Computational Optimization of RIS-Enhanced Backscatter and Direct Communication for 6G IoT:A DDPG-Based Approach with Physical Layer Security  

作　　者：Syed Zain Ul Abideen Mian Muhammad Kamal Eaman Alharbi Ashfaq Ahmad Malik Wadee Alhalabi Muhammad Shahid Anwar Liaqat Ali 

机构地区：[1]College of Computer Science and Technology,Qingdao University,Qingdao,266071,China [2]School of Electronic Science and Engineering,Southeast University,Nanjing,210018,China [3]Computer Science Department,Faculty of Computing and Information Technology,King Abdulaziz University,Jeddah,80200,Saudi Arabia [4]Department of Quality Assurance,Al-Kawthar University,Karachi,75300,Pakistan [5]Department of Computer Science,Immersive Virtual Reality Research Group,King Abdulaziz University,Jeddah,80200,Saudi Arabia [6]Department of AI and Software,Gachon University,Seongnam-si,13120,Republic of Korea [7]Department of Electrical Engineering,University of Science and Technology,Bannu,28100,Pakistan

出　　处：《Computer Modeling in Engineering & Sciences》2025年第3期2191-2210,共20页工程与科学中的计算机建模(英文)

基　　金：funded by the deanship of scientific research(DSR),King Abdukaziz University,Jeddah,under grant No.(G-1436-611-225)。

摘　　要：The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet ofThings(IoT)applications,particularly in terms of ultra-reliable,secure,and energyefficient communication.This study explores the integration of Reconfigurable Intelligent Surfaces(RIS)into IoT networks to enhance communication performance.Unlike traditional passive reflector-based approaches,RIS is leveraged as an active optimization tool to improve both backscatter and direct communication modes,addressing critical IoT challenges such as energy efficiency,limited communication range,and double-fading effects in backscatter communication.We propose a novel computational framework that combines RIS functionality with Physical Layer Security(PLS)mechanisms,optimized through the algorithm known as Deep Deterministic Policy Gradient(DDPG).This framework adaptively adapts RIS configurations and transmitter beamforming to reduce key challenges,including imperfect channel state information(CSI)and hardware limitations like quantized RIS phase shifts.By optimizing both RIS settings and beamforming in real-time,our approach outperforms traditional methods by significantly increasing secrecy rates,improving spectral efficiency,and enhancing energy efficiency.Notably,this framework adapts more effectively to the dynamic nature of wireless channels compared to conventional optimization techniques,providing scalable solutions for large-scale RIS deployments.Our results demonstrate substantial improvements in communication performance setting a new benchmark for secure,efficient and scalable 6G communication.This work offers valuable insights for the future of IoT networks,with a focus on computational optimization,high spectral efficiency and energy-aware operations.

关 键 词：Computational optimization reconfigurable intelligent surfaces(RIS) 6G networks IoT and DDPG physical layer security(PLS) backscatter communication 

分 类 号：TN929.5[电子电信—通信与信息系统]