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Precoder Design for User-Centric Network Massive MIMO: A Symplectic Optimization Approach
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DOI：10.1109/twc.2026.3725189.png)
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Abstract
En 中文
In this paper, we utilize symplectic optimization to design a precoder for user-centric network (UCN) massive multiple-input multiple-output (MIMO) systems, where a subset of base stations (BSs) serves each user terminal (UT) instead of using all BSs. In UCN massive MIMO systems, the dimension of the precoders is reduced compared to conventional network massive MIMO. It simplifies the implementation of precoders in practical systems. However, the matrix inversion in traditional linear precoders still requires high computational complexity. To alleviate this computational burden, we employ the symplectic optimization framework to develop an inversion-free iterative process, where optimization problems are solved based on dissipative Hamiltonian dynamical systems. To better fit symplectic optimization, we transform the received model into the real field and reformulate the weighted sum-rate (WSR) maximization problem. The objective function of the optimization problem is viewed as the potential energy of the dynamical system. Due to kinetic energy dissipation, the continuous dynamical system always converges to a state with minimal potential energy. By discretizing the continuous system while preserving the symplectic structure, we obtain an iterative method for the precoder design. The complexity analysis of the proposed symplectic method is also provided to show its high computational efficiency. Simulation results demonstrate that the proposed precoder design based on symplectic optimization outperforms the distributed weighted minimum mean-square error (WMMSE) precoder in the UCN massive MIMO system, offering a flexible trade-off between strict inversion-free operation and maximum performance based on the initialization strategy.
Keywords:
Symplectic optimization
precoder design
user-centric
network massive MIMO
Journal
IF:
10.7
Papers:
1.3W
Citations:
5.3W