In this thesis, we investigate the linear transceiver design methods for multipleinput
multiple-output (MIMO) interference channel and its extensions. The first part
is concerned with transmit and receive filter optimization for the K-user MIMO interference
channel. Specifically, linear transmit and receive filter sets are designed
which maximize the weighted sum rate while allowing each transmitter to utilize only
the local channel state information. Our approach is based on extending the existing
method of minimizing the weighted mean squared error (MSE) for the MIMO broadcast
channel to the K-user interference channel at hand. For the case of the individual
transmitter power constraint, however, a straightforward generalization of the existing
method does not reveal a viable solution. It is in fact shown that there exists no closedform
solution for the transmit filter but simple one-dimensional parameter search yields
the desired solution. Compared to the direct filter optimization using gradient-based
search, our solution requires considerably less computational complexity and a smaller
amount of feedback resources while achieving essentially the same level of weighted
sum rate. A modified filter design is also presented which provides desired robustness
in the presence of channel uncertainty.
In the second part, we propose transceiver design strategies for the two-cell MIMO
interfering broadcast channel where inter-cell interference (ICI) exists in addition to
inter-user interference (IUI). We first formulate the generalized zero-forcing interference
alignment (ZF-IA) method based on the alignment of IUI and ICI in multidimensional
subspace, establishing the condition for the existence of the ZF-IA solution
capable of handling multiple-stream transmission in each link. We then devise a
minimum weighted-mean-square-error (WMSE) method based on ”regularizing” the
precoders and decoders of the generalized ZF-IA scheme. In contrast to the existing
weighted-su...