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Xin-Wei Yao - IEEE Xplore Author Profile

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Author details

Xin-Wei Yao

Also published under: XinWei Yao, Xinwei Yao

Publications

37

Citations

285

Publications by Year

20102024

Co-Authors:

Masoud AsghariYue-Feng CenChao ChenYi-Wei ChenKaikai Chi

Show All Co-Authors (92)

Xin-Wei Yao

Also published under: XinWei Yao, Xinwei Yao

Affiliation

College of Computer Science and Technology

Zhejiang University of Technology

Hangzhou, China

Institute for Frontiers and Interdisciplinary Sciences

Zhejiang University of Technology

Hangzhou, China

Publication Topics

Energy Harvesting,
Energy Consumption,
Attention Module,
Data Packets,
Data Transmission,
Deep Neural Network,
Feature Space,
Internet Of Things,
Latent Space,
Nanonetwork,
Neural Network,
Time Slot

Biography

Xinwei Yao (Member, IEEE) received the Ph.D. degree in information engineering from the Zhejiang University of Technology, Hangzhou, China, in 2013. From March 2012 to February 2013, he was a Visiting Scholar with Loughborough University, Leicestershire, U.K. From August 2015 to July 2016, he was a Visiting Professor with the University of Buffalo, The State University of New York, Buffalo, NY, USA. He is currently an Associate Professor with the College of Computer Science and Technology, Zhejiang University of Technology. His current research interests include the area of terahertz-band communication networks, electromagnetic nanonetworks, wireless ad hoc and sensor networks, wireless power transfer, and the Internet of Things. He is a me...

Publications

37

Citations

285

Publications by Year

20102024

Co-Authors:

Masoud Asghari
Yue-Feng Cen
Chao Chen
Yi-Wei Chen
Kaikai Chi

Show All Co-Authors (92)

Author's Published Works

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Showing 1-25 of 37 results

Journals (19)

Conferences (17)

Magazines (1)

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Xin-Wei Yao(23)
Xinwei Yao(13)
Qiang Li(9)
Wan-Liang Wang(6)
Chao-Chao Wang(5)
College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China(19)
Institute for Frontier and Interdisciplinary Sciences, Zhejiang University of Technology, Hangzhou, China(6)
School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China(5)
College of Computer Science, Zhejiang University of Technology, Hangzhou, China(3)
Taizhou Key Laboratory of Advanced Manufacturing Technology, Taizhou Institute, Zhejiang University of Technology, Taizhou, China(3)
IEEE Internet of Things Journal(4)
IEEE Access(3)
IEEE Transactions on Mobile Computing(3)
2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops)(2)
2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)(2)
IEEE(37)
Media(2)
Changchun, China(2)
Tianjin, China(2)
Cardiff, UK(1)
Chengdu, China(1)
Chiang Mai, Thailand(1)
Energy Harvesting(9)
Nanonetwork(9)
Energy Consumption(8)
Data Transmission(5)
Energy Efficiency(5)

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ST-GAIN: Generative Dynamic Style Transfer Structure for Missing Traffic Speed Data Imputation

Xin-Wei Yao;Jiacheng Wu;Qiang Li;Zhong-Hua Yao;Zhenzhu Wang

2024 IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA)

Year: 2024 | Conference Paper |

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The sensing coverage of roadside sensing system usually does not cover the entire road network, resulting in block missing values in traffic data. Traditional methods either adopted simple hints or graph neural networks to capture the speed variation. However, these methods fail to consider that block missing values have less surrounding values and are less susceptible to the influence of adjacent...Show More

ST-GAIN: Generative Dynamic Style Transfer Structure for Missing Traffic Speed Data Imputation

Xin-Wei Yao;Jiacheng Wu;Qiang Li;Zhong-Hua Yao;Zhenzhu Wang

2024 IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA)

Year: 2024 | Conference Paper |

SMGNN: Semantic Multi-Connected Graph Neural Network for Traffic Flow Prediction

Xin-Wei Yao;Wei-Cai Li;Xiang-Yang Li;Xiao-Li Zhang;Zhong-Hua Yao;Qiang Li

2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Year: 2024 | Conference Paper |

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Traffic flow prediction, as one of the problems of spatial correlation analysis of time series, has been extensively studied. The extraction and fusion of effective spatio-temporal features are crucial for achieving high-precision traffic flow prediction. Traditionally, the adjacency graph designed based on the neighboring nodes of real-world road networks has been indispensable for learning spati...Show More

SMGNN: Semantic Multi-Connected Graph Neural Network for Traffic Flow Prediction

Xin-Wei Yao;Wei-Cai Li;Xiang-Yang Li;Xiao-Li Zhang;Zhong-Hua Yao;Qiang Li

2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Year: 2024 | Conference Paper |

Decouple and Align Sparse R-CNN for End-to-End Object Detection

Xin-Wei Yao;Yu-Chen Zhang;Yu-Yi Zhi;Kai-Jie Zhang;Zhi-Heng Yuan

2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

Year: 2024 | Conference Paper |

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Real-world applications of object detection, such as video referee at the Hangzhou Asian Games, have high requirements for accuracy. However, the performance of detectors is hindered by the discrepancy between the two sub-tasks of classification and localization, which mainly includes inconsistent feature requirements and inconsistent output pre-dictions. To alleviate the discrepancy, this paper p...Show More

Decouple and Align Sparse R-CNN for End-to-End Object Detection

Xin-Wei Yao;Yu-Chen Zhang;Yu-Yi Zhi;Kai-Jie Zhang;Zhi-Heng Yuan

2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

Year: 2024 | Conference Paper |

Simulated Annealing Deep Q-learning Incentive Mechanism for Mobile Crowd Sensing

Xin-Wei Yao;Wei-Wei Xing;Chu-Feng Qi;Qiang Li;Wei-Qiang Wang;Xing Fu

2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

Year: 2024 | Conference Paper |

Mobile Crowd Sensing (MCS) represents an emerging paradigm for collecting sensory data, leveraging the extensive sensing capabilities of widely used mobile devices to execute sensing tasks. Among the array of challenges facing current MCS systems, the incentive mechanism for data requesters and participants consistently stands out as a paramount concern. Existing incentive mechanisms often rely on...Show More

Simulated Annealing Deep Q-learning Incentive Mechanism for Mobile Crowd Sensing

Xin-Wei Yao;Wei-Wei Xing;Chu-Feng Qi;Qiang Li;Wei-Qiang Wang;Xing Fu

2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

Year: 2024 | Conference Paper |

Collect Spatiotemporally Correlated Data in IoT Networks With an Energy-Constrained UAV

Wenzheng Xu;Heng Shao;Qunli Shen;Jian Peng;Wen Huang;Weifa Liang;Tang Liu;Xin-Wei Yao;Tao Lin;Sajal K. Das

IEEE Internet of Things Journal

Year: 2024 | Volume: 11, Issue: 11 | Journal Article |

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Unmanned aerial vehicles (UAVs) are promising tools for efficient data collections of sensors in Internet of Things networks. Existing studies exploited both spatial and temporal data correlations to reduce the amount of collected redundant data, in which sensors are first partitioned into different clusters, a master sensor in each cluster then collects raw data from other sensors and compresses ...Show More

Collect Spatiotemporally Correlated Data in IoT Networks With an Energy-Constrained UAV

Wenzheng Xu;Heng Shao;Qunli Shen;Jian Peng;Wen Huang;Weifa Liang;Tang Liu;Xin-Wei Yao;Tao Lin;Sajal K. Das

IEEE Internet of Things Journal

Year: 2024 | Volume: 11, Issue: 11 | Journal Article |

Improved Autoencoder Model With Memory Module for Anomaly Detection

Wei Huang;Zhen Liu;Xiaohang Jin;Jinshan Xu;Xinwei Yao

IEEE Sensors Journal

Year: 2024 | Volume: 24, Issue: 8 | Journal Article |

Cited by: Papers (1)

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As a commonly used model for anomaly detection, the autoencoder model for anomaly detection does not train the objective for extracted features, which is a downside of autoencoder model. In addition, it is well known that the autoencoder model has over-prominent reconstruction ability for anomalous data, leading to high false-negative rate. On the other hand, the deep support vector data descripti...Show More

Improved Autoencoder Model With Memory Module for Anomaly Detection

Wei Huang;Zhen Liu;Xiaohang Jin;Jinshan Xu;Xinwei Yao

IEEE Sensors Journal

Year: 2024 | Volume: 24, Issue: 8 | Journal Article |

Maximizing Network Throughput in Heterogeneous UAV Networks

Shuyue Li;Jing Li;Chaocan Xiang;Wenzheng Xu;Jian Peng;Ziming Wang;Weifa Liang;Xinwei Yao;Xiaohua Jia;Sajal K Das

IEEE/ACM Transactions on Networking

Year: 2024 | Volume: 32, Issue: 3 | Journal Article |

Cited by: Papers (3)

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In this paper we study the deployment of an Unmanned Aerial Vehicle (UAV) network that consists of multiple UAVs to provide emergent communication service for people who are trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of people. Unlike most existing studies that focused on ...Show More

Maximizing Network Throughput in Heterogeneous UAV Networks

Shuyue Li;Jing Li;Chaocan Xiang;Wenzheng Xu;Jian Peng;Ziming Wang;Weifa Liang;Xinwei Yao;Xiaohua Jia;Sajal K Das

IEEE/ACM Transactions on Networking

Year: 2024 | Volume: 32, Issue: 3 | Journal Article |

FedAWR: An Interactive Federated Active Learning Framework for Air Writing Recognition

Xiangjie Kong;Wenyi Zhang;Youyang Qu;Xinwei Yao;Guojiang Shen

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 5 | Journal Article |

Cited by: Papers (6)

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The rapid development of technology such as virtual reality and augmented reality, coupled with the reduced direct contact due to the COVID-19 pandemic, has led to the emergence of a more advanced mode of interaction: air handwriting. This new form of human-computer interaction allows users to input text by writing in the air freely. However, deploying and applying existing air handwriting recogni...Show More

FedAWR: An Interactive Federated Active Learning Framework for Air Writing Recognition

Xiangjie Kong;Wenyi Zhang;Youyang Qu;Xinwei Yao;Guojiang Shen

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 5 | Journal Article |

UMIM: Utility-Maximization Incentive Mechanism for Mobile Crowd Sensing

Xin-Wei Yao;Xiao-Tian Yang;Qiang Li;Chu-Feng Qi;Xiang-Jie Kong;Xiang-Yang Li

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 5 | Journal Article |

Cited by: Papers (5)

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Mobile Crowd Sensing (MCS) represents a novel paradigm which utilizes intelligent devices carried by mobile users to collect and transmit data. Appropriate incentives are essential to recruit enough participants for sensing tasks. Existing works have designed some incentive mechanisms for MCS, which are not suitable for scenarios when the participants increase significantly as a result of the boom...Show More

UMIM: Utility-Maximization Incentive Mechanism for Mobile Crowd Sensing

Xin-Wei Yao;Xiao-Tian Yang;Qiang Li;Chu-Feng Qi;Xiang-Jie Kong;Xiang-Yang Li

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 5 | Journal Article |

Low-Dimensional Feature Representation with Hybrid Attention for Few-Shot Image Classification

Xin-Wei Yao;Zhi-Heng Yuan;Yu-Li Fang;Chuan He;Yu-Chen Zhang;Qiang Li

2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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Learning effective image representation and constructing a suitable metric space are two main challenges in few-shot image classification. Existing methods normally consider the joint characteristic distribution of the image to improve the image representation ability, but it also brings high computational cost and produces high-dimensional embedding vectors, which limit their real-world applicabi...Show More

Low-Dimensional Feature Representation with Hybrid Attention for Few-Shot Image Classification

Xin-Wei Yao;Zhi-Heng Yuan;Yu-Li Fang;Chuan He;Yu-Chen Zhang;Qiang Li

2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)

Year: 2023 | Conference Paper |

RepATT: Re-parameterization and Attention-guided Hybrid Anchor Classification for Real-time Lane Detection

Xin-Wei Yao;Kai-Jie Zhang;Yang Yang;Gui-Yang Pu;Qiang Li

2023 International Conference on Artificial Intelligence of Things and Systems (AIoTSys)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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Lane detection is a critical technology in autonomous driving, which requires both high detection accuracy and real-time efficiency, especially in complex scenarios like severe occlusions, and dazzling light conditions. To achieve the above requirements, based on re-parameterization and attention mechanism we propose a real-time lane detection network with a classification-based manner named RepAT...Show More

RepATT: Re-parameterization and Attention-guided Hybrid Anchor Classification for Real-time Lane Detection

Xin-Wei Yao;Kai-Jie Zhang;Yang Yang;Gui-Yang Pu;Qiang Li

2023 International Conference on Artificial Intelligence of Things and Systems (AIoTSys)

Year: 2023 | Conference Paper |

MicroKGCL: A Knowledge Graph for Root Cause Localization of Feedback Issues in Microservices

Xin-Wei Yao;Qi-Chao Lu;Qiang Li;Lin-Lang Liu;Zhi-Chao Zhu

2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security (QRS)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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The popularity of the microservices architecture has led to an evident trend of integration in system design, enabling systems to integrate numerous services to meet the diverse requirements of users. However, with extensive integration, it is difficult to quickly identify the root cause of the issues. In this paper, we propose MicroKGCL, a knowledge graph for root cause localization of feedback i...Show More

MicroKGCL: A Knowledge Graph for Root Cause Localization of Feedback Issues in Microservices

Xin-Wei Yao;Qi-Chao Lu;Qiang Li;Lin-Lang Liu;Zhi-Chao Zhu

2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security (QRS)

Year: 2023 | Conference Paper |

DDIN: Deep Disentangled Interest Network for Click-Through Rate Prediction

Xin-Wei Yao;Chuan He;Wei-Wei Xing;Qi -Chao Lu;Xin-Ge Zhang;Yu-Chen Zhang

2023 International Joint Conference on Neural Networks (IJCNN)

Year: 2023 | Conference Paper |

Cited by: Papers (4)

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Click-Through Rate(CTR) prediction aims to predict the possibility of users clicking on products, which has become the core task of advertising recommendation systems. Due to the richness of user historical behavior, a key to making effective prediction is to capture users' diverse interests from historical behavior. An efficient way to do this is to perform dot product of behavior and target embe...Show More

DDIN: Deep Disentangled Interest Network for Click-Through Rate Prediction

Xin-Wei Yao;Chuan He;Wei-Wei Xing;Qi -Chao Lu;Xin-Ge Zhang;Yu-Chen Zhang

2023 International Joint Conference on Neural Networks (IJCNN)

Year: 2023 | Conference Paper |

A Central High-speed Lane Routing Protocol for Flow-Guided Intra-body Nanonetworks

Xin-Wei Yao;Lang Lin;Masoud Asghari

2023 8th International Conference on Computer and Communication Systems (ICCCS)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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The development of nanotechnology in recent years makes intra-body flow-guided nanonetworks more feasible. Monitoring different biomarkers, detecting infectious agents, locating cancerous cells, delivering drugs accurately and other medical application are under study. Taking the consideration of the laminar blood flow feature of blood vessels, where concentric layers of blood with different veloc...Show More

A Central High-speed Lane Routing Protocol for Flow-Guided Intra-body Nanonetworks

Xin-Wei Yao;Lang Lin;Masoud Asghari

2023 8th International Conference on Computer and Communication Systems (ICCCS)

Year: 2023 | Conference Paper |

A Hybrid Communication Scheme for Throughput Maximization in Backscatter-Aided Energy Harvesting Cognitive Radio Networks

Kechen Zheng;Jiahong Wang;Xiaoying Liu;Xin-Wei Yao;Yang Xu;Jia Liu

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 18 | Journal Article |

Cited by: Papers (11)

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Motivated by the benefits of cognitive radio (CR), energy harvesting (EH), and backscatter communication (BC) technologies to support Internet of Things (IoT) systems, we investigate the backscatter-aided EH CR networks (EH-CRNs) in a multichannel scenario. To achieve high throughput on various channels, we propose a novel hybrid communication scheme that the secondary transmitter (ST) selects one...Show More

A Hybrid Communication Scheme for Throughput Maximization in Backscatter-Aided Energy Harvesting Cognitive Radio Networks

Kechen Zheng;Jiahong Wang;Xiaoying Liu;Xin-Wei Yao;Yang Xu;Jia Liu

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 18 | Journal Article |

Optimal Time Allocation for Backscatter-Aided Relay Cooperative Transmission in Wireless-Powered Heterogeneous CRNs

Xiaoying Liu;Zhongwei Lin;Kechen Zheng;Xin-Wei Yao;Jia Liu

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 18 | Journal Article |

Cited by: Papers (5)

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Nowadays, backscatter, radio-frequency (RF) energy harvesting (EH), and cognitive radio (CR) technologies have been widely applied in Internet of Things (IoT) to address the issues of energy supply and spectrum scarcity. This article focuses on the throughput maximization problem of backscatter-aided wireless-powered heterogeneous CR networks (WPHetCRNs), where two types of secondary transmitters ...Show More

Optimal Time Allocation for Backscatter-Aided Relay Cooperative Transmission in Wireless-Powered Heterogeneous CRNs

Xiaoying Liu;Zhongwei Lin;Kechen Zheng;Xin-Wei Yao;Jia Liu

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 18 | Journal Article |

DRL-Based Offloading for Computation Delay Minimization in Wireless-Powered Multi-Access Edge Computing

Kechen Zheng;Guodong Jiang;Xiaoying Liu;Kaikai Chi;Xinwei Yao;Jiajia Liu

IEEE Transactions on Communications

Year: 2023 | Volume: 71, Issue: 3 | Journal Article |

Cited by: Papers (35)

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Wireless power transfer (WPT) and edge computing have been validated as effective ways to solve the energy-limited problem and computation-capacity-limited problem of wireless devices (WDs), respectively. This paper studies the wireless-powered multi-access edge computing (WP-MEC) network, where WDs conduct either local computing or task offloading for their individable computation tasks. We aim t...Show More

DRL-Based Offloading for Computation Delay Minimization in Wireless-Powered Multi-Access Edge Computing

Kechen Zheng;Guodong Jiang;Xiaoying Liu;Kaikai Chi;Xinwei Yao;Jiajia Liu

IEEE Transactions on Communications

Year: 2023 | Volume: 71, Issue: 3 | Journal Article |

Adaptive Diffusion Pairwise Fused Lasso LMS Algorithm Over Networks

Wei Huang;Haojie Shan;Jinshan Xu;Xinwei Yao

IEEE Transactions on Neural Networks and Learning Systems

Year: 2023 | Volume: 34, Issue: 9 | Journal Article |

Cited by: Papers (2)

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The topic of identification for sparse vector in a distributed way has triggered great interest in the area of adaptive filtering. Grouping components in the sparse vector has been validated to be an efficient way for enhancing identification performance for sparse parameter. The technique of pairwise fused lasso, which can promote similarity between each possible pair of nonnegligible components ...Show More

Adaptive Diffusion Pairwise Fused Lasso LMS Algorithm Over Networks

Wei Huang;Haojie Shan;Jinshan Xu;Xinwei Yao

IEEE Transactions on Neural Networks and Learning Systems

Year: 2023 | Volume: 34, Issue: 9 | Journal Article |

FGOR: Flow-Guided Opportunistic Routing for Intrabody Nanonetworks

Xin-Wei Yao;Yi-Wei Chen;Yi Wu;Kai Zhao;Josep M. Jornet

IEEE Internet of Things Journal

Year: 2022 | Volume: 9, Issue: 21 | Journal Article |

Cited by: Papers (11)

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The advancement of nano communication has opened the door for the development of intrabody medical application services. Flow-guided nano-communication networks have gained major attraction in recent years as an effective solution for intrabody sensing and actuation. This article builds a three-layer vertical network structure for intrabody nanonetworks, i.e., nano nodes, nano routers, and gateway...Show More

FGOR: Flow-Guided Opportunistic Routing for Intrabody Nanonetworks

Xin-Wei Yao;Yi-Wei Chen;Yi Wu;Kai Zhao;Josep M. Jornet

IEEE Internet of Things Journal

Year: 2022 | Volume: 9, Issue: 21 | Journal Article |

Joint optimization of latency and energy consumption for mobile edge computing based proximity detection in road networks

Tongyu Zhao;Yaqiong Liu;Guochu Shou;Xinwei Yao

China Communications

Year: 2022 | Volume: 19, Issue: 4 | Magazine Article |

Cited by: Papers (5)

In recent years, artificial intelligence and automotive industry have developed rapidly, and autonomous driving has gradually become the focus of the industry. In road networks, the problem of proximity detection refers to detecting whether two moving objects are close to each other or not in real time. However, the battery life and computing capability of mobile devices are limited in the actual ...Show More

Joint optimization of latency and energy consumption for mobile edge computing based proximity detection in road networks

Tongyu Zhao;Yaqiong Liu;Guochu Shou;Xinwei Yao

China Communications

Year: 2022 | Volume: 19, Issue: 4 | Magazine Article |

Multi-Hop Deflection Routing Algorithm Based on Reinforcement Learning for Energy-Harvesting Nanonetworks

Chao-Chao Wang;Xin-Wei Yao;Wan-Liang Wang;Josep Miquel Jornet

IEEE Transactions on Mobile Computing

Year: 2022 | Volume: 21, Issue: 1 | Journal Article |

Cited by: Papers (19)

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Nanonetworks are composed of interacting nano-nodes, whose size ranges from several hundred cubic nanometers to several cubic micrometers. The extremely constrained computational resources of nano-nodes, the fluctuations in their energy caused by energy harvesting processes, and their very limited transmission range at Terahertz (THz)-band frequencies (0.1-10 THz), make the design of routing proto...Show More

Multi-Hop Deflection Routing Algorithm Based on Reinforcement Learning for Energy-Harvesting Nanonetworks

Chao-Chao Wang;Xin-Wei Yao;Wan-Liang Wang;Josep Miquel Jornet

IEEE Transactions on Mobile Computing

Year: 2022 | Volume: 21, Issue: 1 | Journal Article |

Distributed estimation for sparse parameter based on fused-lasso technique

Wei Huang;Qiang Li;Chao Chen;Xinwei Yao

2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)

Year: 2019 | Conference Paper |

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Estimation for sparse parameter in adaptive networks has become a hot topic recently in the field of adaptive filtering. In some cases, the sparsity feature may also be found in the differences of successive entries of the true parameter, i.e. the non-zero elements may be assembled in one or more regions of the true parameter. In this paper, we propose the fused sparse diffusion LMS algorithm for ...Show More

Distributed estimation for sparse parameter based on fused-lasso technique

Wei Huang;Qiang Li;Chao Chen;Xinwei Yao

2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)

Year: 2019 | Conference Paper |

Multi-Beam On-Demand Power Allocation MAC Protocol for MIMO Terahertz Communication Networks

Xin-Wei Yao;Fang-Zhou Ni;Chao-Chao Wang

2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops)

Year: 2019 | Conference Paper |

Cited by: Papers (3)

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Terahertz (THz) communication is envisioned as one of the key technologies to achieve Terabit-per-second (Tbps) wireless data transmission speed. However, the communication distance in THz networks is constrained by the severe path loss in THz frequencies and the limited transmission power, which results in the network deployment issue. In recent years, researchers have shown a growing interest in...Show More

Multi-Beam On-Demand Power Allocation MAC Protocol for MIMO Terahertz Communication Networks

Xin-Wei Yao;Fang-Zhou Ni;Chao-Chao Wang

2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops)

Year: 2019 | Conference Paper |

Interference and Coverage Analysis for Indoor THz Communications with Beamforming Antennas

Xin-Wei Yao;Chao-Chao Wang;Chu-Feng Qi

2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops)

Year: 2019 | Conference Paper |

Cited by: Papers (4)

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A general framework to comprehensively investigate the interference and the coverage performance is proposed in this paper for indoor Terahertz (THz) communication with beamforming antenna. The interference of direct and scattering rays from users and Access Points (APs) are separately analyzed by using distance-dependent probability functions. Moreover, the users and APs are all equipped with bea...Show More

Interference and Coverage Analysis for Indoor THz Communications with Beamforming Antennas

Xin-Wei Yao;Chao-Chao Wang;Chu-Feng Qi

2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops)

Year: 2019 | Conference Paper |

ECP: A Probing-Based Error Control Strategy for THz-Based Nanonetworks With Energy Harvesting

Xin-Wei Yao;De-Bao Ma;Chong Han

Year: 2019 | Volume: 7 | Journal Article |

Cited by: Papers (7)

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Nanonetworks are comprised of the nano-sized communication devices that can perform simple tasks, such as computation, data storage, and actuation at the nanoscale. However, the error-prone wireless links as a result of severe path loss in the terahertz band (0.1-10.0 THz) and very limited energy storage capacity in nanodevices are challenging the communication in the nanonetworks. Therefore, effi...Show More

ECP: A Probing-Based Error Control Strategy for THz-Based Nanonetworks With Energy Harvesting

Xin-Wei Yao;De-Bao Ma;Chong Han

Year: 2019 | Volume: 7 | Journal Article |

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