• Antenna and propagation considerations for amateur UAV monitoring

      Abolhasan M; Zhao, Nan; Yang, Xiaodong; Ren, Aifeng; Zhang, Zhiya; Zhao, Wei; Hu, Fangming; Ur-Rehman, Masood; Abbas, Haider; Xidian University; et al. (Institute of Electrical and Electronics Engineers Inc., 2018-05-18)
      The broad application spectrum of unmanned aerial vehicles is making them one of the most promising technologies of Internet of Things era. Proactive prevention for public safety threats is one of the key areas with vast potential of surveillance and monitoring drones. Antennas play a vital role in such applications to establish reliable communication in these scenarios. This paper considers line-of-sight and non-line-of-sight threat scenarios with the perspective of antennas and electromagnetic wave propagation.
    • Biometric behavior authentication exploiting propagation characteristics of wireless channel

      Zhao, Nan; Ren, Aifeng; Ur-Rehman, Masood; Zhang, Zhiya; Yang, Xiaodong; Hu, Fangming; Xidian University; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2016-08-24)
      Massive expansion of wireless body area networks (WBANs) in the field of health monitoring applications has given rise to the generation of huge amount of biomedical data. Ensuring privacy and security of this very personal data serves as a major hurdle in the development of these systems. An effective and energy friendly authentication algorithm is, therefore, a necessary requirement for current WBANs. Conventional authentication algorithms are often implemented on higher levels of the Open System Interconnection model and require advanced software or major hardware upgradation. This paper investigates the implementation of a physical layer security algorithm as an alternative. The algorithm is based on the behavior fingerprint developed using the wireless channel characteristics. The usability of the algorithm is established through experimental results, which show that this authentication method is not only effective, but also very suitable for the energy-, resource-, and interface-limited WBAN medical applications.
    • Detection of essential tremor at the S-band.

      Yang, Xiaodong; Shah, Syed Aziz; Ren, Aifeng; Fan, Dou; Zhao, Nan; Cao, Dongjian; Hu, Fangming; Ur-Rehman, Masood; Wang, Weigang; von Deneen, Karen M.; et al. (Institute of Electrical and Electronics Engineers (IEEE): OAJ / IEEE, 2018-01-24)
      Essential tremor (ET) is a neurological disorder characterized by rhythmic, involuntary shaking of a part or parts of the body. The most common tremor is seen in the hands/arms and fingers. This paper presents an evaluation of ETs monitoring based on finger-to-nose test measurement as captured by small wireless devices working in shortwave or [Formula: see text]-band frequency range. The acquired signals in terms of amplitude and phase information are used to detect a tremor in the hands. Linearly transforming raw phase data acquired in the [Formula: see text]-band were carried out for calibrating the phase information and to improve accuracy. The data samples are used for classification using support vector machine algorithm. This model is used to differentiate the tremor and nontremor data efficiently based on secondary features that characterize ET. The accuracy of our measurements maintains linearity, and more than 90% accuracy rate is achieved between the feature set and data samples.
    • Internet of things: architecture, technology and key problems in implementation

      Yue, Zhijia; Sun, Wanrong; Li, Peijia; Ur-Rehman, Masood; Yang, Xiaodong; Xidian University; University of Bedfordshire (IEEE, 2016-02-18)
      Internet of Things is the convergence of computing, Internet and mobile communication networks resulted by the development of third wave of information technology industry. This paper presents a study by first introducing the basic concepts and features of Internet of Things (IoT) followed by the introduction of the ubiquitous sensor networks (USN) architecture. A simplified model of the USN is also discussed. Furthermore, the key problems in the implementation of IoT are also discussed using the system model. Finally, two practical system model are designed on sensing layer based on ARM9 acquisition and transmission system.
    • Laplacian group sparse modeling of human actions

      Zhang, Xiangrong; Yang, Hao; Jiao, L.C.; Yang, Yang; Dong, Feng; Xidian University; University of Bedfordshire (Elsevier Ltd, 2014-02-20)
      Recently, many local-feature based methods have been proposed for feature learning to obtain a better high-level representation of human behavior. Most of the previous research ignores the structural information existing among local features in the same video sequences, while it is an important clue to distinguish ambiguous actions. To address this issue, we propose a Laplacian group sparse coding for human behavior representation. Unlike traditional methods such as sparse coding, our approach prefers to encode a group of relevant features simultaneously and meanwhile allow as less atoms as possible to participate in the approximation so that video-level sparsity is guaranteed. By incorporating Laplacian regularization the method is capable to ensure the similar approximation of closely related local features and the structural information is successfully preserved. Thus, a compact but discriminative human behavior representation is achieved. Besides, the objective of our model is solved with a closed-form solution, which reduces the computational cost significantly. Promising results on several popular benchmark datasets prove the efficiency and effectiveness of our approach. © 2014 Elsevier Ltd.
    • A low profile antenna for millimeter-wave body-centric applications

      Ur-Rehman, Masood; Malik, Nabeel A.; Yang, Xiaodong; Abbasi, Qammer Hussain; Zhang, Zhiya; Zhao, Nan; University of Bedfordshire; Xidian University; University of Glasgow (Institute of Electrical and Electronics Engineers Inc., 2017-05-03)
      Millimeter-Wave (mm-Wave) frequencies are a front runner contender for the next generation body-centric wireless communications. In this paper, the design of a very low-profile antenna is presented for body-centric applications operating in the mm-Wave frequency band centered at 60 GHz. The antenna has an overall size of 14 × 10.5 × 1.15 mm3 and is printed on a flexible printed circuit board. The performance of the antenna is evaluated in off-body, on-body, and body-to-body communication scenarios using a realistic numerical phantom and verified through measurements. The antenna has a bandwidth of 9.8 GHz and offers a gain of 10.6 dBi in off-body (free space) configuration, while 12.1 dBi in on-body configuration. It also achieves an efficiency of 74% in off-body and 63% in on-body scenario. The small and flexible structure of the antenna along with excellent impedance matching, broad bandwidth, high gain, and good efficiency makes it a suitable candidate to attain simultaneous data transmission/reception at mm-Wave frequencies for the 5G body-centric applications.
    • Monitoring of patients suffering from REM sleep behavior disorder

      Yang, Xiaodong; Shah, Syed Aziz; Ren, Aifeng; Zhao, Nan; Zhao, Jianxun; Hu, Fangming; Zhang, Zhiya; Zhao, Wei; Ur-Rehman, Masood; Alomainy, Akram; et al. (Institute of Electrical and Electronics Engineers Inc., 2018-04-16)
      Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia that involves involuntary, unwanted, and random movements of a dreaming patient. Typically, these dreams contain violent activities. There is a high likelihood of the patient being injured or hurting his bed-partner as a result of these enactments. Continuous monitoring of sleeping RBD patients can prevent these harmful events through timely intervention. This paper presents a novel method for continuous observation of RBD patients exploiting fine-grained amplitude and phase information of the wireless channel response. The variations in the wireless channel response as a result of different patient movements are assessed and used to identify RBD episodes. The data obtained are classified using a support vector machine and deliver an accuracy level of more than 90%. To the best of authors' knowledge, this is a first attempt at using radio frequency signals to sense RBD in real time.
    • Nano-ferrite near-field microwave imaging for in-body applications

      Abbasi, Qammer Hussain; Ren, Aifeng; Qing, Maojie; Zhao, Nan; Wang, Mingming; Gao, Ge; Yang, Xiaodong; Zhang, Zhiya; Hu, Fangming; Ur-Rehman, Masood; et al. (Institute of Electrical and Electronics Engineers, 2018-06-04)
      In recent years, nanotechnology has become indispensable in our lives, especially in the medical field. The key to nanotechnology is the perfect combination of molecular imaging and nanoscale probes. In this paper, we used iron oxide nanoparticles as a nanoprobe because it is widely used in clinical MRI and other molecular imaging techniques. We built our own experimental environment and used absorbing materials during the whole experiment to avoid electromagnetic interference with the surroundings. Moreover, we repeated the experiment many times to exclude the influence of contingency. Hence, the experimental data we obtained were relatively precise and persuasive. Finally, the results demonstrated that the iron oxide nanoparticles were appropriate for use as contrast agents in biological imaging.
    • Patterns-of-life aided authentication

      Zhao, Nan; Ren, Aifeng; Zhang, Zhiya; Zhu, Tianqiao; Ur-Rehman, Masood; Yang, Xiaodong; Hu, Fangming; Xidian University; University of Bedfordshire (MDPI, 2016-09-23)
      Wireless Body Area Network (WBAN) applications have grown immensely in the past few years. However, security and privacy of the user are two major obstacles in their development. The complex and very sensitive nature of the body-mounted sensors means the traditional network layer security arrangements are not sufficient to employ their full potential, and novel solutions are necessary. In contrast, security methods based on physical layers tend to be more suitable and have simple requirements. The problem of initial trust needs to be addressed as a prelude to the physical layer security key arrangement. This paper proposes a patterns-of-life aided authentication model to solve this issue. The model employs the wireless channel fingerprint created by the user’s behavior characterization. The performance of the proposed model is established through experimental measurements at 2.45 GHz. Experimental results show that high correlation values of 0.852 to 0.959 with the habitual action of the user in different scenarios can be used for auxiliary identity authentication, which is a scalable result for future studies.
    • Printed quadrifilar helix antenna with enhanced bandwidth

      Zhang, Zhiya; Yang, Long; Zuo, Shaoli; Ur-Rehman, Masood; Fu, Guang; Zhou, Chuangzhu; Xidian University; University of Bedfordshire; ZTE Corporation R&D Center (Xi'an) (IEEE, 2017-04-24)
      A circular polarised printed quadrifilar helix antenna with enhanced bandwidth is proposed in this study. The helix antenna offers a very compact size and comprises of four arms with varying width, four open stubs, a feeding network and a metal ground plane. The different widths of the helix arms are employed to improve the impedance bandwidth while their varying pitches generate a cardioid radiation pattern. The antenna exhibits a voltage standing wave ratio ≤ 2 in the frequency range of 1.43-1.63 GHz offering impedance bandwidth of 12%. Good radiation characteristics with high gain, a wide 3 dB axial ratio beamwidth of 180° along with small size makes this antenna an excellent candidate for satellite communications and navigation systems.
    • RSSI indoor localization through a Bayesian strategy

      Zhou, Fu; Lin, Kaixian; Ren, Aifeng; Cao, Dongjian; Zhang, Zhiya; Ur-Rehman, Masood; Yang, Xiaodong; Alomainy, Akram; Xidian University; University of Bedfordshire; et al. (IEEE, 2017-10-02)
      A method to locate the position of the user in an indoor environment employing Bayesian theory is presented in this paper. A detailed analysis of the positional accuracy is carried out evaluating effects of two major degradation factors namely the measurement and calculation errors. The proposed technique makes use of the Gaussian distribution of random data in indoor Zigbee propagation model based on received signal strength indicator (RSSI) and the triangular positioning algorithm, maximum likelihood estimation (MLE) and Bayesian theory. It identifies the user's location calculating the maximum probability point. The proposed method offers high accuracy levels with a mean error of 0.1363m as compared to the mean error values of 1.4059m and 0.4291m for the triangular localization and triangular localization with MLE methods, respectively.
    • Study of a novel multi-band antenna for body-centric wireless networks

      Farooq, Waqas; Ur-Rehman, Masood; Yang, Xiaodong; Abbasi, Qammer Hussain; University of Bedfordshire; Xidian University; Texas A & M University at Qatar (Institute of Electrical and Electronics Engineers Inc., 2015-12-07)
      Body-centric wireless networks are used for connectivity between on-body and on-off body communications for various applications for rescue, diagnostics and medical usage. Multiple features of modern portable and wearable devices necessitate antenna operation at a number of frequencies. A compact, low profile and multi-band antenna is presented for body-centric wireless networks in this study. The conventional microstrip rectangular patch antenna has been converted into a multi-band antenna by using layers of mercury and liquid crystal polymer (LCP). The antenna performance in free space and in body-mounted configurations are evaluated and compared using computer simulations. The proposed antenna supports six frequencies for operation at ISM/Wi-Fi/C band. A minimal shift in the operating frequencies while operating in on-body configuration makes this the proposed antenna very resilient to frequency de-tuning caused by the human body presence. The antenna also offers high peak gain values (>7.68 dBi) in the two configurations at all of the operating frequencies.
    • Towards sparse characterisation of on-body ultra-wideband wireless channels

      Yang, Xiaodong; Ren, Aifeng; Zhang, Zhiya; Ur-Rehman, Masood; Abbasi, Qammer Hussain; Alomainy, Akram; Xidian University; University of Bedfordshire; Texas A&M University at Qatar (IET, 2015-07-01)
      With the aim of reducing cost and power consumption of the receiving terminal, compressive sensing (CS) framework is applied to on-body ultra-wideband (UWB) channel estimation. It is demonstrated in this Letter that the sparse on-body UWB channel impulse response recovered by the CS framework fits the original sparse channel well; thus, on-body channel estimation can be achieved using low-speed sampling devices.
    • Wandering pattern sensing at S-band

      Yang, Xiaodong; Shah, Syed Aziz; Ren, Aifeng; Zhao, Nan; Fan, Dou; Hu, Fangming; Ur-Rehman, Masood; von Deneen, Karen M.; Tian, Jie; Xidian University; et al. (Institute of Electrical and Electronics Engineers Inc., 2017-12-27)
      Increasing prevalence of dementia has posed several challenges for care-givers. Patients suffering from dementia often display wandering behavior due to boredom or memory loss. It is considered to be one of the challenging conditions to manage and understand. Traits of dementia patients can compromise their safety causing serious injuries. This paper presents investigation into the design and evaluation of wandering scenarios with patients suffering from dementia using an S-band sensing technique. This frequency band is the wireless channel commonly used to monitor and characterize different scenarios including random, lapping, and pacing movements in an indoor environment. Wandering patterns are characterized depending on the received amplitude and phase information of that measures the disturbance caused in the ideal radio signal. A secondary analysis using support vector machine is used to classify the three patterns. The results show that the proposed technique carries high classification accuracy up to 90% and has good potential for healthcare applications.