Adaptive selection mechanism based on distributed interference alignment

Abstract:

Interference Alignment(IA) technology shows a great potential to improve the capacity of future wireless network immensely, and it becomes a research focus in interference elimination field. Nevertheless, among the existing distributed algorithms like Minimum Interference Leakage(MIL), maximum-SINR (max-SINR) and Minimum Mean Square Error(MMSE), there is no such an optimal solution that could outperform the others throughout the SNR values. Based on a diversity analysis on existing standards, an adaptive selection mechanism is proposed, helping both transmission parties choose the optimal algorithm according to the communication condition. The simulation results show that compared with mono-algorithm, the newly proposed selection scheme can achieve as much as 5 dB SNR gain when the same data rate is obtained.