## 6 Conclusions  
In conclusion, this paper emphasizes the potential benefits of integrating IOSs into C-HNOMA systems to address challenges associated with iSIC and HWDs. The system model is developed for multi-user systems, and the analytical expressions for average outage probability, throughput, and SSE are derived and validated through simulations. The optimization framework for PA has been developed to maximize the SSE. The proposed model demonstrates significant improvements in outage probability, throughput, and SSE  
Figure 17: Throughput (\(\mathrm{bps}/\mathrm{Hz}\)) comparison among the proposed IOS-aided C-HNOMA, conventional HNOMA, and IOS-aided HNOMA schemes with SW-SW pairing for \(\varepsilon=1\%\) and \(d=0.08\).  
Figure 18: SSE (\(\mathrm{bps}/\mathrm{Hz}\)) comparison among the proposed IOS-aided C-HNOMA, conventional HNOMA, and IOS-aided HNOMA schemes with SW-SW pairing for \(\varepsilon=1\%\) and \(d=0.08\).  
performance. The pairing method in the proposed systems enhances overall performance. Specifically, the SW-SW pairing offers an SNR gain ranging from \(\sim\)0.3 to \(\sim\)3.81 dB for the SUE and \(\sim\)0.21 to \(\sim\)3.89 dB for the WUE against other pairing schemes. Additionally, SW-SW pairing consistently shows improved throughput performance, with an increase in SSE of \(\sim\)0.48% to \(\sim\)3.81% compared to other pairing schemes. By optimizing the PA values, with a fixed SIC error of 0.01 and an HWD of 8%, SSE sees \(\sim\)2.24% to \(\sim\)4.06% improvement compared to other PA factors. As the number of IOS components increases, significant improvements are observed even in the presence of iSIC and HVDs.  
These promising results highlight the importance of incorporating IOSs for enhanced performance and scalability in future wireless networks. Future research could focus on optimizing IOS configurations using machine learning, integrating IOSs with advanced technologies such as mmWave communications and massive MIMO, and examining strategies for user pairing and PA to further improve system robustness and efficiency.  
Conceptualization, H.S.J.K. and V.B.K.; methodology, H.S.J.K. and V.B.K.; software, H.S.J.K. and V.B.K.; validation, H.S.J.K. and V.B.K.; formal analysis, H.S.J.K. and V.B.K.; investigation, V.B.K.; resources, H.S.J.K. and V.B.K.; data curation, H.S.J.K. and V.B.K.; writing--original draft preparation, H.S.J.K.; writing--review and editing, V.B.K.; visualization, H.S.J.K.; supervision, V.B.K.; project administration, V.B.K.; All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The corresponding author and co-author give our consent for the publication of identifiable details, which can include images and/or details within the text to be published in this journal and article.  
Data Availability Statement: Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.  
This work was supported by the School of Electronics Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} AO & Alternate optimization \\ BER & Bit error rate \\ C-HNOMA & Cooperative hybrid NOMA \\ C-NOMA & Cooperative NOMA \\
5G & Fifth-generation \\ HWD & Hardware distortion \\ HNOMA & Hybrid NOMA \\ iSIC & Imperfect successive interference cancellation \\ ISAC & Integrated sensing and communication \\ IOS & Intelligent omni-surfaces \\ IoT & Internet of things \\ LoS & Line-of-sight \\ mmWave & Millimeter wave \\ MIMO & Multi-input multi-output \\ NN-FF & Near-near and far-far \\ NOMA & Non-orthogonal multiple access \\ OO-EE & Odd-odd and even-even \\ OMA & Orthogonal multiple access \\ \end{tabular}