Long-Term Precoding for Uplink MIMO Scheduling
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Solution Overview
Problem
Current uplink transmission schemes in SU-MIMO LTE-Advanced systems face challenges with limited channel state information and low feedback rates, leading to inefficiencies and increased complexity, particularly in handling power imbalances and antenna unbalances due to user equipment mobility and orientation changes.
Innovation Solution
The implementation of long-term precoding methods that average fast fading and track slow changes in spatial radio channel characteristics, allowing for periodic updates of the Transmitted Precoding Matrix Indicator (TPMI) and reducing the need for continuous feedback, using existing codebook designs for closed-loop SU-MIMO systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous feedback and short-term precoding are used to track channel variations, then transmission reliability is improved, but device complexity and feedback overhead increase
Solution Approach 1:
The patent segments the channel tracking into two distinct components: long-term channel characteristics (spatial distribution, antenna correlations) and short-term fading variations. By separating these time scales, the system applies different precoding strategies to each component, reducing the overall complexity while maintaining reliability.
Solution Approach 2:
The patent performs preliminary action by establishing long-term precoding matrices based on historical channel statistics and spatial characteristics before actual data transmission. These pre-computed matrices are stored and reused across multiple transmissions, eliminating the need for continuous real-time computation and reducing feedback requirements.
2Measurement precision
If continuous channel state information feedback is implemented, then precoding accuracy is improved, but loss of information and feedback overhead increase
Solution Approach 1:
The patent extracts only the essential long-term channel characteristics (spatial distribution patterns, antenna correlation structures) from the complete channel state information. By separating these static spatial parameters from dynamic fading components, the system feeds back only the necessary spatial information while deriving short-term precoding locally, significantly reducing feedback overhead.
Solution Approach 2:
The system performs preliminary extraction and quantization of long-term channel characteristics in advance, storing them for reuse. This pre-processing eliminates the need for continuous feedback of complete channel state information, as the same spatial characteristics apply across multiple transmission intervals.
3Productivity
If short-term precoding is used to adapt to fast fading, then transmission efficiency is improved, but device complexity increases due to continuous updates
Solution Approach 1:
The patent applies dynamics by using different time scales for different precoding components: long-term spatial characteristics remain static or slowly varying, while short-term fading adaptation occurs dynamically at the transmitter using locally available pilot signals. This dynamic approach maintains transmission efficiency without requiring continuous feedback updates.
Solution Approach 2:
The transmitter performs self-service by locally estimating short-term channel conditions using uplink pilot signals and autonomously adjusting the precoding matrices for downlink transmissions. This self-adaptation mechanism eliminates the need for continuous feedback channels while maintaining responsiveness to fast fading variations.
4Reliability
If antenna imbalances and mobility effects are compensated in real-time, then transmission reliability is improved, but device complexity and processing load increase
Solution Approach 1:
The patent segments the channel compensation into long-term spatial characteristics (antenna correlations, spatial distribution) and short-term mobility effects (Doppler shifts, fast fading). By treating these separately with different update rates and processing requirements, the system maintains coverage reliability without overwhelming processing complexity.
Solution Approach 2:
The system performs preliminary characterization of long-term spatial channel properties and antenna correlations in advance, establishing baseline precoding matrices that account for antenna imbalances. These pre-computed matrices remain valid across multiple transmission intervals, reducing the need for continuous real-time compensation processing.
Data Source
AI summary
In a telecommunication system, a method of controlling and implementing uplink transmission schemes specifically for user equipment having multiple input/multiple output (MIMO) capability, comprising: initializing said scheme at a network element; forwarding a message from said network element to said terminal indicating said scheme; transmitting uplink signals according to said scheme. It may comprises selecting a pre-coding arrangement such as a Transmitted Precoding Matrix Indicator or other scheduling grant information.