The impact of antenna and RF system characteristics on MIMO system capacity
The recent growth in demand for wireless services coupled with the limited spectrum available for these services has spawned new efforts to increase the spectral efficiency of wireless links. Recent research has shown that in multipath propagation environments, the spatial characteristics of the propagation channel can be exploited to increase spectral efficiency through the use of multiple antennas at the transmitting and receiving nodes. Such multiple-input multiple-output (MIMO) systems show promise for dramatic performance gains over their single-antenna counterparts. However, MIMO system performance is influenced by many different factors.
Antenna array configuration directly contributes to MIMO system performance. The ability to build and integrate adaptive antenna arrays into MIMO systems requires the development of strategies for determining which antenna array configuration best enhances performance. Since an exhaustive search of all configurations is computationally prohibitive, this dissertation develops information theoretic based, computationally tractable solutions for determining favorable array configurations.
The characteristics of the MIMO receiver front-end also play a large role in determining how well the system performs. Where portable MIMO devices will be forced to closely space antenna elements, mutual coupling can greatly impact both capacity and diversity performance. To study strategies for mitigating mutual coupling performance degradation, an accurate receiver front-end model is necessary. This work realistically models amplifier noise in the receiver and determines how matching networks may be used to improve system performance in the presence of antenna mutual coupling and amplifier coupling.
Since MIMO systems operate by identifying optimal antenna array weights for the channel of interest, it is surprising that array superdirectivity has yet to be observed in theoretical solutions to the problem. When formulating system capacity using a radiated power constraint, the capacity is shown to be overestimated due to superdirectivity. Since superdirectivity provides for elegant theoretical results and poor realistic performance, this work incorporates constraints into the formulation of system capacity to arrive at physically achievable capacity values.