Gustavo Vejarano

STEM Outreach Expo Reaches Curious Local Community

LMU Public and Media Relations  online

2024-10-28

“I hope attendees find inspiration and become interested in engineering, science, and technology at the expo, where they have one-on-one interactions with exhibitors who are engineers and staff members working on some of the latest technological innovations happening in Southern California,” said Gustavo Vejarano, associate professor of electrical and computer engineering, one of the events main organizers.

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Seaver Summer Research 2024: Alex Alvarez ’25

LMU Public and Media Relations  online

2024-07-12

The Seaver Summer Research Community’s work covered topics in biology, health and human sciences, mechanical engineering, computer science and more disciplines across the college. With such a diversity of research projects to choose from, we spoke to some of the students about their unique summer experience. Today, we spotlight computer science major Alex Alvarez ‘25, whose research was mentored by Gustavo Vejarano, associate professor of electrical and computer engineering.

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A Conversation With Gustavo Vejarano

LMU Magazine  online

2024-01-09

Gustavo Vejarano is a professor of electrical and computer engineering in the LMU Frank R. Seaver College of Science and Engineering. He has received a two-year, $200,000 National Science Foundation grant as principal investigator to study the use of groups of drones to fight wildfires. We asked him about his research goals, challenges of operating drones in fire environments, and the role of artificial intelligence in the project. Vejarano was interviewed by Editor Joseph Wakelee-Lynch.

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NSF Grant Enables Research on Drone Networks that Could Revolutionize Wildfire Monitoring

LMU Public and Media Relations  online

2023-12-01

Thanks to a substantial grant of nearly $200,000 over two years from the National Science Foundation, Vejarano’s project, titled “ERI: Fault-Tolerant Monitoring of Moving Clusters of Targets using Collaborative Unmanned Aerial Vehicles,” aims to harness the power of collaborative drones to monitor ground activities, particularly wildfires, with unprecedented efficiency.

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LMU Hosts Mars Expo

LMU Public and Media Relations  online

2023-11-17

“Promoting science, technology, engineering, and mathematics among K-12 students is important,” said Gustavo Vejarano, associate professor of electrical and computer engineering, who brought the event to LMU’s campus. “Space exploration is a great way to inspire kids, our next generation of STEM professionals.”

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Seaver College establishes new computer engineering major and master's programs

The Los Angeles Loyolan  online

2023-09-21

Vejarano noted LMU’s opportune location for students preparing to enter this field. “We have Silicon Beach, which is on the commercial sector, and we also maintain relations with the aerospace industry ... LMU is located at a strategic place, and our students and faculty are taking advantage of that.”

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Computer Engineering Major and Master’s Program Launch To Meet Global Need

LMU Public and Media Relations  online

2023-09-08

Gustavo Vejarano, associate professor in the Electrical and Computer Engineering Department, explained that although the degrees are new, some of the required courses have been offered in the past. Reflecting student enthusiasm to study computer engineering, the degree programs have risen to meet the demand.

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God wants us to be stargazers, pope’s astronomer tells LMU crowd

Angelus  online

2021-03-16

Gustavo Vejarano, who teaches electrical and computer engineering at LMU, invited Consolmagno to speak. He believes that with university graduates going on to work at local aerospace firms like SpaceX, Raytheon and Northup Grumman, there is a greater need to revisit these upgraded science-vs.-religion questions — and it’s made him think more about what his own Catholic identity within an academic structure like LMU’s should look like.

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Solving a Puzzle in Wireless Sensor Technology

Seaver News, Loyola Marymount University  online

2016-02-23

In the Intelligent and EmWireless Sensor 640x427bedded Networks and Systems Laboratory at Loyola Marymount University, Gustavo Vejarano, Ph.D., studies how wireless sensors can be used in physical therapy to capture a patient’s range of motion and help assess rehabilitation progress. But a recent project was stymied until he asked a colleague, and expert in human physiology, to lend a hand.

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Graduate to a New Level

The Los Angeles Loyolan  print

2015-11-04

"In the Intelligent and Embedded Networks and Systems (Intemnets) Laboratory, Gustavo Vejarano works with graduate students on research projects such as the programming and development of interconnected networks that track a person's movement and vital signs. The data are then used to detect whether a patient in physical therapy is doing the exercises correctly and to analyze the patient's progress. Vejarano takes LMU graduate students to a new level by helping them develop their engineering and research skills in order to improve people's standards of living."

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Motion Capture Using Personal Area Wireless Networks

Seaver News, Loyola Marymount University  online

2014-03-30

An expert in cutting the cord, Gustavo Vejarano, assistant professor of electrical engineering and computer science, is studying applications of wireless technologies. Vejarano is researching networks of wireless sensors to overcome the limitations of infrared-based motion capture systems.

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Educator Sees I.T. As The Next Leading Job Sector In Los Angeles

CBS Los Angeles  online

2013-05-13

“There are technologies being developed that allow any device to connect to the internet. An example of this are cars and homes connected to the internet so that they can be controlled remotely by family members. Another example is the use of our minds to control devices which can, in turn, connect to the internet.”

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Hotspot Detection and Localization with Unmanned Aerial Vehicles (UAVs) and Point Set Registration (PSR)

Summer Opportunities for Advanced Research Award, Seaver College of Science and Engineering, Loyola Marymount University $2,000

2021-05-17

This SOAR submission is continue the involvement of a rising junior of computer science in an ongoing NSF funded project on wildfire monitoring using collaborative drones. The student will be responsible for the completion of the following tasks: (1) geo-referencing of hotspots on local map using actual telemetry data, (2) image processing to model hotspots as discrete point sets on the local map, (3) validation and verification of image-processing algorithm from images acquired from two different flying drones. The data generated from (2) are the input data for the work being completed by graduate students. Graduate students develop algorithms that allow drones to communicate point sets of their thermal images with neighboring drones to characterize the hotspots seen by all drones combined. This characterization is done using a mathematical model known as Gaussian Mixture Model GMM).

ERI: Fault-Tolerant Monitoring of Moving Clusters of Targets using Collaborative Unmanned Aerial Vehicles

Foundational Research in Robotics, National Science Foundation $196,993

2023-09-01

Unmanned aerial vehicles, or drones, have successfully been used to monitor ground activity. However, using small drones for extended periods of time is not yet possible, thus limiting their use. For instance, small quadcopters that can be easily transported and deployed do not exceed forty minutes of flying time in most cases and are susceptible to unexpected failure such as damage from natural hazards. On the other hand, robust quadcopters of longer flying times have large dimensions and weight that greatly delay deployment. As an alternative to a single robust drone, this award supports fundamental research to endow a network of small drones to monitor ground activity with the goal of uninterrupted operation and fault tolerance. Therefore, the solution to this challenge enables drones to join and leave the network as failures and/or battery depletions arise and in the absence of central command to avoid a single point of failure (e.g., loss of communication with central command). This award aims at autonomous drones that collaborate by sharing information with one another including knowledge of targets detected. The sharing of information increases the reliability of detection and localization of target clusters and enables coordination of flight formations and search paths. A demonstration of this concept is applied to the case of wildfire monitoring. The performance of the drone network is evaluated at the San Dimas Experimental Forest in coordination with the US Forest Service via flights over prescribed fires. Furthermore, this award sustains research at a predominantly undergraduate institution and enables a meaningful collaboration with the US Forest Service.

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Configuration of the CubeSat I2C Bus

Summer Opportunities for Advanced Research Award, Seaver College of Science and Engineering, Loyola Marymount University $2,000

2022-05-16

This summer project is to support the progress made on the LMU Cubesat Project. Funds are requested for one student who will continue the work he started in Spring 2022. His assignment has two objectives: (1) to interface the satellite‐communication system (Endurosat Transciever) with the microcontroller of the Cubesat platform (dsPIC33 microcontroller) via I2C (communication protocol for embedded systems), and (2) to write code for the real‐time operating system of the platform (Salvo OS) that configures the communication system in beacon mode. Depending on the progress, a third objective will be considered: (3) to configure the communication system in data mode to transmit test bytes from the cubesat to the ground station.

Wireless Networking for Collaborative Drones

Continuing Faculty Grant, Seaver College of Science and Engineering, Loyola Marymount University $9,320

2021-05-17

Drones are currently being used for a wide variety of applications in the filming, entertainment, defense, and transportation industries. In many of the applications, drones are individual systems that operate independently from other drones. For example, an operator controls one single drone to film an event or to participate in a drone-race competition. However, as application scenarios become more complex, several drones may be considered that work collaboratively to perform one specific task. The technical problem addressed in this proposal considers this collaborative scenario. Specifically, the problem consists of localization of multiple targets on ground in minimum time. When more than one drone is considered, the target-search time can be reduced because different search regions can be covered simultaneously by different drones. Therefore, in order to minimize the search time, the distance between drones increases. From a wireless networking perspective, the increase in distance is a challenge because the transmission power may have to be increased at levels that may not be feasible when the network is to be maintained fully connected (i.e., each drone can communicate with any other drone directly). Infeasibility may be due to different reasons such as required transmission power that exceeds specifications or that depletes drones’ batteries too fast. This project aims at developing transmission-power, information-routing, and drone formation algorithms that enable minimization of target-search time to determine target locations.

EECE-3200 Junior Lab II

This course is a continuation of ELEC-301 Junior Lab I with emphasis on design of both analog and digital systems. It also introduces basic programming on assembler and hardware description languages for FPGA-based system design.

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EECE-3210 Signals and Linear Systems

This course is an introduction to the analysis of continuous and discrete time signals and systems in the time and frequency domains, analog communication systems, and pulse code modulation.

EECE-4110 Analog and Digital Communication Systems

This course is divided into three main parts. The first one is an introduction to the analysis of digital communication systems. The second part is an introduction to the theory of probability, random processes, and spectral analysis. The third part builds on this theory in order to perform the analysis of analog and digital communication systems.

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EECE-5140 Computer Architecture with VHDL

Students will design computing systems that meet desired requirements including organization, functionality, and operation of hardware and instruction sets. Students will also be introduced to VHDL to implement the designed computer architectures.

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EECE-5210 Random Processes

Studies of the fundamental theories of probability, random variables, and stochastic processes at a level appropriate to support graduate coursework/research and practice in industry in electrical and computer engineering. Applications of the theories to engineering and science problems will be emphasized.

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EECE-5270 Wireless Networks

This course is an introduction to wireless networks. It is divided into three main parts: wireless communications, computer networking, and wireless networking. The focus is on wireless networking mainly, which covers cellular networks and wireless local area networks. Selected advanced topics will be presented in the form of student presentations, which are prepared under the guidance of the instructor. Each presentation will be a survey of the current research literature.

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EECE-6111 Information Theory and Coding

This course is an introduction to Information Theory and its application to the analysis of data compression (i.e., the minimum number of bits required to represent information) and channel capacity (i.e., the maximum data transmission rate over a channel).

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EECE-6210 Motion Capture Laboratory

Students will learn how to set up motion capture systems using two different technologies: (1) infra-red cameras and reflective markers, (2) wearable wireless networks. The motion capture systems will be interfaced to a computer to log all motion-capture data and process it using digital-signal-processing and data-classification algorithms.

EECE-6270 Wireless Sensor Networks

This course is an introduction to the programming and implementation of wireless sensor networks (WSN). The course follows a hands-on approach. For every meeting time, students will receive a short lecture on programming concepts, which will be followed by laboratory assignments. In the lab assignments, students will apply the concepts introduced in the lecture to program wireless sensors with the objective of having them collaborate with each other to form a WSN.

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EECE 6901/6902 Graduate Capstone Project

The Graduate Capstone Project is the terminal class taken by graduate students in the Graduate Program in the Department of Electrical and Computer Engineering. It is a project-based seminar in which students are required to select, research, write about, and discuss a subject of current interest to electrical engineers and computer scientists. Students give a number of presentations over the course of the semester according to the schedule in the table below. In class meetings when no project presentations are scheduled, the seminar focuses on informal discussions of various issues and problems raised by students' projects. Students are also required to attend at least one professional meeting from a local chapter of the IEEE, ACM, or another professional society and give an oral report to the class that summarizes the technical topics discussed in the professional meeting.

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EECE-6998 Wireless Network Applications

This is a research-oriented course. Its main goal is to introduce students to a research topic of their choice within the broad field of wireless-network applications. Students will identify a research topic, define a research problem on this topic, provide a research plan for solving the problem, execute their plan, and analyze the findings they obtain from the execution.

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SYEG-695 Preparation for Capstone Project

This course is taken in preparation for SYEG 696 Graduate Capstone Project. It is a project-based course where students are required to select, research, write about, and discuss a subject of current interest to systems engineers. Students give a number of presentations over the course of the semester. In class meetings, when no project presentations are scheduled, the course focuses on informal discussions of various issues and problems raised by students' projects. The goal is to develop a project plan, present the plan to a faculty panel, and gain advisor approval.

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HNRS-2200 Honors Nature of Science, Technology, and Mathematics

This course is an introduction to probability, information theory, data compression, computer networks, and the TCP/IP protocol architecture. These engineering and computer-science topics will be covered from an intuitive point of view with the goal of addressing the following questions: • How is information (e.g., video, audio, text, patterns) represented in binary digits? • How are binary digits (an abstract mathematical concept) materialized using electronics? • How do computers operate individually using those electronics? • How do computers communicate with each other (e.g., Internet) to exchange information? The course will also talk about cybersecurity threats. Students will be required to read about a particular type of cyberattack from 3 different papers at least, write a report on the attack, and present it to the class.

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ELEC-210 Electric Circuit Analysis

This course is an introduction to the principles of electric circuit analysis, which is the process of determining the different characteristics of an electric circuit. These characteristics include current, voltage, and power levels. The course also considers the case of current and voltage levels that vary in time

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ELEC-213 Electric Circuit Analysis Lab

Hands-on experiments in voltage, current, resistance measurement techniques, and use of electric components in simple circuit design and testing.

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ELEC-361 Electromagnetics

Introduction to Maxwell’s equations, wave propagation, transmission line theory, and the solution of static and time-varying field problems. Topics include transmission lines, vector analysis, electrostatics, magnetostatics, time-varying fields, plane-wave propagation, and wave reflection and transmission.

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ELEC-371 Linear Systems

This course is an introduction to the analysis of continuous and discrete time signals and systems in the time and frequency domains

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ELEC-423 Communications I

This course is an introduction to communication systems. It consists of three main sections. The first section introduces the concept of communication systems and the mathematical analysis of the transmission of signals. The second section focuses on analog communications systems. Finally, the third section focuses on digital communication systems.

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ELEC-424 Communications II

This course is divided into three main parts. The first part is an introduction to the theory of probability, random processes, and spectral analysis. The second part builds on this theory in order to perform the analysis of communication systems. Finally, the third part is an introduction to information theory and channel coding.

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ELEC-584 Introduction to Microprocessors II

This course is an introduction to the architecture, programming, and interfacing of the 8-bit, 16-bit, 32-bit, and 64-bit Intel microprocessors. The programming section includes addressing modes, data movement, and arithmetic, logic, and program-control instructions. The interfacing section includes memory, input/output (I/O), interruptions, direct memory access, and the arithmetic coprocessor.

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ELEC-698 Radio Propagation

This is a project-based course. The objective of the project is to validate radio-propagation models available in the research literature using the signal transmitted by LMU’s FM radio station KXLU. Students need to put together the system that measures the spectrum of the received signal at different locations in the city using a laptop, spectrum analyzer, GPS unit, and dipole antenna. The data collected will be used to validate radio-propagation models students need to program using Python.

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Open-Source Quadcopter for Autonomous UAV Networks for Surveillance using Zigbee Radios and Thermal Imaging

Justin Hynes, Alejandro Marcovich, Gustavo Vejarano

2024-10-28

This paper details the development of an open-source quadcopter prototype for UAV-to-UAV communication via a Zigbee network. The prototype integrates a thermal imaging system for surveillance and autonomy to fly to destinations determined onboard without ground control. The prototype is assembled on a Parrot Anafi AI quadcopter utilizing a Raspberry Pi Zero 2 W, an XBee transciever, and a TOPDON TC001 thermal camera. UAV operations are executed onboard via services of the Air SDK open-source architecture and implemented in Python and C++. Ground control of the UAV runs on a separate WiFi network, and it overrides the autonomous operation for safety. Flight tests demonstrate successful UAV-to-UAV communication links of up to 113 meters long in an urban environment. Periodic acquisition of thermal images along with corresponding telemetry data (i.e., altitude, geo-location, pitch, yaw, roll) were confirmed. A separate service controls the flight trajectory, which can be determined as a result of onboard image and telemetry data processing in coordination with other equally equipped UAVs.

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Targeted Broadcast in Vehicular Ad-Hoc Networks

Roberto Ventura, William Bjorndahl, Gustavo Vejarano

2023-11-15

Vehicular ad-hoc networks (VANETs) experience large variations in network connectivity due to changes on traffic levels. At low traffic, vehicles move fast and are distant from one another, so they establish intermittent links reducing connectivity. At high traffic, vehicles move slowly and are in close proximity to one another, increasing connectivity. This paper proposes a novel multi-hop broadcast algorithm that enables vehicles to estimate the traffic level within their two-hop neighborhood and use routing metrics selectively depending on the measured traffic level. Another novel concept is that the broadcast message is targeted to a section of the road, broadcast area, which has an expiration time. The algorithm is designed with the goal of increasing the speed that the broadcast message propagates along the road to deliver it to all vehicles ahead and behind the source vehicle that reach the broadcast area before it expires. Simulation results confirm that the broadcast message is delivered reliably and propagates at a speed that increases with the traffic level and plateaus at high traffic.

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Point Set Registration for Target Localization using Unmanned Aerial Vehicles

Dhruvil Darji, Gustavo Vejarano

2023-09-01

The problem of point set registration (PSR) on images obtained using a group of unmanned aerial vehicles (UAV) is addressed in this paper. UAVs are given a flight plan each, which they execute autonomously. A flight plan consists of a series of GPS coordinates and altitude that indicate where the UAV stops and hovers momentarily to capture an image of stationary targets on ground. A PSR algorithm is proposed that given any two images and corresponding GPS coordinates and altitude, estimates the overlap between the images, identifies targets in the overlapping area, and matches these targets according to the geometric patterns they form. The algorithm estimates the overlap considering the error in UAVs’ locations due to wind, and it differentiates similar geometrical patterns by their GPS location. The algorithm is evaluated using the percent of targets in the overlapping area that are matched correctly and the percent of overlapping images matched correctly. The target-matching rate achieved using only the GPS locations of targets varied from 44% to 55% for target densities that varied from 6.4 down to 3.2 targets/m2. The proposed algorithm achieved target-matching rates of 48% to 87%. Well-known algorithms for PSR achieved lower rates on average.

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Pothole Detection from Dash Camera Images using YOLOv5

Ashit Patel, Lei Huang, Gustavo Vejarano

2022-07-25

In this paper, we propose a new solution to automatically detect potholes on the road surface from dash camera images using a state-of-the-art deep learning based object detection algorithm, namely, You Only Look Once version 5 (YOLOv5). The dash camera image data were preprocessed and augmented as inputs to Convolutional Neural Network (CNN) models, which are trained to output the detected potholes with location bounding boxes. Through transferred learning, different sizes of CNN models with different layer architectures are evaluated in terms of mean Average Precision (mAP) and the number of frames per second (fps). Compared with previous work, experimental results show that our proposed solution using YOLOv5 achieved higher detection accuracy at faster detection speeds, while enabling tradeoffs between accuracy and speed with three different model size options.

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Motion Based Routing and Transmission Power Control in Wireless Body Area Networks

Garrett Newell, Gustavo Vejarano

2020-04-09

Wireless body area networks (WBANs) are characterized by large fluctuations in channel losses due to body shadowing. These fluctuations follow the patterns of the user’s body movements. For example, in the case of walking and running, channel losses follow cyclical patterns. This paper presents an algorithm for transmission power control (TPC) and dynamic routing in WBANs when the user performs periodic body movements. The objective of the algorithm is to decrease the average power consumption to deliver packets to a common sink provided that a desired packet delivery rate (PDR) is guaranteed. This problem is important in WBANs given that replacing batteries is detrimental to several applications of WBANs, especially when sensors of the WBAN are implanted on the user’s body. To the best of our knowledge, the proposed algorithm is the first to consider the joint problem of TPC and dynamic routing while not relying on non-local data (i.e., measurements of received power). This characteristic is important because traditional algorithms rely on data not local to transmitters, so these data have to be transmitted, consuming power unnecessarily. Traditional algorithms are also limited to the star topology only, so routing is not considered, which decreases network connectivity and transmission-power savings. The proposed algorithm is implemented on a WBAN of Shimmer wireless sensors. Experimental results show a reduction in power consumption of 23.4% to 50.4% when compared against transmissions at maximum power and a PDR within 5.6% of the desired value. The power consumption of the overhead of the proposed algorithm can be as small as 11% of that one of traditional algorithms. The algorithm’s complexity is shown to be O(N3), where N is the number of sensors. Finally, the algorithm is compared with traditional algorithms which reduce power consumption by 39.0% on average at most.

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Non-Audible Speech Classification Using Deep Learning Approaches

Rommel Fernandes, Lei Huang, and Gustavo Vejarano

2019-12-05

Research advancement of human-computer interaction (HCI) has recently been made to help post-stroke victims dealing with physiological problems such as speech impediments due to aphasia. This paper investigates different deep learning approaches used for non-audible speech recognition using electromyography (EMG) signals with a novel approach employing continuous wavelet transforms (CWT) and convolutional neural networks (CNNs). To compare its performance with other popular deep learning approaches, we collected facial surface EMG bio-signals from subjects with binary and multi-class labels, trained and tested four models, including a long-short term memory(LSTM) model, a bidirectional LSTM model, a 1-D CNN model, and our proposed CWT-CNN model. Experimental results show that our proposed approach performs better than the LSTM models, but is less efficient than the 1-D CNN model on our collected data set. In comparison with previous research, we gained insights on how to improve the performance of binary and multi-class silent speech recognition.

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Counting Static Targets using an Unmanned Aerial Vehicle On-The-Fly and Autonomously

Dhruvil Darji, Gustavo Vejarano

2018-05-09

The counting of static targets on ground using an unmanned aerial vehicle (UAV) is proposed. To the best of our knowledge, this is the first paper to do such counting on-the-fly and autonomously. The flight path is programmed before take-off. The UAV captures images of the ground which are processed consecutively on-the-fly to count the number of targets along the flight path. Each image is processed using the proposed target-counting algorithm. First, targets' centers are detected in the current image; and second, the targets that were not covered in previous images are identified and counted. The performance of the algorithm depends on its ability to identify in the current image what targets were already counted in previous images and what targets were not, and this ability is affected by the limited accuracy of the UAV to stay on the flight path in the presence of wind. In the experimental evaluation, targets were distributed on ground on three different configurations: one line of targets along the flight path, parallel lines of targets at an angle with the flight path, and random. The accuracy of the target count was 96.0%, 88.9% and 91.9% respectively.

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Volume Estimations for Combined Free-Weight and Rubber-Band Resistance Exercise

Todd Shoepe, Gustavo Vejarano, Nathan Reyes, Nicole Gobreial, and Jeanette Ricci

2017-10-31

Volume, or the total work performed during resistance training is one of the vital variables of resistance exercise programming. The most common definition in use by practitioners is sets x reps x external weight. While appropriate for linear loading incurred through free-weight resistance exercise, this inadequately addresses the nonlinear loading incurred with rubber resistance, a relatively new loading technique. The purpose of this investigation was to derive a theoretical model to describe a method of volume calculation for rubber band plus free-weight exercise. Men (n=51; age 19.5±1.6 years; body height 1.76±0.07 meters; body weight 77.3±11.3 kilograms) and women participants (n=66; age 18.9±1.1 years; body height 1.65±0.07 meters; body weight 62.8±9.1 kilograms) were measured for band lengths incurred at: squat with knee extended position, squat with flexed position, and change in band length was then calculated. Significant gender differences were seen for band length change as a percentage of body height (p

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Human-Motion Based Transmission Power Control in Wireless Body Area Networks

2016-12-12

The development of a transmission power control (TPC) protocol for wireless body area networks (WBANs) is proposed. The WBAN consists of wireless sensors attached to the user. Each sensor has a transceiver and an inertial measurement unit (IMU) to measure user's motion. The protocol increases the WBAN's lifetime by reducing the power consumption of the transceiver. The TPC protocol is based on a mathematical model of the human motion performed by the user. The protocol uses the model to determine the minimum transmission power required to achieve a packet delivery ratio (PDR). The TPC protocol uses the received signal strength indicator (RSSI) to characterize the channel. It uses IMU measurements to determine the parameters of the model and then decide on transmission power levels. Also, the TPC protocol includes a method to reduce the complexity of the human-motion model to reduce the calculations the wireless sensor has to perform. The TPC protocol is implemented and tested real-time on a Shimmer2r wireless sensor. Experimental results on a bicep-curl movement show that the average power per packet decreased from 31.3mW to 19.0mW, which is a reduction of 39%, while maintaining the PDR within a 4% difference from the target PDR.

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Prediction of Received Signal Strength from Human Joint Angles in Body Area Networks

2016-02-18

Focusing on movements of a human participant performing physical-therapy exercises, this paper presents an algorithm that predicts the received signal strength indicator (RSSI) of wireless sensor nodes attached to the user. The body area network (BAN) formed by the nodes is a motion capture system that measures joint angles of the user at the shoulder and elbow. In order to predict the RSSI, we first show that the wireless signal experiences severe attenuation from human body shadowing even though distances between transmitters and receiver are less than 3 meters. Second, we show that the RSSI fluctuates periodically with regular body movements (i.e., physical-therapy exercises). We then model the movements using k-means clustering and Markov chains and determine the probability distribution of the RSSI at each state in the movement. Finally, the RSSI is predicted with a maximum a posteriori probability (MAP) detector. Experimental results show that the RSSI can be predicted with a root mean square error (RMSE) of 3.7 dB, which is an error within 4.2% of the average RSSI level, and when a prediction is made, it is valid for the next 1083 milliseconds (ms) on average.

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Accuracy Improvement on the Measurement of Human Joint Angles

2015-01-09

A measurement technique that decreases the root mean square error (RMSE) of measurements of human joint angles using a personal wireless sensor network (WSN) is reported. Its operation is based on virtual rotations of wireless sensors worn by the user, and it focuses on the arm, whose position is measured on 5 degrees of freedom (DOF). The wireless sensors use inertial magnetic units (IMU) that measure the alignment of the arm with the earth’s gravity and magnetic fields. Due to the biomechanical properties of human tissue (e.g., skin’s elasticity), the sensors’ orientation is shifted, and this shift affects the accuracy of measurements. In the proposed technique, the change of orientation is first modeled from linear regressions of data collected from 15 participants at different arm positions. Then, out of 8 body indices measured with dual-energy X-ray absorptiometry, the percentage of body fat is found to have the greatest correlation with the rate of change in sensors’ orientation. This finding enables us to estimate the change in sensors’ orientation from the user’s body fat percentage. Finally, an algorithm virtually rotates the sensors using quaternion theory with the objective of reducing the error. The proposed technique is validated with experiments on 5 different participants. In the DOF whose error decreased the most, the RMSE decreased from 2:20o to 0:87o. This is an improvement of 60%, and in the DOF whose error decreased the least, the RMSE decreased from 1:64o to 1:37o. This is an improvement of 16%. On average, the RMSE improved by 44%.

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Distributed Throughput Maximization in Wireless Networks using the Stability Region

2014-07-15

In this paper, a game-theoretical framework for the design of distributed algorithms that control the transmission range (TR) of nodes in order to maximize throughput in Wireless Multihop Networks (WMN) is proposed. It is based on the stability region of the link-scheduling policy adopted for the network. The stability region is defined as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). The goal of the TR-control algorithms is to adapt the stability region to a given set of end-to-end flows. In the algorithms, the flows control distributively the nodes' TRs using the stability region in order to enable higher end-to-end packet rates while guaranteeing stability. In order to demonstrate how the algorithms can be designed using the proposed game-theoretical framework, a new TR-control algorithm for IEEE-802.16 WMNs is developed. Its convergence is demonstrated, and a performance bound is calculated. Finally, simulation results show that the algorithm is able to find the optimal TRs more effectively. The TRs achieve throughput levels that are at least 90 percent of the optimal throughput for 72 percent of the simulated scenarios, whereas the classic approach of spatial-reuse maximization does this for 62 percent of the scenarios.

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Development of a Wireless Sensor Network for the Measurement of Human Joint Angles

2013-12-02

The development of a wireless sensor network (WSN) that measures joint angles of the human body is reported. Its principle of operation is based on measuring the alignment of the different segments of the limb being tracked with the earth's gravity and magnetic fields. The focus is on measurements at the shoulder and elbow joints. These are tracked with 3 and 2 degrees of freedom respectively. In order to validate the accuracy of the proposed WSN, experiments are performed with arm movements on each degree of freedom and the WSN's measurements are compared with those of a professional motion capture (mocap) system that uses infra-red (IR) cameras and markers. The average root mean square error (RMSE) across all degrees of freedom was found to be 1.39° and 2.18° when tested on a spherical coordinate system and human arm respectively. Finally, the causes for this increase on the RMSE are discussed in terms of the effects of the arm's skin and muscles on the alignment of the sensors. It is found that when the user performs the greatest efforts to make the movements, the WSN deviates the most from the IR mocap system. In the degree of freedom that is most affected, the RMSE increases from 0.96° to 2.62°. This is an increase of 173%.

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Stability Analysis of Reservation-Based Distributed Scheduling Policies in Wireless Networks

2012-04-15

A major challenge in wireless networks is the ability to maximize the throughput. High throughput in a wireless network requires a relatively low complex scheduling policy with a provable efficiency ratio, which is a measure of the performance of the policy in terms of throughput and stability. For most scheduling policies that achieve provable ratios, at the onset of every frame, a selection is made of a subset of links to transmit data in the immediately following frame. In this paper, we propose a policy that allows links to transmit data in any future frame by means of frame reservations. The new, reservation-based distributed scheduling approach will improve the capacity of the system and provide greater throughput. First, we create a framework to analyze the stability of reservation-based scheduling systems. Then, to demonstrate its efficacy, we propose a reservation-based distributed scheduling policy for IEEE 802.16 mesh networks and use the new framework to find sufficient conditions for the stability of the network under this policy, i.e., we find a lower bound for its efficiency ratio. Finally, by means of simulation, we validate the mathematical analysis and compare the performance of our policy with nonreservation-based policies.

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Stability Region Adaptation using Transmission Power Control for Transport Capacity Optimization in IEEE 802.16 Wireless Mesh Networks

2011-11-15

Transmission power control in multihop wireless networks is a challenging problem due to the effects that different node transmission powers have across the layers of the protocol stack. In this paper, we study the problem of transmission power control in IEEE 802.16 mesh networks with distributed scheduling. We consider the effects of transmission power control on the link-scheduling performance when a set of end-to-end flows established in the network are given. The problem is approached by means of the stability region of the link-scheduling policy. Specifically, the stability region is adapted using transmission-power control to the paths of the flows. This adaptation enables the flows to support higher levels of data traffic under lower levels of end-to-end delay. To the best of our knowledge, the approach of stability-region-based transmission power control has not been studied before. We propose a heuristic transmission-power-control algorithm for solving the problem of adapting the stability region to the flows. It is shown, by means of simulation, that the algorithm outperforms the transmission power control based on spatial reuse, which is a widely used approach. Also, it is shown that the solution of the algorithm has performance close to the optimal solution for moderate-sized networks, i.e., networks with no more than 25 nodes and 25 flows.

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Queue-Stability-Based Transmission Power Control in Wireless Multihop Networks

2010-12-06

In this paper, we study the problem of transmission power control and its effects on the link-scheduling performance when a set of end-to-end flows established in the network are given. This problem is approached by means of the stability region of the link-scheduling policy. The stability region is defined for link-scheduling policies as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). Specifically, the link-scheduling's stability region is adapted to the paths of the flows such that the flows are able to support higher levels of data traffic under lower levels of end-to-end delay. To the best of our knowledge, the approach of transmission power control based on queue stability has not been studied before. Based on this approach, we propose a transmission-power-control algorithm. It is shown, by means of simulation, that the algorithm outperforms the transmission power control based on spatial reuse.

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Reservation-Based Distributed Scheduling in Wireless Networks

2010-06-14

Several distributed scheduling policies for wireless networks that achieve a provable efficiency ratio have been developed recently. These policies are characterized by the selection, at the onset of every time slot, of a subset of links according to the interference model of the network and the length of the links' queues. The selected subset of links is for the next time slot only. In this paper, we propose a new framework for the stability analysis of distributed scheduling policies that allow links to transmit data packets in any future time slots by means of slot reservations. Within this framework, we propose and analyze a reservation-based distributed scheduling policy for IEEE 802.16 mesh networks. We find sufficient conditions for the stability of the network when the traffic uses one hop. Specifically, we prove a lower bound for its efficiency ratio by evaluating the stability conditions obtained from our proposed framework. Finally, we compare this lower bound with the capacity achieved in simulation results.

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WiMAX-RBDS-Sim: An OPNET Simulation Framework for Reservation-Based Distributed Scheduling Policies in IEEE 802.16 Mesh Networks

2010-03-15

In this paper, a simulation model for IEEE 802.16 (WiMAX) wireless mesh networks with distributed scheduling is developed. It provides a framework for the evaluation of reservation-based distributed scheduling (RBDS) policies at the medium access control (MAC) layer. The simulation model, called WiMAX-RBDS-Sim, is developed under the OPNET event-driven simulation environment. It provides interfaces for the integration of RBDS policies and link-establishment algorithms. As an example of the use of WiMAX-RBDS-Sim, a new RBDS policy called Sliced-GM-RBDS is proposed and evaluated. This policy is based on the GM-RBDS policy proposed in [27]. The WiMAX-RBDS-Sim simulation results show that Sliced-GM-RBDS outperforms GM-RBDS in terms of network stability. A link-establishment algorithm is also evaluated with WiMAX-RBDS-Sim to determine the time required for the completion of link establishments across the network. Finally, the performance of WiMAX-RBDS-Sim is evaluated in terms of simulation speed and memory usage.

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A Constructivist Simulation-Based Methodology for Teaching Mobile Communications

2008-11-15

A constructivist simulation-based methodology for teaching mobile communication systems in the electrical engineering curriculum is reported. In this methodology, senior undergraduate students develop simulators under the guidance of an advisor, and the simulators are later used by other students to learn these particular technologies. Evaluations based on students' results and opinions demonstrate the effectiveness of the methodology for improving the teaching-learning process.

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An Intelligent Wireless Mesh Network Backbone

2007-10-22

In this paper, we report on a work-in-progress of an intelligent wireless mesh network backbone. We give a list of guidelines that should be considered for the design of such a network, and analyze them in the context of different application scenarios. We propose a backbone for these networks with the following characteristics: self-formation and maintenance, adaptability, and resiliency. A model for the backbone and a topology control scheme are proposed based on an analysis of the traffic flows generated by final users.

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Introducción a los Sistemas de Comunicaciones Móviles Modernos

2005-01-15

Este artículo presenta una breve historia, aspectos técnicos básicos y aplicaciones de los sistemas de comunicaciones móviles. También hace una pequeña revisión a los nuevos sistemas de comunicaciones móviles disponibles en Colombia.

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Diseño de Funciones DSP usando VHDL, CPLDs y FPGAs

2003-03-25

En este articulo presentamos una metodologia simple para disenar bloques funcionales DSP basicos, y el estado del arte en arquitecturas para procesadores DSP y CPLDs-FPGAs orientados al diseno DSP.

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