… pruning probability. On each node visited, we examine the probability that the rest of the tree
is decoded … If the probability of this event is too small and thus less than a threshold, then we …

… Thus, excessive pruning may need to … probabilistic tree pruning sphere decoding (PTP-SD),
which prunes more nodes by adding a probabilistic noise constraint on top of the sphere …

… original SD algorithm is explained as a special case for pruning probability ϵ = 0. That is, no
… ing the sphere decoding in the next section, we present radiusadaptive sphere decoding in …

… order as the maximum-likelihood decoder (MLD). However, it … In this paper, we combine
the probabilistic tree pruning (PTP… of sphere decoder (SD) such as branch pruning using an …

… sphere decoding algorithm that uses statistical pruning to reduce the exponentially large
search space to one that is much smaller yet contains the optimal solution with high probability. …

… abilistic tree pruning sphere decoding (PTP-SD) algorithm that provides further … to as
probabilistic tree pruning SD (PTP-SD). We have shown that an addition of the probabilistic noise …

… In this paper, we propose a modification to the sphere decoding algorithm that uses statistical
pruning to reduce the search for … With probability P, we make an emor by decoding to s # 1. …

… The sphere decoder (SD) as an efficient ML decoder has therefore … sphere decoder (SESD)
[1]. The method uses a set of bounds, which are computed using the conditional probability …

… Our algorithm is based on pruning (excluding) branches from the search tree arising in the
sphere decoding (SD) algorithm. The choice of the branches to be pruned relies on intuitive …

… well-known method — namely, probabilistic tree pruning SD. … pruning (LP) to the SD for
further reduction of decoding complexity. In the proposed algorithm, the bottom layers are pruned…