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arxiv: 2604.16885 · v1 · submitted 2026-04-18 · 💻 cs.IT · math.IT

Anti-Jamming Optimization for EM-Compliant Active RIS via Decoupling Architecture

Yang Cao , Wenchi Cheng , Jingqing Wang , Lifeng Wang This is my paper

Pith reviewed 2026-05-10 06:51 UTC · model grok-4.3

classification 💻 cs.IT math.IT
keywords anti-jammingactive RISmutual couplingdecoupling architecturealternating optimizationergodic achievable rateEM-compliant modelreconfigurable intelligent surface
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The pith

Decoupling architecture converts coupled active RIS electromagnetic effects into an uncoupled form that supports low-complexity anti-jamming optimization.

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

Active reconfigurable intelligent surfaces can reshape wireless channels to resist jamming, yet realistic hardware introduces mutual coupling and impedance effects that complicate design. The paper builds an electromagnetic-compliant model for active RIS that includes these physical details along with discrete phase shifts and channel correlations. It then applies a decoupling architecture to remove the mutual coupling among elements, converting the original entangled system into a simpler uncoupled representation. An alternating optimization algorithm then maximizes the ergodic achievable rate on this simpler model. A sympathetic reader would care because the method promises to make practical RIS anti-jamming designs computationally feasible without sacrificing the essential electromagnetic behavior.

Core claim

The paper establishes that an EM-compliant active RIS model, which incorporates mutual coupling effects, channel correlation, and discrete phase shifts, permits maximization of the ergodic achievable rate through a decoupling architecture that explicitly eliminates mutual coupling among reflecting elements. This transforms the originally coupled system into a tractable and scalable uncoupled representation, which an alternating optimization algorithm can then solve efficiently.

What carries the argument

The decoupling architecture, which removes mutual coupling effects among reflecting elements to produce an uncoupled system representation suitable for alternating optimization.

If this is right

  • Modeling and optimization complexity is substantially reduced compared with handling the full coupled system.
  • The alternating optimization algorithm converges with markedly fewer iterations.
  • The approach directly accounts for electromagnetic properties including mutual coupling and impedance mismatches while remaining scalable.
  • Numerical evaluations confirm that the resulting designs maintain competitive anti-jamming rates.

Where Pith is reading between the lines

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

  • If the decoupling holds under measured hardware conditions, the same architecture could be applied to other RIS objectives such as secrecy rate or energy efficiency.
  • The reduced iteration count suggests the method may support periodic re-optimization in slowly time-varying jamming environments.
  • Hardware prototypes could test whether the uncoupled approximation remains accurate when element spacing or frequency changes.

Load-bearing premise

The decoupling architecture accurately converts the coupled electromagnetic system into an uncoupled representation without materially changing the achievable rates or anti-jamming performance under realistic conditions.

What would settle it

A direct comparison of the ergodic rate achieved by the decoupling-architecture design against the rate obtained from a full electromagnetic simulation of the original coupled RIS under the same jamming signal; a substantial gap would falsify the claim that the transformation preserves performance.

Figures

Figures reproduced from arXiv: 2604.16885 by Jingqing Wang, Lifeng Wang, Wenchi Cheng, Yang Cao.

Figure 1
Figure 1. Figure 1: Multiport model of EMC-Active RIS with a decoupling ar [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Convergence with fixed EMC-Active RIS size. [PITH_FULL_IMAGE:figures/full_fig_p010_2.png] view at source ↗
Figure 5
Figure 5. Figure 5: The ergodic achievable rate Re versus the number M of REs, where ds = λc/4. with the baseline method (the S-OPT algorithm in [11]) in terms of convergence behavior and computational complexity uunder different values of the number of REs M and the inter￾element spacing ds. As illustrated in [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: The ergodic achievable rate Re versus the jamming power budget PJ,max, where ds = λc/4. 50 100 150 200 250 300 10 12 14 16 18 20 22 [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: The ergodic achievable rate Re versus the Y-axis coordinate of active RIS, where ds = λc/4. number of elements, yielding increasing array gains, but be￾comes inadequate as more REs are added, leading to reduced per-RE amplification. This result reveals a fundamental trade￾off between the amplification power budget and the reflection amplitude constraint, underscoring the importance of jointly selecting PA,… view at source ↗
read the original abstract

Wireless communication systems are increasingly vulnerable to sophisticated jamming attacks with the rapid evolution of jamming technologies and advanced signal processing techniques. While traditional anti-jamming techniques offer limited performance gains, active reconfigurable intelligent surfaces (RISs) have emerged as a promising channel-domain solution for improving resilience against jamming. Nonetheless, existing studies often rely on simplified electromagnetic (EM) models that do not fully capture mutual coupling (MC) and impedance mismatches in RIS hardware. In this paper, we propose an EM-compliant active (EMC-Active) RIS model for anti-jamming systems, explicitly incorporating the EM and physical properties at active RIS, such as MC effects, channel correlation, and discrete phase. To evaluate the anti-jamming performance of the proposed EMC-Active RIS, we develop a low-complexity alternating optimization (AO) algorithm based on the decoupling architecture (DA) to maximize the ergodic achievable rate. By leveraging the DA to explicitly eliminate MC effects among REs, the original coupled system is transformed into a tractable and scalable uncoupled representation. Numerical results demonstrate that the DA-based AO algorithm can significantly reduce the modeling and optimization complexity and efficiently solve the problem in an alternating manner with substantially reduced iteration overhead.

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 proposes an EM-compliant active RIS (EMC-Active RIS) model that incorporates mutual coupling (MC), impedance mismatches, channel correlation, and discrete phases for anti-jamming optimization. It introduces a decoupling architecture (DA) that eliminates MC effects to convert the coupled system into a tractable uncoupled representation, enabling a low-complexity alternating optimization (AO) algorithm that maximizes the ergodic achievable rate. Numerical results are presented to demonstrate that the DA-based AO significantly reduces modeling and optimization complexity while solving the problem with substantially lower iteration overhead compared to direct coupled approaches.

Significance. If the DA transformation is shown to be exact (or its approximation error is rigorously bounded) and the numerical gains hold under the full coupled EM model, the work offers a scalable framework for realistic active RIS deployment in jamming environments. The explicit incorporation of hardware EM effects and the complexity reduction via decoupling address practical limitations in prior simplified RIS models, potentially enabling efficient real-time optimization for larger RIS arrays.

major comments (2)
  1. [§3] §3 (Decoupling Architecture): The claim that DA 'explicitly eliminate[s] MC effects' and transforms the system 'without loss of essential anti-jamming performance' requires explicit proof that the ergodic rate and optimal beamforming vectors in the decoupled representation are identical (or within a quantifiable bound) to those of the original coupled EMC-Active RIS model. If the transformation involves any linearization or residual correlation neglect, the AO solution may be suboptimal when re-evaluated in the coupled domain.
  2. [Numerical Results] Numerical Results section: All reported rate and complexity gains are obtained exclusively in the decoupled domain. A direct comparison (e.g., Table or Figure) of the DA-AO solution re-evaluated under the original coupled MC/impedance model versus a baseline coupled optimizer is needed to confirm that complexity reduction does not come at the expense of degraded anti-jamming performance.
minor comments (2)
  1. [Abstract/Introduction] The abstract and introduction should explicitly state whether the DA is an exact equivalence or an approximation, including any assumptions on far-field conditions or negligible higher-order coupling terms.
  2. [System Model] Notation for the active RIS reflection matrix and the decoupling transformation matrix should be introduced with a clear mapping to the physical EM parameters (e.g., impedance matrix Z) to aid reproducibility.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed comments, which highlight important aspects of rigor and validation for the decoupling architecture. We address each major comment below and will revise the manuscript to incorporate additional proofs and numerical comparisons as suggested.

read point-by-point responses

  1. Referee: [§3] §3 (Decoupling Architecture): The claim that DA 'explicitly eliminate[s] MC effects' and transforms the system 'without loss of essential anti-jamming performance' requires explicit proof that the ergodic rate and optimal beamforming vectors in the decoupled representation are identical (or within a quantifiable bound) to those of the original coupled EMC-Active RIS model. If the transformation involves any linearization or residual correlation neglect, the AO solution may be suboptimal when re-evaluated in the coupled domain.

    Authors: We thank the referee for this observation. In the derivation of the decoupling architecture in Section 3, the mutual coupling matrix is explicitly inverted and absorbed into redefined effective channels and beamforming variables, yielding an exactly equivalent uncoupled representation under the stated EM-compliant model (no linearization or neglected correlations are introduced). The ergodic rate objective is preserved identically because the transformation is bijective. We will add a dedicated proof subsection (or appendix) in the revision that formally shows equivalence of the achievable rates and the one-to-one correspondence of optimal solutions between the coupled and decoupled domains. revision: yes

  2. Referee: [Numerical Results] Numerical Results section: All reported rate and complexity gains are obtained exclusively in the decoupled domain. A direct comparison (e.g., Table or Figure) of the DA-AO solution re-evaluated under the original coupled MC/impedance model versus a baseline coupled optimizer is needed to confirm that complexity reduction does not come at the expense of degraded anti-jamming performance.

    Authors: We agree that re-evaluation under the original coupled model is necessary for complete validation. In the revised Numerical Results section, we will include new experiments that take the DA-AO solutions and evaluate them directly in the full coupled EM model (including MC and impedance mismatches). We will also add a baseline coupled optimizer (e.g., via alternating optimization without decoupling) for direct comparison of achieved ergodic rates and iteration counts, thereby quantifying any performance-complexity trade-off. revision: yes

Circularity Check

0 steps flagged

No circularity: decoupling presented as modeling transformation, not tautological reduction

full rationale

The derivation introduces an EM-compliant model that includes mutual coupling, impedance mismatch, and discrete phases as inputs. The decoupling architecture is then applied as an explicit transformation to remove MC effects and obtain an uncoupled representation, after which an alternating optimization algorithm maximizes the ergodic rate in the resulting domain. Numerical results are reported as empirical validation of complexity reduction in that domain. No equation or claim reduces a performance metric or prediction to a parameter fitted from the same metric; the DA step is not defined in terms of the rate it optimizes, nor does any uniqueness theorem or ansatz rely on self-citation chains. The chain remains self-contained against external EM benchmarks and does not collapse by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on an EM model that incorporates mutual coupling and impedance mismatches as given physical properties, plus the assumption that the decoupling architecture preserves the essential performance metrics. No free parameters are explicitly named in the abstract, but the discrete phase and channel correlation terms are treated as inputs.

axioms (2)
  • domain assumption Mutual coupling and impedance mismatches must be explicitly modeled for active RIS hardware to be EM-compliant.
    Stated in the abstract as the motivation for the new model.
  • ad hoc to paper The decoupling architecture can transform the coupled system into a tractable uncoupled representation without loss of essential anti-jamming performance.
    Core modeling step that enables the low-complexity AO algorithm.

pith-pipeline@v0.9.0 · 5513 in / 1344 out tokens · 22190 ms · 2026-05-10T06:51:26.442304+00:00 · methodology

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