Industrial Viewpoints on RAN Technologies for 6G

Antti Toskala; Dorin Panaitopol; Erik G. Larsson; Flavien Ronteix-Jacquet; Mansoor Shafi; Stefan Parkvall; Xingqin Lin

REVIEW 2 major objections 6 minor 1 cited by

Industrial Viewpoints on RAN Technologies for 6G

T0 review · 2 major / 6 minor · reviewed 2026-08-05 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read The authors predict that 6G's first release will be a 5G-evolved, OFDM-based, AI-augmented RAN with native satellite support, delivered on an early-2029 timeline, and that 6G spectrum will be mid-band rather than sub-THz.

desk verdict Sharp industry roadmap for 6G RAN; the load-bearing traffic claim needs a methodology. read the letter →

arxiv 2508.08225 v1 pith:CTUFHG4T submitted 2025-08-11 cs.NI cs.ITeess.SPmath.IT

Mansoor Shafi , Erik G. Larsson , Xingqin Lin , Dorin Panaitopol , Stefan Parkvall , Flavien Ronteix-Jacquet , Antti Toskala This is my paper

classification cs.NIcs.ITeess.SPmath.IT

keywords 6GRANmassiveMIMOAI-nativeairinterfacenon-terrestrialnetworksmid-bandspectrumOFDMevolutionCSIfeedbackenergyefficiency

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

Writing from inside the standardization process, the authors try to establish what the first 6G radio access network will actually be, as opposed to what academic vision papers imagine. They argue that 6G's first release will be an evolution of 5G: a standalone OFDM-based system that keeps 5G's waveform and adds AI, bigger MIMO arrays, better CSI feedback, and native satellite integration. They predict the preferred spectrum will be mid-bands, not sub-THz, and that 6G KPIs should aim to realize 5G's aspirational targets with bandwidth scaling rather than invent new numbers. If the predictions are right, industry effort will concentrate on MIMO evolution, AI for the air interface, energy savings, and terrestrial–non-terrestrial integration, while deprioritizing sub-THz, new waveforms, RSMA, and reconfigurable intelligent surfaces.

What carries the argument

The load-bearing mechanism is the coherence-block model of massive MIMO, summarized in the paper's sum-rate formula for a single cell with zero-forcing and max-min fairness: the number of terminals worth multiplexing is set by $B_c T_c$, pilot overhead is $1 - K/(B_c T_c)$, and array gain scales as $M-K$. Together with TDD reciprocity, this makes CSI acquisition independent of base-station antenna count and fixes the practical direction of 6G MIMO: more elements, better codebooks, and reciprocity-based operation. The second mechanism is the measured traffic imbalance—96% of sessions are small and 1% of sessions carry 74% of data—which the authors use to argue that 6G's control-plane and sche

What would settle it

One concrete check is to take the claimed traffic distribution and simulate a 6G RAN under an alternative session-size distribution dominated by XR and AI-agent flows (larger sessions, continuous uplink), measuring whether fast setup and early CSI still dominate the performance outcome; if not, the design emphasis is mis-calibrated. A second check: a field trial showing a sub-THz wide-area cell achieving cell-edge reliability and cost comparable to mid-band would falsify the paper's exclusion of sub-THz from first-release 6G.

Watch

Extended reading notes

Core claim

The paper's central claim is that the first 6G release, with complete specifications expected by early 2029, will be a 5G-evolved, standalone-architecture RAN built on OFDM and massive MIMO, augmented by AI/ML and designed from the start for non-terrestrial networks. The authors argue from deployment experience that mid-bands are the preferred spectrum, that sub-THz is not part of the first release because current mmWave experience shows high bands are unsuitable for wide-area coverage, and that 6G should not chase new KPI numbers but realize the 5G aspirational KPIs with bandwidth-appropriate scaling. They support this with measured traffic statistics showing that most sessions are small an

Load-bearing premise

The load-bearing premise is that traffic measurements from one European commercial network—where 96% of sessions are small and 1% of sessions carry 74% of the data—represent the global traffic profile 6G must be designed for, and that today's mmWave experience proves sub-THz cannot work for wide-area cellular.

Editorial extensions

If this is right

6G investment will concentrate on evolving massive MIMO—more antenna elements, 256 to 512 CSI ports, better codebooks, early CSI—rather than on a new physical layer.
AI/ML enters the 6G air interface in concrete forms: CSI compression and prediction, beam management, positioning, and neural receivers, with offline training expected initially.
Non-terrestrial networks (satellites and high-altitude platforms) will be native to 6G, harmonized with the terrestrial interface, enabling global coverage and resilience rather than an afterthought.
New waveforms, RSMA, reconfigurable intelligent surfaces, and sub-THz operation are unlikely to be in the first 6G release; OFDM remains the baseline and any new candidate must be backwards-compatible and evaluated against 5G solutions.
Energy efficiency will shape 6G radio design—ultra-lean signals, deep sleep, deactivating transmit chains—and KPI design will emphasize realized rather than aspirational rates.

Reading between the lines

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

The paper's traffic argument implies a testable prediction: if 6G's own uplink-heavy use cases (AI agents, XR, sensing) shift the session-size distribution toward larger, longer flows, then the emphasis on rapid setup and early CSI will matter less than uplink power and coverage enhancements; this could be checked against early 6G trial traffic once deployed.
If the mid-band spectrum decision holds, the economics of MIMO hardware—power amplifier efficiency, cooling, antenna form factor at 7 GHz—become the binding constraints on 6G performance, a direction the paper partially quantifies but leaves for detailed RF engineering.
The argument that mmWave experience rules out sub-THz wide-area 6G is an extrapolation; a targeted falsifier would be a demonstration that sub-THz backhaul or hotspot deployments reach comparable reliability and cost per area, which would weaken the claim that first-release 6G can safely ignore those bands.
The KPI stance—'realize 5G aspirational KPIs with appropriate bandwidth scaling'—implies that the industry will resist order-of-magnitude KPI jumps, and that marketing expectations for 6G should be reset; that is likely to be contested by vendors and regulators.

Share X Bluesky LinkedIn Reddit HN

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

Let me give you the short version: this is an industry position paper that is better than most of its genre. The authors are key 3GPP players, and they tell you what they expect Release 20/21 to deliver: mid-band massive MIMO, an AI-augmented air interface, OFDM baseline, native NTN, no sub-THz, no RSMA, no RIS. The paper's value is not in new derivations but in the specificity of the roadmap and a few original calculations.

What is genuinely new: Fig 13 shows the energy cost of SSB periodicity using the 3GPP power model, and it is a concrete, reproducible parameterization; Tables VIII and IX give NTN link budgets with stated assumptions; Table III consolidates MIMO configurations in a way I have not seen elsewhere. The CSI compression and positioning plots are compiled from 3GPP studies, but the authors frame them comparatively, which is useful. The survey content is accurate and well-sourced.

The soft spot is Fig 3. That session-size distribution from 'a European network' has no collection methodology, no sample size, no operator, no time window. The text asserts it is 'very similar across time, technologies, geographic area, and operators' without evidence. That single distribution underpins the paper's emphasis on rapid setup, early CSI, and lean signaling. The paper itself predicts 6G use cases like XR, AI agents, and sensing, whose sessions are likely larger and more continuous than the eMBB web traffic in Fig 3. If that traffic shift happens, the design emphasis is miscalibrated. The core stack survives, but the investment-priority argument would not.

Also worth noting: the negative calls on sub-THz, RSMA, and RIS align with the authors' companies' 3GPP workshop positions. That is a viewpoint base to keep in mind, not a disqualifier. The self-citations in load-bearing spots are normal literature base.

Who is this for: researchers and engineers who want a grounded, standards-aware view of where 6G is heading, and who can treat the predictions as conditional. It deserves a serious referee. I would send it out, with a request to broaden the traffic evidence, add sensitivity analysis to the parameterized figures, and soften the strongest predictions. The paper holds up as a roadmap; it just needs to own its weaknesses.

Referee Report

2 major / 6 minor

Summary. The manuscript is an industrial viewpoint article on the radio access network (RAN) technologies expected in the first 6G release. It argues, on the basis of 3GPP Release 20/21 study/work item plans, WRC-23 band decisions, and lessons from commercial 5G, that the first 6G system will be a 5G-evolved, standalone, OFDM-based RAN with massive MIMO evolution, AI/ML at the air interface and RAN management, native NTN integration, and mid-band spectrum as the primary new deployment band. It reviews KPI requirements, architecture and spectrum sharing, and evaluates candidate technologies (new waveforms, RSMA, OTFS, new constellations, coding, RIS, SBFD) with a deployment cost/benefit lens, concluding that most 'disruptive' physical-layer candidates are unlikely to enter the initial 6G specification. The authors state explicitly in the abstract that the predictions are speculative because 3GPP study results are not yet available.

Significance. If the predictions are correct, the paper is a valuable consolidation of an industrial view of 6G RAN, with a particularly useful emphasis on implementation and deployment constraints that are often absent from academic 6G visions. Strengths include the honest disclosure in the abstract that the predictions are speculative; grounding in verifiable standards/regulatory artifacts (3GPP SID RP-251881, WRC-23, ITU-R reports); and several parameterized quantitative examples that are reproducible in principle, notably the energy-versus-SSB-periodicity calculation using the 3GPP TR 38.864 power model and the NTN link-budget tables whose assumptions are stated. The main limitation is evidential: the investment-priority argument rests partly on a single set of traffic measurements presented with no methodology, and the sub-THz dismissal rests on a prior deployment report. These are not internally inconsistent, but they make the falsifiability of some central claims weaker than it should be.

major comments (2)

[Section III, Fig. 3, and Section VI-D] The traffic characterization is load-bearing for the paper's design priorities: 'most sessions (96%) are small and a few sessions (1%) carry most of the data (74%). This traffic behavior needs to be accounted for in the design of 6G' (Section III), and Section VI-D uses the same bursty-traffic assumption to motivate fast setup, early CSI, and fast uplink-downlink decoupling. The caption provides no collection methodology, operator, time window, network generation, service mix, or sample size, yet asserts the pattern is 'very similar across time, technologies, geographic area, and operators.' This is a single European network measurement generalized to a global 6G principle. Since the paper itself predicts that 6G will be shaped by XR, AI agents, sensing, and uplink-heavy flows (Sections II and VI-D), those use cases may produce larger and more continuous sessions that shift the distribut
[Section IV] The statement 'Regardless of WRC approvals, the current experience with mmWave shows that higher frequency bands (and therefore sub-THz) bands are not suitable for wide-area cellular deployments [17]' is categorical. The cited support, [17], is a prior paper co-authored by one of the present authors, but the manuscript gives no details of its measurement conditions, deployment scenarios, or how those results extrapolate across bands (e.g., 28 GHz versus 140 GHz). The paper's core prediction that sub-THz will not be part of the first 6G release is independently supported by the WRC-27 agenda, so the categorical deployment claim is not needed for the central timeline. Please reformulate the mmWave/sub-THz discussion as a deployment-cost and coverage tradeoff with explicit conditions, and treat the WRC-based reason as the primary evidence.

minor comments (6)

[Various] There are several typographical errors: 'wholistic' (Section V-A), 'psuedo-inverse' (repeated), 'interfases' (Section V-D), 'Geostationnary' (Section VI-F), and 'bu' (Section VI-E).
[Fig. 13] The energy-consumption figure has no axis labels and no visible legend; the caption says different colors correspond to different base-station parts, but the reader cannot map colors to components. Please add axis labels and a legend, or describe the curves in the caption.
[Table III] The last row, 'gNB antenna elements', is visually ambiguous: '16-128 1024-4096' appears to merge the '5G spec./5G depl.' and '6G' columns. Split the entries and clarify which values refer to the 5G specification, 5G deployment, and 6G.
[Section VI-E] The citation [202] is used to support a claim about receiver RFE power consumption in terminals, but the reference title is 'Fundamental limits of cooperation' (Lozano et al., 2013), which appears unrelated. Please verify and replace with the intended source.
[Table VIII] The table caption says '8% active beams' but does not define whether 8% of beams are active or whether this is an activity factor. Please define this parameter.
[General] The abstract appropriately labels the predictions as speculative, but the body sometimes uses categorical language (e.g., Section IV 'will primarily be deployed in mid-bands'; Section III 'the preferred spectrum for 6G is in mid-bands'). Harmonize the hedging so that the distinction between prediction, preference, and fact is clear.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: predictions are explicitly speculative and anchored to external 3GPP/ITU inputs; self-citations are supporting evidence, not load-bearing reductions.

full rationale

This paper is an industrial position/review rather than a derivation chain. The abstract itself flags: 'Our predictions in this paper are speculative as there are no results of the study yet,' so no fitted parameter is disguised as a prediction. The traffic characterization in Section III/Fig. 3 is an empirical input used to motivate lean signaling, fast setup, and early CSI; it is not the output of the paper's design arguments. The unsupported generalization in the Fig. 3 caption ('the general behavior is very similar across time, technologies, geographic area, and operators') and the missing collection methodology are evidence-quality concerns, not circularity. Equation (1) is a textbook massive-MIMO rate bound taken from [66] (co-authored by Larsson); it is parameter-free with stated assumptions (independent Rayleigh fading, single cell, ZF, max-min fairness) and is used as background to explain why MIMO remains central, not to generate the 6G conclusions. The sub-THz skepticism cites [17] (first author Shafi) as real-world mmWave deployment experience; that is an externally published, falsifiable empirical result rather than an assumption of the present argument. Other self-citations ([9], [44], [137]) support specific technical statements but are not load-bearing uniqueness claims. The concrete 6G positions (OFDM baseline, SA architecture, mid-band preference, AI, NTN) are anchored to 3GPP work items ([27], [28]), ITU-R decisions ([14]), and backward-compatibility considerations, so they do not reduce to the paper's own definitions. No step exhibits a conclusion equivalent by construction to an input.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

This is a survey, so the ledger holds no fitted parameters for a derivation; what it holds are hand-picked system parameters for illustrative calculations and domain assumptions about how 6G standardization will evolve. The paper introduces no new entities: RSMA, OTFS, D-MIMO, NCR, ISAC, and RIS are all taken from prior literature. The most consequential entries are the assumptions that current mmWave deployment experience extrapolates to sub-THz, that one European network's traffic profile generalizes globally, and that the 3GPP Release 20/21 timeline and study scope hold.

free parameters (3)

C-band NTN link budget parameters = UE gain -2 dBi, Rx NF 7/5.5 dB, sat gain 33.4-35.8 dBi, NF 2 dB, 34 dBW/MHz/beam
Hand-set design targets in Table VIII that produce the SINR and throughput numbers in Table IX; the headline DL SINR of 10.15 dB and DL peak rate of 32.18 Mbps inherit these choices. No sensitivity analysis is provided.
MRSS capacity loss target = <5%
Section V-B states the goal that sharing 5G and 6G carriers costs less than 5% capacity, assuming 6G overhead matches 5G. This assumed target is used to argue MRSS is clearly attractive; it is a design goal, not a measured quantity.
SSB periodicity energy model inputs = 20 ms vs 160 ms SSB periodicity
Fig 13 computes base station power from the 3GPP TR 38.864 model; the claimed 77% reduction relies on unshown component power values and deep-sleep state assumptions for the radio.

assumptions (5)

domain assumption Experience with mmWave in 5G proves that sub-THz bands are unsuitable for wide-area 6G deployment
Sections I and IV: 'the current experience with mmWave shows that higher frequency bands (and therefore sub-THz) bands are not suitable for wide-area cellular deployments', supported by self-cited [17]. The paper's mid-band-centric prediction rests on this extrapolation.
domain assumption The traffic profile of one European commercial network (Fig 3) is representative of global 6G traffic
Section III: 96% of sessions small, 1% carrying 74% of traffic; generalized into a 6G design driver for bursty-traffic handling without multi-network data.
domain assumption The 3GPP Release 20/21 timeline and RP-251881 study scope will hold as described
Section I and Fig 2: the architecture, MRSS, and waveform discussions all assume 6G study items start in fall 2025 and complete specifications by early 2029.
standard math Equation (1), the single-cell massive MIMO sum-rate bound, is accepted as given
Section VI-A(c) reproduces the bound from [66] (Marzetta et al., co-authored by the present author Larsson) and uses it to derive the claim that low-frequency spectrum has tenfold value per MHz; the bound is cited, not re-derived.
domain assumption 5G aspirational KPIs such as peak rate are 'a purely mathematical exercise' and should not define 6G targets
Section III: the recommendation to redefine 6G KPIs rests on this interpretation of ITU-R M.2410 definitions, presented without external validation.

how reviews work

0 comments

Cite this review

Pith. "Pith review of Industrial Viewpoints on RAN Technologies for 6G." pith.science (2026). https://pith.science/paper/CTUFHG4T

@misc{pith2026250808225,
  author       = {Pith},
  title        = {Pith review of: Industrial Viewpoints on RAN Technologies for 6G},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/CTUFHG4T}},
  note         = {Machine review of arXiv:2508.08225}
}

read the original abstract

6G standardization is to start imminently, with commercial deployments expected before 2030. Its technical components and performance requirements are the focus of this article. Our emphasis is on the 6G radio access, especially MIMO, AI, waveforms, coding, signal constellations and integration with non-terrestrial networks. Whilst standardization has not yet formally started, the scope of the 6G study items has been defined. Our predictions in this paper are speculative as there are no results of the study yet, but our views are guided by implementation and deployment aspects. We expect that the views here will guide researchers and industry practitioners.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

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

Computationally Efficient Neural Receivers via Axial Self-Attention
eess.SP 2025-10 conditional novelty 5.0 of 10

Axial attention over time and frequency matches or beats global attention and CNN baselines in a neural OFDM receiver while using roughly 2.8x fewer FLOPs.

Reference graph

Works this paper leans on

300 extracted references · 76 canonical work pages · cited by 1 Pith paper

[17]

Real-time deployment aspects of c-band and millimeter-wave 5G-NR systems,

M. Shafi et al. , “Real-time deployment aspects of c-band and millimeter-wave 5G-NR systems,” in ICC 2020 - 2020 IEEE Inter- national Conference on Communications (ICC) , 2020, pp. 1–7

2020
[1]

On the roots of wireless communications,

A. Antoniou, “On the roots of wireless communications,” IEEE Circuits and Systems Magazine , vol. 11, no. 1, pp. 14–25, 2011

2011
[2]

One Hundred Years of Radio,

L. J. Greenstein, “One Hundred Years of Radio,” Presentation at the Centenary of Radio, Redbank NJ, USA, 1999, http://www.winlab.tgers. edu/archive/Marconi\%20Day/Greenstein.pdf

1999
[3]

Recent Development of 5G-Advanced in 3GPP: Commercial Needs and A Bridge to 6G,

W. Chen et al. , “Recent Development of 5G-Advanced in 3GPP: Commercial Needs and A Bridge to 6G,” submitted to IEEE Com- munications Magazine, 2024

2024
[4]

5G-Advanced toward 6G: Past, present, and future,

——, “5G-Advanced toward 6G: Past, present, and future,” IEEE Journal on Selected Areas in Communications, vol. 41, no. 6, pp. 1592– 1619, 2023

2023
[5]

IEEE proceedings special issue next generation multiple access,

“IEEE proceedings special issue next generation multiple access,” vol. 12, no. 9, Sep. 2024

2024
[6]

The road to 6G: Driving the next wave of connectivity–part II access,

“The road to 6G: Driving the next wave of connectivity–part II access,” Proceedings of the IEEE , 2025

2025
[7]

6G wireless networks: Vision, requirements, archi- tecture, and key technologies,

Z. Zhang et al. , “6G wireless networks: Vision, requirements, archi- tecture, and key technologies,” IEEE Vehicular Technology Magazine, vol. 14, no. 3, pp. 28–41, 2019

2019

Show all 300 references

[8]

Toward 6G networks: Use cases and technologies,

M. Giordani et al., “Toward 6G networks: Use cases and technologies,” IEEE Communications Magazine , vol. 58, no. 3, pp. 55–61, 2020

2020
[9]

6G wireless systems: Vision, requirements, chal- lenges, insights, and opportunities,

H. Tataria et al. , “6G wireless systems: Vision, requirements, chal- lenges, insights, and opportunities,” Proceedings of the IEEE, vol. 109, no. 7, pp. 1166–1199, 2021

2021
[10]

The role of millimeter-wave technologies in 5G/6G wireless communications,

W. Hong et al. , “The role of millimeter-wave technologies in 5G/6G wireless communications,” IEEE Journal of Microwaves, vol. 1, no. 1, pp. 101–122, 2021

2021
[11]

6G and beyond: The future of wireless commu- nications systems,

I. F. Akyildiz et al., “6G and beyond: The future of wireless commu- nications systems,” IEEE Access, vol. 8, pp. 133 995–134 030, 2020

2020
[12]

A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,

W. Saad et al., “A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,” IEEE Network , vol. 34, no. 3, pp. 134–142, 2020

2020
[13]

6G takes shape,

J. G. Andrews et al. , “6G takes shape,” IEEE BITS the Information Theory Magazine , vol. 4, no. 1, p. 2–24, Mar. 2024. [Online]. Available: http://dx.doi.org/10.1109/MBITS.2024.3504521

2024
[14]

WRC 2023 final acts,

“WRC 2023 final acts,” ITU-R, Tech. Rep., Nov. 2023

2023
[15]

TR 23 501, 3GPP, system architecture for the 5G system (5GS) ,stage 2, rel 19,

“TR 23 501, 3GPP, system architecture for the 5G system (5GS) ,stage 2, rel 19,” 3GPP, Tech. Rep. TS 23.501, Mar. 2025

2025
[16]

Perspectives on 6G architectures,

R. Liebhart et al. , “Perspectives on 6G architectures,” IEEE Wireless Communications, vol. 32, no. 1, pp. 108–114, 2025

2025
[18]

6G wireless communication systems: Ap- plications, requirements, technologies, challenges, and research direc- tions,

M. Z. Chowdhury et al. , “6G wireless communication systems: Ap- plications, requirements, technologies, challenges, and research direc- tions,” IEEE Open Journal of the Communications Society , vol. 1, pp. 957–975, 2020

2020
[19]

Framework and overall objectives of the future development of IMT for 2030 and beyond,

“Framework and overall objectives of the future development of IMT for 2030 and beyond,” ITU, Tech. Rep. M 2136, Nov. 2023
[20]

Vision, market drivers and research directions on the path to 6G,

“Vision, market drivers and research directions on the path to 6G,” Tech. Rep., Dec. 2022

2022
[21]

6G - connecting a cyber physical world,

“6G - connecting a cyber physical world,” Ericsson, Tech. Rep., Feb. 2022

2022
[22]

Toward a 6G AI-native air interface,

“Toward a 6G AI-native air interface,” Nokia, Tech. Rep., Mar. 2021

2021
[23]

6G: The next hyper-connected experience for all,

“6G: The next hyper-connected experience for all,” Samsung, Tech. Rep., Jul. 2020

2020
[24]

Ever-present intelligent communication; a research outlook towards 6G,

“Ever-present intelligent communication; a research outlook towards 6G,” Tech. Rep., Nov. 2022

2022
[25]

The envisioned way of life in 2030 and beyond,

“The envisioned way of life in 2030 and beyond,” Ericsson, Tech. Rep., May 2024
[26]

Targets and requirements for 6G - initial E2E architecture, deliverable d1.3,

“Targets and requirements for 6G - initial E2E architecture, deliverable d1.3,” HexaX, Tech. Rep., Feb. 2022

2022
[27]

Chair’s summary of the 3GPP workshop on 6G,

“Chair’s summary of the 3GPP workshop on 6G,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-25243, Mar. 2025

2025
[28]

Study on 6G radio,

“Study on 6G radio,” 3GPP, Prague, Czech Republic, Tech. Rep. RP- 251881, Jun. 2025

2025
[29]

High-level considerations for 6G timeline,

“High-level considerations for 6G timeline,” 3GPP, Tech. Rep. RP- 233985, 2023

2023
[30]

IMT-2020 vision - framework and overall objectives of the future development of IMT for 2020 and beyond,

“IMT-2020 vision - framework and overall objectives of the future development of IMT for 2020 and beyond,” ITU, Tech. Rep., Sep. 2019

2020
[31]

TR 23.870, study on 6G use cases and service requirement, stage 2, rel 19,

“TR 23.870, study on 6G use cases and service requirement, stage 2, rel 19,” 3GPP, Tech. Rep. TR 22.870, Mar. 2025

2025
[32]

Wireless communications research challenges for extended reality (XR),

I. E. Akylidz et al. , “Wireless communications research challenges for extended reality (XR),” ITU Journal on Future and Evolving Technologies, vol. 3, 2022

2022
[33]

Cellular-connected wireless virtual reality: Requirements, challenges, and solutions,

F. Hu et al., “Cellular-connected wireless virtual reality: Requirements, challenges, and solutions,” IEEE Communications Magazine , vol. 58, no. 5, pp. 105–111, 2020

2020
[34]

Toward interconnected virtual reality: Opportunities, challenges, and enablers,

E. Bastug et al., “Toward interconnected virtual reality: Opportunities, challenges, and enablers,” IEEE Communications Magazine , vol. 55, no. 6, pp. 110–117, 2017

2017
[35]

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

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

2024
[36]

6G enabled smart infrastcture for sustainable society: Opportunities, challenges, and research roadmap

A. Imoize et al., “6G enabled smart infrastcture for sustainable society: Opportunities, challenges, and research roadmap.”
[37]

Wireless sensor networks: a survey,

I. F. Akyildiz et al., “Wireless sensor networks: a survey,” in Computer Networks, vol. 38, no. 4, 2002, pp. 393 – 422

2002
[38]

The internet of bio-nano things,

——, “The internet of bio-nano things,” IEEE Communications Mag- azine, vol. 53, no. 3, pp. 32–40, 2015

2015
[39]

Minimum requirements related to the technical performance of IMT- 2020 radio interfaces,

“Minimum requirements related to the technical performance of IMT- 2020 radio interfaces,” ITU-R, Tech. Rep. M.2410, Jan. 2017

2020
[40]

ITU-R M 2410, minimum requirements for IMT 2020,

“ITU-R M 2410, minimum requirements for IMT 2020,” ITU, Tech. Rep. M.2410

2020
[41]

Scaling up MIMO: Opportunities and challenges with very large arrays,

F. Rusek et al., “Scaling up MIMO: Opportunities and challenges with very large arrays,” IEEE Signal Processing Magazine , vol. 30, no. 1, pp. 40–60, 2013

2013
[42]

Communication over fading channels with delay constraints,

R. Berry et al. , “Communication over fading channels with delay constraints,” IEEE Transactions on Information Theory , vol. 48, no. 5, pp. 1135–1149, 2002

2002
[43]

Network 2030 - representative use cases and key network requirements for network 2030,

“Network 2030 - representative use cases and key network requirements for network 2030,” ITU-T, Tech. Rep., Jun. 2020
[44]

Six critical challenges for 6G wireless systems: A summary and some solutions,

H. Tataria et al. , “Six critical challenges for 6G wireless systems: A summary and some solutions,” IEEE Vehicular Technology Magazine, vol. 17, no. 1, pp. 16–26, 2022

2022
[45]

RFC 5681,

“RFC 5681,” IETF, Tech. Rep., 2009

2009
[46]

Millimeter wave mobile communications for 5G cellular: It will work!

T. S. Rappaport et al. , “Millimeter wave mobile communications for 5G cellular: It will work!” IEEE Access, vol. 1, pp. 335–349, 2013

2013
[47]

Massive MIMO in sub-6 GHz and mmwave: Physical, practical, and use-case differences,

E. Bjornson et al. , “Massive MIMO in sub-6 GHz and mmwave: Physical, practical, and use-case differences,” IEEE Wireless Commu- nications, vol. 26, no. 2, pp. 100–108, 2019

2019
[48]

Base station radio transmission and reception,

“Base station radio transmission and reception,” 3GPP, Tech. Rep. TS 38.104, 2019

2019
[49]

Simplifying the 5G ecosystem by reducing archi- tecture options,

T. Cagenius et al., “Simplifying the 5G ecosystem by reducing archi- tecture options,” Ericsson technology Review , Nov. 2018

2018
[50]

The Core Network for 5G Advanced

S. Rommer et al., "The Core Network for 5G Advanced" . Academic Press, 2025

2025
[51]

3GPP & O-RAN alliance joint workshop on 6G coordination: Sum- mary,

“3GPP & O-RAN alliance joint workshop on 6G coordination: Sum- mary,” 3GPP, Sophia Antipolis, France, Tech. Rep. 3ORW-250035, Apr. 2025

2025
[52]

Simplifying spectrum migration from 5G to 6G,

L. Uzeda et al. , “Simplifying spectrum migration from 5G to 6G,” Nokia, Tech. Rep., July 2023

2023
[53]

Waveform for next generation communication systems: Comparing Zak-OTFS with OFDM,

I. A. Khan et al. , “Waveform for next generation communication systems: Comparing Zak-OTFS with OFDM,” 2025. [Online]. Available: https://arxiv.org/abs/2505.13966

2025 arXiv
[54]

Understanding o-ran: Architecture, interfaces, algorithms, security, and research challenges,

M. Polese et al. , “Understanding o-ran: Architecture, interfaces, algorithms, security, and research challenges,” 2022. [Online]. Available: https://arxiv.org/abs/2202.01032

2022 arXiv
[55]

Intelligence and learning in o-ran for data-driven nextg cellular networks,

L. Bonati et al. , “Intelligence and learning in o-ran for data-driven nextg cellular networks,” IEEE Communications Magazine , vol. 59, no. 10, pp. 21–27, 2021

2021
[56]

Summary of 3GPP & O-RAN ALLIANCE joint workshop on 6G coordination,

3GPP, “Summary of 3GPP & O-RAN ALLIANCE joint workshop on 6G coordination,” 3GPP, Prague, Czech Republic, Tech. Rep. RP- 250866, June 2025

2025
[57]

Transoceanic radio communication,

E. F. W. Alexanderson, “Transoceanic radio communication,” Presented at a joint meeting of the American Institute of Electrical Engineers and the Institute of Radio Engineers, New York, NY , Oct. 1919. 30

1919
[58]

Spatial division multiple access wireless communication systems,

R. Roy and B. Ottersten, “Spatial division multiple access wireless communication systems,” US Patent No. 5,515,378, 1991

1991
[59]

Signal design for transmitter diversity wireless communication systems over Rayleigh fading channels,

J. C. Guey et al. , “Signal design for transmitter diversity wireless communication systems over Rayleigh fading channels,” IEEE Trans. Commun., vol. 47, no. 4, pp. 527–537, Apr. 1999

1999
[60]

Space-time codes for high data rate wireless com- munications: performance criterion and code constction,

V . Tarokh et al. , “Space-time codes for high data rate wireless com- munications: performance criterion and code constction,” IEEE Trans. Inf. Theory, vol. 44, no. 2, pp. 744–765, Mar. 1998

1998
[61]

A simple transmit diversity technique for wireless communications,

S. M. Alamouti, “A simple transmit diversity technique for wireless communications,” IEEE J. Sel. Areas Commun. , vol. 16, no. 8, pp. 1451–1458, Oct. 1998

1998
[62]

On limits of wireless communications in a fading environment when using multiple antennas,

G. J. Foschini et al. , “On limits of wireless communications in a fading environment when using multiple antennas,” Wireless Personal communications, vol. 23, no. 6, pp. 311–335, 1998

1998
[63]

Capacity of multi-antenna Gaussian channels,

E. Telatar, “Capacity of multi-antenna Gaussian channels,” European Trans. on Telecommun., vol. 10, no. 6, pp. 585–596, Nov. 1999

1999
[64]

On the achievable throughput of a multi- antenna Gaussian broadcast channel,

G. Caire and S. Shamai, “On the achievable throughput of a multi- antenna Gaussian broadcast channel,” IEEE Trans. Inf. Theory, vol. 49, no. 7, pp. 1691–1706, July 2003

2003
[65]

The capacity region of the Gaussian multiple- input multiple-output broadcast channel,

H. Weingarten et al. , “The capacity region of the Gaussian multiple- input multiple-output broadcast channel,” IEEE Trans. Inf. Theory , vol. 52, no. 9, pp. 3936–3964, Sept. 2006

2006
[66]

T. L. Marzetta et al. , Fundamentals of massive MIMO . Cambridge University Press, 2016

2016
[67]

Fast transfer of channel state information in wireless systems,

——, “Fast transfer of channel state information in wireless systems,” IEEE Transactions on Signal Processing, vol. 54, no. 4, pp. 1268–1278, 2006

2006
[68]

Noncooperative cellular wireless with unlimited numbers of base station antennas,

T. L. Marzetta, “Noncooperative cellular wireless with unlimited numbers of base station antennas,” IEEE transactions on wireless communications, vol. 9, no. 11, pp. 3590–3600, 2010

2010
[69]

Massive MIMO for next generation wireless systems,

E. G. Larsson et al. , “Massive MIMO for next generation wireless systems,” IEEE communications magazine , vol. 52, no. 2, pp. 186– 195, 2014

2014
[70]

Joint spatial division and multiplexing for mm- wave channels,

A. Adhikary et al. , “Joint spatial division and multiplexing for mm- wave channels,” IEEE Journal on Selected Areas in Communications , vol. 32, no. 6, pp. 1239–1255, 2014

2014
[71]

Toward massive MIMO 2.0: Understanding spatial correlation, interference suppression, and pilot contamination,

L. Sanguinetti et al. , “Toward massive MIMO 2.0: Understanding spatial correlation, interference suppression, and pilot contamination,” IEEE Transactions on Communications , vol. 68, no. 1, pp. 232–257, 2019

2019
[72]

Reciprocity calibration for massive MIMO: Proposal, modeling, and validation,

J. Vieira et al., “Reciprocity calibration for massive MIMO: Proposal, modeling, and validation,” IEEE Transactions on Wireless Communi- cations, vol. 16, no. 5, pp. 3042–3056, 2017

2017
[73]

Massive MIMO evolution toward 3GPP release 18,

H. Jin et al. , “Massive MIMO evolution toward 3GPP release 18,” IEEE Journal on Selected Areas in Communications , vol. 41, no. 6, pp. 1635–1654, 2023

2023
[74]

Cell-free massive MIMO versus small cells,

H. Q. Ngo et al., “Cell-free massive MIMO versus small cells,” IEEE Transactions on Wireless Communications , vol. 16, no. 3, pp. 1834– 1850, 2017

2017
[75]

Ultradense cell-free massive MIMO for 6G: Technical overview and open questions,

——, “Ultradense cell-free massive MIMO for 6G: Technical overview and open questions,” Proceedings of the IEEE , 2024

2024
[76]

Foundations of user-centric cell-free massive MIMO,

Ö. T. Demir et al. , “Foundations of user-centric cell-free massive MIMO,” Foundations and Trends® in Signal Processing , vol. 14, no. 3-4, pp. 162–472, 2021

2021
[77]

Network MIMO: Overcoming intercell interfer- ence in indoor wireless systems,

S. Venkatesan et al., “Network MIMO: Overcoming intercell interfer- ence in indoor wireless systems,” in Proceedings Asilomar Conference on Signals, Systems & Computers , 2007

2007
[78]

Ubiquitous cell-free massive MIMO com- munications,

G. Interdonato et al. , “Ubiquitous cell-free massive MIMO com- munications,” EURASIP Journal on Wireless Communications and Networking, 2019

2019
[79]

RadioWeaves for efficient connectivity: analysis and impact of constraints in actual deployments,

L. Van der Perre et al. , “RadioWeaves for efficient connectivity: analysis and impact of constraints in actual deployments,” in Asilomar Conference on Signals, Systems, and Computers , 2019

2019
[80]

Beyond massive MIMO: The potential of data trans- mission with large intelligent surfaces,

S. Hu et al. , “Beyond massive MIMO: The potential of data trans- mission with large intelligent surfaces,” IEEE Transactions on Signal Processing, vol. 66, no. 10, pp. 2746–2758, 2018

2018
[81]

Distributed signal processing for extremely large-scale antenna array systems: State-of-the-art and future directions,

Y . Xu et al. , “Distributed signal processing for extremely large-scale antenna array systems: State-of-the-art and future directions,” IEEE Journal of Selected Topics in Signal Processing , 2025

2025
[82]

Correctly modeling TX and RX chain in (distributed) massive MIMO – new fundamental insights on coherency,

R. Nissel, “Correctly modeling TX and RX chain in (distributed) massive MIMO – new fundamental insights on coherency,” IEEE Communications Letters, pp. 2465–2469, Oct. 2022

2022
[83]

Phase calibration of distributed antenna arrays,

E. G. Larsson et al., “Phase calibration of distributed antenna arrays,” IEEE Communications Letters , 2023

2023
[84]

Beamsync: Over-the-air synchronization for distributed massive MIMO systems,

U. K. Ganesan et al. , “Beamsync: Over-the-air synchronization for distributed massive MIMO systems,” IEEE Transactions on Wireless Communications, vol. 23, no. 7, pp. 6824–6837, 2023

2023
[85]

Massive synchrony in distributed antenna systems,

E. G. Larsson, “Massive synchrony in distributed antenna systems,” IEEE Transactions on Signal Processing , vol. 72, pp. 855–866, 2024

2024
[86]

Reciprocity calibration of distributed massive MIMO access points for coherent operation,

J. Vieira et al., “Reciprocity calibration of distributed massive MIMO access points for coherent operation,” in IEEE PIMRC, 2021

2021
[87]

Breaking the tdd flow for over-the-air phase synchronization in distributed antenna systems,

K.-H. Ngo et al. , “Breaking the tdd flow for over-the-air phase synchronization in distributed antenna systems,” arXiv preprint arXiv:2504.11411, 2025

2025 arXiv
[88]

Massive MIMO networks: Spectral, energy, and hardware efficiency,

E. Björnson et al. , “Massive MIMO networks: Spectral, energy, and hardware efficiency,” Foundations and Trends in Signal Processing , vol. 11, no. 3-4, pp. 154–655, 2017

2017
[89]

3.6 a 60pj/b 300mb/s 128 × 8 massive MIMO precoder-detector in 28nm fd-soi,

H. Prabhu et al. , “3.6 a 60pj/b 300mb/s 128 × 8 massive MIMO precoder-detector in 28nm fd-soi,” in 2017 IEEE International Solid- State Circuits Conference (ISSCC) , 2017, pp. 60–61

2017
[90]

Spatially sparse precoding in millimeter wave MIMO systems,

O. E. Ayach et al. , “Spatially sparse precoding in millimeter wave MIMO systems,” IEEE Transactions on Wireless Communications , vol. 13, no. 3, p. 1499–1513, Mar. 2014. [Online]. Available: http://dx.doi.org/10.1109/TWC.2014.011714.130846

2014
[91]

On the equivalence between hybrid and full digital beamforming in mmwave communications,

M. Shehata et al., “On the equivalence between hybrid and full digital beamforming in mmwave communications,” in 2019 26th International Conference on Telecommunications (ICT) , 2019, pp. 391–395

2019
[92]

Vision & priorities for 6G radio technology,

NTT Docomo, “Vision & priorities for 6G radio technology,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250052, Mar. 2025

2025
[93]

A review of codebooks for csi feedback in 5g new radio and beyond,

Q. Ziao et al. , “A review of codebooks for csi feedback in 5g new radio and beyond,” China Communications , vol. 22, no. 2, pp. 112– 127, 2025

2025
[94]

6G radio and RAN,

Nokia, “6G radio and RAN,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS- 250004, Mar. 2025

2025
[95]

NR MIMO phase 6,

“NR MIMO phase 6,” 3GPP, Prague, Czech Republic, Tech. Rep. RP- 1856, Mar. 2025

2025
[96]

Qualcomm’s 6G radio technology vision and priorities,

Qualcomm, “Qualcomm’s 6G radio technology vision and priorities,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250068, Mar. 2025

2025
[97]

Views on 6G radio,

Huawei, “Views on 6G radio,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS- 250159, Mar. 2025

2025
[98]

LGE’s view on 6G radio technologies,

LGE, “LGE’s view on 6G radio technologies,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250065, Mar. 2025

2025
[99]

Vision and technologies for 6G radio,

Samsung, “Vision and technologies for 6G radio,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250036, Mar. 2025

2025
[100]

Overall vision & priorities for RAN in 6G,

Ericsson, “Overall vision & priorities for RAN in 6G,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250084, Mar. 2025

2025
[101]

view on 6G RAN technology,

vivo, “view on 6G RAN technology,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250049, Mar. 2025

2025
[102]

Vision and priorities for next generation radio technol- ogy,

Interdigital, “Vision and priorities for next generation radio technol- ogy,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250163, Mar. 2025

2025
[103]

Mediatek views on 6G day 1 - radio aspects,

Mediatek, “Mediatek views on 6G day 1 - radio aspects,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250071, Mar. 2025

2025
[104]

V odafone view on next RAN generation,

V odafone, “V odafone view on next RAN generation,” 3GPP, Seoul, Korea, Tech. Rep. 6GWS-250153, Mar. 2025

2025
[105]

Zero-forcing methods for downlink spatial multi- plexing in multiuser MIMO channels,

Q. Spencer et al. , “Zero-forcing methods for downlink spatial multi- plexing in multiuser MIMO channels,” IEEE Transactions on Signal Processing, vol. 52, no. 2, pp. 461–471, 2004

2004
[106]

Non-linear precoding for 5G NR,

F. Hasegawa et al. , “Non-linear precoding for 5G NR,” in 2018 IEEE Conference on Standards for Communications and Networking (CSCN), 2018, pp. 1–7

2018
[107]

Performance enhancement of codebook-based beamforming using least squares approach,

S. J. Lee, “Performance enhancement of codebook-based beamforming using least squares approach,” IEEE Wireless Communications Letters, vol. 13, no. 2, pp. 338–342, 2024

2024
[108]

Ml codebook design for initial access and CSI type-ii feedback in sub-6GHz 5G NR,

R. M. Dreifuerst et al. , “Ml codebook design for initial access and CSI type-ii feedback in sub-6GHz 5G NR,” 2023. [Online]. Available: https://arxiv.org/abs/2303.02850

2023 arXiv
[109]

Massive MIMO in 5G: How beamforming, codebooks, and feedback enable larger arrays,

——, “Massive MIMO in 5G: How beamforming, codebooks, and feedback enable larger arrays,” IEEE Communications Magazine , vol. 61, no. 12, pp. 18–23, 2023

2023
[110]

An overview of limited feedback in wireless commu- nication systems,

D. J. Love et al., “An overview of limited feedback in wireless commu- nication systems,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 8, pp. 1341–1365, 2008

2008
[111]

Linear precoding in the downlink of limited feedback multiuser MIMO systems,

G. Dietl et al., “Linear precoding in the downlink of limited feedback multiuser MIMO systems,” in IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference, 2007, pp. 4359–4364

2007
[112]

Multi-antenna downlink channels with limited feedback and user selection,

T. Yoo et al., “Multi-antenna downlink channels with limited feedback and user selection,” IEEE Journal on Selected Areas in Communica- tions, vol. 25, no. 7, pp. 1478–1491, 2007

2007
[113]

Limited feedback signaling for MIMO broadcast channels,

J. Kim et al. , “Limited feedback signaling for MIMO broadcast channels,” in IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, 2005., 2005, pp. 855–859

2005
[114]

Learning beam codebooks with neural networks: Towards environment-aware mmwave MIMO,

Y . Zhang et al. , “Learning beam codebooks with neural networks: Towards environment-aware mmwave MIMO,” 2020. [Online]. Available: https://arxiv.org/abs/2002.10663 31

2020 arXiv
[115]

NR; 7 - 24GHz frequency range,

“NR; 7 - 24GHz frequency range,” 3GPP, Tech. Rep. TR 38.820, 2021

2021
[116]

Generic unwanted emission characteristic of base stations using the terrestrial radio interfaces of IMT-Advanced0,

“Generic unwanted emission characteristic of base stations using the terrestrial radio interfaces of IMT-Advanced0,” ITU-R, Tech. Rep. M.2070, Feb. 2017
[117]

Out-of-band radiation measure for MIMO arrays with beamformed transmission,

C. Mollén et al., “Out-of-band radiation measure for MIMO arrays with beamformed transmission,” in 2016 IEEE International Conference on Communications (ICC), 2016

2016
[118]

Spatial characteristics of distortion radiated from antenna arrays with transceiver nonlinearities,

C. Mollén et al. , “Spatial characteristics of distortion radiated from antenna arrays with transceiver nonlinearities,” IEEE Transactions on Wireless Communications, vol. 17, no. 10, pp. 6663–6679, 2018

2018
[119]

Passive and active antenna systems for base stations of IMT systems,

“Passive and active antenna systems for base stations of IMT systems,” ITU-R, Tech. Rep. M.2334, Nov. 2014

2014
[120]

Radioweaves for extreme spatial multiplexing in indoor environments,

U. K. Ganesan et al., “Radioweaves for extreme spatial multiplexing in indoor environments,” in 2020 54th Asilomar Conference on Signals, Systems, and Computers , 2020, pp. 1007–1011

2020
[121]

Spatial separation of closely-spaced users in measured distributed massive MIMO channels,

Y . Xu et al. , “Spatial separation of closely-spaced users in measured distributed massive MIMO channels,” in 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2024, pp. 381–385

2024
[122]

RIS in cellular networks – challenges and issues,

M. Åström et al., “RIS in cellular networks – challenges and issues,”
[123]

Achieving distributed MIMO performance with repeater-assisted cellular massive MIMO,

S. Willhammar et al. , “Achieving distributed MIMO performance with repeater-assisted cellular massive MIMO,” IEEE Communications Magazine, vol. 63, no. 3, pp. 114–119, 2025

2025
[124]

Reciprocity calibration of dual-antenna repeaters,

E. G. Larsson et al., “Reciprocity calibration of dual-antenna repeaters,” IEEE Wireless Communications Letters , 2024

2024
[125]

Over-the-air computation for distributed systems: Something old and something new,

Z. Chen et al. , “Over-the-air computation for distributed systems: Something old and something new,” IEEE Network , vol. 37, no. 5, pp. 240–246, 2023

2023
[126]

A survey on over-the-air computation,

A. ¸ Sahin et al. , “A survey on over-the-air computation,” IEEE Com- munications Surveys & Tutorials, vol. 25, no. 3, pp. 1877–1908, 2023

1908
[127]

Over-the-air federated learning with phase noise: Analysis and countermeasures,

M. Dahl et al. , “Over-the-air federated learning with phase noise: Analysis and countermeasures,” in 2024 58th Annual Conference on Information Sciences and Systems (CISS) , 2024, pp. 1–6

2024
[128]

Non-coherent over-the-air decentralized gradient de- scent,

N. Michelusi, “Non-coherent over-the-air decentralized gradient de- scent,” IEEE Transactions on Signal Processing , 2024

2024
[129]

An introduction to deep learning for the physical layer,

T. O’shea et al. , “An introduction to deep learning for the physical layer,” IEEE Transactions on Cognitive Communications and Network- ing, vol. 3, no. 4, pp. 563–575, 2017

2017
[130]

Artificial neural networks-based machine learning for wireless networks: A tutorial,

M. Chen et al. , “Artificial neural networks-based machine learning for wireless networks: A tutorial,” IEEE Communications Surveys & Tutorials, vol. 21, no. 4, pp. 3039–3071, 2019

2019
[131]

The roadmap to 6G: AI empowered wireless networks,

K. B. Letaief et al. , “The roadmap to 6G: AI empowered wireless networks,” IEEE Communications Magazine , vol. 57, no. 8, pp. 84– 90, 2019

2019
[132]

Wireless networks design in the era of deep learning: Model-based, AI-based, or both?

A. Zappone et al. , “Wireless networks design in the era of deep learning: Model-based, AI-based, or both?” IEEE Transactions on Communications, vol. 67, no. 10, pp. 7331–7376, 2019

2019
[133]

Deep learning in mobile and wireless networking: A survey,

C. Zhang et al. , “Deep learning in mobile and wireless networking: A survey,” IEEE Communications Surveys & Tutorials , vol. 21, no. 3, pp. 2224–2287, 2019

2019
[134]

A very brief introduction to machine learning with appli- cations to communication systems,

O. Simeone, “A very brief introduction to machine learning with appli- cations to communication systems,” IEEE Transactions on Cognitive Communications and Networking , vol. 4, no. 4, pp. 648–664, 2018

2018
[135]

Artificial-intelligence-enabled intelligent 6G networks,

H. Yang et al., “Artificial-intelligence-enabled intelligent 6G networks,” IEEE Network, vol. 34, no. 6, pp. 272–280, 2020

2020
[136]

Future technology trends of terrestrial international mobile telecommunications systems towards 2030 and beyond,

ITU-R, “Future technology trends of terrestrial international mobile telecommunications systems towards 2030 and beyond,” Report ITU-R M.2516-0, 2022
[137]

Embracing AI in 5G-Advanced toward 6G: A joint 3GPP and O-RAN perspective,

X. Lin et al., “Embracing AI in 5G-Advanced toward 6G: A joint 3GPP and O-RAN perspective,” IEEE Communications Standards Magazine, vol. 7, no. 4, pp. 76–83, 2023

2023
[138]

Approaching AI-native RANs through generalization and scalability of learning,

P. Soldati et al., “Approaching AI-native RANs through generalization and scalability of learning,” Ericsson Technology Review , vol. 2023, no. 3, pp. 2–12, 2023

2023
[139]

Toward a 6G AI-native air interface,

J. Hoydis et al., “Toward a 6G AI-native air interface,” IEEE Commu- nications Magazine, vol. 59, no. 5, pp. 76–81, 2021

2021
[140]

Defining AI native: A key enabler for advanced intelligent telecom networks,

Ericsson, “Defining AI native: A key enabler for advanced intelligent telecom networks,” white paper, 2023

2023
[141]

Deep learning based communication over the air,

S. Dörner et al. , “Deep learning based communication over the air,” IEEE Journal of Selected Topics in Signal Processing , vol. 12, no. 1, pp. 132–143, 2017

2017
[142]

Deep learning in physical layer communications,

Z. Qin et al., “Deep learning in physical layer communications,” IEEE Wireless Communications, vol. 26, no. 2, pp. 93–99, 2019

2019
[143]

An overview of 5G advanced evolution in 3GPP release 18,

X. Lin, “An overview of 5G advanced evolution in 3GPP release 18,” IEEE Communications Standards Magazine , vol. 6, no. 3, pp. 77–83, 2022

2022
[144]

Overview of deep learning-based CSI feedback in massive MIMO systems,

J. Guo et al. , “Overview of deep learning-based CSI feedback in massive MIMO systems,” IEEE Transactions on Communications , vol. 70, no. 12, pp. 8017–8045, 2022

2022
[145]

Channel state information prediction for 5G wireless communications: A deep learning approach,

C. Luo et al. , “Channel state information prediction for 5G wireless communications: A deep learning approach,” IEEE transactions on Network Science and Engineering , vol. 7, no. 1, pp. 227–236, 2018

2018
[146]

Deep learning for mmWave beam and blockage prediction using sub-6 GHz channels,

M. Alrabeiah et al., “Deep learning for mmWave beam and blockage prediction using sub-6 GHz channels,” IEEE Transactions on Commu- nications, vol. 68, no. 9, pp. 5504–5518, 2020

2020
[147]

Machine learning for millimeter wave and terahertz beam management: A survey and open challenges,

M. Q. Khan et al., “Machine learning for millimeter wave and terahertz beam management: A survey and open challenges,” IEEE Access , vol. 11, pp. 11 880–11 902, 2023

2023
[148]

More is better: Data augmentation for channel- resilient RF fingerprinting,

N. Soltani et al. , “More is better: Data augmentation for channel- resilient RF fingerprinting,” IEEE Communications Magazine , vol. 58, no. 10, pp. 66–72, 2020

2020
[149]

Machine learning for time-of-arrival estimation with 5G signals in indoor positioning,

Z. Liu et al., “Machine learning for time-of-arrival estimation with 5G signals in indoor positioning,” IEEE Internet of Things Journal, vol. 10, no. 11, pp. 9782–9795, 2023

2023
[150]

Study on artificial intelligence (AI)/machine learning (ML) for NR air interface,

3GPP, “Study on artificial intelligence (AI)/machine learning (ML) for NR air interface,” TR 38.843, V18.0.0 , 2024

2024
[151]

The bridge toward 6G: 5G-Advanced evolution in 3GPP release 19,

X. Lin, “The bridge toward 6G: 5G-Advanced evolution in 3GPP release 19,” IEEE Communications Standards Magazine , vol. 9, no. 1, pp. 28–35, 2025

2025
[152]

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

3GPP, “Study on channel model for frequencies from 0.5 to 100 GHz,” TR 38.901, V18.0.0 , 2024

2024
[153]

A tale of two mobile generations: 5G-Advanced and 6G in 3GPP release 20,

X. Lin, “A tale of two mobile generations: 5G-Advanced and 6G in 3GPP release 20,” arXiv preprint arXiv:2506.11828 , 2025

2025 arXiv
[154]

DeepRx: Fully convolutional deep learning re- ceiver,

M. Honkala et al. , “DeepRx: Fully convolutional deep learning re- ceiver,”IEEE Transactions on Wireless Communications, vol. 20, no. 6, pp. 3925–3940, 2021

2021
[155]

A neural receiver for 5G NR multi-user MIMO,

S. Cammerer et al., “A neural receiver for 5G NR multi-user MIMO,” in 2023 IEEE Globecom Workshops (GC Wkshps) . IEEE, 2023, pp. 329–334

2023
[156]

End-to-end learning for OFDM: From neural receivers to pilotless communication,

A. Ait et al., “End-to-end learning for OFDM: From neural receivers to pilotless communication,” IEEE Transactions on Wireless Commu- nications, vol. 21, no. 2, pp. 1049–1063, 2021

2021
[157]

Sionna: An open-source library for next-generation physical layer research,

J. Hoydis et al. , “Sionna: An open-source library for next-generation physical layer research,” arXiv preprint arXiv:2203.11854 , 2022

2022 arXiv
[158]

Artificial-intelligence-enabled air interface for 6G: Solu- tions, challenges, and standardization impacts,

S. Han et al., “Artificial-intelligence-enabled air interface for 6G: Solu- tions, challenges, and standardization impacts,” IEEE Communications Magazine, vol. 58, no. 10, pp. 73–79, 2020

2020
[159]

Continual learning digital predistortion of RF power amplifier for 6G AI-empowered wireless communication,

Y . Yu et al. , “Continual learning digital predistortion of RF power amplifier for 6G AI-empowered wireless communication,” IEEE Trans- actions on Microwave Theory and Techniques , vol. 70, no. 11, pp. 4916–4927, 2022

2022
[160]

A uniform neural network digital predistortion model of RF power amplifiers for scalable applications,

H. Wu et al. , “A uniform neural network digital predistortion model of RF power amplifiers for scalable applications,” IEEE Transactions on Microwave Theory and Techniques, vol. 70, no. 11, pp. 4885–4899, 2022

2022
[161]

Graph neural networks for scalable radio resource man- agement: Architecture design and theoretical analysis,

Y . Shen et al., “Graph neural networks for scalable radio resource man- agement: Architecture design and theoretical analysis,” IEEE Journal on Selected Areas in Communications , vol. 39, no. 1, pp. 101–115, 2021

2021
[162]

AI opportunities in 6G layer 2,

Nokia, “AI opportunities in 6G layer 2,” white paper, 2024

2024
[163]

Spatial deep learning for wireless scheduling,

W. Cui et al. , “Spatial deep learning for wireless scheduling,” IEEE Journal on Selected Areas in Communications, vol. 37, no. 6, pp. 1248– 1261, 2019

2019
[164]

A deep-reinforcement-learning-based approach to dynamic eMBB/URLLC multiplexing in 5G NR,

Y . Huang et al. , “A deep-reinforcement-learning-based approach to dynamic eMBB/URLLC multiplexing in 5G NR,” IEEE Internet of Things Journal, vol. 7, no. 7, pp. 6439–6456, 2020

2020
[165]

Learn to schedule (LEASCH): A deep reinforcement learning approach for radio resource scheduling in the 5G MAC layer,

F. Al-Tam et al., “Learn to schedule (LEASCH): A deep reinforcement learning approach for radio resource scheduling in the 5G MAC layer,” IEEE Access, vol. 8, pp. 108 088–108 101, 2020

2020
[166]

Massive MIMO adaptive modulation and coding using online deep learning algorithm,

E. Bobrov et al. , “Massive MIMO adaptive modulation and coding using online deep learning algorithm,” IEEE Communications Letters , vol. 26, no. 4, pp. 818–822, 2021

2021
[167]

Reinforcement learning for efficient and tuning- free link adaptation,

V . Saxena et al. , “Reinforcement learning for efficient and tuning- free link adaptation,” IEEE Transactions on Wireless Communications, vol. 21, no. 2, pp. 768–780, 2021

2021
[168]

Power control in cellular massive MIMO with varying user activity: A deep learning solution,

T. Van Chien et al. , “Power control in cellular massive MIMO with varying user activity: A deep learning solution,” IEEE Transactions on Wireless Communications, vol. 19, no. 9, pp. 5732–5748, 2020

2020
[169]

ML-based radio resource management in 5G and beyond networks: A survey,

I. A. Bartsiokas et al. , “ML-based radio resource management in 5G and beyond networks: A survey,” IEEE Access , vol. 10, pp. 83 507– 83 528, 2022. 32

2022
[170]

A survey of machine learning applications to handover management in 5G and beyond,

M. S. Mollel et al. , “A survey of machine learning applications to handover management in 5G and beyond,” IEEE Access , vol. 9, pp. 45 770–45 802, 2021

2021
[171]

Study on artificial intelligence (AI)/machine learning (ML) for mobility in NR,

3GPP, “Study on artificial intelligence (AI)/machine learning (ML) for mobility in NR,” TR 38.744, V19.0.0 , 2025

2025
[172]

Towards semantic MAC protocols for 6G: From protocol learning to language-oriented approaches,

J. Park et al., “Towards semantic MAC protocols for 6G: From protocol learning to language-oriented approaches,” IEEE BITS the Information Theory Magazine, 2024

2024
[173]

AI-driven zero touch network and service manage- ment in 5G and beyond: Challenges and research directions,

C. Benzaid et al., “AI-driven zero touch network and service manage- ment in 5G and beyond: Challenges and research directions,” IEEE Network, vol. 34, no. 2, pp. 186–194, 2020

2020
[174]

A survey on intent-based networking,

A. Leivadeas and M. Falkner, “A survey on intent-based networking,” IEEE Communications Surveys & Tutorials , vol. 25, no. 1, pp. 625– 655, 2022

2022
[175]

Large language models for telecom: Forthcoming impact on the industry,

A. Maatouk et al., “Large language models for telecom: Forthcoming impact on the industry,” IEEE communications magazine , 2024

2024
[176]

Distributed learning in wireless networks: Recent progress and future challenges,

M. Chen et al. , “Distributed learning in wireless networks: Recent progress and future challenges,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 12, pp. 3579–3605, 2021

2021
[177]

Machine learning at the edge: A data-driven archi- tecture with applications to 5G cellular networks,

M. Polese et al., “Machine learning at the edge: A data-driven archi- tecture with applications to 5G cellular networks,” IEEE Transactions on Mobile Computing , vol. 20, no. 12, pp. 3367–3382, 2020

2020
[178]

Understanding O-RAN: Architecture, interfaces, algorithms, security, and research challenges,

——, “Understanding O-RAN: Architecture, interfaces, algorithms, security, and research challenges,” IEEE Communications Surveys & Tutorials, vol. 25, no. 2, pp. 1376–1411, 2023

2023
[179]

Communication and computing integrated RAN: A new paradigm shift for mobile network,

Y . Huang et al. , “Communication and computing integrated RAN: A new paradigm shift for mobile network,” IEEE Network, vol. 38, no. 2, pp. 97–112, 2024

2024
[180]

Toward energy efficient RAN: From industry stan- dards to trending practice,

L. Kundu et al. , “Toward energy efficient RAN: From industry stan- dards to trending practice,” IEEE Wireless Communications , vol. 32, no. 1, pp. 36–43, 2025

2025
[181]

AI-RAN Alliance vision and mission white paper,

“AI-RAN Alliance vision and mission white paper,” https://ai-ran. org/wp-content/uploads/2024/12/AI-RAN_Alliance_Whitepaper.pdf, AI-RAN Alliance, Tech. Rep., 2024

2024
[182]

Joint computation and communication cooperation for energy-efficient mobile edge computing,

X. Cao et al. , “Joint computation and communication cooperation for energy-efficient mobile edge computing,” IEEE Internet of Things Journal, vol. 6, no. 3, pp. 4188–4200, 2018

2018
[183]

Traceability for tstworthy AI: A review of models and tools,

M. Mora-Cantallops et al., “Traceability for tstworthy AI: A review of models and tools,” Big Data and Cognitive Computing , vol. 5, no. 2, p. 20, 2021

2021
[184]

Artificial intelligence for 5G and beyond 5G: Imple- mentations, algorithms, and optimizations,

C. Zhang et al., “Artificial intelligence for 5G and beyond 5G: Imple- mentations, algorithms, and optimizations,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems , vol. 10, no. 2, pp. 149– 163, 2020

2020
[185]

The future of AI is hybrid—Part I: Unlocking the gener- ative AI future with on-device and hybrid AI,

Qualcomm, “The future of AI is hybrid—Part I: Unlocking the gener- ative AI future with on-device and hybrid AI,” white paper, 2023

2023
[186]

The AI revolution: Preparing for a surge in 5G uplink traffic,

H. Holma, “The AI revolution: Preparing for a surge in 5G uplink traffic,” 2024, https://www.nokia.com/blog/ the-ai-revolution-preparing-for-a-surge-in-5g-uplink-traffic/

2024
[187]

Ericsson mobility report,

“Ericsson mobility report,” Ericsson, Tech. Rep., Nov. 2024, https://www.ericsson.com/en/reports-and-papers/mobility-report/ reports/november-2024

2024
[188]

TS 38.101-5; NR; User Equipment (UE) radio transmission and reception; part 5: Satellite access radio frequency (RF) and performance requirements,

“TS 38.101-5; NR; User Equipment (UE) radio transmission and reception; part 5: Satellite access radio frequency (RF) and performance requirements,” 3GPP, Tech. Rep. TS 38.101-5, 2025

2025
[189]

Why to decouple the uplink and downlink in cellular networks and how to do it,

F. Boccardi et al., “Why to decouple the uplink and downlink in cellular networks and how to do it,” IEEE Communications Magazine, vol. 54, no. 3, pp. 110–117, 2016

2016
[190]

Dahlman, S

E. Dahlman, S. Parkvall, and J. Sköld, 5G/5G-Advanced NR: The new generation wireless access technology . Elsevier, 2023

2023
[191]

Energy efficient extreme MIMO: Design goals and directions,

S. Wesemann et al. , “Energy efficient extreme MIMO: Design goals and directions,” IEEE Communications Magazine , vol. 61, no. 10, pp. 132–138, 2023

2023
[192]

A 28-ghz 32-element trx phased-array ic with concurrent dual-polarized operation and orthogonal phase and gain control for 5g communications,

B. Sadhu et al. , “A 28-ghz 32-element trx phased-array ic with concurrent dual-polarized operation and orthogonal phase and gain control for 5g communications,” IEEE Journal of Solid-State Circuits , vol. 52, no. 12, pp. 3373–3391, 2017

2017
[193]

Development, implementation, and characterization of a 64-element dual-polarized phased-array antenna module for 28-ghz high-speed data communications,

X. Gu et al. , “Development, implementation, and characterization of a 64-element dual-polarized phased-array antenna module for 28-ghz high-speed data communications,” IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 7, pp. 2975–2984, 2019

2019
[194]

Massive MIMO in the UL/DL of cellular networks: How many antennas do we need?

J. Hoydis et al., “Massive MIMO in the UL/DL of cellular networks: How many antennas do we need?” IEEE Journal on Selected Areas in Communications, vol. 31, no. 2, pp. 160–171, 2013

2013
[195]

Massive MIMO systems with non-ideal hardware: Energy efficiency, estimation, and capacity limits,

E. Björnson et al., “Massive MIMO systems with non-ideal hardware: Energy efficiency, estimation, and capacity limits,” IEEE Transactions on Information Theory , vol. 60, no. 11, pp. 7112–7139, 2014

2014
[196]

Consumption factor and power-efficiency factor: A theory for evaluating the energy efficiency of cascaded communi- cation systems,

J. N. Murdock et al., “Consumption factor and power-efficiency factor: A theory for evaluating the energy efficiency of cascaded communi- cation systems,” IEEE Journal on Selected Areas in Communications , vol. 32, no. 2, pp. 221–236, 2014

2014
[197]

Study on network energy savings for NR,

“Study on network energy savings for NR,” 3GPP, Tech. Rep. TR 38.864, 2025

2025
[198]

Energy efficient massive mimo array configura- tions,

H. Halbauer et al. , “Energy efficient massive mimo array configura- tions,” in 2018 IEEE Globecom Workshops (GC Wkshps) , 2018, pp. 1–6

2018
[199]

Energy and spectral efficiency tradeoff for massive MIMO systems with transmit antenna selection,

Z. Liu et al. , “Energy and spectral efficiency tradeoff for massive MIMO systems with transmit antenna selection,” IEEE Transactions on Vehicular Technology, vol. 66, no. 5, pp. 4453–4457, 2017

2017
[200]

Is massive MIMO energy efficient?

W. Liu et al. , “Is massive MIMO energy efficient?” 2015. [Online]. Available: https://arxiv.org/abs/1505.07187

2015 arXiv
[201]

High-efficiency, multi-mode, multi-band terminal power amplifiers,

E. McCune, “High-efficiency, multi-mode, multi-band terminal power amplifiers,” IEEE Microwave Magazine, vol. 6, no. 1, pp. 44–55, 2005

2005
[202]

Fundamental limits of cooperation,

A. Lozano et al. , “Fundamental limits of cooperation,” IEEE Trans. Inf. Theory, vol. 59, no. 9, pp. 5213–5226, Sept. 2013

2013
[203]

Holma et al

H. Holma et al. , 5G Technology - 3GPP Evolution to 5G-Advanced . Wiley, 2024

2024
[204]

TR 38.811; study on new radio (NR) to support non-terrestrial networks,

“TR 38.811; study on new radio (NR) to support non-terrestrial networks,” 2020

2020
[205]

TR 38.821; solutions for NR to support non-terrestrial networks (NTN),

“TR 38.821; solutions for NR to support non-terrestrial networks (NTN),” 2021

2021
[206]

5G from space: An overview of 3GPP non-terrestrial networks,

X. Lin et al. , “5G from space: An overview of 3GPP non-terrestrial networks,” IEEE Communications Standards Magazine , vol. 5, no. 4, pp. 147–153, 2021

2021
[207]

TS 38.300; NR; NR and NG-RAN overall description; stage-2,

“TS 38.300; NR; NR and NG-RAN overall description; stage-2,” 3GPP, Tech. Rep. TS 38.300, 2025

2025
[208]

A survey on nongeostationary satellite systems: The communication perspective,

H. Al-Hraishawi et al., “A survey on nongeostationary satellite systems: The communication perspective,” IEEE Communications Surveys & Tutorials, vol. 25, no. 1, pp. 101–132, 2023

2023
[209]

A survey of mobility management in non-terrestrial 5G networks: Power constraints and signaling cost,

A. Alsaeedy et al., “A survey of mobility management in non-terrestrial 5G networks: Power constraints and signaling cost,” IEEE Access , vol. 12, pp. 107 529–107 551, 2024

2024
[210]

Seamless handover in LEO based non-terrestrial networks: Service continuity and optimization,

F. Wang et al. , “Seamless handover in LEO based non-terrestrial networks: Service continuity and optimization,” IEEE Transactions on Communications, vol. 71, no. 2, pp. 1008–1023, 2023

2023
[211]

Synchronized RACH-less handover solution for LTE heterogeneous networks,

S. Barbera et al., “Synchronized RACH-less handover solution for LTE heterogeneous networks,” in 2015 International Symposium on Wireless Communication Systems (ISWCS) . IEEE, 2015, pp. 755–759

2015
[212]

Performance evaluation of the 5G NR conditional handover in leo-based non-terrestrial networks,

E. Juan et al. , “Performance evaluation of the 5G NR conditional handover in leo-based non-terrestrial networks,” in 2022 IEEE Wire- less Communications and Networking Conference (WCNC) , 2022, pp. 2488–2493

2022
[213]

Handover challenges in disaggregated open RAN for LEO satellites: tradeoff between handover delay and onboard processing,

S. Seeram et al. , “Handover challenges in disaggregated open RAN for LEO satellites: tradeoff between handover delay and onboard processing,” Frontiers in Space Technologies, vol. 6, p. 1580005, 2025

2025
[214]

Vision, requirements and evaluation guidelines for satellite radio interface(s) of imt-2020,

ITU-R, “Vision, requirements and evaluation guidelines for satellite radio interface(s) of imt-2020,” Report ITU-R M.2514-0 , 2022

2020
[215]

Role and evolution of non-terrestrial networks toward 6G systems,

A. Guidotti et al. , “Role and evolution of non-terrestrial networks toward 6G systems,” IEEE Access, vol. 12, pp. 55 945–55 963, 2024

2024
[216]

Convergence of the telecommunication systems with 5g and 6g,

F. Ronteix et al., “Convergence of the telecommunication systems with 5g and 6g,” Annales des Mines-Enjeux numériques , vol. 25, no. 1, pp. 147–156, 2024

2024
[217]

Multi-layer NTN architectures toward 6G: The ITA-NTN view,

A. Rago et al. , “Multi-layer NTN architectures toward 6G: The ITA-NTN view,” Computer Networks , vol. 254, p. 110725, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/ S1389128624005577

2024
[218]

Enabling effective multi-link data distribution in ntn-based 6g networks,

T. de Cola, “Enabling effective multi-link data distribution in ntn-based 6g networks,” in WSA & SCC 2023; 26th International ITG Workshop on Smart Antennas and 13th Conference on Systems, Communications, and Coding, 2023, pp. 1–5

2023
[219]

Multi-layered satellite communications systems for ultra-high availability and resilience,

M. Höyhtyä et al. , “Multi-layered satellite communications systems for ultra-high availability and resilience,” Electronics, vol. 13, no. 7, p. 1269, 2024

2024
[220]

Channel modeling and rate analysis of optical inter- satellite link (OISL),

B. Shang et al., “Channel modeling and rate analysis of optical inter- satellite link (OISL),” IEEE Transactions on Vehicular Technology , 2025

2025
[221]

(2023) Developing future optical high-capacity satellite

ESA. (2023) Developing future optical high-capacity satellite. [Online]. Available: https://connectivity.esa.int/ developing-future-optical-highcapacity-satellite

2023
[222]

Optical geo feeder link design,

N. Perlot et al. , “Optical geo feeder link design,” in 2012 Future Network & Mobile Summit (FutureNetw) , 2012, pp. 1–8

2012
[223]

5.12Gbps optical communication link between LEO satellite and ground station,

W. Chen et al. , “5.12Gbps optical communication link between LEO satellite and ground station,” in 2017 IEEE International Conference on Space Optical Systems and Applications (ICSOS) , 2017, pp. 260–263. 33

2017
[224]

D3.6 report on 3d multi layered ntn architecture,

“D3.6 report on 3d multi layered ntn architecture,” 6G NTN, Tech. Rep., May 2025

2025
[225]

Non-terrestrial networking for 6G: Evolution, opportunities, and future directions,

Wang et al. , “Non-terrestrial networking for 6G: Evolution, opportunities, and future directions,” 2024. [Online]. Available: https://arxiv.org/abs/2412.00820

2024 arXiv
[226]

White paper : Deployments of o-ran-based non-terrestrial networks,

“White paper : Deployments of o-ran-based non-terrestrial networks,” O-RAN alliance, Tech. Rep., 2025

2025
[227]

E. CSC. (2025, May) Converging Earth and Space: AI-Driven TN/NTN connectivity. [Online]. Available: https://connectivity.esa.int/ sites/default/files/ESA_AI_Driven_TN_NTN_Connectivity.pdf

2025
[228]

(2025) 6g-ntn project

6G-NTN. (2025) 6g-ntn project. [Online]. Available: https://6g-ntn.eu

2025
[229]

IRIS2, the new EU programme providing secure communica- tions via satellites,

ESA, “IRIS2, the new EU programme providing secure communica- tions via satellites,” 3GPP, Hefei, China, Tech. Rep. R2-2409400, Oct. 2024

2024
[230]

Study of further enhancement for disaggregated gnb,

“Study of further enhancement for disaggregated gnb,” 3GPP, Tech. Rep. TR 38.823, 2020

2020
[231]

NG-RAN; architecture description,

“NG-RAN; architecture description,” 3GPP, Tech. Rep. TS 38.401, 2025

2025
[232]

Ran functional splits in ntn: Architectures and challenges,

R. Campana et al. , “Ran functional splits in ntn: Architectures and challenges,” arXiv preprint arXiv:2309.14810 , 2023

2023 arXiv
[233]

A survey of the functional splits proposed for 5G mobile crosshaul networks,

L. Larsen et al. , “A survey of the functional splits proposed for 5G mobile crosshaul networks,” IEEE Communications Surveys & Tutorials, vol. 21, no. 1, pp. 146–172, 2019

2019
[234]

On the path to 6G: Embracing the next wave of low earth orbit satellite access,

X. Lin et al. , “On the path to 6G: Embracing the next wave of low earth orbit satellite access,” IEEE Communications Magazine , vol. 59, no. 12, pp. 36–42, 2022

2022
[235]

Transceiver design and performance analysis for lr-fhss-based direct-to-satellite iot,

S. Jung et al. , “Transceiver design and performance analysis for lr-fhss-based direct-to-satellite iot,” 2023. [Online]. Available: https://arxiv.org/abs/2305.13779

2023 arXiv
[236]

A Proposed Doppler Compen- sation Technique for Massive MIMO-LEO Satellite Communications,

Y . A. Mohammed and A. L. Mahmood, “A Proposed Doppler Compen- sation Technique for Massive MIMO-LEO Satellite Communications,” in 2024 IEEE 13th International Conference on Communication Sys- tems and Network Technologies (CSNT) , 2024, pp. 7–11

2024
[237]

High-mobility wideband massive mimo communications: Doppler compensation, analysis and scaling law,

W. Guo et al. , “High-mobility wideband massive mimo communications: Doppler compensation, analysis and scaling law,”
[238]

Embedded delay-doppler channel estimation for orthogonal time frequency space modulation,

P. Raviteja et al. , “Embedded delay-doppler channel estimation for orthogonal time frequency space modulation,” in 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 2018, pp. 1–5

2018
[239]

Study on GNSS resilient NR-NTN operation,

“Study on GNSS resilient NR-NTN operation,” 3GPP, Prague, Czech Republic, Tech. Rep. RP-251863, Jun. 2025

2025
[240]

(2010) Generic flexible payload technology

ESA. (2010) Generic flexible payload technology. [Online]. Available: https://www.esa.int/Applications/Connectivity_and_Secure_ Communications/Hylas/Generic_Flexible_Payload_technology

2010
[241]

Airbus flexible payload perspective,

G. Thomas et al. , “Airbus flexible payload perspective,” in 39th International Communications Satellite Systems Conference (ICSSC 2022), vol. 2022. IET, 2022, pp. 58–68

2022
[242]

D3.3 software defined payload and its scalability,

“D3.3 software defined payload and its scalability,” 6G NTN, Tech. Rep., Aug. 2024

2024
[243]

(2024) Reconfigurable digital beamforming network

ESA. (2024) Reconfigurable digital beamforming network. [Online]. Available: https://www.esa.int/Enabling_Support/Space_Engineering_ Technology/Reconfigurable_Digital_Beamforming_Network

2024
[244]

[Online]

(2025) Qudice. [Online]. Available: https://qudice.eu

2025
[245]

Satellite antenna radiation patterns for non-geostationary orbit satellite antennas operating in the fixed-satellite service below 30 GHz,

ITU-R, “Satellite antenna radiation patterns for non-geostationary orbit satellite antennas operating in the fixed-satellite service below 30 GHz,” Report ITU-R S.1528 , 2001

2001
[246]

TR 38.863; non-terrestrial networks (ntn) related rf and co-existence aspects,

“TR 38.863; non-terrestrial networks (ntn) related rf and co-existence aspects,” 2025

2025
[247]

Massive MIMO Transmission for LEO Satellite Com- munications,

L. You et al., “Massive MIMO Transmission for LEO Satellite Com- munications,” IEEE Journal on Selected Areas in Communications , vol. 38, no. 8, pp. 1851–1865, 2020

2020
[248]

Signal processing for high-throughput satel- lites: Challenges in new interference-limited scenarios,

A. I. Perez-Neira et al., “Signal processing for high-throughput satel- lites: Challenges in new interference-limited scenarios,” IEEE Signal Processing Magazine, vol. 36, no. 4, pp. 112–131, 2019

2019
[249]

Precoding in multibeam satellite communica- tions: Present and future challenges,

M. Á. Vázquez et al. , “Precoding in multibeam satellite communica- tions: Present and future challenges,” IEEE Wireless Communications, vol. 23, no. 6, pp. 88–95, 2016

2016
[250]

Linear precoding methods for multi-beam broadband satellite systems,

G. Taricco, “Linear precoding methods for multi-beam broadband satellite systems,” in European Wireless 2014; 20th European Wireless Conference, 2014, pp. 1–6

2014
[251]

Communication satellite power amplifiers: current and future sspa and twta technologies,

W. Q. Lohmeyer et al. , “Communication satellite power amplifiers: current and future sspa and twta technologies,” International Journal of Satellite Communications , vol. 34, no. 3, pp. 95–113, 2016

2016
[252]

TS 36.102; evolved universal terrestrial radio access (E-UTRA); user equipment (UE) radio transmission and reception for satellite access,

“TS 36.102; evolved universal terrestrial radio access (E-UTRA); user equipment (UE) radio transmission and reception for satellite access,” 3GPP, Tech. Rep. TS 36.102, 2025

2025
[253]

Satellite access node radio transmission and reception,

“Satellite access node radio transmission and reception,” 3GPP, Tech. Rep. TS 38.108, 2019

2019
[254]

TS 36.108; evolved universal terrestrial radio access (E-UTRA); satellite access node radio transmission and reception,

“TS 36.108; evolved universal terrestrial radio access (E-UTRA); satellite access node radio transmission and reception,” 3GPP, Tech. Rep. TS 36.108, 2025

2025
[255]

FCC Notice of Proposed lemaking, “Single Network Future: Supplemental Coverage from Space, Space Innovation, Notice of Pro- posed lemaking

“FCC Notice of Proposed lemaking, “Single Network Future: Supplemental Coverage from Space, Space Innovation, Notice of Pro- posed lemaking”.” [Online]. Available: https://www.fcc.gov/document/ fcc-proposes-framework-facilitate-supplemental-coverage-space-0
[256]

Spectrum opportunities for the wireless future: From direct-to-device satellite applications to 6g cellular,

T. S. Rappaport et al. , “Spectrum opportunities for the wireless future: From direct-to-device satellite applications to 6g cellular,”
[257]

The road to next-generation multiple access: A 50-year tutorial review,

Y . Liu et al., “The road to next-generation multiple access: A 50-year tutorial review,” Proceedings of the IEEE , vol. 112, no. 9, pp. 1100– 1148, 2024

2024
[258]

Analysis and simulation of a digital mobile channel using orthogonal frequency division multiplexing,

L. Cimini, “Analysis and simulation of a digital mobile channel using orthogonal frequency division multiplexing,” IEEE Transactions on Communications, vol. 33, no. 7, pp. 665–675, 1985

1985
[259]

Nonorthogonal multiple access for 5g and beyond,

Y . Liu et al. , “Nonorthogonal multiple access for 5g and beyond,” Proceedings of the IEEE , vol. 105, no. 12, pp. 2347–2381, 2017

2017
[260]

Non-orthogonal multiple access (NOMA): Concept, performance evaluation and experimental trials,

A. Benjebbour et al. , “Non-orthogonal multiple access (NOMA): Concept, performance evaluation and experimental trials,” in 2015 International Conference on Wireless Networks and Mobile Communi- cations (WINCOM), 2015, pp. 1–6

2015
[261]

A primer on rate-splitting multiple access: Tutorial, myths, and frequently asked questions,

B. Clerckx et al., “A primer on rate-splitting multiple access: Tutorial, myths, and frequently asked questions,” IEEE Journal on Selected Areas in Communications , vol. 41, no. 5, pp. 1265–1308, 2023

2023
[262]

5G field trials: OFDM-based waveforms and mixed numerologies,

P. Guan et al. , “5G field trials: OFDM-based waveforms and mixed numerologies,” IEEE Journal on Selected Areas in Communications , vol. 35, no. 6, pp. 1234–1243, 2017

2017
[263]

OFDM numerology design for 5G new radio to support iot, embb, and mbsfn,

A. A. Zaidi et al. , “OFDM numerology design for 5G new radio to support iot, embb, and mbsfn,” IEEE Communications Standards Magazine, vol. 2, no. 2, pp. 78–83, 2018

2018
[264]

A preliminary study on waveform candidates for 5G mobile radio communications above 6 GHz,

——, “A preliminary study on waveform candidates for 5G mobile radio communications above 6 GHz,” in 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring) , 2016, pp. 1–6

2016
[265]

Physical channels and modulation,

“Physical channels and modulation,” 3GPP, Tech. Rep. TS 38.211 v 18.6.0, Mar. 2025

2025
[266]

Generalized frequency division multiplexing for 5th generation cellular networks,

N. Michailow et al., “Generalized frequency division multiplexing for 5th generation cellular networks,” IEEE Transactions on Communica- tions, vol. 62, no. 9, pp. 3045–3061, 2014

2014
[267]

Signal stcture of the starlink ku-band downlink,

T. E. Humphreys et al. , “Signal stcture of the starlink ku-band downlink,” IEEE Transactions on Aerospace and Electronic Systems , vol. 59, no. 5, pp. 6016–6030, 2023

2023
[268]

Multiple access techniques for intelligent and multifunctional 6G: Tutorial, survey, and outlook,

B. Clerckx et al. , “Multiple access techniques for intelligent and multifunctional 6G: Tutorial, survey, and outlook,” Proceedings of the IEEE, vol. 112, no. 7, pp. 832–879, 2024

2024
[269]

Resource allocation design for next-generation multiple access: A tutorial overview,

Z. Wei et al., “Resource allocation design for next-generation multiple access: A tutorial overview,” Proceedings of the IEEE , vol. 112, no. 9, pp. 1230–1263, 2024

2024
[270]

Modulation and coding for NOMA and RSMA,

H. Jafarkhani et al., “Modulation and coding for NOMA and RSMA,” Proceedings of the IEEE , vol. 112, no. 9, pp. 1179–1213, 2024

2024
[271]

OTFS—a mathematical foundation for communication and radar sensing in the delay-doppler domain,

S. K. Mohammed et al. , “OTFS—a mathematical foundation for communication and radar sensing in the delay-doppler domain,” IEEE BITS the Information Theory Magazine , vol. 2, no. 2, pp. 36–55, 2022

2022
[272]

OTFS—predictability in the delay-doppler domain and its value to communication and radar sensing,

——, “OTFS—predictability in the delay-doppler domain and its value to communication and radar sensing,” IEEE BITS the Information Theory Magazine, vol. 3, no. 2, pp. 7–31, 2023

2023
[273]

Windowed OFDM for small-cell 5G uplink,

D. Mattera et al. , “Windowed OFDM for small-cell 5G uplink,” Physical Communication, 2020

2020
[274]

Filtered multitone modulation for very high- speed digital subscriber lines,

G. Chebini et al. , “Filtered multitone modulation for very high- speed digital subscriber lines,” IEEE Journal on Selected Areas in Communications, vol. 20, no. 5, pp. 1016–1028, 2002

2002
[275]

Multicarrier waveform candidates for beyond 5G,

B. Khan et al. , “Multicarrier waveform candidates for beyond 5G,” in 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) , 2020, pp. 1–6

2020
[276]

Interference channels,

A. Carleial, “Interference channels,” IEEE Transactions on Information Theory, vol. 24, no. 1, pp. 60–70, 1978

1978
[277]

A case where interference does not reduce capacity (corresp.),

——, “A case where interference does not reduce capacity (corresp.),” IEEE Transactions on Information Theory, vol. 21, no. 5, pp. 569–570, 1975

1975
[278]

A new achievable rate region for the interference channel,

T. Han et al. , “A new achievable rate region for the interference channel,” IEEE Transactions on Information Theory , vol. 27, no. 1, pp. 49–60, 1981

1981
[279]

Gaussian interference channel capacity to within one bit,

R. H. Etkin et al. , “Gaussian interference channel capacity to within one bit,” IEEE Transactions on Information Theory , vol. 54, no. 12, pp. 5534–5562, 2008. 34

2008
[280]

A rate-splitting approach to the gaussian multiple- access channel,

B. Rimoldi et al., “A rate-splitting approach to the gaussian multiple- access channel,” IEEE Transactions on Information Theory , vol. 42, no. 2, pp. 364–375, 1996

1996
[281]

Trends in channel coding for 6G,

S. Miao et al., “Trends in channel coding for 6G,” Proceedings of the IEEE, vol. 112, no. 7, pp. 653–675, 2024

2024
[282]

Rate splitting for MIMO wireless networks: a promising phy-layer strategy for lte evolution,

B. Clerckx et al. , “Rate splitting for MIMO wireless networks: a promising phy-layer strategy for lte evolution,” IEEE Communications Magazine, vol. 54, no. 5, pp. 98–105, 2016

2016
[283]

Rate splitting multiple access (rsma) for multi-user MIMO - enhancement of unicast and joint unicast/multicast delivery,

BBC, “Rate splitting multiple access (rsma) for multi-user MIMO - enhancement of unicast and joint unicast/multicast delivery,” 3GPP TSG RAN, Tech. Rep. RP-231938, Sep. 2023

2023
[284]

Lattice codes achieve the capacity of common message gaussian broadcast channels with coded side information,

L. Natarajan et al. , “Lattice codes achieve the capacity of common message gaussian broadcast channels with coded side information,”
[285]

Zak-otfs for identification of linear time-varying systems,

D. Nisar et al. , “Zak-otfs for identification of linear time-varying systems,” 2025. [Online]. Available: https://arxiv.org/abs/2503.18900

2025 arXiv
[286]

Otfs - orthogonal time frequency space,

A. Monk et al. , “Otfs - orthogonal time frequency space,” 2016. [Online]. Available: https://arxiv.org/abs/1608.02993

2016 arXiv
[287]

Orthogonal time frequency space modulation,

R. Hadani et al. , “Orthogonal time frequency space modulation,” in 2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017, pp. 1–6

2017
[288]

Otfs vs. ofdm in the presence of sparsity: A fair comparison,

L. Gaudio et al. , “Otfs vs. ofdm in the presence of sparsity: A fair comparison,” IEEE Transactions on Wireless Communications, vol. 21, no. 6, pp. 4410–4423, 2021

2021
[289]

MIMO-OTFS in high-doppler fading channels: Signal detection and channel estimation,

M. Kollengode Ramachandran et al. , “MIMO-OTFS in high-doppler fading channels: Signal detection and channel estimation,” in 2018 IEEE Global Communications Conference (GLOBECOM) , 2018, pp. 206–212

2018
[290]

Efficient modulation for band-limited channels,

G. Forney et al. , “Efficient modulation for band-limited channels,” IEEE Journal on Selected Areas in Communications , vol. 2, no. 5, pp. 632–647, 1984

1984
[291]

Bandwidth efficient and rate-matched low-density parity-check coded modulation,

G. Böcherer et al., “Bandwidth efficient and rate-matched low-density parity-check coded modulation,” IEEE Transactions on Communica- tions, vol. 63, no. 12, pp. 4651–4665, 2015

2015
[292]

An overview of the atsc 3.0 physical layer specification,

L. Fay et al., “An overview of the atsc 3.0 physical layer specification,” IEEE Transactions on Broadcasting, vol. 62, no. 1, pp. 159–171, 2016

2016
[293]

Comparison of geometric and probabilistic shaping with application to atsc 3.0,

F. Steiner et al. , “Comparison of geometric and probabilistic shaping with application to atsc 3.0,” in SCC 2017; 11th International ITG Conference on Systems, Communications and Coding , 2017, pp. 1–6

2017
[294]

A coherent digital amplitude and phase modu- lation scheme,

C. Campopiano et al., “A coherent digital amplitude and phase modu- lation scheme,” IRE Transactions on Communications Systems, vol. 10, no. 1, pp. 90–95, 1962

1962
[295]

Supporting probabilistic constellation shaping in 5G-NR evolution,

S. Hu et al., “Supporting probabilistic constellation shaping in 5G-NR evolution,” IEEE Transactions Wireless on Communications, no. 4, pp. 3586–3599, Apr. 2024

2024
[296]

Outage simulations for digital microwave radio systems with trellis-coded modulation,

C. Carlisle et al. , “Outage simulations for digital microwave radio systems with trellis-coded modulation,” in IEEE International Confer- ence on Communications, World Prosperity Through Communications,, 1989, pp. 1020–1024 vol.2

1989
[2017]

Available: https://arxiv.org/abs/1509.01332

[Online]. Available: https://arxiv.org/abs/1509.01332

arXiv
[2018]

Available: https://arxiv.org/abs/1807.07438

[Online]. Available: https://arxiv.org/abs/1807.07438

arXiv
[2024]

Available: https://arxiv.org/abs/2404.04753

[Online]. Available: https://arxiv.org/abs/2404.04753

arXiv
[2025]

Available: https://arxiv.org/abs/2506.18672

[Online]. Available: https://arxiv.org/abs/2506.18672

Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.

[1] [17]

Real-time deployment aspects of c-band and millimeter-wave 5G-NR systems,

M. Shafi et al. , “Real-time deployment aspects of c-band and millimeter-wave 5G-NR systems,” in ICC 2020 - 2020 IEEE Inter- national Conference on Communications (ICC) , 2020, pp. 1–7

2020

[2] [1]

On the roots of wireless communications,

A. Antoniou, “On the roots of wireless communications,” IEEE Circuits and Systems Magazine , vol. 11, no. 1, pp. 14–25, 2011

2011

[3] [2]

One Hundred Years of Radio,

L. J. Greenstein, “One Hundred Years of Radio,” Presentation at the Centenary of Radio, Redbank NJ, USA, 1999, http://www.winlab.tgers. edu/archive/Marconi\%20Day/Greenstein.pdf

1999

[4] [3]

Recent Development of 5G-Advanced in 3GPP: Commercial Needs and A Bridge to 6G,

W. Chen et al. , “Recent Development of 5G-Advanced in 3GPP: Commercial Needs and A Bridge to 6G,” submitted to IEEE Com- munications Magazine, 2024

2024

[5] [4]

5G-Advanced toward 6G: Past, present, and future,

——, “5G-Advanced toward 6G: Past, present, and future,” IEEE Journal on Selected Areas in Communications, vol. 41, no. 6, pp. 1592– 1619, 2023

2023

[6] [5]

IEEE proceedings special issue next generation multiple access,

“IEEE proceedings special issue next generation multiple access,” vol. 12, no. 9, Sep. 2024

2024

[7] [6]

The road to 6G: Driving the next wave of connectivity–part II access,

“The road to 6G: Driving the next wave of connectivity–part II access,” Proceedings of the IEEE , 2025

2025

[8] [7]

6G wireless networks: Vision, requirements, archi- tecture, and key technologies,

Z. Zhang et al. , “6G wireless networks: Vision, requirements, archi- tecture, and key technologies,” IEEE Vehicular Technology Magazine, vol. 14, no. 3, pp. 28–41, 2019

2019