Systems and Communications Commons^™

Development And Characterization Of An Iot Network For Agricultural Imaging Applications, Jacob D. Wahl

Master's Theses

Smart agriculture is an increasingly popular field in which the technology of wireless sensor networks (WSN) has played a large role. Significant research has been done at Cal Poly and elsewhere to develop a computer vision (CV) and machine learning (ML) pipeline to monitor crops and accurately predict crop yield numbers. By autonomously providing farmers with this data, both time and money are saved. During the past development of a prediction pipeline, the primary focuses were CV and ML processing while a lack of attention was given to the collection of quality image data. This lack of focus in previous …

Indoor Positioning Using Acoustic Pseudo-Noise Based Time Difference Of Arrival, Nicholas J. Luong

Master's Theses

The Global Positioning System (GPS) provides good precision on a global scale, but is not suitable for indoor applications. Indoor positioning systems (IPS) aim to provide high precision position information in an indoor environment. IPS has huge market opportunity with a growing number of commercial and consumer applications especially as Internet of Things (IoT) develops. This paper studies an IPS approach using audible sound and pseudo-noise (PN) based time difference of arrival (TDoA). The system’s infrastructure consists of synchronized speakers. The object to be located, or receiver, extracts TDoA information and uses multilateration to calculate its position. The proposed IPS …

Distance Estimation Using Ofdm Signals For Ultrasonic Positioning, Kyman Huang

Master's Theses

This paper describes a method of estimating distance via Time-of-Flight (TOF) measurement using ultrasonic Orthogonal Frequency Division Multiplexing (OFDM) signals. Using OFDM signals allows the signals and their sub-carriers to remain orthogonal to each other while continuously transmitting. This estimation method is based on the change of phase of a traveling wave as it propagates through a medium (air for ultrasonic signals). By using signals containing multiple tones, the phase change between each frequency component is slightly different. This phase difference is dependent on the distance traveled and can thus be used to estimate distance. This paper studies the impact …

The Design, Testing, And Analysis Of A Constant Jammer For The Bluetooth Low Energy (Ble) Wireless Communication Protocol, Aiku Shintani

Master's Theses

The decreasing cost of web-enabled smart devices utilizing embedded processors, sensors, and wireless communication hardware have created an optimal ecosystem for the Internet of Things (IoT). IEEE802.15.4, IEEE802.11ah, WirelessHART, ZigBee Smart Energy, Bluetooth (BT), and Bluetooth Low Energy (BLE) are amongst the most commonly used wireless standards for IoT systems. Each of these standards has tradeoffs concerning power consumption, range of communication, network formation, security, reliability, and ease of implementation. The most widely used standards for IoT are Bluetooth, BLE, and Zigbee. This paper discusses the vulnerabilities in the implementation of the PHY and link layers of BLE. The link …

Communications With Spectrum Sharing In 5g Networks Via Drone-Mounted Base Stations, Liang Zhang

Dissertations

The fifth generation wireless network is designed to accommodate enormous traffic demands for the next decade and to satisfy varying quality of service for different users. Drone-mounted base stations (DBSs) characterized by high mobility and low cost intrinsic attributes can be deployed to enhance the network capacity. In-band full-duplex (IBFD) is a promising technology for future wireless communications that can potentially enhance the spectrum efficiency and the throughput capacity. Therefore, the following issues have been identified and investigated in this dissertation in order to achieve high spectrum efficiency and high user quality of service.

First, the problem of deploying DBSs …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

Provenance-Enabled Packet Path Tracing In The Rpl-Based Internet Of Things, Mohammad Abdellatif, Sabah Suhail, Rasheed Hussain, Shashi Raj Pandey, Abid Khan, Choong Seon Hong

Electrical Engineering

The interconnection of resource-constrained and globally accessible things with unreliable Internet make them vulnerable to attacks such as, but not limited to, data forging, false data injection, and packet drop. Such attacks may affect mission-critical applications that rely on sensor data for decision-making processes, hence, necessitates high assurance of trustworthy data. For the data trustworthiness, provenance is considered to be an effective mechanism that tracks both data acquisition and data transmission. However, provenance management for IoT networks is faced with several challenges such as low energy, bandwidth consumption, and efficient storage. In this paper, we propose a bi-fold Provenance-enabled Packed …

Side-Channel Power Resistance For Encryption Algorithms Using Implementation Diversity, Ivan M. Bow

Electrical and Computer Engineering ETDs

This thesis paper investigates countermeasures to hardware side-channel attacks and proposes a new solution to this ever growing threat against data integrity and security. The side-channel attack methods, differential power analysis and correlation power analysis, are both very powerful techniques and are used to gain access to secrets inside of a field programmable gate array that are otherwise inaccessible, in particular the cryptographic key for the Advanced Encryption Standard algorithm. To counter these attacks, we propose a method of changing the internal hardware configuration of the field programmable gate array using dynamic partial reconfiguration. Using this method, we change the …

Design Of A Drone-Flight-Enabled Wireless Isolation Chamber, John Wensowitch

Electrical Engineering Theses and Dissertations

The next wave of drone applications is moving from repeatable, single-drone activities such as evaluating propagation environments to team-based, multi-drone objectives such as drone-based emergency services. In parallel, testbeds have sought to evaluate emerging concepts such as highly-directional and distributed wireless communications. However, there is a lack of intersection between the two works to characterize the impact of the drone body, antenna placement, swarm topologies, and multi-dimensional connectivity needs that require in-flight experimentation with a surrounding testbed infrastructure. In this work, we design a drone-flight-enabled isolation chamber to capture complex spatial wireless channel relationships that drone links experience as applications …

Rapid Restoration Techniques For Software-Defined Networks, Ali Malik, Ruairí De Fréin, Benjamin Aziz

Articles

There is increasing demand in modern day business applications for communication networks to be robust and reliable due to the complexity and critical nature of such applications. As such, data delivery is expected to be reliable and secure even in the harshest of environments. Software-Defined Networking (SDN) is gaining traction as a promising approach for designing network architectures which are robust and flexible. One reason for this is that separating the data plane from the control plane, increases the controller’s ability to configure the network rapidly. When network failure events occur, the network manager may trade-off the optimality of the …

A Real-Time Internet Of Things (Iot) Based Affective Framework For Monitoring Emotions In Infants, Alhagie Sallah

Electrical Engineering Theses

An increase in the number of working parents has led to a higher demand for remotely monitoring activities of babies through baby monitors. The baby monitors vary from simple audio and video monitoring frameworks to advance applications where we can integrate sensors for tracking vital signs such as heart rate, respiratory rate monitoring. The Internet of Things (IoT) is a network of devices where each device can is recognizable in the network. The IoT node is a sensor or device, which primarily functions as a data acquisition unit. The data acquired through the IoT nodes are wirelessly transmitted to the …

Implementation Of A Low Cost, Solar Charged Rf Modem For Underwater Wireless Sensor Networks, Mohammad Abdellatif, Salma M. Maher, Ghazal M. Al-Sayyad, Sameh O. Abdellatif

Electrical Engineering

Underwater communication (UWC) has become an attractive research field over the past few decades. This is mainly due to the increase in underwater applications such as exploration, monitoring, and warning systems. Traditional communications techniques face many obstacles when used underwater. Optical communications require line of sight which is not always maintained underwater due to turbulence. Acoustic communication does not suffer from that, however, it can only operate with very low rates. While radio frequency (RF) communication can only operate over short distances due to the attenuation from the water, it can deliver relatively high data rates and does not require …

Zenneck Waves In Decision Agriculture: An Empirical Verification And Application In Em-Based Underground Wireless Power Transfer, Usman Raza, Abdul Salam

Faculty Publications

In this article, the results of experiments for the observation of Zenneck surface waves in sub GHz frequency range using dipole antennas are presented. Experiments are conducted over three different soils for communications distances of up to 1 m. This empirical analysis confirms the existence of Zenneck waves over the soil surface. Through the power delay profile (PDP) analysis, it has been shown that other subsurface components exhibit rapid decay as compared to the Zenneck waves. A potential application of the Zenneck waves for energy transmission in the area of decision agriculture is explored. Accordingly, a novel wireless through-the-soil power …

Impact Of Large-Scale Correlated Failures On Multilevel Virtualized Networks, Max G. Medina, Mohammed J.F. Alenazi, Egemen K. Cetinkaya

Electrical and Computer Engineering Faculty Research & Creative Works

Communication network architectures have been evolving with increased programmability and virtualization of physical infrastructures. While this evolution enables a faster introduction of new services and efficient utilization of resources, the complexities and interdependencies among the physical and virtual infrastructures, as well as the control and management planes, hinder a complete understanding of the system at hand. It is imperative, therefore, to model and study these evolving virtualized infrastructures. We propose a multilevel virtualized network embedding model and study its performance against correlated failures. Our analysis of multiple synthetic network models identified that grid-like infrastructures capture the realistic Internet2 structure the …

Energy-Efficient Data Transmission With Clustering And Compressive Sensing In Wireless Sensor Networks, Alagirisamy Mukil

Student Works (2020-2029)

One of the most important application of wireless sensor network is environmental monitoring. The application involves lifetime of sensor nodes for longer duration associating its energy module. Wireless sensor nodes deployed in sensing field aggregate enormous amount of sensed data and transfer them to the sink. The inherent limitation of energy carried within the battery of sensor nodes fetches extreme difficulty to acquire adequate network lifetime, becoming a bottleneck in forwarding data to sink. Hence the motivation is to reduce the amount of data transfer and attain energy efficiency. This is achieved by clustering and compressive sensing techniques. First objective …

Wideband And Flat-Gain Optical Amplifier With Hafnia-Bismuth Erbium Co-Doped Fiber, Abduljabbar Al-Azzawi Alabbas Ahmed

Student Works (2020-2029)

A compact optical amplifier with a flat-gain characteristic is demonstrated using hafnia bismuth-erbium co-doped fiber (HB-EDF) as the gain medium. The HB-EDF was recently fabricated using a modified chemical vapor deposition (MCVD) process in conjunction with solution doping (SD) technique. The fiber has an Erbium ions concentration of 12500 wt. ppm, which was realized due to the co-doping with Hafnium and Aluminum ions. Firstly, the proposed amplifier was investigated for both single and double-pass configurations. It is found that the 0.5m long HB-EDF is the optimum length for the C-band region. For double-pass HB-EDFA, at input signal power of -10 …

Low Latency Anomaly Detection With Imperfect Models, Samrat Nath

Graduate Theses and Dissertations

The problem of anomaly detection deals with detecting abrupt changes/anomalies in the distribution of sequentially observed data in a stochastic system. This problem applies to many applications, such as signal processing, intrusion detection, quality control, medical diagnosis, etc. A low latency anomaly detection algorithm, which is based on the framework of quickest change detection (QCD), aims at minimizing the detection delay of anomalies in the sequentially observed data while ensuring satisfactory detection accuracy. Moreover, in many practical applications, complete knowledge of the post-change distribution model might not be available due to the unexpected nature of the change. Hence, the objective …

A Power Constrained 433-Mhz Low Noise Amplifier, Pablo Alvarez Arellano

Graduate Theses and Dissertations

Within wireless communication systems, low noise amplifiers are critical for the performance of receivers. They are primarily responsible for providing enough gain while adding little noise to overcome the noise of the subsequent stages. The LNA presented here is part of a battery-powered transceiver meant to measure crop nutrient data and relay the information. Therefore, power consumption and area become import considerations. To design for a specific power level, a power-constrained noise optimization method is used. The method sizes the amplifying transistor for a fixed source impedance, power dissipation, technology, and operating frequency. The chosen topology is the cascode stage …

Reinforcement Learning In Self Organizing Cellular Networks, Roohollah Amiri

Boise State University Theses and Dissertations

Self-organization is a key feature as cellular networks densify and become more heterogeneous, through the additional small cells such as pico and femtocells. Self- organizing networks (SONs) can perform self-configuration, self-optimization, and self-healing. These operations can cover basic tasks such as the configuration of a newly installed base station, resource management, and fault management in the network. In other words, SONs attempt to minimize human intervention where they use measurements from the network to minimize the cost of installation, configuration, and maintenance of the network. In fact, SONs aim to bring two main factors in play: intelligence and autonomous adaptability. …

Ensemble Malware Classification System Using Deep Neural Networks, Barath Narayanan Narayanan, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

With the advancement of technology, there is a growing need of classifying malware programs that could potentially harm any computer system and/or smaller devices. In this research, an ensemble classification system comprising convolutional and recurrent neural networks is proposed to distinguish malware programs. Microsoft's Malware Classification Challenge (BIG 2015) dataset with nine distinct classes is utilized for this study. This dataset contains an assembly file and a compiled file for each malware program. Compiled files are visualized as images and are classified using Convolutional Neural Networks (CNNs). Assembly files consist of machine language opcodes that are distinguished among classes using …