MIMO Receiver Distance Combining for HARQ Decoding
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Solution Overview
Problem
In multiple-input multiple-output (MIMO) data transmission systems, existing methods struggle to effectively decode received signal vectors due to noise and channel effects, often relying on limited error correction techniques that do not fully utilize information from multiple transmissions.
Innovation Solution
The system employs a method where the receiver combines multiple signal vectors using a decoding metric, calculating distances to determine the likelihood of each possible transmit signal vector, and stores combined distances for incremental updates, allowing for nearly optimal log-likelihood ratio computation and reduced computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional error correction techniques are used, then implementation is straightforward, but decoding performance is insufficient due to not utilizing information from multiple transmissions
Solution Approach 1:
The patent combines multiple received signal vectors into a single combined signal vector by calculating distance metrics for each vector and summing them. This merging process allows the system to utilize information from multiple transmissions to improve decoding performance while maintaining a relatively simple implementation structure.
2Measurement precision
If maximum likelihood decoding is implemented, then decoding accuracy is optimized, but computational complexity increases significantly
Solution Approach 1:
The patent segments the complex maximum likelihood decoding process into manageable steps: calculating distance metrics for each received signal vector separately, then combining these distance metrics. This segmentation reduces the computational burden by breaking down the overall optimization problem into smaller, more tractable calculations.
Solution Approach 2:
Instead of implementing full maximum likelihood decoding which would require exhaustive search of all possible transmitted signals, the patent uses a partial approach by calculating and combining distance metrics from multiple received vectors. This provides near-optimal performance with significantly reduced computational complexity.
3Device complexity
If multiple signal vectors are processed individually, then processing is simpler, but information from multiple transmissions is not fully utilized
Solution Approach 1:
The patent merges multiple received signal vectors by summing their distance metrics to create a combined distance metric. This combining process ensures that information from all transmissions is fully utilized in the decoding process, improving reliability without requiring complex individual processing of each vector.
Data Source
AI summary
Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. For each received signal vector, the receiver evaluates a decoding metric using each possible value of the transmitted signal vector to produce a set of distances. The receiver then combines distances from across the received signal vectors to produce a combined distance associated with each possible value of the transmitted signal vector. Using the combined distances, the receiver may choose among the possible values of the transmit signal vector to determine the actual transmit signal vector.