Efficient near-ml decoding via statistical pruning

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.