Joint Iterative Interference Alignment and SCMA Technique for MIMO-OFDM Systems

Interference alignment (IA) is a well-known transmission strategy for interference channels, with which the sum rate can linearly scale with the number of users at high signal-to-noise ratio (SNR). However, most existing works on IA considered only the maximization of the sum rate without taking into account the bit error rates (BER) performance. In this work, we firstly propose a novel IA algorithm to improve the BER performance for MIMO-OFDM interference channels on a per-subcarrier basis. The proposed IA algorithm is then combined with the sparse code multiple access (SCMA) technique to further enhance the BER performance by exploiting the inherent frequency diversity in the MIMO-OFDM systems. At the receiver, a linear filter is first used to mitigate the inter-user aligned interference and separate the spatial streams, and then an iterative frequency-domain message passing algorithm (MPA) is applied to efficiently separate the overlapped multiple codewords. Simulation results demonstrate that the proposed joint IA and SCMA strategy can provide significant BER gain compared to the existing IA algorithms.