An Adaptive K-nearest-neighbor Interference Alignment Algorithm in Cellular System

For the disadvantages that the high achievement complexity and the heavy overheads of the system when interference alignment was applied to the cellular system for co-channel interference cancellation, this paper, based on the clustered model, proposed an adaptive K-nearest-neighbor interference alignment algorithm and a solving method to get the precoding vector without uniting the transmitter and the receiver. This algorithm could adaptively choose the interference for interference alignment according to the threshold of the signal-to-interference ratio, which could made the interference prechosen and decrease the achievement complexity of interference alignment. Simulation results show that by choosing an appropriate threshold of signal-to-interference ratio, the proposed algorithm could obtain a quite good performance of interference cancellation while the achievement complexity and the overheads could greatly decreased, which improved the applicability of interference alignment algorithm.