Multi-Input Multi-Output (MIMO) is a key technology in broadband wireless communications. Conventional MIMO detection and channel estimation algorithms require a matrix inversion with cubic complexity, which is a major challenge for practical implementation. In this thesis, we have proposed several approximation methods to reduce the complexity to a quadratic level. The proposed methods are particularly useful for massive MIMO systems. In addition, an interpolation based method is proposed to reduce the number of matrix inversion required for data detection of massive MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems.
|Qualification||Doctor of Philosophy|
|Award date||11 Jan 2017|
|Publication status||Unpublished - 2016|