In this thesis, the newly-focused concept, interference alignment (IA), which controls inter-user interference in multi-user wireless communication environment, is dealt with. And its motivation and a variety of interference alignment schemes are briefly overviewed. Furthermore, its necessary and sufficient conditions for IA to apply are investigated as well as its principles. Concentrating on its theoretical aspects, we propose new interference alignment scheme, which is able to significantly reduce interference, improve system performance, and increase capacity, by aligning all interference into the smaller-dimensional subspace of the received signal space. Since our proposed interference alignment scheme maximizes the overlap between the signal spaces of any two interference signals at each receiver, the size of the interference-free space is able to be maximized for the desired signal. There are some problems in designing the precoder based on our proposed IA scheme in the light of the degree of freedom (DOF). For example, some optimization processes are additionally needed in order to improve the sum rate performance. The number of the DOF is equivalent to the multiplexing gain. We determine the basis vectors of precoding matrices for our proposed IA scheme, which are able to make the desired signal space and the interference signal space roughly orthogonal to each other. Then, we find the decoding matrices based on the block Zero-forcing (ZF) method, and the optimal precoding matrices obtained from the IA algorithm according to the decoding method.