Blended Spectral Efficiency Mapping for Wireless Channel Adaptation
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Solution Overview
Problem
Current wireless communication systems face challenges in dynamically adapting spectral efficiency to channel quality indicators (CQI) in real-time, especially due to varying channel conditions, which affects downlink performance.
Innovation Solution
The system employs a method where user equipment (UE) calculates a weighted sum of predefined spectral efficiency - CQI mappings based on channel estimates, using weights determined by frequency selectivity or machine learning, to produce a blended mapping that adapts to current channel conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single predefined SPEF-CQI mapping table is used, then the system is simple to implement, but it cannot adapt to varying channel conditions resulting in suboptimal downlink performance
Solution Approach 1:
The mapping table is segmented into multiple predefined SPEF-CQI mapping tables, each associated with different channel types (e.g., line-of-sight, multi-path). The UE maintains these separate tables and selects or combines them based on current channel conditions, allowing adaptation without requiring a single complex universal table
Solution Approach 2:
The system transitions from a static single mapping table to a dynamic structure where the UE calculates a blended mapping table by taking a weighted sum of multiple predefined tables. The weights are determined based on channel estimates and frequency selectivity, enabling real-time adaptation to varying channel conditions
2Adaptability or versatility
If multiple predefined SPEF-CQI mapping tables are maintained for different channel types, then adaptability to channel conditions improves, but memory storage requirements and processing complexity increase
Solution Approach 1:
Instead of maintaining all possible mapping tables for every conceivable channel condition, the system uses a limited set of predefined tables covering major channel types. The UE then uses weighted combination to partially synthesize the needed mapping for current conditions, reducing memory storage requirements while maintaining adaptability
3Measurement precision
If real-time channel estimation and weighted sum calculation are performed, then spectral efficiency mapping accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
Multiple predefined SPEF-CQI mapping tables are prepared in advance for different channel types. These tables are stored in the UE memory before actual communication occurs. During operation, the UE only needs to perform channel estimation, determine weights based on frequency selectivity, and calculate a weighted sum, rather than building mapping tables from scratch in real-time
Solution Approach 2:
The channel estimate and frequency selectivity measurements act as intermediaries that bridge the predefined mapping tables and the final blended mapping. Instead of directly computing complex mappings, the system uses these intermediate measurements to determine appropriate weights, simplifying the overall calculation process
Data Source
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AI summary
Aspects of the disclosure relate to dynamically adapting the mapping between spectral efficiencies and channel quality indicators in real-time based on the channel conditions. In some examples, a scheduled entity (e.g., a UE) may maintain two or more predefined tables or other mappings, each including a respective mapping between spectral efficiency threshold values and channel quality indicators for a respective channel type. The UE may then calculate respective weighted sums of the spectral efficiency threshold values across the two or more predefined tables based on the current wireless channel. For example, the UE may estimate the wireless channel and determine respective weights to be applied to the spectral efficiency threshold values across the two or more predefined tables based on the channel estimate. Other aspects, features, and embodiments are also claimed and described.