Test Whats new message.
Scheduled Maintenance on Monday 1/13/2025
Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.
Showing 1-25 of 32 results
- Sort
Filter Results
Show
Sort By
Results
A Multiple Wi-Fi Sensors Assisted Human Activity Recognition Scheme for Smart Home
With the development of wireless communication technology, wireless signals have been expanded from mobile communication to behavioral sensing. In particular, human activity recognition (HAR) relying on Wi-Fi signals has attracted increasing attention and demonstrated its great potential in the field of smart healthcare. However, most HAR solutions fail to capture the full scope of the relationshi...Show More
Light Convolutional Neural Network for Digital Predistortion of Radio Frequency Power Amplifiers
Predistortion models of radio frequency (RF) power amplifier (PA), such as the generalized memory polynomial (GMP) model and artificial neural networks (ANNs) model, suffer from limited predistortion precision and high complexity. In this letter, we propose an enhanced digital predistortion (DPD) model based on a light convolutional neural network (CNN) with augmented real-valued and cross-memoriz...Show More
Multi-AP CSI Fusion and Features Optimization-Based Behavioral Sensing on WiFi Platform
Jianyang Ding;Yong Wang;Jing Zhang;Haiming Chen;Hongyan Si;Jie Liu
The prevalence of WiFi infrastructures has enabled the advancement of a wide range of WiFi-based intelligent applications. Behavioral sensing, as an increasingly popular example, is attracting growing research interest in developing a device-free, accurate, and privacy-friendly interaction. Recent advances in behavioral research have shown great promise, but most of existing systems fail to captur...Show More
Multi-Antenna Information Fusion-Based Indoor Localization Using Signals Reflections
With the ubiquitous of WiFi infrastructure, wireless signals-based indoor localization is attracting intensive attentions and fostered a range of intelligent applications. However, most of existing schemes fail to capture the full scope of the relationship between WiFi signals and physical locations. To tackle this issue, we present a framework for device-free localization by estimating the channe...Show More
WiFi Fingerprint-Based Multi-user Localization for Smart Home by WiFi Sensing
Jianyang Ding;Yong Wang;Shaozhong Fu;Haiming Chen;Wendong Xie;Yunsong Liu
2022 IEEE 22nd International Conference on Communication Technology (ICCT)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Device-free and passive indoor localization based on WiFi channel state information (CSI) has attracted a great deal of research interest and yielded a broad range of related applications. However, most of existing approaches are influenced heavily by random noises, and also they fail in the presence of multiple users in the same area. In this paper, we present an accurate indoor localization sche...Show More
Multimodal Fusion-GMM based Gesture Recognition for Smart Home by WiFi Sensing
Jianyang Ding;Yong Wang;Hongyan Si;Jiannan Ma;Jingwen He;Kai Liang;Shaozhong Fu
2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
Year: 2022 | Conference Paper |
Cited by: Papers (5)
With the thriving development of communication systems and the ubiquity of commodity WiFi devices, wireless intelligent sensing has attracted increasingly attention owing to its importance in Human-Computer Interaction (HCI) where hand gesture recognition has been widely studied these years. However, most of gesture recognition approaches have a limited performance owing to the background noises. ...Show More
Multiview Features Fusion and AdaBoost Based Indoor Localization on WiFi Platform
Jianyang Ding;Yong Wang;Shaozhong Fu;Hongyan Si;Jing Zhang;Shang Gao
With the increasing demand for location-based service (LBS), WiFi-based localization has attracted considerable attentions due to the wide deployment and low cost of WiFi devices. However, most of existing approaches need to work within line-of-sight (LoS) range or require users to take dedicated devices. Thus, a device-free and passive indoor localization scheme is still desired. In this paper, a...Show More
Three-Dimensional Indoor Localization and Tracking for Mobile Target Based on WiFi Sensing
IEEE Internet of Things Journal
Cited by: Papers (26)
With the prevalence of commodity WiFi devices and development of the Internet of Things (IoT), the usage of WiFi has been extended from communication to context aware. Based on this, indoor localization has attracted increasing attention in the academic community, without the need for additional sensors and any active engagement from the users. However, the localization performance is vulnerable t...Show More
With the ubiquity of commodity WiFi devices and the rapid development of Internet of Things (IoT), there are increasingly intelligent sensing applications emerging by utilizing fine-grained channel state information (CSI) from WiFi signals, which can realize contactless human-computer interaction (HCI) for smart home. However, most of CSI-based activity recognition approaches are vulnerable to ran...Show More
A WiFi-Based Smart Home Fall Detection System Using Recurrent Neural Network
Falls among the elderly living on their own have been regarded as a major public health worry that can even lead to death. Fall detection system (FDS) that alerts caregivers or family members can potentially save lives of the elderly. However, conventional FDS involves wearable sensors and specialized hardware installations. This article presents a passive device-free FDS based on commodity WiFi f...Show More
Human identity identification based on channel state information (CSI) using commercial WiFi devices has drawn increasingly attention, and it can be used in many applications such as smart home, intrusion detection, building monitoring, activity recognition, etc. However, most of the existing identity identification approaches are sensitive to the influence of random noise derived from indoor envi...Show More
FiPR: A Fine-grained Human Posture Recognition
2019 IEEE 19th International Conference on Communication Technology (ICCT)
Year: 2019 | Conference Paper |
Various pioneering human posture recognition techniques based on Channel State Information (CSI) of WiFi devices have been proposed. The main issue of existing techniques, however, lies in such recognition methods are extremely sensitive to the impacts of random noise derived from indoor environments. In this paper, we present a fine-grained human posture recognition (FiPR) scheme to overcome this...Show More
Novel ACE Scheme for PAPR Reduction of High Broadband OFDM Systems
2019 IEEE 19th International Conference on Communication Technology (ICCT)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
The high broadband Orthogonal Frequency Division Multiplexing (OFDM) system is characterized by high-order constellation and a large of sub-carriers. In order to overcome the major drawback of high Peak-to-Average Power Ratio (PAPR) of OFDM signal, traditional Active Constellation Extension (ACE) techniques maybe pay more price, such as increasing the iteration numbers, thus, costing the more syst...Show More
Human activity recognition based on channel state information (CSI) using commercial WiFi devices plays an increasingly important role in many applications, such as smart home and interactive games. In this paper, we propose a WiFi CSI based human activity recognition approach using deep recurrent neural network (HARNN). HARNN mainly exploits four key techniques to recognize different human activi...Show More
In this paper, an efficient Active Constellation Extension (ACE) based on Extension Projection Onto the Convex Sets (EPOCS-ACE) scheme is proposed for reducing Peak-to-Average Power Ratio (PAPR) of Orthogonal Frequency Division Multiplexing (OFDM) signals especially with a large number of sub-carriers and high-order constellation. Utilizing the specially designed iterative procedure, considerable ...Show More
Fog-Enabled WLANs for Indoor Positioning
2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
This paper presents fog-enabled WLANs for indoor positioning, which can meet its requirements of low latency and high precision. Firstly, we present software-defined and virtualized WLANs, which could be divided into four layers, i.e., application layer, control layer, infrastructure layer and terminal layer. Secondly, we introduce fog computing into software-defined and virtualized WLANs to build...Show More
Joint resource allocation and coordinated computation offloading for fog radio access networks
China Communications
Cited by: Papers (17)
The cloud radio access network (C-RAN) and the fog computing have been recently proposed to tackle the dramatically increasing traffic demands and to provide better quality of service (QoS) to user equipment (UE). Considering the better computation capability of the cloud RAN (10 times larger than that of the fog RAN) and the lower transmission delay of the fog computing, we propose a joint resour...Show More
In order to maximize system energy efficiency (EE) under user quality of service (QoS) restraints in Long Term Evolution-Advanced (LTE-A) networks, a constrained joint resource optimization allocation scheme is presented, which is NP-hard. Hence, we divide it into three sub-problems to reduce computation complexity, i.e., the resource block (RB) allocation, the power distribution, and the modulati...Show More
On Stochastic Analysis of Greedy Routing in Vehicular Networks
Lina Zhu;Changle Li;Yong Wang;Zhe Luo;Zhe Liu;Bingbing Li;Xinbing Wang
Even the greedy routing is widely used in wireless networks, its theoretical study is still limited in vehicle environments. In this paper, we theoretically analyze the performance of the greedy routing under three typical vehicle scenarios, i.e., the single-lane road, the multilane road, and the multilevel road. We first propose the analytical model by analyzing characteristics of traffic environ...Show More
Iterative companding transform and filtering for reducing PAPR of OFDM signal
In this paper, an efficient Iterative Companding Transform and Filtering (ICTF) technique is proposed for reducing the Peak-to-Average Power Ratio (PAPR) of Orthogonal Frequency Division Multiplexing (OFDM) signal. By means of a specially designed iterative procedure, ICTF is able to obtain both an improved Bit Error Rate (BER) and minimized Out-of-Band Interference (OBI) while reducing the PAPR s...Show More
A Fuse-and-Forward Protocol for Two-Way Relaying Networks With Relay Having Its Own Broadcasting Information
IEEE Communications Letters
Cited by: Papers (5)
A fuse-and-forward (FF) relaying protocol is proposed and analyzed for two-way relaying networks where the relay node has its own information to broadcast. In our FF protocol, the relay node will firstly process the received signals to obtain a new signal version by fusing with its own information, then broadcast to all the source nodes. We assume that multiple antennas are deployed to the relay n...Show More
Variable step-size MLMS algorithm for digital predistortion in wideband OFDM systems
As one of the most promising linearization techniques, adaptive Digital Predistortion (PD) has been widely utilized in modern wireless communication systems for improving the efficiency of Power Amplifier (PA). In view of the non-stationary signal environment for the wideband PAs, an efficient indirect learning adaptive PD is proposed in the paper based on the Memory Polynomial Model (MPM). The co...Show More
An Energy-Efficient and Swarm Intelligence-Based Routing Protocol for Next-Generation Sensor Networks
IEEE Intelligent Systems
Cited by: Papers (14)
After providing a brief overview of routing protocols for next-generation sensor networks (NGSNs), the authors propose Bee-Sensor-C, an energy-efficient, swarm intelligence-based, and scalable multipath routing protocol that integrates dynamic clustering, multipath routing, and bee-inspired routing to meet the performance requirements of NGSNs. A performance evaluation is also provided.Show More
Novel adaptive digital predistortion based on the hybrid indirect learning algorithm
2014 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting
Year: 2014 | Conference Paper |
Adaptive digital predistortion (DPD) is one of the most promising linearization technique, which leads to more efficient and cost-effective high power amplifier (HPA). In this paper, we propose a novel adaptive DPD based on the hybrid indirect learning (HIL) algorithm, which can not only remedy the effect caused by measurement noise in the feedback loop effectively, but also improve the convergenc...Show More
Nonlinear Companding Transform for Reduction of Peak-to-Average Power Ratio in OFDM Systems
High peak-to-average power ratio (PAPR) of the transmitted signal is one of the limitations to employing orthogonal frequency division multiplexing (OFDM) system. In this paper, we propose a new nonlinear companding algorithm that transforms the OFDM signals into the desirable statistics form defined by a linear piecewise function. By introducing the variable slopes and an inflexion point in the t...Show More
IEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
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.