Abstract
Aiming at the limitations of the existing Limited Feedback Interference Alignment algorithms, this paper proposes a direct codeword selection scheme that maximizes the lower-bound of the user rate and reduces the sum rate loss by integrating the Bit Allocation algorithm. The target signal is decoded using the maximum signal to interference plus noise ratio (MAX-SINR) algorithm. Moreover, low complexity and global searching mechanisms are deployed to select the optimized codewords from the generated sets of codewords that approach the ideal precoder. Simulation results show that the proposed algorithm effectively improves the rate lower-bound of the system user as compared with the existing state-of-the-art algorithms.
Highlights
Multiple-input multiple-output (MIMO) is a technology which can make great enhancements in terms of the overall throughput of the network
This paper considers the multiple-input multiple-output (MIMO)-MAC model consisting of two-cells and users per cell
This paper proposes an efficient Interference Alignment algorithm for maximizing the achievable sum rate and user rate lower-bound of the MIMO-MAC system
Summary
Multiple-input multiple-output (MIMO) is a technology which can make great enhancements in terms of the overall throughput of the network. Alignment (IA) can solve the interference problem and increase the achievable rates [1,2]. This usually needs to know the local or even global Channel State Information (CSI), and it generally uses the feedback from the receiver. Channel (MIMO-MAC) limited feedback IA algorithm that maximizes the rate lower-bound of the system user. It is based on three main steps of operations.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
