## 5 Conclusions  
The selected mapping (SLM) method has been suggested in the previous work to reduce the PAPR/CM in the UFMC waveform, in which the signal is copied to B candidates. The candidate with lower PAPR/CM can be adopted or selected for data transmission. The SLM introduces additional computational complexity due to the multiple signal representation, to provide B candidates. Furthermore, side information needs to be sent, which reduces the average rate of successful message delivery. The benefit of using selected mapping is that the PAPR/CM capacity is noticeably reduced without degrading the BER performance of the system. Thus, the reduction gain can be increased with the increment of the number of PRV, but this comes with the expense of high computational complexity. The testing results show that the PAPR can be reduced by 1.25 dB and the CM by 0.75 dB when the mapping order is 4-QAM in the 8-PRV case. The 16-QAM achieves the reduction of 1.47 dB PAPR and 0.8 dB CM. Finally, the 64-QAM achieves the reduction of 1.5 dB PAPR and 1.2 dB CM and the 256-QAM achieves the reduction of 1.9 dB PAPR and 0.8 dB CM. The contribution of this work is reducing the PAPR and CM for UFMC waveform by using the SLM technique, without degradation the BER. It is found from the results that there is symmetry between the UFMC improvement needs and the SLM solution. The limitation of this solution is increasing the computational complexity and neglecting side information. The future work considers reducing the computational complexity by using a Dummy Sequence Insertion (DSI) technique and utilizing side information within data transition.  
We would like to declare that all authors contributed equally to this manuscript. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Universiti Tenaga National under Internal Research Grant OPEX type RJO10517919 iRMC Publication Fund and the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by grant code: 19-COM-1-01-0015.  
This research was partially funded by Universiti Tenaga National under Internal Research Grant OPEX type RJO10517919 iRMC Publication Fund. The authors would also like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by grant code: 19-COM-1-01-0015.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference** & \multicolumn{2}{c}{**Method/Waveform**} & \multicolumn{2}{c}{**Remarks**} \\ \hline [PERSON], et al. [20] & \(\bullet\) & SLM & \(\bullet\) & Reduce the PAPR; \\  & \(\bullet\) & OFDM & \(\bullet\) & Neglect the BER; \\  & & & \(\bullet\) & Neglect the computational complexity. \\ \hline [PERSON] et al. [8] & \(\bullet\) & OFDM & \(\bullet\) & Reduce the PAPR; \\  & \(\bullet\) & alternative-signal & \(\bullet\) & Reduce the computational complexity; \\  & & & \(\bullet\) & Neglect the BER. \\ \hline Our Approach & \(\bullet\) & UFMC & \(\bullet\) & Reduce PAPR and CM; \\  & \(\bullet\) & SLM & \(\bullet\) & Slightly Reduce the BER; \\  & & & \(\bullet\) & Neglect the side information; \\  & & & & \(\bullet\) & Neglect the computational complexity. \\ \hline \hline \end{tabular}
\end{table}
Table 8: _Cont._