OFDM and the DFT

Shows how Orthogonal Frequency Division Multiplexing (OFDM) is implemented with a Discrete Fourier Transform (DFT), and how it relates to single carrier digital communications.
Related videos: (see: http://www.iaincollings.com)
• How are OFDM Sub Carrier Spacing and Time Samples Related?    • How are OFDM Sub Carrier Spacing and ...  
• Why is the OFDM Symbol Prefix Shorter in 5G Mobile and 802.11ac WiFi?    • Why is the OFDM Symbol Prefix Shorter...  
• OFDM Waveforms:    • OFDM Waveforms  
• Why is Subcarrier Spacing Bigger in 5G Mobile Communications?    • Why is Subcarrier Spacing Bigger in 5...  
• What is a Cyclic Prefix in OFDM?    • What is a Cyclic Prefix in OFDM?  
• How does OFDM Overcome ISI?    • How does OFDM Overcome ISI?  
• Orthogonal Basis Functions in the Fourier Transform:    • Orthogonal Basis Functions in the Fou...  
For a full list of Videos and Summary Sheets, goto: http://www.iaincollings.com

** Note: I gave the continuous-time version of the Inverse Fourier Transform equation because it's more intuitive to show how the waveforms (at the different frequencies) add up. But if you substitute t=(n/N)T, then you get the standard IDFT equation (in terms of the discrete-time samples, indexed by the variable n). This is because in the IDFT, there are N time-domain samples, which is because there are N frequency-domain subcarriers. I also didn't show the usual scaling by a factor of 1/N (which I probably should have mentioned. ... but it's just a scaling, so it doesn't change any of the intuition, which is what I am trying to show in the video).