Loading web-font TeX/Math/Italic
Carl Radens - IEEE Xplore Author Profile
Subscribe
ADVANCED SEARCH

Author details

< Back

Carl Radens

Also published under: C. Radens, C. J. Radens

Publications
32
Citations
713
Publications by Year
19872019
Co-Authors:
Show All Co-Authors (486)
Headshot silhouette indicating that no photo is available for this author

Carl Radens

Also published under: C. Radens, C. J. Radens

Affiliation

IBM

Publication Topics

Biography

Carl Radens is a Research Staff Member (RSM) with IBM focused on the R&D of cache memory used in computer chips, high-performance processors, AI, and hybrid cloud. He received the B.A. degree in physics from Oberlin College and the Ph.D. degree in electrical engineering from the University of Cincinnati, Cincinnati, OH, USA. Carl has coauthored more than 40 technical publications and holds over 340 issued U.S. patents. Dr. Radens served on the IEEE IEDM Integrated Circuits and Manufacturing Subcommittee and served as an Invited Panelist at the IEEE VLSI Technology and Circuits Symposium.
Publications
32
Citations
713
Publications by Year
19872019
Co-Authors:
Show All Co-Authors (486)
Author's Published Works

Showing 1-25 of 105 results

  • Sort

Filter Results

Show

Sort By

Results

XGate: Scaling LoRa Communications to Massive Logical Channels

Shiming Yu;Xianjin Xia;Ningning Hou;Yuanqing Zheng;Tao Gu

IEEE Transactions on Networking
Year: 2025 | Early Access Article |
LoRa is a promising technology that provides widespread low-power IoT connectivity. With its capabilities for multi-channel communication, orthogonal transmission, and spectrum sharing, LoRaWAN is poised to connect millions of IoT devices across thousands of logical channels. However, current LoRa gateways rely on hardwired Rx chains that cover less than 1% of these channels, restricting the poten...Show More

XGate: Scaling LoRa Communications to Massive Logical Channels

Shiming Yu;Xianjin Xia;Ningning Hou;Yuanqing Zheng;Tao Gu

Year: 2025 | Early Access Article |

Acoustic Sensing for Multi-User Heartbeat Monitoring Using Dualforming

Lei Wang;Tao Gu;Jingyu Li;Haipeng Dai;Chenren Xu;Daqing Zhang

IEEE Transactions on Mobile Computing
Year: 2025 | Early Access Article |
Acoustic sensing for heartbeat monitoring has emerged as a prevailing research topic in wireless sensing. However, existing acoustic sensing systems face two limitations: a restricted sensing range and operation limited to a single user, impeding large-scale deployment of its applications. In this paper, we present DF-Sense, a Dual Forming based multi-user acoustic Sensing system for heartbeat mon...Show More

Acoustic Sensing for Multi-User Heartbeat Monitoring Using Dualforming

Lei Wang;Tao Gu;Jingyu Li;Haipeng Dai;Chenren Xu;Daqing Zhang

Year: 2025 | Early Access Article |

Signal Accumulation and Parameter Estimation for Target Detection on Dual-Function Radar and Communication System

Wenshuai Ji;Yu Wang;Yanqun Tang;Fan Liu;Biao Tian;Tao Gu

IEEE Internet of Things Journal
Year: 2025 | Volume: 12, Issue: 11 | Journal Article |
Spectrum competition and hardware complexity inherent in communication and radar systems can be alleviated by a dual-function radar communication (DFRC) systems. However, enhancing detection capabilities for maneuvering or weak targets remains a significant challenge, as traditional radar signal accumulation algorithms are not directly applicable to DFRC systems. This article proposes a novel meth...Show More

Signal Accumulation and Parameter Estimation for Target Detection on Dual-Function Radar and Communication System

Wenshuai Ji;Yu Wang;Yanqun Tang;Fan Liu;Biao Tian;Tao Gu

Year: 2025 | Volume: 12, Issue: 11 | Journal Article |

FLrce: Resource-Efficient Federated Learning With Early-Stopping Strategy

Ziru Niu;Hai Dong;A. K. Qin;Tao Gu

IEEE Transactions on Mobile Computing
Year: 2024 | Volume: 23, Issue: 12 | Journal Article |
Federated Learning (FL) achieves great popularity in the Internet of Things (IoT) as a powerful interface to offer intelligent services to customers while maintaining data privacy. Under the orchestration of a server, edge devices (also called clients in FL) collaboratively train a global deep-learning model without sharing any local data. Nevertheless, the unequal training contributions among cli...Show More

FLrce: Resource-Efficient Federated Learning With Early-Stopping Strategy

Ziru Niu;Hai Dong;A. K. Qin;Tao Gu

Year: 2024 | Volume: 23, Issue: 12 | Journal Article |

Performance Bounds for Passive Sensing in Asynchronous ISAC Systems

Jingbo Zhao;Zhaoming Lu;J. Andrew Zhang;Weicai Li;Yifeng Xiong;Zijun Han;Xiangming Wen;Tao Gu

IEEE Transactions on Wireless Communications
Year: 2024 | Volume: 23, Issue: 11 | Journal Article |
Cited by: Papers (2)
Sensing in Integrated Sensing and Communications (ISAC) systems with clock asynchronism between the transmitter and receiver poses significant challenges. Understanding the fundamental limits of sensing performance in such setups, which remain largely unknown, is crucial. This paper investigates the sensing performance bounds in the presence of clock asynchronism. In both single-carrier and multi-...Show More

Performance Bounds for Passive Sensing in Asynchronous ISAC Systems

Jingbo Zhao;Zhaoming Lu;J. Andrew Zhang;Weicai Li;Yifeng Xiong;Zijun Han;Xiangming Wen;Tao Gu

Year: 2024 | Volume: 23, Issue: 11 | Journal Article |

A Wireless Signal Correlation Learning Framework for Accurate and Robust Multi-Modal Sensing

Xiulong Liu;Bojun Zhang;Sheng Chen;Xin Xie;Xinyu Tong;Tao Gu;Keqiu Li

IEEE Journal on Selected Areas in Communications
Year: 2024 | Volume: 42, Issue: 9 | Journal Article |
Cited by: Papers (1)
Wireless signal analytics in IoT systems can enable various promising wireless sensing applications such as localization, anomaly detection, and human activity recognition. As a matter of fact, there are significant correlations in terms of dimension, spatial and temporal aspects among wireless signals from multiple sensors. However, none of the wireless sensing research currently in use directly ...Show More

A Wireless Signal Correlation Learning Framework for Accurate and Robust Multi-Modal Sensing

Xiulong Liu;Bojun Zhang;Sheng Chen;Xin Xie;Xinyu Tong;Tao Gu;Keqiu Li

Year: 2024 | Volume: 42, Issue: 9 | Journal Article |

Exploring a Secure Device Pairing Using Human Body as a Conductor

Yao Wang;Tao Gu;Yu Zhang;Minjie Lyu;Hui Li

IEEE Transactions on Mobile Computing
Year: 2024 | Volume: 23, Issue: 12 | Journal Article |
Recent research has been exploring ways to streamline device pairing by introducing touch-to-access that minimizes user interaction. It generates pairing keys by extracting features from a shared information source to ascertain if two devices are being held by the same person. While these solutions focus on verifying the authenticity of the device, they do not consider the legitimacy and pairing i...Show More

Exploring a Secure Device Pairing Using Human Body as a Conductor

Yao Wang;Tao Gu;Yu Zhang;Minjie Lyu;Hui Li

Year: 2024 | Volume: 23, Issue: 12 | Journal Article |

HyLink: Toward High Throughput LPWANs With LoRa Compatible Communication

Xianjin Xia;Qianwu Chen;Ningning Hou;Yuanqing Zheng;Tao Gu

IEEE/ACM Transactions on Networking
Year: 2024 | Volume: 32, Issue: 4 | Journal Article |
Cited by: Papers (1)
This paper presents the design and implementation of HyLink which aims to fill the gap between limited link capacity of LoRa and the diverse bandwidth requirements of IoT systems. At the heart of HyLink is a novel technique named parallel Chirp Spread Spectrum modulation, which tunes the number of modulated symbols to adapt bit-rates according to channel conditions. Over strong link connections, H...Show More

HyLink: Toward High Throughput LPWANs With LoRa Compatible Communication

Xianjin Xia;Qianwu Chen;Ningning Hou;Yuanqing Zheng;Tao Gu

Year: 2024 | Volume: 32, Issue: 4 | Journal Article |

Toward Robust RFID Localization via Mobile Robot

Jiuwu Zhang;Xiulong Liu;Sheng Chen;Xinyu Tong;Zeyu Deng;Tao Gu;Keqiu Li

IEEE/ACM Transactions on Networking
Year: 2024 | Volume: 32, Issue: 4 | Journal Article |
A wide range of scenarios, such as warehousing, and smart manufacturing, have used RFID mobile robots for the localization of tagged objects. The state-of-the-art RFID-robot based localization works are based on the premise of stable speed. However, in reality this assumption can hardly be guaranteed because Commercial-Off-The-Shelf (COTS) robots typically have inconsistent moving speeds, and a sm...Show More

Toward Robust RFID Localization via Mobile Robot

Jiuwu Zhang;Xiulong Liu;Sheng Chen;Xinyu Tong;Zeyu Deng;Tao Gu;Keqiu Li

Year: 2024 | Volume: 32, Issue: 4 | Journal Article |

Power-Efficient Transmissions in LoRa Uplink Systems

Yi Guo;Jinping Niu;Xiangwei Zhou;Tao Gu;Yanyan Li;Dingyi Fang

IEEE Transactions on Vehicular Technology
Year: 2024 | Volume: 73, Issue: 8 | Journal Article |
Cited by: Papers (1)
LoRa has become a promising low-power wide-area network (LPWAN) technology for long-range communications, enabling various Internet of Things (IoT) applications. However, LoRa requires appropriate settings of transmission parameters on end devices (EDs) to achieve good performance for different IoT applications. We investigate in this paper power-efficient transmissions in LoRa uplink systems. To ...Show More

Power-Efficient Transmissions in LoRa Uplink Systems

Yi Guo;Jinping Niu;Xiangwei Zhou;Tao Gu;Yanyan Li;Dingyi Fang

Year: 2024 | Volume: 73, Issue: 8 | Journal Article |

Fine-Grained Recognition of Manipulation Activities on Objects via Multi-Modal Sensing

Xiulong Liu;Bojun Zhang;Lizhang Wang;Sheng Chen;Xin Xie;Xinyu Tong;Tao Gu;Keqiu Li

IEEE Transactions on Mobile Computing
Year: 2024 | Volume: 23, Issue: 10 | Journal Article |
Cited by: Papers (2)
Fine-grained recognition of human manipulation activities on objects is crucial in the era of human-computer-object integration. However, there is a lack of solutions for simultaneous recognition of human identity, manipulation activities (including drawing and rotation), and manipulated objects. Therefore, we propose an RF-Camera system that combines RFID and computer vision techniques to address...Show More

Fine-Grained Recognition of Manipulation Activities on Objects via Multi-Modal Sensing

Xiulong Liu;Bojun Zhang;Lizhang Wang;Sheng Chen;Xin Xie;Xinyu Tong;Tao Gu;Keqiu Li

Year: 2024 | Volume: 23, Issue: 10 | Journal Article |

Simultaneous Authentication of Multiple Users Using a Single mmWave Radar

Yao Wang;Tao Gu;Haibin Zhang

IEEE Internet of Things Journal
Year: 2024 | Volume: 11, Issue: 10 | Journal Article |
Cited by: Papers (2)
User authentication is crucial for maintaining privacy. However, most existing methods are designed for single-user scenarios and may not be efficient for multiple users. To address this issue, we propose M-Auth, a {M} ultiuser Auth entication system that utilizes a commercial mmWave radar to detect the unique breathing pattern. We exploit the phenomenon that chest movements due to breathing ca...Show More

Simultaneous Authentication of Multiple Users Using a Single mmWave Radar

Yao Wang;Tao Gu;Haibin Zhang

Year: 2024 | Volume: 11, Issue: 10 | Journal Article |

OmniResMonitor: Omnimonitoring of Human Respiration using Acoustic Multipath Reflection

Tianben Wang;Zhishen Wang;Xiantao Liu;Wenbo Liu;Leye Wang;Yuanqing Zheng;Jin Hu;Tao Gu;Daqing Zhang

IEEE Transactions on Mobile Computing
Year: 2024 | Volume: 23, Issue: 5 | Journal Article |
Cited by: Papers (1)
Contactless respiration monitoring using wireless signals has drawn much attention in recent years. Many approaches have been proposed, however, they may not work when there is a lack of signals directly reflected from target's chest, e.g., a target faces away from the transceiver or a target is blocked by furniture. In this paper, we design and implement a novel omnimonitoring system for human re...Show More

OmniResMonitor: Omnimonitoring of Human Respiration using Acoustic Multipath Reflection

Tianben Wang;Zhishen Wang;Xiantao Liu;Wenbo Liu;Leye Wang;Yuanqing Zheng;Jin Hu;Tao Gu;Daqing Zhang

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

MultiResp: Robust Respiration Monitoring for Multiple Users Using Acoustic Signal

Tianben Wang;Zhangben Li;Xiantao Liu;Tao Gu;HongHao Yan;Jing Lv;Jin Hu;Daqing Zhang

IEEE Transactions on Mobile Computing
Year: 2024 | Volume: 23, Issue: 5 | Journal Article |
Cited by: Papers (5)
In recent years, we have seen efforts made to monitor respiration for multiple users. Existing approaches capture chest movement relying on signals directly reflected from chest or separate breath waves based on breath rate difference between subjects. However, several limitations exist: 1) they may fail when subjects face away from the transceiver or are blocked by obstacles or other subjects; 2)...Show More

MultiResp: Robust Respiration Monitoring for Multiple Users Using Acoustic Signal

Tianben Wang;Zhangben Li;Xiantao Liu;Tao Gu;HongHao Yan;Jing Lv;Jin Hu;Daqing Zhang

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

Industrial Vision: Rectifying Millimeter-Level Edge Deviation in Industrial Internet of Things With Camera-Based Edge Device

Lei Xie;Zihao Chu;Yi Li;Tao Gu;Yanling Bu;Chuyu Wang;Sanglu Lu

IEEE Transactions on Mobile Computing
Year: 2024 | Volume: 23, Issue: 2 | Journal Article |
Cited by: Papers (1)
Nowadays, to realize the intelligent manufacturing in Industrial Internet of Things (IIoT) scenarios, novel approaches in computer vision are in great demand to tackle the new challenges in IIoT environment. These approaches, which we call Industrial Vision, are expected to offer customized solutions for intelligent manufacturing in an accurate, time efficient and robust manner. In this paper, we ...Show More

Industrial Vision: Rectifying Millimeter-Level Edge Deviation in Industrial Internet of Things With Camera-Based Edge Device

Lei Xie;Zihao Chu;Yi Li;Tao Gu;Yanling Bu;Chuyu Wang;Sanglu Lu

Year: 2024 | Volume: 23, Issue: 2 | Journal Article |

Mobility-Aware and Privacy-Protecting QoS Optimization in Mobile Edge Networks

Huiying Jin;Pengcheng Zhang;Hai Dong;Xinmiao Wei;Yuelong Zhu;Tao Gu

IEEE Transactions on Mobile Computing
Year: 2024 | Volume: 23, Issue: 2 | Journal Article |
Cited by: Papers (7)
With the rapid development of 5G technologies, the demand of quality of service (QoS) from edge users, including high bandwidth and low latency, has increased dramatically. QoS within a mobile edge network is highly dependent on the allocation of edge users. However, the complexity of user movement greatly challenges edge user allocation, leading to privacy leakage. In addition, updating massive d...Show More

Mobility-Aware and Privacy-Protecting QoS Optimization in Mobile Edge Networks

Huiying Jin;Pengcheng Zhang;Hai Dong;Xinmiao Wei;Yuelong Zhu;Tao Gu

Year: 2024 | Volume: 23, Issue: 2 | Journal Article |

ChirpKey: A Chirp-level Information-based Key Generation Scheme for LoRa Networks via Perturbed Compressed Sensing

Huanqi Yang;Zehua Sun;Hongbo Liu;Xianjin Xia;Yu Zhang;Tao Gu;Gerhard Hancke;Weitao Xu

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications
Year: 2023 | Conference Paper |
Cited by: Papers (9)
Physical-layer key generation is promising in establishing a pair of cryptographic keys for emerging LoRa networks. However, existing key generation systems may perform poorly since the channel reciprocity is critically impaired due to low data rate and long range in LoRa networks. To bridge this gap, this paper proposes a novel key generation system for LoRa networks, named ChirpKey. We reveal th...Show More

ChirpKey: A Chirp-level Information-based Key Generation Scheme for LoRa Networks via Perturbed Compressed Sensing

Huanqi Yang;Zehua Sun;Hongbo Liu;Xianjin Xia;Yu Zhang;Tao Gu;Gerhard Hancke;Weitao Xu

Year: 2023 | Conference Paper |

Energy-Efficient Task Offloading in RIS-Aided HetNets With Wireless Backhaul

Li Zhang;Jinping Niu;Yiyao Wang;Gaojie Chen;Tao Gu;Yanyan Li

IEEE Communications Letters
Year: 2023 | Volume: 27, Issue: 9 | Journal Article |
This letter exploits reconfigurable intelligent surface (RIS) in the heterogeneous networks (HetNets) with wireless backhaul to improve the task computing energy efficiency. To minimize the overall energy consumption of all users, we formulate the problem as a combinatorial optimization problem by jointly optimizing the transmit power of users and small cell base stations, computational capacity o...Show More

Energy-Efficient Task Offloading in RIS-Aided HetNets With Wireless Backhaul

Li Zhang;Jinping Niu;Yiyao Wang;Gaojie Chen;Tao Gu;Yanyan Li

Year: 2023 | Volume: 27, Issue: 9 | Journal Article |

Demand Response in NOMA-Based Mobile Edge Computing: A Two-Phase Game-Theoretical Approach

Guangming Cui;Qiang He;Xiaoyu Xia;Feifei Chen;Tao Gu;Hai Jin;Yun Yang

IEEE Transactions on Mobile Computing
Year: 2023 | Volume: 22, Issue: 3 | Journal Article |
Cited by: Papers (26)
Mobile edge computing (MEC), as a key technology that facilitates 5G networks, provides a new and prospective mobile computing paradigm that allows the deployment of edge servers at base stations geographically close to mobile users to reduce their end-to-end network latency. Similar to cloud servers, edge servers running 24/7 in an MEC system consume a large amount of energy, contribute a signifi...Show More

Demand Response in NOMA-Based Mobile Edge Computing: A Two-Phase Game-Theoretical Approach

Guangming Cui;Qiang He;Xiaoyu Xia;Feifei Chen;Tao Gu;Hai Jin;Yun Yang

Year: 2023 | Volume: 22, Issue: 3 | Journal Article |

Your Breath Doesn't Lie: Multi-user Authentication by Sensing Respiration Using mmWave Radar

Yao Wang;Tao Gu;Tom H. Luan;Yong Yu

2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)
Year: 2022 | Conference Paper |
Cited by: Papers (15)
User authentication is critical to privacy preservation. Most of the existing works focus on single-user authentication, which may not work efficiently and practically in multi-user scenarios. To this end, we present a Multi-user Authentication system (M-Auth) that employs a single COTS mmWave radar to capture the user's unique breathing pattern. It exploits the phenomenon that radio frequency (RF...Show More

Your Breath Doesn't Lie: Multi-user Authentication by Sensing Respiration Using mmWave Radar

Yao Wang;Tao Gu;Tom H. Luan;Yong Yu

Year: 2022 | Conference Paper |

HeartPrint: Exploring a Heartbeat-Based Multiuser Authentication With Single mmWave Radar

Yao Wang;Tao Gu;Tom H. Luan;Minjie Lyu;Yue Li

IEEE Internet of Things Journal
Year: 2022 | Volume: 9, Issue: 24 | Journal Article |
Cited by: Papers (22)
Continuous authentication is crucial for protecting user’s privacy throughout their login session. Existing studies employ wireless sensing technologies to provide device-free and unobtrusive authentication; the user’s behavior is continually assessed without their direct involvement until it deviates from their normal pattern. However, these works primarily concentrate on single-user authenticati...Show More

HeartPrint: Exploring a Heartbeat-Based Multiuser Authentication With Single mmWave Radar

Yao Wang;Tao Gu;Tom H. Luan;Minjie Lyu;Yue Li

Year: 2022 | Volume: 9, Issue: 24 | Journal Article |

Edge-Eye: Rectifying Millimeter-level Edge Deviation in Manufacturing using Camera-enabled IoT Edge Device

Zihao Chu;Lei Xie;Tao Gu;Yanling Bu;Chuyu Wang;Sanglu Lu

2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Irradiated Cross-linked Polyethylene Foam (IXPE) has been one of the most commonly used materials in industry. During the production process of IXPE sheets, their edges need keep aligned strictly, otherwise, they could quickly get out of the border of the rolling plate and cause the huge economic loss. In this paper, we propose a camera-enabled approach, called Edge-Eye, to rectify the edge deviat...Show More

Edge-Eye: Rectifying Millimeter-level Edge Deviation in Manufacturing using Camera-enabled IoT Edge Device

Zihao Chu;Lei Xie;Tao Gu;Yanling Bu;Chuyu Wang;Sanglu Lu

Year: 2022 | Conference Paper |

Separating Voices from Multiple Sound Sources using 2D Microphone Array

Xinran Lu;Lei Xie;Fang Wang;Tao Gu;Chuyu Wang;Wei Wang;Sanglu Lu

IEEE INFOCOM 2022 - IEEE Conference on Computer Communications
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Voice assistant has been widely used for human-computer interaction and automatic meeting minutes. However, for multiple sound sources, the performance of speech recognition in voice assistant decreases dramatically. Therefore, it is crucial to separate multiple voices efficiently for an effective voice assistant application in multi-user scenarios. In this paper, we present a novel voice separati...Show More

Separating Voices from Multiple Sound Sources using 2D Microphone Array

Xinran Lu;Lei Xie;Fang Wang;Tao Gu;Chuyu Wang;Wei Wang;Sanglu Lu

Year: 2022 | Conference Paper |

MDLdroid: A ChainSGD-Reduce Approach to Mobile Deep Learning for Personal Mobile Sensing

Yu Zhang;Tao Gu;Xi Zhang

IEEE/ACM Transactions on Networking
Year: 2022 | Volume: 30, Issue: 1 | Journal Article |
Cited by: Papers (3)
Personal mobile sensing is fast permeating our daily lives to enable activity monitoring, healthcare and rehabilitation. Combined with deep learning, these applications have achieved significant success in recent years. Different from conventional cloud-based paradigms, running deep learning on devices offers several advantages including data privacy preservation and low-latency response for both ...Show More

MDLdroid: A ChainSGD-Reduce Approach to Mobile Deep Learning for Personal Mobile Sensing

Yu Zhang;Tao Gu;Xi Zhang

Year: 2022 | Volume: 30, Issue: 1 | Journal Article |

Smart Diagnosis: Deep Learning Boosted Driver Inattention Detection and Abnormal Driving Prediction

Landu Jiang;Wen Xie;Dian Zhang;Tao Gu

IEEE Internet of Things Journal
Year: 2022 | Volume: 9, Issue: 6 | Journal Article |
Cited by: Papers (20)
Inattentive driving is one of the high-risk factors that causes a large number of traffic accidents every year. In this article, we aim to detect driver inattention leveraging on large-scale vehicle trajectory data while at the same time explore how do these inattentive events affect driver behaviors and what following reactions they may cause, especially, for commercial vehicles. Specifically, th...Show More

Smart Diagnosis: Deep Learning Boosted Driver Inattention Detection and Abnormal Driving Prediction

Landu Jiang;Wen Xie;Dian Zhang;Tao Gu

Year: 2022 | Volume: 9, Issue: 6 | Journal Article |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.