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arxiv: 2605.16831 · v2 · pith:RCM5KJXOnew · submitted 2026-05-16 · 📡 eess.SP

Constellation-Independent Range Estimation in Payload-Based OFDM-ISAC

Dongil Yang , Kaitao Meng , Christos Masouros , Kawon Han This is my paper

Pith reviewed 2026-06-30 19:30 UTC · model grok-4.3

classification 📡 eess.SP
keywords OFDM-ISACrange estimationmismatched filtersidelobe suppressionCramér-Rao boundpayload-based sensingconstellation-independent
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The pith

A region-of-interest mismatched filter suppresses data-dependent sidelobes to achieve near-Cramér-Rao-bound ranging in payload-based OFDM-ISAC.

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

The paper establishes that a mismatched filter optimized over a chosen delay interval can remove the sidelobes created by varying communication symbols without needing to know those symbols. This yields range estimates whose mean-square error approaches the theoretical lower bound even when the modulation is not constant-modulus. An efficient closed-form solution is derived via the Woodbury identity, and the approach is shown to outperform both matched and reciprocal filters in analysis and simulation. Over-the-air tests confirm that the ranging accuracy holds for realistic OFDM waveforms.

Core claim

The ROI-MMF is designed to suppress sidelobes inside a prescribed delay region while keeping the mainlobe response intact. Its ranging mean-square error is shown to be lower than that of matched filtering and reciprocal filtering, and simulations across constellations demonstrate that the error approaches the Cramér-Rao bound, confirming that target ranging performance is preserved regardless of the non-constant-modulus payload symbols.

What carries the argument

The region-of-interest mismatched filter (ROI-MMF), which minimizes sidelobe energy inside a pre-chosen delay window while preserving the peak response at the target delay.

If this is right

  • Ranging MSE is theoretically lower than matched filtering and reciprocal filtering.
  • Performance approaches the Cramér-Rao bound for multiple different constellations.
  • Implementation cost grows only with the size of the chosen delay region.
  • The same receiver structure works for both constant- and non-constant-modulus modulations.

Where Pith is reading between the lines

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

  • If a coarse initial delay estimate is available, the region of interest could be updated adaptively in successive frames.
  • The same sidelobe-control idea may improve resolution when multiple targets fall inside the same coarse delay window.
  • Combining the filter output with standard OFDM channel estimation could allow joint sensing and data decoding without extra pilots.

Load-bearing premise

The target delay is guaranteed to lie inside a delay region that can be chosen in advance so the filter can be tuned without knowledge of the exact symbols or location.

What would settle it

Measure ranging mean-square error when the actual target delay is deliberately placed outside the prescribed region of interest; if the error remains near the Cramér-Rao bound the central claim fails.

Figures

Figures reproduced from arXiv: 2605.16831 by Christos Masouros, Dongil Yang, Kaitao Meng, Kawon Han.

Figure 1
Figure 1. Figure 1: Block diagram of the proposed constellation-independent OFDM [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Normalized range profiles of the MF, RF, and the proposed ROI-MMF [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 5
Figure 5. Figure 5: Measured range profiles of the MF, RF, and ROI-MMF receivers [PITH_FULL_IMAGE:figures/full_fig_p005_5.png] view at source ↗
read the original abstract

Orthogonal frequency division multiplexing (OFDM) is a key waveform for integrated sensing and communication (ISAC) due to its spectral efficiency and compatibility with modern wireless standards. In multi-target and clutter-rich environments, however, payload-based OFDM-ISAC can suffer from data-dependent sidelobes induced by non-constant-modulus modulation symbols. To overcome these limitations, this paper proposes a region-of-interest mismatched filter (ROI-MMF) that suppresses sidelobes within a prescribed delay region while preserving the mainlobe response. By leveraging the Woodbury identity, the proposed design admits an efficient closed-form implementation whose complexity scales with the ROI size rather than the number of subcarriers. We theoretically provide the ranging mean-square error (MSE) of the designed ROI-MMF, which shows the superior performance compared to conventional matched filtering (MF) and reciprocal filtering (RF) sensing receivers. Simulations across various constellations show that the proposed sensing receiver achieves a ranging MSE approaching the Cram\'er-Rao bound (CRB), which notably confirms that our design preserves the target ranging performance even under the non-constant-modulus constellation. Finally, the framework is experimentally validated with our over-the-air OFDM-ISAC testbed.

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 manuscript proposes a region-of-interest mismatched filter (ROI-MMF) for payload-based OFDM-ISAC that suppresses data-dependent sidelobes within a user-prescribed delay interval while preserving mainlobe gain. The design admits a closed-form solution via the Woodbury identity whose complexity depends on ROI size rather than subcarrier count. A theoretical expression for the ranging MSE of the ROI-MMF is derived and compared with matched filtering and reciprocal filtering; simulations across constellations demonstrate that the achieved MSE approaches the Cramér-Rao bound, and the method is validated on an over-the-air testbed.

Significance. If the theoretical MSE derivation and the simulation results hold, the work provides a practical route to constellation-agnostic ranging in ISAC systems that reuse communication payloads, removing a key obstacle to the use of high-order QAM or other non-constant-modulus formats in integrated sensing.

major comments (2)
  1. [Abstract / §1] Abstract and §1: the claim that the filter can be designed 'without knowledge of ... exact target location' rests on the assumption that an ROI containing the unknown delay can be prescribed a priori. No procedure is given for selecting or adapting this ROI when target delays are completely unknown a priori; if the ROI must be enlarged to the full delay grid, the sidelobe-suppression benefit is lost. This assumption is load-bearing for the constellation-independent claim.
  2. [§3] §3 (theoretical MSE): the derivation of the ranging MSE for the ROI-MMF is stated to be independent of the payload symbols, yet the filter coefficients themselves depend on the ROI choice. It is unclear whether the final MSE expression remains symbol-independent once the ROI is fixed, or whether an implicit dependence on the chosen interval remains.
minor comments (2)
  1. [§4] Figure captions and §4: the simulation setup (SNR range, number of Monte-Carlo trials, exact constellations tested) should be stated explicitly rather than summarized.
  2. [§2] Notation: the definition of the ROI matrix and its relation to the full delay grid should be introduced with an equation before the Woodbury application is invoked.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments. Below we respond point-by-point to the major comments and indicate planned revisions.

read point-by-point responses

  1. Referee: [Abstract / §1] Abstract and §1: the claim that the filter can be designed 'without knowledge of ... exact target location' rests on the assumption that an ROI containing the unknown delay can be prescribed a priori. No procedure is given for selecting or adapting this ROI when target delays are completely unknown a priori; if the ROI must be enlarged to the full delay grid, the sidelobe-suppression benefit is lost. This assumption is load-bearing for the constellation-independent claim.

    Authors: The ROI-MMF is constellation-independent because its coefficients are computed solely from the chosen ROI and the known OFDM parameters; they do not depend on the payload symbols. This property holds regardless of how the ROI is selected. We agree that the manuscript does not supply an explicit procedure for choosing or adapting the ROI when target delays are entirely unknown a priori. In practice the ROI would be set from system-level prior information (maximum expected range, regulatory constraints, etc.). We will add a short discussion in §1 clarifying this assumption and outlining two practical approaches: (i) a coarse matched-filter pre-scan to identify a reduced ROI, and (ii) a conservative full-grid ROI when no prior information exists (in which case sidelobe suppression is forfeited but symbol independence remains). revision: partial

  2. Referee: [§3] §3 (theoretical MSE): the derivation of the ranging MSE for the ROI-MMF is stated to be independent of the payload symbols, yet the filter coefficients themselves depend on the ROI choice. It is unclear whether the final MSE expression remains symbol-independent once the ROI is fixed, or whether an implicit dependence on the chosen interval remains.

    Authors: The MSE derivation in §3 is performed for any fixed ROI; once the ROI is chosen, the resulting closed-form MSE expression contains no dependence on the instantaneous payload symbols. The ROI appears explicitly in the expression through the Woodbury-based filter, but this is a deterministic design parameter, not a random variable tied to the data. We will insert a clarifying sentence at the beginning of the MSE subsection stating that symbol independence is conditional on a fixed ROI and will note that the ROI dependence is already visible in the filter definition. revision: yes

Circularity Check

0 steps flagged

No circularity; derivation uses standard mismatched-filter optimization and Woodbury identity with independent MSE analysis.

full rationale

The paper's core steps—ROI-MMF design via optimization, closed-form solution via Woodbury identity, and theoretical ranging MSE derivation—are presented as direct applications of standard linear algebra and estimation theory without reducing to self-citations, fitted parameters renamed as predictions, or self-definitional loops. The a-priori ROI prescription is an explicit modeling assumption rather than a hidden tautology in the equations; the MSE comparison to CRB, MF, and RF is derived independently and validated by simulation against external benchmarks. No load-bearing step collapses to its own inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The approach relies on standard linear algebra (Woodbury identity) and mismatched filter optimization; no free parameters, invented entities, or ad-hoc axioms are evident from the abstract.

axioms (1)
  • standard math Woodbury matrix identity for efficient inversion of low-rank updates
    Invoked to obtain closed-form implementation whose complexity scales with ROI size.

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Reference graph

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12 extracted references · 2 canonical work pages · 1 internal anchor

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