MIMO SIC Decoding Order Using Retransmission Channel History
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Solution Overview
Problem
Conventional successive interference cancellation (SIC) methods in multiple input multiple output (MIMO) systems with retransmissions fail to optimize codeword ordering effectively, leading to suboptimal performance due to reliance on current channel conditions alone, neglecting the impact of previous transmission attempts.
Innovation Solution
The system computes an ordering metric based on both the current and previous channel conditions associated with all transmission attempts of a codeword, determining a history-aware SIC ordering that prioritizes codewords with better decoding opportunities across multiple attempts, using metrics like Packet Error Rate (PER), Signal-to-Noise Ratio (SNR), and Signal-to-Interference and Noise Ratio (SINR).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional SIC methods use only current channel conditions for codeword ordering, then the ordering process is simple and fast, but decoding performance is suboptimal due to neglecting historical transmission information
Solution Approach 1:
The patent pre-computes and stores ordering metrics for multiple previous transmission attempts (e.g., T-1, T-2, T-3) before the current transmission. This preliminary action allows the receiver to quickly access historical channel condition data without performing complex real-time computations, thereby improving decoding performance while maintaining computational efficiency.
Solution Approach 2:
The patent extends the ordering metric computation from a single-dimensional current channel condition assessment to a multi-dimensional evaluation that incorporates historical channel conditions across multiple transmission attempts. By adding the time dimension (previous transmissions T-1, T-2, T-3) to the ordering decision process, the system achieves more accurate codeword ordering that reflects the complete transmission history.
2Measurement precision
If the system considers historical channel conditions for all transmission attempts, then decoding accuracy improves, but computational overhead and processing time increase
Solution Approach 1:
The receiver pre-calculates ordering metrics for previous transmission attempts and stores them in memory before the current transmission arrives. This preliminary computation eliminates the need for real-time historical data processing, allowing the system to achieve high measurement precision by considering multiple transmission attempts while avoiding additional processing time delays.
Solution Approach 2:
The patent implements a dynamic ordering metric computation that adaptively selects which previous transmission attempts to consider based on channel variability and transmission conditions. The system can adjust the number of historical attempts (T-1, T-2, T-3) to include in the ordering decision, balancing measurement precision requirements against processing time constraints in different operational scenarios.
Data Source
AI summary
Systems and methods are provided for determining a successive interference cancellation (SIC) decoding ordering in a multiple input multiple output transmission (MIMO) system with retransmissions. A plurality of codewords is transmitted in a current transmission time. Some of the codewords may have been previously transmitted in previous transmission attempts according to a retransmission protocol. The plurality of codewords is received and an ordering metric is computed for a received codeword based on channels associated with multiple transmission attempts of the codeword. A decoding ordering of the codewords is determined based on the computed ordering metric. Performance parameters such as Packet Error Rate (PER), channel gain, and/or equalizer-output Signal-to-Interference and Noise Ratio (SINR) may be used to evaluate a channel quality for each one of the transmission attempts of the codeword. The ordering metric may be updated recursively with each transmission attempt.