Numerical results show that the CKM empowered FBL RSMA outperforms space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA), particularly in high-mobility scenarios, and its performance is improved by a data-based CKM, which provides more accurate large-scale channel information than model-based approaches and enables more precise common-stream allocation.
Yi Wang, Yingyang Chen, Feng Bai et al.· arXiv.org· 0 citations
The unmanned aerial vehicle (UAV)-assisted Internet-of-Things (IoT) network architecture has emerged as a key technology for supporting communications in emergency scenarios. The quality and freshness of the data collected by UAVs directly impact the effectiveness of emergency decision-making and the overall responsiveness of the system in time-critical situations. However, limited by the battery capacity of UAVs, a fundamental tradeoff exists between information freshness and energy consumption in UAV-assisted IoT networks, which constrains the effective coverage range of emergency operations. Accordingly, this paper explores the inherent trade-off between Age of Information (AoI) and energy consumption in UAV-assisted emergency IoT systems. To reflect the highly dynamic and uncertain channel conditions typical of post-disaster environments, this work further incorporates an imperfect channel state information (CSI) model. Then, a probabilistic constraint AoI-energy tradeoff problem is formulated to jointly optimizing the time allocation of data collection, UAV trajectory, and duration of time slots. To address the resulting non-convex non-linear problem, we first convert the probabilistic constraint problem into a non-probability one, then employ a block coordinate descent method to iteratively solve the highly coupled multi-variable problem. Finally, comprehensive simulation results validate the effectiveness of the proposed method.
Mingan Luan, Xin Zhang, Zheng Chang et al.· IEEE Transactions on Green C...· 0 citations
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