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Sphere decoding (SD) has been proposed as an efficient way to perform maximum-likelihood (ML) decoding of Polar codes. Its latency requirements, however, are determined by its ability to promptly exclude from the ML search (i.e., prune) large parts of the corresponding SD tree, without compromising the ML optimality. Traditional depth-first approaches initially find a "promising" candidate solution and then prune parts of the tree that cannot result to a "better" solution. Still, if thisdoi:10.1109/tvt.2017.2761262 fatcat:5o3y2q4tavampcpt7n3rmh65fq