52 research outputs found

    Signal processing techniques for synchronization of wireless sensor networks

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    Plenary PaperClock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated. © 2010 SPIE.published_or_final_versio

    Terahertz Channel Characterisation Inside the Human Skin for Nano-scale Body-Centric Networks

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    THz Time-Domain Spectroscopy of Human Skin Tissue for In-Body Nanonetworks

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    Copyright: 2016. IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications standards/publications/rights/index.html for more information

    Can Artificial Noise Boost Further the Secrecy of Dual-hop RIS-aided Networks?

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    In this paper, we quantify the physical layer security of a dual-hop regenerative relaying-based wireless communication system assisted by reconfigurable intelligent surfaces (RISs). In particular, the setup consists of a source node communicating with a destination node via a regenerative relay. In this setup, a RIS is installed in each hop to increase the source-relay and relay-destination communications reliability, where the RISs' phase shifts are subject to quantization errors. The legitimate transmission is performed under the presence of a malicious eavesdropper attempting to compromise the legitimate transmissions by overhearing the broadcasted signal from the relay. To overcome this problem, we incorporate a jammer to increase the system's secrecy by disrupting the eavesdropper through a broadcasted jamming signal. Leveraging the well-adopted Gamma and Exponential distributions approximations, the system's secrecy level is quantified by deriving approximate and asymptotic expressions of the secrecy intercept probability (IP) metric in terms of the main network parameters. The results show that the secrecy is enhanced significantly by increasing the jamming power and/or the number of reflective elements (REs). In particular, an IP of approximately 10−410^{-4} can be reached with 4040 REs and 1010 dB of jamming power-to-noise ratio even when the legitimate links' average signal-to-noise ratios are 1010-dB less than the eavesdropper's one. We show that cooperative jamming is very helpful in strong eavesdropping scenarios with a fixed number of REs, and the number of quantization bits does not influence the secrecy when exceeding 33 bits. All the analytical results are endorsed by Monte Carlo simulations

    Terahertz Channel Characterization Inside the Human Skin for Nano-Scale Body-Centric Networks

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    This paper focuses on the development of a novel radio channel model inside the human skin at the terahertz range, which will enable the interaction among potential nano-machines operating in the inter cellular areas of the human skin. Thorough studies are performed on the attenuation of electromagnetic waves inside the human skin, while taking into account the frequency of operation, distance between the nano-machines and number of sweat ducts. A novel channel model is presented for communication of nano-machines inside the human skin and its validation is performed by varying the aforementioned parameters with a reasonable accuracy. The statistics of error prediction between simulated and modeled data are: mean (μ)= 0.6 dB and standard deviation (σ)= 0.4 dB, which indicates the high accuracy of the prediction model as compared with measurement data from simulation. In addition, the results of proposed channel model are compared with terhaertz time-domain spectroscopy based measurement of skin sample and the statistics of error prediction in this case are: μ = 2.10 dB and σ = 6.23 dB, which also validates the accuracy of proposed model. Results in this paper highlight the issues and related challenges while characterizing the communication in such a medium, thus paving the way towards novel research activities devoted to the design and the optimization of advanced applications in the healthcare domain

    Anatomical Region-Specific In Vivo Wireless Communication Channel Characterization

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    In vivo wireless body area networks (WBANs) and their associated technologies are shaping the future of healthcare by providing continuous health monitoring and noninvasive surgical capabilities, in addition to remote diagnostic and treatment of diseases. To fully exploit the potential of such devices, it is necessary to characterize the communication channel which will help to build reliable and high-performance communication systems. This paper presents an in vivo wireless communication channel characterization for male torso both numerically and experimentally (on a human cadaver) considering various organs at 915 MHz and 2.4 GHz. A statistical path loss (PL) model is introduced, and the anatomical region-specific parameters are provided. It is found that the mean PL in dB scale exhibits a linear decaying characteristic rather than an exponential decaying profile inside the body, and the power decay rate is approximately twice at 2.4 GHz as compared to 915 MHz. Moreover, the variance of shadowing increases significantly as the in vivo antenna is placed deeper inside the body since the main scatterers are present in the vicinity of the antenna. Multipath propagation characteristics are also investigated to facilitate proper waveform designs in the future wireless healthcare systems, and a rootmean- square (RMS) delay spread of 2.76 ns is observed at 5 cm depth. Results show that the in vivo channel exhibit different characteristics than the classical communication channels, and location dependency is very critical for accurate, reliable, and energy-efficient link budget calculations

    Nano-Communication for Biomedical Applications: A Review on the State-of-the-Art From Physical Layers to Novel Networking Concepts

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    We review EM modeling of the human body, which is essential for in vivo wireless communication channel characterization; discuss EM wave propagation through human tissues; present the choice of operational frequencies based on current standards and examine their effects on communication system performance; discuss the challenges of in vivo antenna design, as the antenna is generally considered to be an integral part of the in vivo channel; review the propagation models for the in vivo wireless communication channel and discuss the main differences relative to the ex vivo channel; and address several open research problems and future research directions

    Ellipticity Statistics of Ultra Wideband MIMO Channels for Body Centric Wireless Communication

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    In this paper, ellipticity statistics of 2 × 2 ultra wideband multiple-input-multiple-output (MIMO) channel for body-centric wireless communication is evaluated by quantifying four different on body links namely; waist-back, waist-chest, waist-ankle and waist-wrist. Results show that at lower values of signal to noise (SNR), spatial multiplexing dependent capacity degrades as the eigen value dispersion decreases (i.e., lower ellipticity statistic), whereas it increases at higher values of SNR

    IEEE 802.11bb reference channel models for indoor environments

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    This contribution proposes 802.11bb reference channel models for indoor environments
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