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In this paper we propose a tree-search algorithm that provides the exact ML solution with lower computational complexity than that required by an exhaustive minimum distance search. The new algorithm, that we call King Decoder, is based on conditional dominance conditions, a set of sufficient conditions for making optimal decisions regardless of multi-antenna interference. The King Decoder does not require any matrix inversion and/or factorization and can be employed in both underdertermined and overdetermined systems. Complexity performances of the proposed algorithm, obtained through numerical simulations, are compared with those of the generalized sphere decoder, showing a lower search complexity for a wide range of SNR's.