# Link and System-Level NOMA Simulator: The Reproducibility of Research
## 5 Verification of the NOMA Simulator
### Exemplary Simulated Results
#### 5.1.2 Bit Error Rate  
To evaluate the receiver performance, the BER was investigated with different SIC variants as interference cancellation techniques. The BER performance of perfect, symbol-level and code-word-level SIC for NEU and FEU with different allocated powers is presented. Adaptive modulation is applied by considering 16-QAM for the NEU and QPSK for the FEU. FTPA is used for power allocation with two different sets, that is, \(P_{1},P_{2}=0.1,0.9\) and \(P_{1},P_{2}=0.2,0.8\). The BER performance of different receivers with \(P_{1},P_{2}=0.1,0.9\) is shown in Figure 8. For a BER of \(10^{-3}\), \(E_{b}/N_{o}\) required for NEUs with perfect SIC, the code-word-level SIC and symbol-level SIC are 13.5 dB, 14 dB and 15 dB, respectively. The code-word-level SIC achieves almost the same performance as perfect SIC with a gain of 1 dB as compared to symbol-level SIC. The same goes for FEU, where code-word level SIC  
Figure 7: BER comparison of uncoded and coded NOMA for NEU and FEU with perfect SIC in the presence of AWGN and Rayleigh fading channel.  
achieves a performance gain of 2.5 dB. However, this performance gain comes at the cost of computational complexity in the form of channel coding and decoding.  
Figure 9 also shows the performance of SIC receivers with different power allocations of \(P_{1},P_{2}=0.2,0.8\). For NEU, perfect and code-word-level SIC achieves the same level of performance with a requirement of \(E_{b}/N_{o}\) equal to 16 dB and 16.5 dB for a BER of \(10^{-2}\), respectively. However, the performance of symbol-level SIC degrades, which shows its incapability to handle errors as compared to other receivers. Furthermore, Figures 8 and 9 show that the difference in user power allocation coefficient effects the BER performance. If the power of the NEU is increased, the BER improves of the NEU; however, in comparison with the combined BER, the FEU takes the effect of less power and shows a slightly higher BER. Another simulated result related to SIC receiver designs for a NOMA system is associated with iterative SIC. An increase in the number of iterations promises better BER performance with increased complexity.  
Figure 10 shows that the SIC is performed at the user with the best channel gain; hence, the iterative process improves the NEU performance. For a BER of \(10^{-3}\), \(E_{b}/N_{o}\) required for NEU with iterative SIC for the first and second iterations is 18.5 dB and 19.5 dB, respectively. Therefore, a performance gain of 1 dB was achieved in the second iteration. Thus, it validates the early assertion that as the number of iterations is increasing, the BER of the receiver improves; however, the price for this improvement is paid in the form of increased computational complexity.  
Figure 8: BER performance comparison of different receivers for NEU and FEU with \(P_{1},P_{2}=0.1,0.9\).  
Figure 10: BER performance comparison of different receivers for NEU and FEU with \(P_{1},P_{2}=0.3,0.7\).  
Figure 9: BER performance comparison of different receivers for NEU and FEU with \(P_{1},P_{2}=0.2,0.8\).