Studies On Modeling And Simulation Of Multiple-Input Multiple-Output Wireless Channel And Analysis Of Channel Properties With Mutual Coupling

Multiple-input multiple-output (MIMO) wireless systems, characterized by antenna arrays at both transmitter and receiver, have demonstrated the great potential for increased capacity. The performance of the MIMO wireless system is determined by the channel, essentially. In order to achieve a compact array, the impacts of mutual coupling should be considered. Therefore, it is of great value to analyze the impacts of mutual coupling on the properties of MIMO channel and study the techniques for MIMO channel modeling and simulation.Firstly, a physically intuitional stochastic MIMO channel model is presented according to the essence of the wireless propagation. This model has involved diversified effects of the channel on the transmitted signal, so that it can accurately characterize the properties of the wireless channel. The channel is modeled as a tapped-delay-line architecture and each tap is based on the linear superposition of plane waves, so it is computationally efficient. The parameters of the model are determined by the statistical properties of the channel and the generation of these parameters is independent of propagation scenario, therefore, it can be suitable to different environments.Then, the spatial, temporal and spatio-temporal correlation properties of MIMO channel are analyzed exhaustively, and close-form expressions of the correlation coefficients for typical power azimuth spectrum (PAS) are derived, based on the stochastic model. Results reveal that the spatial correlation properties of MIMO channel are dependent on the PAS, the antenna pattern and the geometric configuration of the array. When the PASs at the base station (BS) and the mobile station (MS) are independent, the spatial correlation matrix of the MIMO channel is the Kronecker product of the spatial correlation matrix at the BS and the MS. The temporal correlation properties of the MIMO channel are determined by the PAS at the MS, antenna pattern and the traveling speed of the MS. Based on the analysis of the physical essence, the temporal correlation properties are equivalent to the spatial correlation properties at the MS. The joint spatio-temporal correlation properties at the BS and the MS are quite different. When the PASs at the BS and the MS are independent, the spatial correlation at the BS is independent on the temporal correlation, but this is not true for the spatial correlation at the MS.The process for simulating the stochastic MIMO channel is detailed in this dissertation and the simulation results of MIMO wireless channels in different propagation environments are also given. It can be achieved that the simulated MIMO channel can accurately characterize the properties of the channel which are expected, as well as the methods for generating the proper parameters and the procedure of simulation are easy to be implemented in the Matlab software platform.A novel method for estimating the PAS of wireless channel is presented. Based on the power measurements using the directional antenna, the observations, the antenna pattern and the PAS can construct a Fredholm integral equation of the first kind. The Fredholm integral equation of the first kind can be discretized to form a circular convolution by conducting the uniformly azimuth-scanning measurements. Then, the estimations of the PAS can be achieved by processing a deconvolution. The ill-conditioned problems can be overcome by pre-processing the observed data using a lowpass filter. The minimum mean square error (MMSE) estimation of PAS can be achieved by selecting the proper parameters of the lowpass filter according to the MMSE criterion. The directivity of the antenna influences the performance of the estimation essentially and the stronger directivity will lead to a more accurate result. Simulation results show that this method is effective.The impacts of the mutual coupling on the performances of the MIMO wireless channel are also analyzed. The spatial correlation properties of the MIMO channel with mutual coupling are analyzed by using the impedance matrix of the array and generic expressions of the spatial correlation matrices are derived. The effects of mutual coupling on the power transmission of array antenna are analyzed by using the network scattering parameter (S-parameter) representations of array and generator. The capacity of MIMO channel is calculated based on the spatial correlation and the power transmission when the mutual coupling is considered. Results of the analysis and the calculations show that the impacts of the mutual coupling in the transmit array and the receive array are quite different in every aspects of the performance of MIMO channel. Due to the present of the mutual coupling, the positions of the antenna elements in the array and the impedance match impact the performance of the channel. In conclusion, the mutual coupling makes negative impacts on the performances of MIMO channel.