Connectionless Bluetooth LE Channel Sounding via PAwR for Scalable and Energy-Efficient Ranging

Leon Schex; Markus Cremer; Uwe Dettmar

arxiv: 2605.17094 · v1 · pith:BG5R2DOUnew · submitted 2026-05-16 · 📡 eess.SP

Connectionless Bluetooth LE Channel Sounding via PAwR for Scalable and Energy-Efficient Ranging

Leon Schex , Markus Cremer , Uwe Dettmar This is my paper

Pith reviewed 2026-05-20 15:09 UTC · model grok-4.3

classification 📡 eess.SP

keywords Bluetooth Low EnergyChannel SoundingPAwRrangingenergy efficiencyconnectionlessscalable positioningperiodic advertising

0 comments

The pith

A connectionless Bluetooth Channel Sounding system using PAwR coordinates measurements via a shared assignment matrix and reports results without per-pair connections.

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

The paper establishes a new architecture for Bluetooth Low Energy Channel Sounding that replaces traditional LE ACL connections with Periodic Advertising with Responses. A Central Orchestrator distributes a Peer-to-Peer Assignment Matrix through PAwR subevents so that each device can derive its own role, channel sequence, and response slot from its index. This deterministic assignment avoids collisions while a compact data format lets ranging results travel back through the same PAwR response slots. The approach cuts initiation overhead dramatically and lowers steady-state power draw, enabling many more simultaneous ranging partners than connection-based methods allow.

Core claim

The paper claims that LE CS Test commands combined with PAwR produce a fully connectionless ranging system in which devices derive roles and channels from an index plus a distributed Peer-to-Peer Assignment Matrix, eliminating connection setup costs, preventing same-step collisions, and compressing result payloads by roughly 69 percent so that measurements can be aggregated at the application layer.

What carries the argument

The Peer-to-Peer Assignment Matrix distributed via PAwR subevents, from which each device derives its role, channel sequence, and response slot assignment.

If this is right

At a 1 s update cycle the architecture reduces steady-state active charge by 40-48 percent relative to a fair connected baseline.
Per-switch initiation overhead drops by approximately 98 percent.
With per-cycle partner switching the combined savings reach up to 88 percent lower total charge over a 24 h horizon.
An empirical timing model projects an upper bound of 16,384 active devices per PAwR train when each device performs four CS procedures per cycle on 37 channels with a single antenna path.

Where Pith is reading between the lines

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

Large-scale indoor positioning networks could operate with far fewer reconnections if matrix updates are used to re-pair anchors and tags on demand.
The deterministic channel sequence may reduce aggregate interference in dense IoT deployments beyond the collision elimination already demonstrated.
The same matrix-driven coordination could be tested with mobile devices that change partners every cycle to measure real-world timing drift.
Compressing result payloads by omitting recoverable fields might be applied to other BLE ranging primitives for similar efficiency gains.

Load-bearing premise

All devices remain synchronized and can reliably receive and apply the Peer-to-Peer Assignment Matrix distributed via PAwR without packet loss or timing drift.

What would settle it

Measurement of collision-induced ranging outliers or failed matrix updates when more than a few hundred devices operate simultaneously under real radio conditions would falsify the scalability and energy claims.

read the original abstract

Bluetooth Core Specification v6.0 introduces Channel Sounding (CS) as a standardized high-accuracy ranging primitive for Bluetooth Low Energy (BLE). However, standard CS usage remains tied to per-pair LE asynchronous connection logical transport (LE ACL) connections, which adds initiation overhead, limits concurrent partners, and transfers results over the connection itself. We present a connectionless CS architecture that combines the LE CS Test command with Periodic Advertising with Responses (PAwR). A Central Orchestrator, a Gateway, and synchronized Tag/Anchor devices coordinate measurement configurations and aggregate results at the application layer. Each device derives its role, channel sequence, and response slot assignment from its device index and a Peer-to-Peer Assignment Matrix distributed via PAwR. The deterministic channel sequence prevents same-step collisions across parallel CS procedures, while matrix updates reconfigure arbitrary device-to-device pairings within a PAwR subevent group. A compact data plane omits fields recoverable from the shared measurement configuration and reduces the serialized ranging-data payload by approximately 69%, enabling result reporting through PAwR response slots. A proof-of-concept evaluation on the Nordic nRF54L15 platform shows that deterministic channel management eliminates the collision-induced outliers observed under simulated dense-deployment channel overlaps. At a 1 s update cycle, the architecture reduces steady-state active charge by 40-48% relative to a fair connected baseline and cuts per-switch initiation overhead by approximately 98%. Under per-cycle partner switching, these effects combine to up to 88% lower total charge over a 24 h horizon. An empirical timing model projects a capacity upper bound of 16,384 active devices per PAwR train at four CS procedures per device per cycle, 37 channels, and a single antenna path.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

This paper shows how to run Bluetooth channel sounding without per-pair connections by using PAwR for coordination and results, which cuts energy and raises device count on real hardware, but the gains assume perfect sync that the tests do not fully check.

read the letter

The main point is that the authors have taken the new LE Channel Sounding commands and made them work connectionlessly by layering them on Periodic Advertising with Responses. A central node pushes out a Peer-to-Peer Assignment Matrix that lets every device figure out its role, channel sequence, and response slot from its index. This deterministic mapping stops same-step collisions across parallel procedures, and they drop redundant fields to shrink the ranging payload by roughly 69 percent so results fit inside PAwR response slots. The nRF54L15 proof-of-concept confirms that the channel management removes the collision outliers seen in dense connected runs, and the measured charge numbers show 40-48 percent lower steady-state active current at a 1-second cycle plus about 98 percent less initiation cost when partners switch each cycle. Those savings add up to as much as 88 percent lower total charge over 24 hours under frequent switching. The capacity projection of 16,384 devices per train comes from an empirical timing model tied to the platform rather than fitted parameters, which keeps it honest. The measurements are the strongest part; they are taken on actual silicon and support the collision and energy claims directly. The weak spot is the untested assumption that every device stays synchronized and receives the matrix updates without loss or drift. The evaluation only simulates channel overlaps to show collision removal; it does not report packet error rates or long-term timing stability under the exact load of four procedures per device across 37 channels. If subevents are missed in a real dense network, devices would fall back or retransmit and the reported savings would shrink. This work is for engineers building large-scale BLE ranging in IoT or asset tracking. A reader who needs concrete numbers on power and density for connectionless setups will find the implementation choices and platform data useful. It deserves peer review because the core architecture is implemented and measured, even though reviewers will want more data on synchronization robustness in crowded conditions.

Referee Report

2 major / 2 minor

Summary. The paper proposes a connectionless Bluetooth LE Channel Sounding (CS) architecture that leverages Periodic Advertising with Responses (PAwR) to eliminate per-pair LE ACL connections. A Central Orchestrator and Gateway distribute a Peer-to-Peer Assignment Matrix via PAwR subevents; devices derive roles, deterministic channel sequences, and response slots from their index and the matrix. This prevents same-step collisions, supports dynamic pairings, and uses a compact data plane that omits recoverable fields (claimed ~69% payload reduction). A Nordic nRF54L15 proof-of-concept demonstrates collision elimination under simulated overlaps; at a 1 s cycle the design reports 40-48% lower steady-state active charge versus a connected baseline, ~98% lower per-switch initiation overhead, up to 88% lower 24 h total charge under partner switching, and an empirical timing model projects an upper bound of 16,384 active devices per PAwR train at 4 CS procedures/device/cycle, 37 channels, and one antenna path.

Significance. If the synchronization and lossless-matrix-delivery assumptions hold in dense deployments, the architecture offers a concrete path to scalable, low-energy BLE ranging for applications such as asset tracking and indoor positioning. The deterministic collision avoidance, dynamic reconfiguration within a single PAwR subevent group, and measured charge reductions are substantive contributions. The platform evaluation and timing model supply falsifiable quantitative predictions; however, the central energy and capacity claims rest on unverified reliability of PAwR matrix delivery under the exact load used in the model.

major comments (2)

[Abstract and coordination/matrix description paragraphs] Abstract, coordination and matrix description paragraphs: all quantitative claims (40-48% steady-state charge reduction, 98% per-switch overhead cut, 88% 24 h savings, 16,384-device capacity bound) presuppose that every Tag/Anchor remains time-synchronized and reliably decodes/applies the Peer-to-Peer Assignment Matrix without packet loss or timing drift. The nRF54L15 evaluation only demonstrates elimination of simulated channel-overlap outliers; it does not report PAwR packet error rate or long-term drift under the modeled load of 4 CS procedures per device per cycle and 37 channels. This assumption is load-bearing for the central claims.
[Evaluation section] Evaluation section: the reported charge figures lack error bars, explicit exclusion criteria, or a complete measurement methodology. The abstract states that quantitative savings may depend on unstated assumptions about traffic and synchronization; without these details the 40-48% and 88% figures cannot be independently reproduced or generalized.

minor comments (2)

[Abstract] Abstract: the claimed ~69% payload reduction is stated without enumerating the omitted fields or giving the baseline serialized size for direct comparison.
[Throughout] Notation: ensure consistent use of device roles (Tag/Anchor) and that all acronyms (PAwR, CS, LE ACL) are expanded on first appearance in the main body.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments and for acknowledging the contributions of deterministic collision avoidance and the measured energy reductions. We respond to each major comment below and indicate the revisions we will make.

read point-by-point responses

Referee: [Abstract and coordination/matrix description paragraphs] Abstract, coordination and matrix description paragraphs: all quantitative claims (40-48% steady-state charge reduction, 98% per-switch overhead cut, 88% 24 h savings, 16,384-device capacity bound) presuppose that every Tag/Anchor remains time-synchronized and reliably decodes/applies the Peer-to-Peer Assignment Matrix without packet loss or timing drift. The nRF54L15 evaluation only demonstrates elimination of simulated channel-overlap outliers; it does not report PAwR packet error rate or long-term drift under the modeled load of 4 CS procedures per device per cycle and 37 channels. This assumption is load-bearing for the central claims.

Authors: We agree that the quantitative claims rest on the assumptions of sustained time synchronization and reliable PAwR matrix delivery. The nRF54L15 proof-of-concept was scoped to validate the core mechanism of deterministic channel-sequence collision avoidance under simulated overlaps. The manuscript does not contain PAwR packet-error-rate or long-term drift data collected at the modeled load of four CS procedures per device per cycle. In the revised version we will (1) state these assumptions explicitly in the abstract and evaluation sections, (2) add a short discussion of expected PAwR reliability drawn from the Bluetooth Core Specification, and (3) clarify that the 16,384-device bound is an upper-limit projection assuming lossless delivery. Empirical verification of matrix delivery under the exact modeled load is not available from the current data set and would require additional experimentation. revision: partial
Referee: [Evaluation section] Evaluation section: the reported charge figures lack error bars, explicit exclusion criteria, or a complete measurement methodology. The abstract states that quantitative savings may depend on unstated assumptions about traffic and synchronization; without these details the 40-48% and 88% figures cannot be independently reproduced or generalized.

Authors: We accept that the evaluation section requires additional methodological detail for reproducibility. In the next manuscript version we will expand the charge-measurement description to include the full experimental procedure, report error bars obtained from repeated trials, specify any data-exclusion criteria, and enumerate the traffic-pattern and synchronization assumptions underlying the 40-48% steady-state and 88% 24-hour savings figures. revision: yes

Circularity Check

0 steps flagged

No significant circularity; energy and capacity results derive from platform measurements and empirical timing model

full rationale

The paper's quantitative claims (40-48% steady-state charge reduction, 98% per-switch overhead cut, 88% 24 h savings, and 16,384-device capacity bound) are obtained from direct Nordic nRF54L15 measurements and an empirical timing model using stated parameters (1 s cycle, 4 CS procedures per device per cycle, 37 channels, single antenna path). These outputs are not defined in terms of themselves, nor do any equations reduce fitted inputs to predictions by construction. The Peer-to-Peer Assignment Matrix and deterministic channel sequencing are architectural design choices for collision avoidance, not self-referential derivations. No load-bearing self-citations, uniqueness theorems, or ansatzes imported from prior author work appear in the derivation chain. The architecture remains self-contained against the connected baseline benchmark.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The paper relies on the existence and correct implementation of Bluetooth Core Specification v6.0 primitives for CS and PAwR; no new free parameters, invented physical entities, or ad-hoc axioms are introduced beyond standard wireless protocol assumptions.

axioms (1)

domain assumption Bluetooth Core Specification v6.0 defines functional Channel Sounding and PAwR primitives that devices can invoke as described.
The architecture is built directly on these standardized commands and behaviors.

pith-pipeline@v0.9.0 · 5862 in / 1330 out tokens · 54805 ms · 2026-05-20T15:09:23.207569+00:00 · methodology

discussion (0)

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

IndisputableMonolith/Foundation/ArithmeticFromLogic.lean embed_injective unclear

?

unclear
Relation between the paper passage and the cited Recognition theorem.

deterministic channel sequence prevents same-step collisions across parallel CS procedures... j = (i_step + i_pair + i_ms + c_pawr) mod N
IndisputableMonolith/Cost/FunctionalEquation.lean washburn_uniqueness_aczel unclear

?

unclear
Relation between the paper passage and the cited Recognition theorem.

reduces steady-state active charge by 40-48 % ... up to 88 % lower total charge over a 24 h horizon

What do these tags mean?

matches: The paper's claim is directly supported by a theorem in the formal canon.
supports: The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends: The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses: The paper appears to rely on the theorem as machinery.
contradicts: The paper's claim conflicts with a theorem or certificate in the canon.
unclear: Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

20 extracted references · 20 canonical work pages

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work page 2024

[3] [3]

Experimental evaluation of multicarrier phase difference localization in Bluetooth Low Energy,

M. Nikodem, G. Trajnowicz, G. S. de Blasio, and F. A. Quesada- Arencibia, “Experimental evaluation of multicarrier phase difference localization in Bluetooth Low Energy,”IEEE Sensors J., vol. 25, no. 1, pp. 1548–1560, Jan. 2025, DOI. 10.1109/JSEN.2024.3495030

work page doi:10.1109/jsen.2024.3495030 2025

[4] [4]

Enhancing Bluetooth Channel Sounding performance in complex indoor environments,

A. Santra, I. Kravets, N. Kotliar, and A. Pandey, “Enhancing Bluetooth Channel Sounding performance in complex indoor environments,”IEEE Sensors Lett., vol. 8, no. 10, pp. 1–4, Oct. 2024, art. no. 7005104, DOI. 10.1109/LSENS.2024.3456002

work page doi:10.1109/lsens.2024.3456002 2024

[5] [5]

Data-driven process- ing using parametric neural network for improved Bluetooth Channel Sounding distance estimation,

A. Tsemko, A. Santra, O. Kapshii, and A. Pandey, “Data-driven process- ing using parametric neural network for improved Bluetooth Channel Sounding distance estimation,” inProc. IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP), Hyderabad, India, 2025, pp. 1–5, DOI. 10.1109/ICASSP49660.2025.10887852

work page doi:10.1109/icassp49660.2025.10887852 2025

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Support vector regression for Bluetooth ranging in multipath environments,

J. P. Van Marter, A. G. Dabak, N. Al-Dhahir, and M. Torlak, “Support vector regression for Bluetooth ranging in multipath environments,” IEEE Internet Things J., vol. 10, no. 13, pp. 11 533–11 546, Jul. 2023, DOI. 10.1109/JIOT.2023.3244743

work page doi:10.1109/jiot.2023.3244743 2023

[7] [7]

Reduced complexity deep learning approach for Bluetooth ranging in multipath environments,

Z. Bin Tariq, J. P. Van Marter, A. G. Dabak, N. Al-Dhahir, and M. Torlak, “Reduced complexity deep learning approach for Bluetooth ranging in multipath environments,”IEEE Sensors J., vol. 24, no. 19, pp. 31 431–31 441, Oct. 2024, DOI. 10.1109/JSEN.2024.3441596. SCHEXet al.: CONNECTIONLESS BLUETOOTH LE CHANNEL SOUNDING VIA PAWR FOR SCALABLE AND ENERGY -EFF...

work page doi:10.1109/jsen.2024.3441596 2024

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A review of the quality of positioning service of VLP within the indoor positioning system landscape,

S. Bastiaens, M. Alijani, W. Joseph, and D. Plets, “A review of the quality of positioning service of VLP within the indoor positioning system landscape,”IEEE Trans. Instrum. Meas., vol. 75, pp. 1–33, Jan. 2026, DOI. 10.1109/TIM.2026.3655932

work page doi:10.1109/tim.2026.3655932 2026

[9] [10]

Channel sounding: Metrological explo- ration of the design options using related positioning systems,

M. Gunia and F. Ellinger, “Channel sounding: Metrological explo- ration of the design options using related positioning systems,”IEEE Access, vol. 14, pp. 18 913–18 928, Feb. 2026, DOI. 10.1109/AC- CESS.2026.3660596

work page doi:10.1109/ac- 2026

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Impact of 2.4 GHz interference on Bluetooth® 6.0 Channel Sounding ranging measurements,

A. Sheikh, “Impact of 2.4 GHz interference on Bluetooth® 6.0 Channel Sounding ranging measurements,” inProc. IEEE Virtual Conf. Commun. (VCC), Nov. 2025, pp. 1–6, DOI. 10.1109/VCC67261.2025.11351055

work page doi:10.1109/vcc67261.2025.11351055 2025

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A high-accuracy phase-based ranging solution with Bluetooth Low Energy (BLE),

P. Zand, J. Romme, J. Govers, F. Pasveer, and G. Dolmans, “A high-accuracy phase-based ranging solution with Bluetooth Low Energy (BLE),” inProc. IEEE Wireless Commun. Netw. Conf. (WCNC), Marrakesh, Morocco, Apr. 2019, pp. 1–8, DOI. 10.1109/WCNC.2019.8885791

work page doi:10.1109/wcnc.2019.8885791 2019

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A high-accuracy concurrent phase-based ranging for large-scale dense BLE network,

P. Zand, A. Duzen, J. Romme, J. Govers, C. Bachmann, and K. Philips, “A high-accuracy concurrent phase-based ranging for large-scale dense BLE network,” inProc. IEEE 30th Annu. Int. Symp. Pers., Indoor Mobile Radio Commun. (PIMRC), Istanbul, Turkey, Sep. 2019, pp. 1–7, DOI. 10.1109/PIMRC.2019.8904093

work page doi:10.1109/pimrc.2019.8904093 2019

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Exchange of ranging data,

C. Wulff, “Exchange of ranging data,” Int. Patent Appl. WO 2022/117557 A1, Jun. 9, 2022, applicant: Nordic Semiconductor ASA

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