Experimental analysis of dense multipath components in an industrial environment

This work presents an analysis of dense multipath components (DMC) in an industrial workshop. Radio channel sounding was performed with a vector network analyzer and virtual antenna arrays. The specular and dense multipath components were estimated with the RiMAX algorithm. The DMC covariance structure of the RiMAX data model was validated. Two DMC parameters were studied: the distribution of radio channel power between specular and dense multipath, and the DMC reverberation time. The DMC power accounted for 23% to 70% of the total channel power. A significant difference between DMC powers in line-of-sight and nonline-of-sight was observed, which can be largely attributed to the power of the line-of-sight multipath component. In agreement with room electromagnetics theory, the DMC reverberation time was found to be nearly constant. Overall, DMC in the industrial workshop is more important than in office environments: it occupies a fraction of the total channel power that is 4% to 13% larger. The industrial environment absorbs on average 29% of the electromagnetic energy compared to 45%-51% for office environments in literature: this results in a larger reverberation time in the former environment. These findings are explained by the highly cluttered and metallic nature of the workshop

Empirical RF Propagation Modeling of Human Body Motions for Activity Classification

Many current and future medical devices are wearable, using the human body as a conduit for wireless communication, which implies that human body serves as a crucial part of the transmission medium in body area networks (BANs). Implantable medical devices such as Pacemaker and Cardiac Defibrillators are designed to provide patients with timely monitoring and treatment. Endoscopy capsules, pH Monitors and blood pressure sensors are used as clinical diagnostic tools to detect physiological abnormalities and replace traditional wired medical devices. Body-mounted sensors need to be investigated for use in providing a ubiquitous monitoring environment. In order to better design these medical devices, it is important to understand the propagation characteristics of channels for in-body and on- body wireless communication in BANs. The IEEE 802.15.6 Task Group 6 is officially working on the standardization of Body Area Network, including the channel modeling and communication protocol design. This thesis is focused on the propagation characteristics of human body movements. Specifically, standing, walking and jogging motions are measured, evaluated and analyzed using an empirical approach. Using a network analyzer, probabilistic models are derived for the communication links in the medical implant communication service band (MICS), the industrial scientific medical band (ISM) and the ultra- wideband (UWB) band. Statistical distributions of the received signal strength and second order statistics are presented to evaluate the link quality and outage performance for on-body to on- body communications at different antenna separations. The Normal distribution, Gamma distribution, Rayleigh distribution, Weibull distribution, Nakagami-m distribution, and Lognormal distribution are considered as potential models to describe the observed variation of received signal strength. Doppler spread in the frequency domain and coherence time in the time domain from temporal variations is analyzed to characterize the stability of the channels induced by human body movements. The shape of the Doppler spread spectrum is also investigated to describe the relationship of the power and frequency in the frequency domain. All these channel characteristics could be used in the design of communication protocols in BANs, as well as providing features to classify different human body activities. Realistic data extracted from built-in sensors in smart devices were used to assist in modeling and classification of human body movements along with the RF sensors. Variance, energy and frequency domain entropy of the data collected from accelerometer and orientation sensors are pre- processed as features to be used in machine learning algorithms. Activity classifiers with Backpropagation Network, Probabilistic Neural Network, k-Nearest Neighbor algorithm and Support Vector Machine are discussed and evaluated as means to discriminate human body motions. The detection accuracy can be improved with both RF and inertial sensors

Key Generation in Wireless Sensor Networks Based on Frequency-selective Channels - Design, Implementation, and Analysis

Key management in wireless sensor networks faces several new challenges. The scale, resource limitations, and new threats such as node capture necessitate the use of an on-line key generation by the nodes themselves. However, the cost of such schemes is high since their secrecy is based on computational complexity. Recently, several research contributions justified that the wireless channel itself can be used to generate information-theoretic secure keys. By exchanging sampling messages during movement, a bit string can be derived that is only known to the involved entities. Yet, movement is not the only possibility to generate randomness. The channel response is also strongly dependent on the frequency of the transmitted signal. In our work, we introduce a protocol for key generation based on the frequency-selectivity of channel fading. The practical advantage of this approach is that we do not require node movement. Thus, the frequent case of a sensor network with static motes is supported. Furthermore, the error correction property of the protocol mitigates the effects of measurement errors and other temporal effects, giving rise to an agreement rate of over 97%. We show the applicability of our protocol by implementing it on MICAz motes, and evaluate its robustness and secrecy through experiments and analysis.Comment: Submitted to IEEE Transactions on Dependable and Secure Computin

Analysis of a single-mode waveguide at sub-terahertz frequencies as a communication channel

We study experimentally the transmission of an electromagnetic waveguide in the frequency range from 160 to 300 GHz. Photo-mixing is used to excite and detect the fundamental TE10 mode in a rectangular waveguide with two orders-of-magnitude lower impedance. The large impedance mismatch leads to a strong frequency dependence of the transmission, which we measure with a high-dynamic range of up to 80 dB and with high frequency-resolution. The modified transmission function is directly related to the information rate of the waveguide, which we estimate to be about 1 bit per photon. We suggest that the results are applicable to a Josephson junction employed as a single-photon source and coupled to a superconducting waveguide to achieve a simple on-demand narrow-bandwidth free-space number-state quantum channel

Joint Ultra-wideband and Signal Strength-based Through-building Tracking for Tactical Operations

Accurate device free localization (DFL) based on received signal strength (RSS) measurements requires placement of radio transceivers on all sides of the target area. Accuracy degrades dramatically if sensors do not surround the area. However, law enforcement officers sometimes face situations where it is not possible or practical to place sensors on all sides of the target room or building. For example, for an armed subject barricaded in a motel room, police may be able to place sensors in adjacent rooms, but not in front of the room, where the subject would see them. In this paper, we show that using two ultra-wideband (UWB) impulse radios, in addition to multiple RSS sensors, improves the localization accuracy, particularly on the axis where no sensors are placed (which we call the x-axis). We introduce three methods for combining the RSS and UWB data. By using UWB radios together with RSS sensors, it is still possible to localize a person through walls even when the devices are placed only on two sides of the target area. Including the data from the UWB radios can reduce the localization area of uncertainty by more than 60%.Comment: 9 pages, conference submissio

Interference Mitigation for coded MB-OFDM UWB

Frequency Division Multiplexing (MB-OFDM) standard for high rate Ultra Wideband (UWB) wireless communication in the 3.1– 10.6 GHz band. The performance of MB-OFDM is impacted by interference from IEEE 802.16 WiMAX systems operating in the licensed 3.5 GHz band. Motivated by recent work showing the approximately Gaussian nature of the WiMAX interference to MB-OFDM, we propose a simple two-stage interference mitigation technique for coded MB-OFDM transmissions according to the ECMA-368 standard, consisting of interference spectrum estimation during silent periods followed by appropriate bit metric weighting during Viterbi decoding. We compare parametric and non-parametric spectrum estimation techniques for coded MB-OFDM transmissions and WiMAX interference for various scenarios of interest. The proposed two-stage interference mitigation technique is shown to be highly effective at mitigating the impact of WiMAX interference