Bias Optimization for List-Sequential Detection in MIMO Systems

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Executive Summary

Iterative reception involves the computation of high quality Log-Likelihood Ratios (LLR) to run efficiently, but the computation complexity of optimal A Posteriori Probabilities (APP) is exponential in the Multiple-Input Multiple-Output (MIMO) system dimensions. The LISt-Sequential (LISS) detector achieves near-optimal performance by searching for a list of best candidates inside a tree modelizing the system. As this decoder remains complex, the authors propose here to modify its cost metric by adding a positive bias term, which accelerates the decoding algorithm. A good optimization of the bias value results in an important drop-off of the complexity while preserving the performance of the classical LISS decoder.

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