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467 results on '"Chai, Rong"'

1. Structural Knowledge-Driven Meta-Learning for Task Offloading in Vehicular Networks with Integrated Communications, Sensing and Computing

Author

Sun, Ruijin, Wen, Yao, Cheng, Nan, Wan, Wei, Chai, Rong, and Hui, Yilong

Subjects
Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture
Abstract

Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources. However, the overwhelming upload traffic may lead to unacceptable uploading time. To tackle this issue, for tasks taking environmental data as input, the data perceived by roadside units (RSU) equipped with several sensors can be directly exploited for computation, resulting in a novel task offloading paradigm with integrated communications, sensing and computing (I-CSC). With this paradigm, vehicles can select to upload their sensed data to RSUs or transmit computing instructions to RSUs during the offloading. By optimizing the computation mode and network resources, in this paper, we investigate an I-CSC-based task offloading problem to reduce the cost caused by resource consumption while guaranteeing the latency of each task. Although this non-convex problem can be handled by the alternating minimization (AM) algorithm that alternatively minimizes the divided four sub-problems, it leads to high computational complexity and local optimal solution. To tackle this challenge, we propose a creative structural knowledge-driven meta-learning (SKDML) method, involving both the model-based AM algorithm and neural networks. Specifically, borrowing the iterative structure of the AM algorithm, also referred to as structural knowledge, the proposed SKDML adopts long short-term memory (LSTM) network-based meta-learning to learn an adaptive optimizer for updating variables in each sub-problem, instead of the handcrafted counterpart in the AM algorithm.

Published
2024

2. CTGAN: Semantic-guided Conditional Texture Generator for 3D Shapes

Author

Pan, Yi-Ting, Lee, Chai-Rong, Fan, Shu-Ho, Su, Jheng-Wei, Huang, Jia-Bin, Chuang, Yung-Yu, and Chu, Hung-Kuo

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The entertainment industry relies on 3D visual content to create immersive experiences, but traditional methods for creating textured 3D models can be time-consuming and subjective. Generative networks such as StyleGAN have advanced image synthesis, but generating 3D objects with high-fidelity textures is still not well explored, and existing methods have limitations. We propose the Semantic-guided Conditional Texture Generator (CTGAN), producing high-quality textures for 3D shapes that are consistent with the viewing angle while respecting shape semantics. CTGAN utilizes the disentangled nature of StyleGAN to finely manipulate the input latent codes, enabling explicit control over both the style and structure of the generated textures. A coarse-to-fine encoder architecture is introduced to enhance control over the structure of the resulting textures via input segmentation. Experimental results show that CTGAN outperforms existing methods on multiple quality metrics and achieves state-of-the-art performance on texture generation in both conditional and unconditional settings.

Published
2024

3. Knowledge-Driven Resource Allocation for D2D Networks: A WMMSE Unrolled Graph Neural Network Approach

Author

Yang, Hao, Cheng, Nan, Sun, Ruijin, Quan, Wei, Chai, Rong, Aldubaikhy, Khalid, Alqasir, Abdullah, and Shen, Xuemin

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper proposes an novel knowledge-driven approach for resource allocation in device-to-device (D2D) networks using a graph neural network (GNN) architecture. To meet the millisecond-level timeliness and scalability required for the dynamic network environment, our proposed approach incorporates the deep unrolling of the weighted minimum mean square error (WMMSE) algorithm, referred to as domain knowledge, into GNN, thereby reducing computational delay and sample complexity while adapting to various data distributions. Specifically, the aggregation and update functions in the GNN architecture are designed by utilizing the summation and power calculation components of the WMMSE algorithm, which leads to improved model generalization and interpretabiliy. Theoretical analysis of the proposed approach reveals its capability to simplify intricate end-to-end mappings and diminish the model exploration space, resulting in increased network expressiveness and enhanced optimization performance. Simulation results demonstrate the robustness, scalability, and strong performance of the proposed knowledge-driven resource allocation approach across diverse communication topologies without retraining. Our findings contribute to the development of efficient and scalable wireless resource management solutions for distributed and dynamic networks with strict latency requirements.

Published
2023

4. Digital Twin-Assisted Knowledge Distillation Framework for Heterogeneous Federated Learning

Author

Wang, Xiucheng, Cheng, Nan, Ma, Longfei, Sun, Ruijin, Chai, Rong, and Lu, Ning

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Distributed, Parallel, and Cluster Computing, Electrical Engineering and Systems Science - Systems and Control
Abstract

In this paper, to deal with the heterogeneity in federated learning (FL) systems, a knowledge distillation (KD) driven training framework for FL is proposed, where each user can select its neural network model on demand and distill knowledge from a big teacher model using its own private dataset. To overcome the challenge of train the big teacher model in resource limited user devices, the digital twin (DT) is exploit in the way that the teacher model can be trained at DT located in the server with enough computing resources. Then, during model distillation, each user can update the parameters of its model at either the physical entity or the digital agent. The joint problem of model selection and training offloading and resource allocation for users is formulated as a mixed integer programming (MIP) problem. To solve the problem, Q-learning and optimization are jointly used, where Q-learning selects models for users and determines whether to train locally or on the server, and optimization is used to allocate resources for users based on the output of Q-learning. Simulation results show the proposed DT-assisted KD framework and joint optimization method can significantly improve the average accuracy of users while reducing the total delay.

Published
2023

5. A Knowledge Graph for UAV Mission Planning Systems

Author

Duan, Xiaofang, Chai, Rong, Zhang, Siya, Liang, Chengchao, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Feifei, editor, Wu, Jun, editor, Li, Yun, editor, Gao, Honghao, editor, and Wang, Shangguang, editor

Published
2024
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6. Dynamic Resource Allocation for Multi-beam Satellite Communication Systems

Author

Zhang, Siya, Chai, Rong, Liu, Lei, Yang, Guorong, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Feifei, editor, Wu, Jun, editor, Li, Yun, editor, Gao, Honghao, editor, and Wang, Shangguang, editor

Published
2024
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7. Scalable Blockchain-Based Access Control Algorithm for Large-Scale IoT Networks with Byzantine Nodes

Author

Yang, Ningyu, Yang, Xizheng, Chai, Rong, Liang, Chengchao, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Feifei, editor, Wu, Jun, editor, Li, Yun, editor, Gao, Honghao, editor, and Wang, Shangguang, editor

Published
2024
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8. A Two-Stage Heuristic SFC Deployment Approach in Software Defined Satellite Networks

Author

Liu, Zhanjun, Peng, Feng, Liang, Chengchao, Chai, Rong, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Feifei, editor, Wu, Jun, editor, Li, Yun, editor, Gao, Honghao, editor, and Wang, Shangguang, editor

Published
2024
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9. A Novel Approach on Semantic Performance Oriented Radio Resource Allocation

Author

Liu, Zhanjun, Zhao, Kaixuan, Xiao, Ao, Liang, Chengchao, Chai, Rong, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Feifei, editor, Wu, Jun, editor, Li, Yun, editor, Gao, Honghao, editor, and Wang, Shangguang, editor

Published
2024
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12. The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification

Author

Baid, Ujjwal, Ghodasara, Satyam, Mohan, Suyash, Bilello, Michel, Calabrese, Evan, Colak, Errol, Farahani, Keyvan, Kalpathy-Cramer, Jayashree, Kitamura, Felipe C., Pati, Sarthak, Prevedello, Luciano M., Rudie, Jeffrey D., Sako, Chiharu, Shinohara, Russell T., Bergquist, Timothy, Chai, Rong, Eddy, James, Elliott, Julia, Reade, Walter, Schaffter, Thomas, Yu, Thomas, Zheng, Jiaxin, Moawad, Ahmed W., Coelho, Luiz Otavio, McDonnell, Olivia, Miller, Elka, Moron, Fanny E., Oswood, Mark C., Shih, Robert Y., Siakallis, Loizos, Bronstein, Yulia, Mason, James R., Miller, Anthony F., Choudhary, Gagandeep, Agarwal, Aanchal, Besada, Cristina H., Derakhshan, Jamal J., Diogo, Mariana C., Do-Dai, Daniel D., Farage, Luciano, Go, John L., Hadi, Mohiuddin, Hill, Virginia B., Iv, Michael, Joyner, David, Lincoln, Christie, Lotan, Eyal, Miyakoshi, Asako, Sanchez-Montano, Mariana, Nath, Jaya, Nguyen, Xuan V., Nicolas-Jilwan, Manal, Jimenez, Johanna Ortiz, Ozturk, Kerem, Petrovic, Bojan D., Shah, Chintan, Shah, Lubdha M., Sharma, Manas, Simsek, Onur, Singh, Achint K., Soman, Salil, Statsevych, Volodymyr, Weinberg, Brent D., Young, Robert J., Ikuta, Ichiro, Agarwal, Amit K., Cambron, Sword C., Silbergleit, Richard, Dusoi, Alexandru, Postma, Alida A., Letourneau-Guillon, Laurent, Perez-Carrillo, Gloria J. Guzman, Saha, Atin, Soni, Neetu, Zaharchuk, Greg, Zohrabian, Vahe M., Chen, Yingming, Cekic, Milos M., Rahman, Akm, Small, Juan E., Sethi, Varun, Davatzikos, Christos, Mongan, John, Hess, Christopher, Cha, Soonmee, Villanueva-Meyer, Javier, Freymann, John B., Kirby, Justin S., Wiestler, Benedikt, Crivellaro, Priscila, Colen, Rivka R., Kotrotsou, Aikaterini, Marcus, Daniel, Milchenko, Mikhail, Nazeri, Arash, Fathallah-Shaykh, Hassan, Wiest, Roland, Jakab, Andras, Weber, Marc-Andre, Mahajan, Abhishek, Menze, Bjoern, Flanders, Adam E., and Bakas, Spyridon

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR), and the Medical Image Computing and Computer Assisted Interventions (MICCAI) society. Since its inception, BraTS has been focusing on being a common benchmarking venue for brain glioma segmentation algorithms, with well-curated multi-institutional multi-parametric magnetic resonance imaging (mpMRI) data. Gliomas are the most common primary malignancies of the central nervous system, with varying degrees of aggressiveness and prognosis. The RSNA-ASNR-MICCAI BraTS 2021 challenge targets the evaluation of computational algorithms assessing the same tumor compartmentalization, as well as the underlying tumor's molecular characterization, in pre-operative baseline mpMRI data from 2,040 patients. Specifically, the two tasks that BraTS 2021 focuses on are: a) the segmentation of the histologically distinct brain tumor sub-regions, and b) the classification of the tumor's O[6]-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. The performance evaluation of all participating algorithms in BraTS 2021 will be conducted through the Sage Bionetworks Synapse platform (Task 1) and Kaggle (Task 2), concluding in distributing to the top ranked participants monetary awards of $60,000 collectively., Comment: 19 pages, 2 figures, 1 table

Published
2021

15. Beam Illumination and Resource Allocation for Multi-beam Satellite Systems

Author

Tang, Xiaorui, Chai, Rong, Gui, Kang’an, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Feifei, editor, Wu, Jun, editor, Li, Yun, editor, and Gao, Honghao, editor

Published
2023
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16. A Survey on IoT Modules: Architecture, Key Technologies and Future Directions

Author

Gao, Yifan, Chai, Rong, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Deng, Der-Jiunn, editor, Chao, Han-Chieh, editor, and Chen, Jyh-Cheng, editor

Published
2023
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28. Discovery and demonstration of the temperature stress response functions of Dermatophagoides farinae proteins 1 and 2.

Author

Zhang, Wanyu, Niu, Dongling, Zhao, Yae, Hu, Li, Guan, Chenglin, and Chai, Rong

Subjects
GENE expression, POLYMERASE chain reaction, DERMATOPHAGOIDES, ALLERGIES, SURVIVAL rate
Abstract

Background: Dermatophagoides farinae proteins (DFPs) are abundantly expressed in D. farinae; however, their functions remain unknown. Our previous transcriptome sequencing analyses revealed that the basal expression of DFP1 and DFP2 in D. farinae was high and, more importantly, upregulated under temperature stress. Therefore, DFPs were speculated to exert a temperature stress response function. Results: Real-time quantitative polymerase chain reaction detection revealed that both DFP1 and DFP2 were significantly upregulated under temperature stress. Particularly, DFP1 was upregulated under cold stress. Electrophoresis of D. farinae total proteins revealed an increased abundance of DFP1 and DFP2 (40–55 kDa bands) under temperature stress, which was corroborated by the mass spectrometry results. After silencing DFP1 and DFP2 further, temperature stress led to decreases in gene expression and survival rates. Moreover, DFP1 was identified as the upstream regulator of DFP2. Conclusion: This study highlights the temperature stress response functions of DFP1 and DFP2 at the mRNA and protein levels. These results provide important insights for applying DFP1 and DFP2 as potential target genes for the molecular prevention and control of D. farinae to prevent allergic diseases. The newly established methods provide methodological guidance for the study of genes with unknown functions in mites. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Unveiling the spatial distribution and transboundary pathways of FMD serotype O in Western China and its bordering countries.

Author

Zhang, Shuang, Chai, Rong, Hu, Yezhi, Joka, Fekede Regassa, Wu, Xiaodong, Wang, Haoning, and Wang, Xiaolong

Subjects
*FOOT & mouth disease, *VIRUS diseases, *COMMUNICABLE diseases, *DOMESTIC animals, *ECONOMIC impact
Abstract

Foot-and-mouth disease (FMD) is a severe, highly contagious viral disease of livestock that has a significant economic impact on domestic animals and threatens wildlife survival in China and border countries. However, effective surveillance and prevention of this disease is often incomplete and unattainable due to the cost, the great diversity of wildlife hosts, the changing range and dynamics, and the diversity of FMDV. In this study, we used predictive models to reveal the spread and risk of FMD in anticipation of identifying key nodes to control its spread. For the first time, the spatial distribution of FMD serotype O was predicted in western China and border countries using a niche model, which is a combination of eco-geographic, human, topographic, and vegetation variables. The transboundary least-cost pathways (LCPs) model for ungulates in the study area were also calculated. Our study indicates that FMD serotype O survival is seasonal at low altitudes (March and June) and more sensitive to temperature differences at high altitudes. FMD serotype O risk was higher in Central Asian countries and both were highly correlated with the population variables. Ten LCPs were obtained representing Pakistan, Kazakhstan, Kyrgyzstan, and China. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Energy Efficient Computation Offloading for Energy Harvesting-Enabled Heterogeneous Cellular Networks (Workshop)

Author

Mao, Mengqi, Chai, Rong, Chen, Qianbin, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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35. Cost Function Minimization-Based Joint UAV Path Planning and Charging Station Deployment (Workshop)

Author

Wei, Tao, Chai, Rong, Chen, Qianbin, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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36. Delay Optimization-Based Joint Route Selection and Resource Allocation Algorithm for Cognitive Vehicular Ad Hoc Networks (Workshop)

Author

Liu, Changzhu, Chai, Rong, Peng, Shangxin, Chen, Qianbin, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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37. Energy Efficiency Optimization-Based Joint Resource Allocation and Clustering Algorithm for M2M Communication Networks (Workshop)

Author

Liu, Changzhu, Zubair, Ahmad, Chai, Rong, Chen, Qianbin, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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38. Service Delay Minimization-Based Joint Clustering and Content Placement Algorithm for Cellular D2D Communication Systems

Author

Zubair, Ahmad, Ma, Pengfei, Wei, Tao, Wang, Ling, Chai, Rong, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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39. Joint Task Offloading, CNN Layer Scheduling and Resource Allocation in Cooperative Computing System

Author

Song, Xia, Chai, Rong, Chen, Qianbin, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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43. Precoding and Trajectory Design for UAV-Assisted Integrated Communication and Sensing Systems

Author

Chai, Rong, Cui, Xianglin, Sun, Ruijin, Zhao, Dongmei, and Chen, Qianbin

Abstract

Benefited from the characteristics of high mobility, low cost and convenient deployment, unmanned aerial vehicles (UAVs) can be deployed in wireless communication systems as mobile base stations (BSs) to improve the communication performance of users. In addition, by deploying communication and sensing equipment and supporting efficient resource sharing of communication and sensing technologies, UAVs are expected to act as high-performance aerial platforms which integrate communication and sensing technologies. In this paper, a multi-antenna UAV-enabled joint communication and sensing scenario is examined by jointly considering the flight energy of the UAV, multi-antenna transmissions, and the user service requirements. Two optimization problems are respectively formulated for various UAV states. In particular, the problem of communication precoding and UAV flight trajectory optimization is formulated as a minimum user rate maximization problem and the joint optimization problem of UAV sensing position, communication and sensing precoding is formulated as a minimum target detection probability maximization problem. Since the minimum-rate maximization problem is a non-convex optimization problem, which is difficult to solve directly, we decompose the original optimization problem into a communication precoding design subproblem and a UAV trajectory design subproblem, and solve the two subproblems successively by applying an alternate iteration method. Specifically, a zero forcing (ZF) algorithm is put forward for solving the communication precoding design subproblem. A successive convex approximation (SCA) algorithm is applied to determine the optimal trajectory of the UAV. Based on the optimal trajectory of the UAV, the sensing position optimization problem is modeled as a weighted distance minimization problem, and then a heuristic algorithm is proposed to obtain the optimal positions. Finally, a ZF algorithm-based joint communication and sensing precoding is presented. The effectiveness of the proposed algorithm is verified by simulations.

Published
2024
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44. System Cost-Oriented UAV Deployment for Integrated Access and Backhaul Networks

Author

Chai, Rong, He, Lin, Sun, Ruijin, and Chen, Qianbin

Abstract

Unmanned aerial vehicles (UAVs) have emerged as a promising solution to provide wireless data access for ground users (GUs) in various applications. In the scenario where GUs are far away from the gateway, both the access and backhaul links in UAV networks significantly affect the system performance. In this paper, we study the UAV deployment problem in an integrated access and backhaul network (IABN), where a number of UAVs are deployed as aerial base stations (ABSs) and aerial relays (ARs) to forward GUs $^\prime$ data packets to the remote gateway via multi-hop transmissions. Aiming at minimizing the system cost, which is defined as the weighted sum of UAV deployment cost and the energy consumption required for data transmission, a constrained system cost minimization problem is formulated, where the joint UAV deployment, GU association, route selection and resource allocation strategy is optimized. To solve the formulated non-convex problem, we propose an alternative iteration method, which includes two subalgorithms. For the first subalgorithm, we focus on the optimal design of the access links and propose a joint ABS deployment and resource allocation algorithm. Specifically, a modified K-means based clustering scheme is proposed to determine ABS deployment and GU association strategy, then an iterative Lagrange-based power allocation strategy and a greedy Kuhn-Munkras algorithm-based subchannel assignment strategy are presented, respectively. Given the obtained ABS deployment strategy, for the second subalgorithm, we then design a joint AR deployment, route selection and power allocation scheme for the backhaul links and propose a minimum circle algorithm-based AR deployment and route selection strategy. Finally, the suboptimal solution is obtained by alternatively handling the two subalgorithms. Numerical results show that the proposed UAV deployment algorithm can achieve a 19% performance gain over the existing scheme when the packet size is $6\times 10^{6}$ bits and system bandwidth is $0.5\times 10^{6}$ Hz.

Published
2024
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45. Energy-Aware Joint Route Selection and Resource Allocation in Heterogeneous Satellite Networks

Author

Li, Jinhong, Chai, Rong, Liu, Chong, Liang, Chengchao, Chen, Qianbin, and Richard Yu, F.

Abstract

In order to ensure efficient data transmission from satellites to ground stations (GSs), resource allocation schemes must be designed. In cases where direct data transmission from satellites to GSs is not possible due to a dynamic network topology and limited contact time, efficient relay selection or route selection schemes should be employed. This paper considers a satellite communication network in which a number of source low earth orbit(SLEO) satellites are attempting to transmit their data flows to the designated GSs. To improve the transmission performance of the data flows, one geosynchronous earth orbit (GEO) satellite and a number of relay LEO (RLEO) satellites in the network are used as relays. To maximize energy efficiency, a joint route selection and resource allocation mechanism is proposed. The energy cost of the system, which is the sum of the energy cost of the SLEO satellites and the RLEO satellites, is used to formulate the joint route selection and resource allocation as a system energy cost minimization problem. Since the original optimization problem is NP hard, it is transformed into three subproblems: inter-satellite power allocation, satellite-ground power allocation, and route selection. These subproblems are solved using a greedy algorithm, the Lagrange dual method, and a matching-based heuristic algorithm, respectively. The numerical results demonstrate the effectiveness of the proposed scheme.

Published
2024
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46. Joint User Association and Content Placement for D2D-Enabled Heterogeneous Cellular Networks

Author

Li, Yingying, Chai, Rong, Chen, Qianbin, Jin, Chun, Akan, Ozgur, Series Editor, Bellavista, Paolo, Series Editor, Cao, Jiannong, Series Editor, Coulson, Geoffrey, Series Editor, Dressler, Falko, Series Editor, Ferrari, Domenico, Series Editor, Gerla, Mario, Series Editor, Kobayashi, Hisashi, Series Editor, Palazzo, Sergio, Series Editor, Sahni, Sartaj, Series Editor, Shen, Xuemin (Sherman), Series Editor, Stan, Mircea, Series Editor, Xiaohua, Jia, Series Editor, Zomaya, Albert Y., Series Editor, Liu, Xingang, editor, Cheng, Dai, editor, and Jinfeng, Lai, editor

Published
2019
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47. Network Load Minimization-Based Virtual Network Embedding Algorithm for Software-Defined Networking

Author

Xie, Desheng, Chai, Rong, Mao, Mengqi, Chen, Qianbin, Jin, Chun, Akan, Ozgur, Series Editor, Bellavista, Paolo, Series Editor, Cao, Jiannong, Series Editor, Coulson, Geoffrey, Series Editor, Dressler, Falko, Series Editor, Ferrari, Domenico, Series Editor, Gerla, Mario, Series Editor, Kobayashi, Hisashi, Series Editor, Palazzo, Sergio, Series Editor, Sahni, Sartaj, Series Editor, Shen, Xuemin (Sherman), Series Editor, Stan, Mircea, Series Editor, Xiaohua, Jia, Series Editor, Zomaya, Albert Y., Series Editor, Liu, Xingang, editor, Cheng, Dai, editor, and Jinfeng, Lai, editor

Published
2019
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