Cross-layer Integrated Sensing and Communication: A Joint Industrial and Academic Perspective

Aarno P\"arssinen; Abdur Rahman Mohamed Ismail; Ahmad Nimr; Akshay Jain; Antonio de la Oliva; Apostolos Kousaridas; Athanasios Stavridis; Basuki Priyanto; Bilal Khan; Claude Desset

REVIEW 3 major objections 6 minor 1 cited by

Cross-layer Integrated Sensing and Communication: A Joint Industrial and Academic Perspective

T0 review · 3 major / 6 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read This paper introduces a quantitative cross-layer framework that links 6G ISAC design choices to sensing accuracy, resolution, latency, and high-level value indicators.

desk verdict A broad, well-sourced ISAC vision paper whose promised quantitative evaluation is missing from the text; worth a serious referee, but only after the authors actually show the numbers. read the letter →

arxiv 2505.10933 v2 pith:2YEJZMTC submitted 2025-05-16 eess.SP cs.ITmath.IT

Henk Wymeersch , Nuutti Tervo , Stefan Wänstedt , Sharief Saleh , Joerg Ahlendorf , Ozgur Akgul , Vasileios Tsekenis , Sokratis Barmpounakis

show 35 more authors

Liping Bai Martin Beale Rafael Berkvens Nabeel Nisar Bhat Hui Chen Shrayan Das Claude Desset Antonio de la Oliva Prajnamaya Dass Jeroen Famaey Hamed Farhadi Gerhard P. Fettweis Yu Ge Hao Guo Rreze Halili Katsuyuki Haneda Abdur Rahman Mohamed Ismail Akshay Jain Sylvaine Kerboeuf Musa Furkan Keskin Emad Ibrahim Bilal Khan Siddhartha Kumar Stefan Köpsell Apostolos Kousaridas Pekka Kyösti Simon Lindberg Mohammad Hossein Moghaddam Ahmad Nimr Victor Pettersson Aarno Pärssinen Basuki Priyanto Athanasios Stavridis Tommy Svensson Sonika Ujjwal

This is my paper · ORCID

classification eess.SPcs.ITmath.IT

keywords integratedsensingandcommunication6Gcross-layerevaluationKPIkeyvalueindicatorsOFDMlatencyproofofconcept

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

This paper argues that integrated sensing and communication (ISAC) in 6G can be designed and compared fairly only through a cross-layer framework that connects low-level radio choices to sensing accuracy, resolution, and latency, and then to high-level value indicators. It proposes such a framework, built on fifteen degrees of freedom spanning radio configuration (carrier frequency, antennas, subcarriers, OFDM symbols, power) and network processing (where and with what power sensing data is processed), and applies it in simulation and proof-of-concept experiments for indoor, urban, and rural use cases. The authors' central claim is that physical-layer trade-offs, such as waveform choice versus power-amplifier distortion or bandwidth versus coverage, propagate upward and can be quantified so that resource allocation between sensing and communication becomes a system-level decision rather than a per-layer one. A sympathetic reader would care because, if the framework holds, 6G standardization gains a concrete way to evaluate ISAC solutions before deployment, including how sensing latency and accuracy respond to processing location and computational power.

What carries the argument

The central machinery is the cross-layer evaluation framework itself: a parameterized mapping from fifteen degrees of freedom to sensing KPIs. Its operational core is a set of quantitative relations—the resolution formulas $\Delta R=c/(2B)$, $\Delta v=\lambda/(2T_{\mathrm{Tx}})$, and $\Delta\phi=0.89\lambda/D$; the total latency model $T_{\mathrm{total}}=T_{\mathrm{Tx}}+T_{\mathrm{prop}}+T_{\mathrm{proc}}$ with $T_{\mathrm{proc}}=T_{\mathrm{proc}}^{\mathrm{Tx}}+T_{\mathrm{proc}}^{\mathrm{prop}}+T_{\mathrm{proc}}^{\mathrm{comp}}$, where the data-transfer and compute terms depend on processing-location proximity, communication bandwidth, and computational power; and a Cramér–Rao-based accuracy link that connects all twelve radio-layer degrees of freedom. This machinery carries the argument by turning the qualitative claim that physical-layer choices propagate upward into numbers that can be compared across use cases, frequency bands, and processing placements.

What would settle it

Measure range error and range-Doppler noise floor on a real OFDM monostatic ISAC prototype at 30 GHz or 300 GHz with a corner reflector at a known distance, comparing against the paper's phase-noise and power-amplifier distortion curves across transmitter back-off levels; the framework's hardware link would be falsified if measured errors systematically exceed the predicted values by more than the model variance, or if the predicted preference for OFDM over single-carrier reverses.

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Extended reading notes

Core claim

The paper's central claim is that ISAC should be evaluated as a system, not layer by layer, and that a quantitative cross-layer framework can make this evaluation concrete. The framework links fifteen degrees of freedom—twelve radio-layer choices (carrier frequency, number of antennas at base station and user equipment, subcarrier spacing, number of OFDM symbols and subcarriers, transmit power, precoder/combiner design, base station locations, and number of RF chains) and three networking-layer choices (processing location, communication bandwidth to the processor, and computational power)—to sensing KPIs of accuracy, resolution, and latency. Resolution is predicted from closed-form formulas ($\Delta R=c/(2B)$, $\Delta v=\lambda/(2T_{\mathrm{Tx}})$, $\Delta\phi=0.89\lambda/D$); latency is decomposed into transmission, propagation, and processing terms, where processing includes moving the sensing data to a compute node and performing the estimation there; accuracy is tied to the radio degrees of freedom through a Cramér–Rao bound. The paper then exercises the framework on three scenarios: indoor bistatic human detection, urban bistatic intersection hazard detection, and rural monostatic highway hazard detection, using both simulation and proof-of-concept hardware, and reports how the degrees of freedom move the KPIs.

Load-bearing premise

The framework's quantitative results rest on the premise that 6G sensing waveforms will be OFDM or its precoded variant DFTS-OFDM; if a different waveform family is standardized, the resolution, power-amplifier distortion, and resource-allocation conclusions would need to be re-derived.

Editorial extensions

If this is right

A fair comparison of ISAC solutions becomes possible: two designs (e.g., FR3 versus FR2, bistatic versus monostatic) can be evaluated on the same KPI axes of accuracy, resolution, and latency across indoor, urban, and rural scenarios.
Sensing latency becomes partly a networking decision: the model predicts that processing location and computational power, not just radio parameters, set total latency, and that for a target moving at 10 m/s a 100 ms latency contributes 1 m of error independent of estimator accuracy.
Band selection gets quantitative guidance: the range, velocity, and angular resolution formulas show that FR2 and FR3 choices trade coverage and mobility against resolution, with sub-THz offering centimeter-scale range resolution but severe coverage limits.
The waveform discussion concludes that OFDM remains preferable to single-carrier for sensing under power-amplifier nonlinearity in most operating regions, because single-carrier's lower distortion is outweighed by noise enhancement during frequency-domain division.

Reading between the lines

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

Beyond the paper: since the latency model separates transmission, propagation, and compute time, it could be turned into a placement rule—for a target speed of 10 m/s and a required accuracy of 1 m, the total sensing latency budget is 100 ms, which immediately constrains how far from the radio the sensing processor can live.
Beyond the paper: the KVI side of the framework is left qualitative; a natural next step would be to attach utility or revenue to accuracy-latency packages for each use case, making the KPI-to-KVI link numerically testable.
Beyond the paper: the same framework structure could be applied to non-OFDM waveforms or to sub-THz carriers once those are available, since the resolution and latency formulas are waveform-general even though the distortion results are not.

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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

Quick take: this is a genuinely useful cross-layer synthesis of ISAC for 6G, but the paper's central quantitative claim is not currently verified. The abstract promises a framework applied to simulation and proof-of-concept setups, yet the text stops short of showing any KPI results, and the paper itself admits the TPEB/CRLB derivation was left out.

What it does well: the qualitative content is strong. The tables mapping frequency bands, RIS, NTN, massive MIMO, and D-MIMO to coverage, resolution, mobility, propagation, and hardware aspects are practical and will be handy in standardization discussions. The treatment of PA nonlinear distortion and phase noise in monostatic sensing, including the range-correlation effect and delayed-LO mitigation, is specific and well-grounded. The higher-layer architecture (SeMF, SCF, SPF, SUSF, SPCTM, Sensing Store) and the STRIDE/LINDDUN security-privacy analysis are more detailed than most ISAC papers. The authors also state their gaps explicitly, which I appreciate.

The soft spot is exactly where the abstract points. Section VI.B.2 says the accuracy bounds were derived but not included. Section III.C promises a comparison with existing sensing technologies "in Section V," but Section V does not contain it. The manuscript ends mid-sentence in VI.C.4, before any simulation or PoC KPI appears. So the quantitative cross-layer framework is currently a framework plus resolution and latency formulas, not a demonstrated evaluation tool. That is a load-bearing gap, but a fixable one: the GitHub repo is referenced, so the authors could add a few KPI tables, a short description of the CRLB setup, and at least one accuracy-versus-resource plot. The waveform assumption (OFDM/DFTS-OFDM) is a stated bet rather than a hidden one; fine, but it makes the quantitative insights conditional on that choice.

Proportionate verdict: the qualitative content stands on its own, and the missing numbers do not invalidate the synthesis. As submitted, though, the paper overpromises. I would accept it for peer review, because the framework and the enabler tables deserve refereeing, and the missing pieces are checkable via the repository. I would also push for major revision to make the quantitative contribution visible. If the repository lacks the results, the authors should recast the contribution as a qualitative framework plus a research agenda.

Who benefits: standardization engineers and ISAC researchers wanting a cross-layer map. I would bring it to a reading group, and I would cite the enabler tables in my own work. Recommendation: send it to serious referees, but condition acceptance on the authors showing the actual numbers.

Referee Report

3 major / 6 minor

Summary. This manuscript, developed within the Hexa-X-II project, presents a broad cross-layer vision for integrated sensing and communication (ISAC) in 6G. It reviews ISAC integration levels, use cases, KPIs, channel-model requirements, candidate radio enablers (frequency bands, RIS, NTN, massive MIMO, D-MIMO, AI), hardware architectures and impairments, higher-layer protocols and security/privacy, and then introduces a quantitative cross-layer evaluation framework based on fixed and semi-fixed degrees of freedom, resolution formulas, and a latency decomposition. The paper promises simulation and proof-of-concept results for indoor, urban, and rural scenarios at FR2/FR3, and a link from design parameters to both KPIs and KVIs.

Significance. If completed as promised, the proposed framework would give 6G standardization a practical tool for fair ISAC comparisons, and the qualitative synthesis is genuinely valuable: the integration-level taxonomy (Fig. 3), the enabler-by-enabler comparison tables (Tables III–VII), the treatment of PA nonlinearity and phase noise in monostatic sensing, the functional sensing-session architecture, and the STRIDE/LINDDUN threat analysis are strengths supported by extensive citations. The simulation setup is described with explicit assumptions and a public code repository link. However, the advertised quantitative contribution is not present in the reviewed text: the CRLB/TPEB accuracy bounds are stated to have been derived but omitted, and the paper ends before any KPI or KVI results are reported. The paper's value therefore currently rests on its qualitative vision and framework definition, not on the claimed quantitative evaluation.

major comments (3)

[VI.B.2, VI.C.4, I] Section VI.B.2 states that theoretical error bounds on sensing accuracy (TPEB based on the CRLB) "were derived but not included in the paper," and Section VI.C.4 ends mid-sentence before any simulation or PoC KPI results, tables, or comparisons are reported. The Introduction and Contributions promise a "quantitative cross-layer framework linking design parameters to key performance and value indicators" and its application to simulation and PoC setups. As submitted, the quantitative core of the paper is therefore unverified: the reader is given definitions and formulas for resolution and latency, but not the accuracy-DoF link (the CRLB) nor any system-level results. This is the central claim of the paper and must be addressed, either by including the derivation and results or by explicitly reframing the contribution as a framework proposal without quantitative validation.
[III.C, V] Section III.C explicitly promises a "comparison with existing sensing technologies (e.g., radar, camera, UWB), which will be treated in Section V." Section V, however, covers protocols, functions, computing, and security/privacy and contains no such comparison. Since the paper motivates the framework as a way to "compare ISAC solutions fairly," the missing comparison of ISAC with incumbent sensing technologies weakens the stated contribution. The comparison should be added or the promise removed.
[I, VI.B.2] The abstract and contribution list state that the framework links design parameters to both KPIs and KVIs. Section VI.B.2 and the evaluation setup in Section VI connect the degrees of freedom only to the sensing KPIs (accuracy, resolution, latency); no mapping from KPIs to KVIs is provided anywhere in the text. The KVI link is part of the claimed contribution and needs to be either delivered or explicitly deferred.

minor comments (6)

[VI.B.2] In the latency decomposition, the symbol T_proc^prop is used both for the propagation delay between sensing and processing nodes and for the computation time C/F; the latter should be T_proc^comp. The current notation makes the equation internally inconsistent.
[VI.B.1] Table XVIII lists "300 GLFOP" for the core computational power; this appears to be a typo for "GFLOP", consistent with the other entries and with the units stated in the text.
[V.C.2] The word "applicaitons" should be "applications".
[V.C.4] The term "device class RHDRBL" is introduced without definition or explanation; it should be defined or removed.
[III.C.4] In the many-to-one multistatic sensing enumeration, the two options are both labelled "(ii)"; the second should be "(i)" (or the list should be renumbered).
[II.A] In the Level 2 bullet, "analog-to-digital converters (ADCs), analog-to-digital are utilized" should read "analog-to-digital converters are utilized".

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation found; the paper's self-citations are descriptive and its admitted omissions are completeness gaps, not circularity.

full rationale

The central claimed contribution is a quantitative cross-layer framework (Section I: 'we introduce a quantitative cross-layer framework linking design parameters to key performance and value indicators'). The only quantitative links actually exhibited are standard definitions: range resolution Delta_R = c/(2B), velocity resolution Delta_v = lambda/(2T_Tx), angular resolution Delta_phi = 0.89 lambda/D, and the latency decomposition T_total = T_Tx + T_prop + T_proc (Section VI.B.2). These are KPI definitions or textbook formulas, not outputs of a fitted model, and the paper does not claim to predict them from fitted parameters; using a definitional formula is not a circular derivation of a separate result. The paper explicitly admits that the accuracy link is missing: 'Theoretical error bounds on sensing accuracy (i.e., TPEB, which is based on the CRLB) were derived but not included in the paper' (Section VI.B.2). It also promises a comparison with existing sensing technologies, 'which will be treated in Section V' (Section III.C), but Section V contains no such comparison, and the text ends mid-sentence in Section VI.C.4 before any simulation or PoC KPI table is reported. These are gaps in evidence for the central claim, not circularity. The many self-citations to Hexa-X-II deliverables (e.g., [1], [75], [76]) and earlier works [17], [18] are used to describe project context, the SeMF architecture, and integration levels; none is invoked as a uniqueness theorem, fitted parameter, or ansatz that makes the framework's conclusions true by construction. Therefore no circular step meets the evidentiary bar.

Assumptions & free parameters 10 free parameters · 9 assumptions · 4 invented entities

The central claim is a framework and a vision, not a single physical law, so the ledger captures the many modeling choices and architectural proposals the framework rests on. Most free parameters are explicit scenario choices for the quantitative study rather than fitted constants. The axioms are domain assumptions about 6G standardization and simplified propagation models. The invented entities are network functions and privacy components proposed for future 6G, none with independent experimental evidence.

free parameters (10)

Carrier frequency = 10 GHz and 60 GHz
Semi-fixed radio DoF in Section VI.B.1, Table XVII. Chosen to represent FR3 and FR2, not fitted to data. Affects range, angular resolution, and hardware impairment assumptions.
Number of antennas at BSs/UEs = 2x2 and 4x4
Semi-fixed DoF tied to carrier frequency in Table XVII. Controls angular resolution and beamforming complexity.
Number of OFDM symbols = 16 and 256
Semi-fixed DoF in Table XVII, set equal to Tx antennas times Rx antennas. Affects velocity resolution and latency.
Subcarrier spacing = 30 kHz and 120 kHz
Semi-fixed DoF in Table XVII, chosen with carrier frequency. Affects OFDM symbol duration and Doppler tolerance.
Transmit power = 20 dBm
Fixed DoF in Table XVI. Chosen by authors for simulations; affects SNR and coverage.
Number of RF chains at BSs/UEs = 1
Fixed DoF in Table XVI, simplifies the study to single-stream operation.
Number of subcarriers = 792
Fixed DoF in Table XVI, chosen for the simulation bandwidth and resolution.
Processing location parameters = Extreme edge: 0.015 ms, 0.1 Gbps, 10 GFLOP; edge: 0.15 ms, 1 Gbps, 100 GFLOP; core: 0.8 ms, 10 Gbps, 300 GFLOP
Hand-picked values in Table XVIII for the latency study. If real network values differ, the latency trade-off results change.
Computational load for a sensing request = about 4 MFLOP
Estimate in Section VI.C.3 for one delay and angle estimation with 792 subcarriers and 64 OFDM symbols via 2D FFT. This is a rough hand estimate used in the latency model.
Target RCS and reflectivity = not specified
Simulation models target as a point scatterer with magnitude sqrt(sigma_RCS) and unknown phase; actual RCS values are scenario-dependent and not reported.

assumptions (9)

domain assumption OFDM and DFTS-OFDM will be the 6G standardized waveform
Invoked in Section III opening and Section II.F. All ISAC evaluation is built on OFDM frame structures; if another waveform is standardized, waveform-dependent results need revisiting.
domain assumption Communication and sensing channels are identical and reciprocal after calibration
Stated in Section II.E.1 and used to justify using communication signals for sensing. Real transceivers have non-reciprocal impairments that must be calibrated; the paper acknowledges this but still builds on it.
domain assumption Monostatic sensing requires full-duplex or pseudo-full-duplex operation
Section III.C.2 and Section IV.A.3. The analysis of hardware requirements assumes simultaneous Tx and Rx is necessary for monostatic sensing, which shapes the hardware discussion.
domain assumption Targets can be modeled as point scatterers with angle-independent reflectivity in the simulation study
Section VI.C.1 explicitly assumes a single point target with reflectivity independent of angle-of-incidence. Real targets have extended, frequency-dependent RCS.
domain assumption Only first-order reflections from four walls are considered in indoor simulations
Section VI.C.1. Ignores floor and ceiling and higher-order multipath, which affects sensing accuracy results.
domain assumption Latency decomposition T_total = T_Tx + T_prop + T_proc with stated processing model
Section VI.B.2. The framework assumes latency is additive and that processing latency follows the proposed decomposition. This is a model, not a measurement.
standard math Standard resolution formulas: range resolution c/(2B), velocity resolution lambda/(2T_Tx), angular resolution 0.89 lambda/D
Used in Section VI.B.2 to define KPI relationships. These are textbook formulas under far-field, single-target assumptions.
domain assumption 3GPP TR 38.901 statistical channel model can be extended with RCS target modeling and environmental objects
Section II.E.3. The paper relies on ongoing 3GPP discussions and proposed extensions, which are not yet standardized or fully validated.
ad hoc to paper The Ericsson ISAC integration levels 0 to 4 are a valid taxonomy for framing the problem
Section II.A, Fig. 3. The taxonomy is adopted from [28] and shapes the whole paper, but it is a classification choice, not a derived result.

invented entities (4)

Sensing Management Function (SeMF)
purpose: A network function to control and process sensing sessions, including sensing control (SCF) and sensing processing (SPF).
Proposed in Section V.B as a new 6G network function. No independent implementation or falsifiable measurement is provided; it is an architectural proposal.
Sensing Unit Selection Function (SUSF)
purpose: Selects sensing units and sensing modes (monostatic, bistatic, multistatic) within the SeMF.
Introduced in Section V.B, Fig. 26. It is a design proposal for the 6G architecture, not validated by an external benchmark.
Sensing Policy, Consent, and Transparency Management (SPCTM)
purpose: Enforces security, consent, and privacy policies for sensing operations and manages the Sensing Store.
Proposed in Section V.D.3 and [209]. It is a privacy and security architectural element with no independent evidence of deployment.
Sensing Store
purpose: Repository for sensing policies, use case data, consent logs, and transparency data.
Proposed in Section V.D.3 as part of the privacy framework. No prototype or external data supports it.

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Cite this review

Pith. "Pith review of Cross-layer Integrated Sensing and Communication: A Joint Industrial and Academic Perspective." pith.science (2026). https://pith.science/paper/2YEJZMTC

@misc{pith2026250510933,
  author       = {Pith},
  title        = {Pith review of: Cross-layer Integrated Sensing and Communication: A Joint Industrial and Academic Perspective},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/2YEJZMTC}},
  note         = {Machine review of arXiv:2505.10933}
}

read the original abstract

Integrated sensing and communication (ISAC) enables radio systems to simultaneously sense and communicate with their environment. This paper, developed within the Hexa-X-II project funded by the European Union, presents a comprehensive cross-layer vision for ISAC in 6G networks, integrating insights from physical-layer design, hardware architectures, AI-driven intelligence, and protocol-level innovations. We begin by revisiting the foundational principles of ISAC, highlighting synergies and trade-offs between sensing and communication across different integration levels. Enabling technologies (such as multiband operation, massive and distributed MIMO, non-terrestrial networks, reconfigurable intelligent surfaces, and machine learning) are analyzed in conjunction with hardware considerations including waveform design, synchronization, and full-duplex operation. To bridge implementation and system-level evaluation, we introduce a quantitative cross-layer framework linking design parameters to key performance and value indicators. By synthesizing perspectives from both academia and industry, this paper outlines how deeply integrated ISAC can transform 6G into a programmable and context-aware platform supporting applications from reliable wireless access to autonomous mobility and digital twinning.

Figures

Figures reproduced from arXiv: 2505.10933 by the authors.

**Figure 2.** User positioning, sensing, and object localization. [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗

**Figure 3.** Ericsson proposed several levels of ISAC integration, which can [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗

Figures from the paper (28 more)

**Figure 4.** Figure 4: Examples of ISAC use cases. resources are allocated to both sensing and communication, ensuring maximal resource utilization efficiency and synergy. Such integration is inherent to monostatic sensing,1 since the sensing transmitter and receiver are collocated and shar…

**Figure 5.** Figure 5: A non-exhaustive list of desired ISAC channel model features. [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]

**Figure 6.** Figure 6: ISAC in the Hexa-X-II 6G E2E system, based on [75]. [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]

**Figure 7.** Figure 7: Representative AI/ML for ISAC use cases. [PITH_FULL_IMAGE:figures/full_fig_p010_7.png]

**Figure 8.** Figure 8: A selection of candidate 6G radio enablers that complement ISAC. [PITH_FULL_IMAGE:figures/full_fig_p012_8.png]

**Figure 10.** Figure 10: RIS for ISAC: the monostatic BS with few antennas relies on the [PITH_FULL_IMAGE:figures/full_fig_p014_10.png]

**Figure 11.** Figure 11: NTN for ISAC, where a user is localized based on fusing information [PITH_FULL_IMAGE:figures/full_fig_p015_11.png]

**Figure 12.** Figure 12: Massive MIMO for ISAC, in lower and higher bands. [PITH_FULL_IMAGE:figures/full_fig_p016_12.png]

**Figure 13.** Figure 13: D-MIMO for ISAC relies on cooperation between widely DUs via [PITH_FULL_IMAGE:figures/full_fig_p017_13.png]

**Figure 14.** Figure 14: Monostatic sensing may be performed by UEs (in uplink) or BSs (in [PITH_FULL_IMAGE:figures/full_fig_p019_14.png]

**Figure 15.** Figure 15: Bistatic sensing. The focus of the figure is on downlink, though [PITH_FULL_IMAGE:figures/full_fig_p020_15.png]

**Figure 16.** Figure 16: Multistatic sensing exemplifying scenarios: 1) uplink UE positioning and target sensing; 2) downlink UE positioning and target sensing; 3a) uplink [PITH_FULL_IMAGE:figures/full_fig_p021_16.png]

**Figure 17.** Figure 17: Analog beamforming approaches: (a) typical phased array, (b) true [PITH_FULL_IMAGE:figures/full_fig_p023_17.png]

**Figure 18.** Figure 18: Array configuration modes with phase-TTD array architecture for [PITH_FULL_IMAGE:figures/full_fig_p023_18.png]

**Figure 19.** Figure 19: Full duplex architectures for ISAC. (a) MIMO IBFD provides [PITH_FULL_IMAGE:figures/full_fig_p024_19.png]

**Figure 21.** Figure 21: Block diagram of shared LO source in monostatic sensing and PN [PITH_FULL_IMAGE:figures/full_fig_p025_21.png]

**Figure 22.** Figure 22: Range error in monostatic sensing caused by the LO PN vs the [PITH_FULL_IMAGE:figures/full_fig_p026_22.png]

**Figure 23.** Figure 23: Illustration of anchor calibration and deployment in ISAC systems. [PITH_FULL_IMAGE:figures/full_fig_p026_23.png]

**Figure 24.** Figure 24: Functional architecture for ISAC with UE involvement. [PITH_FULL_IMAGE:figures/full_fig_p028_24.png]

**Figure 25.** Figure 25: Sequence diagram for a sensing session with UE involvement. (Blue text represents actions due to UE involvement). [PITH_FULL_IMAGE:figures/full_fig_p030_25.png]

**Figure 26.** Figure 26: Detailed view of the sensing control function. [PITH_FULL_IMAGE:figures/full_fig_p030_26.png]

**Figure 27.** Figure 27: Privacy controls for ISAC. 3) Potential Privacy Controls: Considering the sensitivity of the sensing data and the privacy of sensing targets, several enhancements have been considered to be introduced to the network. • Dedicated functions: A new network function calle…

**Figure 28.** Figure 28: Indoor simulation scenario 1, 60 GHz. Tx and Rx are placed at the [PITH_FULL_IMAGE:figures/full_fig_p038_28.png]

**Figure 29.** Figure 29: Indoor simulation scenario 2, 60 GHz. Tx and Rx are placed facing [PITH_FULL_IMAGE:figures/full_fig_p038_29.png]

**Figure 33.** Figure 33: Simulation of the effect of higher-layer computational load distribu [PITH_FULL_IMAGE:figures/full_fig_p039_33.png]

**Figure 32.** Figure 32: Rural highway simulation, error CDF plot for 10 GHz and 60 GHz [PITH_FULL_IMAGE:figures/full_fig_p039_32.png]

**Figure 34.** Figure 34: Predicting pose of a human with mmWave ISAC: Blue colored [PITH_FULL_IMAGE:figures/full_fig_p040_34.png]

**Figure 35.** Figure 35: PoC measurement results using the ISAC testbed. [PITH_FULL_IMAGE:figures/full_fig_p041_35.png]

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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

A Framework for Geometry-based Statistical Channel Modeling in ISAC Systems
eess.SP 2025-11 conditional novelty 5.0 of 10

A bistatic ISAC channel framework decomposes the channel into target and background parts, adds deterministic geometric clusters to TR38.901, and claims BER/capacity parity while enabling sensing evaluation.

Reference graph

Works this paper leans on

226 extracted references · 72 canonical work pages · cited by 1 Pith paper

[1]

Early results of 6G radio key enablers,

A. Nimret al., “Early results of 6G radio key enablers,” Hexa-X-II project Deliverable D4.3, 2024. [Online]. Available: https://hexa-x-ii.eu/deliverables/

2024
[2]

Integrated sensing and communications: Toward dual- functional wireless networks for 6G and beyond,

F. Liuet al., “Integrated sensing and communications: Toward dual- functional wireless networks for 6G and beyond,”IEEE Journal on Selected Areas in Communications, vol. 40, no. 6, pp. 1728–1767, 2022

2022
[3]

The integrated sensing and communication revolution for 6G: Vision, techniques, and applications,

N. Gonz ´alez-Prelcicet al., “The integrated sensing and communication revolution for 6G: Vision, techniques, and applications,”Proceedings of the IEEE, vol. 112, no. 7, pp. 676–723, July 2024

2024
[4]

Cmwave and sub-THz: Key radio enablers and complementary spectrum for 6G,

M. V . Katweet al., “Cmwave and sub-THz: Key radio enablers and complementary spectrum for 6G,”arXiv preprint arXiv:2406.18391, 2024

arXiv 2024
[5]

NTN-based 6G localization: Vision, role of leos, and open problems,

H. K. Dureppagariet al., “NTN-based 6G localization: Vision, role of leos, and open problems,”IEEE Wireless Communications, vol. 30, no. 6, pp. 44–51, 2023

2023
[6]

Integrated sensing and communication with mmwave massive MIMO: A compressed sampling perspective,

Z. Gaoet al., “Integrated sensing and communication with mmwave massive MIMO: A compressed sampling perspective,”IEEE Trans- actions on Wireless Communications, vol. 22, no. 3, pp. 1745–1762, 2022

2022
[7]

Integrated communication, localization, and sensing in 6G D-MIMO networks,

H. Guoet al., “Integrated communication, localization, and sensing in 6G D-MIMO networks,”IEEE Wireless Communication Magazine, vol. 32, no. 2, pp. 214–221, 2025

2025
[8]

Integrated sensing and communication for 6G: Ten key machine learning roles,

U. Demirhanet al., “Integrated sensing and communication for 6G: Ten key machine learning roles,”IEEE Communications Magazine, vol. 61, no. 5, pp. 113–119, 2023

2023

Show all 226 references

[9]

Joint waveform and beamforming design for RIS- aided ISAC systems,

K. Zhonget al., “Joint waveform and beamforming design for RIS- aided ISAC systems,”IEEE Signal Processing Letters, vol. 30, pp. 165–169, 2023

2023
[10]

Active reconfigurable intelligent surface-assisted MISO integrated sensing and communication systems for secure oper- ation,

A. A. Salemet al., “Active reconfigurable intelligent surface-assisted MISO integrated sensing and communication systems for secure oper- ation,”IEEE Trans. Veh. Technol., vol. 72, no. 4, pp. 4919–4931, Apr. 2023

2023
[11]

Muet al.,Exploiting Non-orthogonal Multiple Access in Integrated Sensing and Communications

X. Muet al.,Exploiting Non-orthogonal Multiple Access in Integrated Sensing and Communications. Wiley Online Library, 2024, pp. 205– 225

2024
[12]

Rate-splitting multiple access for simultaneous multi- user communication and sensing,

K. Chenet al., “Rate-splitting multiple access for simultaneous multi- user communication and sensing,”IEEE Trans. Veh. Technol., vol. 73, no. 9, pp. 13 909–13 914, Sept. 2024. 42

2024
[13]

Next-generation multiple access for integrated sensing and communications,

Y . Liuet al., “Next-generation multiple access for integrated sensing and communications,”Proceedings of the IEEE, vol. 112, no. 9, pp. 1467–1496, Sept. 2024

2024
[14]

RIS-assisted cooperative multicell ISAC systems: A multi-user and multi-target case,

X. Yanget al., “RIS-assisted cooperative multicell ISAC systems: A multi-user and multi-target case,”IEEE Trans. Wireless Commun., vol. 23, no. 8, pp. 8683–8699, Aug. 2024

2024
[15]

Joint target assignment and resource allocation for multi- base station cooperative ISAC in UA V detection,

R. Liet al., “Joint target assignment and resource allocation for multi- base station cooperative ISAC in UA V detection,”IEEE Trans. Veh. Technol., vol. 74, no. 5, pp. 7700–7714, May 2025

2025
[16]

6G positioning and sensing through the lens of sustainability, inclusiveness, and trustworthiness,

H. Wymeerschet al., “6G positioning and sensing through the lens of sustainability, inclusiveness, and trustworthiness,”IEEE Wireless Communications, vol. 32, no. 1, pp. 68–75, Feb. 2025

2025
[17]

Integration of communication and sensing in 6G: A joint industrial and academic perspective,

H. Wymeerschet al., “Integration of communication and sensing in 6G: A joint industrial and academic perspective,” in2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2021, pp. 1–7

2021
[18]

Joint communication and sensing for 6G- a cross-layer perspective,

H. Wymeerschet al., “Joint communication and sensing for 6G- a cross-layer perspective,” in2024 IEEE 4th International Symposium on Joint Communications & Sensing (JC&S), 2024, pp. 01–06

2024
[19]

Intelligent integrated sensing and communication: a survey,

J. Zhanget al., “Intelligent integrated sensing and communication: a survey,”Science China - Information Sciences, vol. 68, no. 3, MAR 2025

2025
[20]

Realizing joint communication and sensing RF receiver front-ends: A survey,

S. Georgeet al., “Realizing joint communication and sensing RF receiver front-ends: A survey,”IEEE Access, vol. 12, pp. 9440–9457, 2024

2024
[21]

Coordinated multipoint jcas in 6G mobile networks,

Y . Suet al., “Coordinated multipoint jcas in 6G mobile networks,” IEEE Access, vol. 12, pp. 98 530–98 545, 2024

2024
[22]

Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G,

G. Zhuet al., “Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G,” Science China - Information Sciences, vol. 66, no. 3, SI, MAR 2023

2023
[23]

Deterministic signal processing techniques for OFDM-based radar sensing: An overview,

M. Mirabellaet al., “Deterministic signal processing techniques for OFDM-based radar sensing: An overview,”IEEE Access, vol. 11, pp. 68 872–68 889, 2023

2023
[24]

Security and privacy for reconfigurable intelligent surface in 6G: A review of prospective applications and challenges,

F. Naeemet al., “Security and privacy for reconfigurable intelligent surface in 6G: A review of prospective applications and challenges,” IEEE Open Journal of the Communications Society, vol. 4, pp. 1196– 1217, 2023

2023
[25]

A review of millimeter wave device-based local- ization and device-free sensing technologies and applications,

A. Shastriet al., “A review of millimeter wave device-based local- ization and device-free sensing technologies and applications,”IEEE Communications Surveys & Tutorials, vol. 24, no. 3, pp. 1708–1749, 2022

2022
[26]

Enabling joint communication and radar sensing in mobile networks—a survey,

J. A. Zhanget al., “Enabling joint communication and radar sensing in mobile networks—a survey,”IEEE Commun. Surv. Tutorials, vol. 24, no. 1, pp. 306–345, 2022

2022
[27]

Seventy years of radar and communications: The road from separation to integration,

F. Liuet al., “Seventy years of radar and communications: The road from separation to integration,”IEEE Signal Processing Magazine, vol. 40, no. 5, pp. 106–121, 2023

2023
[28]

(2024) Integrated sensing and communication

Robert Baldemair (Ericsson). (2024) Integrated sensing and communication. [Online]. Available: https://www.ericsson.com/en/ blog/2024/6/integrated-sensing-and-communication

2024
[29]

Integrated sensing and communication signals toward 5G-A and 6G: A survey,

Z. Weiet al., “Integrated sensing and communication signals toward 5G-A and 6G: A survey,”IEEE Internet of Things Journal, vol. 10, no. 13, pp. 11 068–11 092, 2023

2023
[30]

Multicarrier ISAC: Advances in waveform design, signal processing, and learning under nonidealities,

V . Koivunenet al., “Multicarrier ISAC: Advances in waveform design, signal processing, and learning under nonidealities,”IEEE Signal Processing Magazine, vol. 41, no. 5, pp. 17–30, 2024

2024
[31]

6G use cases and requirements,

J. Almodovaret al., “6G use cases and requirements,” Hexa- X-II project Deliverable D1.2, 2023. [Online]. Available: https: //hexa-x-ii.eu/deliverables/

2023
[32]

Hybrid precoding and combining for mmwave full-duplex joint radar and communication systems under self- interference,

M. Bayraktaret al., “Hybrid precoding and combining for mmwave full-duplex joint radar and communication systems under self- interference,” inInternational Conference on Communications. IEEE, 2024, pp. 915–920

2024
[33]

High-rate uninterrupted internet of vehicle communica- tions in highways: Dynamic blockage avoidance and CSIT acquisition,

H. Guoet al., “High-rate uninterrupted internet of vehicle communica- tions in highways: Dynamic blockage avoidance and CSIT acquisition,” IEEE Commun. Mag., vol. 60, no. 7, pp. 44–50, Jul. 2022

2022
[34]

Predictor antenna: A technique to boost the performance of moving relays,

H. Guoet al., “Predictor antenna: A technique to boost the performance of moving relays,”IEEE Commun. Mag., vol. 59, no. 7, pp. 80–86, Jul. 2021

2021
[35]

Joint radar and communications: Architectures, use cases, aspects of radio access, signal processing, and hardware,

V . Shatovet al., “Joint radar and communications: Architectures, use cases, aspects of radio access, signal processing, and hardware,”IEEE Access, vol. 12, pp. 47 888–47 914, 2024

2024
[36]

Leveraging Rough-Relay-Surface Scattering for Non- Line-of-Sight mmWave Radar Sensing,

Y . Xuet al., “Leveraging Rough-Relay-Surface Scattering for Non- Line-of-Sight mmWave Radar Sensing,”IEEE Internet of Things Journal, vol. 11, no. 6, pp. 10 964–10 978, March 2024

2024
[37]

Millimeter-wave radio SLAM: End-to-end processing methods and experimental validation,

E. Rastorgueva-Foiet al., “Millimeter-wave radio SLAM: End-to-end processing methods and experimental validation,”IEEE Journal on Selected Areas in Communications, vol. 42, no. 9, Sept. 2024

2024
[38]

Resources reservation schemes for time-sensitive networked vehicular applications with a view on ISAC,

A. Al-Khatibet al., “Resources reservation schemes for time-sensitive networked vehicular applications with a view on ISAC,”IEEE Access, vol. 12, pp. 139 649–139 668, 2024

2024
[39]

Resource allocation for ISAC and HRLLC in UA V- assisted HSR system with a hybrid PSO-genetic algorithm,

Y . Qiaoet al., “Resource allocation for ISAC and HRLLC in UA V- assisted HSR system with a hybrid PSO-genetic algorithm,”IEEE Internet of Things Journal, pp. 1–1, 2024

2024
[40]

Intelligent multi-modal sensing-communication inte- gration: Synesthesia of machines,

X. Chenget al., “Intelligent multi-modal sensing-communication inte- gration: Synesthesia of machines,”IEEE Communications Surveys & Tutorials, vol. 26, no. 1, pp. 258–301, 2024

2024
[42]

Joint vehicle connection and beamforming opti- miziation in digital-twin-assisted integrated sensing and communication vehicular networks,

W. Dinget al., “Joint vehicle connection and beamforming opti- miziation in digital-twin-assisted integrated sensing and communication vehicular networks,”IEEE Internet of Things Journal, vol. 11, no. 20, pp. 32 923–32 938, 2024

2024
[43]

Joint task offloading and resource allocation for integrated VLC and sensing in digital twin-aided vehicular edge computing networks,

H. N. Yanget al., “Joint task offloading and resource allocation for integrated VLC and sensing in digital twin-aided vehicular edge computing networks,”IEEE Trans. Veh. Technol., vol. 73, no. 1, pp. 45–56, Jan. 2024

2024
[44]

Site-specific outdoor propagation assessment and ray-tracing analysis for wireless digital twins,

M. Ghaderi Aramet al., “Site-specific outdoor propagation assessment and ray-tracing analysis for wireless digital twins,” inProc. IEEE EuCAP, 2025

2025
[45]

Network digital twins for multi-domain planning and operations,

M. Goudy, “Network digital twins for multi-domain planning and operations,” inProc. IEEE Int. Conf. Microw., Commun., Antennas, Electron. Syst., Feb. 2024, pp. 230–235

2024
[46]

Leveraging deep learning on multimodal sensor data for wireless communication: From mmWave beamforming to digital twins,

B. Salehihikouei, “Leveraging deep learning on multimodal sensor data for wireless communication: From mmWave beamforming to digital twins,” Ph.D. dissertation, ProQuest, May 2024

2024
[47]

An information-theoretic approach to joint sensing and communication,

M. Ahmadipouret al., “An information-theoretic approach to joint sensing and communication,”IEEE Transactions on Information The- ory, vol. 70, no. 2, pp. 1124–1146, 2024

2024
[48]

Fundamental trade-offs in monostatic ISAC: A holistic investigation towards 6G,

M. F. Keskinet al., “Fundamental trade-offs in monostatic ISAC: A holistic investigation towards 6G,”IEEE Transactions on Wireless Communications, 2025

2025
[49]

Joint radar-communication systems: Mod- ulation schemes and system design,

L. Giroto de Oliveiraet al., “Joint radar-communication systems: Mod- ulation schemes and system design,”IEEE Transactions on Microwave Theory and Techniques, vol. 70, no. 3, pp. 1521–1551, 2022

2022
[50]

Optimized waveform design for OFDM-based ISAC systems under limited resource occupancy,

S. Muraet al., “Optimized waveform design for OFDM-based ISAC systems under limited resource occupancy,”IEEE Transactions on Wireless Communications, vol. 24, no. 6, pp. 5241–5254, 2025

2025
[51]

When are sensing symbols required for ISAC?

M. B. Salmanet al., “When are sensing symbols required for ISAC?” IEEE Transactions on Vehicular Technology, vol. 73, no. 10, pp. 15 709–15 714, 2024

2024
[52]

Cram ´er-rao bound optimization for joint radar- communication beamforming,

F. Liuet al., “Cram ´er-rao bound optimization for joint radar- communication beamforming,”IEEE Transactions on Signal Process- ing, vol. 70, pp. 240–253, 2022. 43

2022
[53]

Limited feedforward waveform design for OFDM dual-functional radar-communications,

M. F. Keskinet al., “Limited feedforward waveform design for OFDM dual-functional radar-communications,”IEEE Transactions on Signal Processing, vol. 69, pp. 2955–2970, 2021

2021
[54]

System-level analysis of joint sensing and commu- nication based on 5G new radio,

L. Pucciet al., “System-level analysis of joint sensing and commu- nication based on 5G new radio,”IEEE Journal on Selected Areas in Communications, vol. 40, no. 7, pp. 2043–2055, 2022

2022
[55]

On outage-based beamforming design for dual- functional radar-communication 6G systems,

A. Bazziet al., “On outage-based beamforming design for dual- functional radar-communication 6G systems,”IEEE Transactions on Wireless Communications, vol. 22, no. 8, pp. 5598–5612, 2023

2023
[56]

The potential of context-aided communications,

H. Guoet al., “The potential of context-aided communications,” in 2023 International Workshop on Antenna Technology (iWAT). IEEE, 2023, pp. 1–3

2023
[57]

Integrated Sensing and Communication Channel: Measurements, Characteristics, and Modeling,

J. Zhanget al., “Integrated Sensing and Communication Channel: Measurements, Characteristics, and Modeling,”IEEE Communications Magazine, vol. 62, no. 6, pp. 98–104, 2024

2024
[58]

Study on channel model for frequencies from 0.5 to 100 GHz,

“Study on channel model for frequencies from 0.5 to 100 GHz,” 3GPP, Tech. Rep. 38.901 (V17.0.0), Mar. 2022

2022
[59]

Generalized radar clutter model,

D. A. Shnidman, “Generalized radar clutter model,”IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no. 3, pp. 857–865, 2002

2002
[60]

6G localization and sensing in the near field: Fea- tures, opportunities, and challenges,

H. Chenet al., “6G localization and sensing in the near field: Fea- tures, opportunities, and challenges,”IEEE Wireless Communications, vol. 31, no. 4, pp. 260–267, 2024

2024
[61]

Near-field tracking with large antenna arrays: Fundamental limits and practical algorithms,

A. Guerraet al., “Near-field tracking with large antenna arrays: Fundamental limits and practical algorithms,”IEEE Transactions on Signal Processing, vol. 69, pp. 5723–5738, 2021

2021
[62]

Effects of building materials and structures on radiowave propagation above about 100 MHz,

“Effects of building materials and structures on radiowave propagation above about 100 MHz,” International Telecommunication Union, Recommendation P.2040-3, 2023. [Online]. Available: https://www. itu.int/rec/R-REC-P.2040/

2023
[63]

Permittivity of Pure Water, at Standard Atmospheric Pressure, over the Frequency range – 0-25THz and the Temperature Range –100°C,

W. J. Ellison, “Permittivity of Pure Water, at Standard Atmospheric Pressure, over the Frequency range – 0-25THz and the Temperature Range –100°C,”J. Physical and Chemical Reference Data, vol. 36, no. 1, pp. 1–18, Feb. 2007

2007
[64]

A discrete environment-driven GPU-based ray launch- ing algorithm,

J. S. Luet al., “A discrete environment-driven GPU-based ray launch- ing algorithm,”IEEE Trans. Ant. Prop., vol. 67, no. 2, pp. 1180–1192, 2019

2019
[65]

Map-Based Channel Model for Evaluation of 5G Wireless Communication Systems,

P. Ky ¨ostiet al., “Map-Based Channel Model for Evaluation of 5G Wireless Communication Systems,”IEEE Trans. Ant. Prop., vol. 65, no. 12, pp. 6491–6504, 2017

2017
[66]

Rough-Surface Scattering Theory and Modeling for 6G ISAC,

X. Liet al., “Rough-Surface Scattering Theory and Modeling for 6G ISAC,” inGlobecom Works. (GC Wkshps 2022), 2022, pp. 1310–1316

2022
[67]

A Scatterer-based Hybrid Channel Model for Integrated Sensing and Communications (ISAC),

Y . Chenet al., “A Scatterer-based Hybrid Channel Model for Integrated Sensing and Communications (ISAC),” inProc. 34th Annual Int. Symp. Personal, Indoor and Mobile Radio Commun. (PIMRC2023), Tronto, ON, Sep. 2023, pp. 1–7

2023
[68]

The COST 2100 MIMO channel model,

L. Liuet al., “The COST 2100 MIMO channel model,”IEEE Wireless Communications, vol. 19, no. 6, pp. 92–99, 2012

2012
[69]

QuaDRiGa: A 3-D multi-cell channel model with time evolution for enabling virtual field trials,

S. Jaeckelet al., “QuaDRiGa: A 3-D multi-cell channel model with time evolution for enabling virtual field trials,”IEEE Transactions on Antennas and Propagation, vol. 62, no. 6, pp. 3242–3256, 2014

2014
[70]

Empirical Path Loss Channel Modeling at 28 GHz for Integrated Sensing and Communication System,

Z. Chaiet al., “Empirical Path Loss Channel Modeling at 28 GHz for Integrated Sensing and Communication System,” in2023 Interna- tional Conference on Wireless Communications and Signal Processing (WCSP), 2023, pp. 366–370

2023
[71]

Latest progress for 3GPP ISAC channel modeling standardization

Y . Zhanget al., “Latest progress for 3GPP ISAC channel modeling standardization.” Springer, 2024

2024
[72]

Simulating the Radar Cross Section of a Bare Tree: From Megahertz to Terahertz,

O. Csernyavaet al., “Simulating the Radar Cross Section of a Bare Tree: From Megahertz to Terahertz,” inProc. 16th European Conf. Ant. Prop. (EuCAP 2022), Madrid, Spain, Apr. 2022, pp. 1–5

2022
[73]

A Shared Cluster-Based Stochastic Channel Model for Integrated Sensing and Communication Systems,

Y . Liuet al., “A Shared Cluster-Based Stochastic Channel Model for Integrated Sensing and Communication Systems,”IEEE Transactions on Vehicular Technology, vol. 73, no. 5, pp. 6032–6044, 2024

2024
[74]

Experimental Analysis and Modeling of Monostatic AA V RCS for ISAC Channels,

Z. Yuanet al., “Experimental Analysis and Modeling of Monostatic AA V RCS for ISAC Channels,”IEEE Antennas and Wireless Propa- gation Letters, vol. 24, no. 1, pp. 222–226, 2025

2025
[75]

Deliverable d2.3 interim overall 6G system design,

Z. Zhenhuaet al., “Deliverable d2.3 interim overall 6G system design,” Hexa-X-II project Deliverable D2.3, 2024. [Online]. Available: https://hexa-x-ii.eu/deliverables/

2024
[76]

Deliverable D2.3 Interim overall 6G system de- sign,

Hexa-X-II, “Deliverable D2.3 Interim overall 6G system de- sign,” https://hexa-x-ii.eu/wp-content/uploads/2024/07/Hexa-X-II D2. 3-v1.1.pdf, [Accessed 11-02-2025]

2024
[77]

5G; 5G System; Network Exposure Function Northbound APIs; Stage 3,

3GPP, “5G; 5G System; Network Exposure Function Northbound APIs; Stage 3,” https://www.etsi.org/deliver/etsi ts/129500 129599/129522/ 16.04.00 60/ts 129522v160400p.pdf, [Accessed 11-02-2025]

2025
[78]

Service Enabler Architecture Layer for Verticals (SEAL); Functional architecture and information flows,

3GPP, “Service Enabler Architecture Layer for Verticals (SEAL); Functional architecture and information flows,” https://www.etsi.org/deliver/etsi ts/123400 123499/123434/17.06. 00 60/ts 123434v170600p.pdf, [Accessed 11-02-2025]

2025
[79]

API Overview 2013; Camara Project — camarapro- ject.org,

CAMARA, “API Overview 2013; Camara Project — camarapro- ject.org,” https://camaraproject.org/api-overview/, [Accessed 11-02- 2025]

2013
[80]

The Hexa-X project vision on artificial intelligence and machine learning-driven communication and computation co- design for 6G,

M. Merluzziet al., “The Hexa-X project vision on artificial intelligence and machine learning-driven communication and computation co- design for 6G,”IEEE Access, vol. 11, pp. 65 620–65 648, 2023

2023
[81]

Next generation mobile networks’ enablers: Machine learning-assisted mobility, traffic, and radio channel prediction,

H. Ryd ´enet al., “Next generation mobile networks’ enablers: Machine learning-assisted mobility, traffic, and radio channel prediction,”IEEE Communications Magazine, vol. 61, no. 10, pp. 94–98, 2023

2023
[82]

6G AI-driven air interface: Hexa-X-II view,

H. Farhadiet al., “6G AI-driven air interface: Hexa-X-II view,”IEEE Comm. Magazine, 2025

2025
[83]

A deep learning receiver for non-linear transmitter,

H. Farhadiet al., “A deep learning receiver for non-linear transmitter,” IEEE Access, vol. 11, pp. 2796–2803, 2023

2023
[84]

Machine learning empowered context-aware receiver for high-band transmission,

H. Farhadiet al., “Machine learning empowered context-aware receiver for high-band transmission,” in2020 IEEE Globecom Workshops (GC Wkshps, 2020, pp. 1–6

2020
[85]

Millimeter wave wireless assisted robot navigation with link state classification,

M. Yinet al., “Millimeter wave wireless assisted robot navigation with link state classification,”IEEE Open J. Commun. Soc., vol. 3, pp. 493– 507, May. 2022

2022
[86]

Network-controlled repeater–an introduction,

F. Carvalhoet al., “Network-controlled repeater–an introduction,”arXiv preprint arXiv:2403.09601, 2024

2024 arXiv
[87]

Towards 6G with THz communications: Understanding the propagation channels,

X. Caiet al., “Towards 6G with THz communications: Understanding the propagation channels,”IEEE Commun. Mag., vol. 62, no. 2, pp. 32–38, 2024

2024
[88]

V2X sidelink positioning in FR1: Scenarios, algorithms, and performance evaluation,

Y . Geet al., “V2X sidelink positioning in FR1: Scenarios, algorithms, and performance evaluation,”IEEE Journal on Selected Areas in Communications, vol. 42, no. 10, pp. 2608–2624, 2024

2024
[89]

6G wireless channel measurements and models: Trends and challenges,

C.-X. Wanget al., “6G wireless channel measurements and models: Trends and challenges,”IEEE Vehicular Technology Magazine, vol. 15, no. 4, pp. 22–32, 2020

2020
[90]

Wideband mmwave massive MIMO channel estimation and localization,

S. Wenget al., “Wideband mmwave massive MIMO channel estimation and localization,”IEEE Wireless Communications Letters, vol. 12, no. 8, pp. 1314–1318, 2023

2023
[91]

Modeling and analysis of OFDM-based 5G/6G local- ization under hardware impairments,

H. Chenet al., “Modeling and analysis of OFDM-based 5G/6G local- ization under hardware impairments,”IEEE Transactions on Wireless Communications, vol. 23, no. 7, pp. 7319–7333, 2024

2024
[92]

Twelve scientific challenges for 6G: Rethinking the foundations of communications theory,

M. Chafiiet al., “Twelve scientific challenges for 6G: Rethinking the foundations of communications theory,”IEEE Commun. Surv. Tutor., vol. 25, no. 2, pp. 868–904, Apr. 2023

2023
[93]

Cellular wireless networks in the upper mid-band,

S. Kanget al., “Cellular wireless networks in the upper mid-band,” IEEE Open J. Commun. Soc., vol. 5, pp. 2058–2075, Mar. 2024

2024
[94]

Upper mid-band channel measurements and character- ization at 6.75 GHz FR1(C) and 16.95 GHz FR3 in an indoor factory scenario,

M. Yinget al., “Upper mid-band channel measurements and character- ization at 6.75 GHz FR1(C) and 16.95 GHz FR3 in an indoor factory scenario,”arXiv preprint arXiv:2411.03565, Nov. 2024. 44

2024 arXiv
[95]

Comprehensive FR1(C) and FR3 lower and upper mid-band propagation and material penetration loss measurements and channel models in indoor environment for 5G and 6G,

D. Shakyaet al., “Comprehensive FR1(C) and FR3 lower and upper mid-band propagation and material penetration loss measurements and channel models in indoor environment for 5G and 6G,”IEEE Open J. Commun. Soc., vol. 5, pp. 5192–5218, Oct. 2024

2024
[96]

An experimental multi-band channel characterization in the upper mid-band,

R. Bomfinet al., “An experimental multi-band channel characterization in the upper mid-band,”arXiv preprint arXiv:2411.12888, Nov. 2024

2024 arXiv
[97]

The rise of intelligent reflecting surfaces in integrated sensing and communications paradigms,

A. M. Elbiret al., “The rise of intelligent reflecting surfaces in integrated sensing and communications paradigms,”IEEE Network, vol. 37, no. 6, pp. 224–231, 2023

2023
[98]

Reconfigurable intelligent surfaces: A signal pro- cessing perspective with wireless applications,

E. Bj ¨ornsonet al., “Reconfigurable intelligent surfaces: A signal pro- cessing perspective with wireless applications,”IEEE Signal Processing Magazine, vol. 39, no. 2, pp. 135–158, 2022

2022
[99]

Modeling and coverage analysis of RIS-assisted integrated sensing and communication networks,

X. Ganet al., “Modeling and coverage analysis of RIS-assisted integrated sensing and communication networks,”IEEE Transactions on Wireless Communications, 2025

2025
[100]

Joint beamforming for RIS-assisted integrated sensing and communication systems,

Y . Xuet al., “Joint beamforming for RIS-assisted integrated sensing and communication systems,”IEEE Transactions on Communications, vol. 72, no. 4, pp. 2232–2246, 2023

2023
[101]

RIS-aided NLoS monostatic sensing under mobility and angle-Doppler coupling,

M. K. Ercanet al., “RIS-aided NLoS monostatic sensing under mobility and angle-Doppler coupling,” inIEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2024, pp. 1–6

2024
[102]

RIS-aided monostatic sensing and object detection with single and double bounce multipath,

H. Kimet al., “RIS-aided monostatic sensing and object detection with single and double bounce multipath,” inIEEE International Conference on Communications Workshops, 2023, pp. 1883–1889

2023
[103]

Calibration in RIS-aided integrated sensing, local- ization and communication systems,

R. Ghazalianet al., “Calibration in RIS-aided integrated sensing, local- ization and communication systems,”arXiv preprint arXiv:2409.16931, 2024

2024 arXiv
[104]

RIS-aided mobile localization error bounds under hardware impairments,

F. Ghaseminajmet al., “RIS-aided mobile localization error bounds under hardware impairments,”IEEE Transactions on Communications, vol. 70, no. 12, pp. 8331–8341, 2022

2022
[105]

Six integration avenues for ISAC in 6G and beyond,

N. Gonz ´alez-Prelcicet al., “Six integration avenues for ISAC in 6G and beyond,”IEEE Vehicular Technology Magazine, vol. 20, no. 1, pp. 18–39, 2025

2025
[106]

Non-terrestrial networks in the 6G era: Challenges and opportunities,

M. Giordaniet al., “Non-terrestrial networks in the 6G era: Challenges and opportunities,”IEEE Network, vol. 35, no. 2, pp. 244–251, 2021

2021
[107]

ISAC towards 6G satellite–terrestrial communications: Principles, status, and prospects,

Y . Guet al., “ISAC towards 6G satellite–terrestrial communications: Principles, status, and prospects,”Electronics, vol. 13, no. 7, p. 1369, 2024

2024
[108]

Integrated 6G TN and NTN localization: Challenges, opportunities, and advancements,

S. Salehet al., “Integrated 6G TN and NTN localization: Challenges, opportunities, and advancements,”IEEE Communications Standards Magazine, 2025

2025
[109]

An integrated LEO communication and PNT system for beyond 5G NTN,

R. De Gaudenzi, “An integrated LEO communication and PNT system for beyond 5G NTN,”International Journal of Satellite Communica- tions and Networking, 2025

2025
[110]

Joint communication and sensing toward 6G: Models and potential of using MIMO,

X. Fanget al., “Joint communication and sensing toward 6G: Models and potential of using MIMO,”IEEE Internet of Things Journal, vol. 10, no. 5, pp. 4093–4116, 2023

2023
[111]

An overview of massive MIMO: Benefits and challenges,

L. Luet al., “An overview of massive MIMO: Benefits and challenges,” IEEE journal of selected topics in signal processing, vol. 8, no. 5, pp. 742–758, 2014

2014
[112]

Channel estimation for extremely large-scale massive MIMO: Far-field, near-field, or hybrid-field?

X. Weiet al., “Channel estimation for extremely large-scale massive MIMO: Far-field, near-field, or hybrid-field?”IEEE Communications Letters, vol. 26, no. 1, pp. 177–181, 2021

2021
[113]

On the impact of hardware impairments on massive MIMO,

U. Gustavssonet al., “On the impact of hardware impairments on massive MIMO,” inIEEE Globecom Workshops (GC Wkshps). IEEE, 2014, pp. 294–300

2014
[114]

Toward seamless sensing coverage for cellular multi-static integrated sensing and communication,

R. Liet al., “Toward seamless sensing coverage for cellular multi-static integrated sensing and communication,”IEEE Transactions on Wireless Communications, vol. 23, no. 6, pp. 5363–5376, 2023

2023
[115]

Joint localization, synchronization and mapping via phase-coherent distributed arrays,

A. Fascistaet al., “Joint localization, synchronization and mapping via phase-coherent distributed arrays,”IEEE Journal of Selected Topics in Signal Processing, vol. 19, no. 2, pp. 412–429, 2025

2025
[116]

Cell-free massive MIMO: A survey,

S. Elhoushyet al., “Cell-free massive MIMO: A survey,”IEEE Communications Surveys & Tutorials, vol. 24, no. 1, pp. 492–523, 2021

2021
[117]

Trajectory design and resource allocation for multi- UA V-assisted sensing, communication, and edge computing integra- tion,

S. Penget al., “Trajectory design and resource allocation for multi- UA V-assisted sensing, communication, and edge computing integra- tion,”IEEE Transactions on Communications, vol. 73, no. 4, pp. 2847– 2861, 2025

2025
[118]

The degrees-of-freedom in monostatic ISAC channels: NLoS exploitation vs. reduction,

S. Luet al., “The degrees-of-freedom in monostatic ISAC channels: NLoS exploitation vs. reduction,”IEEE Transactions on Vehicular Technology, vol. 72, no. 2, pp. 2643–2648, 2022

2022
[119]

Personal mobile radars with millimeter-wave massive arrays for indoor mapping,

F. Guidiet al., “Personal mobile radars with millimeter-wave massive arrays for indoor mapping,”IEEE Transactions on Mobile Computing, vol. 15, no. 6, pp. 1471–1484, 2015

2015
[120]

K. Wuet al., “Sensing in bistatic ISAC systems with clock asyn- chronism: A signal processing perspective [special issue on signal processing for the integrated sensing and communications revolution],” IEEE Signal Processing Magazine, vol. 41, no. 5, pp. 31–43, 2024

2024
[121]

RISs and sidelink communications in smart cities: The key to seamless localization and sensing,

H. Chenet al., “RISs and sidelink communications in smart cities: The key to seamless localization and sensing,”IEEE Communications Magazine, vol. 61, no. 8, pp. 140–146, 2023

2023
[122]

Mmwave mapping and SLAM for 5G and beyond,

Y . Geet al., “Mmwave mapping and SLAM for 5G and beyond,” in Integrated Sensing and Communications. Springer, 2023, pp. 445– 475

2023
[123]

Bistatic integrated sensing and communication sce- narios with transmitter and receiver-side trade-offs,

S. Fodoret al., “Bistatic integrated sensing and communication sce- narios with transmitter and receiver-side trade-offs,” in2025 IEEE 5th International Symposium on Joint Communications & Sensing (JC&S). IEEE, 2025, pp. 1–6

2025
[124]

Cooperative sensing for 6G mobile cellular networks: feasibility, performance and field trial,

G. Liuet al., “Cooperative sensing for 6G mobile cellular networks: feasibility, performance and field trial,”IEEE Journal on Selected Areas in Communications, vol. 42, no. 10, pp. 2863–2876, 2024

2024
[125]

Cooperative ISAC networks: Performance analysis, scaling laws and optimization,

Z. Honget al., “Cooperative ISAC networks: Performance analysis, scaling laws and optimization,”IEEE Transactions on Wireless Com- munications, vol. 24, no. 2, pp. 877–892, 2025

2025
[126]

Robustness of ISAC waveforms to power amplifier distortion,

A. R. Mohamed Ismailet al., “Robustness of ISAC waveforms to power amplifier distortion,” in2024 IEEE 4th International Symposium on Joint Communications & Sensing (JC&S), 2024, pp. 1–6

2024
[127]

A survey on hybrid beamforming techniques in 5g: Architecture and system model perspectives,

I. Ahmedet al., “A survey on hybrid beamforming techniques in 5g: Architecture and system model perspectives,”IEEE Communications Surveys & Tutorials, vol. 20, no. 4, pp. 3060–3097, 2018

2018
[128]

True Time Delay in Phased Arrays,

R. Rotmanet al., “True Time Delay in Phased Arrays,”Proc. IEEE, vol. 104, no. 3, pp. 504–518, 2016

2016
[129]

True-Time-Delay Beamforming With a Rotman- Lens for Ultrawideband Antenna Systems,

A. Lambrechtet al., “True-Time-Delay Beamforming With a Rotman- Lens for Ultrawideband Antenna Systems,”IEEE Trans. Antennas & Prop., vol. 58, no. 10, pp. 3189–3195, 2010

2010
[130]

Hardware aspects of sub-THz antennas and recon- figurable intelligent surfaces for 6G communications,

K. Rasilainenet al., “Hardware aspects of sub-THz antennas and recon- figurable intelligent surfaces for 6G communications,”IEEE Journal on Selected Areas in Communications, vol. 41, no. 8, pp. 2530–2546, 2023

2023
[131]

Chen,Handbook of Antenna Technologies, ser

Z. Chen,Handbook of Antenna Technologies, ser. Handbook of An- tenna Technologies. Springer Singapore, 2016

2016
[132]

Butler matrix based beamforming networks for phased array antenna systems: A comprehensive review and future directions for 5G applications,

A. K. Vallappilet al., “Butler matrix based beamforming networks for phased array antenna systems: A comprehensive review and future directions for 5G applications,”IEEE Access, vol. 9, pp. 3970–3987, 2021

2021
[133]

Analog beamforming based on Fourier Rotman lens for multibeam applications,

P. Turalchuket al., “Analog beamforming based on Fourier Rotman lens for multibeam applications,” in2018 48th European Microwave Conference (EuMC), 2018, pp. 1573–1576

2018
[134]

A review on the development of Rotman lens antenna,

S. Vashistet al., “A review on the development of Rotman lens antenna,”Chinese Journal of Engineering, vol. 2014, no. 1, p. 385385,

2014
[135]

Multibeam for joint communication and radar sensing using steerable analog antenna arrays,

J. A. Zhanget al., “Multibeam for joint communication and radar sensing using steerable analog antenna arrays,”IEEE Trans. Veh. Technol., vol. 68, no. 1, pp. 671–685, Jan. 2019. 45

2019
[136]

Multibeam design for joint communication and sensing in 5G new radio networks,

C. B. Barnetoet al., “Multibeam design for joint communication and sensing in 5G new radio networks,” inICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020, pp. 1–6

2020
[137]

Overview of generalized monopulse estimation,

U. Nickel, “Overview of generalized monopulse estimation,”IEEE Aerospace and Electronic Systems Magazine, vol. 21, no. 6, pp. 27–56, 2006

2006
[138]

Range compression and waveform optimization for MIMO radar: A Cram´er–Rao bound based study,

J. Liet al., “Range compression and waveform optimization for MIMO radar: A Cram´er–Rao bound based study,”IEEE Transactions on Signal Processing, vol. 56, no. 1, pp. 218–232, 2008

2008
[139]

Optimal spatial signal design for mmWave positioning under imperfect synchronization,

M. F. Keskinet al., “Optimal spatial signal design for mmWave positioning under imperfect synchronization,”IEEE Transactions on Vehicular Technology, vol. 71, no. 5, pp. 5558–5563, 2022

2022
[140]

Phased array architecture enabling scalable integrated sensing and communication,

K. E. Kolodziejet al., “Phased array architecture enabling scalable integrated sensing and communication,” inIEEE Radar Conference (RadarConf23), 2023

2023
[141]

Phased-array antenna beam squinting related to frequency dependency of delay circuits,

S. K. Garakouiet al., “Phased-array antenna beam squinting related to frequency dependency of delay circuits,” in2011 41st Eur. Microw. Conf., 2011, pp. 1304–1307

2011
[142]

Wideband Channel Estimation for mmWave Massive MIMO Systems with Beam Squint Effect,

B. Wanget al., “Wideband Channel Estimation for mmWave Massive MIMO Systems with Beam Squint Effect,” inIEEE Global Comm. Conf. (GLOBECOM), 2018, pp. 1–6

2018
[143]

Effect of wideband beam squint on codebook design in phased-array wireless systems,

M. Caiet al., “Effect of wideband beam squint on codebook design in phased-array wireless systems,” inIEEE Global Comm. Conf. (GLOBECOM), 2016, pp. 1–6

2016
[144]

Beam squint and channel estimation for wideband mmwave massive MIMO-OFDM systems,

B. Wanget al., “Beam squint and channel estimation for wideband mmwave massive MIMO-OFDM systems,”IEEE Trans. Signal Pro- cess., vol. 67, no. 23, pp. 5893–5908, 2019

2019
[145]

Fast Beam Training With True-Time-Delay Arrays in Wideband Millimeter-Wave Systems,

V . Boljanovicet al., “Fast Beam Training With True-Time-Delay Arrays in Wideband Millimeter-Wave Systems,”IEEE Trans. Circuits & Syst.I: Regular Papers, vol. 68, no. 4, pp. 1727–1739, 2021

2021
[146]

Joint Phase-Time Arrays: A Paradigm for Frequency-Dependent Analog Beamforming in 6G,

V . V . Ratnamet al., “Joint Phase-Time Arrays: A Paradigm for Frequency-Dependent Analog Beamforming in 6G,”IEEE Access, vol. 10, pp. 73 364–73 377, 2022

2022
[147]

Joint Millimeter-Wave AoD and AoA Estimation Using one OFDM Symbol and Frequency-Dependent Beams,

V . Boljanovicet al., “Joint Millimeter-Wave AoD and AoA Estimation Using one OFDM Symbol and Frequency-Dependent Beams,” inIEEE Int. Conf. Acoust., Speech & Signal Process. (ICASSP), 2023, pp. 1–5

2023
[148]

Structured Two-Stage True-Time-Delay Array Code book Design for Multi - User Data Communication,

A. Wadaskaret al., “Structured Two-Stage True-Time-Delay Array Code book Design for Multi - User Data Communication,” inIEEE Global Comm. Conf., 2023, pp. 3378–3384

2023
[149]

Design of Millimeter-Wave Single-Shot Beam Training for True-Time-Delay Array,

V . Boljanovicet al., “Design of Millimeter-Wave Single-Shot Beam Training for True-Time-Delay Array,” inIEEE Int. Workshop Signal Process. Adv. Wireless Comm. (SPAWC), 2020, pp. 1–5

2020
[150]

3D Rainbow Beam Design for Fast Beam Training with True-Time-Delay Arrays in Wideband Millimeter-Wave Systems,

A. Wadaskaret al., “3D Rainbow Beam Design for Fast Beam Training with True-Time-Delay Arrays in Wideband Millimeter-Wave Systems,” in2021 55th Asilomar Conf. Signals, Syst. & Comput., 2021, pp. 85– 92

2021
[151]

Multi-mode spatial signal processor with rainbow- like fast beam training and wideband communications using true-time- delay arrays,

C.-C. Linet al., “Multi-mode spatial signal processor with rainbow- like fast beam training and wideband communications using true-time- delay arrays,”IEEE Journal of Solid-State Circuits, vol. 57, no. 11, pp. 3348–3360, 2022

2022
[152]

Design and analysis of potential phased array config- urations for wideband near-field beamforming,

D. Delfiniet al., “Design and analysis of potential phased array config- urations for wideband near-field beamforming,” inIEEE International Symposium on Phased Array Systems and Technology (ARRAY), 2024, pp. 1–6

2024
[153]

THz prism: One-shot simultaneous localization of multiple wireless nodes with leaky-wave THz antennas and transceivers in cmos,

H. Saeidiet al., “THz prism: One-shot simultaneous localization of multiple wireless nodes with leaky-wave THz antennas and transceivers in cmos,”IEEE Journal of Solid-State Circuits, vol. 56, no. 12, pp. 3840–3854, 2021

2021
[154]

Chip-to-Chip Interfaces for Large-Scale Highly Config- urable mmWave Phased Arrays,

A. Sethiet al., “Chip-to-Chip Interfaces for Large-Scale Highly Config- urable mmWave Phased Arrays,”IEEE J. Solid-State Circuits, vol. 58, no. 7, pp. 1987–2004, 2023

1987
[155]

Impact of the Asymmetric Signal Routing on the Wideband Spatial Behavior of Large Modular Phased Arrays,

D. Delfiniet al., “Impact of the Asymmetric Signal Routing on the Wideband Spatial Behavior of Large Modular Phased Arrays,” in2023 17th Eur. Conf. Antennas & Propag. (EuCAP), 2023, pp. 1–5

2023
[156]

Tapering Impact on the Spatial and Frequency Responses of Broadband Asymmetrically Routed Phased Arrays,

D. Delfiniet al., “Tapering Impact on the Spatial and Frequency Responses of Broadband Asymmetrically Routed Phased Arrays,” in 2024 18th Eur. Conf. Antennas & Propag. (EuCAP), 2024, pp. 1–5

2024
[157]

M. A. Richards,Fundamentals of Radar Signal Processing, 2nd ed. McGraw-Hill Education, 2014

2014
[158]

In-band full-duplex radar-communication sys- tem,

S. A. Hassaniet al., “In-band full-duplex radar-communication sys- tem,”IEEE Systems Journal, vol. 15, no. 1, pp. 1086–1097, 2021

2021
[159]

Analog/RF solutions enabling compact full-duplex radios,

B. Debaillieet al., “Analog/RF solutions enabling compact full-duplex radios,”IEEE Journal on Selected Areas in Communications, vol. 32, no. 9, pp. 1662–1673, 2014

2014
[160]

Full duplex radios,

D. Bharadiaet al., “Full duplex radios,”SIGCOMM Comput. Commun. Rev., vol. 43, no. 4, p. 375–386, Aug. 2013. [Online]. Available: https://doi.org/10.1145/2534169.2486033

2013
[161]

Towards circulator-free multi antenna transmitters for 5G,

A. Prataet al., “Towards circulator-free multi antenna transmitters for 5G,” in2017 IEEE MTT-S International Microwave Symposium (IMS), 2017, pp. 677–680

2017
[162]

Joint Tx-Rx beamforming for optimal gain and self- interference mitigation in in-band full-duplex arrays: Theory, figures of merit, and validation,

M. Ayebeet al., “Joint Tx-Rx beamforming for optimal gain and self- interference mitigation in in-band full-duplex arrays: Theory, figures of merit, and validation,”IEEE Antennas and Wireless Propagation Letters, pp. 1–5, 2025

2025
[163]

Subband full-duplex large-scale deployed network designs and tradeoffs,

M. Abdelghaffaret al., “Subband full-duplex large-scale deployed network designs and tradeoffs,”Proceedings of the IEEE, vol. 112, no. 5, pp. 487–510, 2024

2024
[164]

Waveforms for the massive MIMO downlink: Amplifier efficiency, distortion, and performance,

C. Moll ´enet al., “Waveforms for the massive MIMO downlink: Amplifier efficiency, distortion, and performance,”IEEE Transactions on Communications, vol. 64, no. 12, pp. 5050–5063, 2016

2016
[165]

Horlinet al.,Digital Compensation for Analog Front-Ends: A New Approach to Wireless Transceiver Design

F. Horlinet al.,Digital Compensation for Analog Front-Ends: A New Approach to Wireless Transceiver Design. Wiley, 05 2008

2008
[166]

PAPR reduction in single carrier modulation at sub-Thz band,

A. R. M. Ismailet al., “PAPR reduction in single carrier modulation at sub-Thz band,” inGLOBECOM 2024 - 2024 IEEE Global Commu- nications Conference, 2024, pp. 1563–1568

2024
[167]

PAPR reduction in single carrier modulation with hybrid beamforming,

A. R. M. Ismailet al., “PAPR reduction in single carrier modulation with hybrid beamforming,” in2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), 2025

2025
[168]

Phase-noise compensation for OFDM systems exploiting coherence bandwidth: Modeling, algorithms, and analysis,

M. Chunget al., “Phase-noise compensation for OFDM systems exploiting coherence bandwidth: Modeling, algorithms, and analysis,” IEEE Transactions on Wireless Communications, vol. 21, no. 5, pp. 3040–3056, 2022

2022
[169]

Dahlmanet al.,5G NR: The next generation wireless access technology

E. Dahlmanet al.,5G NR: The next generation wireless access technology. Academic Press, 2020

2020
[171]

Range correlation effects in radars,

M. C. Budgeet al., “Range correlation effects in radars,” inThe Record of the 1993 IEEE National Radar Conference, April 1993, pp. 212– 216

1993
[172]

On the safe road toward autonomous driving: Phase noise monitoring in radar sensors for functional safety compli- ance,

M. Gerstmairet al., “On the safe road toward autonomous driving: Phase noise monitoring in radar sensors for functional safety compli- ance,”IEEE Signal Processing Magazine, vol. 36, no. 5, pp. 60–70, 2019

2019
[173]

Uplink cell-free massive MIMO OFDM with phase noise-aware channel estimation: Separate and shared LOs,

Y . Wuet al., “Uplink cell-free massive MIMO OFDM with phase noise-aware channel estimation: Separate and shared LOs,”arXiv preprint arXiv:2410.18722, 2024

2024 arXiv
[174]

Physical-environment-map-aided 3-D deployment opti- mization for UA V-assisted integrated localization and communication in urban areas,

S. Biet al., “Physical-environment-map-aided 3-D deployment opti- mization for UA V-assisted integrated localization and communication in urban areas,”IEEE Internet of Things Journal, vol. 11, no. 9, pp. 15 490–15 503, 2024

2024
[175]

Machine learning for coverage optimization in wireless sensor networks: a comprehensive review,

O. S. Egwucheet al., “Machine learning for coverage optimization in wireless sensor networks: a comprehensive review,”Annals of Operations Research, pp. 1–67, 2023

2023
[176]

Fluid antenna-assisted ISAC systems,

L. Zhouet al., “Fluid antenna-assisted ISAC systems,”IEEE Wireless Communications Letters, vol. 13, no. 12, pp. 3533–3537, 2024. 46

2024
[177]

Joint discrete antenna positioning and beamforming optimization in movable antenna enabled full-duplex ISAC networks,

Z. Liet al., “Joint discrete antenna positioning and beamforming optimization in movable antenna enabled full-duplex ISAC networks,” arXiv preprint arXiv:2411.04419, 2024

2024
[178]

Joint maneuver and beamforming design for UA V- enabled integrated sensing and communication,

Z. Lyuet al., “Joint maneuver and beamforming design for UA V- enabled integrated sensing and communication,”IEEE Transactions on Wireless Communications, vol. 22, no. 4, pp. 2424–2440, 2022

2022
[179]

Experimental validation of single BS 5G mmwave positioning and mapping for intelligent transport,

Y . Geet al., “Experimental validation of single BS 5G mmwave positioning and mapping for intelligent transport,”IEEE Transactions on Vehicular Technology, vol. 73, no. 11, pp. 16 744–16 757, 2024

2024
[180]

Jrcup: Joint RIS calibration and user positioning for 6G wireless systems,

P. Zhenget al., “Jrcup: Joint RIS calibration and user positioning for 6G wireless systems,”IEEE Transactions on Wireless Communications, vol. 23, no. 6, pp. 6683–6698, 2024

2024
[181]

Misspecified Cram ´er-Rao bound of RIS-aided lo- calization under geometry mismatch,

P. Zhenget al., “Misspecified Cram ´er-Rao bound of RIS-aided lo- calization under geometry mismatch,” inICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023, pp. 1–5

2023
[182]

RIS-aided localization under pixel failures,

C. Ozturket al., “RIS-aided localization under pixel failures,”IEEE Transactions on Wireless Communications, vol. 23, no. 8, pp. 8314– 8329, 2024

2024
[183]

Monostatic sensing with OFDM under phase noise: From mitigation to exploitation,

M. F. Keskinet al., “Monostatic sensing with OFDM under phase noise: From mitigation to exploitation,”IEEE Transactions on Signal Processing, vol. 71, pp. 1363–1378, 2023

2023
[184]

Simultaneous localization and calibration for cooperative radio navigation,

R. P ¨ohlmannet al., “Simultaneous localization and calibration for cooperative radio navigation,”IEEE Transactions on Wireless Com- munications, vol. 21, no. 8, pp. 6195–6210, 2022

2022
[185]

Model-based end-to-end learning for multi-target integrated sensing and communication under hardware impairments,

J. M. Mateos-Ramoset al., “Model-based end-to-end learning for multi-target integrated sensing and communication under hardware impairments,”IEEE Transactions on Wireless Communications, vol. 24, no. 3, pp. 2574–2589, 2025

2025
[186]

ISAC prototype system for multi-domain cooperative communication networks,

J. Yanget al., “ ISAC prototype system for multi-domain cooperative communication networks,”IEEE Wireless Com. Lett., vol. 14, no. 1, pp. 108–112, Nov. 2025

2025
[187]

mmWave joint communication and sensing (JCAS/ ISAC) testbed,

TMYTEK, “mmWave joint communication and sensing (JCAS/ ISAC) testbed,”Tech. Rep., Jul. 2023

2023
[188]

Radar-assisted predictive beamforming for vehicular links: Communication served by sensing,

F. Liuet al., “Radar-assisted predictive beamforming for vehicular links: Communication served by sensing,”IEEE Trans. Wireless Com- mun., vol. 19, no. 11, pp. 7704–7719, Nov. 2020

2020
[189]

Integrating sensing and communications for ubiquitous IoT: Applications, trends and challenges,

Y . Cuiet al., “Integrating sensing and communications for ubiquitous IoT: Applications, trends and challenges,”IEEE Netw., vol. 35, no. 5, pp. 158–167, Oct. 2021

2021
[190]

Channel measurements and modeling for joint/integrated communication and sensing,

N. G. Alliance, “Channel measurements and modeling for joint/integrated communication and sensing,”Next G Alliance Rep., Jul. 2024

2024
[191]

Networking-based ISAC hardware testbed and perfor- mance evaluation,

K. Jiet al., “Networking-based ISAC hardware testbed and perfor- mance evaluation,”IEEE Commun. Mag., vol. 61, no. 2, pp. 102–108, Feb. 2023

2023
[192]

Distributed MIMO measurements for integrated communication and sensing in an industrial environment,

C. Nelsonet al., “Distributed MIMO measurements for integrated communication and sensing in an industrial environment,”Sensors, vol. 24, no. 5, p. 1385, 2024

2024
[193]

S. Faghih-Nainiet al., “Hardware design challenges and modulation schemes in joint communication and sensing: Analyzation and com- parison of the state-of-the-art co-located communication and sensing systems,”IEEE Microw. Mag., vol. 25, no. 3, pp. 84–97, Mar. 2024

2024
[194]

A shared cluster-based stochastic channel model for integrated sensing and communication systems,

Y . Liuet al., “A shared cluster-based stochastic channel model for integrated sensing and communication systems,”IEEE Trans. Veh. Tech., vol. 73, no. 5, pp. 6032–6044, May 2024

2024
[195]

A flexible millimeter-wave channel sounder with absolute timing,

G. R. MacCartneyet al., “A flexible millimeter-wave channel sounder with absolute timing,”IEEE J. Sel. Areas Commun., vol. 35, no. 6, pp. 1402–1418, Jun. 2017

2017
[196]

Deliverable D3.3 Initial analysis of architectureal en- ablers and framework,

Hexa-X-II, “Deliverable D3.3 Initial analysis of architectureal en- ablers and framework,” https://hexa-x-ii.eu/wp-content/uploads/2024/ 04/Hexa-X-II D3.3 v1.0.pdf, 2024, [Accessed 09-04-2025]

2024
[197]

Service enabler architecture layer for verticals (seal); functional architecture and information flows,

3GPP, “Service enabler architecture layer for verticals (seal); functional architecture and information flows,” 3GPP TS23.434, V19.3.0, Tech. Rep., September 2024

2024
[198]

Common API framework for 3GPP northbound APIs,

3GPP, “Common API framework for 3GPP northbound APIs,” 3GPP TS23.222, V19.3.0, Tech. Rep., September 2024

2024
[199]

Addressing privacy concerns in joint communication and sensing for 6G networks: challenges and prospects,

P. Dasset al., “Addressing privacy concerns in joint communication and sensing for 6G networks: challenges and prospects,” inAnnual Privacy Forum. Springer, 2024, pp. 87–111

2024
[200]

Howard,The security development lifecycle

M. Howard,The security development lifecycle. Microsoft Press, 2006

2006
[201]

A privacy threat analysis framework: supporting the elicitation and fulfillment of privacy requirements,

M. Denget al., “A privacy threat analysis framework: supporting the elicitation and fulfillment of privacy requirements,”Requirements Engineering, vol. 16, no. 1, pp. 3–32, 2011

2011
[202]

Secure integrated sensing and communications (S-ISAC) network,

T. Guoet al., “Secure integrated sensing and communications (S-ISAC) network,” inIEEE Vehicular Technology Conference (VTC2024-Fall). IEEE, 2024, pp. 1–6

2024
[203]

Privacy and security in ubiquitous integrated sensing and communication: Threats, challenges and future directions,

K. Quet al., “Privacy and security in ubiquitous integrated sensing and communication: Threats, challenges and future directions,”IEEE Internet of Things Magazine, vol. 7, no. 4, pp. 52–58, 2024

2024
[204]

Indoor monitoring human movements using dual-receiver radar,

B. Liuet al., “Indoor monitoring human movements using dual-receiver radar,” inIEEE Radar Conference (RadarConf). IEEE, 2017, pp. 0520–0523

2017
[205]

A survey of security threats on 4G networks,

Y . Parket al., “A survey of security threats on 4G networks,” inIEEE Globecom workshops. IEEE, 2007, pp. 1–6

2007
[206]

Security assurance specification (scas) threats and critical assets in 3GPP network product classes (3GPP TR 33.926 version 18.4.0 Release 18),

3GPP, “Security assurance specification (scas) threats and critical assets in 3GPP network product classes (3GPP TR 33.926 version 18.4.0 Release 18),” 3GPP, Tech. Rep. TR 33.926, 2024

2024
[207]

Mobile device security,

NIST, “Mobile device security,”NIST SPECIAL PUBLICATION, no. NIST 1800-22, p. 22A, 2023

2023
[208]

Security architecture and procedures for 5G system 3GPP TS 33.501 version 18.8.0 Release 18,

3GPP, “Security architecture and procedures for 5G system 3GPP TS 33.501 version 18.8.0 Release 18,” 3GPP, Tech. Rep. TR 33.501, 2025

2025
[209]

End-to-end system evaluation results from the interim overall 6G system,

M. Raulet al., “End-to-end system evaluation results from the interim overall 6G system,” Hexa-X-II project Deliverable D2.4, 2024. [Online]. Available: https://hexa-x-ii.eu/deliverables/

2024
[210]

Trusted execution environments: properties, appli- cations, and challenges,

P. Jauerniget al., “Trusted execution environments: properties, appli- cations, and challenges,”IEEE Security & Privacy, vol. 18, no. 2, pp. 56–60, 2020

2020
[211]

Radar: Residual analysis for anomaly detection in attributed networks

J. Liet al., “Radar: Residual analysis for anomaly detection in attributed networks.” inIJCAI, vol. 17, 2017, pp. 2152–2158

2017
[212]

Anomaly detection in radar data using pointnets,

T. Griebelet al., “Anomaly detection in radar data using pointnets,” inIEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021, pp. 2667–2673

2021
[213]

Context-aware security for 6G wireless: The role of physical layer security,

A. Chortiet al., “Context-aware security for 6G wireless: The role of physical layer security,”IEEE Communications Standards Magazine, vol. 6, no. 1, pp. 102–108, 2022

2022
[214]

Enhancing frequency hopping security in ISAC systems: A physical layer security approach,

A. K. Boroujeniet al., “Enhancing frequency hopping security in ISAC systems: A physical layer security approach,” inIEEE International Symposium on Joint Communications & Sensing (JC&S), 2024, pp. 1–6

2024
[215]

RF hardware reconfigurability for privacy-preserving integrated sensing and communication,

P. Senet al., “RF hardware reconfigurability for privacy-preserving integrated sensing and communication,” inIEEE International Sympo- sium on Joint Communications & Sensing (JC&S), 2025, pp. 1–6

2025
[216]

A methodology for the pseudonymization of medical data,

T. Neubaueret al., “A methodology for the pseudonymization of medical data,”International journal of medical informatics, vol. 80, no. 3, pp. 190–204, 2011

2011
[217]

5G suci-catchers: Still catching them all?

M. Chlostaet al., “5G suci-catchers: Still catching them all?” in Proceedings of the 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks, 2021, pp. 359–364

2021
[218]

Service requirements for integrated sensing and communication (3GPP TS 22.137 version 19.0.0 Release 19),

3GPP, “Service requirements for integrated sensing and communication (3GPP TS 22.137 version 19.0.0 Release 19),” 3GPP, Tech. Rep. TS 22.137, 2024

2024
[219]

S. M. Kay,Fundamentals of statistical signal processing: estimation theory. Prentice-Hall, Inc., 1993. 47

1993
[220]

V . Koivunenet al., “Multicarrier ISAC: Advances in waveform design, signal processing, and learning under nonidealities [special issue on signal processing for the integrated sensing and communications revo- lution],”IEEE Signal Processing Magazine, vol. 41, no. 5, pp. 17–30, 2024

2024
[221]

M. A. Richards,Fundamentals of Radar Signal Processing. Tata McGraw-Hill Education, 2005

2005
[222]

Positioning and sensing in 6G: Gaps, challenges, and opportunities,

A. Behravanet al., “Positioning and sensing in 6G: Gaps, challenges, and opportunities,”IEEE Vehicular Technology Magazine, vol. 18, no. 1, pp. 40–48, 2022

2022
[223]

Deep 3D human pose estimation: A review,

J. Wanget al., “Deep 3D human pose estimation: A review,”Computer Vision and Image Understanding, vol. 210, p. 103225, 2021

2021
[224]

Real-time human gesture grading based on openpose,

S. Qiaoet al., “Real-time human gesture grading based on openpose,” in2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2017, pp. 1–6

2017
[225]

Human pose estimation using mediapipe pose and optimization method based on a humanoid model,

J.-W. Kimet al., “Human pose estimation using mediapipe pose and optimization method based on a humanoid model,”Applied sciences, vol. 13, no. 4, p. 2700, 2023

2023
[226]

Going deeper with convolutions,

C. Szegedyet al., “Going deeper with convolutions,” inProceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 1–9

2015
[227]

5G new radio: Unveiling the essentials of the next gen- eration wireless access technology,

X. Linet al., “5G new radio: Unveiling the essentials of the next gen- eration wireless access technology,”IEEE Communications Standards Magazine, vol. 3, no. 3, pp. 30–37, 2019

2019
[2014]

Available: https://onlinelibrary.wiley.com/doi/abs/10

[Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10. 1155/2014/385385

2014

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.

[1] [1]

Early results of 6G radio key enablers,

A. Nimret al., “Early results of 6G radio key enablers,” Hexa-X-II project Deliverable D4.3, 2024. [Online]. Available: https://hexa-x-ii.eu/deliverables/

2024

[2] [2]

Integrated sensing and communications: Toward dual- functional wireless networks for 6G and beyond,

F. Liuet al., “Integrated sensing and communications: Toward dual- functional wireless networks for 6G and beyond,”IEEE Journal on Selected Areas in Communications, vol. 40, no. 6, pp. 1728–1767, 2022

2022

[3] [3]

The integrated sensing and communication revolution for 6G: Vision, techniques, and applications,

N. Gonz ´alez-Prelcicet al., “The integrated sensing and communication revolution for 6G: Vision, techniques, and applications,”Proceedings of the IEEE, vol. 112, no. 7, pp. 676–723, July 2024

2024

[4] [4]

Cmwave and sub-THz: Key radio enablers and complementary spectrum for 6G,

M. V . Katweet al., “Cmwave and sub-THz: Key radio enablers and complementary spectrum for 6G,”arXiv preprint arXiv:2406.18391, 2024

arXiv 2024

[5] [5]

NTN-based 6G localization: Vision, role of leos, and open problems,

H. K. Dureppagariet al., “NTN-based 6G localization: Vision, role of leos, and open problems,”IEEE Wireless Communications, vol. 30, no. 6, pp. 44–51, 2023

2023

[6] [6]

Integrated sensing and communication with mmwave massive MIMO: A compressed sampling perspective,

Z. Gaoet al., “Integrated sensing and communication with mmwave massive MIMO: A compressed sampling perspective,”IEEE Trans- actions on Wireless Communications, vol. 22, no. 3, pp. 1745–1762, 2022

2022

[7] [7]

Integrated communication, localization, and sensing in 6G D-MIMO networks,

H. Guoet al., “Integrated communication, localization, and sensing in 6G D-MIMO networks,”IEEE Wireless Communication Magazine, vol. 32, no. 2, pp. 214–221, 2025

2025

[8] [8]

Integrated sensing and communication for 6G: Ten key machine learning roles,

U. Demirhanet al., “Integrated sensing and communication for 6G: Ten key machine learning roles,”IEEE Communications Magazine, vol. 61, no. 5, pp. 113–119, 2023

2023