Stability Analysis of Unfolded WMMSE for Power Allocation
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Abstract (arXiv)
Power allocation is one of the fundamental problems in wireless networks and a wide variety of algorithms address this problem from different perspectives. A common element among these algorithms is that they rely on an estimation of the channel state, which may be inaccurate on account of hardware defects, noisy feedback systems, and environmental and adversarial disturbances. Therefore, it is essential that the output power allocation of these algorithms is stable with respect to input perturbations, to the extent that the variations in the output are bounded for bounded variations in the input. In this paper, we focus on UWMMSE -- a modern algorithm leveraging graph neural networks --, and illustrate its stability to additive input perturbations of bounded energy through both theoretical analysis and empirical validation.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 18 of its 31 references that are in the map. First posted on arXiv 14 Oct 2021.
Builds on
18 of 31 references.
References · 18
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6 more
- 2019A Graph Neural Network Approach for Scalable Wireless Power Controlcited by 26
- 2020Adaptive Contention Window Design using Deep Q-learningcited by 13
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.