MIMO communications with mutual coupling and channel correlation

Previous researches have shown that multiple-input multiple-output (MIMO) technology is one of the most promising approaches in emerging wireless communication systems. Compared with the traditional single-input single-output (SISO) technology, MIMO can significantly increase system capacity and link reliability without any extra requirement in bandwidth or overall transmit power. However in practice, the theoretical prediction is not achievable due to many reasons. In this thesis, we study MIMO communication systems with the effects of mutual coupling and channel correlation. Both effects are the unavoidable results of closely packed antennas. First, the performance degradation of MIMO systems due to channel correlation is studied through simulations. Different schemes exhibit distinct sensitivities towards channel correlation. Next, the mutual coupling effect is discussed in details. Based on previous research results, we develop a generalized framework of mutual coupling and analyze several aspects of the phenomenon. By using this framework, we study an interesting problem about the capacity of an antenna array with fixed length and variable number of antennas. This gives insights to practical system designs. After that, we formulate the STBC precoder design problem with both antenna mutual coupling and channel correlations. The precoder is confined to two practical power constraints simultaneously. Convex optimization is used to find the optimal solution. Furthermore, the method can be applied to solve other problems with mutually coupled transmit antennas under dual power constraints. Finally we turn to antenna selection, another technique to fight channel correlation. In particular, we analyze an antenna selection problem in a frequency-selective WLAN system with the aim of reducing the packer error rate (PER). The proposed algorithms are evaluated through simulations on the TGn channel models and outperform other algorithms in previous works