Artificial diversity for UWB MB-OFDM Interference Alignment based on real-world channel models and antenna selection techniques

Main objective of this contribution is to apply Interference Alignment (IA) algorithms in real-world indoor environments for UWB MIMO MB-OFDM communication systems. In indoor environments, the required orthogonality between multi-users channels, which is necessary for proper IA, could be hardly reached. The spatial diversity among the users/nodes is mostly insufficient to obtain a robust performance for IA algorithms. In this work, a practical artificial channel diversity technique is applied through antenna selection to choose the best scenario providing the maximum orthogonality and consequentially the best overall system performance. Our analysis considers deterministic UWB MIMO channel model based on EM Ray-tracing in a real-world multi-user indoor environment. Simulation results present a significant enhancement in the overall system performance. Furthermore, the impact of the directional properties and the orientations of the antennas on the system are investigated.