Project 2: Channel Estimation and Adaptive Equalization

In this project, we analyze the performance of channel estimation and adaptive equalization in slow fading channel. The first simulation is AWGN channel. Following the prompt from command line, you will see the three outputs which are the original image, received image, and BER curve. The second simulation is flat fading channel. Following the prompt from command line, you will see five outputs which are the original image, dynamic constellation plot for channel estimation, received image without channel estimation, adjusted image with channel estimation, and BER curve. The third simulation is frequency selective fading channel. Following the prompt properly from command line, you will see five outputs, which are the original image, dynamic constellation plot for adaptive equalization, received image without equalization, adjusted image with equalization, and BER curve.

Category:

Education

Tags:

• fading
• channel
• estimation

[phoonjzc]

I need help。 how do I plot S0(t)= sqrt (2*E/T) sin(pi*t/T) where E is normalised matched filter output and T is period.

Help! I am not sure where to put E and T

[Amishman35]

Most of this is way over my head..I do notice that with the equalization and channel estimation that the image looks better.