arXiv subjects

Indrakshi Dey

Publications and source records attributed to Indrakshi Dey.

At least 37 records · Page 2Linked to original sources

arXiv2026

Adaptive RSMA-OMA for Resilient MIMO Networks Under Imperfect CSI and SIC

This paper addresses the challenge of power control in Rate-Splitting Multiple Access (RSMA) systems for downlink Multi-Input Multi-Output (MIMO) networks under practical impairments such as spatial correlation, imperfect Channel State Information (CSI), and residual Successive Interference Cancellation (SIC) errors. We propose a novel degeneracyaware framework that adaptively adjusts the power allocation between the common and private streams, ensuring optimal performance despite CSI uncertainty and imperfect SIC. Our approach incorporates a dynamic switching mechanism between RSMA and Orthogonal Multiple Access (OMA) to maintain system feasibility and resilience in the face of these impairments. Extensive analytical and simulation results demonstrate that the proposed framework significantly enhances power efficiency, mitigates outage probability, and improves overall system robustness, making RSMA a viable and efficient solution for modern wireless networks with realistic CSI and SIC conditions.

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arXiv2026

Graph-Spectral Fusion of Wavelet Packets and Higher-Order Statistics for Anomaly Detection in Industrial IoT Networks

Industrial Internet of Things (IIoT) networks demand reliable anomaly detection under harsh wireless conditions, yet most detectors fail on four fronts: hostile fading, stealthy non-Gaussian faults, discarded spatial structure, or constrained edge hardware. We propose Graph WPT+HOS, a classical label-free detector that fuses three complementary views: the Graph Fourier Transform (GFT) for spatial inconsistency, the Wavelet Packet Transform (WPT) for transient time-frequency localization, and Higher-Order Statistics (HOS) for non-Gaussian shape. The fused features are scored by a Mahalanobis distance with Ledoit-Wolf shrinkage and converted to alarms by a one-sided CUSUM. The pipeline is asymptotically optimal at the decision stage, requires no labeled anomalies, and runs on ARM-class edge hardware without GPU acceleration. Across six baselines and four domain-shift regimes under Rayleigh fading, Graph WPT+HOS attains the highest ROC-AUC and PR-AUC and reduces CUSUM detection latency.

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arXiv2026

Degeneracy-Aware Functional and Algorithmic Resilience in Virtualized 6G Networks Under Correlated Failures

Redundancy is widely used to sustain service continuity in programmable and virtualized networks; however, replicated functions often share platforms, software stacks, and control dependencies, making them vulnerable to correlated failures. Consequently, replica counts alone may overestimate true resilience. This paper adopts a degeneracy-aware perspective, where robustness depends on the availability of structurally diverse yet functionally equivalent alternatives. We formalize this perspective through three complementary metrics: the Functional Substitution Score (FSS), which quantifies structurally distinct substitutes for a function; the Algorithmic Resilience Quotient (ARQ), which measures diversity among algorithms that remain comparable in delivered performance; and the Multi-Layer Degeneracy Index (MLDI), which captures how functional diversity is distributed across architectural layers. Using targeted disruption protocols on a synthesized data, we show that redundancy and robustness can diverge substantially. The results show that FSS separates structural diversity from replica count, ARQ distinguishes genuine algorithmic alternatives from near-duplicate implementations, and MLDI captures cross-layer buffering that remains hidden under redundancy-only analysis. These findings establish degeneracy as a practical resilience primitive for open, disaggregated, and virtualized 6G systems.

cs.NI↗

arXiv2026

Degeneracy-Aware Agent-Based Resource Allocation for Multi-User MIMO RSMA Network

This paper proposes a pilot-aware, degeneracy-driven Agent-Based Modelling (ABM) framework for distributed resource allocation in RSMA-enabled multi-user MIMO systems under imperfect Channel State Information (CSI) and residual Successive Interference Cancellation (SIC) error. The centralized RSMA power allocation problem is reformulated as a distributed multi-agent system, where users operate as autonomous agents that iteratively adapt transmit powers based on locally observed feasibility conditions. To capture the joint impact of interference coupling, CSI estimation errors, pilot overhead, and residual SIC error, a novel degeneracy index defined as the ratio of target to achieved signal-to-interference-plus-noise ratio (SINR) is introduced as a unified feasibility metric. This enables a scalable fixed-point power control mechanism that characterizes the feasible operating region without requiring global CSI. Analytical expressions for user-level and system-level outage probabilities are derived under spatially correlated fading, providing insights into reliability under practical impairments. The fundamental interplay between degeneracy, outage probability, and effective throughput is established, revealing that system performance is governed by the feasibility of the bottleneck user. To further enhance resilience, Degeneracy-Weighted Path Robustness (DWPR) and Functional Substitution Score (FSS) are incorporated to exploit path diversity and functional redundancy. Numerical results show that the proposed framework achieves near-centralized performance in sparse networks, while providing notable throughput gains and improved scalability in dense deployments, highlighting its effectiveness for robust and distributed resource management in next-generation wireless systems.

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arXiv2026

RIS-aided Wireless Communication with Movable Elements Geometry Impact on Performance

Reconfigurable Intelligent Surfaces (RIS) are known as a promising technology to improve the performance of wireless communication networks, and have been extensively studied. Movable Antennas (MA) are a novel technology that fully exploits the antenna placement for enhancing the system performance. This article aims at evaluating the impact of transmit power and number of antenna elements on the outage probability performance of an MA-enabled RIS structure (MA-RIS), compared to existing Fixed-Position Antenna RIS (FPA-RIS). The change in geometry caused by the movement of antennas and its implications for the effective number of illuminated elements, are studied for 1D and 2D array structures. Our numerical results confirm the performance advantage provided by MA-RIS, achieving 24\% improvement in outage probability, and 2 dB gain in Signal-to-Noise Ratio (SNR), as compared to FPA-RIS.

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arXiv2026

Blockage-aware Hierarchical Codebook Design for RIS-Assisted Movable Antenna Systems

In this paper, we propose a novel blockage-aware hierarchical beamforming framework for movable antenna (MA) systems operating at millimeter-wave (mm-Wave) frequencies. While existing works on MA systems have demonstrated performance gains over conventional systems, they often neglect the design of specialized codebooks to leverage MA's unique capabilities and address the challenges of increased energy consumption and latency inherent to MA systems. To address these aspects, we first integrate blockage detection into the codebook design process based on the Gerchberg-Saxton (GS) algorithm, significantly reducing inefficiencies due to beam evaluations done in blocked directions. Then, we use a two-stage approach to reduce the complexity of the joint beamforming and Reconfigurable Intelligent Surfaces (RIS) optimization problem. The simulations demonstrate that the proposed adaptive codebook successfully improves the Energy Efficiency (EE) and reduces the beam training overhead, substantially boosting the practical deployment potential of RIS-assisted MA systems in future wireless networks.

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arXiv2025

Spatio-Temporal Graph Neural Networks for Dairy Farm Sustainability Forecasting and Counterfactual Policy Analysis

This study introduces a novel data-driven framework and the first-ever county-scale application of Spatio-Temporal Graph Neural Networks (STGNN) to forecast composite sustainability indices from herd-level operational records. The methodology employs a novel, end-to-end pipeline utilizing a Variational Autoencoder (VAE) to augment Irish Cattle Breeding Federation (ICBF) datasets, preserving joint distributions while mitigating sparsity. A first-ever pillar-based scoring formulation is derived via Principal Component Analysis, identifying Reproductive Efficiency, Genetic Management, Herd Health, and Herd Management, to construct weighted composite indices. These indices are modelled using a novel STGNN architecture that explicitly encodes geographic dependencies and non-linear temporal dynamics to generate multi-year forecasts for 2026-2030.

cs.LG↗

arXiv2025

Wavelet-Packet-based Noise Signatures With Higher-Order Statistics for Anomaly Prediction

This note develops the first-ever noise-centric anomaly prediction method for a fused discrete-time signal. A Wavelet Packet Transform (WPT) provides a time--frequency expansion in which structure and residual can be separated via orthogonal projection. Higher-Order Statistics (HOS), particularly the third-order cumulant (and its bispectral interpretation), quantify non-Gaussianity and nonlinear coupling in the extracted residual. Compact noise signatures are constructed and an analytically calibrated Mahalanobis detector yields a closed-form decision rule with non-central chi-square performance under mean-shift alternatives. Propositions and proofs establish orthonormality, energy preservation, Gaussian-null behavior of cumulants, and the resulting test statistics.

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arXiv2025

Engel p-adic Isogeny-based Cryptography over Laurent Series: Foundations, Security, and an ESP32 Implementation

Securing the Internet of Things (IoT) against quantum attacks requires public-key cryptography that (i) remains compact and (ii) runs efficiently on microcontrollers, capabilities many post-quantum (PQ) schemes lack due to large keys and heavy arithmetic. We address both constraints simultaneously with, to our knowledge, the first-ever isogeny framework that encodes super-singular elliptic-curve isogeny data via novel Engel expansions over the p-adic Laurent series. Engel coefficients compress torsion information, thereby addressing the compactness constraint, yielding public keys of ~1.1 - 16.9 kbits preserving the hallmark small sizes of isogeny systems. Engel arithmetic is local and admits fixed-precision p-adic operations, enabling micro-controller efficiency with low-memory, branch-regular kernels suitable for embedded targets.

cs.CR↗

arXiv2025

QMA Complete Quantum-Enhanced Kyber: Provable Security Through CHSH Nonlocality

Post-quantum cryptography (PQC) must secure large-scale communication systems against quantum adversaries where classical hardness alone is insufficient and purely quantum schemes remain impractical. Lattice-based key encapsulation mechanisms (KEMs) such as CRYSTALS-Kyber provide efficient quantum-resistant primitives but rely solely on computational hardness assumptions that are susceptible to hybrid classical-quantum attacks. To overcome this limitation, we introduce the first Clauser-Horne-Shimony-Holt (CHSH)-certified Kyber protocol, which embeds quantum non-locality verification directly within the key exchange phase. The proposed design integrates CHSH entanglement tests using Einstein-Podolsky-Rosen (EPR) pairs to yield measurable quantum advantage values exceeding classical correlation limits, thereby coupling information--theoretic quantum guarantees with lattice-based computational security. Formal reductions demonstrate that any polynomial-time adversary breaking the proposed KEM must either solve the Module Learning With Errors (Module-LWE) problem or a Quantum Merlin-Arthur (QMA)-complete instance of the 2-local Hamiltonian problem, under the standard complexity assumption QMA $\subset$ NP. The construction remains fully compatible with the Fujisaki-Okamoto (FO) transform, preserving chosen-ciphertext attack (CCA) security and Kyber's efficiency profile. The resulting CHSH-augmented Kyber scheme therefore establishes a mathematically rigorous, hybrid post-quantum framework that unifies lattice cryptography and quantum non-locality to achieve verifiable, composable, and forward-secure key agreement.

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arXiv2025

Measurement Strategies and Estimation Precision in Quantum Network Tomography

This work investigates measurement strategies for link parameter estimation in Quantum Network Tomography (QNT), where network links are modeled as depolarizing quantum channels distributing Werner states. Three distinct measurement schemes are analyzed: local Z-basis measurements (LZM), joint Bell-state measurements (JBM), and pre-shared entanglement-assisted measurements (PEM). For each scheme, we derive the probability distributions of measurement outcomes and examine how noise in the distributed states influences estimation precision. Closed-form expressions for the Quantum Fisher Information Matrix (QFIM) are obtained, and the estimation precision is evaluated through the Quantum Cramer-Rao Bound (QCRB). Numerical analysis reveals that the PEM scheme achieves the lowest QCRB, offering the highest estimation accuracy, while JBM provides a favorable balance between precision and implementation complexity. The LZM method, although experimentally simpler, exhibits higher estimation error relative to the other schemes; however, it outperforms JBM in high-noise regimes for single-link estimation. We further evaluate the estimation performance on a four-node star network by comparing a JBM-only configuration with a hybrid configuration that combines JBM and LZM. When two monitors are used, the JBM-only strategy outperforms the hybrid approach across all noise regimes. However, with three monitors, it achieves a lower QCRB only in low-noise regimes with heterogeneous links. The results establish a practical basis for selecting measurement strategies in experimental quantum networks, enabling more accurate and scalable link parameter estimation under realistic noise conditions.

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arXiv2025

Next-Generation MAC Technique for Priority Handling in Industrial Cyber-Physical Systems

Next Generation Media Access Control (NGMA) techniques have been designed to support diverse applications with heterogeneous priorities. In industrial cyber-physical systems (CPS), the number of connected devices and systems is expected to grow significantly, demanding dependable and prompt network services. In this work, we present a novel scheme, Dynamic Fragmentation-MAC (DyFrag-MAC) that offers dynamic, differentiated channel access to the traffic of various priorities. DyFrag-MAC works on fragmenting the data of normal priority in order to support early delivery of urgent priority data. In prior work, urgent priority data either had to wait for the complete transmission of lower-priority packets or relied on multi-channel protocols to gain access. We compared the proposed fragmentation scheme with FROG-MAC and industrial Deterministic and Synchronous Multi-channel Extension (i-DSME). FROG-MAC fragmented the lower priority packets, but did not adjust the fragment size dynamically, whereas i-DSME utilized multiple channels and adaptive contention mechanisms; both protocols lack the ability to preempt ongoing lower-priority transmissions. Hence, the performance evaluation in terms of average delay and throughput reveals better performance of DyFRAG-MAC for the heterogeneous traffic.

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arXiv2025

Optimizing Next Generation Wireless BAN with Prioritized Access for Heterogeneous Traffic

Efficient management of heterogeneous traffic with varying priorities is critical in Wireless Body Area Networks (WBANs). The priority mechanisms embedded in Media Access Control (MAC) schemes largely govern the performance of WBAN in terms of reliability, delay and energy efficiency. Minimizing the delay between packet generation and reception is critical for enhancing WBAN performance and associated health outcomes; however, delay optimization must be tailored to each traffic priority. In this work, we proposed a novel priority-based MAC protocol, Adaptive and Dynamic Polling MAC for Prioritized Traffic (ADP2-MAC), designed to support heterogeneous traffic in WBANs. The protocol utilizes a probabilistic approach to dynamically determine channel polling/listening intervals. ADP2-MAC not only identifies traffic arrival patterns to determine optimal polling intervals but also interrupts the transmission of lower-priority data when urgent packets are expected. The performance of ADP2-MAC has been compared with the MAC protocol for Variable Data Rates (MVDR) which supports heterogeneous traffic by assigning different data rates based on traffic priority. ADP2-MAC outperforms MVDR due to its use of probabilistic polling intervals and an interruption mechanism designed to efficiently handle urgent-priority data.

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arXiv2025

Efficient Medium Access Control for Low-Latency Industrial M2M Communications

Efficient medium access control (MAC) is critical for enabling low-latency and reliable communication in industrial Machine-to-Machine (M2M) net-works, where timely data delivery is essential for seamless operation. The presence of multi-priority data in high-risk industrial environments further adds to the challenges. The development of tens of MAC schemes over the past decade often makes it a tough choice to deploy the most efficient solu-tion. Therefore, a comprehensive cross-comparison of major MAC protocols across a range of performance parameters appears necessary to gain deeper insights into their relative strengths and limitations. This paper presents a comparison of Contention window-based MAC scheme BoP-MAC with a fragmentation based, FROG-MAC; both protocols focus on reducing the delay for higher priority traffic, while taking a diverse approach. BoP-MAC assigns a differentiated back-off value to the multi-priority traffic, whereas FROG-MAC enables early transmission of higher-priority packets by fragmenting lower-priority traffic. Simulations were performed on Contiki by varying the number of nodes for two traffic priorities. It has been shown that when work-ing with multi-priority heterogenous data in the industrial environment, FROG-MAC results better both in terms of delay and throughput.

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arXiv2025

A Study on Delay Assessment for Heterogenous Traffic in VANET

Vehicular Ad hoc Networks (VANETs) comprise of multi-priority hetero-genous nodes, both stationary and/or mobile. The data generated by these nodes may include messages relating to information, safety, entertainment, traffic management and emergency alerts. The data in the network needs dif-ferentiated service based on the priority/urgency. Media Access Control (MAC) protocols hold a significant value for managing the data priority. This paper studies a comparison of 802.11p which is a standard PHY and MAC protocol for VANET with a fragmentation-based protocol, FROG-MAC. The major design principle of 802.11-p is to allow direct Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication without associa-tion, using Enhanced Distributed Channel Access (EDCA) to prioritize safety-critical messages. However, if non-critical messages already start to transmit, the nodes with critical data have to wait. FROG-MAC reduces this delay by transmitting normal packets in fragments with short pauses between them, al-lowing urgent packets to access the channel during these intervals. Simula-tions have been performed to assess the delay and throughput for high and low priority data. We report that FROG-MAC improves both the performance parameters due to offering an early channel access to the emergency traffic.

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arXiv2025

IoT-Enabled Sleep Monitoring and Cognitive Assessment for Evaluating Teacher Well-Being

Sleep quality is an important indicator of the efficient cognitive function for high school teachers. Due to the high work stress and multi-tasking expectations, the teachers often face issues with their sleep quality and cognitive function, which has a clearly negative influence on their teaching abilities. In this work, we propose a unique but simple method of deploying Internet of Things (IoT) technology to monitor the sleep quality of high school teachers at Pakistan. Smart watches embedded with pulse rate and SpO2 sensors were used to collect data and categorize the sleep quality as "poor", "fair" or "good". Moreover, we used a psychological tool, Cognitive Assessment Questionnaire (CAQ) for the self-assessment of teachers' cognitive function. The study was conducted over 208 high school teachers from across Pakistan. It has been found that most of the teachers had a poor sleep quality and cognitive function; The link between these two variables indicate that the workload and other factors must be improved for the teachers to ensure their well-being, which will in turn have a positive impact on their teaching quality.

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arXiv2025

Delay Management Using Packet Fragmentation in Wireless Industrial Automation Systems

Managing delay is one of the core requirements of industrial automation applications due to the high risk associated for equipment and human lives. Using efficient Media Access Control (MAC) schemes guarantees the timely transmission of critical data, particularly in the industrial environments where heterogeneous data is inherently expected. This paper compares the performance of Fragmentation based MAC (FROG-MAC) against Fuzzy Priority Scheduling based MAC (FPS-MAC), both of which have been designed to optimize the performance of heterogenous wireless networks. Contiki has been used as a simulation platform and a single hop star topology has been assumed to resemble the industrial environment. It has been shown that FROG-MAC has the potential to outperform FPS-MAC in terms of energy efficiency and delay both, due to its inherent feature of interrupting ongoing lower priority transmission on the channel.

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arXiv2025

A Comparative Analysis of High-Level vs. Low-Level Simulations for Dynamic MAC Protocols in Wireless Sensor Networks

Simulation studies are conducted at different levels of details for assessing the performance of Media Access Control (MAC) protocols in Wireless Sensor Networks (WSN). In the present-day scenario where hundreds of MAC protocols have been proposed, it is important to assess the quality of performance evaluation being conducted for each of the proposed protocols. It therefore becomes crucial to compare the results of high-level theoretical simulations with the detailed implementation results before any network protocol could be deployed for a real-world scenario. In this work, we present a comparison of high-level theoretical and detailed implementation results for Adaptive and Dynamic Polling-MAC (ADP-MAC). MATLAB has been used for conducting initial theoretical simulations and TinyOS has been used to develop the detailed implementation of protocol for Mica2 platform. Performance evaluation of ADP-MAC using the two levels of simulation has been conducted based on energy and delay. In the high-level implementation, energy consumption was found to be decreasing whereas delay was found to be increasing for increasing channel polling intervals. On the other hand, when detailed implementation was developed, it was observed that both energy consumption and delay revealed an increasing trend with the increasing polling intervals. Therefore, it has been shown that the trends for high- and low-level simulations for ADP-MAC are significantly different, due to the lack of realistic assumptions in the higher-level study.

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