This course is a comprehensive introduction to control system synthesis in which the digital computer plays a major role, reinforced with hands-on laboratory experience. The course covers elements of real-time computer architecture; input-output interfaces and data converters; analysis and synthesis of sampled-data control systems using classical and modern (state-space) methods; analysis of trade-offs in control algorithms for computation speed and quantization effects. Laboratory projects emphasize practical digital servo interfacing and implementation problems with timing, noise, and nonlinear devices.

This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. The labs are done in MATLAB® during weekly lab sessions that take place in an electronic classroom. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the biological signals processed in the labs.

Encoding Communication is an openly licesed image from Wikimedia commons liceensed under CC BY-SA 3.0. It focuses on the process of communication as promotion of undersatanding through shared symbols, context, and feedback. There is an indirect pointer to possible barrriers to effective communication (noise) emanating from various sources.

This class explores sound and what can be done with it. Sources are recorded from students' surroundings - sampled and electronically generated (both analog and digital). Assignments include composing with the sampled sounds, feedback, and noise, using digital signal processing (DSP), convolution, algorithms, and simple mixing. The class focuses on sonic and compositional aspects rather than technology, math, or acoustics, though these are examined in varying detail. Students complete weekly composition and listening assignments; material for the latter is drawn from sound art, experimental electronica, conventional and non-conventional classical electronic works, popular music, and previous students' compositions.

This class explores interaction with mobile computing systems and telephones by voice, including speech synthesis, recognition, digital recording, and browsing recorded speech. Emphasis on human interface design issues and interaction techniques appropriate for cognitive requirements of speech. Topics include human speech production and perception, speech recognition and text-to-speech algorithms, telephone networks, and spatial and time-compressed listening. Extensive reading from current research literature.

6.777J / 2.372J is an introduction to microsystem design. Topics covered include: material properties, microfabrication technologies, structural behavior, sensing methods, fluid flow, microscale transport, noise, and amplifiers feedback systems. Student teams design microsystems (sensors, actuators, and sensing/control systems) of a variety of types, (e.g., optical MEMS, bioMEMS, inertial sensors) to meet a set of performance specifications (e.g., sensitivity, signal-to-noise) using a realistic microfabrication process. There is an emphasis on modeling and simulation in the design process. Prior fabrication experience is desirable. The course is worth 4 Engineering Design Points.

Filtering is the process of removing or separating the unwanted part of a mixture. In signal processing, filtering is specifically used to remove or extract part of a signal, and this can be accomplished using an analog circuit or a digital device (such as a computer). In this lesson, students learn the impact filtering can have on different types of signals, the concepts of frequency and spectrum, and the connections these topics have to real-world signals such as musical signals. Students also learn the roles that these concepts play in designing different types of filters. The lesson content prepares students for the associated activity in which they use an online demo and a variety of filters to identify the message in a distress signal heavily corrupted by noise.

Students learn the basic principles of filtering as well as how to apply digital filters to extract part of an audio signal by using an interactive online demo website. They apply this knowledge in order to isolate a voice recording from a heavily noise-contaminated sound wave. After completing the associated lesson, expect students to be able to attempt (and many successfully finish) this activity with minimal help from the instructor.

Students learn the physical properties of sound, how it travels and how noise impacts human health—including the quality of student learning. They learn different techniques that engineers use in industry to monitor noise level exposure and then put their knowledge to work by using a smart phone noise meter app to measure the noise level at an area of interest, such as busy roadways near the school. They devise an experimental procedure to measure sound levels in their classroom, at the source of loud noise (such as a busy road or construction site), and in between. Teams collect data using smart phones/tablets, microphones and noise apps. They calculate wave properties, including frequency, wavelength and amplitude. A PowerPoint® presentation, three worksheets and a quiz are provided.

This course introduces theoretical and practical principles of design of oceanographic sensor systems. Topics include: transducer characteristics for acoustic, current, temperature, pressure, electric, magnetic, gravity, salinity, velocity, heat flow, and optical devices; limitations on these devices imposed by ocean environments; signal conditioning and recording; noise, sensitivity, and sampling limitations; and standards. Lectures by experts cover the principles of state-of-the-art systems being used in physical oceanography, geophysics, submersibles, acoustics. For lab work, day cruises in local waters allow students to prepare, deploy and analyze observations from standard oceanographic instruments.

Using a systems framework, this textbook provides a clear and comprehensive introduction to the performance, analysis, and design of radio systems for students and practicing engineers. Presented within a consistent framework, the first part of the book describes the fundamentals of the subject: propagation, noise, antennas, and modulation. The analysis and design of radios including RF circuit design and signal processing is covered in the second half of the book.

Key features
- Numerous examples within the text involve realistic analysis and design activities, and emphasize how practical experiences may differ from theory or taught procedures.
- RF circuit design and analysis is presented with minimal involvement of Smith charts, enabling students to more readily grasp the fundamentals.
- Both traditional and software-defined/direct sampling technology are described with pros and cons of each strategy explained.
- 517 pages. Licensed CC BY NC 4.0.

"This textbook gives engineering students a complete overview of radio systems and provides practicing wireless engineers with a convenient comprehensive reference."
- Patrick Roblin, Ohio State University

Radio Systems Engineering, Revised First Edition was previously published by Cambridge University Press (2016) ISBN 9781107068285. This version is © Steven W. Ellingson and has been lightly updated to correct known errata, minor issues with text and figures, and to present examples in color highlight boxes and some figures in color. It is made freely available and under a Creative Commons Attribution NonCommercial International License (CC BY NC 4.0).

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How to access the book
The main landing page for this book is https://doi.org/10.21061/radiosystemsengineering-revised1st.
The open textbook is freely available online in multiple formats including PDF and HTML [forthcoming].
A paperback print version (in color) is available for order here: https://www.amazon.com/Radio-Systems-Engineering-Revised-First/dp/1957213752

ISBNs
ISBN (PDF): 978-1-957213-76-7
ISBN (HTML): 978-1-957213-77-4 (accessible version forthcoming)
ISBN (print): 978-1-957213-75-0

Table of contents
Chapter 1: Introduction
Chapter 2: Antenna Fundamentals
Chapter 3: Propagation
Chapter 4: Noise
Chapter 5: Analog Modulation
Chapter 6: Digital Modulation
Chapter 7: Radio Link Analysis
Chapter 8: Two-Port Concepts
Chapter 9: Impedance Matching
Chapter 10: Amplifiers
Chapter 11: Linearity, Multistage Analysis, and Dynamic Range
Chapter 12: Antenna Integration
Chapter 13: Analog Filters & Multiplexers
Chapter 14: Frequency and Quadrature Conversion in the Analog Domain
Chapter 15: Receivers
Chapter 16: Frequency Synthesis
Chapter 17: Transmitters
Chapter 18: Digital Implementation of Radio Functions
Appendix A: Empirical Modeling of Mean Path Loss
Appendix B: Characteristics of Some Common Radio Systems

About the author
Dr. Steven W. Ellingson
Steven W. Ellingson is an Associate Professor of Electrical & Computer Engineering at Virginia Tech. He received the Ph.D. degree in Electrical Engineering from the Ohio State University. He held senior engineering positions at Booz-Allen & Hamilton, Raytheon, and the Ohio State University ElectroScience Laboratory before joining the faculty of Virginia Tech. His research is in the areas of antennas and propagation, applied signal processing, and radio frequency instrumentation, with funding from the U.S. National Science Foundation, National Aeronautics and Space Administration, the Defense Advanced Research Projects Agency, and the commercial communications and aerospace industries. Dr. Ellingson serves as a consultant to industry and government on topics pertaining to radio frequency systems.

Suggested citation
Ellingson, Steven W. (2023). Radio Systems Engineering, Revised First Edition. Blacksburg. https://doi.org/10.21061/radiosystemsengineering-revised1st. Licensed with CC BY NC 4.0.

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Accessibility
Virginia Tech is committed to making its publications accessible in accordance with the Americans with Disabilities Act of 1990.

This class teaches the fundamentals of signals and information theory with emphasis on modeling audio/visual messages and physiologically derived signals, and the human source or recipient. Topics include linear systems, difference equations, Z-transforms, sampling and sampling rate conversion, convolution, filtering, modulation, Fourier analysis, entropy, noise, and Shannon's fundamental theorems. Additional topics may include data compression, filter design, and feature detection. The undergraduate subject MAS.160 meets with the two half-semester graduate subjects MAS.510 and MAS.511, but assignments differ.

Students learn the connections between the science of sound waves and engineering design for sound environments. Through three lessons, students come to better understand sound waves, including how they change with distance, travel through different mediums, and are enhanced or mitigated in designed sound environments. They are introduced to audio engineers who use their expert scientific knowledge to manipulate sound for music and film production. They see how the invention of the telephone pioneered communications engineering, leading to today's long-range communication industry and its worldwide impact. Students analyze materials for sound properties suitable for acoustic design, learning about the varied environments created by acoustical engineers. Hands-on activities include modeling the placement of microphones to create a specific musical image, modeling and analyzing a string telephone, and applyling what they've learned about sound waves and materials to model a controlled sound room.

Students are introduced to the sound environment as an important aspect of a room or building. Several examples of acoustical engineering design for varied environments are presented. Students learn the connections between the science of sound waves and engineering design for sound environments.

Students learn the decibel reading of various noises and why high-level readings damage hearing. Sound types and decibel readings are written on sheets of paper, and students arrange the sounds from the lowest to highest decibel levels. If available, a decibel meter can be used to measure sounds by students.

Students follow the steps of the engineering design process to create their own ear trumpet devices (used before modern-day hearing aids), including testing them with a set of reproducible sounds. They learn to recognize different pitches, and see how engineers must test designs and materials to achieve the best amplifying properties.

This is the last of five sound lessons, and it introduces acoustics as the science of studying and controlling sound. Students learn how different materials reflect and absorb sound.