Course Description

Course Name: Signal Processing For Wireless Communications

Course Start Date: Feb 20, 2025, Orientation, videos released weekly

Q&A Workshops: Thurs: Feb 27, Mar 6, 13, 20, 27 4-5:30PM EDT

Location: Zoom Webinar

Speaker: Dan Boschen

Pre-Recorded Videos combined with Live Q&A Workshops

This is a hands-on course providing pre-recorded lectures that students can watch on their own schedule and an unlimited number of times prior to live Q&A/Workshop sessions with the instructor. Ten 1.5 hour videos released 2 per week while the course is in session will be available for up to two months after the conclusion of the course.  If a sufficient number of students sign-up, a second workshop session may be added earlier in the day for convenience to those in other time-zones. Workshop sessions are recorded and Dan is available throughout the course to answer questions as well.

Course Summary

This course is a fresh view of the fundamental and practical concepts of digital signal processing applicable to the design of mixed signal design with A/D conversion, digital filters, operations with the FFT, and multi-rate signal processing.  This course will build an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and applications in GPS and mixed signal (analog/digital) modern transceivers. This course is applicable to Signal Processing algorithm development with a focus on meeting practical hardware development challenges in both the analog and digital domains, and not a tutorial on working with specific Signal Processing processor hardware.

Jupyter Notebooks

This course includes Jupyter Notebooks which incorporates graphics together with Python simulation code to provide a “take-it-with-you” interactive user experience. No knowledge of Python is required but the notebooks will provide a basic framework for proceeding with further signal processing development using that tool for those that have interest in doing so.

This course will not be teaching Python, but using it for demonstration. A more detailed course on Python itself is covered in a separate course also taught by Dan titled “Python Applications for Digital Design and Signal Processing”.

Students will be encouraged but not required to load all the Python tools needed, and all set-up information for installation will be provided prior to the start of class.

Target Audience:

All engineers involved in or interested in signal processing applications. Engineers with significant experience with Signal Processing will also appreciate this opportunity for an in-depth review of the fundamental Signal Processing concepts from a different perspective than that given in a traditional introductory Signal Processing course. Please contact Dan at boschen@loglin.com if you are uncertain about your background or if you would like more information on the course.

Benefits of Attending/ Goals of Course:

Attendees will build a stronger intuitive understanding of the fundamental signal processing concepts involved with digital filtering and mixed signal analog and digital design. With this, attendees will be able to implement more creative and efficient signal processing architectures in both the analog and digital domains. The knowledge gained from this course will have immediate practical value for any work in the signal processing field.

  • 30-minute meeting to go over getting started with the course.

  • Correlation, Fourier Transform, Laplace Transform

  • Sampling and A/D Conversion, Z –transform, D/A Conversion

  • IIR and FIR Digital filters, Direct Fourier Transform

  • Windowing, Digital Filter Design, Fixed Point vs Floating Point

  • Fast Fourier Transform, Multi-rate Signal Processing, Multi-rate Filters

Topics / Schedule:

GPS sliding corretion.png
Linear phase FIR Fiilter (2).png
multi-state CIC.png

Speaker’s Bio

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems and has taught courses on Signal Processing for over 20 years. Dan is a contributor to dsprelated.com and Signal Processing Stack Exchange dsp.stackexchange.com/, and is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions. .

For more background information, please view Dan’s Linked-In page at: http://www.linkedin.com/in/danboschen

Ready to Learn More or Enroll?

Explore the full course schedule and registration options on these platforms:

Courses through DSPRelated
Courses through IEEE

Client Testimonials

  • Ken Houston, Massachusetts

    “I have been using Signal Processing for many years, so the theory on fundamental Signal Processing concepts was mainly a refresher. The real value for me was introducing Python and Jupyter notebooks. I have been using Matlab for a long time but never made the jump to Python, until now. The course is very well organized with detailed notes and examples covering the Signal Processing concepts, as well as installation instructions and code for Python and Jupyter notebooks. You will learn a lot about Python as well as Signal Processing . Dan is an excellent instructor who answers questions patiently and competently. I went on to take his "Software Radio" and "Python for Digital Design and Signal Processing" courses as well.”

  • Dr. Alan Palevsky - Raytheon Engineering Fellow (retired), Keysight ADS Certified Expert

    “Dan Boschen's Course "Signal Processing for Wireless Communications" is an excellent class for both new engineers learning the material and for senior personnel getting a refresher course. The lecture material is clear and concise and the verbal presentation is excellent. Most engineers obtain a basic understanding of the Fourier and Laplace transforms in their undergraduate courses. However, the z-transform is key to digital processing. Dan does an excellent job introducing and explaining the power of the z-transform. I highly recommend this course both to junior and senior engineers working modern communication systems”

  • Alan S, Massachusetts

    “I enjoyed taking Dan's "Signal Processing for Wireless Communications" course on-line. Dan is clearly an expert with the material, and has planned, organized, and paced his presentation very well. He explained the tools as well as the theory, and had plenty of well-sized exercises to reinforce the material. I had a light-buld moment when he explained the implementation of FFT. Highly recommended!”

  • Eddie B, Colorado

    “I highly recommend Dan Boschen's "Signal Processing for Wireless Communications" class. The material covers a range of useful topics, from refreshers on fundamentals to treatment of real-world signal processing techniques. Dan has a strong command of the subject matter and works with enthusiasm to share this knowledge with his students.”

  • Sudarshan N.

    I found this course very practical. Its use of Python is the cherry on the pie. It is directly applicable in day-to-day Signal Processing work. Starting with core fundamentals, the course quickly ramps up to cover several advanced Signal Processing concepts. Dan's ability to link all the concepts back to the fundamentals is truly remarkable, and helps understand the topics better.

  • Scott Siclari

    “This course is advantageous for those who are experienced in the subject, as well as those who are new to it. Dan presents a lucid and intuitive account to the highly mathematical subject matter, which I have not experienced with any textbook. As well, his Python based Jupyter notebooks which accompany his material presents a distinct advantage to those wishing to learn how to use the material to a practical advantage!”

  • Marcin P, Poland

    “I was enrolled in Signal Processing for Wireless Communication course led by Dan. Huge amount of practical and theoretical knowledge was passed during the classes. Examples in the form of python codes given by the tutor were great hands-on experience and helped to understand the problems. Weekly workshops and direct contact with Dan gave an opportunity to clarify most of the problems during learning. Moreover, videos on-demand with long-term access provide you with convenient self-paced training and learning.”

  • Jester Putterman, CTO, OptimERA Engineering

    “The Signal Processing for Wireless Communication course managed to clarify a notoriously complex set of mathematical topics that I have struggled with for a long time. The course's interweaving of classical "white board" presentation of the mathematics with animated diagrams combined with examples of the physical wiring of components gave a much more practical and intuitive grasp how filters are applied to grab a specific carrier, and how information can be encoded in that carrier. Dan's lessons are clear, his examples flow efficiently and clearly, and he is persistent and dedicated to the cause of explaining the content to the listener. I strongly recommend this course to anyone dealing with wireless carriers.”