Sum Rate Maximization for RIS-Aided NOMA With Direct Links

Li, Xingwang; Xie, Zhen; Huang, Gaojian; Zhang, Jianhua; Zeng, Ming; Chu, Zheng

doi:10.1109/lnet.2022.3161981

Cited by 20 publications

(11 citation statements)

References 14 publications

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“…For a preliminary scale of the received power gain, we ignore the direct channel link from (6) and analyze (7). If we set i = 2 and ϑ = 1 in (7), we then obtain…”

Section: Resultsmentioning

confidence: 99%

Blockage and RIS Cooperative Joint Beamforming for mmWave MIMO Systems

Sarker¹,

Baek²,

Han³

2023

Preprint

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The revised version has been submitted to the IEEE Transactions on Vehicular Technology. A reconfigurable intelligent surface (RIS) is a kind of metasurface that provides an adaptable way of controlling the propagation of radio signals in wireless systems, allowing for improved coverage and system efficiency. Instead of the traditional RIS-assisted single-to-multiple reflection channel, we present a time-variant location-based hybrid reflection channel(TL-HRC) model in this paper. The designed TL-HRC model can easily tune a cooperative situation between the mobile blockage and RIS in millimeter wave massive multiple-input and multiple-output systems and satisfactorily scale a high received power gain. Based on the designed TL-HRC model, we establish a joint active and passive beamforming problem for the weighted sum rate maximization and propose an alternative optimization with a RIS element selection (AO-RES) algorithm to tackle the challenging high dimensional coupled parameters. Through simulation experiments the effectiveness of the proposed TL-HRC-based AO-RES algorithm is validated in terms of the weighted sum rate with the case of perfect channel state information.

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“…For a preliminary scale of the received power gain, we ignore the direct channel link from (6) and analyze (7). If we set i = 2 and ϑ = 1 in (7), we then obtain…”

Section: Resultsmentioning

confidence: 99%

Blockage and RIS Cooperative Joint Beamforming for mmWave MIMO Systems

Sarker¹,

Baek²,

Han³

2023

Preprint

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“…Benefiting from both active and passive RIS technologies, a novel system is proposed to enable uplink-NOMA over-the-air to the users, where the QoS of both users is enhanced by using a hybrid design rather than a fully active design. In conventional uplink-NOMA, the users require a sort of power allocation scheme to share the same time and frequency resources [32], [34], [35]. On the contrary, in the proposed method, the users may transmit with the same power and do not worry about interference with the confidence of the RIS providing them their required QoS.…”

Section: B Main Contributionsmentioning

confidence: 99%

Reconfigurable Intelligent Surface Enabled Over-the-Air Uplink NOMA

Arslan

Kilinc

Arzykulov

et al. 2023

IEEE Trans. on Green Commun. Netw.

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Innovative reconfigurable intelligent surface (RIS) technologies are rising and recognized as promising candidates to enhance 6G and beyond wireless communication systems. RISs acquire the ability to manipulate electromagnetic signals, thus, offering a degree of control over the wireless channel and the potential for many more benefits. Furthermore, active RIS designs have recently been introduced to combat the critical double fading problem and other impairments passive RIS designs may possess. In this paper, the potential and flexibility of active RIS technology are exploited for uplink systems to achieve virtual non-orthogonal multiple access (NOMA) through power disparity over-the-air rather than controlling transmit powers at the user side. Specifically, users with identical transmit power, path loss, and distance can communicate with a base station sharing time and frequency resources in a NOMA fashion with the aid of the proposed hybrid RIS system. Here, the RIS is partitioned into active and passive parts and the distinctive partitions serve different users aligning their phases accordingly while introducing a power difference to the users' signals to enable NOMA. First, the end-to-end system model is presented considering two users. Furthermore, outage probability calculations and theoretical error probability analysis are discussed and reinforced with computer simulation results.

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“…The transmitted signal from the ground user propagates through the direct link and the reflected link, the latter link reaching the satellite under the reflection of the RIS mounted on the HAP by means of changing the phase of the RIS reflecting elements. We define that

denotes the phase shift diagonal matrix applied to the reflective RIS for input by

, where

is the magnitude and

denotes the phase shift caused by the passive reflection of each reflective element of the RIS [ 43 ]. Thus, the signal received by the satellite at the t -th time step can then be further expressed in the following:

where

denotes the system zero mean additive white Gaussian noise (AWGN) followed by

.…”

Section: System Model Descriptionmentioning

confidence: 99%

Joint Beamforming Design for RIS-Assisted Integrated Satellite-HAP-Terrestrial Networks Using Deep Reinforcement Learning

Zhu

et al. 2023

Sensors

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In this paper, we consider reconfigurable intelligent surface (RIS)-assisted integrated satellite high-altitude platform terrestrial networks (IS-HAP-TNs) that can improve network performance by exploiting the HAP stability and RIS reflection. Specifically, the reflector RIS is installed on the side of HAP to reflect signals from the multiple ground user equipment (UE) to the satellite. To aim at maximizing the system sum rate, we jointly optimize the transmit beamforming matrix at the ground UEs and RIS phase shift matrix. Due to the limitation of the unit modulus of the RIS reflective elements constraint, the combinatorial optimization problem is difficult to tackle effectively by traditional solving methods. Based on this, this paper studies the deep reinforcement learning (DRL) algorithm to achieve online decision making for this joint optimization problem. In addition, it is verified through simulation experiments that the proposed DRL algorithm outperforms the standard scheme in terms of system performance, execution time, and computing speed, making real-time decision making truly feasible.

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Sum Rate Maximization for RIS-Aided NOMA With Direct Links

Cited by 20 publications

References 14 publications

Blockage and RIS Cooperative Joint Beamforming for mmWave MIMO Systems

Blockage and RIS Cooperative Joint Beamforming for mmWave MIMO Systems

Reconfigurable Intelligent Surface Enabled Over-the-Air Uplink NOMA

Joint Beamforming Design for RIS-Assisted Integrated Satellite-HAP-Terrestrial Networks Using Deep Reinforcement Learning

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