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Energy-Efficient Massive MIMO With Decentralized Precoder Design
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DOI：10.1109/TVT.2020.3040619.png)
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摘要
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This paper presents an energy-efficient downlink precoding scheme in a multi-cell Massive MIMO system. We approach the precoder design problem to maximize the system energy efficiency by jointly considering power control, interference management, antenna switching and user throughput in a cluster of base stations. This is computationally difficult as it requires solving a sparsity-inducing non-convex optimization problem, which is NP-hard. To alleviate the solution complexity, first a stochastic smooth approximation of zero-norm is applied in the antenna power management to enable fast, gradient-based algorithms. For efficient convergence, we develop a novel optimization algorithm combining augmented multiplier (AM) and quadratic programming (QP), and show how this scheme permits decentralized implementation by offloading parts of the computation to the individual base stations to reduce communication overhead. We provide theoretical proof that the proposed algorithm converges both locally and globally under realistic assumptions. Numerical results confirm that our method achieves higher energy efficiency with a superior convergence rate compared to different types of existing methods, and illustrate the relationship between energy efficiency performance and system design parameters.
Keyword:
Throughput
Precoding
Massive MIMO
Computer architecture
Antennas
Optimization
Microprocessors
Massive MIMO
5G
beamforming
energy-efficiency
distributed optimization
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IF:
7.1
论文数:
1.8W
被引数:
6.6W
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