Recently, interference alignment (IA) has emerged as a promising technique to effectively mitigate interference in wireless communication systems. It has also evolved as a powerful technique to achieve the optimal degrees of freedom of interference channel. IA can be constructed in many domains such as space, time, frequency and codes. Currently, most researches on developing IA assume that channel state information (CSI) is well-known at the transceiver. However, in practice, perfect CSI at the transceiver can¡¦t be obtained due to many factors such as channel estimation error, quantization error, and feedback error. Under our investigation, the performance of IA is very sensitive to imperfect CSI. Therefore, this thesis proposes a spatial domain IA scheme for the three-user multiple-input multiple-output (MIMO) downlink interference channels, and analyzes the effect of channel estimation errors by modeling the estimation error as independent complex Gaussian random variables. The approximated bit error rate (BER) for the system with MIMO Zero-Forcing equalizer using IA is derived.