Unveiling the Potential of NOMA: A Journey to Next Generation Multiple Access

Adeel Ahmed; Ammar Hawbani; Arumugam Nallanathan; Derrick Wing Kwan Ng; Hina Tabassum; Muhammad Umar Farooq Qaisar; Naofal Al-Dhahir; Wang Xingfu; Weijie Yuan; Yuanwei Liu

REVIEW 4 major objections 7 minor 299 references

Unveiling the Potential of NOMA: A Journey to Next Generation Multiple Access

T0 review · 4 major / 7 minor · reviewed 2026-08-11 · deepseek-v4-flash

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Pith's one-line read This survey argues that NOMA, by letting many users share the same radio resource through power or code separation, is the leading candidate for 6G's next-generation multiple access.

desk verdict A genuinely comprehensive NOMA survey whose 'frontrunner' claim is weakened by a NOMA-only selection filter; worth refereeing as a survey, but the comparative claims need major tempering. read the letter →

arxiv 2412.17160 v1 pith:C536KSJE submitted 2024-12-22 cs.IT eess.SPmath.IT

Adeel Ahmed , Wang Xingfu , Ammar Hawbani , Weijie Yuan , Hina Tabassum , Yuanwei Liu , Muhammad Umar Farooq Qaisar , Zhiguo Ding

show 3 more authors

Naofal Al-Dhahir Arumugam Nallanathan Derrick Wing Kwan Ng

This is my paper · ORCID

classification cs.ITeess.SPmath.IT

keywords non-orthogonalmultipleaccessnext-generation6Gnetworksmassiveconnectivitysuccessiveinterferencecancellationpower-domainNOMAcode-domainrate-splitting

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This survey sets out to establish that non-orthogonal multiple access (NOMA), not its competitors, is the leading candidate for next-generation multiple access (NGMA) in 6G. The audience is anyone deciding where to invest research or standardization effort: the 6G vision of trillions of connected devices requires an access scheme that can serve far more users than orthogonal resource slots allow. The survey's case rests on NOMA's defining move, letting many users share the same time-frequency-code resource, separated by power (power-domain NOMA) or by sparse and overlapping codes (code-domain NOMA), and on the argument that this is exactly what overloaded, rank-deficient 6G scenarios demand. It compiles roughly three hundred papers to show what NOMA has delivered, what it is providing in areas like reconfigurable intelligent surfaces, UAVs, integrated sensing and communications, and terahertz networks, and what design guidelines follow.

What carries the argument

The load-bearing mechanism is non-orthogonal resource sharing. In power-domain NOMA, the base station superimposes user signals with distinct power coefficients and each receiver applies successive interference cancellation (SIC), decoding stronger users' signals first and subtracting them; in code-domain NOMA, users are separated by sparse or low-cross-correlation spreading sequences (SCMA, PDMA, MUSA, and others) with message-passing or SIC-based multiuser detection. The same resource block can therefore carry many users, which is the property the paper points to for massive connectivity, relaxed channel feedback, and grant-free low-latency uplink access.

What would settle it

Run a head-to-head system-level comparison of NOMA and rate-splitting multiple access (RSMA) in the same overloaded, rank-deficient cell with imperfect CSI and equal total power, counting supported users, sum rate, and latency; if RSMA serves more users or achieves a higher sum rate under those conditions, the paper's frontrunner claim does not survive.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central claim is that NOMA is the frontrunner for NGMA because it is the multiple-access scheme best matched to 6G's defining condition: a massive number of devices competing for scarce, often rank-deficient radio resources. The paper argues that by superposing users in the power domain (with successive interference cancellation at receivers) or by spreading users with non-orthogonal low-correlation codes, NOMA removes the strict limit that orthogonal access imposes on simultaneous connections, cuts access latency through grant-free uplink transmission, and remains compatible with the main 6G enabling technologies. The survey presents this not as a marginal improvement over orthogonal multiple access but as a capacity-relevant shift: superposition coding and successive interference cancellation are capacity-achieving in single-antenna broadcast and multiple-access channels, and the overloaded regime is precisely where the paper says NOMA outperforms OMA and where 6G will live.

Load-bearing premise

The conclusion that NOMA is the frontrunner would collapse if the surveyed literature were chosen without a NOMA-centric filter, because papers that frame their results around competing schemes were largely left out of the comparison.

Editorial extensions

If this is right

Standardization of 6G multiple access would be justified in building on NOMA, building on the multiuser superposition transmission already included in 3GPP Release 15.
Network designs for massive IoT, URLLC, RIS, UAV, terahertz, and ISAC would treat NOMA as the default access layer rather than as an add-on.
Grant-free uplink NOMA would become a primary mechanism for meeting sub-1 ms latency targets in machine-type traffic.
Design effort should concentrate on SIC robustness, CSI acquisition, and user pairing and power allocation, since these are the points where the non-orthogonal gain is won or lost.

Reading between the lines

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

Editorial inference (not a paper claim): because the survey's literature filter starts from papers that use 'NOMA' in the title, its 'frontrunner' verdict may overstate NOMA's margin; a neutral meta-review would likely narrow the gap with rate-splitting multiple access, which the paper itself notes collapses to NOMA or SDMA at interference extremes.
Editorial inference (not a paper claim): the same non-orthogonal machinery that NOMA uses for massive access could be tested as a short-packet enabler in the finite-blocklength regime, which the paper flags as open.
Editorial inference (not a paper claim): a practical test would be to implement a two-user SIC decoder in a real testbed with imperfect CSI and measure the error-propagation floor, since the paper acknowledges SIC error propagation as a weakness.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

Two things to know. First, this is a survey, not a research paper, so judge it as one. Second, the useful core is real: the paper organizes a large body of NOMA work—variants, fundamental operations, and interplay with MIMO, RIS, ISAC, THz, UAVs, and the rest—into a reasonably navigable structure. The tables comparing prior surveys are helpful, and the 2022–2024 references bring the coverage up to date. The basic NOMA equations and the qualitative descriptions of code-domain variants are standard and correctly stated. If you need a one-stop entry point into the NOMA literature for 6G, this does that job.

The soft spots are in proportion. The load-bearing claim that NOMA is the 'frontrunner' for NGMA is not supported by the evidence as selected. Section I.C lists fifteen criteria, and every one of them requires NOMA in the title or NOMA-framed content. Papers that compare NOMA unfavorably to RSMA or SDMA, or that treat another scheme as the better candidate, are systematically excluded unless they happen to frame their title around NOMA. That is a real selection bias, and the stress-test note is right. The treatment of RSMA is illustrative: it is dismissed with phrases like 'higher encoding complexity, higher signalling burden, and higher optimization burden' with no citation and no quantitative comparison. The 'rank-deficient scenarios' claim in Section I is asserted without a theorem, simulation, or comparative citation. So the survey shows that NOMA has been extensively studied and works well in many settings. It does not show NOMA is the frontrunner over the named alternatives.

There is also a broader editing problem. The text has typos and incomplete sentences (e.g., the stray '9 10' in Section II.A, the duplicated 'analysis.' entries in Table II). These are fixable, but they are numerous enough that the paper reads as unpolished.

Who is this for? A graduate student or researcher new to NOMA who wants a structured map of the field and a bibliography. It is less useful for someone trying to decide between NOMA and RSMA as a 6G candidate.

My recommendation: send it to peer review, but as a survey that must be revised. The authors should either temper the 'frontrunner' language to something like 'a promising candidate' or add a genuinely neutral comparison with RSMA and other NGMA contenders. As it stands, the central interpretive claim overreaches the evidence base.

Referee Report

4 major / 7 minor

Summary. This paper is a survey of non-orthogonal multiple access (NOMA) positioned as the 'frontrunner' for next-generation multiple access (NGMA) in 6G. It reviews NOMA variants (PD-NOMA and CD-NOMA), fundamental downlink/uplink operations, key enabling technologies (multi-antenna systems, artificial intelligence, URLLC, terahertz, cooperative communications, backscatter, RIS, cognitive radio, MEC, ISAC, VLC, non-terrestrial networks), research trends, challenges, design recommendations, and future perspectives. The survey claims to have reviewed approximately 300 papers using fifteen NOMA-centric selection criteria and compares its scope with prior surveys via Tables II and III.

Significance. If the 'frontrunner' claim were convincingly supported, this survey would serve as a valuable synthesis of NOMA's role in 6G and a useful entry point for researchers. The paper's strength is its breadth: it catalogs many NOMA variants and their interplays with a wide set of technologies, and the state-of-the-art tables provide a convenient reference. However, the survey contains no new technical derivations or data, and its central comparative claim is not backed by a neutral evidence base. Its significance is therefore conditional on the authors revising the framing and methodology to adequately support the headline conclusion.

major comments (4)

[Section I.C] The selection methodology in Section I.C is inherently NOMA-centric: all fifteen criteria (e.g., 'NOMA' in the title, NOMA resource allocation, learning-enabled NOMA, multi-antenna NOMA) require papers to be framed around NOMA. Comparative studies that evaluate NOMA against RSMA, SDMA, or OMA are systematically excluded unless they happen to use 'NOMA' in the title. This biases the evidence base for the paper's central claim (Abstract; Section I.A; Section I.E) that NOMA is 'the frontrunner' for NGMA. The treatment of RSMA in Section I.B.2 illustrates the problem: RSMA's disadvantages ('higher encoding complexity, higher signalling burden, and higher optimization burden') are stated without citation, and no quantitative rate-region or complexity comparison is provided. Please either broaden the selection to include comparative literature and provide a meta-analysis, or revise the claim to 'a promising candidate' with an explicit caveat about the NOMA-centric selection.
[Section I.A] The bullet list of NOMA advantages includes 'Massive connectivity' with the assertion that 'NOMA is capable of significantly increasing the number of simultaneous connections in rank-deficient scenarios; hence, it has the potential to support massive connectivity.' This load-bearing claim is asserted without a theorem, simulation, or citation to a comparative study. The adjacent bullet on 'Relaxed channel feedback' similarly states a benefit with no supporting reference. Since these advantages motivate the entire survey, each should be supported by a cited analysis or explicitly flagged as a research hypothesis.
[Section I.B.2-I.B.5] Candidate NGMA techniques (RSMA, SDMA, LDMA, FAMA) are described with brief qualitative advantages and disadvantages, but no structured comparison (e.g., a table of overloading capability, CSI sensitivity, SIC complexity, or standardization status) is provided. Given the paper's claim that NOMA is the frontrunner, the absence of a quantitative or at least systematic comparison with the named alternatives leaves the central argument largely anecdotal. Please add a comparative table or a synthesis section that evaluates all candidates on common metrics.
[Section I.C] The survey states that 'approximately three hundred papers' were reviewed, but the methodology does not describe database sources, search strings, inclusion/exclusion decisions, or a quality assessment. The fifteen criteria are broad and overlapping, and no PRISMA-style flow diagram is given. This lack of reproducibility makes it difficult for readers to verify the 'comprehensive' claim in Tables II and III, and it compounds the selection-bias concern raised above.

minor comments (7)

[Section II.A] The text contains a stray '9 10' immediately before 'Multiple user's signals are superimposed,' which appears to be a leftover footnote reference and should be removed.
[Table IV] The header 'CHARACTERISRTICS' is misspelled; it should read 'CHARACTERISTICS.'
[Section II.B.12] In the IGMA subsection, the sentence 'Sparse mapping based on In contrast to the requirement...' is grammatically broken and appears to have missing words.
[Section III.G] The last sentence of Section III.G ends mid-word: '...combined them with the DQN algo rith'. Please complete this sentence.
[Equation (6)] The free-space path loss formula has a minus sign, making FSPL negative, and uses 'demotes' instead of 'denotes'; typically FSPL(dB) is positive, e.g., 20 log10(4π f d0 / c). Please correct the sign and the typo.
[Table VIII] The table has duplicate 'Main Findings' column headers; one should be renamed to reflect the different content (e.g., 'Optimization Techniques').
[Figure 1] The caption calls Fig. 1 'A world map of 6G research and development hotspots,' but the figure appears to be a text list of projects rather than a map.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the survey's frontrunner claim is an advocacy thesis, and the technical content is self-contained; only minor non-load-bearing self-citations appear.

full rationale

This paper is a survey/position paper rather than a first-principles derivation, so the circularity patterns involving fitted parameters or exact-equation equivalences do not arise. The central claim ('NOMA as the frontrunner for NGMA') is an evaluative thesis supported by a NOMA-centric literature selection, not by an equation fitted to data. The concrete technical content, such as the two-user NOMA rate expressions (Eqs. 1–4) and the superposition-coding/SIC capacity-region statements, is standard and externally checkable; the capacity-achieving assertions are backed by classical superposition-coding capacity-region results, not solely by the authors' own work. The paper does contain several self-citations (notably [27], [37], and [97]) used to frame the survey and to state that NOMA-centric NGMA research has been initiated, but these claims also carry external citations or are standard results, so the self-citations are not load-bearing. One flagged limitation is methodological rather than circular: the selection criteria in Section I.C restrict the reviewed corpus to NOMA-framed papers, which weakens the external comparison behind the 'frontrunner' conclusion; however, the conclusion is not entailed by the inclusion criteria, so this is an evidentiary bias, not a circular equivalence. The unsupported assertion that NOMA 'significantly increases simultaneous connections in rank-deficient scenarios' (Section I.A) is a support gap, not a circular step. Overall, there is no specific reduction, equation, or fitted parameter that makes the survey's results equivalent to its inputs by construction.

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

No free parameters or invented entities; the survey makes no quantitative predictions. It relies on standard information-theoretic results and domain assumptions about 6G requirements.

assumptions (3)

standard math Superposition coding with SIC achieves the capacity region of the scalar broadcast and multiple access channels.
Taken from the information-theoretic literature [28], [29] as summarized in Section II-A.
domain assumption 6G will require massive connectivity (up to 10 million devices per square kilometer) and ultra-low latency.
Stated in Section I as the basis for why NGMA is needed.
domain assumption The surveyed papers are representative of the state of NOMA research.
The selection criteria in Section I.C assume the chosen literature is sufficient to draw the frontrunner conclusion.

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Cite this review

Pith. "Pith review of Unveiling the Potential of NOMA: A Journey to Next Generation Multiple Access." pith.science (2026). https://pith.science/paper/C536KSJE

@misc{pith2026241217160,
  author       = {Pith},
  title        = {Pith review of: Unveiling the Potential of NOMA: A Journey to Next Generation Multiple Access},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/C536KSJE}},
  note         = {Machine review of arXiv:2412.17160}
}

read the original abstract

Revolutionary sixth-generation wireless communications technologies and applications, notably digital twin networks (DTN), connected autonomous vehicles (CAVs), space-air-ground integrated networks (SAGINs), zero-touch networks, industry 5.0, and healthcare 5.0, are driving next-generation wireless networks (NGWNs). These technologies generate massive data, requiring swift transmission and trillions of device connections, fueling the need for sophisticated next-generation multiple access (NGMA) schemes. NGMA enables massive connectivity in the 6G era, optimizing NGWN operations beyond current multiple access (MA) schemes. This survey showcases non-orthogonal multiple access (NOMA) as NGMA's frontrunner, exploring What has NOMA delivered?, What is NOMA providing?, and What lies ahead?. We present NOMA variants, fundamental operations, and applicability in multi-antenna systems, machine learning, reconfigurable intelligent surfaces (RIS), cognitive radio networks (CRN), integrated sensing and communications (ISAC), terahertz networks, and unmanned aerial vehicles (UAVs). Additionally, we explore NOMA's interplay with state-of-the-art wireless technologies, highlighting its advantages and technical challenges. Finally, we unveil NOMA research trends in the 6G era and provide design recommendations and future perspectives for NOMA as the leading NGMA solution for NGWNs.

Figures

Figures reproduced from arXiv: 2412.17160 by the authors.

**Figure 2.** Paper outline diagram with hierarchical sections and sub-sections. [PITH_FULL_IMAGE:figures/full_fig_p013_2.png] view at source ↗

**Figure 3.** Illustration of NOMA transmission; (a) Power domain multiplexing of two users’s signals in same time/frequency [PITH_FULL_IMAGE:figures/full_fig_p014_3.png] view at source ↗

Figures from the paper (16 more)

**Figure 4.** Figure 4: A comparative representation of different code domain NOMA schemes. [PITH_FULL_IMAGE:figures/full_fig_p017_4.png]

**Figure 6.** Figure 6: An illustration of LDS-SVE. A vector’s dimension corresponds to the resources in a group. Each individual element within the vector is associated with a distinct resource within a designated resource group [135]. 8) Low-Density Spreading Signature Vector Extension (LDS…

**Figure 7.** Figure 7: A typical transmission structure of SCMA with six [PITH_FULL_IMAGE:figures/full_fig_p019_7.png]

**Figure 8.** Figure 8: 12) Interleave Grid Multiple Access (IGMA): IGMA leverages the integration of bit-level interleaving and symbollevel sparse grid mapping as a means to improve the overall efficiency of the entire network. In the IGMA framework, Channel Compensation UE 1 UE Channel Co…

**Figure 9.** Figure 9: (a) IGMA transmitter and grid mapping; (b) LCRS transmission scheme; (c) The transmission structure of single-carrier [PITH_FULL_IMAGE:figures/full_fig_p020_9.png]

**Figure 10.** Figure 10: The block diagram of transmitter and receiver of LDS-OFDM. [PITH_FULL_IMAGE:figures/full_fig_p021_10.png]

**Figure 11.** Figure 11: Building block sparse-constellation based orthogonal [PITH_FULL_IMAGE:figures/full_fig_p021_11.png]

**Figure 12.** Figure 12: The transmission structure of IDMA with K multi [PITH_FULL_IMAGE:figures/full_fig_p022_12.png]

**Figure 13.** Figure 13: Interplay of NOMA with other wireless communica [PITH_FULL_IMAGE:figures/full_fig_p022_13.png]

**Figure 14.** Figure 14: (a) Beamforming-based mMIMO-NOMA. (b) Cluster-based MIMO-NOMA. [PITH_FULL_IMAGE:figures/full_fig_p023_14.png]

**Figure 15.** Figure 15: NOMA-assisted FL in smart city. addition, utilizing a centralized training and distributed execution approach, the proposed approach not only acquired proficient decentralized policies but also alleviated the user’s computational load and exhibited satisfactory perfo…

**Figure 16.** Figure 16: UAV-relay aided cooperative NOMA transmission. [PITH_FULL_IMAGE:figures/full_fig_p031_16.png]

**Figure 17.** Figure 17: RIS assisted NOMA networks. maximum transmit power constraint, and successful decoding order constraint. In [290], the authors conducted an analysis of the BER performance of a NOMA-enhanced BackCom system with imperfect SIC. The mentioned research work focuses on der…

**Figure 18.** Figure 18: (a) NOMA-inspired integrated sensing and communications. (b) NOMA-inspired uplink integrated sensing and [PITH_FULL_IMAGE:figures/full_fig_p037_18.png]

**Figure 19.** Figure 19: NOMA assisted VLC. that VLC systems that use NOMA can provide greater spectral efficiency than their OMA counterparts. L. Non-Terrestrial Networks Non-Terrestrial networks (NTNs), which include UAVs, high altitude platforms (HAPS), and satellite networks, are traditio…

**Figure 20.** Figure 20: NOMA-based NTN [PITH_FULL_IMAGE:figures/full_fig_p039_20.png]

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[294]

On power minimization for irs-aided downlink noma systems,

H. Wang, C. Liu, Z. Shi, Y . Fu, and R. Song, “On power minimization for irs-aided downlink noma systems,” IEEE wireless communications letters, vol. 9, no. 11, pp. 1808–1811, 2020

2020
[295]

Power efficient irs-assisted noma,

J. Zhu, Y . Huang, J. Wang, K. Navaie, and Z. Ding, “Power efficient irs-assisted noma,” IEEE Trans. Commun., vol. 69, no. 2, pp. 900–913, 2021

2021
[296]

Exploiting benefits of IRS in wireless powered NOMA networks,

X. Li, Z. Xie, Z. Chu, V . G. Menon, S. Mumtaz, and J. Zhang, “Exploiting benefits of IRS in wireless powered NOMA networks,” IEEE Trans. Green Commun. and Net. , vol. 6, no. 1, pp. 175–186, 2022

2022
[297]

Sum rate maxi- mization for irs-assisted uplink noma,

M. Zeng, X. Li, G. Li, W. Hao, and O. A. Dobre, “Sum rate maxi- mization for irs-assisted uplink noma,” IEEE Commun. Lett. , vol. 25, no. 1, pp. 234–238, 2021

2021
[298]

Energy-efficient design of IRS-NOMA networks,

F. Fang, Y . Xu, Q.-V . Pham, and Z. Ding, “Energy-efficient design of IRS-NOMA networks,” IEEE Trans. Veh. Technol., vol. 69, no. 11, pp. 14 088–14 092, 2020

2020
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Energy- efficient IRS-aided NOMA beamforming for 6G wireless communi- cations,

A. Ihsan, W. Chen, M. Asif, W. U. Khan, Q. Wu, and J. Li, “Energy- efficient IRS-aided NOMA beamforming for 6G wireless communi- cations,” IEEE Trans. Green Commun. and Net. , vol. 6, no. 4, pp. 1945–1956, 2022

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On the performance of multi-antenna IRS-assisted NOMA networks with continuous and discrete IRS phase shifting,

Z. Sun and Y . Jing, “On the performance of multi-antenna IRS-assisted NOMA networks with continuous and discrete IRS phase shifting,” IEEE Trans. Wireless Commun. , vol. 21, no. 5, pp. 3012–3023, 2022

2022

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.

[1] [1]

Multi-band Wireless Networks: Architectures, Challenges, and Comparative Analysis

M. A. Saeidi, H. Tabassum, and M.-S. Alouini, “Multi-band wireless networks: Architectures, challenges, and comparative analysis,” arXiv preprint arXiv:2212.07606, 2022

work page Pith review arXiv 2022

[2] [2]

Ee-tar: Energy efficient and thermal aware routing protocol for software defined wireless body area networks,

A. Ahmed, X. Wang, A. Hawbani, M. U. Farooq, T. Qureshi, and S. Ullah, “Ee-tar: Energy efficient and thermal aware routing protocol for software defined wireless body area networks,” in 2020 IEEE 8th International Conference on Information, Communication and Networks (ICICN), 2020, pp. 51–55

2020

[3] [3]

Vehicle communication network in intelligent transportation system based on internet of things,

H. Zhang and X. Lu, “Vehicle communication network in intelligent transportation system based on internet of things,” Computer Commu- nications, vol. 160, pp. 799–806, 2020

2020

[4] [4]

Navigating industry 5.0: A survey of key enabling technologies, trends, challenges, and opportunities,

R. Tallat, A. Hawbani, X. Wang, A. Al-Dubai, L. Zhao, Z. Liu, G. Min, A. Y . Zomaya, and S. H. Alsamhi, “Navigating industry 5.0: A survey of key enabling technologies, trends, challenges, and opportunities,” IEEE Communications Surveys & Tutorials , pp. 1–1, 2023

2023

[5] [5]

Potential of satellite- airborne sensing technologies for agriculture 4.0 and climate-resilient: A review,

A. I. Hazmy, A. Hawbani, X. Wang, A. Al-Dubai, A. Ghannami, A. A. Yahya, L. Zhao, and S. H. Alsamhi, “Potential of satellite- airborne sensing technologies for agriculture 4.0 and climate-resilient: A review,” IEEE Sensors Journal, vol. 24, no. 4, pp. 4161–4180, 2024

2024

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Agriculture digitalization: A global examination based on bibliometric analysis,

M. E. Latino, M. Menegoli, and A. Corallo, “Agriculture digitalization: A global examination based on bibliometric analysis,” IEEE Transac- tions on Engineering Management , vol. 71, pp. 1330–1345, 2024

2024

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Optimized data fusion with scheduled rest periods for enhanced smart agriculture via blockchain integration,

A. Ahmed, I. Parveen, S. Abdullah, I. Ahmad, N. Alturki, and L. Jamel, “Optimized data fusion with scheduled rest periods for enhanced smart agriculture via blockchain integration,” IEEE Access , vol. 12, pp. 15 171–15 193, 2024

2024

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A digital twin-assisted intelligent partial offloading approach for vehicular edge computing,

L. Zhao, Z. Zhao, E. Zhang, A. Hawbani, A. Y . Al-Dubai, Z. Tan, and A. Hussain, “A digital twin-assisted intelligent partial offloading approach for vehicular edge computing,” IEEE Journal on Selected Areas in Communications , vol. 41, no. 11, pp. 3386–3400, 2023

2023