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REVIEW 3 major objections 5 minor 44 references

Doppler Estimation and Compensation Techniques in LoRa Direct-to-Satellite Communications

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read A midamble-point Doppler estimator, which refreshes the frequency correction at pilot chirps inside the payload, keeps LoRa-to-satellite symbol error rates close to the no-Doppler ideal across SNR, payload length, and satellite position.

desk verdict The headline robustness claim for midamble-point estimation is not yet established because the SF=12 configuration uses nint=1, turning the payload into known pilots without reporting throughput. read the letter →

arxiv 2506.20858 v1 pith:PZBJ5HPA submitted 2025-06-25 eess.SP

Jamil Farhat , Gianni Pasolini , Enrico Paolini , Muhammad Asad Ullah , Richard Demo Souza This is my paper · ORCID
classification eess.SP
keywords LoRadirect-to-satelliteLEOsatellitesDopplerestimationcompensationchirpspreadspectrummidamblesymbolerrorrate
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

The paper sets out to remove the main obstacle to LoRa direct-to-satellite links: the large, time-varying Doppler shift and Doppler rate produced by fast low-Earth-orbit satellites. It proposes four receiver-side estimation and compensation frameworks, all built from FFT peaks of dechirped chirps already present in the LoRa frame, and compares them by simulation against a no-Doppler benchmark. The central result is that the midamble-point framework, which inserts symbol-0 upchirps into the payload and refreshes a piecewise-constant Doppler correction at each one, delivers symbol error rates close to the best strategy in every tested scenario. A sympathetic reader would care because the method requires no hardware or protocol changes beyond software or firmware, so it could extend the usable visibility window and payload sizes of existing LoRaWAN satellite deployments.

What carries the argument

The load-bearing mechanism is the dechirp-and-FFT operation: multiplying a received LoRa chirp by the conjugate of a pure chirp maps a Doppler-shifted carrier onto a single frequency bin, so the bin index $S$ is the Doppler estimate. Point estimation applies the phase ramp $\hat{\theta}(t)=2\pi S t$ from the last preamble downchirp to the whole payload; linear estimation computes a slope $\alpha$ from the first and last downchirps and applies $\hat{\theta}_{\mathrm{linear}}(t)$; midamble-point refreshes $S$ at symbol-0 upchirps placed in the payload, and midamble-linear refreshes both $S$ and $\alpha$ between those midambles. The midamble insertion itself is standard LoRa: a midamble is just the symbol $0$, so it costs no new modulation.

What would settle it

Run the LoRa physical-layer link at SF=12, 120-bit payload, and the maximum-Doppler-rate geometry with midamble-point estimation and midambles on every chirp; if the measured symbol error rate does not stay within a small gap of the no-Doppler AWGN curve over the SNR sweep, the consistency claim fails. A complementary check is to compare the true Doppler trajectory from a real 550 km pass with the piecewise-constant assumption and count how many segments exceed the half-bin tolerance $\pm B/(2M)$.

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Extended reading notes

Core claim

On the paper's own terms, the discovery is that a LoRa receiver can estimate the instantaneous Doppler shift simply by dechirping a known chirp and reading the frequency bin of the FFT peak, and that repeating this estimate at pilot chirps embedded in the payload makes the compensation robust to the Doppler rate. The point estimator uses the last preamble downchirp as a single constant correction; the linear estimator fits a line through the first and last downchirps; midamble-point and midamble-linear rewrite the correction at midambles, modeling the Doppler shift as piecewise constant or piecewise linear over the frame. The numerical comparison shows midamble-point performing nearly as well as the best alternative under different SNR levels, payload lengths, and satellite positions, including both the high-shift/low-rate and low-shift/high-rate extremes, and it identifies the optimal midamble spacing for each configuration.

Load-bearing premise

The load-bearing premise is that within each inter-midamble segment the Doppler shift is constant (midamble-point) or linear (midamble-linear) in time, and that the FFT peak of a single dechirped chirp is a reliable local Doppler estimate; the paper itself notes this model breaks down for long SF=12 frames at high Doppler rate.

Editorial extensions

If this is right

  • Existing LoRaWAN satellites and IoT devices can adopt the midamble-point scheme through firmware updates, effectively lengthening the time window in which a satellite pass is usable.
  • For high spreading factors (SF=12) and long payloads under high Doppler rate, midamble-point keeps symbol error rates low where point and linear estimators fail, so long frames become viable in high-Doppler-rate geometries.
  • Enabling the built-in Low Data Rate Optimization mode gives an extra robustness margin that matters most at high Doppler rate, informing how spreading factor and LDRO should be paired.
  • The estimation strategy should be chosen by satellite position and spreading factor: point-based methods suffice at high shift and low rate, linear-based methods help at low shift and high rate, and midamble-point is the safe default across both.
  • The choice of midamble interval $n_{\mathrm{int}}$ is a real trade-off: sparse midambles are enough under high shift and low rate, while dense midambles are needed under high Doppler rate, so fixed-interval settings should be set from the worst-case Doppler rate.

Reading between the lines

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

  • Inference: because the paper deems per-frame adaptation impractical, a natural extension is to let the satellite receiver estimate the Doppler-rate proxy from the preamble and choose the midamble interval per pass, rather than fixing it system-wide.
  • Inference: the same FFT-bin pilot approach should transfer to other chirp spread spectrum IoT waveforms or to the downlink, where the satellite knows its own ephemeris and can pre-compensate.
  • Inference: the simulation's reliance on exact orbital Doppler bounds from the cited analytical model leaves open how atmospheric drag or non-circular orbits affect the claimed margins; real telemetry would settle that.
  • Inference: the paper implicitly values consistency over peak performance, so a practical system would use midamble-point even when a linear estimator wins in a specific geometry, because it avoids estimating which Doppler regime the link is in.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. This paper addresses Doppler estimation and compensation for LoRa direct-to-satellite links in LEO scenarios. It proposes four receiver-side strategies: point estimation, which uses the last preamble downchirp to estimate a constant Doppler shift; linear estimation, which interpolates the Doppler shift from the first and last downchirps; midamble-point estimation, which refines the point estimate with pilot upchirps inserted in the payload; and midamble-linear estimation, which refines the linear model with such pilots. The strategies are evaluated through LoRa physical-layer simulations under two satellite positions (high Doppler shift / low Doppler rate and low Doppler shift / high Doppler rate), spreading factors 7, 10, and 12, with and without LDRO, for varying SNR, payload length, and pilot insertion interval. The paper concludes that midamble-point estimation is the most consistent approach, performing nearly as well as the best strategy in every scenario.

Significance. If the results are validated, the paper offers a useful, firmware-only design guideline for LoRa DtS links, and its exploration of LDRO and of pilot-insertion trade-offs is a genuine contribution. The strengths are the broad scenario coverage, the comparison against an ideal no-Doppler reference, and the explicit attention to spreading-factor-dependent Doppler effects. However, the central claim rests on simulated SER comparisons that are not normalized for the pilot overhead introduced by the midamble schemes, and the favorable pilot intervals appear to be selected from the same experiments used to demonstrate robustness. No code or data is released, and there are no confidence intervals for the Monte Carlo results.

major comments (3)
  1. [§VII-A, Table II; Figs. 11(c), 16] The SF=12 midamble-point configuration uses nint,point=1. Under the paper's own definition in §VII-D of nint as the number of chirps between consecutive midambles, this means that either every payload chirp or every other payload chirp is a known zero-symbol pilot, so the midamble-point frame effectively carries no data or at most half the data rate, while the point, linear, and midamble-linear baselines still transmit 120 data bits. The SER of a frame composed of known pilots is not directly comparable with the SER of random data, because the receiver knows every transmitted pilot symbol and the FFT peak is measured on a zero chirp. The paper never reports pilot overhead, effective throughput, or the equivalent Es/N0/Eb/N0 penalty for discarded symbols. Please rerun the comparison with equal information-bit rates, or equivalently report SER versus Eb/N0 and effective throughput, choosing nint so that all schemes transmit the same number of data bits.
  2. [§VI-C1, Eqs. (19)-(20); §VII-D, Fig. 17] The per-SF nint values in Table II (SF=12:1, SF=10:4, SF=7:12) appear to be selected after inspecting Fig. 17, which is the same experiment later used to claim that midamble-point is the most consistent approach. No independent validation is provided for these choices. This makes the main claim depend on fitted pilot placement rather than on a design rule derived from Eq. (19). Please validate the chosen nint values on Doppler realizations and payload lengths not used in the selection, or propose a fixed worst-case rule and show the sensitivity of the conclusions to the tolerance factor k.
  3. [§II-B and §VII] The paper criticizes prior art [35]-[37] for not considering LDRO, for lacking comparisons between strategies, and for providing limited evaluation, but no quantitative comparison against these existing estimators appears in the numerical results. Add at least the preamble-based estimator of [35] and the regression/pilot-based estimator of [37] to the SER curves so that the claimed advantage is established against existing art rather than only against the paper's own simple baselines.
minor comments (5)
  1. [§VI-C1, Eq. (20), §VII-A] The definition of nint is ambiguous: Eq. (20) uses ceil(nsym/nint,point), which treats nint as the pilot period in symbols, while §VII-A says nint,point is the 'interval between consecutive midambles', which can be read as the number of data chirps between pilots. Please define nint unambiguously and make Table II consistent with Eq. (20).
  2. [§VII-B] All SER curves are shown without error bars or confidence intervals, so at the displayed low SER values it is difficult to assess whether the visible differences between point and midamble-point are statistically significant; please report the number of Monte Carlo trials and, where possible, provide bootstrap intervals for the key figures.
  3. [§VII-A] The table states L=120 bits but does not give the resulting number of payload symbols nsym for each spreading factor, nor how CR=1 (4/5 coding) and the LDRO mode modify nsym; without this information the reader cannot verify Eq. (20) or reproduce the pilot overhead.
  4. [§VIII] The conclusion refers to 'point-midamble' while the rest of the paper uses 'midamble-point'; please make the terminology uniform.
  5. [§VI-C1, Eq. (19)] Equation (19) defines Tpoint,mid through a tolerance factor k, but k is introduced only informally as a tolerance with 'typical values' from 0 to 0.5, and the example uses k=0.1 without derivation or sensitivity analysis; if Eq. (19) is intended as a design rule, please justify the value of k or show how the results change with k.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the proposed Doppler estimators are standard FFT-based algorithms evaluated by Monte Carlo simulation, and no claimed result is equivalent to its inputs by construction.

full rationale

The claimed contributions are algorithmic and simulation-based. Equations (10)-(23) describe standard dechirp/FFT-peak Doppler estimation with recursive midamble updates; no estimated quantity is defined in terms of the SER or of the 'consistent performance' conclusion. The Doppler shift/rate model is anchored in an external reference [44] and the standard approximation F_D = -(v/c)F_C; Cases 1 and 2 are scenario definitions, not derived from the target claim. The only tuning inputs are the tolerance k in Eq. (19) and the nint values in Table II; these are stated design choices and ablation settings rather than fitted parameters renamed as predictions, and they do not make the SER curves equal to the simulation inputs by construction. The SF=12 nint=1 setting does change the frame composition by inserting many known midamble pilots, so the comparison is not normalized by throughput; that is a fairness/correctness concern, not a circularity reduction. Self-citations [12] (validated simulator) and [17] (prior Doppler limits) support tooling and background, but no load-bearing argument reduces to an unverified self-citation or to an imported uniqueness theorem. Accordingly, no circular step is identified.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The paper introduces no new physical entities. The analysis rests on the LoRa signal model, the classical Doppler model with orbital bounds, and the assumption that single-chirp FFT peaks give unbiased Doppler estimates. The main free parameters are the midamble insertion intervals and the tolerance factor k, both of which are chosen for the simulated scenarios rather than derived from first principles.

free parameters (3)
  • k (tolerance factor in midamble interval formula) = 0.1 (example; range 0-0.5)
    Used in eq. (19) to set the recommended midamble update interval; chosen ad hoc from [43] with no sensitivity analysis of the SER to k.
  • nint,point (midamble insertion interval for midamble-point) = 1 (SF=12), 4 (SF=10), 12 (SF=7)
    Given in Table II; these per-SF values appear to be selected after the nint scan in Fig. 17, so they are effectively fitted to the simulated scenarios.
  • nint,linear (midamble insertion interval for midamble-linear) = 6 for all SF
    Table II; this fixed value is justified only by noting that too-small intervals reduce the precision of the slope estimate.
assumptions (4)
  • standard math LoRa chirp signal model and dechirping demodulation as in [12], including the relationship B*Tc = 2^SF.
    Equations (1)-(6) in Section III-A/B are taken as given and used in all estimation strategies.
  • domain assumption Doppler shift at the satellite follows the classical formula F_D(t) = -v(t) F_C / c and the orbit-specific bounds from [44].
    Section IV uses this to generate the Case 1 and Case 2 Doppler profiles.
  • domain assumption The channel is AWGN plus Doppler, with no fading, interference, or timing errors.
    Section VII-A states the channel model used in the simulator.
  • domain assumption The FFT peak bin of a dechirped pilot chirp gives the Doppler shift.
    Equations (10) and the midamble update procedures assume the peak location equals the Doppler-induced frequency offset.

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Pith. "Pith review of Doppler Estimation and Compensation Techniques in LoRa Direct-to-Satellite Communications." pith.science (2026). https://pith.science/paper/PZBJ5HPA

@misc{pith2026250620858,
  author       = {Pith},
  title        = {Pith review of: Doppler Estimation and Compensation Techniques in LoRa Direct-to-Satellite Communications},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/PZBJ5HPA}},
  note         = {Machine review of arXiv:2506.20858}
}
read the original abstract

Within the LPWAN framework, the LoRa modulation adopted by LoRaWAN technology has garnered significant interest as a connectivity solution for IoT applications due to its ability to offer low-cost, low-power, and long-range communications. One emerging use case of LoRa is DtS connectivity, which extends coverage to remote areas for supporting IoT operations. The satellite IoT industry mainly prefers LEO because it has lower launch costs and less path loss compared to Geostationary orbit. However, a major drawback of LEO satellites is the impact of the Doppler effect caused by their mobility. Earlier studies have confirmed that the Doppler effect significantly degrades the LoRa DtS performance. In this paper, we propose four frameworks for Doppler estimation and compensation in LoRa DtS connectivity and numerically compare the performance against the ideal scenario without the Doppler effect. Furthermore, we investigate the trade-offs among these frameworks by analyzing the interplay between spreading factor, and other key parameters related to the Doppler effect. The results provide insights into how to achieve robust LoRa configurations for DtS connectivity.

Figures

Figures reproduced from arXiv: 2506.20858 by the authors.

Figure 1
Figure 1. Representation of the instantaneous frequency devi [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 3
Figure 3. Variation of the received carrier frequency, [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. The LEO-satellite Doppler Shift and Doppler Rate for [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figures from the paper (9 more)
Figure 5
Figure 5. Figure 5: Doppler shifts are analyzed for different [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]
Figure 7
Figure 7. Figure 7: Frequency deviation within a LoRa frame with [PITH_FULL_IMAGE:figures/full_fig_p008_7.png]
Figure 8
Figure 8. Figure 8: Frequency deviation within a LoRa frame with [PITH_FULL_IMAGE:figures/full_fig_p009_8.png]
Figure 9
Figure 9. Figure 9: Frequency deviation within a LoRa frame with [PITH_FULL_IMAGE:figures/full_fig_p009_9.png]
Figure 10
Figure 10. Figure 10: Symbol error rate for the proposed Doppler estimati [PITH_FULL_IMAGE:figures/full_fig_p012_10.png]
Figure 11
Figure 11. Figure 11: Symbol error rate for different Doppler estimation [PITH_FULL_IMAGE:figures/full_fig_p012_11.png]
Figure 12
Figure 12. Figure 12: SER performance of different estimation strategie [PITH_FULL_IMAGE:figures/full_fig_p012_12.png]
Figure 16
Figure 16. Figure 16: SER performance as a function of payload length for a [PITH_FULL_IMAGE:figures/full_fig_p013_16.png]
Figure 17
Figure 17. Figure 17: SER as a function of nint for point and linear midamble estimation frameworks in Case 1 and Case 2 scenarios. the precision of αmid. To enhance accuracy, the midambles used for estimation should be sufficiently separated. VIII. CONCLUSION This paper investigates the i…

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Reference graph

Works this paper leans on

44 extracted references · 44 canonical work pages

  1. [36]

    Com pensation of the Frequency Offset in Communication Systems with LoRa Modulation,

    S. Mukhamadiev, E. Rogozhnikov, and E. Dmitriyev, “Com pensation of the Frequency Offset in Communication Systems with LoRa Modulation,” Symmetry, vol. 14, no. 4, 2022. [Online]. Available: https://www.mdpi.com/2073-8994/14/4/747

    work page 2022

  2. [35]

    Reception of LoRa signals from LEO satellites,

    G. Colavolpe, T. Foggi, M. Ricciulli, Y . Zanettini, and J.-P . Mediano- Alameda, “Reception of LoRa signals from LEO satellites,” IEEE Transactions on Aerospace and Electronic Systems , vol. 55, no. 6, pp. 3587–3602, 2019

    work page 2019

  3. [37]

    Regression based Pilot Design for Doppler Effect Estimati on and Compensation in LEO Satellite Communication with LoRa,

    J. Kang, G. Im, D.-H. Jung, S. Jung, J.-B. Kim, P . Kim, and J. Gyu Ryu, “Regression based Pilot Design for Doppler Effect Estimati on and Compensation in LEO Satellite Communication with LoRa,” in 2022 27th Asia Pacific Conference on Communications (APCC) , 2022, pp. 631–632

    work page 2022

  4. [1]

    A comprehen- sive study on LPW ANs with a focus on the potential of LoRa/LoR aW AN systems,

    C. Milarokostas, D. Tsolkas, N. Passas, and L. Merakos, “ A comprehen- sive study on LPW ANs with a focus on the potential of LoRa/LoR aW AN systems,” IEEE Communications Surveys & Tutorials , vol. 25, no. 1, pp. 825–867, 2023

    work page 2023

  5. [2]

    Do small cells make sense for simple low cost LPW ANs?

    A. N. Arun, A. B. Das, C. G. Brinton, D. J. Love, and J. V . Kro gmeier, “Do small cells make sense for simple low cost LPW ANs?” IEEE Wireless Communications Letters , pp. 1–1, 2024

    work page 2024

  6. [3]

    Power-ef ficient transmissions in LoRa uplink systems,

    Y . Guo, J. Niu, X. Zhou, T. Gu, Y . Li, and D. Fang, “Power-ef ficient transmissions in LoRa uplink systems,” IEEE Transactions on V ehicular Technology, pp. 1–13, 2024

    work page 2024

  7. [4]

    Key Drivers and Research Challenges for 6G Ubiquitous Wireless Intelligence,

    6G Flagship, “Key Drivers and Research Challenges for 6G Ubiquitous Wireless Intelligence,” University of Oulu, Tech. Rep. 6G R esearch Visions 1, Sep. 2019

    work page 2019

  8. [5]

    A s urvey on scalable LoRaW AN for massive IoT: Recent advances, potenti als, and challenges,

    M. Jouhari, N. Saeed, M.-S. Alouini, and E. M. Amhoud, “A s urvey on scalable LoRaW AN for massive IoT: Recent advances, potenti als, and challenges,” IEEE Communications Surveys & Tutorials , vol. 25, no. 3, pp. 1841–1876, 2023

    work page 2023

Show all 44 references
  1. [6]

    Low-Powe r Wide- Area networks for sustainable IoT,

    Z. Qin, F. Y . Li, G. Y . Li, J. A. McCann, and Q. Ni, “Low-Powe r Wide- Area networks for sustainable IoT,” IEEE Wireless Communications , vol. 26, no. 3, pp. 140–145, 2019

    2019

  2. [7]

    Enabl ing LP- W AN massive access: Grant-Free random access with massive M IMO,

    H. Jiang, D. Qu, J. Ding, Z. Wang, H. He, and H. Chen, “Enabl ing LP- W AN massive access: Grant-Free random access with massive M IMO,” IEEE Wireless Communications , vol. 29, no. 4, pp. 72–77, 2022

    2022

  3. [8]

    Space-terrestrial integrated Internet of Things: Challenges and opportunities,

    J. A. Fraire, O. Iova, and F. V alois, “Space-terrestrial integrated Internet of Things: Challenges and opportunities,” IEEE Communications Mag- azine, vol. 60, no. 12, pp. 64–70, 2022

    2022

  4. [9]

    Chirp Spread Spectr um-based waveform design and detection mechanisms for LPW AN-based I oT: A survey,

    A. W. Azim, R. Shubair, and M. Chafii, “Chirp Spread Spectr um-based waveform design and detection mechanisms for LPW AN-based I oT: A survey,” IEEE Access , vol. 12, pp. 24 949–25 017, 2024

    2024

  5. [10]

    A survey on L oRa networking: Research problems, current solutions, and ope n issues,

    J. P . Shanmuga Sundaram, W. Du, and Z. Zhao, “A survey on L oRa networking: Research problems, current solutions, and ope n issues,” IEEE Communications Surveys & Tutorials , vol. 22, no. 1, pp. 371– 388, 2020

    2020

  6. [11]

    Wireless communication method,

    O. B. A. Seller, “Wireless communication method,” 2017 , US Patent 9,647,718. [Online]. Available: http://www.google.it/patents/US9647718

    2017

  7. [12]

    On the LoRa Chirp Spread Spectrum modulat ion: Signal properties and their impact on transmitter and receiver arc hitectures,

    G. Pasolini, “On the LoRa Chirp Spread Spectrum modulat ion: Signal properties and their impact on transmitter and receiver arc hitectures,” IEEE Transactions on Wireless Communications, vol. 21, no. 1, pp. 357– 369, 2022

    2022

  8. [13]

    Experimental study of LoRa modulation imm unity to Doppler effect in CubeSat radio communications,

    A. A. Doroshkin, A. M. Zadorozhny, O. N. Kus, V . Y . Prokop yev, and Y . M. Prokopyev, “Experimental study of LoRa modulation imm unity to Doppler effect in CubeSat radio communications,” IEEE Access , vol. 7, pp. 75 721–75 731, 2019

    2019

  9. [14]

    LEO small-satellite constell ations for 5G and beyond-5G communications,

    I. Leyva-Mayorga, B. Soret, M. R¨ oper, D. W¨ ubben, B. Ma tthiesen, A. Dekorsy, and P . Popovski, “LEO small-satellite constell ations for 5G and beyond-5G communications,” IEEE Access , vol. 8, pp. 184 955– 184 964, 2020

    2020

  10. [15]

    Direct -To-Satellite IoT - a survey of the state of the art and future research perspect ives,

    J. A. A. Fraire, S. C´ espedes, and N. Accettura, “Direct -To-Satellite IoT - a survey of the state of the art and future research perspect ives,” 2019, pp. 241–258

    2019

  11. [16]

    Enabling mMTC i n Remote Areas: LoRaW AN and LEO Satellite Integration for Offshore Wind Farm Monitoring,

    M. A. Ullah, K. Mikhaylov, and H. Alves, “Enabling mMTC i n Remote Areas: LoRaW AN and LEO Satellite Integration for Offshore Wind Farm Monitoring,” IEEE Transactions on Industrial Informatics, vol. 18, no. 6, pp. 3744–3753, 2022

    2022

  12. [17]

    Understand- ing the limits of LoRa Direct-to-Satellite: The Doppler per spectives,

    M. Asad Ullah, G. Pasolini, K. Mikhaylov, and H. Alves, “ Understand- ing the limits of LoRa Direct-to-Satellite: The Doppler per spectives,” IEEE Open Journal of the Communications Society , vol. 5, pp. 51–63, 2024

    2024

  13. [18]

    Satellite comm uni- cations in the new space era: A survey and future challenges,

    O. Kodheli, E. Lagunas, N. Maturo, S. K. Sharma, B. Shank ar, J. F. M. Montoya, J. C. M. Duncan, D. Spano, S. Chatzinotas, S. Kissel eff, J. Querol, L. Lei, T. X. Vu, and G. Goussetis, “Satellite comm uni- cations in the new space era: A survey and future challenges, ” IEEE Co...

    2021

  14. [19]

    A survey on technologies, standards and open challenges in satellite IoT,

    M. Centenaro, C. E. Costa, F. Granelli, C. Sacchi, and L. V angelista, “A survey on technologies, standards and open challenges in satellite IoT,” IEEE Communications Surveys & Tutorials , vol. 23, no. 3, pp. 1693–1720, 2021

    2021

  15. [20]

    Uplink transmission policies for LoRa-based Direct-to-S atellite IoT,

    G. ´Alvarez, J. A. Fraire, K. A. Hassan, S. C´ espedes, and D. Pesc h, “Uplink transmission policies for LoRa-based Direct-to-S atellite IoT,” IEEE Access , vol. 10, pp. 72 687–72 701, 2022

    2022

  16. [21]

    Efficient design of Chirp Spread Spectrum modulation for Low-Power Wi de-Area Networks,

    T. T. Nguyen, H. H. Nguyen, R. Barton, and P . Grossetete, “Efficient design of Chirp Spread Spectrum modulation for Low-Power Wi de-Area Networks,” IEEE Internet of Things Journal , vol. 6, no. 6, pp. 9503– 9515, 2019

    2019

  17. [22]

    A tuto rial on Chirp Spread Spectrum modulation for LoRaW AN: Basics and key adva nces,

    A. Maleki, H. H. Nguyen, E. Bedeer, and R. Barton, “A tuto rial on Chirp Spread Spectrum modulation for LoRaW AN: Basics and key adva nces,” IEEE Open Journal of the Communications Society , vol. 5, pp. 4578– 4612, 2024

    2024

  18. [23]

    Assess- ing LoRa for satellite-to-earth communications consideri ng the impact of ionospheric scintillation,

    L. Fernandez, J. A. Ruiz-De-Azua, A. Calveras, and A. Ca mps, “Assess- ing LoRa for satellite-to-earth communications consideri ng the impact of ionospheric scintillation,” IEEE Access , vol. 8, pp. 165 570–165 582, 2020

    2020

  19. [24]

    Fractional Ch irp Rate Based CSS Division Multiple Access over LEO Satellite Inter net-of- Things,

    R. Zhang, J. Ma, S. Zhang, and O. A. Dobre, “Fractional Ch irp Rate Based CSS Division Multiple Access over LEO Satellite Inter net-of- Things,” IEEE Journal of Selected Topics in Signal Processing , pp. 1– 15, 2024

    2024

  20. [25]

    Improving uplink scalability of LoRa- based Direct- to-Satellite IoT networks,

    S. Herrer´ ıa-Alonso, M. Rodr´ ıguez-P´ erez, R. F. Rodr ´ ıguez-Rubio, and F. P´ erez-Font´ an, “Improving uplink scalability of LoRa- based Direct- to-Satellite IoT networks,” IEEE Internet of Things Journal , vol. 11, no. 7, pp. 12 526–12 535, 2024

    2024

  21. [26]

    Preamble structure and timing advanc e method for satellite IoT,

    W. Wu and W. Wang, “Preamble structure and timing advanc e method for satellite IoT,” IEEE Wireless Communications Letters , vol. 13, no. 4, pp. 1088–1092, 2024

    2024

  22. [27]

    Packet Collision Probability of Direct-to- Satellite IoT Systems,

    E. Testi and E. Paolini, “Packet Collision Probability of Direct-to- Satellite IoT Systems,” IEEE Internet of Things Journal , vol. 12, no. 2, pp. 1843–1855, 2025

    2025

  23. [28]

    On the LoRa modulation for Io T: Waveform properties and spectral analysis,

    M. Chiani and A. Elzanaty, “On the LoRa modulation for Io T: Waveform properties and spectral analysis,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 8463–8470, 2019

    2019

  24. [29]

    Low-cost SDR-based tool for evaluating LoRa satellite com munica- tions,

    R. M. Colombo, A. Mahmood, E. Sisinni, P . Ferrari, and M. Gidlund, “Low-cost SDR-based tool for evaluating LoRa satellite com munica- tions,” in 2022 IEEE International Symposium on Measurements & Networking (M&N) , 2022, pp. 1–6

    2022

  25. [30]

    Performance of a low-power wide-area network bas ed on LoRa technology: Doppler robustness, scalability, and coverag e,

    J. Pet¨ aj¨ aj¨ arvi, K. Mikhaylov, M. Pettissalo, J. Jan hunen, and J. H. Iinatti, “Performance of a low-power wide-area network bas ed on LoRa technology: Doppler robustness, scalability, and coverag e,” International Journal of Distributed Sensor Networks , vol. 13, 2017

    2017

  26. [31]

    LoRa on t he Move: Performance Evaluation of LoRa in V2X Communications,

    Y . Li, S. Han, L. Y ang, F.-Y . Wang, and H. Zhang, “LoRa on t he Move: Performance Evaluation of LoRa in V2X Communications,” in 2018 IEEE Intelligent V ehicles Symposium (IV) , 2018, pp. 1107–1111

    2018

  27. [32]

    Laboratory testing of LoRa modulation for CubeSat radio co mmunica- tions,

    A. Doroshkin, A. Zadorozhny, O. Kus, V . Prokopyev, and Y . Prokopyev, “Laboratory testing of LoRa modulation for CubeSat radio co mmunica- tions,” in MATEC W eb of Conferences, vol. 158. EDP Sciences, 2018, p. 01008

    2018

  28. [33]

    Tinygs: A collaborative satellite ground sta tion network,

    TinyGS, “Tinygs: A collaborative satellite ground sta tion network,” https://tinygs.com/, accessed: 2025-02-07

    2025

  29. [34]

    First Flight-Testing of LoRa Modulation in Satellite Radio Communications in Low -Earth Orbit,

    A. M. Zadorozhny, A. A. Doroshkin, V . N. Gorev, A. V . Melk ov, A. A. Mitrokhin, V . Y . Prokopyev, and Y . M. Prokopyev, “First Flight-Testing of LoRa Modulation in Satellite Radio Communications in Low -Earth Orbit,” IEEE Access , vol. 10, pp. 100 006–100 023, 2022

    2022

  30. [38]

    An Overview o f Direct- to-Satellite IoT: Opportunities and Open Challenges,

    M. Asad Ullah, K. Mikhaylov, and H. Alves, “An Overview o f Direct- to-Satellite IoT: Opportunities and Open Challenges,” in 2023 IEEE 9th W orld F orum on Internet of Things (WF-IoT) , 2023, pp. 1–8

    2023

  31. [39]

    Situational awareness for autonomous ships in the arctic: mmtc direct- to-satellite connectivity,

    M. Asad Ullah, A. Y astrebova, K. Mikhaylov, M. H¨ oyhty¨a, and H. Alves, “Situational awareness for autonomous ships in the arctic: mmtc direct- to-satellite connectivity,” IEEE Communications Magazine , vol. 60, no. 6, pp. 32–38, 2022. 15

    2022

  32. [40]

    S ubterranean mmtc in remote areas: Underground-to-satellite connectiv ity approach,

    K. Lin, M. A. Ullah, H. Alves, K. Mikhaylov, and T. Hao, “S ubterranean mmtc in remote areas: Underground-to-satellite connectiv ity approach,” IEEE Communications Magazine , vol. 61, no. 5, pp. 136–142, 2023

    2023

  33. [41]

    AN1200.80: LoRa® Modem Doppler Immunity , Semtech Corp., 2023, Rev. 1.0. [Online]. Available: https://www.semtech.com/products/wireless-rf/lora-connect/sx1272#documentation

    2023

  34. [42]

    SX1272 - Datasheet, Semtech Corp., 2019, Rev. 4.0. [Online]. Available: https://www.semtech.com/products/wireless-rf/lora-connect/sx1272#documentation

    2019

  35. [43]

    Characterizing the impact of Doppler effects on body-cent ric LoRa links with SDR,

    T. Ameloot, M. Moeneclaey, P . V an Torre, and H. Rogier, “Characterizing the impact of Doppler effects on body-cent ric LoRa links with SDR,” Sensors, vol. 21, no. 12, 2021. [Online]. Available: https://www.mdpi.com/1424-8220/21/12/4049

    2021

  36. [44]

    Doppler shift distribu tion in satellite constellations,

    A. Al-Hourani and B. Al Homssi, “Doppler shift distribu tion in satellite constellations,” IEEE Communications Letters , vol. 28, no. 9, pp. 2131– 2135, 2024

    2024

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.