Low-complexity opportunistic interference alignment

Abstract

Interference is deemed to be the most critical issue in every wireless communication network; a high interference can cause major disruptions to the original signal, thereby degrading the quality of a particular transmitted signal. To counteract this issue, we introduce the concept of Interference Alignment (IA) which is aimed at reducing or eradicating all the unwanted interfering signals caused by other users in the vicinity of the desired signal. In our study, we managed to propose three main algorithms: Minimum Generated Interference (Min-GIN), Maximum Signal-to-Noise Ratio (Max-SNR) and Maximum Signal-to-Generated-Interference-plus-Noise Ratio (Max-SGINR). They basically set the selection criteria whereby only two best users from a particular cell will be chosen for the transmission such that the most ideal performance could be simulated. Our proposed algorithms has been proven to be successful in boosting sum-rates per cell thereby, increasing efficiency for the signal to be transmitted. Thus, the implementation of the concept of Opportunistic Interference Alignment (OIA) is proven to be rather promising especially in the real world where there is increasing demand for traffic load with the growing population.