arXiv subjects

Lina Yuan

Publications and source records attributed to Lina Yuan.

4 recordsLinked to original sources

arXiv2025

Huayu: Advanced Real-Time Precipitation Estimation from Geostationary Satellite

As climate change drives increased frequency and intensity of extreme precipitation and flooding worldwide, posing escalating threats to public safety and economic assets, accurate and real-time satellite-based precipitation estimation is essential for operational large-scale hydrometeorological analysis and disaster monitoring. NASA's Integrated Multi-satellitE Retrievals for GPM (IMERG Final Run) combines information from "all" satellite microwave observations with gauge correction and climatological adjustment to produce precipitation estimates at 0.1° spatial and 30-min temporal resolution. However, its latency of approximately 3.5 months restricts its utility for real-time applications, despite outperforming mainstream satellite precipitation datasets in representing rainfall patterns and variability. We present Huayu, a novel machine learning-based real-time satellite precipitation retrieval system that relies solely on infrared observations from the FengYun-4B geostationary satellite to provide a more accurate precipitation estimate at a finer spatiotemporal resolution (15 min, 0.05°) over a 120° by 120° domain. Performance evaluations demonstrate that Huayu achieves strong consistency with rain gauge observations, yielding a critical success index (CSI) of 0.693 - representing a 3.43% improvement over IMERG Final Run (CSI: 0.670). Experimental results confirm that infrared satellite observations can deliver more accurate precipitation estimates than conventional multi-source algorithms.

physics.ao-ph↗

arXiv2019

Optimizing Throughput Fairness of Cluster-based Cooperation in Underlay Cognitive WPCNs

In this paper, we consider a secondary wireless powered communication network (WPCN) underlaid to a primary point-to-point communication link. The WPCN consists of a multi-antenna hybrid access point (HAP) that transfers wireless energy to a cluster of low-power wireless devices (WDs) and receives sensing data from them. To tackle the inherent severe user unfairness problem in WPCN, we consider a cluster-based cooperation where a WD acts as the cluster head that relays the information of the other WDs. Besides, we apply energy beamforming technique to balance the dissimilar energy consumptions of the WDs to further improve the fairness. However, the use of energy beamforming and cluster-based cooperation may introduce more severe interference to the primary system than the WDs transmit independently. To guarantee the performance of primary system, we consider an interference-temperature constraint to the primary system and derive the throughput performance of each WD under the peak interference-temperature constraint. To achieve maximum throughput fairness, we jointly optimize the energy beamforming design, the transmit time allocation among the HAP and the WDs, and the transmit power allocation of each WD to maximize the minimum data rate achievable among the WDs (the max-min throughput). We show that the non-convex joint optimization problem can be transformed to a convex one and then be efficiently solved using off-the-shelf convex algorithms. Moreover, we simulate under practical network setups and show that the proposed method can effectively improve the throughput fairness of the secondary WPCN, meanwhile guaranteeing the communication quality of the primary network.

cs.NI↗

arXiv2019

Throughput Maximization for Ambient Backscatter Communication: A Reinforcement Learning Approach

Ambient backscatter (AB) communication is an emerging wireless communication technology that enables wireless devices (WDs) to communicate without requiring active radio transmission. In an AB communication system, a WD switches between communication and energy harvesting modes. The harvested energy is used to power the devices operations, e.g., circuit power consumption and sensing operation. In this paper, we focus on maximizing the throughput performance of AB communication system by adaptively selecting the operating mode under fading channel environment. We model the problem as an infinite-horizon Markov Decision Process (MDP) and accordingly obtain the optimal mode switching policy by the value iteration algorithm given the channel distributions. Meanwhile, when the knowledge of channel distribution is absent, a Q-learning (QL) method is applied to explore a suboptimal strategy through device repeated interaction with the environment. Finally, our simulations show that the proposed QL method can achieve close-to-optimal throughput performance and significantly outperforms the other than representative benchmark methods.

cs.NI↗

arXiv2017

Multi-antenna Enabled Cluster-based Cooperation in Wireless Powered Communication Networks

In this paper, we consider a wireless powered communication network (WPCN) consisting of a multi-antenna hybrid access point (HAP) that transfers wireless energy to and receives sensing data from a cluster of low-power wireless devices (WDs). To enhance the throughput performance of some far-away WDs, we allow one of the WDs to act as the cluster head (CH) that helps forward the messages of the other cluster members (CMs). However, the performance of the proposed cluster-based cooperation is fundamentally limited by the high energy consumption of the CH, who needs to transmit all the WDs' messages including its own. To tackle this issue, we exploit the capability of multi-antenna energy beamforming (EB) at the HAP, which can focus more transferred power to the CH to balance its energy consumption in assisting the other WDs. Specifically, we first derive the throughput performance of each individual WD under the proposed scheme. Then, we jointly optimize the EB design, the transmit time allocation among the HAP and the WDs, and the transmit power allocation of the CH to maximize the minimum data rate achievable among all the WDs (the max-min throughput) for improved throughput fairness among the WDs. An efficient optimal algorithm is proposed to solve the joint optimization problem. Moreover, we simulate under practical network setups and show that the proposed multi-antenna enabled cluster-based cooperation can effectively improve the throughput fairness of WPCN.

cs.NI↗