Digital Signal Processing for Software Radio

Digital Signal Processing (DSP) for Software Radio

Digital Signal Processing (DSP) for Software Radio 150 150 ieeeeduweek

Digital Signal Processing (DSP) for Software Radio

First Video Release and Orientation, Saturday, January 21, 2023, 1:00PM – 1:30PM  Additional videos released weekly in advance of that week’s live session!

Live Workshops:  1:00PM – 2:30PM EST; Saturdays, January 28, February 4, 11, 18 and 25. 

Attendees will have access to the recorded session and exercises for two months (until April 25) after the live session ends!

New Format Combining Live Workshops with Pre-recorded Video

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.

Course Summary

This course builds on the IEEE course “DSP for Wireless Communications” also taught by Dan Boschen, further detailing digital signal processing most applicable to practical real-world problems and applications in radio communication systems. Students need not have taken the prior course if they are familiar with fundamental DSP concepts such as the Laplace and Z transform and basic digital filter design principles.

This course brings together core DSP concepts to address signal processing challenges encountered in radios and modems for modern wireless communications. Specific areas covered include carrier and timing recovery, equalization, automatic gain control, and considerations to mitigate the effects of RF and channel distortions such as multipath, phase noise and amplitude/phase offsets.

Dan builds an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and real-world applications for mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges, rather than a tutorial on implementations with DSP processors.

Now with Jupyter Notebooks!

Digital Signal Processing (DSP) for Software Radio

Digital Signal Processing (DSP) for Software Radio 150 150 ieeeeduweek

Digital Signal Processing (DSP) for Software Radio

First Video Release, Wednesday, May 25, additional videos released weekly in advance of that week’s live session!

Live Workshops:  6:00PM – 7:30PM EST; Tuesdays, May 31, 7, 14, 21, 28

Attendees will have access to the recorded session and exercises for two months (until August 28) after the live session ends!

New Format Combining Live Workshops with Pre-recorded Video

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.

Course Summary

This course builds on the IEEE course “DSP for Wireless Communications” also taught by Dan Boschen, further detailing digital signal processing most applicable to practical real-world problems and applications in radio communication systems. Students need not have taken the prior course if they are familiar with fundamental DSP concepts such as the Laplace and Z transform and basic digital filter design principles.

This course brings together core DSP concepts to address signal processing challenges encountered in radios and modems for modern wireless communications. Specific areas covered include carrier and timing recovery, equalization, automatic gain control, and considerations to mitigate the effects of RF and channel distortions such as multipath, phase noise and amplitude/phase offsets.

Dan builds an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and real-world applications for mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges, rather than a tutorial on implementations with DSP processors.

Now with Jupyter Notebooks!