Joint interference alignment precoding based on the optimization algorithm on the Grassmannian manifold |
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| Affiliation: | 1. Department of Mechatronics and BioMedical Engineering, Universiti Tunku Abdul Rahman, Selangor, Malaysia;2. Department of Electrical and Electronics Engineering, Universiti Tunku Abdul Rahman, Selangor, Malaysia;1. School of Information Engineering, Xijing University, Xi’an 710123, China;2. Information and Navigation College, Air Force Engineering University, Xi’an 710077, China;1. Department of ECE, Madanapalle Institute of Technology and Science, Andhra Pradesh 517325, India;2. Department of ECE, Pondicherry Engineering College, Puducherry 605014, India;1. School of Computer Engineering, Huaihai Institute of Technology, Lianyungang 222005, China;2. Centre for RFIC and System Technology, School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;1. Department of Electronics & Communication Engineering, Government Engineering College, Palakkad, India;2. Division of Electronics, School of Engineering, Cochin University of Science & Technology, Cochin, India |
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| Abstract: | To solve the interference problem between users of the multiuser MIMO system, we first transform the system sum rate maximization problem into joint optimization of interference signal power and useful signal power. On this basis, we propose a weighted interference alignment objective function, causing the system to obtain a higher sum rate by adjusting the weight with different signal-to-noise ratios. Then, we model the transmit subspace and the interference subspace on the Grassmannian manifold and propose joint interference alignment precoding based on the Grassmannian conjugacy gradient algorithm (GCGA-JIAP algorithm). In contrast to conventional interference alignment algorithms, our proposed algorithm can reduce the computational cost by transforming the constrained optimization of the complex Euclidean space into unconstrained optimization with the degenerate dimension on the Grassmannian manifold. Computer simulation shows that the proposed algorithm improves the convergence of the iterative optimization of the transmitter precoding matrix and the receiver postprocessing matrix and also improves the sum rate performance of the multiuser MIMO interference system. |
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| Keywords: | MIMO systems Interference alignment Grassmannian manifold Precoding |
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