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arxiv: 2604.10120 · v1 · submitted 2026-04-11 · 📡 eess.SP

Bistatic Integrated Sensing and Communication in the Presence of a Disco Reconfigurable Intelligent Surface: Disruption, Enhancement, or Both?

Huan Huang , Hongliang Zhang , Weidong Mei , Minghui Min , Dusit Niyato , Zhu Han This is my paper

Pith reviewed 2026-05-10 15:54 UTC · model grok-4.3

classification 📡 eess.SP
keywords integrated sensing and communicationreconfigurable intelligent surfacebistatic systemactive channel agingSINR lower boundCramer-Rao lower boundangle of arrivalangle of departure
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The pith

A disco reconfigurable intelligent surface disrupts communication in bistatic ISAC systems but improves angle of arrival sensing accuracy while worsening angle of departure accuracy.

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

This paper studies a bistatic system that performs both wireless communication and sensing at the same time when a special reconfigurable surface is present. The surface, called a disco reconfigurable intelligent surface, has reflection coefficients that change randomly and quickly over time. This breaks the usual assumption that the wireless channels stay stable long enough for the system to work well. The analysis shows that the changing surface adds interference that lowers the quality of the communication link. For sensing, it makes it harder to accurately estimate the direction from which signals are sent out but easier to estimate the direction from which they arrive.

Core claim

The DRIS with random time-varying reflection coefficients induces active channel aging that leads to a lower bound on the communication SINR and closed-form expressions for the CRLB of sensing parameters, specifically degrading communication performance and AoD estimation accuracy while enhancing AoA estimation accuracy.

What carries the argument

The disco reconfigurable intelligent surface (DRIS) with its random and time-varying reflection coefficients that produce active channel aging (ACA) in the involved channels.

Load-bearing premise

The reflection coefficients on the DRIS change randomly and independently from one time slot to the next, enabling closed-form derivation of the active channel aging statistics.

What would settle it

Experimental measurement in a lab setup of a bistatic ISAC system equipped with a physical DRIS prototype, checking whether the observed SINR drops and the opposing changes in AoA and AoD CRLBs match the derived bounds.

Figures

Figures reproduced from arXiv: 2604.10120 by Dusit Niyato, Hongliang Zhang, Huan Huang, Minghui Min, Weidong Mei, Zhu Han.

Figure 1
Figure 1. Figure 1: Illustration of a bistatic ISAC system with a bistatic radar configuration [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Average achievable sum rate vs. total transmit power for different [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Mean Square Error (MSE) of (a) AoD (θ1) and (b) AoA (θ2) estimates versus total transmit power for different ISAC waveforms under MLE [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Average achievable sum rate vs. number of DRIS elements for different [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Mean Square Error (MSE) of (a) AoD (θ1) and (b) AoA (θ2) estimates versus number of DRIS elements for different ISAC waveforms under MLE [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Average achievable sum rate vs. distance between ISAC BS and DRIS [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Mean Square Error (MSE) of (a) AoD (θ1) and (b) AoA (θ2) estimates versus distance between ISAC BS and DRIS for different ISAC waveforms under MLE. V. CONCLUSIONS In this work, we have investigated the impact of a DRIS on bistatic ISAC systems. To the best of our knowledge, this is the first time that the impact of a DRIS on bistatic ISAC systems has been quantitatively characterized. Specifically, we have… view at source ↗
read the original abstract

Integrated sensing and communication (ISAC) is widely regarded as one of the key enabling technologies for future sixth-generation (6G) wireless communication systems. In this work, we investigate a bistatic ISAC system in the presence of a disco reconfigurable intelligent surface (DRIS), whose random and time-varying reflection coefficients emulate a "disco ball." The introduction of the DRIS breaks the underlying assumption in existing ISAC systems that the sensing and communication channels remain static or quasi-static within the channel coherence time. We first develop a bistatic system model incorporating the DRIS and characterize all involved wireless channels. Then, an ISAC waveform design that balances sensing and communication performance is proposed by formulating a Pareto optimization problem, where the trade-off is controlled through a tunable factor. Communication and sensing performance in the bistatic ISAC system are quantified by the signal-to-interference-plus-noise ratio (SINR) and the Cramer-Rao lower bound (CRLB), respectively. To quantify the impact of the DRIS on the bistatic ISAC system, we derive the statistical characteristics of DRIS-induced active channel aging (ACA) channels for communications and the cascaded DRIS-based sensing channel. Then, we establish a theoretical lower bound on the SINR and closed-form CRLB expressions in the presence of a DRIS. The analysis reveals several distinctive properties of the DRIS in bistatic ISAC systems. In particular, the DRIS degrades communication performance significantly due to the introduction of ACA interference. In contrast, with respect to sensing performance, the DRIS decreases the estimation accuracy of the angle of departure (AoD) while concurrently enhancing that of the angle of arrival (AoA). Numerical results validate the derived theoretical analysis and confirm these DRIS-induced behaviors.

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

2 major / 2 minor

Summary. The paper analyzes a bistatic ISAC system with a disco reconfigurable intelligent surface (DRIS) whose reflection coefficients vary randomly and independently over time, emulating a disco ball and inducing active channel aging (ACA). It characterizes the resulting channels, proposes a Pareto-optimal waveform design with a tunable trade-off factor, derives a closed-form lower bound on communication SINR due to ACA interference, and obtains closed-form CRLB expressions for sensing that show the DRIS reduces AoD estimation accuracy while improving AoA accuracy. Numerical results are presented to validate the bounds and the opposing performance impacts.

Significance. If the independent random time-variation model for the DRIS holds, the closed-form SINR bound and CRLB derivations provide concrete, analytically tractable insights into how dynamic surfaces can produce opposing effects on communication and sensing in bistatic ISAC, which could inform 6G waveform and surface design. The explicit statistical characterization of the cascaded DRIS sensing channel and ACA channels is a technical strength that enables the performance claims.

major comments (2)
  1. [Channel characterization and subsequent bound derivations] Channel characterization and bound derivation sections: The SINR lower bound and CRLB expressions rest on the assumption that DRIS reflection coefficients vary randomly and independently over time to produce the ACA statistics and cascaded channel distributions. The manuscript should include either hardware-motivated justification for this model or a sensitivity analysis showing how temporal correlation or periodicity would alter the interference covariance and Fisher information matrix entries, since any deviation directly changes the claimed degradation in SINR and the opposing AoD/AoA effects.
  2. [Numerical results] Numerical validation section: The simulations are stated to validate the closed-form expressions, but the manuscript does not report how the random coefficient realizations are generated (e.g., distribution parameters, independence enforcement) or include error bars/confidence intervals on the Monte-Carlo curves. This makes it difficult to confirm that the plotted SINR and CRLB curves match the derived bounds without post-hoc fitting.
minor comments (2)
  1. [Abstract] The abstract and introduction could explicitly list the key system parameters (e.g., number of antennas, DRIS elements, carrier frequency) used in the derivations to improve readability.
  2. [System model] Notation for the tunable Pareto factor and the ACA channel matrices should be introduced with a single consistent symbol table or early definition to avoid ambiguity when moving between communication and sensing analyses.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback and positive assessment of the technical contributions regarding the opposing impacts of the DRIS on communication and sensing. We address each major comment below and outline the revisions planned for the next version of the manuscript.

read point-by-point responses

  1. Referee: [Channel characterization and subsequent bound derivations] Channel characterization and bound derivation sections: The SINR lower bound and CRLB expressions rest on the assumption that DRIS reflection coefficients vary randomly and independently over time to produce the ACA statistics and cascaded channel distributions. The manuscript should include either hardware-motivated justification for this model or a sensitivity analysis showing how temporal correlation or periodicity would alter the interference covariance and Fisher information matrix entries, since any deviation directly changes the claimed degradation in SINR and the opposing AoD/AoA effects.

    Authors: We agree that the independent random time-variation model is foundational to the closed-form SINR bound and CRLB derivations. The model is introduced to emulate the rapid, unpredictable changes of a disco ball, breaking the quasi-static channel assumption typical in ISAC literature. In the revised manuscript, we will expand the system model section with additional hardware motivation drawn from practical RIS implementations featuring fast phase switching, and we will add a sensitivity analysis subsection that examines how introducing temporal correlation affects the interference covariance matrix and the Fisher information matrix entries, thereby confirming the robustness of the reported degradation in SINR and the opposing AoD/AoA estimation effects. revision: partial

  2. Referee: [Numerical results] Numerical validation section: The simulations are stated to validate the closed-form expressions, but the manuscript does not report how the random coefficient realizations are generated (e.g., distribution parameters, independence enforcement) or include error bars/confidence intervals on the Monte-Carlo curves. This makes it difficult to confirm that the plotted SINR and CRLB curves match the derived bounds without post-hoc fitting.

    Authors: We appreciate this observation on reproducibility. The DRIS reflection coefficients are generated as independent and identically distributed uniform random phases over [0, 2π) for each element and each time slot. In the revised manuscript, we will explicitly document this generation process, including the independence enforcement, in the numerical results section. Additionally, we will include error bars (representing one standard deviation across Monte Carlo trials) on all relevant curves to allow direct visual confirmation of the agreement between the simulated results and the derived analytical bounds. revision: yes

Circularity Check

0 steps flagged

No circularity: derivation proceeds from posited DRIS model to closed-form statistics and bounds

full rationale

The paper posits a DRIS model whose reflection coefficients vary randomly and independently over time, then derives the statistical properties of the induced ACA channels and cascaded sensing channel directly from this assumption. The SINR lower bound and CRLB expressions follow mathematically from those statistics and the standard bistatic ISAC signal model. No step reduces a claimed prediction to a fitted parameter by construction, invokes a self-citation as the sole justification for a uniqueness or ansatz claim, or renames a known result. The opposing effects on AoD versus AoA accuracy are consequences of the derived Fisher information matrix entries under the stated model rather than being presupposed. The chain is therefore self-contained given the initial modeling assumptions.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 1 invented entities

The central claims rest on standard far-field wireless propagation models plus the new statistical characterization of DRIS-induced ACA; one tunable trade-off parameter appears in the Pareto formulation.

free parameters (1)
  • tunable factor in Pareto optimization
    Controls the balance between sensing and communication objectives in the waveform design problem.
axioms (2)
  • standard math Wireless channels are modeled under far-field assumptions with additive white Gaussian noise.
    Invoked when defining SINR and CRLB expressions.
  • domain assumption DRIS reflection coefficients vary randomly and independently across time and elements.
    Required to derive the statistical properties of ACA channels and cascaded sensing channel.
invented entities (1)
  • Disco reconfigurable intelligent surface (DRIS) no independent evidence
    purpose: Models a RIS whose reflection coefficients change randomly over time to emulate a disco ball.
    New postulated surface behavior introduced to break the static-channel assumption.

pith-pipeline@v0.9.0 · 5646 in / 1565 out tokens · 22449 ms · 2026-05-10T15:54:10.288238+00:00 · methodology

discussion (0)

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