Reconfigurable MEMS Antennas and Coupling Matrix Estimation

Abstract: One of the demands for future wireless communication systems is higher data rates. New applications demand higher data rates and higher data rates give the service providers the possibility to offer new services. To achieve higher data rates the concept of MIMO (Multiple-Input Multiple-Output) systems has emerged. The basic principle behind MIMO is to use multiple antennas in contrast to the currently deployed systems mostly based on single antenna systems. The handheld devices need to be small and at the same time ver- satile due to the mobility of the user. To improve the overall performance following the MIMO paradigm, several antenna elements may be introduced on each handheld device. Requiring one feed chain per antenna element, this would result in a considerable increase in space, cost, and complexity and makes the implementation of large MIMO systems a difficult task. One way to overcome the setbacks is the use of reconfigurable antennas. For a fixed number of antenna elements in an antenna array, the choice of reconfigurable elements will increase the number of possibilities. The reconfigurability is preferably achieved by integrating switches with the antenna to save space. RF-MEMS (Radio Frequency Microelectromechanical Systems) switches be- long to a relatively new concept with advantages such as having low loss, better bandwidth properties, and demanding low actuation voltage. In this thesis, two different topics are treated related to wireless com- munication. Part I presents four different reconfigurable MEMS integrated antennas for MIMO applications. A frequency reconfigurable meander slot antenna, a polarization reconfigurable PIFA, and a frequency reconfigurable PIFA are presented followed by a pattern reconfigurable monopole array. Sim- ulation and measurement results are presented along with brief discussions on the topic of antenna selection with reconfigurable antenna elements. In addi- tion, channel measurements are presented for the reconfigurable array with an analysis of the impact of the reconfigurable antenna on the wireless channel. Part II presents an estimator for the coupling matrix of an antenna ar- ray with two slightly different approaches. In adaptive antenna arrays, signal processing is used as a basis for decisions. An accurate estimate of the in- coming signal is therefore of importance. As part of that, the modelling of the antenna array is crucial. Otherwise, the estimated signal could be biased and the decision made based on that will deviate from the optimal choice. Assuming ideal behavior by the antenna array when estimating the incoming signal is typically something that leads to results that deviate from the op- timum and reduces the performance. One of the major contributors to the non-ideal behavior is the mutual coupling between the antenna elements of the array. The coupling matrix is introduced and represents the interaction between the different antenna elements of an antenna array, called mutual coupling. To model a non-isotropic behavior, another matrix is introduced representing the element factor. A possible shift relative to the phase center of the array may occur because of difficulties finding the true phase center, which is also modelled with a matrix. The problem discussed in Part II of this thesis is that of finding the coupling matrix using the matrix based model. When the coupling matrix is found, a more accurate estimate of the signal is possible leading to improved performance. The introduction of the element factor and phase center representations improve the accuracy of the coupling matrix estimation, which is seen in the subsequent analysis of the estimator. CRB is derived and discussed in terms of parameter cost.