Abstract--In this paper, we propose a near-maximum likelihood (ML) detection method referred to as reduced dimension ML search (RD-MLS). The RD-MLS detector is based on a partition...
The interest in near-ML detection algorithms for Multiple-Input/lMultiple-Output (MIMO) systems have always been high due to their drastic performance gain over suboptimal algorith...
—When the maximum number of best candidates retained at each tree search level of the K-Best Sphere Detection (SD) is kept low for the sake of maintaining a low memory requiremen...
In this paper, we consider a low-complexity detection technique referred to as a reduced dimension maximum-likelihood search (RD-MLS). RD-MLS is based on a partitioned search which...
Jun Won Choi, Byonghyo Shim, Andrew C. Singer, Nam...
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...