Near ML-achieving Lattice Search for Multiple Antenna Systems

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 sequential cost metrics, the proposed method accounts for the contribution of non-causal symbols with an aid of perpath minimum mean square error (MMSE) symbol estimation. From the simulations performed over multi-input multi-output (MIMO) wireless channels, it is shown that the computational complexity of the proposed algorithm is substantially smaller than the existing SD algorithms while providing negligible performance loss.