Multiple input multiple output (MIMO) technology has attracted a lot of attentions for many years . This technology is being used in different wireless standards due to its capability of improvement in capacity and reliability of wireless systems . The gains in multi-user MIMO systems are more impressive since they propose the possibility of transmitting simultaneously to several users . There exist some drawbacks in using multiple antennas such as increasing complexity of the hardware and complexity and energy consumption of the signal processing at both ends . In order to achieve more gain and simplify the signal processing , massive MIMO systems have been proposed . When the number of antennas are increased , due to the asymptotics of random matrix theory , things that were random before , now start to look deterministic . Also , when dimensions are large , some of matrix operations such as inversion can be done fast . Asymptotic arguments based on random matrix theory show that the effects of uncorrelated noise and small-scale fading are eliminated , the number of users per cell are independent of the size of the cell , and the required transmitted energy per bit vanishes as the number of antennas in a MIMO cell grows to infinity . Performance of massive MIMO systems depend on channel information . Base Stations (BS) usually obtain the channel state information (CSI) corresponding to all users based on uplink pilot transmis sion . Channel estimation is done at the BS by letting all users send orthogonal pilots . However due to the limited channel coherence time , the pilot sequences employed by users in neighboring cells may not be orthogonal anymore which leads to pilot contamination . In a time-division duplex (TDD) setting and assuming the channel reciprocity , this effect is studied and different methods has been proposed . Interference alignment (IA) is a technique that allows many interfering terminals to communicate simultaneously over a finite number of signaling dimensions by aligning the interference at each receiver in a suace with a small number of dimensions , while keeping the desired signal separable from interference . The desired signal can be recovered by projecting the signal into the null space of the interference . IA was initially introduced as a coding scheme for the two-user MIMO X-channel . It was shown that IA can achieve multiplexing gains strictly higher than that of the embedded MIMO interference channel , multiple-access channel , and broadcast channel taken separately . IA is based on linear precoding at the transmitters and zero-forcing at the receivers and requires channel state information . IA has attracted many attentions in cellular networks specially in two-tier macrocell-femtocell networks . This method which seems useful for interference reduction in cellular networks , seems to be a good candidate for designing precoders for pilot decontamination . In this thesis , a precoding method based on IA for is proposed to improve the performance of the two-tier cellular network . Trying to maximize the SLNR in the network , this method uses the basis of IA and design precoders in both transmitter and receiver sides . Considering the criterion for designing the precoders , with maximizing the SNR in the network , sum throughput of the network is expected to improve . Simulation results reveal that using the proposed method for designing the precoders in two-tier network , improves the sum throughput of the network as expected . Keywords Femtocell , Interference Alignment , Massive MIMO , Pilot Contamination , Two-Tier Network