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arxiv: 2604.28044 · v1 · submitted 2026-04-30 · 📡 eess.SP

Experimental Performance of a 5G N78 Reconfigurable Intelligent Surface: From Controlled Measurements to Commercial Network Deployment

Sefa Kayrakl{\i}k , Samed Ke\c{s}ir , Batuhan Kaplan , Ahmet Muaz Akta\c{s} , Emre Arslan , Ahmet Faruk Coskun This is my paper

Pith reviewed 2026-05-07 06:55 UTC · model grok-4.3

classification 📡 eess.SP
keywords reconfigurable intelligent surface5G N78 bandcoverage enhancementnon-line-of-sightcommercial network deploymentRSRPSINRexperimental validation
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The pith

A reconfigurable intelligent surface placed in a live 5G network restores connectivity and raises signal quality in zones that previously had no service.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper tests a modular RIS designed for the 5G N78 band through three successive stages: controlled indoor measurements, long-range outdoor trials, and placement inside an operating commercial 5G standalone network. Baseline drive tests first locate a non-line-of-sight region where users cannot connect; the RIS is then positioned to reflect signals into that region. Recorded results show higher reference signal received power and better signal-to-interference-plus-noise ratio at multiple test points, together with full 5G service restoration at locations that had none before the surface was installed.

Core claim

The central claim is that the modular RIS prototype, once installed in the commercial network, delivers measurable coverage gains inside the identified NLoS zone and re-establishes 5G connectivity at user locations that baseline testing showed to be unreachable, with the improvements appearing in both RSRP and SINR values.

What carries the argument

The modular reconfigurable intelligent surface prototype tuned to reflect and phase-align 5G N78 signals from the base station toward blocked user locations.

If this is right

  • One RIS unit can fill a coverage hole that would otherwise require a new base station.
  • The staged validation sequence (indoor, outdoor, then live network) supplies repeatable performance baselines before commercial use.
  • Service becomes available at previously unreachable points once the surface is aligned to the NLoS zone.
  • Both received power and signal-quality metrics improve under the same deployment conditions.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Dynamic phase control could be added so the same surface adapts to moving users without manual repositioning.
  • Multiple nearby gaps might be served by a single larger surface if its reflection pattern can be split.
  • Integration with the operator's existing network-management system would allow the RIS to be turned on only when the baseline drive tests show a gap.

Load-bearing premise

The recorded rises in signal strength and the return of service are produced by the RIS reflection rather than by changes in traffic load, weather, or the timing of the measurements.

What would settle it

Repeating the drive-test route with the RIS powered off or physically removed should cause the original coverage gaps and zero-service locations to reappear at the same coordinates.

Figures

Figures reproduced from arXiv: 2604.28044 by Ahmet Faruk Coskun, Ahmet Muaz Akta\c{s}, Batuhan Kaplan, Emre Arslan, Samed Ke\c{s}ir, Sefa Kayrakl{\i}k.

Figure 1
Figure 1. Figure 1: N78 RIS prototype structure and capacity. Compared to mmWave, N78 signals experience lower path loss and improved penetration, enabling wider connectivity and more robust performance in practical cases [8], [9]. The propagation environment at C-band is typically rich in scattering, with multiple reflections, and diffractions contributing to more stable signal reception, and the path loss exponent in line-o… view at source ↗
Figure 2
Figure 2. Figure 2: Indoor RIS-assisted communication Mobile CPE is utilized on the receiver side, which is equipped with the Qualcomm Snapdragon X55 5G chipset. During the measurement, KPI records are monitored for the RIS-on and RIS-off cases. Among the various KPIs, Received Signal Strength Indicator (RSSI), RSRP, Reference Signal Received Quality (RSRQ), and SINR are collected to demonstrate the efficiency of the 5G NR si… view at source ↗
Figure 4
Figure 4. Figure 4: Top view of the RIS-free site survey showing the network nodes and view at source ↗
Figure 5
Figure 5. Figure 5: Top view of the RIS-assisted 5G wireless communications scenario view at source ↗
Figure 6
Figure 6. Figure 6: Indoor RIS-assisted communication measurement results view at source ↗
Figure 9
Figure 9. Figure 9: Comparison of RSRP and SINR measured at fixed CPE/UE points view at source ↗
read the original abstract

This paper presents a real-world experimental analysis of a modular reconfigurable intelligent surface (RIS) prototype designed to operate in the 5G N78 band. Unlike most RIS studies in the literature that focus on simulations or controlled setups, the proposed system is validated through three phases consisting of indoor measurements, outdoor long-range tests, and deployment in a live commercial 5G standalone network. The RIS is exploited to enhance coverage in a non-line-of-sight (NLoS) zone, identified through baseline drive tests. Results show promising gains in RSRP and SINR, while also restoring 5G service at user locations where access was previously not available. The results highlight the practical potential of RIS for coverage enhancement in operational 5G networks.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 2 minor

Summary. This paper reports experimental results for a reconfigurable intelligent surface (RIS) prototype operating in the 5G N78 frequency band. The study encompasses three phases: indoor controlled measurements, outdoor long-range propagation tests, and a deployment in an operational commercial 5G standalone network. The RIS is used to improve coverage in a non-line-of-sight (NLoS) region previously identified by drive tests. The authors claim improvements in RSRP and SINR metrics and the restoration of 5G connectivity in areas where service was previously unavailable.

Significance. The significance lies in the transition from laboratory and simulated environments to a live commercial network deployment, which is relatively rare in the RIS literature. This provides practical insights into the feasibility of using RIS for coverage extension in 5G systems. The modular design and focus on the N78 band (3.5 GHz) align with current 5G deployments, potentially informing future standardization and implementation efforts. The multi-stage validation approach is a positive aspect.

major comments (1)
  1. [§5 (Commercial Network Deployment)] §5 (Commercial Network Deployment): The central empirical claim—that the RIS is responsible for the observed gains in RSRP, SINR, and service restoration—relies on a before-and-after comparison of drive tests without reported controls for confounding variables (e.g., temporal changes in traffic load, weather, or network configuration). No on/off RIS toggling experiments under matched conditions or quantitative statistical analysis (error bars, confidence intervals) are described to isolate the RIS contribution. This is load-bearing for the paper's conclusion regarding practical deployment benefits.
minor comments (2)
  1. [Abstract] The abstract refers to 'promising gains' without specifying the magnitude of improvements in RSRP or SINR or the number of measurement points, which would strengthen the summary.
  2. [Figures] Ensure that all figures showing measurement locations or results include clear legends, scale bars, and error indicators where applicable.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the positive evaluation of the paper's significance and for the constructive major comment. We address the concern regarding the isolation of RIS effects in the commercial deployment section below, with a commitment to textual revisions that clarify limitations without overstating the results.

read point-by-point responses

  1. Referee: [§5 (Commercial Network Deployment)] §5 (Commercial Network Deployment): The central empirical claim—that the RIS is responsible for the observed gains in RSRP, SINR, and service restoration—relies on a before-and-after comparison of drive tests without reported controls for confounding variables (e.g., temporal changes in traffic load, weather, or network configuration). No on/off RIS toggling experiments under matched conditions or quantitative statistical analysis (error bars, confidence intervals) are described to isolate the RIS contribution. This is load-bearing for the paper's conclusion regarding practical deployment benefits.

    Authors: We agree that a live commercial network presents inherent challenges for rigorous isolation of the RIS contribution. On/off toggling experiments were not feasible due to operator restrictions on service disruption and the need for continuous network operation during the trial window. The before-and-after drive tests were conducted over a short period with no other documented network changes, and the observed gains are consistent in magnitude and direction with the controlled indoor and outdoor measurements reported in earlier sections. We will revise §5 to include an explicit discussion of potential confounders (traffic load, weather, and configuration changes), note the absence of toggling data as a methodological limitation, and incorporate available variability measures (e.g., standard deviations across repeated runs) from the drive-test dataset. Full confidence-interval analysis would require additional data collection that was outside the scope of the commercial trial. revision: partial

Circularity Check

0 steps flagged

No circularity: purely experimental reporting with no derivations or self-referential claims

full rationale

The paper consists of three phases of hardware measurements (indoor controlled tests, outdoor long-range tests, and live commercial 5G network deployment) that directly compare RSRP, SINR, and service availability before and after RIS installation in an identified NLoS zone. No equations, models, fitted parameters, or mathematical derivations appear in the described structure or abstract. Claims rest on empirical observations rather than any chain that reduces predictions to inputs by construction. No self-citations are invoked to justify uniqueness theorems or ansatzes, and no renaming of known results occurs. The report is therefore self-contained as measurement data; potential confounding factors in the commercial phase affect causal attribution but do not constitute circularity in any derivation.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The work is purely experimental and invokes only standard electromagnetic propagation assumptions already established in the wireless-communications literature. No free parameters, ad-hoc axioms, or new physical entities are introduced in the abstract.

axioms (1)
  • standard math Standard electromagnetic reflection and phase-shift principles govern RIS behavior at N78 frequencies.
    This background assumption is required for any RIS to function but is not derived or tested within the paper.

pith-pipeline@v0.9.0 · 5459 in / 1407 out tokens · 85470 ms · 2026-05-07T06:55:35.669456+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

16 extracted references

  1. [1]

    NR; Base Station (BS) Radio Transmission and Reception,

    3GPP, “NR; Base Station (BS) Radio Transmission and Reception,” 3rd Generation Partnership Project (3GPP), Tech. Rep. TS 38.104, 2025

    2025

  2. [2]

    Wireless communications through reconfigurable intelligent surfaces,

    E. Basar, M. D. Renzo, J. de Rosny, M. Debbah, M.-S. Alouini, and R. Zhang, “Wireless communications through reconfigurable intelligent surfaces,”IEEE Access, vol. 7, pp. 116 753–116 773, 2019

    2019

  3. [3]

    Intelligent reflecting surface-aided wireless communications: A tutorial,

    Q. Wu, S. Zhang, B. Zheng, C. You, and R. Zhang, “Intelligent reflecting surface-aided wireless communications: A tutorial,”IEEE Transactions on Communications, vol. 69, no. 5, pp. 3313–3351, May 2021

    2021

  4. [4]

    Reconfigurable intelligent surface-based wireless communications: Antenna design, pro- totyping, and experimental results,

    L. Dai, B. Wang, M. Wang, X. Yang, J. Tan, S. Bi, S. Xu, F. Yang, Z. Chen, M. D. Renzo, C.-B. Chae, and L. Hanzo, “Reconfigurable intelligent surface-based wireless communications: Antenna design, pro- totyping, and experimental results,”IEEE Access, vol. 8, pp. 45 913– 45 923, 2020

    2020

  5. [5]

    Reconfigurable intelligent surface (RIS) in the sub- 6 GHz band: Design, implementation, and real-world demonstration,

    A. Araghi, M. Khalily, M. Safaei, A. Bagheri, V . Singh, F. Wang, and R. Tafazolli, “Reconfigurable intelligent surface (RIS) in the sub- 6 GHz band: Design, implementation, and real-world demonstration,” IEEE Access, 2022

    2022

  6. [6]

    Reconfigurable intelligent surface identification in mobile networks: Opportunities and challenges,

    E. Arslan, A. T. Dogukan, F. Kilinc, A. F. Coskun, and E. Basar, “Reconfigurable intelligent surface identification in mobile networks: Opportunities and challenges,”IEEE Wireless Communications, vol. 32, no. 4, pp. 132–139, 2025

    2025

  7. [7]

    N78 frequency band modular RIS design and implementation,

    S. Kayraklık, R. Bas,, H. O. C ¸ alıs ¸kan, S. S ¸ahino˘glu, S. Erdo ˘gan, ˙I. ¨Unal, ˙I. H ¨okelek, K. Nurdan, and A. G ¨orc ¸in, “N78 frequency band modular RIS design and implementation,” in2025 55th European Microwave Conference (EuMC), 2025, pp. 795–798

    2025

  8. [8]

    Massive MIMO in sub-6 GHz and mmWave: Physical, practical, and use-case differences,

    E. Bjornson, L. Van der Perre, S. Buzzi, and E. G. Larsson, “Massive MIMO in sub-6 GHz and mmWave: Physical, practical, and use-case differences,”IEEE Wir. Commun., vol. 26, no. 2, pp. 100–108, 2019

    2019

  9. [9]

    Reconfigurable intelligent surfaces (RIS); study on propagation models and use cases,

    ETSI, “Reconfigurable intelligent surfaces (RIS); study on propagation models and use cases,” ETSI, Tech. Rep. GR RIS 003, 2025

    2025

  10. [10]

    Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming,

    Q. Wu and R. Zhang, “Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming,”IEEE Transactions on Wireless Communications, vol. 18, no. 11, pp. 5394–5409, 2019

    2019

  11. [11]

    Multi-scenario broadband channel measure- ment and modeling for sub-6 GHz RIS-assisted wireless communication systems,

    J. Sang, M. Zhou, J. Lan, B. Gao, W. Tang, X. Li, S. Jin, E. Basar, C. Li, Q. Cheng, and T. J. Cui, “Multi-scenario broadband channel measure- ment and modeling for sub-6 GHz RIS-assisted wireless communication systems,”IEEE Transactions on Wireless Communications, vol. 23, no. 6, pp. 6312–6329, 2024

    2024

  12. [12]

    Physical channel modeling for RIS-empowered wireless networks in sub-6 GHz bands,

    F. Kilinc, I. Yildirim, and E. Basar, “Physical channel modeling for RIS-empowered wireless networks in sub-6 GHz bands,” in2021 55th Asilomar Conf. Signals, Systems, and Computers, 2021, pp. 704–708

    2021

  13. [13]

    Indoor measurements for RIS-aided communication: Practical phase shift optimization, coverage enhancement, and physical layer security,

    S. Kayraklik, I. Yildirim, I. Hokelek, Y . Gevez, E. Basar, and A. Gorcin, “Indoor measurements for RIS-aided communication: Practical phase shift optimization, coverage enhancement, and physical layer security,” IEEE Open J. Commun. Soc., vol. 5, pp. 1243–1255, 2024

    2024

  14. [14]

    Path loss in reconfigurable intelligent surface-enabled channels,

    S. W. Ellingson, “Path loss in reconfigurable intelligent surface-enabled channels,” in2021 IEEE 32nd Annual International Symp. Personal, Indoor and Mobile Radio Commun. (PIMRC), 2021, pp. 829–835

    2021

  15. [15]

    NR; Overall description; Stage-2,

    3rd Generation Partnership Project (3GPP), “NR; Overall description; Stage-2,” 3GPP, Technical Specification TS 38.300, 2023

    2023

  16. [16]

    A tutorial on beam management for 3GPP NR at mmWave frequencies,

    M. Giordani, M. Polese, A. Roy, D. Castor, and M. Zorzi, “A tutorial on beam management for 3GPP NR at mmWave frequencies,”IEEE Communications Surveys & Tutorials, vol. 21, no. 1, pp. 173–196, 2019

    2019