English(EN) Graph Neural Networks for Resource Allocation in Integrated Sensing and Communication

图神经网络优化车联网ISAC网络的功率分配

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 00:54

一篇新论文介绍了一种基于图神经网络（GNN）的算法GNN-ISAC，旨在优化车联网集成传感与通信（ISAC）网络中的功率分配。该方法旨在最大化通信总速率，同时满足传感信号与干扰加噪声比（SINR）的约束。与WMMSE等现有方法相比，GNN-ISAC表现出有竞争力的性能，在显著降低计算成本和传感链路违规率的同时，实现了相似的通信速率。该模型还显示出强大的泛化能力，无需重新训练即可适应更大的网络配置。 AI

影响这项研究可能为未来车联网通信和传感系统带来更高效的资源管理。

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-11-05 00:54

用于集成感知与通信中资源分配的图神经网络

In vehicular integrated sensing and communication (ISAC) networks, each service-provider vehicle uses a limited power budget to serve multiple sensing targets and communication receivers. Maximizing the communication sum-rate subject to sensing signal-to-interference-plus-noise r…

本文如何被排名

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用于集成感知与通信中资源分配的图神经网络

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