The paper reports on investigations into the effect of spatial correlation on channel estimation and capacity of a multiple input multiple output (MIMO) wireless communication system. Least square (LS), scaled least square (SLS) and minimum mean square error (MMSE) methods are considered for estimating channel properties of a MIMO system using training sequences. The undertaken mathematical analysis reveals that the accuracy of the scaled least square (SLS) and minimum mean square error (MMSE) channel estimation methods are determined by the sum of eigenvalues of the channel correlation matrix. It is shown that for a fixed transmitted power to noise ratio (TPNR) assumed in the training mode, a higher spatial correlation has a positive effect on the performance of SLS and MMSE estimation methods. The effect of accuracy of the estimated Channel State Information (CSI) on MIMO system capacity is illustrated by computer simulations for an uplink case in which only the mobile station (MS) transmitter is surrounded by scattering objects
Abstract-This paper reports investigations into capacity of a multiuser Multiple-Input Multiple-Output (MIMO) system which uses a block diagonalization (BD) scheme with antenna selection at mobile stations (MSs). It is shown that the antenna selection at MSs improves capacity while at the same time it offers an effective solution to hardware size and cost. Also it is advantageous from the point of view of simplicity of signal processing at mobile stations. Two antenna selection schemes are investigated, one is the norm-based selection and the other is project-maximization selection. The simulations results show that the project-maximization selection is superior over the norm-based selection.
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