Research Assistant
University of New Mexico, Electrical and Computer Engineering Dept.
Amir Raeisi
An electrical engineer and researcher, Amir Raeisi is PhD candidate in electrical engineerig at UNM’s school of engineering. His research spans signal processing, digital and wireless communications. He focuses on questions such as: How to develope signal processong algorithms in order to enhance and improve communication systems. Amir currently works on applying Machine Learning to Communications systems and also IOT.
He also teaches courses in electrical engineering department and also developed several course curriculum and teaching is one of his favorites.
Academic Experiences
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Present 2012
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2015 2014
Adjunct Faculty
University of New Haven, College of Engineering
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Present 2014
Teacher Assistant
University of New Mexico, Electrical and Computer Engineering Dept.
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Education & Training
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Ph.D. 2020
Ph.D. in Electrical Engineering wi
Electrical and Computer Engineering Dept, University of New Mexico
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M.Sc2015
Master of Science in Electrical Engineering
Eectrical and Computer Engineering Dept, University of New Mexico
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B.Sc.2008
Bachelor of Science in Electrical Engineering
Shahrekord University, Iran
I always like to look on the optimistic side of life, but I am realistic enough to know that life is a complex matter.
Honors, Awards and Grants
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Coming Soon
Research
Research Summary
The dramatic increase in demand for higher capacity and higher data rates has been an important problem for contemporary wireless communication systems. The development of these capabilities is severely limited by the scarcity of two of the principal resources in wireless networks: energy and bandwidth. Emerging generations of wireless standards are addressing these issues through the use of techniques such as cooperative communications, spectrum sharing, energy harvesting, cloud processing and densification of infrastructure.
Focus of my recent work in wireless communication systems has addressed the novel algorithm of such techniques through information theoretic and related analyses of systems, and the role of Discrete Fractional Fourier Transform in improving communications performance in such systems. Another focus has been on the development and analysis of new signaling and networking structures, such as fractional orthogonal frequency division multiplex (Fr-OFDM) and visible light communication networks (VLC), designed to enable the techniques noted above. A further issue that we are addressing is the fundamental ability of Machine Learning in developed techniqus and other methods to exploit this capability.
Interests
- Time-Frequency Signal Procssing
- Signal Processong in Communication
- Machine Learning
- Internet of Things
- Smart Communications
- Green Communications
Publications
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Bit Error Rate {(BER)} Analysis of Discrete Fractional Fourier Transform
Conference Paper IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON, 2017.
BER OF DFRFT BASED OFDM SYSTEMS
This paper investigates the performance of Orthogonal Frequency Division Multiplex (OFDM) system by integrating the Discrete Fractional Fourier Transform (DFrFT). Here the total number of OFDM subcarriers are 64 where 48 of them are data carriers, and bandwidth allocated to OFDM is 20 MHz. The transmitted signals are assumed to travel through an Additive White Gaussian Noise (AWGN) channel. Simulations are conducted to investigate the Bit Error Rate (BER) performance of OFDM system as a function of energy per bit to noise power spectral density ratio Eb/N0 for both cases of conventional OFDM (FFT-OFDM) and proposed OFDM in this paper based on DFrFT (Fr-OFDM). Simulations confirm the proposed Fr-OFDM performance.
High performance DOA/TOA-based Endoscopy Capsule localization and tracking via 2D circular arrays and inertial measurement unit
Conference Paper 2013 Wireless for Space and Extreme Environments (WiSEE), IEEE International Conference on, Baltimore MD, USA
Wireless Capsul Localization Based on TOA/DOA
This paper investigates the performance of Wireless Capsule Endoscopy (WCE) tracking within the irregular environment of digestion system by incorporating the Directional-of-Arrival (DOA), Time-of-Arrival (TOA) and Inertial Measurement Unit (IMU) measurements with the Extended Kalman Filter (EKF). The emitter sends a signal to the WCE, and the WCE replies the signal back to the antenna arrays. Then, the round trip TOA, and the DOA of the signals transmitted from the emitter to the WCE are measured. An EKF is designed to integrate the DOA, TOA and IMU measurements to improve the WCE localization. Simulations are conducted to investigate the EKF localization performance as a function of the number of antenna arrays and TOA estimation accuracy. The impact of IMU on the localization performance will also be studied. Simulations confirm the feasibility of the WCE tracking by integrating the DOA, TOA and IMU measurements with Kalman Filter.
Detecting breathing rates and depth of breath using LPCs and Restricted Boltzmann Machines
Journal Paper Elsevier Biomedical Signal Processing and Control,Vol 48, Pages 1-11.
Detecting Breathing Rates
This paper presents the use of a Restricted Boltzmann Machine to develop an unsupervised machine learning approach to process breathing sounds to predict breathing rates and depth or length of breaths. Breath detection and monitoring has been the subject of several studies involving the health monitoring of patients on respirators. We are proposing to extend the use of non-invasive techniques to provide measures of physical exhaustion or activity. The level of activity or exhaustion could be used to prevent accidents or manage exposure to physically demanding environments such as firefighting or working underwater.
Circular Arrays and Inertial Measurement Unit for DOA/TOA/TDOA-Based Endoscopy Capsule Localization: Performance and Complexity Investigation
Journal Paper IEEE Sensor Journal, Vol 14 , Issue 11 , Nov 2014.
WCE Localization
This paper investigates the performance of wireless capsule endoscopy (WCE) tracking within the irregular environment of digestion system by integrating directional-of-arrival (DOA), time-of-arrival (TOA) [or time-difference-of-arrival (TDOA)], and inertial measurement unit (IMU) measurements using the extended Kalman filter (EKF). Here, an emitter transmits a signal to the WCE, and the WCE replies the signal back to a set of antenna arrays. Then, the round trip TOA, and the DOA of the signals transmitted from WCE to the antenna arrays are measured. The digestion system path model is considered unknown, and the movement model between two consecutive signals is assumed linear. Simulations are conducted to investigate the EKF performance as a function of the number of antenna arrays, antenna array configuration, and TOA (and TDOA) estimation accuracy. In addition, the impact of IMU on the localization performance will be studied. Simulations confirm the proposed WCE tracking performance. In addition, the computational complexity of the EKF with respect to the number of antenna array is studied.
Applying the FRFT to an OFDM System for Li-Fi : A Design Experiment for Peace Engineering Education
Conference Paper IEEE 2018 World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC)
Applying DFRFT to Li-Fi
This paper investigates the performance of wireless capsule endoscopy (WCE) tracking within the irregular environment of digestion system by integrating directional-of-arrival (DOA), time-of-arrival (TOA) [or time-difference-of-arrival (TDOA)], and inertial measurement unit (IMU) measurements using the extended Kalman filter (EKF). Here, an emitter transmits a signal to the WCE, and the WCE replies the signal back to a set of antenna arrays. Then, the round trip TOA, and the DOA of the signals transmitted from WCE to the antenna arrays are measured. The digestion system path model is considered unknown, and the movement model between two consecutive signals is assumed linear. Simulations are conducted to investigate the EKF performance as a function of the number of antenna arrays, antenna array configuration, and TOA (and TDOA) estimation accuracy. In addition, the impact of IMU on the localization performance will be studied. Simulations confirm the proposed WCE tracking performance. In addition, the computational complexity of the EKF with respect to the number of antenna array is studied.
Projects
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Contact Me
Contact & Meet Me
I would be happy to talk to you if you think I can help you with your Research or working for your company. The best way to contact me is through Email.
- office: 505-225 0330
- lab: 505-225-330
- amirorn@unm.edu
- arnafchi@gmail.com
- amirorn
- #goodgoodek
- us.linkedin.com/in/amir-r-nafchi-27b38331/
At My Office
You can find me at my office located at University of New Mexico department of electrical engineering room 223.
I am at my office every day from 7 am until 6 pm, but you may consider an email to fix an appointment.
At My Lab
You can find me at my office located at University of New Mexico department of electrical engineering room 223.
I am at my office every day from 7 am until 6 pm, but you may consider an email to fix an appointment.