[en] Intelligent Reflecting Surfaces (IRS), software-controlled metasurfaces, have emerged as an upcoming sixth-generation (6G) wireless communication technology. IRS intelligently manipulates and optimizes signal propagation using a large-scale array of intelligent elements, enhancing signal coverage, increasing capacity, mitigating path loss, and combating multipath fading This work provides a new energy-efficiency model for multi-IRS-assisted multi-cell non-orthogonal multiple access (NOMA) vehicular to infrastructure communication networks. The objective is the joint optimization of the total power budget at the roadside unit (RSU), NOMA power allocation for the user equipment, and designing phase shifts for IRS in each cell to maximize the achievable energy efficiency of the system. Due to non-convexity, the original non-convex problem is first decoupled and transformed using block coordinate descent and successive convex approximation methods. Then, an efficient solution is achieved using Gradient-based and interior-point methods. We also consider two benchmark schemes: (1) NOMA power optimization at RSU with random phase shift design at IRS and (2) orthogonal multiple access power allocation with optimal phase shift design at IRS. Numerical results show the superiority of the proposed solution compared to the benchmark schemes. The proposed solution outperforms the benchmarks, demonstrating a 59.57% and 151.21% improvement over the NOMA and orthogonal schemes, respectively, at pct=2 dBm. Additionally, it shows up to a 10.43% better performance than OMA at 10 IRS elements.
Disciplines :
Computer science
Author, co-author :
Maashi, Mashael ; Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia
Alabdulkreem, Eatedal; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
Negm, Noha; Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia
Darem, Abdulbasit A.; Department of Computer Science at college of Science, Northern Border University, Arar, Saudi Arabia
Al Duhayyim, Mesfer; Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
Dutta, Ashit Kumar; Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Riyadh, Saudi Arabia
KHAN, Wali Ullah ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Nauman, Ali ; School of Computer Science and Engineering Yeungnam University, Gyeongsan, South Korea
External co-authors :
yes
Language :
English
Title :
Energy efficiency optimization for 6G multi-IRS multi-cell NOMA vehicle-to-infrastructure communication networks
Original title :
[en] Energy efficiency optimization for 6G multi-IRS multi-cell NOMA vehicle-to-infrastructure communication networks
Ajou University Deanship of Scientific Research, King Khalid University Deanship of Academic Research, University of Jordan King Khalid University Deanship of Scientific Research, Prince Sattam bin Abdulaziz University Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University King Saud University Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University
Funding text :
Acknowledgement: The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under grant number ( RGP2/96/44 ). Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R161), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Research Supporting Project number (RSPD2024R787), King Saud University, Riyadh, Saudi Arabia. The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number ( NBU-FFR-2024-2913-04 ). This study is supported via funding from Prince Sattam bin Abdulaziz University project number ( PSAU/2024/R/1445 ). The authors would like to acknowledge the support provided by AlMaarefa University while conducting this research work.The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number (RGP2/86/45). Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R161), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Research Supporting Project number (RSPD2024R787), King Saud University, Riyadh, Saudi Arabia. The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number (NBU-FFR-2024-2903-05). This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2024/R/1445). This work was also supported by the Researchers Supporting Project Number (MHIRSP-005) Almaarefa University, Riyadh, Saudi Arabia.
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