Ergodic Rate Analysis and IRS Configuration for Multi-IRS Dual-Hop DF Relaying Systems

Sun, Qiang; Qian, Panpan; Duan, Wei; Zhang, Jiayi; Wang, Jue; Wong, Kai-Kit

doi:10.1109/lcomm.2021.3100347

Cited by 30 publications

(16 citation statements)

References 17 publications

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“…We derive closed-form expressions for the achievable rates for two NOMA users under the channel models of Rayleigh and Rician. Compared with recent work [30], our result could be combined with their result to provide complete ergodic performance analysis in a more practical circumstance.…”

mentioning

confidence: 85%

Ergodic Performance Analysis of Double Intelligent Reflecting Surfaces-Aided NOMA–UAV Systems with Hardware Impairment

Nguyen

Phan

et al. 2022

Drones

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In this work, we design an intelligent reflecting surface (IRS)-assisted Internet of Things (IoT) by enabling non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAV) approaches. We pay attention to studying the achievable rates for the ground users. A practical system model takes into account the presence of hardware impairment when Rayleigh and Rician channels are adopted for the IRS–NOMA–UAV system. Our main findings are presented to showcase the exact expressions for achievable rates, and then we derive their simple approximations for a more insightful performance evaluation. The validity of these approximations is demonstrated using extensive Monte Carlo simulations. We confirm the achievable rate improvement decided by main parameters such as the average signal to noise ratio at source, the position of IRS with respect to the source and destination and the number of IRS elements. As a suggestion for the deployment of a low-cost IoT system, the double-IRS model is a reliable approach to realizing the system as long as the hardware impairment level is controlled. The results show that the proposed scheme can greatly improve achievable rates, obtain optimal performance at one of two devices and exhibit a small performance gap compared with the other benchmark scheme.

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mentioning

confidence: 85%

Ergodic Performance Analysis of Double Intelligent Reflecting Surfaces-Aided NOMA–UAV Systems with Hardware Impairment

Nguyen

Phan

et al. 2022

Drones

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“…Moreover, the authors in [29] studied the deployment strategy in RIS-assised relaying system, and showed that the multi-RIS relaying system attains a higher capacity order. In [30], a multi-RIS relaying system in Nakagami-m fading channels was investigated, where closed-form expressions are derived for the upper bound on the ergodic capacity. In [31], a deep reinforcement learning algorithm was proposed to design the relay selection scheme in RIS-assisted cooperative networks, which was shown to achieve significant performance gains as compared to random relay selection and random passive beamforming designs.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Intelligent Surface Assisted OFDM Relaying: Subcarrier Matching with Balanced SNR

Zhang¹,

Wang²,

Zhuang³

et al. 2022

Preprint

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Reconfigurable intelligent surface (RIS) is a promising solution to enhance the performance of wireless communications via reconfiguring the wireless propagation environment. In this paper, we investigate the joint design of RIS passive beamforming and subcarrier matching in RIS-assisted orthogonal frequency division multiplexing (OFDM) dual-hop relaying systems under two cases, depending on the presence of the RIS reflected link from the source to the destination in the first hop. Accordingly, we formulate a mixed-integer nonlinear programming (MINIP) problem to maximize the sum achievable rate over all subcarriers by jointly optimizing the RIS passive beamforming and subcarrier matching. To solve this challenging problem, we first develop a branch-and-bound (BnB)based alternating optimization algorithm to obtain a near-optimal solution by alternatively optimizing the subcarrier matching by the BnB method and the RIS passive beamforming by using semidefinite relaxation techniques. Then, a low-complexity difference-of-convex penalty-based algorithm is proposed to reduce the computation complexity in the BnB method. To further reduce the computational complexity, we utilize the learningto-optimize approach to learn the joint design obtained from optimization techniques, which is more amenable to practical implementations. Lastly, computer simulations are presented to evaluate the performance of the proposed algorithms in the two cases. Simulation results demonstrate that the RIS-assisted OFDM relaying system achieves sustainable achievable rate gain as compared to that without RIS, and that with random passive beamforming, since RIS passive beamforming can be leveraged to recast the subcarrier matching among different subcarriers and balance the signal-to-noise ratio within each subcarrier pair.

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“…It proved that the rate performance of the proposed new system is better than that of the conventional IRS without relaying. The authors proposed a multi-IRS-aided DF relay network [24], where the IRS configuration including the numbers of IRSs and IRS reflecting elements was considered to maximize the rate. For a given channel coherence time, it was indicated that fewer IRSs with a larger number of reflecting elements tend to have better rate performance.…”

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confidence: 99%

Phase Optimization for Massive IRS-Aided Two-Way Relay Network

Zhang

Wang

Feng

et al. 2022

IEEE Open J. Commun. Soc.

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Ergodic Rate Analysis and IRS Configuration for Multi-IRS Dual-Hop DF Relaying Systems

Cited by 30 publications

References 17 publications

Ergodic Performance Analysis of Double Intelligent Reflecting Surfaces-Aided NOMA–UAV Systems with Hardware Impairment

Ergodic Performance Analysis of Double Intelligent Reflecting Surfaces-Aided NOMA–UAV Systems with Hardware Impairment

Reconfigurable Intelligent Surface Assisted OFDM Relaying: Subcarrier Matching with Balanced SNR

Phase Optimization for Massive IRS-Aided Two-Way Relay Network

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