Beyond fixed neighborhood search in the likelihood ascent algorithm for MIMO systems


Neighborhood search algorithms have been proposed for detection in large/massive multiple-input multiple-output (MIMO) systems. They iteratively search for the best vector in a fixed neighborhood. However, the ML solution may not lie in the searched space or the search may take a large number of intermediate vectors to converge. Instead of searching in a… (More)
DOI: 10.1109/ICC.2016.7511055


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