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arxiv: 2605.01587 · v1 · submitted 2026-05-02 · 📡 eess.SP

Channel-Aware Waveform Selection Criteria Across Different Waveform Domains

Hamza Haif , Abdelali Arous , Huseyin Arslan This is my paper

Pith reviewed 2026-05-09 17:49 UTC · model grok-4.3

classification 📡 eess.SP
keywords 6G waveformschannel modelingwaveform selectionAFDMOTFSOFDMdelay-Dopplerspectral efficiency
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The pith

Generalized channel models show OFDM and DFT-s-OFDM can outperform AFDM and OTFS in reliability for dense urban conditions.

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

Evaluations of 6G waveforms have typically used simplified sparse and stationary channel models that do not capture the full complexity of urban environments and high mobility. This paper develops a generalized channel model including cluster birth-death dynamics, Doppler spectral spreading, time-varying delays, and piecewise local stationarity. Using this model, the input-output relationships for AFDM, OTFS, OFDM, and DFT-s-OFDM are derived to show distinct interference patterns. A channel-aware framework prioritizes waveforms based on resolvability, stationarity, SINR, and cell distribution. Simulations demonstrate that the advantages of AFDM and OTFS are restricted to sparse stationary cases, while OFDM and DFT-s-OFDM offer more stable performance when tuned appropriately.

Core claim

The paper establishes that the effective performance of waveforms depends critically on the channel's delay-Doppler resolvability and stationarity. Under the proposed model, AFDM and OTFS retain spectral efficiency and path combining gains exclusively when channels are sparse and stationary, whereas OFDM and DFT-s-OFDM can be adjusted to provide superior reliability and stability in more complex propagation environments.

What carries the argument

The generalized channel model with cluster birth-death dynamics, Doppler spectral spreading, time-varying delays, and piecewise local stationarity, which is used to derive waveform-specific effective input-output relations and build a prioritization framework based on resolvability, stationarity, effective SINR, and UE distribution.

If this is right

  • Waveform selection criteria must incorporate specific conditions of resolvability and stationarity rather than assuming universal benefits for any modulation.
  • AFDM and OTFS are suitable primarily for environments meeting sparse and stationary assumptions.
  • OFDM and DFT-s-OFDM can be optimized for enhanced reliability in non-ideal channel conditions common to dense urban settings.
  • Performance comparisons should account for the full interference structures exposed by the generalized model.

Where Pith is reading between the lines

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

  • 6G networks could benefit from dynamic waveform adaptation that switches based on measured channel stationarity intervals.
  • Extending this analysis to additional waveforms or hybrid designs might reveal further optimization opportunities in mixed environments.
  • The emphasis on stability suggests that reliability metrics should weigh more heavily than peak spectral efficiency in high-mobility deployments.

Load-bearing premise

The generalized channel model incorporating cluster birth-death dynamics, Doppler spectral spreading, time-varying delays, and piecewise local stationarity accurately models real propagation in dense urban and high-mobility environments.

What would settle it

Empirical channel measurements from dense urban high-mobility scenarios showing persistent path resolvability and long stationarity periods without significant birth-death dynamics would contradict the model's predictions and the resulting waveform performance rankings.

Figures

Figures reproduced from arXiv: 2605.01587 by Abdelali Arous, Hamza Haif, Huseyin Arslan.

Figure 1
Figure 1. Figure 1: Behavior of channel effects: delays, Doppler shifts, and channel coefficients under sparse channel model and proposed view at source ↗
Figure 2
Figure 2. Figure 2: Effective channel representation across OFDM, DFT-s-OFDM, AFDM, and OTFS waveforms: The first row represents view at source ↗
Figure 3
Figure 3. Figure 3: Pulse shape interpretation for Doppler spectrum in view at source ↗
Figure 4
Figure 4. Figure 4: Block diagram illustrating the proposed channel dependent adaptive waveform prioritization framework. view at source ↗
Figure 5
Figure 5. Figure 5: CE NMSE versus SNR under sparse and proposed view at source ↗
Figure 6
Figure 6. Figure 6: CE NMSE versus normalized Doppler under the view at source ↗
Figure 8
Figure 8. Figure 8: BER versus SNR under the proposed channel model view at source ↗
Figure 9
Figure 9. Figure 9: Spectral efficiency with fair resource mapping band view at source ↗
Figure 11
Figure 11. Figure 11: Achievable-rate heat maps across the cell for the four waveforms: (a)-(d) sparse model and (e)-(h) proposed model. view at source ↗
read the original abstract

Waveform evaluation for sixth generation (6G) networks has largely relied on sparse and quasi-stationary channel models that enabled mathematical tractability, diversity gains, and Doppler robustness. However, such models obscure the propagation complexity of dense urban environments, high mobility scenarios, and heterogeneous network deployments. This paper sheds light on a generalized and scalable channel model that incorporates cluster birth-death dynamics, Doppler spectral spreading, time-varying delays, and piecewise local stationarity. Based on this model, the effective input-output relationships of the main 6G waveforms are derived, exposing waveform dependent interference structures that remain hidden under conventional sparse assumptions. Building on these effective channels, a channel-aware waveform prioritization framework is developed based on delay-Doppler resolvability, stationarity conditions, effective signal-to-interference-plus-noise ratio (SINR), and user equipment (UE) cell distribution. Simulation results under the proposed channel model using 3GPP CDL parameters confirm that affine frequency division multiplexing (AFDM) and orthogonal time frequency space (OTFS) retain their spectral efficiency advantage and path combining gains only under sparse, resolvable, stationarity conditions, whereas orthogonal frequency division multiplexing (OFDM) and discrete Fourier transform spread (DFT-s)-OFDM can be both tuned to achieve superior reliability and more stable performance under the proposed channel model.

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 / 1 minor

Summary. The paper proposes a generalized channel model for 6G scenarios that includes cluster birth-death dynamics, Doppler spectral spreading, time-varying delays, and piecewise local stationarity. It derives effective input-output relationships for AFDM, OTFS, OFDM, and DFT-s-OFDM, exposing waveform-specific interference structures. A channel-aware prioritization framework is developed using delay-Doppler resolvability, stationarity conditions, effective SINR, and UE cell distribution. Simulations under the proposed model with 3GPP CDL parameters indicate that AFDM and OTFS retain spectral efficiency and path-combining gains only under sparse, resolvable, stationary conditions, while OFDM and DFT-s-OFDM can be tuned for superior reliability and stability.

Significance. If the simulations fully implement the generalized dynamics, the work offers a useful analytical framework for comparing waveforms beyond quasi-stationary assumptions and could inform 6G waveform selection by identifying regimes where conventional OFDM tuning outperforms OTFS/AFDM. The derivations of effective channels provide a concrete tool for interference analysis. However, the significance is tempered by uncertainty over whether the reported performance reversal arises from the new model features or from standard CDL parameterization.

major comments (1)
  1. [Numerical Evaluation / Simulation Setup] The central claim (abstract and §4) that AFDM/OTFS advantages hold only under sparse/resolvable/stationary conditions while OFDM/DFT-s-OFDM can be tuned for better reliability rests on simulations 'under the proposed channel model using 3GPP CDL parameters'. Standard 3GPP CDL specifies fixed cluster counts, power-delay profiles, and Doppler spectra without explicit Poisson birth-death processes, delay drift terms, or piecewise local stationarity transitions. It is unclear whether the numerical evaluation activates these dynamics (e.g., nonzero birth-death rates and time-varying delays) or uses only the static CDL components; if the latter, the interference structures and performance reversal reduce to those already known under quasi-stationary assumptions and do not test the generalized model invoked in the model definition.
minor comments (1)
  1. [Introduction] The abstract and introduction could more explicitly distinguish the proposed model's novel elements (birth-death rates, delay drift, local stationarity transitions) from prior non-stationary channel models in the literature.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the careful and constructive review of our manuscript. The major comment raises an important point about the clarity of our simulation setup, which we address below. We have revised the manuscript to provide additional details on how the generalized channel dynamics are implemented.

read point-by-point responses

  1. Referee: The central claim (abstract and §4) that AFDM/OTFS advantages hold only under sparse/resolvable/stationary conditions while OFDM/DFT-s-OFDM can be tuned for better reliability rests on simulations 'under the proposed channel model using 3GPP CDL parameters'. Standard 3GPP CDL specifies fixed cluster counts, power-delay profiles, and Doppler spectra without explicit Poisson birth-death processes, delay drift terms, or piecewise local stationarity transitions. It is unclear whether the numerical evaluation activates these dynamics (e.g., nonzero birth-death rates and time-varying delays) or uses only the static CDL components; if the latter, the interference structures and performance reversal reduce to those already known under quasi-stationary assumptions and do not test the generalized model invoked in the model definition.

    Authors: We thank the referee for this observation, which highlights the need for explicit clarification. The simulations in Section 4 are performed under the full generalized channel model defined in Section 2, using 3GPP CDL parameters solely to set the base power-delay profiles, cluster powers, and Doppler spectra. These are extended with the dynamic features of the model: Poisson cluster birth-death processes (with nonzero rates), time-varying delay drifts for individual paths, Doppler spectral spreading, and transitions across piecewise locally stationary segments. The effective input-output relations derived in Section 3 are evaluated directly under these active dynamics, producing the reported interference structures and performance trends. To eliminate ambiguity, we have added a dedicated paragraph in Section 4 specifying the dynamic parameter values (e.g., birth-death rates, delay variation coefficients, and stationarity interval lengths) and included an additional figure comparing results with and without the dynamic components. This demonstrates that the observed advantages of OFDM and DFT-s-OFDM arise specifically from the generalized dynamics rather than static CDL assumptions alone. revision: yes

Circularity Check

0 steps flagged

No significant circularity; derivations and simulations remain independent of inputs by construction

full rationale

The paper defines a generalized channel model incorporating birth-death dynamics and time-varying parameters, derives waveform-specific effective channels and interference structures directly from that model's equations, and then evaluates performance via numerical simulations parameterized by external 3GPP CDL values. No equations or claims in the abstract reduce a derived result to a fitted parameter or self-citation by construction; the prioritization framework is built on explicit resolvability and SINR metrics extracted from the model rather than presupposing the final performance ordering. The reported advantages for OFDM/DFT-s-OFDM versus AFDM/OTFS are simulation outcomes under the stated conditions, not tautological renamings or self-referential fits.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on the accuracy of the proposed channel model components and the validity of the effective SINR derivations under piecewise stationarity; no new physical entities are postulated beyond standard wireless propagation assumptions.

axioms (2)
  • domain assumption The 3GPP CDL parameters can be extended to incorporate cluster birth-death dynamics and time-varying delays while preserving statistical validity.
    Invoked when applying the model to simulations and deriving waveform-specific interference.
  • domain assumption Piecewise local stationarity holds over intervals sufficient for waveform processing.
    Used to derive effective input-output relationships for each waveform.

pith-pipeline@v0.9.0 · 5537 in / 1408 out tokens · 41826 ms · 2026-05-09T17:49:08.395337+00:00 · methodology

discussion (0)

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Reference graph

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