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arxiv: 2606.25574 · v1 · pith:EQ2YTVGMnew · submitted 2026-06-24 · 💻 cs.IT · math.IT

Performance Analysis for Heterogeneous Air-Ground ISAC in Coordinated Multipoint Networks

Yihang Jiang , Xiaoyang Li , Guangxu Zhu , Changsheng You , Xiaowen Cao , Dingzhu Wen , Bingpeng Zhou , Xinyi Wang
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Rui Zhang
This is my paper

Pith reviewed 2026-06-25 19:33 UTC · model grok-4.3

classification 💻 cs.IT math.IT
keywords ISACCoMPheterogeneous networksair-ground networksperformance analysissensing and communication trade-offstwo-tier deploymentlow-altitude economy
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The pith

A CoMP-based heterogeneous air-ground ISAC architecture with hybrid mono/bi-static sensing supports terrestrial communication and aerial sensing while exposing performance trade-offs under cooperation and density changes.

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

The paper proposes a heterogeneous air-ground integrated sensing and communication network using coordinated multipoint techniques. It features a two-tier base station deployment with master stations in a hexagonal lattice and slave stations distributed as a Poisson point process. A cooperative hybrid mono/bi-static sensing scheme boosts spatial diversity for aerial targets alongside terrestrial user communication. The developed performance analysis framework incorporates channel and network parameters. Simulations identify trade-offs in communication and sensing metrics that vary with the degree of base station cooperation and overall network density.

Core claim

A heterogeneous air-ground ISAC network architecture based on CoMP is proposed, which incorporates a cooperative hybrid mono/bi-static sensing scheme to enhance spatial diversity and sensing capability. In the proposed architecture, a two-tier base station deployment is adopted: master BSs are arranged in a hexagonal lattice, while slave BSs follow a Poisson point process distribution. This structure concurrently supports communication for terrestrial users and sensing for aerial targets. A holistic performance analysis framework for both C&S is further developed, accounting for key channel and network parameters. Simulation results reveal inherent trade-offs between C&S performance, especia

What carries the argument

The cooperative hybrid mono/bi-static sensing scheme in the two-tier CoMP architecture, which combines master and slave base stations to deliver spatial diversity for sensing aerial targets while serving terrestrial communication.

If this is right

  • Trade-offs between communication and sensing performance emerge particularly under multi-BS cooperation.
  • Changes in network density alter the balance between C&S metrics.
  • The analysis framework incorporates effects from key channel and network parameters in the two-tier setup.
  • The results supply practical guidance for deploying scalable ISAC networks in low-altitude economy scenarios.

Where Pith is reading between the lines

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

  • If the model assumptions hold, operators may need to tune cooperation levels to maintain sensing performance as density increases.
  • The two-tier structure could guide similar integrated designs in other environments with mixed user types.
  • Incorporating explicit mobility models for aerial targets would test whether the reported trade-offs persist.

Load-bearing premise

The two-tier BS deployment model with master stations in a hexagonal lattice and slave stations as a Poisson point process, together with the assumed channel and network parameters, accurately captures real air-ground propagation, interference, and mobility effects without significant unmodeled factors that would alter the reported C&S trade-offs.

What would settle it

Field measurements of communication rates and sensing detection probabilities in a real air-ground environment under comparable multi-BS cooperation levels and densities that deviate from the simulated trade-off curves.

Figures

Figures reproduced from arXiv: 2606.25574 by Bingpeng Zhou, Changsheng You, Dingzhu Wen, Guangxu Zhu, Rui Zhang, Xiaowen Cao, Xiaoyang Li, Xinyi Wang, Yihang Jiang.

Figure 1
Figure 1. Figure 1: Geometric topology for the CoMP ISAC network. [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Geometry model for the air-ground ISAC network. [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 2
Figure 2. Figure 2: The BSs, CUs, and STs are positioned at heights [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Illustration of sensing serving distance under different cases, [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Sensing network structure with low-altitude aerial STs. [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 7
Figure 7. Figure 7: Per-BS EE as a function of the number of cooperative [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 6
Figure 6. Figure 6: Per-CU EE as a function of the number of cooperative [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 9
Figure 9. Figure 9: Per-CU EE as a function of the density of slave BSs [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Per-RE EE as a function of the density of slave BSs [PITH_FULL_IMAGE:figures/full_fig_p012_10.png] view at source ↗
Figure 12
Figure 12. Figure 12: The approximated ACRBs as a function of the numbers [PITH_FULL_IMAGE:figures/full_fig_p012_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: Link-level RDCP under given CFARs as a function of [PITH_FULL_IMAGE:figures/full_fig_p013_13.png] view at source ↗
read the original abstract

The emergence of the \textit{low-altitude economy} (LAE) calls for highly integrated and reliable wireless systems that can simultaneously support \textit{communication and sensing} (C\&S) functions. Although \textit{integrated sensing and communication} (ISAC) has been widely studied, most existing works focused on link-level or single-cell architectures in terrestrial environments, leaving the potential of network-level cooperative air-ground ISAC largely unexplored. To bridge this gap, a heterogeneous air-ground ISAC network architecture based on \textit{coordinated multipoint} (CoMP) is proposed, which incorporates a cooperative hybrid mono/bi-static sensing scheme to enhance spatial diversity and sensing capability. In the proposed architecture, a two-tier \textit{base station} (BS) deployment is adopted: master BSs are arranged in a hexagonal lattice, while slave BSs follow a Poisson point process distribution. This structure concurrently supports communication for terrestrial users and sensing for aerial targets. A holistic performance analysis framework for both C\&S is further developed, accounting for key channel and network parameters. Simulation results reveal inherent trade-offs between C\&S performance, especially under multi-BS cooperation and varying network density. These findings provide practical guidance for the deployment of scalable and efficient ISAC networks in LAE scenarios.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

1 major / 1 minor

Summary. The manuscript proposes a heterogeneous air-ground ISAC network architecture based on CoMP for low-altitude economy scenarios. It features a two-tier BS deployment (master BSs on hexagonal lattice, slave BSs as PPP), a cooperative hybrid mono/bi-static sensing scheme to improve spatial diversity, a holistic performance analysis framework accounting for channel and network parameters, and simulation results that reveal trade-offs between communication and sensing performance under multi-BS cooperation and varying network density.

Significance. If the analysis framework and reported trade-offs hold, the work would provide practical guidance for deploying scalable ISAC networks in air-ground LAE settings by quantifying C&S performance under cooperation. The extension of ISAC to network-level cooperative heterogeneous architectures using standard stochastic geometry tools is a positive contribution.

major comments (1)
  1. [System Model] System Model section: The two-tier deployment (master BSs in hexagonal lattice, slave BSs as PPP) together with the assumed channel parameters is load-bearing for the central claim of inherent C&S trade-offs; the manuscript provides no sensitivity analysis or comparison to alternative models (e.g., fully random deployment or inclusion of mobility) to confirm that unmodeled air-ground propagation and interference effects would not alter the reported trade-offs. A concrete test would be to vary the lattice spacing and PPP intensity and verify persistence of the multi-BS cooperation gains.
minor comments (1)
  1. [Abstract] Abstract: The description of the 'holistic performance analysis framework' does not name the specific metrics (e.g., achievable rate, sensing SNR, detection probability) or the exact stochastic geometry tools employed, which would improve immediate readability.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their thorough review and valuable suggestions. Below we provide a point-by-point response to the major comment.

read point-by-point responses

  1. Referee: [System Model] System Model section: The two-tier deployment (master BSs in hexagonal lattice, slave BSs as PPP) together with the assumed channel parameters is load-bearing for the central claim of inherent C&S trade-offs; the manuscript provides no sensitivity analysis or comparison to alternative models (e.g., fully random deployment or inclusion of mobility) to confirm that unmodeled air-ground propagation and interference effects would not alter the reported trade-offs. A concrete test would be to vary the lattice spacing and PPP intensity and verify persistence of the multi-BS cooperation gains.

    Authors: The referee correctly notes that the system model is central to our claims. The two-tier deployment is motivated by practical LAE scenarios, with master BSs on a hexagonal lattice representing fixed, planned infrastructure and slave BSs as PPP for random additional nodes. This allows us to analyze the benefits of cooperation in a heterogeneous setting using stochastic geometry. Our existing simulations vary the overall network density and show that the C&S trade-offs and cooperation gains hold. To directly address the suggestion, we will add in the revised version explicit sensitivity analysis by varying the lattice spacing (affecting master BS density) and PPP intensity, as well as a comparison case with fully random deployment. This will confirm the persistence of the gains. We note that incorporating mobility would entail a major extension to the static channel models used and is left for future research. revision: partial

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The paper's core claims rest on a proposed two-tier BS deployment (hexagonal masters + PPP slaves) and hybrid mono/bi-static CoMP sensing, with performance metrics derived via standard stochastic geometry and channel models. No load-bearing step reduces by construction to a fitted parameter, self-citation chain, or renamed input; the abstract and context indicate independent modeling choices whose outputs are not forced by definition. This is the typical non-circular case for simulation-based network analysis.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Review based on abstract only; ledger is therefore incomplete. Relies on standard stochastic geometry for BS placement and typical wireless channel assumptions.

axioms (2)
  • domain assumption Master BSs follow hexagonal lattice and slave BSs follow Poisson point process distributions
    Stated in abstract as the adopted two-tier deployment structure for performance analysis.
  • domain assumption Standard models for air-ground channels and interference apply without modification
    Implicit in the holistic performance analysis framework accounting for key channel and network parameters.

pith-pipeline@v0.9.1-grok · 5789 in / 1360 out tokens · 23581 ms · 2026-06-25T19:33:22.578292+00:00 · methodology

discussion (0)

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