiver based on wireless environment conditions. The receiver type is not fixed but changes according to channel characteristics, allowing the system to use simple receivers in good conditions and complex AI receivers in poor conditions, thus resolving the contradiction between performance and complexity.
Solution Approach 2:
The system changes the operational parameters of the receiver by switching between different receiver modes (general vs. AI receiver) based on measured wireless environment parameters such as SNR, delay spread, and frequency variation. This parameter-based adaptation allows optimal reception performance while managing complexity.
2Reliability
If an AI receiver is used for signal reception, then reception performance is improved in complex wireless environments, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The system dynamically selects between general and AI receivers based on real-time wireless environment assessment. The AI receiver is only activated when necessary (in complex environments), maintaining operational simplicity in normal conditions while providing enhanced performance when needed.
Solution Approach 2:
The patent introduces an intermediary switching mechanism that manages the transition between general and AI receivers. This intermediary layer handles the complexity of AI receiver operation transparently, allowing the system to use advanced AI processing only when required while maintaining simple operation for the user.
3Reliability
If switching between general receiver and AI receiver is implemented, then reception performance is optimized for varying wireless environments, but device complexity increases due to switching determination requirements
Solution Approach 1:
The patent segments the receiver functionality into distinct modules: a general receiver, an AI receiver, and a switching determination unit. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by clearly separating concerns between reception and switching functions.
Solution Approach 2:
The system performs preliminary assessment of wireless environment parameters (SNR, delay spread, frequency variation) before deciding whether to switch receivers. This preliminary action allows the switching determination to be based on pre-measured parameters, reducing the complexity of real-time decision-making.
4Reliability
If AI technology is applied to the physical layer receiver, then reception performance approaches maximum likelihood detector with low complexity, but requires machine learning and deep learning infrastructure
Solution Approach 1:
The patent separates the AI processing functionality into a distinct AI receiver module that can be independently managed. This segmentation allows the system to incorporate advanced AI capabilities without requiring the entire receiver chain to be complex, as the AI processing is confined to specific functional blocks.
Solution Approach 2:
The system designs the AI receiver to handle multiple reception scenarios and functions, making it a universal solution that can replace various specialized receivers. This multi-functionality justifies the investment in AI infrastructure by providing broad applicability across different wireless conditions and receiver types.
Data Source
AI summary
An intelligent computing device according to an embodiment of the present specification may receive a request for terminal information related to a terminal from a base station, transmit the terminal information to the base station, receive a resource for data transmission or reception, which is allocated by the base station, and transmit or receive data to or from the base station by using the allocated resource, wherein the data is transmitted or received by using a receiver selected from among a normal receiver of the terminal and an artificial intelligence receiver of the terminal on the basis of wireless communication environment information of the terminal, so that the conventional normal receiver and the artificial intelligence receiver provided at the terminal can be efficiently used in a wireless communication environment. One or more of a base station, a terminal, an intelligent computing device, and a server of the present specification may be associated with an artificial intelligence module, a drone (unmanned aerial vehicle; UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to a 5G service, etc.