OFDM Based Bistatic Integrated Sensing and Communication: Sensing Beyond CP Limit

Cagri Goken; Cuneyd Ozturk

REVIEW 4 major objections 6 minor 19 references

OFDM Based Bistatic Integrated Sensing and Communication: Sensing Beyond CP Limit

T0 review · 4 major / 6 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read In a bistatic OFDM ISAC link, a sliding-window receiver that sees only pilot symbols estimates target range and velocity for delays beyond the cyclic prefix, approaching the Cramer-Rao bounds at high SNR.

desk verdict Plausible sliding-window extension for bistatic pilot-only ISAC, but the printed estimator equations drop the coarse delay and swap axes, so the central claim isn't reproducible. read the letter →

arxiv 2505.12166 v1 pith:P6NDSMX6 submitted 2025-05-17 eess.SP

Cuneyd Ozturk , Cagri Goken This is my paper · ORCID

classification eess.SP

keywords integratedsensingandcommunicationOFDMcyclicprefixbistaticradarsliding-windowdetectionpilotsymbolsCramer-Raoboundrangevelocityestimation

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper tries to show that the sensing range of an OFDM-based bistatic integrated sensing and communication link need not stop at the cyclic prefix (CP), the guard interval that normally caps allowable echo delay. The proposed receiver knows only pilot symbols, not the full data stream, yet it slides an FFT window over CP-length blocks, forms least-squares channel estimates on the pilot grid, and takes periodogram peaks to detect a target and estimate its bistatic range and velocity for delays several CPs long. The paper reports simulations in which this estimator tracks the Cramer-Rao bounds at high SNR for three pilot densities, both when the line-of-sight path is blocked and when it is present. If correct, the result removes the main distance cap in bistatic OFDM sensing without changing the transmitted waveform or requiring full symbol knowledge at the sensing receiver.

What carries the argument

The load-bearing mechanism is the sliding-window delay decomposition: $\tau_{\text{NLOS}} = \ell T_{cp} + \epsilon$ with $0 \le \epsilon < T_{cp}$, where each hypothesis $H_\ell$ corresponds to a different CP-length block. For each hypothesis the receiver shifts its FFT window by $\ell N_{cp}$ samples, which turns the long delay into a residual delay within the CP, so pilot-based LS channel estimates remain ISI-free. The decision metric is the peak of a 2D periodogram computed from the pilot-grid channel estimates, followed by a finer sliding window over sample indices and quadratic interpolation for sub-bin accuracy.

What would settle it

Fix a target with bistatic delay just above the CP duration, tell the receiver the true CP-block hypothesis $\ell_0$, and compare the pilot-only LS estimator RMSE to the Cramer-Rao bound from [5]; if the RMSE floor stays above the CRB at high SNR, the conditional-validity premise fails.

Watch

Extended reading notes

Core claim

The central claim is that in a bistatic OFDM ISAC system, the sensing receiver can detect a target and estimate its bistatic range and projected velocity even when the NLOS echo delay exceeds the CP duration, using only the pilot symbols embedded in the time-frequency grid. The method decomposes the delay into CP-length blocks plus a residual, and for each block hypothesis computes LS channel estimates on the pilot subcarriers after shifting the FFT window. The decision metric is the peak of the resulting two-dimensional periodogram; after a coarse block-level search and a finer sample-level window, quadratic interpolation yields the range and velocity estimates. Numerical results show RMSE closely approaching the expected Cramer-Rao bounds in the high-SNR regime, for both the LOS-blocked and LOS-present scenarios, indicating the CP is no longer the limiting factor for sensing range.

Load-bearing premise

The whole performance comparison rests on assuming that the Cramer-Rao bound formulas from earlier work, derived for delays no longer than the CP, remain exact theoretical bounds when the estimator is first gated by the sliding-window hypothesis test, but the paper does not prove that conditional validity.

Editorial extensions

If this is right

A bistatic OFDM sensing link can extend its ISI-free range from the CP-limited value $c T_{cp}$ (300 m in the paper's example) up to a chosen maximum range $R_{max}$ (3000 m), a tenfold extension, without changing the OFDM frame structure.
Because only pilots are needed, the sensing receiver does not require full modulation-symbol knowledge or time-domain reconstruction, so the approach works with standard OFDM communication waveforms.
Sparse pilot patterns with overhead 0.125 perform nearly as well as denser patterns with overhead 0.5, suggesting sensing can piggyback on existing pilot grids without major throughput loss.
Velocity estimation is sensitive to angle-of-arrival error: range estimation stays accurate under AoA mismatch, but velocity degrades, so practical deployments need AoA estimation at the sensing receiver.
When a LOS path is present, the method detects and subtracts it, but reliable NLOS estimation requires the NLOS echo to arrive within one CP after the LOS path; outside that delay difference the cancellation argument is not made.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

A natural test is to separate detection loss from estimation loss: compute an unconditional Cramer-Rao bound that accounts for the search over the hypothesis $\ell$, rather than conditioning on a correct hypothesis choice; this would show how much of the gap between RMSE and ECRB comes from the sliding-window decision itself.
The same sliding-window idea could be applied to interference suppression in communication receivers, where a long-delay signal from a second transmitter could be treated as a target-like component and cancelled using only pilot positions.
Combining the sliding window with coherent compensation of the residual delay, along the lines of the coherent-compensation approach cited in the paper, may improve SINR beyond what the current method achieves, since the current method discards energy outside the selected window.
In a multi-static ISAC network, several transmitter-receiver pairs could share the same pilot grid and fuse their periodogram peaks to localize targets without exchanging full data symbols, an extension the paper explicitly leaves for future work.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

Two things to know about arXiv:2505.12166. The problem is real—bistatic OFDM ISAC with a pilot-only receiver is exactly the kind of setup you'd want for a practical 6G sensing node, and extending the usable range beyond the CP limit matters. And the paper makes a genuine adaptation: it takes the sliding-window principle from monostatic [17], applies it to a bistatic pilot-only receiver, and adds an explicit LOS cancellation stage. That combination is new.

That said, the central estimator as printed does not work. Equation (24) gives the range as ep c/(np Δf Np), with no dependence on the coarse delay block bk selected by the sliding window. For delays that span multiple CP blocks, the fine periodogram peak is periodic in the pilot subcarrier spacing; without adding the block offset you cannot recover the absolute bistatic range. The axes are also swapped: range should come from the delay axis q, but Eq. (24) uses the Doppler index ep; Eq. (27) uses the delay index eq for velocity. So the text as written does not contain a working estimator for the claimed beyond-CP regime. This is not a nitpick; it means the RMSE curves in Figs. 3–5 cannot be produced from the equations given.

The weaknesses go a bit further. The threshold computation in Sec. III-D requires knowing the true hypothesis to define the complementary window; that's oracle information, and the numerical results are conditioned on successful detection and correct hypothesis selection. The claim that the CRBs from the authors' own [5] remain valid under this conditioning is asserted without proof. And Scenario II assumes τNLOS − τLOS ≤ Tcp, which is restrictive and not discussed.

Credit where due: the system model is clearly written, the LOS cancellation step is thoughtfully designed, and the paper honestly states when it conditions on successful detection. The figures show the expected qualitative behavior.

This is a repairable paper. A competent referee should send it back for major revision: fix the range/velocity equations, remove the oracle threshold (or provide an unconditional evaluation), and either prove the CRB claim or drop it. The core idea is plausible and worth pursuing. I would not cite it in current form, but it deserves a serious referee—not a desk reject—and with corrections it could become a solid incremental contribution.

Referee Report

4 major / 6 minor

Summary. The manuscript proposes a sliding-window, pilot-only receiver for bistatic OFDM ISAC that aims to estimate target range and velocity when the echo delay exceeds the cyclic prefix duration. The receiver divides the maximum sensing range into CP-length blocks, computes least-squares channel estimates on pilot subcarriers under each block hypothesis, and selects a refined window with the largest periodogram peak. Range and velocity are then read from the interpolated periodogram, and the results are compared with expected Cramér-Rao bounds (ECRBs) taken from the authors' prior work, for both LOS-blocked and LOS-present scenarios.

Significance. If the claims were fully established, the pilot-only sliding-window approach would be a useful contribution: bistatic sensing receivers generally lack access to the full transmitted modulation symbols, and several prior beyond-CP studies assume full symbol knowledge or monostatic operation. The paper identifies a real gap and the core mechanism is intuitively plausible. However, as written, the central validation rests on an incomplete range estimator and on a circular conditioning on correct hypothesis identification, so the significance is not yet demonstrated.

major comments (4)

[Sec. III-C, Eq. (24)] The range estimator bRbis = ep c/(np Δf Np) does not include the coarse delay offset bkTs selected by the sliding-window search. The pilot-subcarrier periodogram is periodic in delay with a period determined by np Δf, so the interpolated peak ep identifies only the residual delay within one unambiguous interval. For delays spanning several CP blocks, as in Sec. IV where the bistatic range exceeds 2000 m and corresponds to at least the 7th CP block, the absolute range cannot be recovered from Eq. (24) alone. The printed estimator therefore cannot reproduce the RMSE curves in Figs. 3–5.
[Sec. III-D, Eqs. (28)–(29)] The threshold computation uses the true hypothesis ell_0 to define the complementary window Wc_0 and the maximum statistic b_ell. This is circular and not implementable, because at the detection stage the receiver does not know ell_0. As a result, the false-alarm probability and the subsequent detection/estimation results are conditioned on information that is not available to the algorithm.
[Sec. IV, CRB comparison] The statement that the CRBs derived in [5] under the condition tau_NLOS <= Tcp remain exact bounds when conditioned on correctly identifying the true hypothesis is asserted without proof. The windowed observation model involves a discrete coarse-delay selection and a residual-delay estimation problem, so the Fisher information and the resulting bound are not obviously the same as in the CP-limited model. Comparing conditional RMSE to these ECRBs is not a valid benchmark unless the conditional Cramér-Rao bound is derived. The sentence 'This is confirmed by the simulation results' is circular.
[Sec. III-E, LOS gain estimate] The estimated LOS gain b_alpha_LOS = e^{-j2πfc b_tau_LOS} λ/(π b_tau_LOS c) does not match Eq. (14), where alpha_LOS = e^{-j2πfc tau_LOS} λ/(4π c tau_LOS). The factor-of-4 discrepancy in the denominator would directly affect the LOS cancellation step and hence the Scenario II range and velocity results shown in Fig. 5.

minor comments (6)

[Eq. (9)] The denominator contains the typo '||p - p||' and should read '||p - p_rx||'.
[Eqs. (24) and (27)] The mapping of the periodogram axes p and q to the interpolated indices ep and eq, and then to range and velocity, is confusing and should be stated explicitly. In particular, clarify that peak positions on the subcarrier axis are used for range and on the symbol-time axis for velocity.
[Eq. (24)] The quantity Np is not defined in the manuscript. If it denotes the FFT size Nper, that should be stated; if it denotes the number of pilot subcarriers, its value and role in the estimator should be given.
[Sec. III-C] The stopping rule 'let h be the smallest index such that eta_h >= kappa' is not clearly connected to the refined window selection. Explain how h, the window size W, and the search range W are related, and why W=2 is sufficient for the numerical setup.
[Eq. (19)] The DFT expression uses the phase e^{-j2π(k-Ncp)n/Nsc} with k running from 0; the indexing should be checked and the relation between the CP-removal offset and the delay decomposition in Eq. (15) should be clarified.
[Table I] The FFT sizes Nper and Mper are larger than Nsc and Msym, respectively. State explicitly whether zero-padding is used in the 2D periodogram and how the periodogram resolution is affected.

Circularity Check

2 steps flagged · score 5.0 of 10

Validation is partially circular: the threshold is set using the true hypothesis, and the beyond-CP validity of the self-cited CRB is confirmed by the same RMSE curves it benchmarks; the printed range estimate also drops the coarse window offset.

self definitional [Sec. III-D, Threshold Computation (Scenario I), used in Sec. IV simulations.]
"Let ℓ0 denote the true hypothesis, meaning the bi-static range satisfies (ℓ0−1)Tcp ≤ Rbis < ℓ0Tcp. Then, given windowing size W, we define the complementary window of interest as Wc0 ≜{1,...,L}\{ℓ0−⌊W/2⌋,...,ℓ0+⌊(W+1)/2⌋}. The index corresponding to the maximum decision metric outside the window of interest is then defined as bℓ = arg max ℓ∈Wc0 ηℓ. The threshold κ is subsequently determined such that the probability of a false alarm satisfies Pr{η_bℓ≥κ} = Pf."

The detection threshold κ is computed from the true hypothesis ℓ0, which is exactly the unknown label the sliding-window detector is supposed to find. The numerical RMSEs are then evaluated 'conditioned on successful target detection' (Sec. IV). Thus the detector is tested only on outcomes that the oracle-informed threshold is constructed to admit; the event that the algorithm finds the correct hypothesis is built into the evaluation rather than being an independent, falsifiable outcome. The claimed detection and estimation performance therefore reduces, at the validation stage, to a decision rule whose design already knows the answer.
self citation load bearing [Sec. IV, Numerical Results, paragraph following Table I.]
"To benchmark the performance of the proposed approach, we utilize the CRB expressions for range and velocity estimation derived in [5]. Although these CRBs are obtained under the assumption that the NLOS propagation delay satisfies τNLOS≤ Tcp, they remain valid as exact theoretical bounds when conditioned on correctly identifying the true hypothesis found via the procedures outlined in Secs. III-B, III-C, and III-D. This is confirmed by the simulation results shown in Figs. 3-4."

The CRB benchmark is taken from the authors' own prior work [5], where it was derived only for the CP-limited case τNLOS≤Tcp. The paper extends it to the sliding-window, beyond-CP problem by assertion, with no derivation of the conditional validity. The only evidence offered for that extension is the agreement of Figs. 3-4, which are exactly the curves that the CRB curves are being used to validate. The bound's applicability and the estimator's near-optimality are therefore mutually confirming: the estimator is said to approach the CRB because the CRB is said to be valid, and the CRB is said to be valid because the estimator approaches it. This circular confirmation is load-bearing for the central 'closely approaches the CRBs' conclusion.

full rationale

The sliding-window coarse-to-fine search itself is not circular: the algorithm genuinely evaluates multiple window offsets and selects one by a periodogram peak, and that component has independent algorithmic content. However, the paper's validation loop is partially circular. First, the threshold in Sec. III-D is defined using the true hypothesis ℓ0, i.e., oracle knowledge of the delay block, and the RMSE curves are conditioned on successful detection; the measured 'success' is therefore a built-in selection rather than an independent outcome. Second, the CRB benchmark is imported from the authors' own [5], where it holds only for τNLOS≤Tcp; the paper asserts without proof that it remains exact when conditioned on correct hypothesis identification, and supports that assertion by the same Figs. 3-4 that the CRB curves are supposed to benchmark. The estimator and the bound thus confirm each other in a closed loop. Separately, Eq. (24), bRbis = epc/(np∆fNp), contains no bk or hypothesis-index term, so the printed estimator cannot return the absolute beyond-CP range used in Sec. IV, where the delay spans 'at least the 7th CP block'; this is a correctness/reproducibility defect rather than a circularity, and it reinforces the need for caution but is not counted as a separate circular step. The score is 5 rather than higher because the central sliding-window mechanism is not inherently circular, and the original CP-limited CRB in [5] is a legitimate independent result for the regime in which it was derived.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

The central claim rests on standard OFDM signal-modeling assumptions plus two paper-specific premises: the restrictive Scenario II delay-difference assumption and the unproved conditional validity of the self-cited CRBs. No new physical entities, forces, or conserved quantities are introduced. The main free design choices are the pilot pattern, window size, false-alarm probability, and maximum range, none of which are fitted to data.

free parameters (4)

Pilot spacing (np, mp) = (2,4), (2,2), (2,1)
Design parameters of the periodic pilot pattern in Eq. (3), varied in simulation. They are not fitted to data but directly set the overhead and the CRB comparison points.
Sliding-window size W = 2
Design parameter in Sec III-C for the fine search around the detected hypothesis. No sensitivity study is provided, and it affects the probability of selecting the correct hypothesis.
False alarm probability Pf = 1e-3
Used in Sec III-D to define the threshold kappa, but the distribution of the test statistic is not derived, so the threshold is not computed from first principles.
Maximum sensing range Rmax = 3000 m
Introduced to limit the number of hypothesis blocks L in Eq. (16). The paper says it is a complexity parameter, so behavior beyond Rmax is not characterized.

assumptions (6)

domain assumption Single-target environment with only one NLOS path and optionally one LOS path
The system model in Sec II assumes exactly one target; multi-target interference and clutter are not modeled.
domain assumption Bistatic Doppler model f_D = 2||v||/lambda cos(phi) cos(beta/2)
Adopted from Ref. [18] and used throughout the estimator; assumes a point target and stationary transmitter and receiver.
ad hoc to paper Scenario II requires tau_NLOS - tau_LOS <= Tcp
Stated at the start of Sec III-E without justification. It restricts the LOS-present case to targets whose echo arrives within one CP after the direct path, and it is load-bearing for the LOS cancellation procedure.
domain assumption CRB expressions from [5] remain valid as exact bounds when conditioned on correct hypothesis identification
Asserted in Sec IV without proof. The CRBs were derived in the authors' prior work for tau_NLOS <= Tcp, and their validity for the residual delay after window shifting is not established.
domain assumption Analysis window is restricted to a single OFDM frame
Stated in footnote 2 of Sec III-B; targets whose delay spans more than one frame duration are not handled.
domain assumption Perfect knowledge of pilot positions and pilot modulation at the sensing receiver
The receiver knows only the pilot symbols by construction, but the model assumes perfect pilot synchronization and no pilot contamination or timing offset.

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Cite this review

Pith. "Pith review of OFDM Based Bistatic Integrated Sensing and Communication: Sensing Beyond CP Limit." pith.science (2026). https://pith.science/paper/P6NDSMX6

@misc{pith2026250512166,
  author       = {Pith},
  title        = {Pith review of: OFDM Based Bistatic Integrated Sensing and Communication: Sensing Beyond CP Limit},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/P6NDSMX6}},
  note         = {Machine review of arXiv:2505.12166}
}

read the original abstract

This work investigates a bistatic OFDM-based integrated sensing and communication (ISAC) system under a single-target scenario, considering both line-of-sight (LOS) presence and LOS blockage cases. A sliding window-based sensing receiver architecture is proposed to extend the intersymbol interference (ISI)-free sensing range beyond the cyclic prefix (CP) duration by exploiting pilot symbols embedded in the time-frequency grid. The performance of the proposed receiver is evaluated in terms of range and velocity estimation accuracy and is compared against the Cramer-Rao bounds (CRBs) for the bi-static ISAC setting. Numerical results confirm that the proposed method achieves estimation performance that closely approaches the CRBs in the high signal-to-noise ratio (SNR) regime.

Figures

Figures reproduced from arXiv: 2505.12166 by the authors.

**Figure 2.** System geometry when the LOS path between the sensing transmitter [PITH_FULL_IMAGE:figures/full_fig_p002_2.png] view at source ↗

**Figure 3.** RMSE of the bi-static range estimation along with the ECRB values [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗

Figures from the paper (2 more)

**Figure 4.** Figure 4: RMSE of the bi-static velocity estimation along with the ECRB [PITH_FULL_IMAGE:figures/full_fig_p005_4.png]

**Figure 5.** Figure 5: RMSE of the bistatic range estimation under LOS path along with [PITH_FULL_IMAGE:figures/full_fig_p006_5.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

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Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.

[1] [17]

How does cp length affect the sensing range for ofdm-isac?

X. Xu, Z. Zhou, and Y . Zeng, “How does cp length affect the sensing range for ofdm-isac?” 2025. [Online]. Available: https://arxiv.org/abs/2503.08062

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[3] [1]

The integrated sensing and communication revolution for 6g: Vision, techniques, and applications,

N. Gonzalez-Prelcic, M. Furkan Keskin, O. Kaltiokallio, M. Valkama, D. Dardari, X. Shen, Y . Shen, M. Bayraktar, and H. Wymeersch, “The integrated sensing and communication revolution for 6g: Vision, techniques, and applications,” Proceedings of the IEEE, vol. 112, no. 7, pp. 676–723, 2024

work page 2024

[4] [2]

Fundamental trade- offs in monostatic isac: A holistic investigation towards 6g,

M. F. Keskin, M. M. Mojahedian, J. O. Lacruz, C. Marcus, O. Eriksson, A. Giorgetti, J. Widmer, and H. Wymeersch, “Fundamental trade- offs in monostatic isac: A holistic investigation towards 6g,” IEEE Transactions on Wireless Communications , pp. 1–1, 2025

work page 2025

[5] [3]

A novel joint angle-range-velocity estimation method for mimo-ofdm isac systems,

Z. Xiao, R. Liu, M. Li, Q. Liu, and A. L. Swindlehurst, “A novel joint angle-range-velocity estimation method for mimo-ofdm isac systems,” IEEE Transactions on Signal Processing, vol. 72, pp. 3805–3818, 2024

work page 2024

[6] [4]

System-level analysis of joint sensing and communication based on 5g new radio,

L. Pucci, E. Paolini, and A. Giorgetti, “System-level analysis of joint sensing and communication based on 5g new radio,” IEEE Journal on Selected Areas in Communications, vol. 40, no. 7, pp. 2043–2055, 2022

work page 2022

[7] [6]

Bistatic sensing at thz frequencies via a two-stage ultra-wideband mimo-ofdm system,

T. Bacchielli, L. Pucci, D. Dardari, and A. Giorgetti, “Bistatic sensing at thz frequencies via a two-stage ultra-wideband mimo-ofdm system,”

work page

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Perfor- mance analysis of a bistatic joint sensing and communication system,

L. Pucci, E. Matricardi, E. Paolini, W. Xu, and A. Giorgetti, “Perfor- mance analysis of a bistatic joint sensing and communication system,” in 2022 IEEE International Conference on Communications Workshops (ICC Workshops), 2022, pp. 73–78

work page 2022