Symbol detection aided minimum mean square error interference alignment

Abstract

With the presence of perfect channel state information(CSI), the achievable degrees of freedom (DoF) in wireless interference networks can be linearly scaled up with the number of users. However, with the presence of imperfect CSI, the sum rate becomes degraded and full DoF may not be achievable anymore. Interference Alignment (IA) is an appealing interference management technique since it enables us to achieve significant degrees of freedom in wireless interference networks. In IA, a complex data symbol is detected via iterative calculation on precoder and combiner in reciprocal network under a same principle, such as minimum mean square error (MMSE). A symbol detection aided MMSE (SDA-MMSE) IA iterative algorithm is proposed to improve performance. It has been shown via computer simulations that the proposed detection algorithm exhibits better performance than conventional MMSE IA algorithm.