AWGN : Recombining AWGN to obtain new AWGN I am a newbie to AWGN.

My professor has given me a task of taking 4 different AWGN (0 mean and SD of 1) channels (Lets say each channel has 100 samples). Then I recombine these noise samples by adding all the noise samples together. Now I divide the AWGN channel by the square root of the channel count. In this case, I have 4 samples so I divide the newly generated channel by 2. Now as I understand this new channel has same mean and SD as each of the channels that were recombined to generate this new channel. I now use this new AWGN and combine it with my signal and study a Decoders performance using signal+newly created AWGN. I will be adding the noise to a BIAWGN channel. So my signal will be +1 or -1 and noise will be added on top of that

My questions are as follows:
1. What could be the motivation of doing this. Will this help me in any way?
2. Does anyone know of any research papers that employ this method when studying a decoders performance?
My guess is your professor is trying to teach you about how noise in a dual-pol QAM system affects decoder performance. In such a system, there are 4 uncorrelated AWGN noise channels (XI,XQ,YI,YQ). It could also be that your professor is trying to teach you about linear impairments and their properties.