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. Achievability is based on the idea of interference alignment (IA). However, with the presence of imperfect CSI, the sum rate becomes degraded and full DoF may not be achievable anymore. In this paper and by considering a generalized CSI mismatch model, we propose a novel MMSE-based IA scheme such that the unitary beamformers are adaptively designed to achieve better performance when only imperfect CSI is available. We then compare the performance of the proposed scheme with maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. We show that while under perfect CSI the proposed algorithm achieves the same performance as Max-SINR, the former outperforms the latter under CSI mismatch. Meanwhile, it is shown that the proposed algorithm needs less CSI to be available and has less computational complexity compared to Max-SINR.
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