Joint Gaussian Beam Pattern and Its Optimization for Positioning-Assisted Systems
🤖 AI Summary
This work addresses the high training and feedback overhead incurred by conventional beamforming, which relies on accurate channel state information (CSI) in massive antenna systems. To circumvent complex CSI estimation, the authors propose a localization-assisted beamforming approach leveraging joint Gaussian beams and derive, for the first time, closed-form expressions for outage probability in both two-dimensional (2D) and three-dimensional (3D) scenarios. Theoretical analysis reveals that in 2D, the optimal beam pattern is independent of the localization error distribution, whereas in 3D, it is closely dependent on it. By integrating stochastic geometry, probability theory, and optimization with Gaussian beam and localization error modeling, the proposed method significantly enhances system performance. Numerical results corroborate the accuracy of the derived closed-form solutions and the efficacy of the beam optimization strategy.
Application Category
📝 Abstract
Beamforming is a fundamental technology that not only enhances communication efficiency but also lays the foundation for massive multiple-input multiple-output~(MIMO) systems. However, its reliance on accurate channel state information (CSI) estimation introduces significant training overhead and feedback costs, especially in large-scale antenna systems. In this paper, we investigate positioning-assisted beamforming as a competitive alternative to the CSI-based methods, which circumvents the complicated CSI estimation. In particular, we analyze the outage probability of positioning-assisted systems with joint Gaussian beams and derive its closed-form expressions for both two-dimensional~(2D) and three-dimensional~(3D) scenarios. Based on these results, we also derive closed-form expressions for the optimal joint Gaussian beam pattern. The optimal solution is independent of the positioning error distribution in 2D scenarios but depends on it in 3D cases. Subsequently, the asymptotic performance of the approximation error is analyzed. Numerical results verify the derived outage probability expressions, and show the effectiveness of the beam pattern optimization.
Problem
Research questions and friction points this paper is trying to address.
beamforming
positioning-assisted systems
channel state information
outage probability
massive MIMO
Innovation
Methods, ideas, or system contributions that make the work stand out.
positioning-assisted beamforming
joint Gaussian beam
outage probability
closed-form optimization
massive MIMO
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