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REVIEW 3 major objections 4 minor 30 references

WakeMod: A 6.9uW Wake-Up Radio Module with -72.6dBm Sensitivity for On-Demand IoT

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

Pith's one-line read WakeMod is an open-source wake-up radio module that idles at 6.9 µW, holds −72.6 dBm sensitivity, and wakes a receiver up to 130 m away in under 54 ms.

desk verdict Solid, honestly reported hardware engineering with a useful 6.9 µW wake-up module; the 130 m range headline needs a PDR caveat—reliable range is about 100 m. read the letter →

arxiv 2505.21529 v2 pith:VF5SUHMQ submitted 2025-05-23 cs.NI

classification cs.NI
keywords wake-upradioultra-lowpowerIoTOOKmodulationasynchronouscommunication868MHzISMbandpacketdeliveryratioopen-sourcehardwaree-inkdisplay
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

Wake-up radios promise to remove the central tradeoff of low-power wireless: the choice between listening continuously and draining the battery, or sleeping and missing events. This paper argues that the tradeoff can now be eliminated with off-the-shelf parts by building WakeMod, an open-source transceiver module that idles at 6.9 µW while remaining on call with −72.6 dBm sensitivity. A wake-up call costs the receiver 17.7 µJ and arrives within 54.3 ms, and field tests show that more than 94% of calls succeed out to 100 m using a 2.8 dBm transmitter. In an e-ink price-tag demonstration, the same module idles at 7.17 µW, which the authors project to roughly eight years of daily updates on one CR2032 coin cell. If these numbers hold in deployment, always-on listening becomes affordable enough for event-driven IoT nodes that must live for years.

What carries the argument

The load-bearing component is the FH101RF, a commercially available tri-band wake-up receiver chip that draws as little as 4.7 µW while listening for on-off keying (OOK) wake-up calls at its rated −75 dBm sensitivity. Around it, the module's central design trick is a two-rate preamble scheme: the wake-up preamble is encoded as a 32-bit maximum-length sequence (a pseudo-random bit pattern the receiver correlates against) at a low data rate of 1024 bps, where idle listening costs 6.88 µW, while the 16-bit address and 6-byte payload are sent at a configurable high rate up to 32 768 bps, so the receiver stays cheap while dormant and fast while decoding. The MAX41462 transmitter remains in shutdown at 34.2 nW until a data-line toggle starts a call, and the STM32U031 MCU sleeps in a 29 nW shutdown mode, waking in 290 µs to service an interrupt. This pairing of an always-on nanowatt receiver with a normally-off transmitter is what lets the module claim a watchful idle power of 6.9 µW total, including the MCU and antenna switch.

What would settle it

Run the open-field PDR sweep again at 100 m and 130 m with 100 wake-up calls per distance, and meter the module's idle current at 1024 bps with the MCU in shutdown: a 130 m success rate far above the reported 11%, a plateau that collapses well before 100 m, or an idle draw clearly above 7 µW would each force a correction to the headline numbers.

Watch

Extended reading notes

Core claim

The central claim is that a complete, open-source wake-up transceiver — wake-up receiver, OOK transmitter, single-antenna RF switch, and control MCU on a 16 mm × 16 mm board that drops into existing radio sockets — can provide always-on listening at 6.9 µW without giving up reach or responsiveness. Measured at the module level, the receiver achieves −72.6 dBm sensitivity (−70.18 dBm peak envelope power), consumes 17.7 µJ per wake-up with latency below 54.3 ms, and, with the transmitter at 2.8 dBm, keeps packet delivery above 94% out to 100 m and reaches its nominal 130 m limit in an open field. In the e-ink price-tag demonstration, the whole system idles at 7.17 µW and is estimated to run about eight years on a CR2032 coin cell with daily display updates. The paper's point is that always-on wake-up radio has matured into a low-cost, drop-in building block for event-driven IoT.

Load-bearing premise

The headline 130 m range is read at the point where only 11 of 100 wake-up calls succeed (Section V-B, Fig. 4); if a reliable wake-up link must deliver most calls, the useful range is roughly 100 m, and the paper never states the minimum delivery rate behind its range limit.

Editorial extensions

If this is right

  • An IoT node can remain always reachable at roughly 7 µW of idle power, so multi-year battery life no longer requires duty cycling or accepting seconds of wake-up latency.
  • Because the module's 16 mm × 16 mm footprint matches common sub-GHz radio modules and it is controlled over I2C, existing node designs can be retrofitted with wake-up capability without a board redesign.
  • A wake-up call costs the sender about 1.33 mJ over 72.6 ms in the low-idle configuration, or 539 µJ over 42.3 ms when a faster preamble is acceptable, putting selective addressing of many battery-powered nodes within reach.
  • Reliable wake-up at above 94% packet delivery holds out to 100 m with a 2.8 dBm transmitter and −2.1 dBi antennas, covering room- and building-scale deployments in open space.
  • The e-ink price-tag demonstration shows that update-driven display devices can run for years on a coin cell, with the 132 mJ display refresh — not the radio — dominating the energy budget at daily update rates.

Reading between the lines

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

  • The dependable range for a real deployment depends on the reliability threshold: the paper's 130 m figure is the last distance at which any call got through, with only 11 of 100 succeeding, so a deployment that requires roughly 90% delivery should plan for about 100 m.
  • The gap between the FH101RF's rated −75 dBm sensitivity and the module's measured −72.6 dBm is about 2.4 dB, consistent with insertion loss through the antenna switch and board; a future revision that recovers part of that margin could extend range at no extra power.
  • The slow-preamble/fast-address split is a general pattern: any OOK wake-up receiver with a configurable data rate could adopt it, so the 6.9 µW idle figure is best read as a design template rather than a chip-specific result.
  • Because raising the supply from 1.8 V to 3.3 V lifts transmit power from 2.78 dBm to 10.92 dBm at a power cost of about 108 mW versus 26 mW, system designers can trade battery draw against link margin simply by choosing the supply rail.
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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 / 4 minor

Summary. WakeMod is an 868 MHz wake-up transceiver module built around the RF ICIENT FH101RF WuR and the Analog Devices MAX41462 OOK transmitter, with an STM32U031 MCU and a single RF switch to share one antenna. The paper reports direct measurements of the module's idle listening power (6.88 µW at 1024 bps), receiver sensitivity (-72.62 dBm), per-wake-up energy (17.75 µJ), latency (54.28 ms), transmitter output power and spectrum, and packet delivery ratio versus distance. A demonstration system, WakeTag, integrates WakeMod with an e-ink display and achieves 7.17 µW idle consumption, with an estimated 8-year CR2032 battery life for daily display updates based on the stated 220 mAh capacity and 1% annual self-discharge assumption. The paper claims an operational range of approximately 130 m, based on the last distance at which any wake-up call was received, with PDR above 94% only up to 100 m.

Significance. If the reported measurements hold, WakeMod is a useful open-source building block for asynchronous, ultra-low-power IoT communication. The strengths of the paper are that the central power, sensitivity, and PDR numbers come from direct measurements with commercially available instruments; the design is open-source; the WakeTag demonstration provides a realistic end-to-end energy profile; and the battery-lifetime estimate is a transparent arithmetic calculation with stated assumptions. The main weakness is the range metric: the abstract and conclusion advertise 130 m as the operational range even though this point corresponds to an 11% packet delivery ratio, and no minimum PDR threshold is defined. This makes the headline range claim load-bearing and in need of correction or careful qualification.

major comments (3)
  1. [Section V-B, Fig. 4, Abstract, Conclusion] The 130 m "operational range limit" is based on only 11 successful wake-up calls out of 100 (11% PDR), while PDRs above 94% are reported only up to 100 m. The paper never defines a minimum PDR or reliability criterion for the term "operational range limit." The abstract and conclusion present 130 m as the range without disclosing this caveat, which is misleading for a wake-up radio where a single missed wake-up call can be critical. Please define a PDR threshold (e.g., 90%) and report the corresponding range, or clearly state both the reliable range (about 100 m) and the last-successful-packet distance (130 m) in the abstract, results, and conclusion.
  2. [Section V-B and Section IV-C] The sensitivity value -72.62 dBm is reported without the PDR or packet-error criterion at which it was measured, and the PDR characterization at each distance is based on a single batch of 100 wake-up calls with no repeated trials. At 130 m, the 11/100 result has a 95% binomial confidence interval of roughly [5.6%, 18.7%], so the claimed range limit carries substantial statistical uncertainty. Please specify the detection criterion for sensitivity, report the number of repetitions, and provide confidence intervals or error bars for the PDR curve and the sensitivity value.
  3. [Section V-B and Section IV-B] The reported range claims appear inconsistent with a free-space link-budget check. With a transmitter power of 2.8 dBm, antenna gains of -2.1 dBi at both ends, and a measured sensitivity of -72.6 dBm, the free-space path loss at 100 m is about 71.2 dB, which places the sensitivity-limited range at roughly 100 m; at 130 m the received power would be about 2.3 dB below the reported sensitivity. The paper does not discuss this discrepancy. The authors should explain whether the 11% PDR at 130 m arises from multipath/fading, from the sensitivity definition, or from measurement variability, so that the range and sensitivity numbers are presented consistently.
minor comments (4)
  1. [Section II and Table I] The company name is written inconsistently as "RF ICICENT" in the introduction and "RF ICIENT" in Table I; please standardize the spelling.
  2. [Section III-A] The paper states that WakeMod is a "drop-in replacement" for HOPEF RFM modules based on a similar 16 mm x 16 mm footprint, but drop-in compatibility requires pin-level and electrical compatibility, which is not demonstrated; please rephrase to "footprint-compatible" or provide the pinout comparison.
  3. [Section V-A] The claim that the module's total consumption is "approximately 9% lower than the typical consumption figures specified in [29] for the FH101RF itself" is ambiguous because the datasheet range is 2.7-87.3 µW depending on data rate; please specify which datasheet configuration is used for the 9% comparison.
  4. [Section IV-C and V-B] The text says that no wake-up calls were successfully received at distances above 130 m, but the measurement distances above 130 m are not enumerated; please list the exact distances tested (e.g., 140 m, 150 m) so the reader knows the granularity of the "no success above 130 m" statement.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: all headline figures are direct measurements or transparent arithmetic estimates; the self-citations are not load-bearing for any derivational claim.

full rationale

WakeMod's central claims are empirical measurements, not derived predictions. The idle power of 6.9 uW, the per-event energy of 17.7 uJ, the latency of 54.3 ms, and the sensitivity of -72.6 dBm are all obtained from instrumentation (Keysight N6705C/N6781A, R&S SMBV100A, R&S FSIQ 3) and reported as measured values in Tables II and Fig. 3-4; there is no fitted model whose output is then relabeled as a prediction. The 130 m range figure is a measured PDR point (11% at 130 m, 0% beyond), not a derived quantity, and while the absence of an explicit PDR threshold for 'operational range limit' is a legitimate correctness/interpretation concern, it is not circularity. The battery life estimate is transparent arithmetic from measured idle power, display-update energy, and a stated CR2032 capacity and self-discharge assumption, with no parameter fitted to force the 8-year result. The paper cites several prior works by the same authors or group ([3], [14], [26], [28]), but only as related work or context; none of these citations supplies the uniqueness, ansatz, or calibrated parameters on which WakeMod's measured results depend. The FH101RF sensitivity and configuration are taken from an external manufacturer datasheet, not from the authors' own prior claims. No equation is defined in terms of another, no fitted input is renamed as a prediction, and no load-bearing step reduces to a self-citation chain. The derivation chain, insofar as there is one, is self-contained and directly tied to measurements and stated assumptions.

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

The core metrics are measured, not fitted, so there are no fitted free parameters. The main assumptions are the battery model inputs, the datasheet behavior of the FH101RF, and the unspecified PDR threshold used to call 130 m an operational range.

assumptions (3)
  • domain assumption The FH101RF datasheet values for sensitivity and power consumption are representative of the specific chip used and were correctly configured in the module.
    The module's headline sensitivity and idle power depend on the chip's internal behavior; the paper does not independently verify every datasheet claim beyond the measured module-level values.
  • domain assumption A CR2032 coin cell delivers 220 mAh at 3 V with 1 percent annual self-discharge over the estimated lifetime.
    Used in Section V-C for the 8-year battery estimate; real cells have voltage-dependent capacity, current-rate effects, and temperature behavior that can shift the result.
  • ad hoc to paper A wake-up call is considered successfully received even when the packet delivery ratio at that distance is only 11 percent.
    The 130 m operational range limit is set where PDR is 11 percent; no minimum PDR threshold is stated, making the '130 m range' claim sensitive to a loose success criterion.

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Cite this review

Pith. "Pith review of WakeMod: A 6.9uW Wake-Up Radio Module with -72.6dBm Sensitivity for On-Demand IoT." pith.science (2026). https://pith.science/paper/VF5SUHMQ

@misc{pith2026250521529,
  author       = {Pith},
  title        = {Pith review of: WakeMod: A 6.9uW Wake-Up Radio Module with -72.6dBm Sensitivity for On-Demand IoT},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VF5SUHMQ}},
  note         = {Machine review of arXiv:2505.21529}
}
read the original abstract

Large-scale Internet of Things (IoT) applications, such as asset tracking and remote sensing, demand multi-year battery lifetimes to minimize maintenance and operational costs. Traditional wireless protocols often employ duty cycling, introducing a tradeoff between latency and idle consumption - both unsuitable for event-driven and ultra-low power systems. A promising approach to address these issues is the integration of always-on wake-up radios (WuRs). They provide asynchronous, ultra-low power communication to overcome these constraints. This paper presents WakeMod, an open-source wake-up transceiver module for the 868MHz ISM band. Designed for easy integration and ultra-low power consumption, it leverages the -75dBm sensitive FH101RF WuR. WakeMod achieves a low idle power consumption of 6.9uW while maintaining responsiveness with a sensitivity of -72.6dBm. Reception of a wake-up call is possible from up to 130m of distance with a -2.1dBi antenna, consuming 17.7uJ with a latency below 54.3ms. WakeMod's capabilities have further been demonstrated in an e-ink price tag application, achieving 7.17uW idle consumption and enabling an estimated 8-year battery life with daily updates on a standard CR2032 coin cell. WakeMod offers a practical solution for energy-constrained, long-term IoT deployments, requiring low-latency, and on-demand communication.

Figures

Figures reproduced from arXiv: 2505.21529 by the authors.

Figure 1
Figure 1. System overview: High-level block diagram of the main platform [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. WakeTag: (a) Front view, (b) Back view. 0213BBDMFGN-R. As the display needs at least 2.7 V, it is directly powered by the non-rechargeable CR2032-sized 3 V coin cell battery. A dedicated boost converter circuit generates the positive and negative voltages required to drive the pixel electrodes. Both sub-systems are powered through a VISHAY SIP32431 power switch and can be disconnected from the battery to minimize po… view at source ↗
Figure 3
Figure 3. Power consumption of WAKEMOD during reception (a) and transmission (b) of a WuC. (c) shows an analysis of the transmitter’s spectrum at 1.8 V. on the supply voltage is evident. As the voltage increases from 1.8 V to 3.3 V, the transmitted power increases from 2.78 dBm to 10.92 dBm. Jointly, the module’s power consumption during transmission rises substantially, from 26.08 mW to 108.54 mW [PITH_FULL_IMAGE:figures/fu… view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: PDR of wake-up calls sent and received by WA [PITH_FULL_IMAGE:figures/full_fig_p005_4.png]
Figure 5
Figure 5. Figure 5: Power profile of WAKETAG on receiving a single WuC and refreshing the display. C. WakeTag Evaluation The power consumption of WAKETAG, as illustrated in [PITH_FULL_IMAGE:figures/full_fig_p005_5.png]

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Reference graph

Works this paper leans on

30 extracted references · 16 canonical work pages

  1. [1]

    Internet of things for smart factories in industry 4.0, a review,

    M. Soori, B. Arezoo, and R. Dastres, “Internet of things for smart factories in industry 4.0, a review,” Internet of Things and Cyber-Physical Systems, vol. 3, pp. 192–204, 2023. [Online]. Available: http://dx.doi.org/10.1016/j.iotcps.2023.04.006

  2. [2]

    Towards a non-invasive monitoring system for wind turbine blades,

    N. Scharer, T. Polonelli, J. Deparday, and M. Magno, “Towards a non-invasive monitoring system for wind turbine blades,” in 2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) , 5 2024, pp. 1–6. [Online]. Available: http: //dx.doi.org/10.1109/I2MTC60896.2024.10561240

  3. [3]

    A passive and asynchronous wake-up receiver for acoustic underwater communication,

    L. Schulthess, P. Mayer, L. Benini, and M. Magno, “A passive and asynchronous wake-up receiver for acoustic underwater communication,” in 2024 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) , 6 2024, pp. 480–485. [Online]. Available: http://dx.doi.org/10.1109/SPEEDAM61530.2024.10609075

  4. [4]

    Internet of things integrated with solar energy applications: a state-of-the-art review,

    D. C. Nath, I. Kundu, A. Sharma, P. Shivhare, A. Afzal, M. E. M. Soudagar, and S. G. Park, “Internet of things integrated with solar energy applications: a state-of-the-art review,” Environment, Development and Sustainability, vol. 26, no. 10, pp. 24 597–24 652, 2023. [Online]. Available: http://dx.doi.org/10.1007/s10668-023-03691-2

  5. [5]

    Thermal energy harvester using ambient temperature fluctuations for self-powered wireless iot sensing systems: a review,

    T. T. K. Tuoi, N. V . Toan, and T. Ono, “Thermal energy harvester using ambient temperature fluctuations for self-powered wireless iot sensing systems: a review,” Nano Energy , vol. 121, p. 109186, 2024. [Online]. Available: http://dx.doi.org/10.1016/j.nanoen.2023.109186

  6. [6]

    Integration of wireless power transfer and low power wide area networks in iot applications-a review,

    M. J. Makhetha, E. D. Markus, and A. M. Abu-Mahfouz, “Integration of wireless power transfer and low power wide area networks in iot applications-a review,” Sensors International , vol. 5, p. 100284, 2024. [Online]. Available: http://dx.doi.org/10.1016/j.sintl.2024.100284

  7. [7]

    Energy efficient adaptive sensing framework for wsn-assisted iot applications,

    R. Bensaid, A. B. Mnaouer, and H. Boujemaa, “Energy efficient adaptive sensing framework for wsn-assisted iot applications,” IEEE Access, vol. 12, pp. 93 033–93 050, 2024. [Online]. Available: http://dx.doi.org/10.1109/ACCESS.2024.3423706

  8. [8]

    Event-triggered sensing for high-quality and low-power cardiovascular monitoring systems,

    G. Surrel, T. Teijeiro, A. Aminifar, D. Atienza, and M. Chevrier, “Event-triggered sensing for high-quality and low-power cardiovascular monitoring systems,” IEEE Design & Test , vol. 37, no. 5, pp. 85– 93, 2020. [Online]. Available: http://dx.doi.org/10.1109/MDAT.2019. 2951126

Show all 30 references
  1. [9]

    Power consumption reduction for iot devices thanks to edge-ai: Application to human activity recognition,

    A. C. Muhoza, E. Bergeret, C. Brdys, and F. Gary, “Power consumption reduction for iot devices thanks to edge-ai: Application to human activity recognition,” Internet of Things , vol. 24, p. 100930, 2023. [Online]. Available: http://dx.doi.org/10.1016/j.iot.2023.100930

  2. [10]

    Device vs edge computing for mobile services: Delay-aware decision making to minimize power consumption,

    M. Masoudi and C. Cavdar, “Device vs edge computing for mobile services: Delay-aware decision making to minimize power consumption,” IEEE Transactions on Mobile Computing , vol. 20, no. 12, pp. 3324–3337, 2021. [Online]. Available: http://dx.doi.org/10. 1109/TMC.2020.2999784

  3. [11]

    Synchronous transmissions in low-power wireless,

    M. Zimmerling, L. Mottola, and S. Santini, “Synchronous transmissions in low-power wireless,” ACM Computing Surveys , vol. 53, no. 6, pp. 1–39, 2021. [Online]. Available: http://dx.doi.org/10.1145/3410159

  4. [12]

    Survey on latency issues of asynchronous mac protocols in delay-sensitive wireless sensor networks,

    M. Doudou, D. Djenouri, and N. Badache, “Survey on latency issues of asynchronous mac protocols in delay-sensitive wireless sensor networks,” IEEE Communications Surveys & Tutorials , vol. 15, no. 2, pp. 528–550, 2013. [Online]. Available: http: //dx.doi.org/10.1109/SURV .2012...

  5. [13]

    Sutton, R

    F. Sutton, R. D. Forno, J. Beutel, and L. Thiele, “Blitz,” ACM Transactions on Sensor Networks , vol. 15, no. 2, pp. 1–38, 2019. [Online]. Available: http://dx.doi.org/10.1145/3309702

  6. [14]

    Wakeloc: an ultra-low power, accurate and scalable on-demand rtls using wake-up radios,

    S. Cortesi, C. V ogt, and M. Magno, “Wakeloc: an ultra-low power, accurate and scalable on-demand rtls using wake-up radios,” 2025. [Online]. Available: https://arxiv.org/abs/2504.20545

  7. [15]

    Energy- efficient timetable display for meeting rooms using e-paper technology and low-powered microcontrollers,

    C. Szab ´o, K.-T. Antal, L.-Z. Bartus, and K. Simon, “Energy- efficient timetable display for meeting rooms using e-paper technology and low-powered microcontrollers,” in 2023 IEEE 21st Jubilee International Symposium on Intelligent Systems and Informatics (SISY), 9 2023, pp. ...

  8. [16]

    Intelligent integration of e-ink displays: Leveraging electronics for label automation and enhanced user experience,

    S. E, S. E. M, D. K, B. M, and D. S, “Intelligent integration of e-ink displays: Leveraging electronics for label automation and enhanced user experience,” in 2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS) , 7 2024, pp. 169–174. [Online]....

  9. [17]

    Shellhammer, A

    S. Shellhammer, A. Asterjadhi, and Y . Sun, Wak-up Radio Concept . Wiley-IEEE Press, 2023, pp. 25–42. [Online]. Available: http: //dx.doi.org/10.1002/9781119671015.ch3

  10. [18]

    Charging and wake-up of iot devices using harvested rf energy with near- zero power consumption,

    A. A. Benbuk, N. Kouzayha, J. Costantine, and Z. Dawy, “Charging and wake-up of iot devices using harvested rf energy with near- zero power consumption,” IEEE Internet of Things Magazine , vol. 6, no. 1, pp. 162–167, 2023. [Online]. Available: http: //dx.doi.org/10.1109/IOTM.0...

  11. [19]

    Low-power rf wake-up receivers: Analysis, tradeoffs, and design,

    P. P. Mercier, B. H. Calhoun, P.-H. P. Wang, A. Dissanayake, L. Zhang, D. A. Hall, and S. M. Bowers, “Low-power rf wake-up receivers: Analysis, tradeoffs, and design,” IEEE Open Journal of the Solid-State Circuits Society , vol. 2, pp. 144–164, 2022. [Online]. Available: http:...

  12. [20]

    A tuned-rf duty-cycled wake-up receiver with -90 dbm sensitivity,

    S. Bdiri, F. Derbel, and O. Kanoun, “A tuned-rf duty-cycled wake-up receiver with -90 dbm sensitivity,” Sensors, vol. 18, no. 2, p. 86, 2017. [Online]. Available: http://dx.doi.org/10.3390/s18010086

  13. [21]

    Wake-up radio enabled ble wearables: empirical and analytical evaluation of energy efficiency,

    K. Mikhaylov and H. Karvonen, “Wake-up radio enabled ble wearables: empirical and analytical evaluation of energy efficiency,” in 2020 14th International Symposium on Medical Information Communication Technology (ISMICT) , 5 2020. [Online]. Available: http://dx.doi.org/10.1109...

  14. [22]

    Enabling low-latency bluetooth low energy on energy harvesting batteryless devices using wake-up radios,

    A. K. Sultania, C. Delgado, and J. Famaey, “Enabling low-latency bluetooth low energy on energy harvesting batteryless devices using wake-up radios,” Sensors, vol. 20, no. 18, p. 5196, 2020. [Online]. Available: http://dx.doi.org/10.3390/s20185196

  15. [23]

    A 2.4uw wake-up receiver for wireless sensor nodes with -71dbm sensitivity,

    C. Hambeck, S. Mahlknecht, and T. Herndl, “A 2.4uw wake-up receiver for wireless sensor nodes with -71dbm sensitivity,” in 2011 IEEE International Symposium of Circuits and Systems (ISCAS) , 5 2011, pp. 534–537. [Online]. Available: http://dx.doi.org/10.1109/ISCAS.2011. 5937620

  16. [24]

    Beyond duty cycling: Wake-up radio with selective awakenings for long-lived wireless sensing systems,

    D. Spenza, M. Magno, S. Basagni, L. Benini, M. Paoli, and C. Petrioli, “Beyond duty cycling: Wake-up radio with selective awakenings for long-lived wireless sensing systems,” in 2015 IEEE Conference on Computer Communications (INFOCOM) , 4 2015, p. 9. [Online]. Available: http...

  17. [25]

    Sutton, B

    F. Sutton, B. Buchli, J. Beutel, and L. Thiele, “Zippy,” in Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems , 11

  18. [26]

    Ultra-low power wake-up receiver for location aware objects operating with uwb,

    T. Polonelli, F. Villani, and M. Magno, “Ultra-low power wake-up receiver for location aware objects operating with uwb,” in 2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) , 10 2021, p. 8. [Online]. Available: http://...

  19. [27]

    A novel architecture for semi-active wake-up radios attaining sensitivity beyond -70dbm: Demo abstrace,

    G. Kazdaridis, N. Sidiropoulos, I. Zografopoulos, and T. Korakis, “A novel architecture for semi-active wake-up radios attaining sensitivity beyond -70dbm: Demo abstrace,” in 2021 20th International Conference on Information Processing in Sensor Networks , 5 2021, pp. 398–399....

  20. [28]

    A 36nw ultra- wideband wake-up receiver with -86dbm sensitivity and addressing capabilities,

    F. Villani, E. Masina, T. Burger, and M. Magno, “A 36nw ultra- wideband wake-up receiver with -86dbm sensitivity and addressing capabilities,” in 2024 IEEE International Symposium on Circuits and Systems (ISCAS) , 5 2024, p. 5. [Online]. Available: http: //dx.doi.org/10.1109/I...

  21. [29]

    Rficient® ultra-low power wake-up receiver fh101rf datasheet,

    LZE GMBH, “Rficient® ultra-low power wake-up receiver fh101rf datasheet,” Frauenhofer IIS, 2024, FH101RF LZE Datasheet Revision 1p3b A1. [Online]. Available: https://cdn.shopify.com/s/files/1/0315/ 0879/1435/files/FH101RF LZE Datasheet Revision 1p3b A 1.pdf

  22. [2015]

    Available: http://dx.doi.org/10.1145/2809695.2809705

    [Online]. Available: http://dx.doi.org/10.1145/2809695.2809705

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.