Managing the interference is the main challenge in cellular networks. Multiple-Input Multiple-Output (MIMO) schemes have emerged as a means of achieving high-capacity in wireless communications. The most efficient MIMO techniques are based on managing the interference instead of avoiding it by employing orthogonal resource allocation schemes. These transmission schemes require the knowledge of the Channel State Information at the Transmitter (CSIT) to achieve the optimal Degrees of Freedom (DoF), also known as multiplexing gain. Providing an accurate CSIT in cellular environments involves high-capacity backhaul links and accurate synchronization, which imply the use of a large amount of network resources. Recently, a Blind Interference Alignment (BIA) scheme was devised as a means of achieving a growth in DoF regarding the amount of users served without the need for CSIT in the Multiple-Input Single-Output (MISO) Broadcast Channel (BC). It is demonstrated that BIA achieves the optimal DoF in the BC without CSIT. However, the implementation of BIA in cellular networks is not straightforward. This dissertation investigates the DoF and the corresponding sum-rate of cellular networks in absence of CSIT and their achievability by using BIA schemes. First, this dissertation derives the DoF-region of homogenous cellular networks with partial connectivity. Assuming that all the Base Stations (BSs) cooperate in order to transmit to all users in the network, we proposed an extension of the BIA scheme for the MISO BC where the set of BSs transmits as in a network MIMO. It is shown that the cooperation between BSs results futile because of the lack of full connectivity in cellular networks. After that, this dissertation presents several transmission schemes based on the network topology. By differentiating between users that can treat this interference optimally as noise and those who need to manage the interference from neighbouring BSs, a network BIA scheme is devised to achieve the optimal DoF in homogeneous cellular networks. Second, the use of BIA schemes is analyzed for heterogeneous cellular networks. It is demonstrated that the previous BIA schemes based on the network topology result nonoptimal in DoF because of the particular features of the heterogenous cellular networks. More specifically, assuming a macro-femto network, cooperation between both tiers leads to a penalty for macro users while femto users do not exploit the particular topology of this kind of network. In this dissertation, the optimal linear DoF (lDoF) in a two-tier network are derived subject to optimality in DoF for the upper tier. It is demonstrated that, without CSIT or any cooperation between tiers, the lower tier can achieve nonzero DoF while the upper tier attains the optimal DoF by transmitting independently of the lower tier deployment. After that, a cognitive BIA scheme that achieves this outer bound is devised for macro-femto cellular networks. The third part of this dissertation is focused on the implementation of BIA in practical scenarios. It is shown that transmission at limited SNR and coherence time are the main hurdles to overcome for practical implementations of BIA. With aim of managing both constraints, the use of BIA together with orthogonal approaches is proposed in this work. An improvement on the inherent noise increase of BIA and the required coherence time is achieved at expenses of losing DoF. Therefore, there exists a trade-off between multiplexing gain, sum-rate at finite SNR and coherence time in practical scenarios. The optimal resource allocation for orthogonal transmission is obtained after solving a very specific optimization problem. To complete the characterization of the performance of BIA in realistic scenarios a experimental evaluation based on a hardware implementation is presented at the end of this work. It is shown that BIA outperforms the sum-rate of schemes based on CSIT such as LZFB because of the hardware impairments and the costs of providing CSIT in a realist implementation.
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