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Advancements in UAV-based Integrated Sensing and Communication: A Comprehensive Survey

T0 review · 4 major / 5 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read This survey argues that UAV-based integrated sensing and communication can become a coherent backbone for 6G, and that the scattered literature on the topic can be organized into six recurring optimization problems.

desk verdict A serviceable but editorially sloppy survey of UAV-ISAC; the core content is useful, but the tables need a legend and the citations need a careful proofread before it can be trusted as a roadmap. read the letter →

arxiv 2501.06526 v1 pith:KD5KJHYZ submitted 2025-01-11 cs.ET cs.NIeess.SP

Manzoor Ahmed , Ali Arshad Nasir , Mudassir Masood , Kamran Ali Memon , Khurram Karim Qureshi , Feroz Khan , Wali Ullah Khan , Fang Xu
show 1 more author
Zhu Han
This is my paper · ORCID
classification cs.ETcs.NIeess.SP
keywords UAVintegratedsensingandcommunication6Gchannelestimationbeamtrackingphysicallayersecurityageofinformationenergyefficiency
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 UAV-based integrated sensing and communication (ISAC) is a coherent and promising path for 6G wireless networks, and that its many scattered results can be organized into a small set of recurring engineering problems. It reviews recent work on channel estimation, target and beam tracking, throughput maximization, weighted sum rate and sensing trade-offs, delay and age-of-information reduction, energy efficiency, and security. The survey's contribution is a structured map: it classifies each study by UAV role, sensing type and metric, optimization variables, and objective, and it draws cross-cutting lessons, most notably that trajectory and resource allocation must jointly balance sensing and communication because the sensing path suffers an inherent extra path loss. A sympathetic reader would take the survey's core claim to be a roadmap claim: these categories and open challenges define what is needed to build efficient, adaptive, and secure UAV-ISAC systems.

What carries the argument

The survey's load-bearing apparatus is its classification scheme: every reviewed study is placed into one of six optimization axes and then summarized across common dimensions, namely UAV role, number of UAVs and users, sensing type and sensing metric, CSI availability, methodology, optimization variables, and objective. This uniform table structure is what lets the survey claim a comparative view rather than an annotated list. Conceptually, the paper also uses the sensing-for-communication versus communication-for-sensing distinction, and monostatic, bistatic, and multistatic sensing geometries, as the physical basis for UAV sensing and as the starting point for its taxonomies.

What would settle it

A concrete check is to sample table entries and read the corresponding primary papers: for example, verify whether the rows marked with available CSI in Tables III through VIII actually assume full channel knowledge, and whether the cited method matches the table's stated objective and optimization variables. A specific test is the survey's attribution of a MARL-based method to reference [15], whose listed title concerns sensing and communication adaptation for an internet of drones; comparing that claim to the source paper would directly test the reliability of the survey's comparative claims.

Watch

Extended reading notes

Core claim

On its own terms, the central claim is that UAV-based ISAC can unify radar-like sensing and wireless communication on a single aerial platform, and that the research area has matured enough to be systematically assessed rather than merely listed. The discovery is an organizational synthesis: across the six thematic areas (channel estimation and beam tracking, throughput under sensing constraints, weighted sum rate and sensing trade-offs, delay and age of information, energy efficiency, and security), the survey argues that the dominant bottleneck is joint optimization of UAV trajectory, resource allocation, and beamforming under coupled sensing and communication constraints. It further claims that the sensing signal's extra reflection path loss creates a structural imbalance between the two functions, so any practical design must deliberately trade one against the other. The survey closes by identifying the open challenges it regards as decisive for real deployment: standardization, interference management, mobility management, security and privacy, cost and scalability, environmental adaptation, and the need for efficient algorithms.

Load-bearing premise

The survey's value as a roadmap depends on its summary tables faithfully representing each cited paper's system model, assumptions, and reported results; if any table entry misstates a paper's setup or objective, the comparative analysis built on those entries becomes unreliable.

Editorial extensions

If this is right

  • If UAV-ISAC delivers on its promise, 6G networks can reuse one spectrum allocation and one hardware chain for both radar-like sensing and communication, reducing cost, energy, and hardware redundancy relative to separate systems.
  • Trajectory optimization emerges as the central design lever: the survey's lessons point to user-distribution mapping and real-time trajectory adaptation as the main determinants of both throughput and sensing accuracy.
  • Because the sensing signal travels an extra reflected path, sensing and communication objectives are inherently imbalanced, so designs must explicitly optimize a trade-off such as weighted sum rate versus sensing accuracy, and no single schedule stays optimal across time slots.
  • Standardization and seamless integration with terrestrial and satellite networks are stated as prerequisites for actual deployment; the lack of globally harmonized protocols currently blocks interoperability and spectrum sharing.
  • Across all six areas, the survey identifies scalability, computational overhead, and adaptability to dynamic environments as the near-term research targets, with machine learning repeatedly proposed as the route to real-time adaptation.
  • The summary tables, if accurate, provide a ready-made comparative baseline: a new UAV-ISAC paper can locate its contribution by stating which sensing metric, which optimization variables, and which UAV role it addresses relative to the surveyed works.

Reading between the lines

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

  • The survey's own summaries repeatedly note that almost every cited method assumes available CSI; a natural extension is to test how these algorithms degrade under imperfect, delayed, or absent channel knowledge, which the paper flags only as a per-work limitation.
  • The recurrence of the same solver families (EKF-based tracking, successive convex approximation, deep reinforcement learning) across all six areas suggests that a shared software benchmark comparing these solvers on identical UAV-ISAC scenarios would be a high-value next step, one the survey does not itself propose.
  • The path-loss imbalance lesson implies a quantitative prediction: fixed-altitude or LoS-constrained UAV deployments should systematically underperform those that adapt altitude and trajectory in real time, a claim that could be tested by controlled simulations varying only the altitude adaptation policy.
  • The security section shows that many secrecy analyses assume the eavesdropper's CSI is available to the system; a practical extension would evaluate secrecy rates when the eavesdropper's channel is unknown, matching the more realistic threat model the survey says remains open.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 5 minor

Summary. The manuscript surveys UAV-based integrated sensing and communication (ISAC), organizing recent literature into six technical thrusts: channel estimation and beam/target tracking, throughput maximization under sensing constraints, weighted sum rate and sensing optimization, delay and age-of-information reduction, energy efficiency, and security enhancement. It provides taxonomy figures, comparative summary tables (Tables III–VIII), a positioning table of prior surveys (Table II), lessons learned, and a list of open challenges. The central claim is that the survey offers a comprehensive, up-to-date roadmap for designing efficient, adaptive, and secure UAV-ISAC systems.

Significance. If the survey's characterizations of the cited literature are faithful, it is a useful and timely synthesis: it covers a broad set of recent papers, organizes them by optimization objective, and offers a compact comparative apparatus that could help researchers locate relevant techniques. The lessons-learned section and the list of open challenges are sensible and largely consistent with the surveyed material. However, the survey's value is essentially secondary: it has no primary results, so its contribution rests entirely on the accuracy of its reported summaries and table entries. The specific errors and ambiguities identified below directly affect that load-bearing premise and must be addressed before the manuscript can serve as a reliable roadmap.

major comments (4)
  1. [Section III-C, Summary paragraph] The text states: "However, [15] employs MARL to enhance the adaptability of UAVs by optimizing bandwidth and sensing accuracy." Reference [15] is A. Hazarika and M. Rahmati, "Adaptnet: Rethinking sensing and communication for a seamless internet of drones experience," arXiv:2405.07318, whose title and content do not match the described MARL-based bandwidth and sensing optimization. This reference is also not cited in the body of Section III-C. This mis-citation is a concrete failure in the survey's secondary reporting. Please correct the citation or remove the sentence, and systematically audit all in-text citations against the referenced papers' actual contributions.
  2. [Tables III–VIII, CSI columns] Every CSI entry in Tables III–VII and the 'Eve's CSI' entries in Table VIII are marked 'Avail.' with no definition in any table legend or the text. The surveyed papers make materially different CSI assumptions (perfect, imperfect, statistical, or no CSI; CSI of legitimate links versus CSI of the eavesdropper), and flattening these into 'Avail.' obscures precisely the distinctions a comparative survey should expose. For Table VIII, it is particularly unclear whether 'Avail.' means the transmitter knows Eve's CSI, the legitimate users' CSI, or both. Define 'Avail.' explicitly and re-verify each table entry to reflect the source paper's actual assumptions.
  3. [Table II, row for [26]] The row for reference [26] contains eight symbols ('* * * × × × × ×') but the table has six coverage columns (CE/Target and Beam Tracking, System Throughput, WSR and Sensing, Delay, EE, Security). This misalignment makes the coverage comparison unreliable. Additionally, some rows use '***' and '**' while others use '*' and '**' with the legend placed below the table; please reformat so every row has exactly one mark per column and the legend is applied consistently.
  4. [Sections III-A, III-B, V; Table IV] There are multiple verbatim repeated sentences: the DIA/EKF beam-tracking sentence is duplicated in Section III-A, the OCDM-FMCW hardware-complexity sentence is duplicated in Section III-B, and the concluding sentence of Section V is repeated verbatim. In Table IV, row [74], the sensing metric column reads 'Range velocity estimation and', which is an incomplete fragment. Individually these are local errors, but their density in the sections that carry the survey's comparative content further undermines confidence in the accuracy of the summaries and should be corrected in a careful revision.
minor comments (5)
  1. [References [12] and [37]] References [12] and [37] are the same paper (Y. Zeng, Q. Wu, and R. Zhang, "Accessing from the sky: A tutorial on UAV communications for 5G and beyond," Proceedings of the IEEE, 2019). Please consolidate the duplicate reference.
  2. [Table III and Table I] The acronym 'VBO' appears in Table III (row [61]) but is not defined in Table I or the table legend. Please define it or spell it out.
  3. [Table III legend placement] The legend defining S-, M-, T&S, R&S, etc. appears after Table IV rather than with Table III, where those abbreviations first appear. Please move the legend to the first table that uses it.
  4. [Throughout] The abbreviation 'SC' is used in a few places where 'S&C' is meant, for example in the first sentence of Section III-B ('managing SC') and in Section V ('balancing SC trade-offs'). Please correct these typographical inconsistencies.
  5. [Tables III–VIII, Role column] The 'Role' column uses abbreviations such as 'T&S', 'R&S', and 'BS' whose status (UAV role vs. function) is not always clear; please align these with definitions in Table I or the shared legend.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation: the survey synthesizes external literature and makes no predictive or first-principles claims that reduce to its own inputs.

full rationale

This paper is a survey. Its output is a structured characterization of previously published UAV-ISAC results; it contains no new equations, no fitted parameters, no uniqueness theorems, and no derivation chain whose conclusion is equivalent to an input by construction. The claimed value is organizational: summarizing channel estimation, beam tracking, throughput, WSR, delay/AoI, energy efficiency, and security work, and extracting lessons learned and research directions. None of these claims is forced by a self-definition or by a self-citation chain. The skeptical reviewer's concern is about the accuracy of secondary reporting: the text attributes a MARL method to reference [15] in Section III-C ('However, [15] employs MARL to enhance the adaptability of UAVs by optimizing bandwidth and sensing accuracy'), and Tables III-VII use an undefined 'Avail.' CSI convention. These are legitimate correctness and clarity risks for a survey, but they are not circularity: a mis-citation or an ambiguous table entry does not make the survey's conclusions equivalent to its inputs. The survey does not predict anything from its own assumptions, so the circularity burden is minimal. No step satisfies the requirement of exhibiting a specific reduction of a claimed result to an input, a fitted parameter renamed as a prediction, or a load-bearing self-citation. Score 0.

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

The paper introduces no free parameters, mathematical axioms, or new entities. It is a review; its only assumptions are about the completeness and representativeness of its literature selection and the trustworthiness of the cited results.

assumptions (3)
  • domain assumption The taxonomy of sensing into monostatic, bistatic, and multistatic is complete and standard.
    Section II-B1 presents these three types as the primary sensing methods; if a UAV-ISAC system could use another sensing geometry not covered, the classification would be incomplete.
  • domain assumption The surveyed papers' simulation results are valid and correctly reported.
    The survey's lessons learned and comparative statements rely on trusting the cited papers' reported gains. This is an external validity assumption the authors do not test.
  • domain assumption The categorization of research into six topics (CE/beam tracking, throughput, WSR/sensing, delay/AoI, EE, security) is meaningful and non-overlapping enough for the comparison.
    Some papers appear in only one subsection, but many could fit several; the assignment is the authors' choice.

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Cite this review

Pith. "Pith review of Advancements in UAV-based Integrated Sensing and Communication: A Comprehensive Survey." pith.science (2026). https://pith.science/paper/KD5KJHYZ

@misc{pith2026250106526,
  author       = {Pith},
  title        = {Pith review of: Advancements in UAV-based Integrated Sensing and Communication: A Comprehensive Survey},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KD5KJHYZ}},
  note         = {Machine review of arXiv:2501.06526}
}
read the original abstract

Unmanned aerial vehicle (UAV)-based integrated sensing and communication (ISAC) systems are poised to revolutionize next-generation wireless networks by enabling simultaneous sensing and communication (S\&C). This survey comprehensively reviews UAV-ISAC systems, highlighting foundational concepts, key advancements, and future research directions. We explore recent advancements in UAV-based ISAC systems from various perspectives and objectives, including advanced channel estimation (CE), beam tracking, and system throughput optimization under joint sensing and communication S\&C constraints. Additionally, we examine weighted sum rate (WSR) and sensing trade-offs, delay and age of information (AoI) minimization, energy efficiency (EE), and security enhancement. These applications highlight the potential of UAV-based ISAC systems to improve spectrum utilization, enhance communication reliability, reduce latency, and optimize energy consumption across diverse domains, including smart cities, disaster relief, and defense operations. The survey also features summary tables for comparative analysis of existing methodologies, emphasizing performance, limitations, and effectiveness in addressing various challenges. By synthesizing recent advancements and identifying open research challenges, this survey aims to be a valuable resource for developing efficient, adaptive, and secure UAV-based ISAC systems.

Figures

Figures reproduced from arXiv: 2501.06526 by the authors.

Figure 3
Figure 3. An illustration of ISAC system for throughput maxi [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 4
Figure 4. An illustration of a UAV-based ISAC system where UAVs simultaneously communicate with the UEs and sense the targets. The same UAV can be equipped with both transmit￾ter and receiver antennas to transmit joint communication and sensing signals, and to receive sensing echoes from the targets (left Tx-Rx UAV). Alternatively, the receiver UAV could be a separate UAV dedicated to receiving the sensing echoes (right Rx UA… view at source ↗
Figure 5
Figure 5. An illustration of ISAC system where nodes employ [PITH_FULL_IMAGE:figures/full_fig_p016_5.png] view at source ↗
Figures from the paper (1 more)
Figure 6
Figure 6. Figure 6: An illustration of secure UAV-assisted ISAC, where a single ISAC UAV also functions as a jammer (left side), or two separate UAVs coordinate for jamming and ISAC operations (right side). effectively tracks Bob’s movements and balances the trade-off between legitimate a…

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Forward citations

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Reference graph

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Pith tools

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