arXiv subjects

Aydin Sezgin

Publications and source records attributed to Aydin Sezgin.

At least 37 records · Page 2Linked to original sources

arXiv2026

Measurement-Based Validation of Geometry-Driven RIS Beam Steering in Industrial Environments

Reconfigurable intelligent surfaces (RISs) offer programmable control of radio propagation for future wireless systems. For configuration, geometry-driven analytical approaches are appealing for their simplicity and real-time operation, but their performance in challenging environments such as industrial halls with dense multipath and metallic scattering is not well established. To this end, we present a measurement-based evaluation of geometry-driven RIS beam steering in a large industrial hall using a 5 GHz RIS prototype. A novel RIS configuration is proposed in which four patch antennas are mounted in close proximity in front of the RIS to steer the incident field and enable controlled reflection. For this setup, analytically computed, quantized configurations are implemented. Two-dimensional received power maps from two measurement areas reveal consistent, spatially selective focusing. Configurations optimized near the receiver produce clear power maxima, while steering to offset locations triggers a rapid 20-30 dB reduction. With increasing RIS-receiver distance, elevation selectivity broadens due to finite-aperture and geometric constraints, while azimuth steering remains robust. These results confirm the practical viability of geometry-driven RIS beam steering in industrial environments and support its use for spatial field control and localization under non-ideal propagation.

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arXiv2026

Deep Unfolded Fractional Optimization for Maximizing Robust Throughput in 6G Networks

The sixth-generation (6G) of wireless communication networks aims to leverage artificial intelligence tools for efficient and robust network optimization. This is especially the case since traditional optimization methods often face high computational complexity, motivating the use of deep learning (DL)-based optimization frameworks. In this context, this paper considers a multi-antenna base station (BS) serving multiple users simultaneously through transmit beamforming in downlink mode. To account for robustness, this work proposes an uncertainty-injected deep unfolded fractional programming (UI-DUFP) framework for weighted sum rate (WSR) maximization under imperfect channel conditions. The proposed method unfolds fractional programming (FP) iterations into trainable neural network layers refined by projected gradient descent (PGD) steps, while robustness is introduced by injecting sampled channel uncertainties during training and optimizing a quantile-based objective. Simulation results show that the proposed UI-DUFP achieves higher WSR and improved robustness compared to classical weighted minimum mean square error, FP, and DL baselines, while maintaining low inference time and good scalability. These findings highlight the potential of deep unfolding combined with uncertainty-aware training as a powerful approach for robust optimization in 6G networks.

cs.IT↗

arXiv2025

A Lightweight Framework for Integrated Sensing and Communications with RIS

Reconfigurable Intelligent Surfaces (RIS) have been recognized as a promising technology to enhance both communication and sensing performance in integrated sensing and communication (ISAC) systems for future 6G networks. However, existing RIS optimization methods for improving ISAC performance are mainly based on semidefinite relaxation (SDR) or iterative algorithms. The former suffers from high computational complexity and limited scalability, especially when the number of RIS elements becomes large, while the latter yields suboptimal solutions whose performance depends on initialization. In this work, we introduce a lightweight RIS phase design framework that provides a closed-form solution and explicitly accounts for the trade-off between communication and sensing, as well as proportional beam gain distribution toward multiple sensing targets. The key idea is to partition the RIS configuration into two parts: the first part is designed to maximize the communication performance, while the second introduces small perturbations to generate multiple beams for multi-target sensing. Simulation results validate the effectiveness of the proposed approach and demonstrate that it achieves performance comparable to SDR but with significantly lower computational complexity.

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arXiv2025

RL-Aided Cognitive ISAC: Robust Detection and Sensing-Communication Trade-offs

This paper proposes a reinforcement learning (RL)-aided cognitive framework for massive MIMO-based integrated sensing and communication (ISAC) systems employing a uniform planar array (UPA). The focus is on enhancing radar sensing performance in environments with unknown and dynamic disturbance characteristics. A Wald-type detector is employed for robust target detection under non-Gaussian clutter, while a SARSA-based RL algorithm enables adaptive estimation of target positions without prior environmental knowledge. Based on the RL-derived sensing information, a joint waveform optimization strategy is formulated to balance radar sensing accuracy and downlink communication throughput. The resulting design provides an adaptive trade-off between detection performance and achievable sum rate through an analytically derived closed-form solution. Monte Carlo simulations demonstrate that the proposed cognitive ISAC framework achieves significantly improved detection probability compared to orthogonal and non-learning adaptive baselines, while maintaining competitive communication performance. These results underline the potential of RL-assisted sensing for robust and spectrum-efficient ISAC in next-generation wireless networks.

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arXiv2025

Optimizing Movable Antenna Position and Transmissive RIS Phase for Efficient Base Station Design

Movable antennas (MA) and transmissive reconfigurable intelligent surfaces (TRIS) represent two innovative technologies that significantly enhance the flexibility of wireless communication systems. In this paper, we propose a novel and compact base station architecture that synergistically integrates a movable antenna with a transmissive RIS in the near field, enabling joint optimization of antenna positioning and TRIS phase adjustments. The proposed model compensates for phase quantization loss and significantly enhances signal strength, even with low-resolution (1-2 bit) phase shifters. Leveraging this framework, we systematically evaluate system performance as a function of TRIS size and antenna placement. Our results indicate that antenna mobility provides an additional degree of freedom to enhance the desired signal and achieve a higher SNR, particularly when combined with TRIS capabilities. These findings demonstrate that MA-TRIS integration offers a cost-effective and energy-efficient pathway toward compact 6G base stations, combining hardware simplicity with strong performance gains.

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arXiv2025

Event-Based Framework for Agile Resilience in Criticality-Aware Wireless Networks

As mission- and safety-critical wireless applications grow in complexity and diversity, next-generation wireless systems must meet increasingly stringent and multifaceted requirements. These systems demand resilience along with enhanced intelligence and adaptability to ensure reliable communication under diverse conditions. This paper proposes an event-based multi-stage resilience framework for systematically integrating complementary error mitigation techniques in wireless networks. The framework is applied to uplink transmission of mixedcriticality data under random link blockages. A key component is a novel mixed-criticality rate-splitting multiple access (MC-RSMA) scheme that combines multi- and single-connectivity to balance rate and blockage robustness. MC-RSMA is complemented by one-sided access point cooperation and central decoding, which are integrated into an event-driven algorithm. Here, increasingly effective but more complex mechanisms are activated sequentially to systematically counteract blockages while balancing resilience with cost. From a cross-layer perspective, two transmit power allocation problems are formulated: One for separate decoding and one for central decoding, to ensure fair queue utilization under heterogeneous quality-of-service requirements. Extensive simulations are used to evaluate the delay performance under varying blockage durations and examine the cost tradeoffs among resilience mechanisms within the proposed framework. Results show that the proposed framework achieves resilience across disruption regimes: MC-RSMA balances efficiency and robustness as a criticality-aware core scheme, active robustness strategies handle frequent short-term fluctuations, and adaptive recovery ensures performance during rare, prolonged blockages.

cs.IT↗

arXiv2025

Hardware-Efficient Cognitive Radar: Multi-Target Detection with RL-Driven Transmissive RIS

Cognitive radar has emerged as a key paradigm for next-generation sensing, enabling adaptive, intelligent operation in dynamic and complex environments. Yet, conventional cognitive multiple-input multiple-output (MIMO) radars offer strong detection performance but suffer from high hardware complexity and power demands. To overcome these limitations, we develop a reinforcement learning (RL)-based framework that leverages a transmissive reconfigurable intelligent surface (TRIS) for adaptive beamforming. A state-action-reward-state-action (SARSA) agent tunes TRIS phase shifts to improve multi-target detection in low signal-to-noise ratio (SNR) conditions while operating with far fewer radio frequency (RF) chains. Simulations confirm that the proposed TRIS-RL radar matches or, for large number of elements, even surpasses MIMO performance with reduced cost and energy requirements.

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arXiv2025

6G Resilience -- White Paper

6G must be designed to withstand, adapt to, and evolve amid prolonged, complex disruptions. Mobile networks' shift from efficiency-first to sustainability-aware has motivated this white paper to assert that resilience is a primary design goal, alongside sustainability and efficiency, encompassing technology, architecture, and economics. We promote resilience by analysing dependencies between mobile networks and other critical systems, such as energy, transport, and emergency services, and illustrate how cascading failures spread through infrastructures. We formalise resilience using the 3R framework: reliability, robustness, resilience. Subsequently, we translate this into measurable capabilities: graceful degradation, situational awareness, rapid reconfiguration, and learning-driven improvement and recovery. Architecturally, we promote edge-native and locality-aware designs, open interfaces, and programmability to enable islanded operations, fallback modes, and multi-layer diversity (radio, compute, energy, timing). Key enablers include AI-native control loops with verifiable behaviour, zero-trust security rooted in hardware and supply-chain integrity, and networking techniques that prioritise critical traffic, time-sensitive flows, and inter-domain coordination. Resilience also has a techno-economic aspect: open platforms and high-quality complementors generate ecosystem externalities that enhance resilience while opening new markets. We identify nine business-model groups and several patterns aligned with the 3R objectives, and we outline governance and standardisation. This white paper serves as an initial step and catalyst for 6G resilience. It aims to inspire researchers, professionals, government officials, and the public, providing them with the essential components to understand and shape the development of 6G resilience.

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arXiv2025

Optimized Frequency-Diverse Movable Antenna Arrays for Directional Secrecy in Wireless Systems

Movable-antenna (MA) arrays are envisioned as a promising technique for enhancing secrecy performance in wireless communications by leveraging additional spatial degrees of freedom. However, when the eavesdropper is located in the same direction as the legitimate user, particularly in mmWave/THz bands where line-of-sight (LOS) propagation dominates, the secrecy performance of MA arrays becomes significantly limited, thus directionally insecure. To address this challenge, we employ a joint design that combines an MA array with a frequency-diverse array (FDA) at the transmitter to secure the transmission across both range and direction. Specifically, we derive closed-form expressions for the optimal antenna positions and frequency shifts, assuming small perturbations in both parameters from a linear frequency-diverse MA configuration. Furthermore, we compare the worst-case secrecy rate under this minor perturbation assumption with that obtained under a general constraint, where simulated annealing is employed to numerically determine the optimal parameters. Simulation results confirm that the proposed optimized frequency diverse MA approach significantly enhances secrecy performance in the presence of an eavesdropper aligned with the direction of the legitimate receiver.

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arXiv2025

When Every Symbol Counts: Resilient Wireless Systems Under Finite Blocklength Constraints

As 6G evolves, wireless networks become essential for critical operations and enable innovative applications that demand seamless adaptation to dynamic environments and disruptions. Because these vital services require uninterrupted operation, their resilience to unforeseen disruptions is essential. However, implementing resilience necessitates rapid recovery procedures, which operate in the finite blocklength (FBL) regime, where short packets and added error-correction overhead can severely degrade communication efficiency. Due to this performance loss, always attempting recovery can backfire and result in worse outcomes than simply enduring the disruption under longer blocklengths. In this work, we study these effects of FBL constraints within a resilience framework, incorporating reconfigurable intelligent surfaces (RIS) to enhance adaptation capabilities. By actively shaping the wireless environment, RIS help counteract some of the performance losses caused by FBL, enabling more effective recovery from disruptions. Numerical results reveal two critical blocklength thresholds: the first enables full recovery from the FBL penalty, while the second, at a higher blocklength, allows the system to recover from both the FBL penalty and the initial disruption, yielding a significant improvement in resilience performance. Additionally, we show that the number of RIS elements shifts these thresholds, enabling faster reconfiguration with shorter blocklengths and providing insights to the trade-offs between rate, blocklength, and reconfiguration effort under FBL conditions.

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arXiv2025

Anomaly Detection for Sensing Security

Various approaches in the field of physical layer security involve anomaly detection, such as physical layer authentication, sensing attacks, and anti-tampering solutions. Depending on the context in which these approaches are applied, anomaly detection needs to be computationally lightweight, resilient to changes in temperature and environment, and robust against phase noise. We adapt moving average filters, autoregression filters and Kalman filters to provide predictions of feature vectors that fulfill the above criteria. Different hypothesis test designs are employed that allow omnidirectional and unidirectional outlier detection. In a case study, a sensing attack is investigated that employs the described algorithms with various channel features based on commodity WiFi devices. Thereby, various combinations of algorithms and channel features show effectiveness for motion detection by an attacker. Countermeasures only utilizing transmit power randomization are shown insufficient to mitigate such attacks if the attacker has access to channel state information (CSI) measurements, suggesting that mitigation solutions might require frequency-variant randomization.

cs.IT↗

arXiv2025

Terahertz Defect Detection in Multi-Layer Materials Using Echo Labeling

Non-destructive testing is an important technique for detecting defects in multi-layer materials, enabling the evaluation of structural integrity without causing damage on test materials. Terahertz time-domain spectroscopy (THz-TDS) offers unique capabilities for this purpose due to its sensitivity and resolution. Inspired by room geometry estimation methods in acoustic signal processing, this work proposes a novel approach for defect detection in multi-layer composite materials using THz-TDS, enhanced by high-power sources. The proposed method utilizes Euclidean distance matrices to reduce problem complexity compared to state-of-the-art approaches, and effectively distinguishes and maps higher-order reflections from sublayers, enabling precise defect localization in composite materials without artifacts.

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arXiv2025

The Wideband Analysis of the Impact of I/Q Imbalance on THz Communication

The terahertz (THz) band is a promising solution to the increasing data traffic demands of future wireless networks. However, developing transceivers for THz communication is a complex and toilsome task due to the difficulty in designing devices that operate at this frequency and the impact of hardware impairments on performance. This paper investigates the impact of radio frequency (RF) impairment, in-phase/quadrature imbalance (IQI). To this end, we express an IQI model for the THzspecific array-of-subarrays (AoSA) architecture considering the unique features of THz communication; vast bandwidth, severe power drawdown, and pencil-like beams. We further model the impact of IQI in the power limited regime in order to investigate the power and ultra-wideband trade-off. To achieve this, we express the spectral efficiency in terms of wideband slope and bit energy to noise ratio which are the two important information theoretic metrics that reveals the performance of the ultrawideband systems as in THz communication. Our results show that THz systems with IQI have a strict limit in achievable rate although they provide immense spectrum. We also demonstrate with our simulation results that compared to low frequencies, IQI is a more serious concern in THz links.

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arXiv2025

Towards Smarter Sensing: 2D Clutter Mitigation in RL-Driven Cognitive MIMO Radar

Motivated by the growing interest in integrated sensing and communication for 6th generation (6G) networks, this paper presents a cognitive Multiple-Input Multiple-Output (MIMO) radar system enhanced by reinforcement learning (RL) for robust multitarget detection in dynamic environments. The system employs a planar array configuration and adapts its transmitted waveforms and beamforming patterns to optimize detection performance in the presence of unknown two-dimensional (2D) disturbances. A robust Wald-type detector is integrated with a SARSA-based RL algorithm, enabling the radar to learn and adapt to complex clutter environments modeled by a 2D autoregressive process. Simulation results demonstrate significant improvements in detection probability compared to omnidirectional methods, particularly for low Signal-to-Noise Ratio (SNR) targets masked by clutter.

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arXiv2025

Single Antenna Terahertz Sensing using Preconfigured Metasurfaces

The development of mobile terahertz (THz) sensing and localization with minimal infrastructure has garnered significant attention due to its substantial practical implications. Single-antenna radar systems are a favored choice for mobile platforms, as they offer notable advantages in terms of cost, weight, and simplicity. However, these systems face a critical limitation: the inability to extract angular information using a single antenna, which consequently prevents the achievement of complete localization. This paper proposes an angular estimation method for a single-antenna radar augmented with a pair of preconfigured metasurfaces. The metasurface pair is used for creating an interference pattern in the scene, which depends on the target angles and operating frequency. Moreover, the beam squint effects caused by the wide frequency range in the THz band provides suitable conditions for using sparse reconstruction techniques to obtain angular estimates. We utilize these properties to perform angular estimation with a single antenna. The simulation results show that with this method it is possible to perform fast and accurate multi-target estimation for a broad operating range.

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arXiv2024

RIS-Aided Radar Imaging Utilizing the Virtual Source Principle

This paper investigates signle-antenna radar imaging with a reconfigurable intelligent surface (RIS). Configuring phase shifts in a RIS-aided radar system can be thought as synthetic aperture radar (SAR) imaging with a moving virtual source. With this perspective, the problem is modeled in the wavenumber domain and image forming algorithms are formulated for near and far field regions. Thus, a novel and intuitive perspective has been introduced to the RIS-aided radar imaging formation problem, opening a new avenue for adapting well-known SAR methods in the literature to these systems.

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arXiv2024

Spatial-Domain Wireless Jamming with Reconfigurable Intelligent Surfaces

Wireless communication infrastructure is a cornerstone of modern digital society, yet it remains vulnerable to the persistent threat of wireless jamming. Attackers can easily create radio interference to overshadow legitimate signals, leading to denial of service. The broadcast nature of radio signal propagation makes such attacks possible in the first place, but at the same time poses a challenge for the attacker: The jamming signal does not only reach the victim device but also other neighboring devices, preventing precise attack targeting. In this work, we solve this challenge by leveraging the emerging RIS technology, for the first time, for precise delivery of jamming signals. In particular, we propose a novel approach that allows for environment-adaptive spatial control of wireless jamming signals, granting a new degree of freedom to perform jamming attacks. We explore this novel method with extensive experimentation and demonstrate that our approach can disable the wireless communication of one or multiple victim devices while leaving neighboring devices unaffected. Notably, our method extends to challenging scenarios where wireless devices are very close to each other: We demonstrate complete denial-of-service of a Wi-Fi device while a second device located at a distance as close as 5 mm remains unaffected, sustaining wireless communication at a data rate of 25 Mbit/s. Lastly, we conclude by proposing potential countermeasures to thwart RIS-based spatial domain wireless jamming attacks.

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arXiv2024

Resilience and Criticality: Brothers in Arms for 6G

In this paper, we develop the first comprehensive tutorial on designing future 6G networks that synergistically integrate notions of resilience and criticality from the ground up. While resilience refers to the ability to absorb, adapt to, and recover from adversarial or challenging conditions, criticality indicates the degree of importance or urgency assigned to a particular service or component. Despite a spiking interest in designing resilient wireless networks, most prior works do not provide a unified resilience definition, nor harness the intricate interplay between resilience and criticality. In order to fill this gap, in this paper, we highlight the importance of a criticality-aware approach as a key enabler for providing reliable and resilient service functionality. Moreover, we delve into the unique challenges and opportunities of the envisioned 6G features pertaining to resilience and (mixed) criticality. After reviewing resilience definitions, we present a core resilience strategy, a unified resilience metric, different criteria for service criticality, and prioritization frameworks, that augment the 6G resilience prospects. Afterwards, we explore the opportunities presented by promising technologies that enable a resilient 6G network design from a radio access network protocol stack perspective. We briefly revisit state-of-the-art network architectures, establish a rough connection to the Open-RAN Alliance vision, and discuss opportunities, existing techniques, and promising enabling mechanisms for 6G at each layer. Finally, the article discusses important research directions and open problems concerning resilience and criticality in 6G.

cs.IT↗