Study on Selection Diversity for MIMO 3-User Interference Channel with Interference Alignment

This paper explores selection diversity in the context of MIMO 3-user interference channels with interference alignment (IA), focusing on enhancing reliability through diversity order (DO) analysis. While degrees of freedom (DoF) have traditionally been emphasized for throughput optimization in IA, limited research has addressed diversity order to improve error performance. In this work, we define a conditional DO and propose a beamforming vector selection method that achieves a conditional DO of M2/2, where M is the number of antennas per transceiver. The proposed scheme employs a two-stage decoding approach, combining zero-forcing for interference cancellation with maximum likelihood (ML) decoding for desired signal recovery, which is augmented by orthogonalization techniques. Simulations demonstrate the superiority of the proposed scheme in both error probability and conditional DO values compared to conventional IA methods, particularly in scenarios with higher antenna counts. These results provide insights into optimizing IA for enhanced reliability and form the foundation for future exploration of advanced decoding and beamforming strategies.