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Ozgur B. Akan

Publications and source records attributed to Ozgur B. Akan.

At least 37 records · Page 2Linked to original sources

A Control-Referenced Tri-Channel OECT Receiver for Hybrid Molecular Communication Toward Brain Organoid Interfaces

Brain organoid interfaces that seek neuromodulator readout benefit from chemical receivers with molecular specificity and tolerance to drift. This paper presents a receiver-centric theoretical study of a control-referenced tri-channel organic electrochemical transistor (OECT) receiver with dopamine- and serotonin-selective pixels alongside a hydrogel-matched control pixel. The Ag/AgCl electrode provides the electrochemical gate reference, whereas the control pixel is used only as a matched reference for common-mode drift and other low-frequency baseline fluctuations during amplitude decisions. We couple finite-duration release, restricted diffusion with clearance, aptamer binding, OECT transduction, and correlated thermal, flicker, and drift noise, and we evaluate MoSK, CSK-4, and a 2-bit Hybrid detector on the same front-end by Monte Carlo simulation. At $r=45$ micrometers, control referencing mainly benefits the Hybrid amplitude branch, reducing Hybrid SER from $3.71\times 10^{-2}$ to $1.09\times 10^{-2}$ at $N_m=1.40\times 10^4$ molecules/symbol while barely changing the MoSK component. In calibrated no-ISI front-end benchmarks, Hybrid+CTRL reaches an LoD of 11866 molecules/symbol at 45 micrometers and remains below CSK-4+CTRL over much of the medium-to-long-distance range studied. The reported SER and LoD values are scenario-based receiver forecasts, whereas the more transferable result is the regime-dependent rule for when matched control referencing benefits Hybrid amplitude decoding.

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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 $K = 16$.

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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.

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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.

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Graph Representation-based Model Poisoning on the Heterogeneous Internet of Agents

Internet of Agents (IoA) envisions a unified, agent-centric paradigm where heterogeneous large language model (LLM) agents can interconnect and collaborate at scale. Within this paradigm, federated fine-tuning (FFT) serves as a key enabler that allows distributed LLM agents to co-train an intelligent global LLM without centralizing local datasets. However, the FFT-enabled IoA systems remain vulnerable to model poisoning attacks, where adversaries can upload malicious updates to the server to degrade the performance of the aggregated global LLM. This paper proposes a graph representation-based model poisoning (GRMP) attack, which exploits overheard benign updates to construct a feature correlation graph and employs a variational graph autoencoder to capture structural dependencies and generate malicious updates. A novel attack algorithm is developed based on augmented Lagrangian and subgradient descent methods to optimize malicious updates that preserve benign-like statistics while embedding adversarial objectives. Experimental results show that the proposed GRMP attack can substantially decrease accuracy across different LLM models while remaining statistically consistent with benign updates, thereby evading detection by existing defense mechanisms and underscoring a severe threat to the ambitious IoA paradigm.

cs.NI↗

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.

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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).

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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.

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Local Differential Privacy for Molecular Communication Networks

Molecular communication (MC) enables information exchange in nanoscale sensor networks operating in biological environments, yet privacy remains largely unaddressed. We integrate local differential privacy (LDP) into diffusion-based MC by privatizing each user's measurement at the transmitter and conveying the resulting randomized report over the MC channel. To our knowledge, this is the first systematic LDP implementation for diffusion-based MC, enabling privacy-preserving aggregate data analysis for in-body health monitoring and other population-scale sensing applications. We benchmark major LDP mechanisms under a realistic channel model. Simulation results show that k-ary Randomized Response (KRR) and Optimized Local Hashing (OLH) achieve the lowest average $\ell_1$ distribution-estimation error under the MC channel: OLH is preferable when channel resources are sufficient and the number of possible user values (alphabet size) $k$ is moderate to large, whereas the KRR is more robust as the MC transmission quality deteriorates. We further propose RLIM-LDP, which combines run-length-limited ISI-mitigation (RLIM) coding with LDP coding. Extensive simulation results demonstrate that RLIM-LDP improves end-to-end reliability and reduces the final distribution-estimation error when time and molecule resources are limited.

cs.IT↗

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.

physics.med-ph↗

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.

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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.

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Chemo Hydrodynamic Transceivers for the Internet of Bio-Nano Things, Modeling the Joint Propulsion Transmission trade-off

The Internet of Bio-Nano Things (IoBNT) requires mobile nanomachines that navigate complex fluids while exchanging molecular signals under external supervision. We introduce the chemo-hydrodynamic transceiver, a unified model for catalytic Janus particles in which an external optical control simultaneously drives molecular emission and active self-propulsion. Unlike common abstractions that decouple mobility and communication, we derive a stochastic channel model that captures their physicochemical coupling and shows that actuation-induced distance jitter can dominate the received-signal variance, yielding a fundamental trade-off: stronger actuation increases emission but can sharply reduce reliability through motion-induced fading. Numerical results reveal a unimodal reliability profile with a critical actuation level beyond which the signal-to-noise ratio collapses, and an optimal control level that scales approximately linearly with link distance. Compared with Brownian-mobility baselines, the model exposes a pronounced estimation gap: neglecting active motility noise can underestimate the bit error probability by orders of magnitude. These findings provide physical-layer guidelines for mobility-aware IoBNT protocol design and closed-loop control of nanorobotic swarms.

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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.

cs.IT↗

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.

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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.

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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.

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Run-Length-Limited ISI-Mitigation (RLIM) Coding for Molecular Communication

Inter-symbol interference (ISI) limits reliability in diffusion-based molecular communication (MC) channels. We propose RLIM, a family of run-length-limited (RLL) codes that form fixed-size codebooks by minimizing the total number of 1-bits, increasing the per-symbol molecule budget under standard power normalizations and thus improving reliability. We develop a provably optimal linear-time greedy decoder that is equivalent to Viterbi decoding under a deterministic last-wins tie-break and has lower computational complexity; empirically, it outperforms first-wins and random Viterbi variants on RLL baselines. Extensive binomial and particle-tracking simulations show that RLIM achieves lower bit error rate (BER) than classical RLL and other prominent coding schemes across a broad range of scenarios.

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