Low-Complex Waveform, Modulation and Coding Designs for 3GPP Ambient IoT

Changlong Xu; Chao Wei; Chengjin Zhang; Hao Xu; Kazuki Takeda; Mingxi Yin; Yinhua Jia

REVIEW 3 major objections 5 minor 1 cited by

Low-Complex Waveform, Modulation and Coding Designs for 3GPP Ambient IoT

T0 review · 3 major / 5 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read Square-wave baseband modulation with convolutional coding and a coherent receiver outperforms RFID line coding by up to 6 dB on the A-IoT device-to-reader link.

desk verdict Competent standards-plus-simulation paper; the headline 6 dB conflates receiver and waveform gains, but the coherent-to-coherent 3 dB supports the core claim. read the letter →

arxiv 2501.08555 v1 pith:NWMCRUKE submitted 2025-01-15 eess.SP

Mingxi Yin , Chao Wei , Kazuki Takeda , Yinhua Jia , Changlong Xu , Chengjin Zhang , Hao Xu This is my paper · ORCID

classification eess.SP

keywords AmbientIoTbackscattercommunicationssquare-wavemodulationRFIDlinecodingconvolutionalnestedCRCFDMA3GPPRelease19

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

3GPP Ambient IoT aims to bring passive-RFID-style backscatter tags into cellular networks with larger coverage. This paper argues that on the device-to-reader link, the RFID-style line codes FM0 and MMS-2 are the wrong building block once forward error correction and a coherent receiver are available, and that a square-wave baseband modulation underneath the backscatter modulation performs better. In link simulations over a TDL-A channel with convolutional coding, the proposed square-wave BPSK/MSK/OOK formats give about a 3 dB gain over coherently decoded FM0/MMS-2 and about a 6 dB gain over non-coherent correlation decoding, for example reaching BLER 0.01 near 22 dB $E_b/N_0$ where non-coherent MMS-2 needs about 28 dB. The paper also contributes a memory-free nested convolutional-code design, a nested CRC that shares one generator, a method for reusing OFDM transmitters on the forward link by inserting check chips to preserve Manchester rules, and an FDMA scheme that places users at even multiples of a square-wave frequency. If the coherent-receiver assumption is met in practice, the result matters because it buys 3-6 dB of link budget for low-power backscatter devices without added transmit power.

What carries the argument

The central object is the square-wave baseband modulation placed between the FEC encoder and the backscatter modulator. Each coded bit or bit group is represented by a square wave whose amplitude (square-OOK), initial phase (square-BPSK/QPSK), or frequency (square-MSK) carries the information; the square wave is then mapped to ASK or PSK backscatter coefficients on the carrier. The square wave's oscillation provides clock information and shifts the D2R spectrum away from the carrier, avoiding CW interference, and its odd-harmonic spectrum enables FDMA by assigning even-multiple frequencies to additional users. On the receive side, the square wave is treated like a sinusoid, so coherent soft-decision decoding of the concatenated convolutional code works directly. The paper also uses nested convolutional codes ($K=6$ or $K=7$, rates down to 1/6) and a nested CRC-6/11/16 sharing one generator to keep encoder/decoder complexity low.

What would settle it

Run the same PDRCH link simulation without perfect channel state information, inserting pilot-based least-squares channel estimation and a sampling clock offset of $10^4$-$10^5$ ppm, and check whether square-wave BPSK with coherent soft-decision convolutional decoding still beats non-coherent MMS-2 by about 6 dB at BLER 0.01.

Watch

Extended reading notes

Core claim

The central claim is that the physical-layer design for the Ambient IoT device-to-reader link should replace RFID line coding with square-wave baseband modulation when convolutional coding and coherent detection are used. The paper shows by link-level simulation that the inter-bit waveform correlations of FM0 and MMS-2 line codes interfere with soft-decision convolutional decoding, whereas square-wave BPSK, MSK, and OOK baseband waveforms preserve the coding gain; with the same CC [133,171], coherent square-wave BPSK outperforms coherent FM0 and MMS-2 by about 3 dB and non-coherent MMS-2 by about 6 dB at BLER 0.01. Enhanced Manchester and square-wave BPSK produce the same waveform, which the paper takes as evidence that line coding is redundant when coherent reception and FEC are present. The claim is framed for the D2R link of 3GPP Release 19 A-IoT, with the monostatic/bistatic backscatter channel, TDL-A fading, 60 kbps bit rate and 240 kHz square-wave frequency shift used in the simulations.

Load-bearing premise

The 3-6 dB gain is computed assuming the receiver knows the backscatter channel perfectly, so it may shrink if real channel estimation and clock synchronization errors on the backscatter link are taken into account.

Editorial extensions

If this is right

On the A-IoT D2R link, if the coherent receiver assumption holds, line coding such as FM0 and MMS-2 becomes redundant; square-wave BPSK gives the same waveform as enhanced Manchester with more flexibility.
Adopting square-wave baseband modulation together with convolutional coding and coherent detection translates into a 3-6 dB link-budget gain, which directly supports the A-IoT coverage target of tens of meters.
FDMA among backscatter devices is feasible by assigning square-wave frequencies at even multiples of a reference, provided residual sampling clock offset is kept near $10^4$ ppm; at $10^5$ ppm the paper's simulations show error floors.
A constraint-length-6 nested convolutional code halves decoding complexity relative to $K=7$ at a cost of 0.3-0.4 dB at BLER 1%, and the polynomial-sweeping encoder removes the need for an interleaver buffer.
A nested CRC with lengths 6, 11 and 16 uses one generator with 16 shift registers instead of 24 for two separate CRCs, lowering hardware complexity for a given false-alarm protection.

Reading between the lines

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

If the 6 dB coherent gain survives practical channel estimation, the same square-wave baseband approach could be transplanted to other backscatter systems (Wi-Fi, Bluetooth, LoRa backscatter) that currently rely on line codes or FSK; the paper does not test those links.
The paper's even-multiple FDMA idea implies a scheduling-free multiple-access dimension for dense tag populations, but the $10^4$ ppm clock requirement means the practical bottleneck moves from waveform design to oscillator calibration and the paper leaves that calibration scheme unspecified.
The near-identity of enhanced Manchester and square-wave BPSK suggests that the WMC design space can be simplified by dropping line coding as a separate block whenever coherent detection is supported; this is a design conclusion the authors state only within the A-IoT context.
A direct testable extension is to replace the perfect-channel-knowledge assumption with pilot-aided estimation and measure the BLER gap as a function of channel estimation error; the paper's Figure 5(b) caption flags that assumption but does not stress-test it.

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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

Colleague,

Read the A-IoT WMC paper (arXiv:2501.08555). Short version: it is a competent standards-contribution summary plus a link-level simulation study. The genuinely new bit is the unified square-wave baseband modulation framework — square-BPSK/MSK/OOK as a replacement for line coding, nested CC/CRC polynomial families, and an even-harmonic FDMA scheme. The paper does well at positioning these against the Release 19 study and at stating the relationship between enhanced Manchester and square-BPSK (they are the same waveform). The 3 dB coherent-to-coherent gain over FM0/MMS-2 with CC is a clean and plausible result: line coding introduces inter-bit correlation that hurts Viterbi decoding, and the simulation setup is concrete. The FDMA idea, putting other users at even harmonic positions to avoid interference, is neat and the paper honestly shows the clock-accuracy limits.

The soft spots are in the headline and in the receiver idealization. The abstract says "6 dB improvements" but that number stacks square-wave modulation, a coherent receiver, and soft-decision CC decoding against RFID line coding with a non-coherent correlation receiver and hard decisions. The paper's own contribution bullet says 3–6 dB and the body clearly separates the comparisons, so this is a framing issue in the abstract and conclusion, not a fabrication. The fair waveform-only comparison is the 3 dB where both sides are coherent and soft.

More substantively, the coherent receiver assumes perfect channel knowledge (Fig. 5(b) caption). On a backscatter link with independent CW2D and D2R fading, CW leakage, and device clock offsets, that assumption is load-bearing. The paper gives no channel estimation or pilot design, so an independent implementation cannot reproduce the headline without inventing that piece. I do not think this destroys the contribution — standards proposals often assume perfect estimation to isolate PHY gains — but it should be said plainly. Also minor: the CC and CRC polynomial lists are given without search criteria or a comparison against an exhaustive set, and no code or data are provided, so the reader has to take the search on faith.

Final thought: this is a useful paper for people working on 3GPP A-IoT PHY or backscatter standardization. It is not a methodological breakthrough, and the 6 dB number should be quoted with the 3 dB caveat. It deserves a serious referee: the simulations are described well enough to check, and the perfect-channel-knowledge issue should be forced out into the open. I would accept it for review with the expectation of a revision that separates the receiver-type gain from the waveform gain.

Referee Report

3 major / 5 minor

Summary. The paper addresses physical-layer waveform, modulation, and coding for 3GPP Ambient IoT (Release 19). It contrasts RFID PHY practice with A-IoT requirements, proposes square-wave baseband modulations (square-BPSK, square-MSK, square-OOK) for the device-to-reader link, and combines them with nested convolutional codes and nested CRC designs. Link-level simulations over TDL-A channels compare the proposed schemes with FM0 and MMS-2 line coding under convolutional coding, reporting a 3-6 dB BLER gain, and an FDMA scheme based on even-multiple square-wave frequencies is evaluated under sampling clock offset. The paper also describes a check-chip method for R2D OFDM/OOK compatibility.

Significance. If the central performance claim holds, the paper gives a concrete argument that square-wave baseband modulation with coherent reception is preferable to RFID-style line coding when FEC is employed, and the FDMA even-harmonic placement is an elegant way to reuse square-wave spectra. Strengths include the concrete simulation assumptions, comparison against standardized RFID baselines, explicit complexity reasoning for the nested CC/CRC designs, and the authors' transparency in labeling the perfect-channel-knowledge assumption in Fig. 5(b). The main limitation is that the headline 6 dB gain has not been stress-tested against channel estimation errors, phase noise, or residual frequency offset; the fair coherent-to-coherent gain is 3 dB, and the non-coherent baseline uses hard decisions, so the comparison mixes multiple dimensions.

major comments (3)

[Section V-A, Fig. 5(b) caption] The headline "6 dB improvement" conflates the waveform choice with the receiver choice. The text states that square-wave modulations with a coherent receiver outperform FM0/MMS-2 by 3 dB with coherent receivers and by 6 dB with non-coherent receivers, and the caption notes "Perfect channel knowledge is assumed." Because the non-coherent baseline does not require channel estimation while the coherent square-wave receiver does, the 6 dB difference is not a pure waveform gain. In addition, the non-coherent baseline is decoded with hard decisions while the coherent curves use soft decisions. To support the conclusion that square-wave modulation is the better PHY choice, the authors should either headline the coherent-to-coherent 3 dB gain or add a channel estimation procedure and evaluate BLER with estimated channels, including phase noise and residual SFO, so that the practical margin over the non-coherent benchmark is quantified.
[Section IV-A and IV-B] The nested CC and nested CRC designs are asserted as searched results, but the search procedure is not given. The reader is told that the nested CC polynomial groups are searched with good error performance, but not the search metric, the search space, the puncturing/rate-matching rule, or the tail-biting termination details used in Fig. 5(a). Similarly, the "new search nested CRC" is reported to lower undetected error probability from 2.4e-6 to 1.4e-6, but the simulation conditions (input length, channel, error model, false-alarm criterion) are not specified. These omissions prevent independent verification of the coding claims and should be supplied, or the claims should be downgraded to illustrative examples.
[Section III-B and Section V-A] The simulation setup for square-wave modulations is underspecified at the waveform level. The paper says the receiver can use either the first harmonic or a wider bandwidth that combines higher-order harmonics, but Fig. 5(b) does not state which option is simulated; since the square-wave harmonics carry a significant fraction of the energy, this choice affects the reported Eb/N0. In addition, the statement that square-wave harmonics only appear at odd harmonics assumes a 50% duty cycle, which is never stated; duty-cycle tolerance matters because even harmonics would break the FDMA placement described in Fig. 4. Please specify the duty cycle, the transmit pulse shape, and the receiver filtering/combining model used in the simulations.

minor comments (5)

[Abstract and Section I] The abstract says "6 dB improvements" while the contributions list says "3-6 dB gain"; please make the primary comparison explicit and consistent.
[Fig. 6 caption and legend] The caption has the typo "4 usres" instead of "4 users", and the legend labels for the sampling clock offsets are rendered in a way that can be misread as 104 ppm and 105 ppm rather than 10^4 ppm and 10^5 ppm; please correct both.
[Section III-B] The phrase "a 1.5x relationship" for the two square-wave MSK frequencies is imprecise; specify the exact frequency ratio and the phase-continuity condition, and consider naming the scheme square-FSK to avoid implying sinusoidal MSK.
[Section V-B and Fig. 6] The FDMA simulation lists square-wave frequencies of 60, 120, 240, and 480 Hz with a bit rate of 7.5 kbps, which is implausible unless the frequency unit is kHz; please correct the units or the bit rate.
[Section III-A] The check-chip insertion for R2D is described in words only; a small diagram or pseudocode would clarify how the copied and inverted starting chips interact with cyclic prefix insertion.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the 3–6 dB gain claim is an empirical comparison against external RFID baselines with a fixed external CC; the perfect-CSI assumption is a robustness risk, not a circular step.

full rationale

The paper's headline 3–6 dB gain claim is an empirical link-level comparison, not a derived quantity. In Fig. 5(b), square-wave BPSK/MSK/OOK with coherent soft-decision receivers are compared against FM0 and MMS-2 line codes with both coherent-soft and non-coherent-hard receivers, using the fixed external LTE convolutional code [133,171] in all curves ('The CC [133,171] is used in all cases.'). The FM0/MMS-2 baselines come from the external EPC-C1G2 RFID standard, and the paper explicitly notes that enhanced Manchester and square-BPSK produce identical waveforms, so the comparison is not manufactured by definition. The searched nested CC/CRC polynomials in Section IV are candidate design options evaluated in Fig. 5(a) and Section IV-B, but they are not used in the central waveform comparison, so no fitted parameter is renamed as a prediction. There is no load-bearing self-citation: the references to 3GPP TRs are standardization documents, and the one cited CC polynomial set [133,171,165,117] is attributed to IEEE 802.16m. The 'Perfect channel knowledge is assumed' statement in Fig. 5(b) is a genuine robustness limitation: the coherent receiver's gain is not stress-tested against channel estimation error, phase noise, or the large SFO values discussed in Fig. 6. That is an unverified assumption about the evaluation setting, not a circular reduction of the conclusion to its inputs. I therefore find no circular step meeting the quoted-equation standard.

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

The central comparison assumes coherent reception with perfect channel knowledge, an external CW backscatter model, and specific clock-accuracy values; no new physical entities are introduced. The searched CC/CRC polynomials are the main hand-chosen elements and are re-used in the evaluation, which introduces mild selection dependence.

free parameters (3)

Nested CC polynomial set (K=6) = [45,73,75,67,57,55] (option a)
Searched for good error performance in Fig. 5(a); the reported coding gains are conditional on this searched set.
Nested CC polynomial set (K=7) = [133,171,165,117]
One of three nested options based on LTE convolutional codes; chosen for lower code rates in Section IV-A.
Nested CRC-16 polynomial = x^16 + x^11 + x^6 + x^4 + x^3 + 1
New searched nested CRC; reported undetected error probabilities compare this against the NR-based x^16 + x^11 + x^6 + x^5 + 1.

assumptions (4)

domain assumption Backscatter transmitted signal is the product of backscatter coefficients and an external continuous wave
Used throughout Section III and Fig. 2 for the D2R link; standard in RFID and A-IoT but stated as a given, not derived.
standard math Square wave harmonics appear only at odd multiples, so even-multiple frequencies can be assigned to other users
Fourier property used in Section III-B to justify the even-harmonic FDMA scheme; not proven in the paper.
domain assumption The receiver has perfect channel knowledge
Figure 5 caption; supports the coherent receiver curves that produce the headline gain.
domain assumption Device clock accuracy yields sampling frequency offsets of about 10^4 ppm (Device 1) and 10^5 ppm (Device 2a)
Used in Section V-B to conclude that only the smaller SFO is tolerable for FDMA.

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Cite this review

Pith. "Pith review of Low-Complex Waveform, Modulation and Coding Designs for 3GPP Ambient IoT." pith.science (2026). https://pith.science/paper/NWMCRUKE

@misc{pith2026250108555,
  author       = {Pith},
  title        = {Pith review of: Low-Complex Waveform, Modulation and Coding Designs for 3GPP Ambient IoT},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/NWMCRUKE}},
  note         = {Machine review of arXiv:2501.08555}
}

read the original abstract

This paper presents a comprehensive study on low-complexity waveform, modulation and coding (WMC) designs for the 3rd Generation Partnership Project (3GPP) Ambient Internet of Things (A-IoT). A-IoT is a low-cost, low-power IoT system inspired by Ultra High Frequency (UHF) Radio Frequency Identification (RFID) and aims to leverage existing cellular network infrastructure for efficient RF tag management. The paper compares the physical layer (PHY) design challenges and requirements of RFID and A-IoT, particularly focusing on backscatter communications. An overview of the standardization for PHY designs in Release 19 A-IoT is provided, along with detailed schemes of the proposed low-complex WMC designs. The performance of device-to-reader link designs is validated through simulations, demonstrating 6 dB improvements of the proposed baseband waveform with coherent receivers compared to RFID line coding-based solutions with non-coherent receivers when channel coding is adopted.

Figures

Figures reproduced from arXiv: 2501.08555 by the authors.

**Figure 1.** System model for 3GPP A-IoT. primarily operate in line-of-sight (LOS) environments. When LOS paths are obstructed, RFID tags struggle to connect with readers. Additionally, the limited receiver sensitivity of tags and the simplistic physical layer design restrict the coverage, typically to less than 10 meters, making passive RFID suitable mainly for indoor scenarios. A-IoT targets indoor environments with a larger … view at source ↗

**Figure 2.** Block diagram for PHY of UHF RFID and 3GPP A-IoT. [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗

**Figure 3.** Waveforms in RFID and A-IoT. (a) Line codes in RFID and A-IoT [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗

Figures from the paper (2 more)

**Figure 4.** Figure 4: Illustration for D2R waveform spectrum to allow FDMA. [PITH_FULL_IMAGE:figures/full_fig_p005_4.png]

**Figure 6.** Figure 6: BLER performance for A-IoT D2R FDMA with 4 users enabled [PITH_FULL_IMAGE:figures/full_fig_p006_6.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

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Pith tools

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

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B. Clerckx, R. Zhang, R. Schober, D. W. K. Ng, D. I. Kim and H. V . Poor, “Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs,” IEEE Journal on Selected Areas in Communications , vol. 37, no. 1, pp. 4-33, Jan. 2019

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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, Fourthquarter 2018

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