Joint Power Allocation and User Association Optimization for IRS-Assisted mmWave Systems

Zhao, Dan; Lu, Hancheng; Wang, Yazheng; Sun, Huan; Gui, Yongqiang

doi:10.1109/twc.2021.3098447

Cited by 58 publications

(38 citation statements)

References 36 publications

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“…When it comes to IRS-user association and mode selection, some essential practical factors to take into account include the user's QoS requirements, co-channel interference levels, channel condition, and deployment strategy [25]. Moreover, the associated BS might remain unchanged for a mobile user within a cell, but the associated IRS and communication mode might need to be adaptively adjusted.…”

Section: Networkmentioning

confidence: 99%

Intelligent Reflective Surface Deployment in 6G: A Comprehensive Survey

Naeem¹,

Kaddoum²,

Khan³

et al. 2022

Preprint

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Intelligent reflecting surfaces (IRSs) are considered a promising technology that can smartly reconfigure the wireless environment to enhance the performance of future wireless networks. However, the deployment of IRSs still faces challenges due to highly dynamic and mobile unmanned aerial vehicle (UAV) enabled wireless environments to achieve higher capacity. This paper sheds light on the different deployment strategies for IRSs in future terrestrial and non-terrestrial networks. Specifically, in this paper, we introduce key theoretical concepts underlying the IRS paradigm and discuss the design aspects related to the deployment of IRSs in 6G networks. We also explore optimizationbased IRS deployment techniques to improve system performance in terrestrial and aerial IRSs. Furthermore, we survey modelfree reinforcement learning (RL) techniques from the deployment aspect to address the challenges of achieving higher capacity in complex and mobile IRS-assisted UAV wireless systems. Finally, we highlight challenges and future research directions from the deployment aspect of IRSs for improving system performance for the future 6G network.

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Section: Networkmentioning

confidence: 99%

Intelligent Reflective Surface Deployment in 6G: A Comprehensive Survey

Naeem¹,

Kaddoum²,

Khan³

et al. 2022

Preprint

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“…In particular, IRS can be seen as an effective method to achieve hybrid BF/precoding since the analog phase shift can conduct by the reflection elements at the IRS. Recently, [30] studied the joint BF and user association optimization for IRSassisted mmWave multiuser MISO networks. Besides, [31] and [32] investigated the joint precoding and phase shifts design for IRS-assisted mmWave massive MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

“…i according to(30); e) Calculate the Polak-Ribiere parameter t i+1 1 in (29); f) Compute the conjugate direction d i+1 by (31); g) i ← i + 1.…”

mentioning

confidence: 99%

Double Intelligent Reflecting Surface-Assisted Multi-User MIMO Mmwave Systems With Hybrid Precoding

Niu

Chu

Zhou

et al. 2022

IEEE Trans. Veh. Technol.

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“…In order to take advantage of the IRS mentioned above, extensive researches on deploying IRS in various wireless communication systems have been conducted to improve the performance under different metrics. By judiciously adjusting IRS elements, the reflected signals are intelligently elaborated to achieve performance improvement in terms of spectral efficiency [11], energy efficiency [12], transmit power [13], [14], sum-rate [15]- [17], etc., for single-user/multi-user MIMO/multi-input single-output (MISO) [11]- [16], wideband orthogonal frequency division multiplexing (OFDM) [17], or multi-cell systems [18]. In addition, researchers have explored the designs of IRS with low-resolution phase-shift [19] and phase error [20] or under imperfect channel state information (CSI) [21].…”

Section: Introductionmentioning

confidence: 99%

IRS-assisted Multi-cell Multi-band Systems: Practical Reflection Model and Joint Beamforming Design

Cai¹,

Liu²,

Li³

et al. 2022

Preprint

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Intelligent reflecting surface (IRS) has been regarded as a promising and revolutionary technology for future wireless communication systems owing to its capability of tailoring signal propagation environment in an energy/spectrum/hardware-efficient manner. However, most existing studies on IRS optimizations are based on a simple and ideal reflection model that is impractical in hardware implementation, which thus leads to severe performance loss in realistic wideband/multi-band systems. To deal with this problem, in this paper we first propose a more practical and more tractable IRS reflection model that describes the difference of reflection responses for signals at different frequencies. Then, we investigate the joint transmit beamforming and IRS reflection beamforming design for an IRS-assisted multi-cell multi-band system. Both power minimization and sum-rate maximization problems are solved by exploiting popular second-order cone programming (SOCP), Riemannian manifold, minimization-majorization (MM), weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results illustrate the significant performance improvement of our proposed joint transmit beamforming and reflection design algorithms based on the practical reflection model in terms of power saving and rate enhancement.

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Joint Power Allocation and User Association Optimization for IRS-Assisted mmWave Systems

Cited by 58 publications

References 36 publications

Intelligent Reflective Surface Deployment in 6G: A Comprehensive Survey

Intelligent Reflective Surface Deployment in 6G: A Comprehensive Survey

Double Intelligent Reflecting Surface-Assisted Multi-User MIMO Mmwave Systems With Hybrid Precoding

IRS-assisted Multi-cell Multi-band Systems: Practical Reflection Model and Joint Beamforming Design

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