Link scheduling using graph neural networks
NettetWe consider the problem of binary power control, or link scheduling, in wireless interference networks, where the power control policy is trained using graph … Nettet2. feb. 2024 · Linear assignment [ 2] is a fundamental problem of combinatorial optimization; it aims to assign the elements of some finite set to the elements of another set. This is done under one-to-one matching constraints such that the resulting assignment satisfies some optimality conditions, like a minimum cost, or, in a dual way, a maximum …
Link scheduling using graph neural networks
Did you know?
Nettet23. feb. 2024 · We propose a scalable and low complexity one-shot (single inference without loops) UE scheduling using graph neural networks (GNN). Our results show … Nettet18. jul. 2024 · Abstract and Figures Distributed power allocation is important for interference-limited wireless networks with dense transceiver pairs. In this paper, we aim to design low signaling overhead...
NettetDistributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks. Abstract: Distributed scheduling algorithms for throughput or utility maximization in dense wireless multi-hop networks can have overwhelmingly high overhead, causing increased congestion, energy consumption, radio footprint, and security vulnerability. Nettet12. sep. 2024 · Link Scheduling using Graph Neural Networks 12 Sep 2024 ... The main challenge stems from the fact that optimal link scheduling involves solving a maximum weighted independent set (MWIS) problem, which is known to be NP-hard. In practical schedulers, ...
Nettet31. des. 2024 · Inferring missing links or detecting spurious ones based on observed graphs, known as link prediction, is a long-standing challenge in graph data analysis. … NettetWhile offline portfolio approaches focus on finding a single invocation schedule that is expected to work well across all planning tasks, online methods learn to choose the right planner for each given task.In our paper, Online Planner Selection with Graph Neural Networks and Adaptive Scheduling, published in AAAI 2024, we propose a new …
Nettet18. nov. 2024 · For practical link scheduling schemes, distributed greedy approaches are commonly used to approximate the solution of the MWIS problem. However, these greedy schemes mostly ignore important topological information of the wireless networks. To overcome this limitation, we propose a distributed MWIS solver based on graph …
NettetarXiv.org e-Print archive cal worthington car dealershipsNettetsolvers suitable for link scheduling in wireless networks. Specically: 1) We propose the rst GCN-based distributed MWIS solver for link scheduling by combining the topology … cal worthington akNettet7. jun. 2024 · Graph Neural Network-Based Scheduling for Multi-UAV-Enabled Communications in D2D Networks Pei Li, Lingyi Wang, Wei Wu, Fuhui Zhou, Baoyun Wang, Qi-hui Wu Computer Science Digital Communications and Networks 2024 3 PDF View 2 excerpts, cites methods Scalable Power Control/Beamforming in … coffee and plants menuNettet1. jan. 2024 · The centralized-link-scheduling problem in a wireless network graph involves solving the maximum-weighted-independent-set (MWIS) problem on the … coffee and philosophyNettetDistributed scheduling algorithms for throughput or utility maximization in dense wireless multi-hop networks can have overwhelmingly high overhead, causing increased congestion, energy consumption, radio footprint, and security vulnerability. For wireless networks with dense connectivity, we propose a distributed scheme for link … calworthington.comNettet18. okt. 2024 · Daniel Nikovski Tomihiro Takano Show all 5 authors No full-text available Asynchronous Traveling Wave-based Distribution System Protection with Graph Neural Networks Conference Paper... calworth outdoor furnitureNettet5. aug. 2024 · This manuscript extends our conference paper, “Distributed Scheduling Using Graph Neural Networks” published in IEEE ICASSP 2024, from multiple … cal worthington chevrolet sacramento