A Review on Phase Rotation and Beamforming Scheme for Intelligent Reflecting Surface Assisted Wireless Communication Systems

XING Zhitong; LI Yun; WU Guangfu; XIA Shichao

doi:10.11999/JEIT250790

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XING Zhitong, LI Yun, WU Guangfu, XIA Shichao. A Review on Phase Rotation and Beamforming Scheme for Intelligent Reflecting Surface Assisted Wireless Communication Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250790

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XING Zhitong, LI Yun, WU Guangfu, XIA Shichao. A Review on Phase Rotation and Beamforming Scheme for Intelligent Reflecting Surface Assisted Wireless Communication Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250790

Citation:

XING Zhitong, LI Yun, WU Guangfu, XIA Shichao. A Review on Phase Rotation and Beamforming Scheme for Intelligent Reflecting Surface Assisted Wireless Communication Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250790

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A Review on Phase Rotation and Beamforming Scheme for Intelligent Reflecting Surface Assisted Wireless Communication Systems

doi: 10.11999/JEIT250790 cstr: 32379.14.JEIT250790

XING Zhitong^{1, 2},
LI Yun^{1, 2
,
,},
WU Guangfu^{1, 2},
XIA Shichao^{1, 2}

1.
Chongqing Key Laboratory of Mobile Communications Technology, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications; Chongqing, 400065, China
2.
School of Computer Science and Technology, Chongqing University of Posts and Telecommunications; Chongqing, 400065, China

Funds: National Natural Science Foundation of China (62301100), Scientific and Technological Research Program of Chongqing Municipal Education Commission Youth Project (KJQN202200606, KJQN202300638), Chongqing Natural Science Foundation (CSTB2024NSCQ-MSX0210, CSTB2024NSCQ-QCXMX0063, CSTC2024YCJH-BGZXM003), Chongqing Natural Science Foundation Innovation and Development Joint Fund(CSTB2025NSCQ-LZX0053)

Received Date: 2025-08-25
Accepted Date: 2025-11-05
Rev Recd Date: 2025-11-05

Available Online: 2025-11-13

Abstract

Abstract

Objective With the large-scale commercial deployment of 5G networks since 2020 and the ongoing research into 6G technology, modern communication systems face the challenge of adapting to increasingly complex channel environments. These include ultra-high-density urban areas, remote oceanic regions, deserts, forests, and other locations with demanding propagation conditions. To address these challenges, there is a pressing need for low-energy solutions that can dynamically adjust and reconfigure wireless communication channels. Such advancements would not only enhance transmission performance—reducing latency, increasing data rates, and improving signal reception—but also facilitate more efficient deployment in challenging environments. Intelligent Reflecting Surface (IRS) has emerged as a promising technology for reshaping channel conditions. Unlike traditional active relays, IRS operates passively, introducing minimal additional energy consumption. When integrated with existing communication architectures such as Single Input Single Output (SISO), Multiple Input Single Output (MISO), and Multiple Input Multiple Output (MIMO), IRS can significantly improve transmission efficiency, reduce power consumption, and enhance adaptability in complex scenarios. This paper aims to provide a comprehensive review of IRS-assisted communication systems, focusing on signal transmission models, beamforming techniques, and phase-shift optimization strategies. Methods This review presents a systematic analysis of Intelligent Reflecting Surface (IRS) technology in modern communication systems through comprehensive examination of signal transmission models across three fundamental configurations. Beginning with IRS-assisted SISO (Single Input Single Output) systems, we investigate how IRS revolutionizes single-antenna communications by intelligently manipulating incident signals through sophisticated reflection and phase-shifting techniques, thereby overcoming traditional limitations in signal propagation. The analysis then progresses to more complex MISO (Multiple Input Single Output) and MIMO (Multiple Input Multiple Output) architectures, where we explore the critical interplay between IRS phase shifts and advanced MIMO precoding strategies to achieve maximal spectral efficiency. Building upon these transmission models, our study provides an in-depth review of joint optimization and precoding schemes specifically designed for IRS-enhanced MIMO systems. These optimization algorithms are systematically classified into four distinct yet complementary objectives that address diverse operational requirements: The first category focuses on power consumption minimization, developing strategies to reduce total energy expenditure while maintaining satisfactory communication quality - particularly valuable for energy-sensitive applications like IoT networks and sustainable green communications. The second category pursues energy efficiency maximization, optimizing the crucial ratio of achievable data rate to power consumption rather than simply reducing energy use, thus ensuring superior performance per energy unit. The third category targets sum-rate maximization, concentrating on boosting aggregate data throughput across all users to enhance overall system capacity - an essential consideration for high-density urban 5G/6G deployments. The fourth category emphasizes fairness-aware rate maximization, implementing sophisticated resource allocation mechanisms to guarantee equitable bandwidth distribution among users while maintaining high Quality of Service (QoS) standards in multi-user environments. Together, these optimization frameworks establish a comprehensive methodology for advancing IRS-assisted MIMO systems, enabling engineers and researchers to precisely balance performance metrics, energy efficiency, and user fairness according to specific application demands and operational scenarios, thereby unlocking the full potential of IRS technology in next-generation wireless networks. Results and Discussions This comprehensive review demonstrates that Intelligent Reflecting Surface (IRS)-assisted communication systems offer transformative capabilities for next-generation wireless networks through four key advantages. Firstly, IRS provides substantial performance enhancement by intelligently reconfiguring propagation environments, particularly improving signal strength and coverage in challenging non-line-of-sight scenarios such as urban canyons, indoor spaces, and remote areas, while also maintaining connectivity in high-mobility applications like vehicular communications. Secondly, the technology achieves remarkable energy efficiency through its passive operation, introducing minimal power overhead while significantly boosting spectral efficiency - a crucial feature for sustainable massive IoT deployments and green 6G networks that may even incorporate energy-harvesting capabilities. Thirdly, IRS exhibits exceptional adaptability through seamless integration with various communication architectures, including SISO systems for basic signal enhancement, MISO for optimized beamforming, and MIMO for spatial multiplexing gains, making it versatile for diverse environments from ultra-dense urban networks to remote and aerial communications. Finally, advanced beamforming and phase-shift optimization techniques enable maximized signal-to-noise ratio through coherent signal combining, effective interference suppression in multi-user scenarios, low-latency performance for critical applications, and increasingly sophisticated real-time optimization through machine learning approaches like deep reinforcement learning. These combined capabilities position IRS as a cornerstone technology for future 6G networks, promising to enable smart radio environments and ubiquitous connectivity, though further research is needed to address practical deployment challenges including channel estimation, scalability, and standardization efforts. Conclusions This review underscores the transformative potential of IRS in next-generation wireless communication systems. By enabling dynamic channel reconfiguration with minimal energy overhead, IRS can enhance the performance of SISO, MISO, and MIMO systems, making them more robust in complex environments. The reviewed signal transmission models and optimization techniques provide a foundation for further advancements in IRS-assisted communications. As the industry progresses toward 6G, IRS is expected to play a pivotal role in achieving ultra-reliable, low-latency, and energy-efficient global connectivity. Future work should focus on practical deployment challenges, including hardware design, real-time signal processing, and standardization efforts.
- IRS,
- Beamforming,
- Phase Rotation Scheme,
- Signal Transmission

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References(75)

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