Efficient near-ml decoding via statistical pruning
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Maximum-likelihood (ML) decoding often reduces to finding
the closest (skewed) lattice point in N-dimensions to
a given point x ϵ C^N. Sphere decoding is an
algorithm that does this. We modify the sphere decoder to
reduce the computational complexity of decoding while
maintaining near-ML performance.