arXiv subjects

Ozgur B. Akan

Publications and source records attributed to Ozgur B. Akan.

At least 19 recordsLinked to original sources

arXiv2026

EPR Count for Runtime Prediction in Distributed Quantum Computing

EPR-pair consumption is commonly used as a communication-cost objective in distributed quantum computing, but minimizing EPR cost does not necessarily minimize distributed execution time. Despite its widespread use, the reliability of EPR count as a runtime surrogate has received limited direct characterization across different workloads and communication conditions. This work addresses this gap by systematically evaluating the relationship between EPR cost and runtime over all balanced two-QPU mappings of QFT, QAOA, and CDKM circuits. The results show that mappings with identical EPR cost can have substantially different execution times, lower-EPR mappings can be slower, and minimum-EPR mappings can be runtime-suboptimal. The reliability of EPR count is strongly workload dependent and also changes with the communication operating regime: increasing EPR-generation latency amplifies runtime differences hidden by equal EPR cost, while increased communication concurrency can reduce the ability of EPR count to preserve runtime ordering. These results show that EPR count and execution time are related but distinct optimization objectives, and identify regimes in which explicit communication-aware runtime modeling is necessary.

cs.DC↗

arXiv2026

Reading While Writing: Baseline Information Requirements for Molecular Neural Interfaces

Molecular neural interfaces that deliver and sense the same neurotransmitter must estimate endogenous release in the presence of their own chemical input. We study two exchanging regions with shared saturable uptake and concentration change measurements. Known delivery and exchange permit identification of apparent uptake at the driven region, but an unknown resting concentration difference leaves the source region's incremental uptake uncertain. We characterize all admissible source histories consistent with both ideal records and show how delivery and baseline information affect release classification. A dopamine-inspired example produces identical ideal concentration-change records for mean release-rate changes of -8.99 and +1.31 nanomolar per second. Stronger delivery changes whether all compatible sources imply suppression, with the true source held fixed. Under a Gaussian observation model, we bound discrimination based on chemical fluctuations. A baseline reference with an assumed standard deviation of 3.3 nanomolar reduces root-mean-square error from 10.41 to 1.21 nanomolar per second compared with an incorrect fixed baseline under exact gain calibration. Classification errors remain substantial with weak excitation, gain errors or responses near the category boundaries.

cs.ET↗

arXiv2026

Information and Communication Theoretical Foundations of Plant Communication: Mechanisms, Models, and Empirical Approaches

Plants exchange information through chemical, electrical, and mechanical signaling, engaging not only with neighboring plants but also with insects, animals, and microorganisms. These interactions support a broad range of ecological functions, from resource coordination and reproductive signaling to collective responses to environmental change. Despite extensive biological documentation of these processes, their systematic analysis from an Information and Communication Technology (ICT) perspective remains limited. This article addresses that gap as a tutorial with survey elements. It first establishes the biological foundations of plant communication across chemical, mechanical, and electrical modalities, covering the full range of interacting agents and signal functions. Building on this foundation, it reformulates plant signaling within ICT frameworks by defining transmitter, channel, and receiver models for each modality and introducing the relevant mathematical descriptions. Empirical studies and state-of-the-art sensing approaches are then reviewed to ground the models in experimental reality and identify where theory and measurement diverge. The paper concludes with a lessons learned section that distills cross-cutting insights on the fidelity of biology-to-ICT mappings, the distinctive channel properties of plant communication, multimodal coupling, receiver design principles, and observability constraints. By integrating biological depth with communication-theoretic rigor, this article provides a comprehensive foundation for the communications research community and identifies the open problems that will define interdisciplinary progress in this field.

eess.SP↗

arXiv2026

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. To quantify waveform distortion and guide the design of orthogonal signaling waveforms, the Orthogonality Loss Ratio (OLR) is introduced as a structural metric. 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.

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arXiv2026

Low-Complexity Run-Length-Limited ISI-Mitigation (RLIM) Codes for Molecular Communication

Molecular communication suffers from severe inter-symbol interference, which makes constrained coding essential for reliable transmission. Run-length-limited ISI-mitigation codes are attractive because they select low-weight constrained codebooks, reducing ISI while allowing more molecules to be assigned to each transmitted $1$-symbol under the usual molecular-communication normalization. Previous results showed strong bit-error-rate performance for these codes, but their original realization required full codebook generation and storage. This exponential storage growth is unsuitable for resource-constrained molecular communication channels and also limits the exploration of larger information dimensions. This is particularly important for nano-scale molecular communication, where transmitter and receiver nodes are expected to operate under severe memory and computational constraints. This paper removes that realization bottleneck by replacing full codebook storage with an enumerative realization based on Cover's ranking framework, constant-weight run-length-limited counting, and cumulative weight-layer offsets. The resulting encoder and decoder preserve the selected RLIM codebooks and the original projection-based decoding behavior while storing only polynomial-size counting tables. Storage and runtime measurements confirm the resulting exponential-to-polynomial reduction, while diffusion-based molecular-communication simulations show that the newly accessible larger information dimensions can improve the best mean bit-error-rate performance attainable by individual RLIM orders in several tested channel regimes.

cs.IT↗

arXiv2026

Masked Neural Detection for Run-Length-Limited Channel Coding in Molecular Communication

Molecular communication (MC) suffers from severe diffusion memory because molecules released for one symbol may arrive during later symbol intervals. Neural sequence detectors, especially sliding bidirectional recurrent neural networks (SBRNNs), substantially outperform threshold detection in such channels. This raises a central question for MC channel coding: does a code whose superiority was established under threshold detection retain it when both coded and uncoded transmission are evaluated with neural detection? This letter answers this question for run-length-limited ISI-mitigation (RLIM) codes by proposing a decoder-aware training mask that removes the positions the RLIM decoder has a high probability of deterministically overwriting, steering compact-SBRNN capacity toward the information-bearing positions. The masked RLIM$_2$-SBRNN beats the best uncoded receiver (threshold or SBRNN) at 40 of 57 operating points; gains peak at 43$\times$ under favorable channels, while losses, confined to the most adverse, never exceed 2.7$\times$. Masking improves the unmasked RLIM$_2$-SBRNN in 56 of 57 matched comparisons. Finally, with storage counted equally in SBRNN weights and MLSE table entries, the masked RLIM$_2$-SBRNN is the more accurate receiver up to a few thousand stored values despite using no channel knowledge; channel-state-aware uncoded MLSE moves ahead only beyond tens of thousands.

cs.IT↗

arXiv2026

Reliability Limits and Decoding for Partial Nanopore Protein Rereads With Persistent State

Repeated observations of one physical object need not constitute independent channel uses. We model partial nanopore protein rereads as a finite-alphabet channel with canonical content, persistent readout, and pass-local coverage and synchronization. For exact compound-pass data, matched inference approaches the equivalence-class canonical posterior, and sitewise excess Bayes risk admits an action-aware achievable exponent. In an aligned specialization, observation-local redraw can cause linear-in-$K$ growth in true-label negative log-likelihood (NLL). We derive order-$b$ projection-stability bounds and an exact passwise-fusion diagnostic. On a PASTOR-informed semi-synthetic hard-symbol channel, label-blind deterministic-mixture importance sampling (LB-IS) agrees with exact enumeration at $L=7$. At $L=24, K=10$, LB-IS meets every prespecified aggregate absolute marginal-posterior and score-agreement criterion against a fixed high-allocation reference in three selected conditions. Joint agreement holds for the representative and high-NLL conditions, while the near-zero condition remains inconclusive. Exact $L \leq 6$ benchmarks identify order 4 as the smallest tested common cap. At target scale, the reference supports selected unprojected functionals, while neither order 4 nor 5 attains joint agreement, defining a tested finite-memory boundary. Across 16 cells, the order-4 shared branch lowers NLL by 0.033-0.224 nats per residue relative to pass-local.

cs.IT↗

arXiv2026

MC-BRIDGE: A Modular Receiver-Chain Simulation Framework for OECT-Based Molecular Communication

Organic electrochemical transistor (OECT)-based molecular communication (MC) receivers connect transport and binding to device current, noise, calibration, and detection. We present MC-BRIDGE (Molecular Communication Bioelectronic Receiver-chain Integrated Design and Guided Evaluation), a modular framework linking release, extracellular diffusion, finite-area observation, stochastic binding, and OECT transduction to charge-domain detection. On an independent electrical time grid, it generates sequence-wide multichannel colored noise, performs control-channel referencing and charge integration, and supports molecule-shift-keying (MoSK), concentration-shift-keying (CSK), and Hybrid decisions. Through common module interfaces, it estimates symbol error rate (SER) and decoded-symbol mutual information and analyzes inter-symbol interference (ISI). At nominal separation, the passive finite-area observer retains 27.5 percent of the center-point decision-charge magnitude, while correlation between the selective and control channels determines whether control referencing helps. After adaptive search, held-out records with seeds disjoint from search and calibration test the selected and next-lower budgets, yielding a tested-grid upper bound on the minimum budget meeting the SER target. This passive-field test resets receptor occupancy, excludes ISI, and calibrates thresholds on separate records at each operating point. Retaining transport and receptor memory instead produces high SER. Thus, geometry, covariance, calibration, and memory can change receiver conclusions.

cs.IT↗

arXiv2026

Edge-Side Fingerprints of Service Tiering and Quota Throttling in Starlink

We design and evaluate an edge-side measurement procedure for auditing service tiering and quota-based throttling in Starlink. Using a 232.8-hour plan-hopping campaign on a UK residential terminal, we align 1 Hz terminal telemetry with host-side probes to obtain portal-labeled traces spanning priority, post-quota throttling, stay-active operation, and residential service. These regimes manifest as distinct signatures in goodput, PoP RTT, and an internal-to-user ratio $R=C_{\mathrm{int}}/T_{\mathrm{user}}$. We further show that high-speed $R$ is stable over 30-minute sub-windows, that low-rate clusters have no aligned persistent obstruction or PoP-loss signature, and that clean high-speed dips do not move $R$ into the low-rate band. A lightweight rule on windowed medians separates high-speed from low-rate operation on this trace without operator visibility.

eess.SP↗

arXiv2026

Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs

Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated learning, FFT enables distributed agents to jointly refine a shared pretrained LLM by aggregating local LLM updates without sharing local raw data. However, FFT-based LLMs remain vulnerable to model manipulation threats, in which adversarial participants upload manipulated LLM updates that corrupt the aggregation process and degrade the performance of the global LLM. In this paper, we propose an Augmented Model maniPulation (AugMP) strategy against FFT-based LLMs. Specifically, we design a novel graph representation learning framework that captures feature correlations among benign LLM updates to guide the generation of malicious updates. To enhance manipulation effectiveness and stealthiness, we develop an iterative manipulation algorithm based on an augmented Lagrangian dual formulation. Through this formulation, malicious updates are optimized to embed adversarial objectives while preserving benign-like parameter characteristics. Experimental results across multiple LLM backbones demonstrate that the AugMP strategy achieves the strongest manipulation performance among all competing baselines, reducing the global LLM accuracy by up to $26\%$ and degrading the average accuracy of local LLM agents by up to $22\%$. Meanwhile, AugMP maintains high statistical and geometric consistency with benign updates, enabling it to evade conventional distance- and similarity-based defense methods.

cs.LG↗

arXiv2026

Deadline-Bound Finite-Object Delivery over Intermittent LEO Satellite Contact Plans under Residual-Service Accounting

Low-Earth-orbit (LEO) relay networks deliver finite objects -- sensing tiles, telemetry blocks, model updates, and checkpoints -- over intermittent inter-satellite and space-to-ground contact plans. Partial delivery is insufficient when the complete object misses its deadline. When an object is split across candidate paths, a path-private evaluation can count the same contact service more than once and silently under-count completion. We develop a residual-service-aware delivery layer that consumes candidate paths from contact-plan route generation and tests whether the complete object can be delivered before its deadline under per-edge first-in-first-out residual service. Under controlled shared-contact contention, path-private evaluation under-counts completion by up to 154 s and can report finite completion for a fixed plan with no residual-service completion. For edge-disjoint complementary contacts, the layer reduces to fixed-path service; we derive a sufficient service-budget condition under which two-way striping strictly enlarges the feasible payload region. We verify a restricted exhaustive reference, characterize runtime over a 20-180-satellite procedural contact model, and show that bounded two-way striping reduces mean and median gaps to the restricted reference by about 40%, while P90 and worst-case gaps remain unchanged.

eess.SP↗

arXiv2026

Access Selection for Finite-SNR Modal Recoverability in Sampled-Wave Receivers

Large-aperture wave receivers can contain a large number of candidate sensor locations, antenna ports, or measurement blocks, while hardware and processing constraints allow only a subset to be activated. In this paper, receiver selection is formulated as a finite-SNR modal-recoverability problem, where the selected subset is required to support reliable recovery in every direction of a prescribed modal subspace. However, large trace, log-det, or codebook-distance values alone do not ensure that every prescribed modal direction is resolved. Specifically, the proposed framework consists of three nested recoverability criteria for individual modal degrees, a joint target subspace, and target modes in the presence of active non-target modes. The third criterion, the Schur-complement information floor, provides an exact worst-direction posterior-error interpretation. We further show that stricter recoverability criteria require at least as many active receiver accesses and derive tests that identify reliability targets that remain unattainable even when all available accesses are activated. Next, we specialize the framework to finite spherical-wave sampling and compare greedy receiver-selection rules. Numerical results demonstrate that global log-det is generally more access-efficient at moderate reliability floors, whereas Schur-based selection is more effective at stringent floors. While this paper is motivated by holographic and XL-MIMO receivers, the framework can be applied to general sampled wave systems.

eess.SP↗

arXiv2026

Acoustic, VOC, and Multimodal Stress Source Localization in the Internet of Plants

The Internet of Plants (IoP) treats distributed plant networks as bio-sensing infrastructure for environmental monitoring, but spatial localization of stress sources within such networks remains unaddressed. Plant stress signals have fundamentally different spatial dynamics: acoustic emissions propagate omnidirectionally and independently of wind, while volatile organic compound (VOC) plumes are narrow and advection-dominated. We propose a two-stage, coarse-to-fine localization pipeline for a network of ``agent plants'' -- bio-hybrid sensing nodes embedded in the canopy. Stage 1 localizes the source via time-difference-of-arrival (TDOA) multilateration on acoustic time-of-arrival (ToA) readings; Stage 2 refines this estimate using a closed-form, steady-state Green's function model of VOC dispersion. A VOC informativeness gate and an inverse-variance fusion rule combine the two estimates according to their across-trial reliability, with graceful degradation to the TDOA-only estimate when no informative VOC signal is detected. We evaluate TDOA-only, VOC-only, and fused approaches on a new open-source dataset of 52 scenarios generated via a finite-volume advection-diffusion solver and a ray-based acoustic attenuation model. Across network densities of 1 to 50 agent plants, TDOA multilateration achieves sub-meter mean absolute error (MAE) once three or more agents are within acoustic range, far outperforming VOC-only localization (MAE $> 3$ m at all densities). Fusion differences from the TDOA-only estimate are small and statistically indistinguishable from noise in most cases. The pipeline is robust to physical parameter perturbations, ToA noise, the VOC gate threshold, and the bounding radius. TDOA localization is deployable with current acoustic hardware, whereas VOC localization remains a forward-looking capability pending advances in compact biochemical sensors.

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arXiv2026

HRTFformer: A Spatially-Aware Transformer for Individual HRTF Upsampling in Immersive Audio Rendering

Individual Head-Related Transfer Functions (HRTFs) are starting to be introduced in many commercial immersive audio applications and are crucial for realistic spatial audio rendering. However, one of the main hesitations regarding their introduction is that creating individual HRTFs is impractical at scale due to the complexities of the HRTF measurement process. To mitigate this drawback, HRTF spatial upsampling has been proposed with the aim of reducing the measurements required. While prior work has seen success with different machine learning (ML) approaches, these models often struggle with long-range preservation of local spatial variation patterns across neighbouring source directions and generalization at high upsampling factors. In this paper, we propose a novel transformer-based architecture for HRTF upsampling, leveraging the attention mechanism to better capture spatial correlations across the HRTF sphere. Working in the spherical harmonic (SH) domain, our model learns to reconstruct high-resolution HRTFs from sparse input measurements with significantly improved accuracy. To enhance spatial coherence, we introduce a neighbour dissimilarity loss that promotes magnitude smoothness, yielding more realistic upsampling. We evaluate our method using both perceptual localization models and objective spectral distortion metrics. Experiments show that our model outperforms existing methods across several evaluation metrics in generating realistic, high-fidelity HRTFs.

cs.SD↗

arXiv2026

A reversed solar illumination dependence of unintended emission from Starlink Direct-to-Cell satellites at 72-234 MHz with the EDA2

Second-generation Starlink Direct-to-Cell (DTC) satellites carry an additional payload for direct cellular phone connectivity whose unintended electromagnetic radiation (UEMR) at sub-300 MHz frequencies has not been individually characterised. We reanalyse 112,534 detections from 1,806 Starlink satellites observed with the Engineering Development Array version 2 (EDA2) at 21 frequencies between 72.685 and 234.375 MHz (Grigg et al. 2025), separating 175 DTC and 1,623 Ku-only v2-Mini comparison satellites via the McDowell General Catalogue (McDowell 2020). DTC satellites emit a range-corrected flux density 1.45x that of the Ku-only comparison (Cliff's delta = +0.30, p = 2.6e-11). At 230.469 MHz the XX detection fraction reaches 0.811 against a 0.481 baseline (p ~ 1e-274), and 11 of 21 frequency channels show Benjamini-Hochberg-significant polarisation anomalies. The DTC population is brighter in eclipse than in sunlight (illuminated/eclipsed flux density ratio 0.47) while the Ku-only comparison shows the opposite sense (1.18); the reversal persists across altitude, sub-satellite latitude, frequency, and launch-epoch matching. The reversal strongly disfavours UEMR mechanisms that scale monotonically with instantaneous solar photocurrent and favours an active on-board source whose effective duty cycle is larger at lower equilibrium temperature. Within the 230.469 MHz coarse channel, fine-channel inspection isolates the excess to a single ~24 kHz bin near 230.627 MHz, tail-driven and absent at five control channels. Three falsifiable mechanism-discrimination tests show this feature is not coincident with the LOFAR-resolved Bassa et al. (2024) clock fundamentals, is unresolved at the EDA2 24 kHz resolution, and is heterogeneously expressed across the v2-Mini fleet rather than driven by a few permanently bright units or by uniform thermal scaling.

eess.SP↗

arXiv2026

Dispersion-Domain Detection for Mobile Molecular Communication Under Multiplicative Geometry Uncertainty

Mobile molecular communication (MC) links with counting receivers are sensitive to transmitter--receiver geometry especially when nodes are mobile. We study binary detection from within-symbol count observations with unknown finite-memory inter-symbol interference (ISI) and a block-constant multiplicative geometry gain. Under a mixed-Poisson view mobility and geometry uncertainty can randomize the latent received intensity and create extra-Poisson dispersion. We propose a profiled dispersion-domain statistic $T_k^{(Δ)}$ formed after profiling the deterministic mean shape. The statistic subtracts the intrinsic Poisson component and normalizes by the squared profiled mean to target threshold stability under the stated multiplicative-gain model. Activity gating makes conditional and gate-integrated false-alarm probabilities explicit. We characterize $T_k^{(Δ)}$ using a time-series central-limit-theorem (CLT)-motivated Gaussian working approximation with long-run-variance dependence correction yielding Gaussian-approximate receiver operating characteristic (ROC)/bit-error-rate (BER) formulas and separability design metrics. Simulations with symbol-dependent active-Brownian mobility and finite-memory ISI support the proposed mechanism show empirical threshold stability over the tested gain range and indicate usefulness when mean-domain differences are weak unreliable or intentionally suppressed.

eess.SY↗

arXiv2026

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.

eess.SY↗

arXiv2026

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 $K = 16$.

eess.SP↗