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In this paper, we present a near ML-achieving sphere search technique that reduces the number of search operations significantly over existing sphere decoding (SD) algorithms. While the SD algorithm relies only on causal symbols in evaluating path metric, proposed method accounts for the contribution of non-causal symbols with the aid of per-path minimum mean square error (MMSE) symbol estimation...
In this paper, we present a near ML-achieving sphere decoding algorithm that reduces the number of search operations in the sphere-constrained search. Specifically, by adding a probabilistic noise constraint on top of the sphere constraint, a more stringent necessary condition is provided, particularly at an early stage, and, hence, branches unlikely to be survived are removed in the early stage of...
In this paper, we propose a radius-adaptive sphere decoding algorithm that reduces the number of operations in sphere- constrained search while achieving performance close to ML decoding. Specifically, by adding a probabilistic noise constraint on top of sphere constraint, a more stringent necessary condition is provided, particularly at an early stage, and hence many branches that are unlikely to...
In P2P systems, the speed of searching for desired lists of sharable files is one of the most important measurement issues in evaluation of overall system performance. Although the searching schemes of existing non-structured P2P systems have been improved to enhance speed considerably, they still never reach to the level of those of the centralized and structured systems. In this paper, we propose...
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