Energy-Efficient Resource Allocation and Antenna Selection for IRS-Assisted Multicell Downlink Networks

Rezaei, Atefeh; Khalili, Ata; Jalali, Jalal; Shafiei, Hossein; Wu, Qingqing

doi:10.1109/lwc.2022.3161410

Cited by 21 publications

(12 citation statements)

References 16 publications

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“…Besides, we define the product of two variables u k and W k as a new auxiliary variable Wk based on the big-M method [14], we impose the following additional constraints:…”

Section: Problem Formulationmentioning

confidence: 99%

“…IRS could help to maximize the admitted number of such users. To the best of our knowledge, the gain of deploying the IRS platform in an MTC-enabled system with short packet length to maximize the EE simultaneously with the number of admitted IoT users has not been studied in the literature yet [8]- [14]. Besides, it would be interesting to understand if the QoS is met in the face of short packet transmissions in an IRS-aided IoT system.…”

Section: Introductionmentioning

confidence: 99%

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IRS-Based Energy Efficiency and Admission Control Maximization for IoT Users With Short Packet Lengths

Jalali

Khalili

Rezaei

et al. 2023

IEEE Trans. Veh. Technol.

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In this paper, we study a multiuser multiple-input single-output (MISO) machine type communication (MTC)enabled intelligent reflecting surface (IRS) system, where a multiantenna access point (AP) transmits information symbols to a set of Internet of Things (IoT) users with short packet transmission. In particular, the total energy efficiency (EE) and the number of IoT users that could be served fairly are maximized by jointly optimizing active and passive beamformers. An efficient algorithm based on alternating optimization (AO) is proposed to solve the main optimization problem iteratively. To this end, we adopt the difference of convex functions (DC) and successive convex approximation (SCA) to make a concave-convex function. Then, we employ the fractional programming based on the quadratic form to obtain a sub-optimal solution for the active beamformers at the AP and the number of admitted users. In the passive beamforming case, a penalty-based approach is utilized together with the SCA technique to handle the unit-modulus constraints at the IRS. Simulation results unveil an interesting tradeoff between EE and user admissibility performance. Besides, the results show the effectiveness of the IRS deployment in improving EE and successfully admitted users.

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“…Besides, we define the product of two variables u k and W k as a new auxiliary variable Wk based on the big-M method [14], we impose the following additional constraints:…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

IRS-Based Energy Efficiency and Admission Control Maximization for IoT Users With Short Packet Lengths

Jalali

Khalili

Rezaei

et al. 2023

IEEE Trans. Veh. Technol.

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show abstract

“…Because of reconfigurability, IRS has been viewed as an enabling and potential technology to achieve performance enhancement, spectral and energy efficiency improvement. With more and more research on IRS, IRS has been widely applied to the following scenarios, physical layer security [20]- [22], simultaneous wireless information and power transfer (SWIPT) [23], [24], multicell MIMO communications [25], [26], covert communications [27], [28], and wireless powered communication network (WPCN) [29]- [31]. To maximize secrecy rate for IRS-assisted multi-antenna systems in [22], where an efficient alternating algorithm was developed to jointly optimize the transmit covariance of the source and the phase shift matrix of the IRS.…”

Section: Introductionmentioning

confidence: 99%

Three Efficient Beamforming Methods for Hybrid IRS plus AF Relay-aided Metaverse

Wang¹,

Feng²,

Huang³

et al. 2023

Preprint

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Due to the "double fading" effect caused by conventional passive intelligent reflecting surface (IRS), the signal via the reflection link is weak. To enhance the received signal, active elements with the ability to amplify the reflected signal are introduced to the passive IRS forming hybrid IRS. In this paper, a hybrid IRS-aided amplify-and-forward (AF) relay wireless network is considered, where an optimization problem is formulated to maximize signal-to-noise ratio (SNR) by jointly optimizing the beamforming matrix at AF relay and the reflecting coefficient matrices at IRS subject to the constraints of transmit power budgets at the source/AF relay/hybrid IRS and that of unit-modulus for passive IRS phase shifts. To achieve high rate performance and extend the coverage range, a high-performance method based on semidefinite relaxation and fractional programming (HP-SDR-FP) algorithm is presented. Due to its extremely high complexity, a low-complexity method based on successive convex approximation and FP (LC-SCA-FP) algorithm is put forward. To further reduce the complexity, a lower-complexity method based on whitening filter, general power iterative and generalized Rayleigh-Ritz (WF-GPI-GRR) is proposed, where different from the above two methods, it is assumed that the amplifying coefficient of each active IRS element is equal, and the corresponding analytical solution of the amplifying coefficient can be obtained according to the transmit powers at AF relay and hybrid IRS. Simulation results show that the proposed three methods can greatly improve the rate performance compared to the existing networks, such as the passive IRS-aided AF relay and only AF relay network. In particular, a 50.0% rate gain over the existing networks is approximately achieved in the high power budget region of hybrid IRS. Moreover, it is verified that the proposed three efficient beamforming methods have an increasing

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“…NOMA network. Moreover, Rezaei et al [8] have provided an energy efficiency optimization scheme for the RIS-NOMA network based on successive convex approximation. Based on the existing literature, several issues in multi-cell RIS-NOMA networks still need to be addressed.…”

Section: Introductionmentioning

confidence: 99%

“…First, the authors in the above studies consider simple scenarios. For instance, the work in [6] considers three-cell while the works [7], [8] consider only two-cell system models. Second, they consider only one RIS supporting all cells, which looks impractical.…”

Section: Introductionmentioning

confidence: 99%

Integration of NOMA with Reflecting Intelligent Surfaces: A Multi-cell Optimization with SIC Decoding Errors

Khan¹,

Lagunas²,

Ali³

et al. 2022

Preprint

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Reflecting intelligent surfaces (RIS) has recently emerged as one of the promising technologies for achieving high energy and spectral efficiency in next-generation wireless networks. By using low-cost passive reflecting elements, RIS can smartly reconfigure the signal propagation to extend the wireless communication coverage. On the other side, Non-orthogonal multiple access (NOMA) has been proved as a key air interface technique for supporting massive connections over limited resources. This letter proposes a new optimization framework for the multicell RIS-NOMA network. In particular, we address the system spectral efficiency maximization with successive interference cancellation (SIC) decoding errors. The closed-form expressions of transmit power at the base station and power allocation coefficients of users are derived using Karush-Kuhn-Tucker conditions. Moreover, an efficient reflection matrix for RIS in each cell is designed using successive convex approximation and DC programming. Simulation results are provided to demonstrate the benefits of the proposed optimization in the multi-cell RIS-NOMA network.

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Energy-Efficient Resource Allocation and Antenna Selection for IRS-Assisted Multicell Downlink Networks

Cited by 21 publications

References 16 publications

IRS-Based Energy Efficiency and Admission Control Maximization for IoT Users With Short Packet Lengths

IRS-Based Energy Efficiency and Admission Control Maximization for IoT Users With Short Packet Lengths

Three Efficient Beamforming Methods for Hybrid IRS plus AF Relay-aided Metaverse

Integration of NOMA with Reflecting Intelligent Surfaces: A Multi-cell Optimization with SIC Decoding Errors

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