# Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks
## 4 Simulation Results and Discussions
### Performance Versus ID Requirements  
We assume the RNs to have the same ID requirement and evaluate the performance of the proposed algorithm given the specific BER targets as shown in Figure 2. To compare, the performance of four refereed algorithms are also illustrated. For the simplicity of presentation, we termed them as follows:  
**Scheme 1:** perform equal power allocation with fixed PS ratio and iteration number,  
**Scheme 2:** perform adaptive power splitting with equal power allocation and fixed iteration number,  
**Scheme 3:** perform adaptive power allocation with fixed PS ratio and iteration number,  
**Scheme 4:** perform joint power allocation and power splitting with fixed iteration number.  
We first evaluate the performance of the proposed scheme when \(K=8\) and \(E_{c}=5\)\(\mu\)W, as illustrated in Figure 2a. It is observed that the proposed algorithm outperforms the other alternatives invariant of the BER targets. It is reasonable since the proposed algorithm considers all three factors that may have impact on the transmit power, i.e., power assignment, \(\{\rho_{k}\}\) and \(\{Q_{k}\}\). While the other schemes take none or only one to two parameters into consideration. It is also found that Scheme 2 performs better than Scheme 3 when BER requirement is low, while worse than the latter as the BER requirement increases. It reveals that power allocation owns higher impact on minimizing the transmitter power when ID constraint is stronger, while the PS ratio \(\{\rho_{k}\}\) is more important when EH is the dominant constraint. In addition, the performance of Scheme 4 is superior than that of others except for the proposed algorithm. The main reason is owing to the fact that Scheme 4 do not consider \(\{Q_{k}\}\). Henceforce the EH constraint might be over-estimated. However, it can be observed that the performance gap between the proposed algorithm and Scheme 4 turns out to be smaller when BER requirement rises from \(10^{-2}\) to \(10^{-6}\). Apparently, as BER target getting harder to achieve, the optimal power allocation problem falls into the **ID Dominated Case** as discussed in Section 3.1. To meet such a tough requirement, SN has to keep increasing the transmit power although the EH requirement has already been reached. In such scenario, the impact of \(\{Q_{k}\}\) on the transmit power still remains but turns to be weaker. We further verify the performance of our proposed scheme by changing the number of RN \(K=16\), which is shown in Figure 2b. The observation coincide with that of \(K=8\) case. Nevertheless, we can find the system gets into **ID Dominated Case** at an earlier stage when the number of RNs get larger. That is mainly due to the even severer multi-user interference caused by containing more RNs, which makes the ID requirement to be harder to meet.  
To get a better insight into the impact of ID constraint on the performance, we further illustrated the resulted transmit power of various algorithms by varying the target SINR \(\Gamma_{k}\) from 1-10 dB, as shown in Figure 3. The other setup parameters are the same as that in Figure 2. The observation here coincides with that in Figure 2. And we can find that as \(\Gamma_{k}\) increases, the curves of proposed algorithm and Scheme 4 are getting closer and finally kept almost parallel with each other. Such observation shows that it still provide benefits to minimizing the total transmit power by involving \(\{Q_{k}\}\) into the optimization process, even in **ID Dominated Case**.