Reconfigurable Intelligent Surfaces for Energy Efficiency in Multicast Transmissions

Du, Linsong; Zhang, Wei; Ma, Jianhui; Tang, Youxi

doi:10.1109/tvt.2021.3080302

Cited by 43 publications

(24 citation statements)

References 16 publications

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“…To find the Pareto optimal solution to this problem, we know that one common way is to combine the objectives using the linear-scalarization method. For this case, a scalar with values between 0 and 1 can be used to combine the two dummy variables, and the multiobjective optimization in (36) is then converted into a single-objective optimization problem as…”

Section: Multiobjective Optimization For Both Mct and Non-mct Groupsmentioning

confidence: 99%

Multiobjective Optimization for Intelligent Reflective Surface-Aided Physical-Layer Multicasting

Lee

2022

IEEE Open J. Commun. Soc.

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In this paper, we examine the use of intelligent reflective surface (IRS) to reconfigure the wireless propagation environment which assists the physical-layer multicast transmission with simple single-antenna radios in the network. Different phase-shift strategies are employed to adjust the reflection of the IRS. On the one hand, the max-min criterion is utilized to enhance the achievable rate of the receive nodes inside the multicast-target group. On the other hand, for the nodes outside the multicast-target group in the same network, we take advantage of another min-max criterion to let them all be less interfered with by the specific multicast communication. Multiobjective optimization is then set to reveal the compromises between the effect on the nodes of the two different groups. Simulation results show that the proposed IRS-aided physical-layer multicasting can fulfill the above-stated task, and can let the nodes in either group gain better results.

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Section: Multiobjective Optimization For Both Mct and Non-mct Groupsmentioning

confidence: 99%

Multiobjective Optimization for Intelligent Reflective Surface-Aided Physical-Layer Multicasting

Lee

2022

IEEE Open J. Commun. Soc.

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“…Recently, reconfigurable intelligent surface (RIS) [5] [6] shows the capability to control and optimize the radio environments of wireless channels between transceivers, which could be utilized to improve the SE [7] and EE [8] [9]. The wireless communication prototype based on RIS was developed in [10], which has a new type of high-gain yet low-cost RIS with 256 elements.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Intelligent Surface-Aided Spectrum Sharing Coexisting with Multiple Primary Networks

Tian¹,

Chen²,

Wang³

et al. 2022

Preprint

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In the spectrum sharing system (SSS) coexisting with multiple primary networks, a well-designed reconfigurable intelligent surface (RIS) is employed to control the radio environments of wireless channels and relieve the scarcity of the spectrum resource in this work, which can realize high spectral efficiency (SE) and energy efficiency (EE). Specifically, the SE enhancement in the considered SSS is decomposed into two subproblems which are a second-order programming (SOP) and a fractional programming of the convex quadratic form (CQFP), respectively, to optimize alternatively the beamforming vector at the secondary access point and the reflecting coefficients at the RIS. The CQFP subproblem about optimizing the reflecting coefficients can be solved by the domain and envelope shrinking algorithm (DES), providing the best SE performance. Besides, a low-complexity method of gradient-based linearization with domain (GLD) is proposed for obtaining a sub-optimal reflecting coefficients for fast deployment. Considering the power consumption in the practical application of RISaided SSS, the EE performance of our proposed GLD method has significant gain over that of the SSS without RIS. The simulation results indicate the effectiveness of the DES algorithm and show that the GLD method improves the SE and EE performance in RIS-aided SSS with multiple primary networks.

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“…multicasting has naturally gained increasing interest in recent years. Some of the recent works on IRS-assisted single-group multicast system design include [6]- [8], whereas those on IRS-assisted multigroup multicast (IRS-MGMC) system design include [9]- [11].…”

Section: Introductionmentioning

confidence: 99%

“…A similar assumption on the perfect CSI availability was considered in[6],[9]-[11],[14]. Also, since in this paper our main motivation is to provide an efficient low-complexity algorithm for the sum rate maximization problem in an IRS-MGMC system, the problem of channel estimation is out of scope of this paper 2.…”

mentioning

confidence: 99%

On the Achievable Rate of IRS-Assisted Multigroup Multicast Systems

Farooq¹,

Kumar²,

Juntti³

et al. 2022

Preprint

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Intelligent reflecting surfaces (IRSs) have shown huge advantages in many potential use cases and thus have been considered a promising candidate for next-generation wireless systems. In this paper, we consider an IRS-assisted multigroup multicast (IRS-MGMC) system in a multiple-input single-output (MISO) scenario, for which the related existing literature is rather limited.In particular, we aim to jointly design the transmit beamformers and IRS phase shifts to maximize the sum rate of the system under consideration. In order to obtain a numerically efficient solution to the formulated non-convex optimization problem, we propose an alternating projected gradient (APG) method where each iteration admits a closed-form and is shown to be superior to a known solution that is derived from the majorizationminimization (MM) method in terms of both achievable sum rate and required complexity, i.e., run time. In particular, we show that the complexity of the proposed APG method grows linearly with the number of IRS tiles, while that of the known solution in comparison grows with the third power of the number of IRS tiles. The numerical results reported in this paper extend our understanding on the achievable rates of large-scale IRS-assisted multigroup multicast systems.

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Reconfigurable Intelligent Surfaces for Energy Efficiency in Multicast Transmissions

Cited by 43 publications

References 16 publications

Multiobjective Optimization for Intelligent Reflective Surface-Aided Physical-Layer Multicasting

Multiobjective Optimization for Intelligent Reflective Surface-Aided Physical-Layer Multicasting

Reconfigurable Intelligent Surface-Aided Spectrum Sharing Coexisting with Multiple Primary Networks

On the Achievable Rate of IRS-Assisted Multigroup Multicast Systems

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