Jhanak Parajuli

• Multi-user wireless communication is interference limited. Information theoretically, even the capacity region of a two-user Gaussian interference channel (IC) is an open problem. Recently a new cooperative interference management technique, called the interference alignment (IA), is proposed and proved to achieve the optimum degrees of freedom (DOF) in any interference networks. IA is a technique in which all the interfering signals observed from different transmitters are aligned onto the same direction or a common subspace while maintaining independence with the desired signal in a particular receiver. One of the main drawbacks of IA is the requirement of instantaneous channel state information at the transmitter (CSIT) and a robust generalized IA algorithm for any interference network still remains an open problem. In this thesis, we address these existing challenges and provide following three fold contributions: 1.Improvement of existing IA algorithms: Using cooperation among the receivers, it is shown that a proper precoding and zero-forcing matrix can be designed iteratively by minimizing the interference power and maximizing the desired signal power simultaneously. Simulation results show that such precoding matrices improve the system capacity. 2.Relaxation of the requirement of CSIT: A space-time transmission scheme is proposed that requires only the knowledge of delayed CSIT and is proved to achieve greater than one DOF in any multiple input single output interference broadcast channels (MISO-IBC). 3.Proposition of a new alignment technique: A new grouping based IA technique is proposed where the receivers within a group cooperatively align the interference from a common source onto an overlapping space. By doing so, they take benefit from the unused spatial dimensions. By determining the optimal overlapping between any two adjacent receivers, a chain based DOF analysis technique, called receiver chain alignment (RCA) is proposed.