Modeling RIS Empowered Outdoor-to-Indoor Communication in mmWave Cellular Networks

Nemati, Hossein Mashad; Maham, Behrouz; Pokhrel, Shiva Raj; Choi, Jinho

doi:10.1109/tcomm.2021.3104878

Cited by 30 publications

(19 citation statements)

References 52 publications

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“…This can also enable leveraging compressive sensing and deep learning approaches to efficiently estimate the RIS channels [4]. From the network perspective, prior work has analyzed the covcerage performance in outdoor or indoor settings utilizing the RIS for reflection [5]- [8], refraction to enhance the outdoor-toindoor coverage [9], and for joint transmission and reflection [10], [11]. The prior work in [4]- [9], [25]- [29], however, was mainly limited to simulation data.…”

Section: B Prior Work On Reconfigurable Intelligent Surfacesmentioning

confidence: 99%

“…From the network perspective, prior work has analyzed the covcerage performance in outdoor or indoor settings utilizing the RIS for reflection [5]- [8], refraction to enhance the outdoor-toindoor coverage [9], and for joint transmission and reflection [10], [11]. The prior work in [4]- [9], [25]- [29], however, was mainly limited to simulation data. To accurately evaluate the potential of the RIS surfaces, it is crucial to build proof-ofconcept prototypes and assess the expected coverage and data rate gains of RIS-integrated systems in real world wireless communication environments.…”

Section: B Prior Work On Reconfigurable Intelligent Surfacesmentioning

confidence: 99%

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Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment

Trichopoulos

Theofanopoulos

Kashyap

et al. 2022

IEEE Open J. Commun. Soc.

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Reconfigurable intelligent surfaces (RISs) have promising coverage and data-rate gains for wireless communication systems in 5G and beyond. Prior work has mainly focused on analyzing the performance of these surfaces using simulations or lab-level prototypes. To draw accurate insights about the actual performance of these systems, this paper develops an RIS proof-of-concept prototype and extensively evaluates its potential gains in the field under realistic wireless communication settings. In particular, a 160-element RIS, operating at a 5.8 GHz band, is designed, fabricated, and accurately measured in the anechoic chamber. This surface is then integrated into a wireless communication system and the beamforming gains, pathloss, and coverage improvements are evaluated in realistic outdoor communication scenarios. When both the transmitter and receiver employ directional antennas, the developed RIS achieves 15-20 dB gain in the signal-to-noise ratio (SNR) in a range of ±60 • beamforming angles. In terms of coverage, and considering a far-field experiment with a blockage between a basestation and a grid of mobile users and with an average signal path of 35 m, the RIS provides an average SNR improvement of 6 dB (max 8 dB) within an area > 75 m 2 . Thanks to the scalable RIS design, these SNR gains can be directly increased with larger RIS areas. For example, a single 1,600-element RIS with the same design is expected to provide 26 dB SNR gain for a similar deployment (theoretical estimation). These results draw useful insights into the design and performance of RIS systems and provide an important proof for their potential gains in real-world far-field wireless communication environments.

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Section: B Prior Work On Reconfigurable Intelligent Surfacesmentioning

confidence: 99%

Section: B Prior Work On Reconfigurable Intelligent Surfacesmentioning

confidence: 99%

Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment

Trichopoulos

Theofanopoulos

Kashyap

et al. 2022

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

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“…As illustrated in Fig. 1(b), according to [9], each antenna empowered STAR-IOS cell actually consists of two antenna elements, which are connected by a tunable delay line (waveguide). The antenna elements facing the incident wave operate similarly to the reflectingonly RIS elements but a certain fraction of the incident energy is transferred along the delay lines and it is re-radiated into the transmission space.…”

Section: Hardware Implementations For Star-iossmentioning

confidence: 99%

Simultaneously Transmitting and Reflecting Intelligent Omni-Surfaces: Modeling and Implementation

Liu

et al. 2022

IEEE Veh. Technol. Mag.

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Given the rapid development of advanced electromagnetic manipulation technologies, researchers have turned their attentions to the investigation of smart surfaces for enhancing the radio coverage. Simultaneously transmitting and reflecting intelligent omni-surfaces (STAR-IOSs) constitute one of the most promising categories. Although previous research contributions have demonstrated the benefits of STAR-IOSs in terms of its wireless communication performance gains, several important issues remain unresolved, including both their practical hardware implementations and their accurate physical models. In this paper, we address these issues by discussing four practical hardware implementations of STAR-IOSs, as well as three hardware modeling techniques and five channel modeling methods. We clarify the taxonomy of the smart surface technologies in support of further investigating the family of STAR-IOSs.

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“…Specifically, RIS is a reflecting/refracting surface composed of numerous low-cost passive elements, each of which is capable of adjusting the amplitude and/or phase of the incident signal independently via a controller connected to the base station (BS). Owing to the above benefits, substantial research efforts have been invested in the design of RIS-aided communication systems, including full-duplex systems [6], unmanned aerial vehicle (UAV) aided [7], [8] and mmWave communication [9]- [14], etc. In [9], the authors exploited the refraction capability of RISs and developed a RIS-tiled wall for intelligently transitting the signal from an outdoor BS to indoor user equipment, which increases the chance of high-integrity outdoor-to-indoor communication.…”

mentioning

confidence: 99%

“…Owing to the above benefits, substantial research efforts have been invested in the design of RIS-aided communication systems, including full-duplex systems [6], unmanned aerial vehicle (UAV) aided [7], [8] and mmWave communication [9]- [14], etc. In [9], the authors exploited the refraction capability of RISs and developed a RIS-tiled wall for intelligently transitting the signal from an outdoor BS to indoor user equipment, which increases the chance of high-integrity outdoor-to-indoor communication. As a further advance, in [12], the authors harnessed the RIS as a reflection-type surface and studied a point-to-point RIS-aided mmWave system relying on hybrid precoding/combining, where a manifold optimization based algorithm was developed for maximizing the spectral efficiency.…”

mentioning

confidence: 99%

RIS-Aided Hybrid Massive MIMO Systems Relying on Adaptive-Resolution ADCs: Robust Beamforming Design and Resource Allocation

Wang

Chen

Hanzo

2022

IEEE Trans. Veh. Technol.

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The large-scale multiple-input multiple-output (MI-MO) uplink is investigated in the presence of channel-induced uncertainty, where variable-resolution analog-to-digital converters (ADCs) are used at the base station (BS) and a reconfigurable intelligent surface (RIS) is employed for supporting communications between the single-antenna users and the multiantenna BS. We formally maximize the system throughput by jointly optimizing the ADC's resolution, the transmit power, the passive reflection coefficients of the RIS and the hybrid combiner of the BS subject to practical constraints under statistical cascaded channel state information (CSI) error model. The robust nonconvex optimization problem is firstly decoupled via the classic Lagrangian dual transform and fractional programming method, followed by a powerful decoupling-based alternating maximization (D-AltMax) algorithm to solve this challenging problem. Our simulation results reveal the supremacy of our proposed algorithm over the benchmark schemes by quantifying the improved system throughput of this robust design.

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Modeling RIS Empowered Outdoor-to-Indoor Communication in mmWave Cellular Networks

Cited by 30 publications

References 52 publications

Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment

Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment

Simultaneously Transmitting and Reflecting Intelligent Omni-Surfaces: Modeling and Implementation

RIS-Aided Hybrid Massive MIMO Systems Relying on Adaptive-Resolution ADCs: Robust Beamforming Design and Resource Allocation

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