An optimized interference alignment algorithm based on dynamic power allocation for MIMO system

TL;DR: A joint IA and power allocation algorithm that designed to find the interference mitigation solution and allocate power among different data streams of the users with less computational cost and has better engineering applicability is proposed.

Abstract: High density small cells with large number of simultaneously connected devices will be controlled by the macro cell in the future 5G wireless standards. In this context, interference management becomes critical in achieving high spectral efficiency. An approach called interference alignment (IA) technique has shown great promise in many theoretical studies. However, the performance improvement brought by IA in the MIMO interference network has not been investigated well when combined with power allocation. In this paper, we propose a joint IA and power allocation algorithm that designed to find the interference mitigation solution and allocate power among different data streams of the users with less computational cost. The proposed algorithm combines the maximum of total system signal interference noise ratio (Max-SINR) criterion and the maximum chord distance of channel matrix criterion not only maximize the distances between the interference subspace and the signal spanned, but also further reduce the interference between users by power allocation. Further, the algorithm in this paper which does not use iterative to get the precoding matrix or the mitigation matrix minimizes the complexity of the whole system and has better engineering applicability. Finally, simulation results show that the proposed method outperforms other known interference alignment algorithms in terms of throughput and the energy efficiency, which also accord with the green communications.