This project explores different methods of implementing Con-NOMA (Constellation-based Non-Orthogonal Multiple Access) and providing simulations results and optimization.
The first Con-NOMA system this report is going to investigate is one using two uniform M- PAM constellations and composing them in an orthogonal manner, creating an M1 ∗ M2 -QAM constellation. This is described as follows: The transmitter uses 2 uniform M-PAM constellations, one as the I component and the latter as the Q component of a QAM modulation, in order to transmit to 2 users simultaneously. More specifically if the first M-PAM’s symbols are s1 and the second M-PAM’s s2 , the transmitter essentially composes them "orthogonally" and transmits symbols in the form of:
This is implemented in PAM.jl
with
function orthogonalComposition(mPAM1::M_PAM, mPAM2::M_PAM)
Given a sample system of
- Two uniform 4-PAM constellations
- Average Symbol Energy (
$E_s$ ):$E_{s1} = a$ ,$E_{s2} = 1 - a$
Starting with an
A simulation on a range of SNR levels will be ran in
order to characterize the SEP (Symbol Error Probability) values of each user. In our model, it is assumed that the two users receive the signal at different noise levels.
More specifically the noise added to the received complex symbol follows a complex normal
distribution which is
Here we aim to find the optimal value of
A value of
The second Con-NOMA system under investigation is one using a QAM constellation that is
rotated by some angle
This is implemented in PAM.jl
with
function rotationComposition(c::Constellation, θ::Real)
Thus, given the system’s requirements an orthogonal uniform 4-QAM constellation will be used. Below a sample constructed constellation is shown, for a rotation angle θ = 0.2 rad
In the same way as for the previous system, we are going to conduct simulations for the optimization of the value of the rotation angle θ. We are going to use the same measure (
As it is also shown in the figure above, the optimal value of θ that ensures user fairness is
around 0.45 rad or 26.35
The first system seems more efficient than the second because:
- The SEP is generally lower, and it drops to it’s minimum at around 3 dB
- Both users are subjected to almost the exact same SEP, ensuring user fairness