Dynamic Decoding Order and Reconstruction Weights for MIMO SIC
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Solution Overview
Problem
In Multiple Input Multiple Output (MIMO) systems, determining the optimal decoding order and reconstruction weights for successive interference cancellation is challenging, affecting system performance and throughput due to varying channel conditions and interference.
Innovation Solution
A method and apparatus for dynamically determining the decoding order and calculating reconstruction weights based on signal-to-noise ratio (SNR) and channel conditions, using algorithms that select the optimal order to maximize successful decoding and throughput, involving re-encoding, re-modulation, and interference cancellation with calculated weight vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed decoding order and reconstruction weights are used in SIC, then system complexity is reduced, but decoding performance and throughput deteriorate under varying channel conditions
Solution Approach 1:
The patent implements dynamic selection of decoding order and reconstruction weights based on current channel conditions. The receiver determines channel quality indicators and uses them to adaptively select the optimal decoding order and weight values, transforming the static SIC process into a dynamic one that responds to varying channel states, thereby improving throughput without excessive complexity increase
Solution Approach 2:
The patent changes the parameters of the SIC process (decoding order sequence and reconstruction weight values) based on measured channel conditions. By adjusting these parameters dynamically according to channel quality indicators, the system optimizes decoding performance and throughput for different channel scenarios while maintaining manageable complexity through algorithmic selection
2Productivity
If dynamic decoding order and reconstruction weights are determined, then decoding performance and throughput are improved, but system complexity increases
Solution Approach 1:
The patent performs preliminary determination of channel quality indicators and pre-calculates optimal decoding orders and reconstruction weights based on these indicators. By preparing the decoding strategy in advance based on channel measurements, the system avoids complex real-time adjustments during decoding, thus improving throughput while controlling complexity through pre-computation
Solution Approach 2:
The SIC receiver autonomously determines its own optimal decoding order and reconstruction weights based on measured channel conditions without requiring external control. The system self-adjusts by calculating channel quality indicators and selecting appropriate decoding parameters, reducing the need for complex external coordination while improving adaptive performance
3Speed
If reconstruction weights are not calculated, then processing speed is increased, but interference cancellation accuracy deteriorates
Solution Approach 1:
The patent calculates reconstruction weights selectively based on channel conditions rather than always computing them. By determining when weight calculation is necessary based on interference levels and channel quality, the system achieves adequate cancellation accuracy only when needed, thus maintaining processing speed while improving accuracy in critical scenarios
Data Source
AI summary
Certain aspects provide a method for determining decoding order and reconstruction weights for decoded streams to be cancelled in a MIMO system with successive interference cancellation, based on estimates of the channel characteristics, the received composite signal and parameters of the system.