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.

Information Theoretic Modeling of Interspecies Molecular Communication

Plants and insects communicate using chemical signals like volatile organic compounds (VOCs). A plant encodes information using different blends of VOCs, which propagate through the air to represent different symbolic information. This communication occurs in a noisy environment, characterized by wind, distance, and complex biological reactions. At the receiver, cross-reactive olfactory receptors produce stochastic binding events whose discretized durations form the receiver observation. In this paper, an information-theoretic framework is developed to model interspecies molecular communication (MC), where receptor responses are modeled probabilistically using a multinomial distribution. Numerical results show that the communication depends on environmental parameters such as wind speed, distance, and the number of released molecules. The proposed framework provides fundamental insights into the VOC-based interspecies communication under realistic biological and environmental conditions.

Channel Modeling and Experimental Validation of Odor-Based Molecular Communication Systems

Odor-based Molecular Communication (OMC) employs odor molecules to convey information, contributing to the realization of the Internet of Everything (IoE) vision. Despite this, the practical deployment of OMC systems is currently limited by the lack of comprehensive channel models that accurately characterize particle propagation in diverse environments. While existing literature explores various aspects of molecular transport, a holistic approach that integrates theoretical modeling with experimental validation for bounded channels remains underdeveloped. In this paper, we address this gap by proposing mathematical frameworks for both bounded and unbounded OMC channels. To verify the accuracy of the proposed models, we develop a novel experimental testbed and conduct an extensive performance analysis. Our results demonstrate a strong correlation between the theoretical derivations and experimental data, providing a robust foundation for the design and analysis of future end-to-end OMC systems.

Intrinsic MIMO Particle Communication Channel with Random Advection

In this work, receiver diversity in advection-dominated diffusion-advection channels is investigated. Strong directed flow fundamentally alters the communication-theoretic properties of molecular communication systems (MC). Specifically, advection preserves the temporal ordering and shape of transmitted pulses, enabling pulse-based and higher-order modulation schemes that are typically infeasible in purely diffusive environments. Focusing on a single transmitter and a single type of information molecule, it is demonstrated that spatially distributed receivers can observe distinct realizations of the same transmitted signal, giving rise to diversity gain. Several receiver combining strategies are evaluated and shown to improve detection performance compared to single-receiver operation, particularly in low-to-moderate signal-to-noise ratio (SNR) regimes. The results provide a structured framework for understanding receiver-side diversity in molecular communication, highlighting the role of advection as a key enabler for reliable pulse-based signaling. This perspective establishes a foundation for future studies on advanced modulation, joint equalization and detection, and multi-molecule MIMO extensions that can further enhance the performance and physical applicability of MC systems.

Neural-Inspired Multi-Agent Molecular Communication Networks for Collective Intelligence

Molecular Communication (MC) is a pivotal enabler for the Internet of Bio-Nano Things (IoBNT). However, current research often relies on super-capable individual agents with complex transceiver architectures that defy the energy and processing constraints of realistic nanomachines. This paper proposes a paradigm shift towards collective intelligence, inspired by the cortical networks of the biological brain. We introduce a decentralized network architecture where simple nanomachines interact via a diffusive medium using a threshold-based firing mechanism modeled by Greenberg-Hastings (GH) cellular automata. We derive fixed-point equations for steady-state populations via mean-field analysis and validate them against stochastic simulations. We demonstrate that the network undergoes a second-order phase transition at a specific activation threshold. Crucially, we show that both pairwise and collective mutual information peak exactly at this critical transition point, confirming that the system maximizes information propagation and processing capacity at the edge of chaos.

Airborne Particle Communication Through Time-varying Diffusion-Advection Channels

Particle based communication using diffusion and advection has emerged as an alternative signaling paradigm recently. While most existing studies assume constant flow conditions, real macro scale environments such as atmospheric winds exhibit time varying behavior. In this work, airborne particle communication under time varying advection is modeled as a linear time varying (LTV) channel, and a closed form, time dependent channel impulse response is derived using the method of moving frames. Based on this formulation, the channel is characterized through its power delay profile, leading to the definition of channel dispersion time as a physically meaningful measure of channel memory and a guideline for symbol duration selection. System level simulations under directed, time varying wind conditions show that waveform design is critical for performance, enabling multi symbol modulation using a single particle type when dispersion is sufficiently controlled. The results demonstrate that time varying diffusion advection channels can be systematically modeled and engineered using communication theoretic tools, providing a realistic foundation for particle based communication in complex flow environments.

Physical Limits of Proximal Tumor Detection via MAGE-A Extracellular Vesicles

Early cancer detection relies on invasive tissue biopsies or liquid biopsies limited by biomarker dilution. In contrast, tumour-derived extracellular vesicles (EVs) carrying biomarkers like melanoma-associated antigen-A (MAGE-A) are highly concentrated in the peri-tumoral interstitial space, offering a promising near-field target. However, at micrometre scales, EV transport is governed by stochastic diffusion in a low copy number regime, increasing the risk of false negatives. We theoretically assess the feasibility of a smart-needle sensor detecting MAGE-A-positive microvesicles near a tumour. We use a hybrid framework combining particle-based Brownian dynamics (Smoldyn) to quantify stochastic arrival and false negative probabilities, and a reaction-diffusion PDE for mean concentration profiles. Formulating detection as a threshold-based binary hypothesis test, we find a maximum feasible detection radius of approximately 275 micrometers for a 6000 s sensing window. These results outline the physical limits of proximal EV-based detection and inform the design of minimally invasive peri-tumoral sensors.

Environment-to-Link ISAC with Space-Weather Sensing for Ka-Band LEO Downlinks

Ka-band low-Earth-orbit (LEO) downlinks can suffer second-scale reliability collapses during flare-driven ionospheric disturbances, where fixed fade margins and reactive adaptive coding and modulation (ACM) are either overly conservative or too slow. This paper presents a GNSS-free, link-internal predictive controller that senses the same downlink via a geometry-free dual-carrier phase observable at 10~Hz: a high-pass filter and template-based onset detector, followed by a four-state nearly-constant-velocity Kalman filter, estimate $Δ$VTEC and its rate, and a short look-ahead (60~s) yields an endpoint outage probability used as a risk gate to trigger one-step discrete MCS down-switch and pilot-time update with hysteresis. Evaluation uses physics-informed log replay driven by real GOES X-ray flare morphologies under a disjoint-day frozen-calibration protocol, with uncertainty reported via paired moving-block bootstrap. Across stressed 60~s windows, the controller reduces peak BLER by 25--30\% and increases goodput by 0.10--0.15~bps/Hz versus no-adaptation baselines under a unified link-level abstraction. The loop runs in $\mathcal{O}(1)$ per 0.1~s epoch (about 0.042~ms measured), making on-board implementation feasible, and scope and deployment considerations for dispersion-dominated events are discussed.

Performance Limits of Hardware-Constrained THz Inter-Satellite MIMO-ISAC Systems

Terahertz inter-satellite links (THz-ISL) offer unprecedented bandwidth for future space networks but face fundamental constraints from onboard power and thermal budgets. This paper establishes theoretical performance limits for MIMO Integrated Sensing and Communication (ISAC) systems under per-element constant-envelope (CE) transmission constraints. We demonstrate that hardware distortions -- specifically power amplifier nonlinearity, ADC quantization, and oscillator phase noise -- impose a capacity ceiling that cannot be overcome by increasing transmit power. A unified link budget framework integrates wideband beam squint, aperture pointing errors, and colored noise sources through a spectral consistency principle that ensures residual phase noise is counted exactly once across communication and sensing analyses. The sensing bounds are derived via the Whittle-Fisher Information Matrix under a Constant Acceleration kinematic model with jerk noise, yielding closed-form scaling laws: residual phase noise variance scales as $α^{-1}$ while dynamic state-estimation error (DSE) variance scales as $α^{-5}$ with pilot overhead $α$. Numerical results show divergent MIMO scaling: sensing precision improves with array size ($\mathrm{RMSE} \propto 1/\sqrt{N_t N_r}$), while the critical SNR exhibits scale invariance regarding array size, implying that the distortion-limited transition point stabilizes regardless of the array scale. The steep $α^{-5}$ DSE scaling creates an operationally infeasible region at $α< α^* \approx 0.16$, where $α^* = (C_{\mathrm{DSE}}/C_{\mathrm{PN}})^{1/4}$ -- a constraint-driven threshold under the adopted baseline for LEO operation. These findings provide design guidelines for hardware-efficient THz-ISL constellations.

Modeling and Analysis of VOC-based Interplant Molecular Communication Channel

Molecular communication (MC) enables information transfer using particles inspired by biological systems. Volatile Organic Compounds (VOCs) are one of the most abundant and diverse classes of signaling molecules used by living or non-living objects. VOC-based MC holds great promise in developing long-range, bio-compatible communication systems capable of interfacing nano- and micro-scale devices. In this paper, we present a comprehensive end-to-end framework for VOC-based interplant MC from an ICT perspective. The communication process is divided into three stages: transmission (VOC biosynthesis and emission from leaves), channel propagation (advection-diffusion in turbulent wind via Gaussian puff for stress-induced VOC release and Gaussian plume for constitutive VOC release), and reception (VOC uptake and physiological response in the receiver plant). Each stage is analyzed by its attenuation and delay. Numerical results demonstrate that VOC-based channels exhibit low-pass behavior, with bandwidth and capacity heavily influenced by distance, wind velocity, and noise. Though the physical channel supports moderate frequencies, biological constraints at the transmitter restrict the end-to-end channel to slow-varying signals.