Physical Layer Design for Ambient IoT

Anil Kumar Yerrapragada; Radha Krishna Ganti; Rohit Singh

REVIEW 3 major objections 7 minor 1 cited by

Physical Layer Design for Ambient IoT

T0 review · 3 major / 7 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read The paper maps the 3GPP Ambient IoT physical layer and shows through link simulations that adaptive thresholding beats fixed thresholding on the reader-to-device link and a second receive antenna yields about 2 dB on the device-to-reader…

desk verdict Useful, honest 3GPP A-IoT PHY survey with a solid R2D simulation; the D2R antenna-gain claim is not established because the model omits the carrier wave and small frequency shift that define real backscatter. read the letter →

arxiv 2501.09416 v1 pith:AWMCKDU3 submitted 2025-01-16 eess.SP

Rohit Singh , Anil Kumar Yerrapragada , Radha Krishna Ganti This is my paper · ORCID

classification eess.SP

keywords AmbientIoTbackscattercommunication3GPPphysicallayerOOKmodulationDFT-spreadOFDMlink-levelsimulationadaptivethresholdingdevice-to-readerlink

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

Ambient IoT aims to bring battery-less, maintenance-free devices into cellular networks by using backscatter communication, and this paper lays out the physical layer that 3GPP is standardizing for it: one reader-to-device channel (PRDCH) built on OOK over DFT-spread OFDM, one device-to-reader channel (PDRCH) built on backscatter with line coding and a small frequency shift, plus the associated timing signals, midambles, and random access procedure. Against that design, the paper runs link-level simulations under 3GPP evaluation assumptions (TDL-A channel, 30 ns delay spread, 3 km/h, 0.9 GHz) to compare receiver and configuration choices. Its central simulation findings are that adaptive thresholding beats fixed thresholding for both tested transport block sizes, that a second receive antenna gives about 2 dB of gain on the device-to-reader link, and that raising the number of OOK chips per OFDM symbol raises data rate but costs SNR per chip. A sympathetic reader would care because these are the concrete choices that determine whether battery-less devices can actually close the link in the standard being written.

What carries the argument

The mechanism that carries the argument is the physical-layer chain itself: for R2D, OOK-4 chips (1, 2, or 4 chips per OFDM symbol) generated by DFT-spread OFDM with 15 kHz subcarrier spacing, received by RF envelope detection with fixed or adaptive thresholding; for D2R, Manchester-coded OOK baseband at 7.5 kchips/s backscattered from a carrier, received non-coherently with thresholding and optional equal-gain combining across two antennas. Adaptive thresholding — a mean over four consecutive chips used as the comparison level — does the main work in the R2D simulations, acting as a form of channel equalization by following the Doppler-induced envelope.

What would settle it

Run the same link-level configurations at passband with the carrier wave and small frequency shift included, plus oscillator drift near the roughly 105 ppm budget; if adaptive thresholding no longer beats fixed thresholding on either transport block size, or the two-antenna D2R gain drops well below 2 dB, the paper's rankings would not carry over to real operation.

Watch

Extended reading notes

Core claim

The paper's central assertion is that the 3GPP Ambient IoT physical layer can be built around two minimal channels — a reader-to-device channel (PRDCH) that sends OOK chips on a DFT-spread OFDM waveform and a device-to-reader channel (PDRCH) that backscatters line-coded, frequency-shifted baseband data onto a carrier wave — and that the performance of these channels is governed by a few receiver-side choices. Link-level simulations show adaptive thresholding outperforming fixed thresholding for transport block sizes 20 and 96 bits, with the gain larger for the longer block because the threshold tracks the channel envelope caused by Doppler. On the device-to-reader link, a second receive antenna with equal-gain combining gives almost 2 dB improvement, and it removes the high-SNR error floor seen with one antenna at 96 bits. The paper also documents the transmitter and receiver chains for both links, the random access procedure, and the four deployment topologies, positioning this as a design summary plus a first-order performance comparison for the ongoing standardization.

Load-bearing premise

The load-bearing premise is that the simplified link-level simulation setup — TDL-A channel at 30 ns delay spread and 3 km/h, no FEC or repetition, baseband-only D2R with no carrier wave or small frequency shift, and 1.92 Msps resampling — is representative enough that the qualitative rankings (adaptive over fixed thresholding, two antennas over one, the M tradeoff) hold in real A-IoT operation.

Editorial extensions

If this is right

A battery-less A-IoT device can implement an R2D receiver with sample-by-sample threshold comparison and majority voting, since the paper finds adaptive thresholding improves results without per-symbol averaging.
Standardization can select adaptive thresholding over fixed thresholding with no change to the PRDCH waveform, since the gain comes entirely from receiver processing.
Deploying two receive antennas at the reader is a concrete coverage lever: about 2 dB on the D2R link, and it removes the high-SNR Doppler floor for 96-bit blocks.
The number of chips per OFDM symbol M should be set against link budget, because doubling M increases data rate but requires more SNR to hold the same BLER.
Smaller transport blocks (20 bits versus 96 bits) are more robust under Doppler and are therefore a natural choice for control or status messages.

Reading between the lines

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

Because the D2R simulations are baseband-only, the interaction between the small frequency shift and the non-coherent threshold receiver is untested; adding the carrier wave and shift could change the optimal thresholding window, so a natural next simulation is the full passband model.
The adaptive-thresholding gain over longer blocks hints that the same receiver logic could extend A-IoT operation to device velocities higher than the 3 km/h evaluation assumption, since threshold tracking is what compensates for Doppler.
The paper's no-FEC, no-repetition baseline implies the practical gain of the two-antenna receiver may shrink once repetition and convolutional coding are added, since those mechanisms also combat Doppler; a testable extension is to rerun the D2R curves with the Release 19 repetition options enabled.
Since the carrier wave can come from outside the topology, the effective D2R link budget depends on where the continuous wave originates; a full system-level study could translate the 2 dB antenna gain into coverage or deployment-density terms.

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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

Here's my read on arXiv:2501.09416. It's a competent, clearly written summary of where 3GPP's Ambient IoT physical layer stands, based mainly on TR 38.769 and RAN1 agreements, with link-level simulations comparing thresholding, chips-per-OFDM-symbol, and receiver antenna count. If you need a single entry point to the A-IoT PHY—device types, topologies, PRDCH/PDRCH structure, R-TAS/D-TAS, line coding, the small frequency shift for multiple access, random access—this paper gives you that. That is real value, and the authors clearly know the standards material.

The simulations are more mixed. The R2D part is reasonably anchored: parameters follow 3GPP evaluation assumptions, TDL-A with 30 ns delay spread at 3 km/h, RF-ED receiver, fixed and adaptive thresholding. The qualitative conclusions—adaptive thresholding helps more on larger transport blocks, larger M costs power per chip, smaller TBS is more robust—are plausible and internally consistent. I don't see fabrication or circularity; nothing is fitted to a target.

The soft spot is the D2R simulation, and it is load-bearing. Section IV says the D2R runs are done in baseband and that 'carrier wave and small frequency shift are not used.' That is not a benign simplification for this link. Section III-B1 describes the small frequency shift as the mechanism that separates the backscattered signal from the carrier leakage and enables multiple access. Omitting both means the simulation is essentially a conventional baseband OOK link, not a backscatter link. So the headline D2R result—'almost 2 dB improvement with 2 receiver antennas'—is not established for the actual A-IoT device-to-reader channel. The paper is honest about the simplification in one sentence, but still presents the antenna-count comparison as a robust finding. That overstates the evidence. The 'for any TBS' generalization also exceeds the two tested TB sizes, and there are no confidence intervals or code, so the reader cannot assess variability.

Who is this for? Engineers and researchers new to A-IoT who want a map of the 3GPP PHY discussion, and standards people who want a quick reference. It is not a paper that breaks new scientific ground. But it is a useful, honest overview with a legitimate—if incomplete—R2D evaluation.

I would send it to review, not desk-reject it. A serious referee should push for either a D2R model that includes the carrier wave and small frequency shift, or a much more careful statement that the 2 dB gain is from a baseband-only model and may not carry over. Also ask for error bars or code. With those changes, this becomes a solid reference for the community.

Referee Report

3 major / 7 minor

Summary. This paper presents an overview of the 3GPP Release 19 Ambient IoT (A-IoT) physical layer design as captured in recent 3GPP TRs, covering device types, topology options, the reader-to-device (PRDCH) and device-to-reader (PDRCH) channels, and the random access framework. It then reports link-level simulations for two links: R2D with OOK-4 DFT-s-OFDM under fixed and adaptive thresholding at M=1,2,4 chips per symbol, and D2R with Manchester-coded OOK, a non-coherent receiver, adaptive thresholding, and one vs. two receiver antennas with equal gain combining. The main empirical claims are that adaptive thresholding outperforms fixed thresholding for all tested TBS and M values, and that two receiver antennas give almost 2 dB gain on the D2R link.

Significance. If the simulation results are reliable, the paper offers a useful, accessible summary of the 3GPP A-IoT PHY and indicative relative comparisons. The overview portion is a strong point: it is clearly organized and appears consistent with the cited TRs (TR 38.848, TR 38.769, RAN1 agreements), and it does not attempt to hide the provisional nature of the standardization items. The simulation study is also transparent about many parameter choices, including the channel model, sampling rates, and receiver structures. However, the quantitative D2R conclusion is based on a deliberately simplified baseband model that omits two features the paper itself identifies as essential to the A-IoT D2R design, so the stated antenna gain is not established for the actual PDRCH. The absence of error bars and code further limits confidence in the exact dB figures, though the qualitative directions may still be reasonable.

major comments (3)

[Section IV (D2R paragraph) and Section III-B1] The D2R link-level simulation is run "in the baseband and carrier wave and small frequency shift are not used." This is not a benign simplification for the antenna-gain claim. In Section III-B1 the small frequency shift is the mechanism that separates backscattered data from carrier leakage and enables multiple access; the PDRCH receiver in Section III-B2 is described as compensating for this shift after down-conversion. Omitting the carrier wave removes the strong self-interference/DC offset that a real non-coherent detector must suppress, so the simulated channel is effectively a conventional baseband OOK link rather than a backscatter channel. The "almost 2 dB improvement with 2 receiver antennas" is therefore an idealized result that may not transfer to the A-IoT D2R channel. The authors should either add representative simulations with the carrier wave and small frequency shift (including at least a simplified model of leakage) or explicitly re-scope the claim as an ideal-channel lower bound and temper the abstract and conclusion accordingly.
[Section IV (D2R paragraph) and Section III-B1/B2] The simulations deliberately omit FEC, repetition, and the midamble ("For a basic understanding of the link, FEC and repetition are not used"), even though these are integral parts of the PDRCH design described earlier and are used in the receiver for channel, SFO and CFO estimation. With no midamble and no FEC, the simulation receiver is not the PDRCH receiver architecture of Section III-B2, and the link comparisons do not exercise the mechanisms that dominate D2R coverage in practice. The paper should include at least one configuration with FEC/repetition/midamble, or clearly label the presented results as an idealized stripped-down link rather than as a comparison of the standardized PDRCH configurations.
[Section IV, Fig. 5] No information is given on the number of Monte Carlo trials, channel realizations, or confidence intervals for the BLER curves, and no simulation code is provided. Since the central claims are empirical ("adaptive thresholding performs better than fixed thresholding for any TBS", "almost 2 dB improvement"), the absence of statistical characterization makes it impossible to assess whether the observed differences are significant. At minimum, the number of runs should be reported, and preferably confidence intervals or the simulation code should be made available.

minor comments (7)

[Section IV] The sentence "As a baseline, for R2D, the midamble is not considered in our simulations" appears to be a typo for "for D2R", since midambles are only defined for the D2R link in Section III-B.
[Table I] The D2R row "Transmission bandwidth, Chip rate 15 kHz, 7.5 kchips/sec" and the row "Line coding, Modulation Manchester, OOK" should each be split into separate parameter entries for clarity.
[Section III-A1] The chip length formula "Chip Length = 1 M × SCS" is ambiguous; it should be written as 1/(M × SCS), and the data rate formula should define the effective number of bits and the total symbol count explicitly.
[Section IV (R2D paragraph)] The expression "4096/32 M samples per chip" is unclear; with resampling from 61.44 Msps to 1.92 Msps, one OFDM symbol of 4096 samples becomes 128 samples, so the samples per chip is 128/M; please rewrite.
[Section III-B2] The statement "Adaptive thresholding can be used to remove the channel effects" should be rephrased as "mitigate" or "equalize", since thresholding cannot fully remove channel effects.
[Throughout] Several typos remain: "presene" (Section IV), "deterimined" (Section III-A2), "presene of Doppler" should be "presence", and "line coded symbol is called a chip" should be "line-coded".
[References] Reference [13] is cited as the source for the OOK-4 DFT-s-OFDM waveform; please confirm that this is the correct TR (possibly TR 38.769 rather than TR 38.869) and update if needed.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity identified; the paper's derivations and simulation comparisons are self-contained and do not reduce to their inputs by construction.

full rationale

The paper presents an overview of 3GPP Ambient IoT physical layer design and link-level simulation results. The design content is attributed to external 3GPP documents and other public references, not to a claim derived from the paper's own output. The simulation comparisons are empirical: the paper simulates PRDCH with fixed versus adaptive thresholding and different numbers of chips per OFDM symbol, and simulates PDRCH with one versus two receiver antennas. These are not quantities defined in terms of fitted parameters, nor are any simulation conclusions used to define the inputs. The statement that 'adaptive thresholding performs better than fixed thresholding for any TBS' is a reported simulation outcome, and the paper gives a plausible mechanism ('adaptive thresholding acts as a kind of channel equalizer'), but the comparison is not circular because the thresholding methods are independent detection configurations, not parameters fitted to the BLER curves being reported. Similarly, the 'almost 2 dB improvement with 2 receiver antennas' is an observed comparison under the stated assumptions, not an analytical identity. The acknowledged simplification for D2R that 'these simulations are carried out in the baseband and carrier wave and small frequency shift are not used' is a modeling limitation that may affect whether the quantitative gains carry over to real backscatter operation, but it does not make the simulation conclusion equivalent to its input by definition. There are no self-citations in the load-bearing argument, no imported uniqueness theorem, and no renamed known result presented as a derivation. The paper is self-contained against external benchmarks: the PHY design comes from 3GPP agreements and the simulations use standard evaluation assumptions with clearly stated parameters. Therefore the appropriate finding is no significant circularity.

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

The central results do not come from a closed-form derivation, so the ledger records the domain assumptions and hand-chosen simulation parameters. No parameters are fitted to a target conclusion, and no new physical entities are postulated. The main burden is that the simulation scenario is assumed representative of 3GPP evaluation and real deployments.

free parameters (4)

TDL-A delay spread and device velocity = 30 ns, 3 km/h
Simulation channel parameters chosen from 3GPP evaluation assumptions; all BLER curves depend on this single benign channel profile.
D2R chip rate = 7.5 kchips/s
Adopted for the PDRCH simulations; modulates sampling-per-chip count (256 samples/chip) and data rate, but is not fitted to the conclusions.
Adaptive threshold averaging window = mean over 4 consecutive chips
Chosen for both R2D and D2R thresholding; no sensitivity analysis is shown, so the reported adaptive-thresholding gain depends on this window.
M, chips per OFDM symbol = 1, 2, 4
Explored design axis; performance trends (higher data rate, lower per-chip power) depend on these chosen values.

assumptions (4)

domain assumption The TDL-A channel with 30 ns delay spread and 3 km/h device velocity is representative of A-IoT deployment for both R2D and D2R links.
Section IV, Table I sets these parameters 'in accordance with the A-IoT evaluation assumptions agreements in 3GPP Release 19'; the simulation conclusions inherit this representativeness assumption.
domain assumption The RF envelope detector can be modeled as square-law detection followed by low-pass filtering, resampling at 1.92 Msps, and threshold comparison.
Section III.A.2 describes RF-ED implementation; Section IV uses it with fixed and adaptive thresholding. The LLS results depend on this receiver model.
domain assumption A baseband-only D2R simulation without carrier wave, small frequency shift, FEC, or repetition preserves the relative performance of the compared receiver configurations.
Section IV states 'For simplicity, these simulations are carried out in the baseband and carrier wave and small frequency shift are not used.' The 2-RX and Doppler conclusions rest on this simplification.
domain assumption The R-TAS preamble can provide reliable threshold, chip-duration, and sampling-frequency-offset estimates to the device before PRDCH decoding.
Section III.A.2 says 'The threshold information, the chip length, and the correct sampling frequency obtained from R-TAS helps the device to decode the PRDCH.' The R2D LLS assumes these estimates are available.

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Cite this review

Pith. "Pith review of Physical Layer Design for Ambient IoT." pith.science (2026). https://pith.science/paper/AWMCKDU3

@misc{pith2026250109416,
  author       = {Pith},
  title        = {Pith review of: Physical Layer Design for Ambient IoT},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/AWMCKDU3}},
  note         = {Machine review of arXiv:2501.09416}
}

read the original abstract

There is a growing demand for ultra low power and ultra low complexity devices for applications which require maintenance-free and battery-less operation. One way to serve such applications is through backscatter devices, which communicate using energy harvested from ambient sources such as radio waves transmitted by a reader. Traditional backscatter devices, such as RFID, are limited by range, interference, low connection density, and security issues. To address these problems, the Third Generation Partnership Project (3GPP) has started working on Ambient IoT (A-IoT). For the realization of A-IoT devices, various aspects ranging from physical layer design, to the protocol stack, to the device architecture should be standardized. In this paper, we provide an overview of the standardization efforts on the physical layer design for A-IoT devices. The various physical channels and signals are discussed, followed by link level simulations to compare the performance of various configurations of reader to device and device to reader channels.

Figures

Figures reproduced from arXiv: 2501.09416 by the authors.

**Figure 1.** Various topologies for Ambient IoT • Topology 1: In Topology 1, an A-IoT device directly communicates with a base station in a bi-directional manner. The communication between the base station and the A-IoT device includes A-IoT data and/or signaling. This topology includes the possibility that the base station transmitting to the A-IoT device is different from the base station receiving from the A-IoT device. • Top… view at source ↗

**Figure 2.** Physical channels and signals for A-IoT. (a) Reader to device (R2D) (b) Device to reader (D2R) [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗

**Figure 3.** PRDCH transmitter and receiver design. (a) PRDCH transmitter architecture at the reader. (b) PRDCH receiver [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗

Figures from the paper (2 more)

**Figure 4.** Figure 4: PDRCH transmitter and receiver design. (a) PDRCH transmitter architecture at the Ambient IoT device. (b) PDRCH [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]

**Figure 5.** Figure 5: Link level simulations for R2D and D2R. (a) PRDCH [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

Considerations on the Design of Transceivers for Ambient Internet of Things
eess.SY 2025-04 reject novelty 4.0 of 10

An approximate low-IF, crystal-less receiver with carrier-auxiliary IF feedback LO synthesis is proposed for Type-B/C Ambient IoT, with -88 dBm sensitivity estimated from a link budget rather than measured.

Reference graph

Works this paper leans on

15 extracted references · 15 canonical work pages · cited by 1 Pith paper

[1]

RFID security and privacy: a research survey,

A. Juels, “RFID security and privacy: a research survey,” IEEE Journal on Selected Areas in Communications , vol. 24, no. 2, pp. 381–394, 2006

work page 2006
[2]

NB-IoT and LTE- M towards massive MTC: Complete performance evaluation for 5g mMTC,

A. Abou El Hassan, A. El Mehdi, and M. Saber, “NB-IoT and LTE- M towards massive MTC: Complete performance evaluation for 5g mMTC,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 23, no. 1, pp. 308–320, 2021

work page 2021
[3]

Wireless energy harvesting for the Internet of Things,

P. Kamalinejad, C. Mahapatra, Z. Sheng, S. Mirabbasi, V . C. M. Leung, and Y . L. Guan, “Wireless energy harvesting for the Internet of Things,” IEEE Communications Magazine , vol. 53, no. 6, pp. 102–108, 2015

work page 2015
[4]

Ambient Backscatter: Wireless Communication Out of Thin Air,

V . Liu, A. Parks, V . Talla, S. Gollakota, D. Wetherall, and J. R. Smith, “Ambient Backscatter: Wireless Communication Out of Thin Air,” ACM SIGCOMM computer communication review , vol. 43, no. 4, pp. 39–50, 2013

work page 2013
[5]

Ambient Backscatter Communications: A Contemporary Survey,

N. Van Huynh, D. T. Hoang, X. Lu, D. Niyato, P. Wang, and D. I. Kim, “Ambient Backscatter Communications: A Contemporary Survey,”IEEE Communications Surveys & Tutorials , vol. 20, no. 4, pp. 2889–2922, 2018

work page 2018
[6]

Study on Ambient IoT (Internet of Things) in RAN,

3GPP, “Study on Ambient IoT (Internet of Things) in RAN,” 3GPP, Tech. Rep. TR 38.848 V18.0.0, Sep.2023

work page 2023
[7]

RAN1 Chair’s Notes,

3GPP RAN 1, “RAN1 Chair’s Notes,” 3GPP, Tech. Rep., Nov.2024

work page 2024
[8]

5G Network Enhancements to Support Ambient IoT Devices,

A. K. Salkintzis and D. Dimopoulos, “5G Network Enhancements to Support Ambient IoT Devices,” in 2023 IEEE Conference on Standards for Communications and Networking (CSCN) , 2023, pp. 302–307

work page 2023

Show all 15 references

[9]

Ambient IoT: A Missing Link in 3GPP IoT Devices Landscape,

M. M. Butt, N. R. Mangalvedhe, N. K. Pratas, J. Harrebek, J. Kimionis, M. Tayyab, O.-E. Barbu, R. Ratasuk, and B. Vejlgaard, “Ambient IoT: A Missing Link in 3GPP IoT Devices Landscape,” IEEE Internet of Things Magazine , vol. 7, no. 2, pp. 85–92, 2024

2024
[10]

Ambient IoT: Insight and Challenge of Enabling Technologies for Future Study,

R. Jian, Y . Ding, M. Qu, J. Miao, X. Tang, W. Huang, and Y . Zhang, “Ambient IoT: Insight and Challenge of Enabling Technologies for Future Study,” in 2024 6th International Conference on Electronics and Communication, Network and Computer Technology (ECNCT) , 2024, pp. 451–458

2024
[11]

Cellular Backscatter Communication: Ambient IoT Technology,

J. Xin and S. Xu, “Cellular Backscatter Communication: Ambient IoT Technology,” in 2024 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) , 2024, pp. 1–6

2024
[12]

Ambient IoT Toward 6G: Standardization, Potentials, and Challenges,

K. Zheng, R. Xu, J. Mei, H. Yang, L. Lei, and X. Wang, “Ambient IoT Toward 6G: Standardization, Potentials, and Challenges,” IEEE Access, vol. 12, pp. 146 668–146 677, 2024

2024
[13]

Study on low-power wake-up signal and receiver for NR,

3GPP, “Study on low-power wake-up signal and receiver for NR,” 3GPP, Tech. Rep. TR 38.869 V18.0.0, Dec.2023

2023
[14]

Study on solutions for Ambient IoT (Internet of Things),

3GPP, “Study on solutions for Ambient IoT (Internet of Things),” 3GPP, Tech. Rep. TR 38.769 V2.0.0, Dec.2024

2024
[15]

EPC Radio-Frequency Identity Protocols Class-1 Generation-2 UHF RFID Protocol for Communications at 860 MHz–960 MHz,

“EPC Radio-Frequency Identity Protocols Class-1 Generation-2 UHF RFID Protocol for Communications at 860 MHz–960 MHz,” EPCglobal Standard Specification

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.

[1] [1]

RFID security and privacy: a research survey,

A. Juels, “RFID security and privacy: a research survey,” IEEE Journal on Selected Areas in Communications , vol. 24, no. 2, pp. 381–394, 2006

work page 2006

[2] [2]

NB-IoT and LTE- M towards massive MTC: Complete performance evaluation for 5g mMTC,

A. Abou El Hassan, A. El Mehdi, and M. Saber, “NB-IoT and LTE- M towards massive MTC: Complete performance evaluation for 5g mMTC,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 23, no. 1, pp. 308–320, 2021

work page 2021

[3] [3]

Wireless energy harvesting for the Internet of Things,

P. Kamalinejad, C. Mahapatra, Z. Sheng, S. Mirabbasi, V . C. M. Leung, and Y . L. Guan, “Wireless energy harvesting for the Internet of Things,” IEEE Communications Magazine , vol. 53, no. 6, pp. 102–108, 2015

work page 2015

[4] [4]

Ambient Backscatter: Wireless Communication Out of Thin Air,

V . Liu, A. Parks, V . Talla, S. Gollakota, D. Wetherall, and J. R. Smith, “Ambient Backscatter: Wireless Communication Out of Thin Air,” ACM SIGCOMM computer communication review , vol. 43, no. 4, pp. 39–50, 2013

work page 2013

[5] [5]

Ambient Backscatter Communications: A Contemporary Survey,

N. Van Huynh, D. T. Hoang, X. Lu, D. Niyato, P. Wang, and D. I. Kim, “Ambient Backscatter Communications: A Contemporary Survey,”IEEE Communications Surveys & Tutorials , vol. 20, no. 4, pp. 2889–2922, 2018

work page 2018

[6] [6]

Study on Ambient IoT (Internet of Things) in RAN,

3GPP, “Study on Ambient IoT (Internet of Things) in RAN,” 3GPP, Tech. Rep. TR 38.848 V18.0.0, Sep.2023

work page 2023

[7] [7]

RAN1 Chair’s Notes,

3GPP RAN 1, “RAN1 Chair’s Notes,” 3GPP, Tech. Rep., Nov.2024

work page 2024

[8] [8]

5G Network Enhancements to Support Ambient IoT Devices,

A. K. Salkintzis and D. Dimopoulos, “5G Network Enhancements to Support Ambient IoT Devices,” in 2023 IEEE Conference on Standards for Communications and Networking (CSCN) , 2023, pp. 302–307

work page 2023