Rain Rate Estimation Bounds and Weather-Adaptive Pilot Allocation for LEO Satellite ISAC

Rain attenuates Ku-band satellite signals by up to 20~dB, encoding precipitation information along the Earth-space slant path. This paper derives the Bayesian Cramér-Rao bound (BCRB) for rain rate estimation from LEO broadband OFDM downlinks. Using corrected ITU-R P.838-3 coefficients, the standard CRB yields a minimum detectable rain rate $R_{\min} \approx 4.3\mmh$ for a single link at the $38^\circ$ reference elevation. We derive the prior Fisher information in closed form for log-normal rain ($c_v = 1.05$, from 186{,}292 samples) and show that a single-snapshot BCRB reduces $R_{\min}$ to $1.1\mmh$; exploiting temporal correlation ($ρ= 0.95$) over a 30-min window further tightens it to $0.95\mmh$, while multi-link fusion across $N = 215$ links lowers the operating-point RMSE \emph{lower bound} at $R = 20\mmh$ to approximately $0.07\mmh$. Building on these bounds, we formulate a weather-adaptive pilot allocation that minimizes the BCRB subject to a hard spectral-efficiency constraint, characterize its three-regime structure (full-sensing, throughput-tracking, outage), and pair it with a CUSUM rain onset detector achieving sub-10-min delay for $R \geq 20\mmh$. A closed-form analysis of dynamic LEO slant geometry identifies a sensing-optimal elevation at the P.618-validity floor of $15^\circ$ that yields a $1.58\times$ geometric improvement over the $38^\circ$ baseline, exposing a structural anti-correlation between sensing- and communication-optimal elevations along an orbital pass. Validation against 9.4~million radar samples from 215 Ku-band GEO satellite links ($r = 0.72$, RMSE~$= 1.24\dB$) and 113 rain gauges confirms the underlying attenuation model; the bounds transfer to LEO constellations under matched OFDM signal parameters, with dedicated LEO validation left for future work.

CisLunarSense: Opportunistic ISAC for Debris Detection at the Lunar Gateway

We propose CisLunarSense, an opportunistic integrated sensing and communication (ISAC) framework that exploits the Lunar Gateway's Ka-band relay for monostatic debris detection, addressing the absence of cislunar space situational awareness infrastructure beyond the reach of ground-based radars. Using NASA/ESA-documented system parameters with author-selected sensing settings and a CR3BP-based 9:2 near-rectilinear halo orbit model, we derive the orbit-phase-dependent Cramér--Rao bound under OFDM inter-carrier interference, quantify a 36~dB cislunar sensing advantage over a ground-based Ka-band reference, and design a velocity-adaptive processor with mode switching at 337~m/s. Gateway operational debris ($v_\mathrm{rel} < 50$~m/s) is detectable within 700~km with over 30~minutes of warning; external threats ($v_\mathrm{rel}$ up to 500~m/s) remain detectable within 400--630~km. An orbit-phase-adaptive allocation reduces the sensing duty cycle from 60\% to 19\%, increasing relay throughput from 44 to 90~Mbps. A closed-form sensing outage probability for $K$-CPI non-coherent integration under Swerling~I fluctuation shows that the 10\%-outage detection range reaches 91\% of the deterministic maximum at the nominal operating point $K = 16$.

Fisher Information Limits of Satellite RF Fingerprint Identifiability for Authentication

RF fingerprinting authenticates satellite transmitters by exploiting hardware-specific signal impairments, yet existing methods operate without theoretical performance guarantees. We derive the Fisher information matrix (FIM) for joint estimation of in-phase/quadrature (IQ) imbalance and power amplifier (PA) nonlinearity parameters, establishing Cramér-Rao bounds (CRBs) whose structure depends on constellation moments. A necessary condition for full IQ identifiability is that the identifiability factor~$β$ exceeds zero; for binary phase-shift keying (BPSK), $β= 0$ yields a rank-deficient FIM, rendering IQ parameters unidentifiable. This provides a plausible theoretical explanation for OrbID's near-random performance (area under the ROC curve, AUC~$= 0.53$) on Orbcomm. From the FIM, we define a discrimination metric that predicts which hardware parameters dominate authentication for a given modulation. For constant-modulus PSK signals, PA nonlinearity features are predicted to dominate while IQ features are ineffective. We validate the framework on 24~Iridium satellites using two recording campaigns, achieving cross-file PA fingerprint correlation $r = 0.999$ and confirming all four CRB predictions. A discrimination-ratio-weighted (DR-weighted) authentication test achieves AUC~$= 0.934$ from six features versus $0.807$ with equal weighting, outperforming machine-learning classifiers (AUC~$\leq 0.69$) on the same data.

Performance Bounds and Robust Filtering for LEO Inter-Satellite Synchronization under Cross-Epoch Doppler Coupling

Low Earth orbit (LEO) inter-satellite links (ISLs) must achieve joint synchronization and ranging under severe hardware impairments, namely oscillator phase noise, clock drift, and measurement outliers, exacerbated by rapid relative dynamics exceeding 7~km/s. In coherent Doppler processing, the frequency observable depends on the \emph{difference} between consecutive carrier phase states, creating a cross-epoch coupling structure that fundamentally affects estimation-theoretic performance limits. This paper makes three contributions. First, we prove analytically that this cross-epoch Doppler coupling is \emph{necessary} to avoid unbounded carrier phase uncertainty: without it, phase variance grows linearly without bound. Second, we derive a posterior Cramér-Rao bound (PCRB) via the Tichavský recursion that explicitly incorporates the resulting 10$\times$10 block information structure. Third, we propose a hybrid robust filtering framework combining hard gating for impulsive cycle-slip outliers with Huber M-estimation for heavy-tail contamination, using TASD-aware innovation covariance to account for cross-epoch uncertainty in residual normalization. Monte Carlo simulations at Ka-band confirm that the PCRB accurately lower-bounds estimator performance under nominal conditions, while the hybrid method reduces 95th-percentile phase error by 27--93\% compared to standard extended Kalman filtering across different outlier regimes.

Distortion Is Not Noise: On the Limits of the Kappa Model for Monostatic ISAC

Monostatic ISAC sensing differs from communication because the transmitter can monitor its distorted transmit waveform. Thus, the aggregate $κ$ distortion model, which treats impairments as unknown noise, is appropriate for communication but pessimistic for monostatic sensing. We derive PA-aware sensing Cramér--Rao bounds (CRBs) and a PN-aware CRB that reveals an irreducible velocity-error floor, and quantify when $κ$-based bounds overestimate sensing degradation. Simulations validate the analysis and show robustness to practical DPD template errors (less than 1~dB overhead at a typical $-25$~dB NMSE).

A Policy-Aware Cross-Layer Auditing Service for Tiering and Throttling in Starlink

We present a policy-aware, cross-layer methodology for edge-side auditing of service tiering and quota-based throttling in Starlink. Using a multi-week plan-hopping campaign (232.8 h) on a UK residential terminal, we align 1 Hz terminal telemetry with host-side probes to obtain portal-labeled traces spanning priority (pre-quota), post-quota throttling, stay-active operation, and residential service. Using portal status only as ground truth (independent of throughput), we show these policy regimes manifest as distinct signatures in goodput, PoP RTT, and an internal-to-user ratio $R=C_{\mathrm{int}}/T_{\mathrm{user}}$. A lightweight rule on windowed medians separates high-speed from low-rate operation without operator visibility.

Continuous Blood Monitoring with Particle-based Integrated Sensing and Communication (ISAC)

Although the circulatory system functions as a continuous source of physiological data, contemporary diagnostics remain bound to intermittent, time-delayed assessments. To resolve this, we present a framework for ubiquitous hematological profiling driven by Integrated Sensing and Communication (ISAC). We demonstrate how electromagnetic signals can be exploited to monitor blood in real-time, effectively converting them into diagnostic tools. We analyze the biological foundations of blood, review existing Complete Blood Count (CBC) and sensing technologies, and detail a novel pipeline for continuous blood monitoring. Furthermore, we discuss the potential applications of deploying these devices to enable real-time CBC and biomarker detection, ultimately revolutionizing how we predict, detect, and manage individual and public health.

Odor Communication with Green Leaf Volatiles for Stress Signalling in the Internet of Plants

This paper develops an end-to-end odor communication model for stress signaling between plants using Green Leaf Volatiles (GLV). A damaged transmitter plant emits (Z)-3-hexenal, (Z)-3-hexenol, and (Z)-3-hexenyl acetate, which propagate through a time-varying diffusion-advection channel and undergo multiplicative loss at the receiver. The sink plant is modeled with a biochemical receiver network that converts the received GLVs into the defensive metabolite (Z)-3-hexenyl $β$-vicianoside, and an alarm decision is defined based on its concentration level. Numerical results show that (Z)-3-hexenol is the primary driver of the system and that plant perception generally operates in a non-linear region. These findings provide a framework for understanding the evolution of plant-plant communication and for developing next-generation precision farming technologies.

Cramer--Rao Bounds for Magneto-Inductive Integrated Sensing and Communications

Magnetic induction (MI) enables communication in RF-denied environments (underground, underwater, in-body), where the medium conductivity imprints a deterministic signature on the channel. This letter derives a closed-form Cramér--Rao bound (CRB) for the joint estimation of range and medium conductivity from MI pilot observations in an integrated sensing and communication (ISAC) framework. The Fisher information matrix reveals that the joint estimation penalty converges to 3\,dB in the near-field regime, meaning conductivity sensing adds at most a factor-of-two loss in ranging precision. Monte Carlo maximum-likelihood simulations confirm that the CRB is achievable under practical operating conditions.

MI-ISAC: Magneto-Inductive Integrated Sensing and Communication in the Reactive Near-Field for RF-Denied Environments

Radio-frequency integrated sensing and communication (RF-ISAC) is ineffective inunderground, underwater, and in-body environments where conductive media attenuate electromagnetic waves by tens of dB per meter. This article presents magneto-inductive ISAC (MI-ISAC), a paradigm that exploits the reactive near-field quasi-static coupling inherent to MI links, enabling a fundamentally different approach to ISAC in these RF-denied environments. Five foundational results are established: (i)~tri-axial coils are necessary and sufficient for identifiable joint range-and-angle estimation; (ii)~coupling strength changes sharply with range, enabling theoretical sub-millimeter accuracy at typical MI distances despite kHz-level bandwidth; (iii)~time-of-flight is ineffective under such narrow bandwidth, but the coupling gradient provides approximately six orders of magnitude finer resolution; (iv)~MI-ISAC can provide 4--10+\,dB sensing gain over time-division baselines; and (v)~the MI-MIMO channel is geometry-invariant and well-conditioned across all orientations. Applications and a research roadmap are discussed.