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

SECOND ORDER STATISTICS OF DUAL SELECTION DIVERSITY OVER CORRELATED WEIBULL FADING CHANNELS IN THE PRESENCE OF INTERFERENCE

In this paper, second order statistics of dual selection combining (SC) system applying desired signal decision algorithm are obtained for the case when that diversity system operates in Weibull interference-limited environment. Namely, a novel closed-form expression for outage probability (OP), necessary for an analysis of average fade duration (AFD), in the term of Meijer’s G-function is derived for general case in which desired signal and cochannel interference (CCI) are exposed to fading with different severities. Depending on fading environment, semi-analytical and analytical expressions for average lever crossing rate (LCR) are obtained, too. Numerical results are presented to accomplish proposed mathematical analysis and to examine the effects of system and channel parameters on concerned quantities

Eigenvalue Dynamics of a Central Wishart Matrix with Application to MIMO Systems

We investigate the dynamic behavior of the stationary random process defined by a central complex Wishart (CW) matrix ${\bf{W}}(t)$ as it varies along a certain dimension $t$. We characterize the second-order joint cdf of the largest eigenvalue, and the second-order joint cdf of the smallest eigenvalue of this matrix. We show that both cdfs can be expressed in exact closed-form in terms of a finite number of well-known special functions in the context of communication theory. As a direct application, we investigate the dynamic behavior of the parallel channels associated with multiple-input multiple-output (MIMO) systems in the presence of Rayleigh fading. Studying the complex random matrix that defines the MIMO channel, we characterize the second-order joint cdf of the signal-to-noise ratio (SNR) for the best and worst channels. We use these results to study the rate of change of MIMO parallel channels, using different performance metrics. For a given value of the MIMO channel correlation coefficient, we observe how the SNR associated with the best parallel channel changes slower than the SNR of the worst channel. This different dynamic behavior is much more appreciable when the number of transmit ($N_T$) and receive ($N_R$) antennas is similar. However, as $N_T$ is increased while keeping $N_R$ fixed, we see how the best and worst channels tend to have a similar rate of change.Comment: 15 pages, 9 figures and 1 table. This work has been accepted for publication at IEEE Trans. Inf. Theory. Copyright (c) 2014 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to [email protected]

Extreme Level Crossing Rate: A New Performance Indicator for URLLC Systems

Level crossing rate (LCR) is a well-known statistical tool that is related to the duration of a random stationary fading process \emph{on average}. In doing so, LCR cannot capture the behavior of \emph{extremely rare} random events. Nonetheless, the latter events play a key role in the performance of ultra-reliable and low-latency communication systems rather than their average (expectation) counterparts. In this paper, for the first time, we extend the notion of LCR to address this issue and sufficiently characterize the statistical behavior of extreme maxima or minima. This new indicator, entitled as extreme LCR (ELCR), is analytically introduced and evaluated by resorting to the extreme value theory and risk assessment. Capitalizing on ELCR, some key performance metrics emerge, i.e., the maximum outage duration, minimum effective duration, maximum packet error rate, and maximum transmission delay. They are all derived in simple closed-form expressions. The theoretical results are cross-compared and verified via extensive simulations whereas some useful engineering insights are manifested.Comment: Accepted for publication in IEEE TV

Transmit antenna selection in fading wireless communication systems

Includes abstract.Includes bibliographical references (leaves 79-83).To address the drawbacks associated with multiple-input multiple-output (MIMO) systems, we propose the use of the transmit antenna selection technique. In transmit antenna selection, the best performing antenna(s) is selected from all the available transmit antennas for transmission. Transmit antenna selection reduces the number of radio frequency chains, and the system complexity while still achieving the goals of multiple antenna systems. In this thesis the performance of a MIMO system employing transmit antenna selection and maximal-ratiocombining is studied

Motorway Vehicular Networks with Renewable Energy Powered Access Points

The goal of this work is to consider the potential of using renewable energy only to power roadside units (RSUs), which not only reduces CO2 footprint but also reduces the infrastructure needed in motorway vehicular communication. The thesis begins with collation and analysis of wind and motorway traffic data for the purpose of determining the energy demand of vehicular networks as well as the energy supply obtainable from wind. This is followed by the study of a standalone RSU powered by wind energy. Small size standalone wind energy systems which have benefits of low cost, easy and large scale deployments are implemented for the low power RSUs. The concept of wind energy based rate adaptation is introduced and implemented in the RSU through which RSU can vary transmission power according to the availability of wind energy. This reduces the outage and improves the overall service quality. Traditionally rate adaptation was employed to cater for wireless channel unavailability. A queuing model for the RSU is developed and verified through simulation to evaluate the performance in terms of delay, packet loss and utilisation. Channel fading is considered and the performance of the RSU is re-evaluated in terms of the same quality of service parameters, viz. delay, packet loss and utilisation to investigate the impact of fading in the network. Next, the reliability of the RSU is redefined in the context of unavailability of sufficient wind power. The transient nature of wind energy causes the RSUs to either transmit at full data rate or not transmit at all depending on the availability of sufficient energy. Thus, a failure occurs when the wind power is less than the load. Therefore, a framework has been developed for redefining a number of reliability parameters in the context of wind powered RSUs. A detailed wind data analysis was carried out based upon the hourly wind speed obtained from the UK air information resource (AIR) database for a period of five years, to determine the energy model of the deployed micro-turbine. An energy storage device (a small battery) is connected to the micro-wind turbine for improved service quality

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios