Minimizing the interference leakage using a novel IA algorithm to provide perfect alignment solutions

The goal of this paper is to design a new interference alignment (IA) precoders and decoders algorithm capable of finding perfect alignment solutions which is similar to the AltMin-IA in terms of convergence speed and reliability. Finally, extended the AltMin-IA algorithm to incorporate the rank constraint in the form of a minimum eigenvalue condition, and a transmit power constraint, which results in a generalized eigenvalue problem at each step of the alternating optimization procedure. In the interference channel (IC), K transmitter-receiver pairs exploit the channel state information (CSI) to jointly design their transmit strategies. Specifically here, consider orthogonal frequency-division multiplexing (OFDM) transmissions, where the application of existing IA algorithms require an additional level of cooperation; time synchronization. To avoid such demand, apply the precoders and decoders at the sample level in the time domain, which allows the users to transmit asynchronously.