Abstract
This article presents limited feedback-based precoder quantization schemes for Interference Alignment (IA) with bounded channel state information (CSI) uncertainty. Initially, this work generalizes the min-max mean squared error (MSE) framework, followed by the development of robust precoder and decoder designs based on worst case MSE minimization. The proposed precoder and decoder designs capture the effect of CSI uncertainty using a single parameter, which is independent of the CSI uncertainty in the direct links. The IA algorithms derived employing these proposed designs are shown to be globally convergent under certain conditions. Moreover, precoder quantization schemes are presented for scenarios with and without CSI uncertainty for practical implementation of these techniques in systems with limited feedback. An optimal bit allocation scheme is presented to maximize the sum rate via analysis of the rate loss upper bound. Simulation results demonstrate the improved performance of the proposed IA schemes for various scenarios considering imperfect CSI as well as limited feedback.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IEEE Transactions on Signal and Information Processing over Networks
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.