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arxiv: 2509.06070 · v2 · submitted 2025-09-07 · 📡 eess.SP

Quantum Radar for ISAC: Sum-Rate Optimization

Abdulmohsen Alsaui , Octavia A. Dobre , Neel Kanth Kundu , Abdulkarim Hariri , Hyundong Shin This is my paper

Pith reviewed 2026-05-18 18:08 UTC · model grok-4.3

classification 📡 eess.SP
keywords quantum radarISACquantum illuminationsum-rate optimizationbeamformingsuccessive convex approximationintegrated sensing and communication
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The pith

Integrating quantum illumination radar into a base station enables higher communication rates than classical ISAC while satisfying sensing constraints.

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

This paper develops a framework for embedding quantum illumination radar into wireless base stations to support both classical communication and enhanced target detection. It sets up a sum-rate maximization problem that jointly tunes transmit power and beamforming vectors under radar sensing requirements. Successive convex approximation solves the resulting non-convex optimization. Performance bounds derived from statistical detection theory show quantum protocols outperforming classical ones when signal-to-interference-plus-noise ratios are low. Simulations confirm the integrated system delivers more throughput than conventional ISAC baselines while meeting detection targets.

Core claim

The paper claims that an integrated quantum sensing and classical communication system achieves higher communication throughput than conventional ISAC baselines while satisfying the sensing requirement, with quantum advantage clearest in low signal-to-interference-plus-noise ratio regimes according to the derived statistical detection bounds.

What carries the argument

The IQSCC system whose sum-rate is maximized subject to radar sensing constraints, solved by successive convex approximation of the joint power and beamforming problem, with classical-versus-quantum performance bounds supplied by statistical detection theory.

If this is right

  • The optimized beamforming and power allocation simultaneously enable full-duplex classical communication and quantum-enhanced target detection.
  • Quantum radar protocols deliver higher detection probability than classical ones under low-power and high-noise conditions.
  • The sum-rate increases while the radar sensing constraint remains satisfied, as verified by the successive convex approximation solution.
  • The framework applies to scenarios where spectrum efficiency and hardware convergence are required.

Where Pith is reading between the lines

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

  • Hardware prototypes could reveal how decoherence scales with distance and frequency in real channels.
  • The same optimization structure might extend to multi-user or multi-target settings without changing the core formulation.
  • Designers of future wireless systems could use the low-SINR quantum advantage to relax transmit power budgets while keeping sensing quality fixed.

Load-bearing premise

Quantum illumination radar can be embedded into base station hardware and channel models without major additional losses or decoherence that would invalidate the performance bounds.

What would settle it

A side-by-side measurement of achieved communication sum-rate and target detection probability for the quantum system versus a classical ISAC baseline, performed at low SINR in a controlled hardware testbed, would confirm or refute the reported throughput gains.

Figures

Figures reproduced from arXiv: 2509.06070 by Abdulkarim Hariri, Abdulmohsen Alsaui, Hyundong Shin, Neel Kanth Kundu, Octavia A. Dobre.

Figure 1
Figure 1. Figure 1: Illustration of the considered ISAC system with a DL user, a UL user, and a monostatic radar target. [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The benchmarking radars used to evaluate the performance of each quantum radar. [PITH_FULL_IMAGE:figures/full_fig_p009_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Detection probability versus SINR for the derived classical CW radar model and reference expressions. [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Thermal photon count as a function of frequency and background temperature. [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Detection probability as a function of the SINR for the classical CW and CS radar models for different thermal noise photon count numbers, with [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Detection probability versus SINR for the QI and classical CS radar models. [PITH_FULL_IMAGE:figures/full_fig_p012_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Required SINR versus Pd for QI and CS radar models at Pf = 10−6 . IV. INTEGRATED QUANTUM SENSING AND CLASSICAL COMMUNICATION (IQSCC) SYSTEM In the proposed quantum ISAC system, a TMSV-based QI radar is employed for target sensing. The radar SINR expression derived in (14) is not directly applicable to the QI radar case, as the total transmit covariance, Vt, includes contributions from both the radar-specif… view at source ↗
Figure 8
Figure 8. Figure 8: Beampattern gain for the (a) conventional ISAC [PITH_FULL_IMAGE:figures/full_fig_p014_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Achieved sum rate versus iteration index for the conventional ISAC and proposed IQSCC systems. [PITH_FULL_IMAGE:figures/full_fig_p014_9.png] view at source ↗
read the original abstract

Integrated sensing and communication (ISAC) is emerging as a key enabler for spectrum-efficient and hardware-converged wireless networks. However, classical radar systems within ISAC architectures face fundamental limitations under low signal power and high-noise conditions. This paper proposes a novel framework that embeds quantum illumination radar into a base station to simultaneously support full-duplex classical communication and quantum-enhanced target detection. The resulting integrated quantum sensing and classical communication (IQSCC) system is optimized via a sum-rate maximization formulation subject to radar sensing constraints. The non-convex joint optimization of transmit power and beamforming vectors is tackled using the successive convex approximation technique. Furthermore, we derive performance bounds for classical and quantum radar protocols under the statistical detection theory, highlighting the quantum advantage in low signal-to-interference-plus-noise ratio regimes. Simulation results demonstrate that the proposed IQSCC system achieves a higher communication throughput than the conventional ISAC baseline while satisfying the sensing requirement.

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 / 2 minor

Summary. The manuscript proposes an Integrated Quantum Sensing and Classical Communication (IQSCC) system embedding quantum illumination radar into a base station for simultaneous full-duplex classical communication and quantum-enhanced target detection. It formulates a sum-rate maximization problem subject to radar sensing constraints, solves the resulting non-convex joint optimization of transmit power and beamforming vectors via successive convex approximation (SCA), derives performance bounds for classical versus quantum radar protocols under statistical detection theory, and presents simulations claiming higher communication throughput than conventional ISAC baselines while meeting sensing requirements, with the quantum advantage emphasized in low-SINR regimes.

Significance. If the central claims hold after addressing the noted limitations, the work would offer a concrete optimization framework for quantum-enhanced ISAC and demonstrate potential throughput gains from quantum illumination in low-power regimes using standard tools (SCA and statistical detection bounds). The simulations supporting higher sum-rate under sensing constraints provide empirical grounding, but the overall significance depends on whether the derived quantum advantage survives realistic channel impairments.

major comments (1)
  1. [performance bounds derivation] The section deriving performance bounds for classical and quantum radar protocols (referenced in the abstract and used to support the low-SINR advantage): the quantum detection-probability improvement is derived under ideal entanglement preservation without explicit round-trip transmissivity loss (η) or decoherence terms in the ISAC wireless channel model. Standard quantum illumination results show this advantage vanishes for η ≲ 0.5 or imperfect idler-signal correlation; because the sensing constraint and the claim of quantum superiority in the optimization rest on these bounds, the omission is load-bearing for the central claim.
minor comments (2)
  1. [simulation results] The simulation results section would be strengthened by reporting the number of Monte Carlo trials, exact parameter values (e.g., specific η, decoherence rates, or SINR thresholds), and error bars or confidence intervals on the sum-rate curves.
  2. [system model] Notation for the beamforming vectors and power allocation variables should be introduced consistently in the system model section before their use in the SCA formulation.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the constructive feedback on our manuscript. We address the major comment below and will revise the manuscript to strengthen the performance bounds section.

read point-by-point responses

  1. Referee: The section deriving performance bounds for classical and quantum radar protocols (referenced in the abstract and used to support the low-SINR advantage): the quantum detection-probability improvement is derived under ideal entanglement preservation without explicit round-trip transmissivity loss (η) or decoherence terms in the ISAC wireless channel model. Standard quantum illumination results show this advantage vanishes for η ≲ 0.5 or imperfect idler-signal correlation; because the sensing constraint and the claim of quantum superiority in the optimization rest on these bounds, the omission is load-bearing for the central claim.

    Authors: We acknowledge that the current derivation of the performance bounds assumes ideal entanglement preservation and does not explicitly include round-trip transmissivity loss η or decoherence terms. To address this limitation, we will revise the statistical detection theory analysis in the manuscript to incorporate these parameters. The updated bounds will model the effective quantum illumination channel with η and account for idler-signal correlation degradation, allowing us to re-derive the detection probability expressions and clarify the regimes where the quantum advantage holds under realistic ISAC conditions. This revision will directly support the sensing constraints in the sum-rate optimization and provide a more robust justification for the low-SINR claims. revision: yes

Circularity Check

0 steps flagged

No circularity: bounds and optimization derive from standard detection theory and SCA without reducing to self-fitted inputs or self-citations.

full rationale

The paper's central derivation uses statistical detection theory to obtain classical vs. quantum radar performance bounds and applies successive convex approximation to a standard sum-rate maximization problem subject to sensing constraints. These steps are independent of the target result; the quantum advantage in low-SINR regimes follows from the model assumptions rather than being presupposed or fitted by construction. No self-definitional loops, renamed predictions, or load-bearing self-citations appear in the described chain. The approach remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The framework relies on standard assumptions from quantum radar and wireless communication literature, with optimization variables treated as decision variables rather than fitted constants; no new entities postulated.

free parameters (1)
  • Transmit power and beamforming vectors
    Jointly optimized decision variables in the sum-rate maximization subject to sensing constraints.
axioms (1)
  • domain assumption Quantum illumination provides detection advantage in low SINR regimes per statistical detection theory
    Invoked when deriving performance bounds and highlighting quantum advantage.

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