A Thesis for the Degree of Master Efficient Detection Algorithms for MMSE-SIC in MIMO Systems

In this thesis, computationally efficient detection algorithms for the minimum mean square error (MMSE) estimation with successive interference cancellation (SIC), or with generalized decision feedback equalizer (GDFE) are considered in spatial multiplexing multiple-input multipleoutput (MIMO) systems. The MMSE-SIC and the MMSE-GDFE architectures are known to achieve the ergodic capacity of MIMO fading channels. This thesis presents a new understanding of SIC and GDFE to provide further insights. This perspective shows that 1) SIC and GDFE are a special case of the two-dimensional estimation with side information (or decision feedback), and 2) SIC can be expressed in terms of the Cholesky decomposition, as GDFE is. Inspired by the latter, we propose fast algorithms based on the Cholesky decomposition for SIC and GDFE in multiple antenna systems. Although existing detection algorithms can provide an impressive reduction of computational complexity for a large M , the reduction is relatively small for a moderate M of practical interest (i.e. M ≤ 16). The Cholesky decomposition is computationally more efficient than the