arXiv subjects

Christos Liaskos

Publications and source records attributed to Christos Liaskos.

At least 19 recordsLinked to original sources

arXiv2026

Deep Reinforcement Learning Orchestration of Game-Theoretic User Association and Resource Allocation in HetNets

Managing dynamic User Association and Resource Allocation (UARA) in modern Heterogeneous Cellular Networks (HetNets) remains a critical open challenge. Existing mathematical optimization and Reinforcement Learning approaches face limitations in handling low-latency decision-making under dynamic traffic conditions. This paper introduces a novel orchestration scheme for game-theoretic UARA in HetNets. The proposed bilevel framework distributes UARA decisions to User Equipment through a multi-objective non-cooperative game. Overlaying the distributed game, a centralized Deep Reinforcement Learning controller orchestrates network performance by dynamically configuring the game's utility parameters, enabling transitions between power awareness, coverage enhancement, and balanced operation. Evaluated on urban HetNet topologies with 3GPP TR 38.901-compliant channel modeling, the proposed framework closely approximates the optimal policy for the considered operational objectives, while delivering higher network throughput than conventional association methods. Furthermore, it incurs low computational overhead and maintains stable performance across the evaluated traffic densities without retraining.

eess.SP↗

arXiv2026

Geometry-Informed Optimization of Binary RIS Configurations for Communication and Sensing

Practical Reconfigurable Intelligent Surfaces (RISs) often support only a small number of phase states, making their configuration inherently discrete. For a 1-bit RIS with $N$ elements, direct optimization requires searching among $2^N$ binary configurations. This work shows that this exponential configuration space is not unstructured. By reformulating 1-bit RIS optimization as the maximization of the norm of a signed sum of channel-dependent vectors, we prove that every globally optimal configuration must be induced by the signs of their projections onto a common direction. This geometric characterization restricts the class of configurations that can contain global optima and leads to different algorithmic consequences depending on the signal-space dimension. For general Multiple-Input-Multiple-Output (MIMO) systems, we develop a geometry-informed sampling method that evaluates only structurally admissible configurations. For Single-Input-Single-Output (SISO) systems, the same principle reduces to a two-dimensional angular partition, allowing the complete candidate set to be characterized and the global optimum to be recovered through polynomial-time enumeration, by evaluating at most $N+1$ out of the $2^N$ configurations. Finally, we apply the same binary optimization principle to an Integrated Sensing and Communication (ISAC) scenario, where communication enhancement and target localization reduce to the same underlying geometric problem. The proposed framework therefore provides a unified approach for exploiting the structure of practical 1-bit RIS configurations across communication and sensing functionalities.

cs.IT↗

arXiv2026

SCROOGE: A Physics-Aware Framework for Efficient Orchestration of RIS-Assisted Networks

Reconfigurable Intelligent Surfaces (RISs) are emerging as a key enabler of Programmable Wireless Environments for 6G, but their practical integration into operational networks still lacks orchestration mechanisms that can jointly support resource allocation, energy efficiency, and admission control with low online complexity. This paper presents SCROOGE, a physics-aware orchestration framework for multi-user RIS-assisted networks that operates on information generated offline during RIS codebook compilation, namely optimal codebook entries and per-element influence scores. Rather than relying on online optimization or idealized fading-based abstractions, SCROOGE exploits physics-derived descriptors to support low-latency operating-phase decisions that remain compatible with network-level control requirements. Specifically, SCROOGE introduces: i) an influence-aware, tier-consistent resource-allocation mechanism that combines user priority and element importance in the construction of a common RIS configuration; ii) an energy-efficiency mechanism that deactivates globally low-influence elements; and iii) an admission-control mechanism that accepts or rejects candidate users based on tier-aware compatibility with the currently deployed RIS state.

eess.SP↗

arXiv2026

RF-Fencing: A Novel RIS-Based Service for Proactive Covert Communications

Programmable wireless environments (PWEs), empowered by reconfigurable intelligent surfaces (RISes), have emerged as a transformative paradigm for next-generation networks, enabling deterministic control over electromagnetic (EM) propagation to enhance both performance and security. In this work, we introduce RF-Fencing, a novel RIS-enabled PWE service that enforces spatially selective control over wireless transmissions, simultaneously suppressing unwanted signal exposure while sustaining robust connectivity for legitimate users. To realize this vision, we develop SHIELD, a lightweight and scalable algorithm that orchestrates multiple RIS units by multiplexing precompiled codebook entries with real-time, low-complexity optimization. Through extensive evaluations across diverse frequencies, RIS configurations, and deployment scenarios, SHIELD demonstrates both far-field directional control and near-field quiet-zone creation, thereby enhancing network security. Our findings reveal that SHIELD effectively balances proactive covert communication with service delivery by dynamically managing multiple signal suppression and delivery areas, while enabling the realization of EM quiet zones with minimal impact on surrounding regions, ultimately establishing RF-Fencing as a practical RIS-based foundation for privacy-preserving and adaptive wireless environments in future 6G networks.

eess.SP↗

arXiv2026

Physics-Aware RIS Codebook Compilation for Near-Field Beam Focusing under Mutual Coupling and Specular Reflections

Next-generation wireless networks are envisioned to achieve reliable, low-latency connectivity within environments characterized by strong multipath and severe channel variability. Programmable wireless environments (PWEs) address this challenge by enabling deterministic control of electromagnetic (EM) propagation through software-defined reconfigurable intelligent surfaces (RISs). However, effectively configuring RISs in real time remains a major bottleneck, particularly under near-field conditions where mutual coupling and specular reflections alter the intended response. To overcome this limitation, this paper introduces MATCH, a physics-based codebook compilation algorithm that explicitly accounts for the EM coupling among RIS unit cells and the reflective interactions with surrounding structures, ensuring that the resulting codebooks remain consistent with the physical characteristics of the environment. Finally, MATCH is evaluated under a full-wave simulation framework incorporating mutual coupling and secondary reflections, demonstrating its ability to concentrate scattered energy within the focal region, confirming that physics-consistent, codebook-based optimization constitutes an effective approach for practical and efficient RIS configuration.

eess.SP↗

arXiv2026

A Tutorial on Controlling Metasurfaces from the Network Perspective

Metasurfaces have emerged as transformative electromagnetic structures for wireless communications, enabling the real-time control over wave propagation, yielding potential for improved data rates, privacy, energy efficiency and even precise environmental sensing. This tutorial offers a perspective on controlling metasurfaces by treating them as components of a larger networked system. Towards this end, we first review the physical principles of metasurfaces and their various applications, followed by an exploration of manufacturing approaches for creating these structures. Then, aligning with standard network layer concepts, we describe the modeling of metasurfaces as wave routers, enabling us to describe systems of metasurfaces using graph theory. This approach enables the development of a performance objective framework for optimizing these systems, while classes of heuristic and path-finding-driven algorithms are discussed as practical solvers. The paper also examines the integration of metasurfaces with communication systems, by presenting their overall workflow, discussing its relation to ongoing standardization efforts, as well as defining a context for their integration to network simulators, using Omnet++ as a driving example. Finally, the paper explores future directions for research in this field, identifying graph-theoretic, standardization and integration challenges, relating to several networking disciplines including AI-driven applications.

cs.NI↗

arXiv2025

Ergodic Rate Analysis of Two-State Pinching-Antenna Systems

Flexible Antenna Systems (FAS) are a key enabler of next-generation wireless networks, allowing the antenna aperture to be dynamically reconfigured to adapt to channel conditions and service requirements. In this context, pinching-antenna systems (PASs) implemented on software-controllable dielectric waveguides provide the ability to reconfigure both channel characteristics and path loss by selectively exciting discrete radiation points. Existing works, however, typically assume continuously adjustable pinching positions, neglecting the spatial discreteness imposed by practical implementations. This paper develops a closed-form analytical framework for the ergodic rate of two-state PASs, where pinching antennas are fixed and only their activation states are controlled. To quantify the impact of spatial discretization, pinching discretization efficiency is introduced, characterizing the performance gap relative to the ideal continuous case. Finally, numerical results show that near-continuous performance can be achieved with a limited number of pinching points, providing design insights for scalable PASs.

cs.IT↗

arXiv2024

Realizing RF Wavefront Copying with RIS for Future Extended Reality Applications

Lately a new approach to Extended Reality (XR), denoted as XR-RF, has been proposed which is realized by combining Radio Frequency (RF) Imaging and programmable wireless environments (PWEs). RF Imaging is a technique that aims to detect geometric and material features of an object through RF waves. On the other hand, the PWE focuses on the the conversion of the wireless RF propagation in a controllable, by software, entity through the utilization of Reconfigurable Intelligent Surfaces (RISs), which can have a controllable interaction with impinging RF waves. In that sense, this dynamic synergy leverages the potential of RF Imaging to detect the structure of an object through RF wavefronts and the PWE's ability to selectively replicate those RF wavefronts from one spatial location to wherever an XR-RF mobile user is presently located. Then the captured wavefront, through appropriate hardware, is mapped to the visual representation of the object through machine learning models. As a key aspect of the XR-RF's system workflow is the wavefront copying mechanism, this work introduces a new PWE configuration algorithm for XR-RF. Moreover, it is shown that the waveform replication process inevitably yields imprecision in the replication process. After statistical analysis, based on simulation results, it is shown that this imprecision can be effectively modeled by the gamma distribution.

cs.ET↗

arXiv2024

On the Performance of RIS-assisted Networks with HQAM

In this paper, we investigate the application of hexagonal quadrature amplitude modulation (HQAM) in reconfigurable intelligent surface (RIS)-assisted networks, specifically focusing on its efficiency in reducing the number of required reflecting elements. Specifically, we present analytical expressions for the average symbol error probability (ASEP) and propose a new metric for conditioned energy efficiency, which assesses the network energy consumption while ensuring the ASEP remains below a certain threshold. Additionally, we introduce an innovative detection algorithm for HQAM constellations that implements sphere decoding in O(1) complexity. Finally, our study reveals that HQAM significantly enhances both the ASEP and energy efficiency compared to traditional quadrature amplitude modulation (QAM) schemes.

cs.IT↗

arXiv2022

Dynamic Programmable Wireless Environment with UAV-mounted Static Metasurfaces

Reconfigurable intelligent surfaces (RISs) are artificial planar structures able to offer a unique way of manipulating propagated wireless signals. Commonly composed of a number of reconfigurable passive cell components and basic electronic circuits, RISs can almost freely perform a set of wave modification functionalities, in order to realize programmable wireless environments (PWEs). However, a more energy-efficient way to realize a PWE is through dynamically relocating static metasurfaces that perform a unique functionality. In this paper, we employ a UAV swarm to dynamically deploy a set of lowcost passive metasurfaces that are able to perform only one electromagnetic functionality, but with the benefit of requiring no power. Specifically, the UAV-mounted static metasurfaces are carefully positioned across the sky to create cascaded channels for improved user service and security hardening. The performance evaluation results, based on

cs.ET↗

arXiv2022

An Open Platform for Simulating the Physical Layer of 6G Communication Systems with Multiple Intelligent Surfaces

Reconfigurable Intelligent Surfaces (RIS) constitute a promising technology that could fulfill the extreme performance and capacity needs of the upcoming 6G wireless networks, by offering software-defined control over wireless propagation phenomena. Despite the existence of many theoretical models describing various aspects of RIS from the signal processing perspective (e.g., channel fading models), there is no open platform to simulate and study their actual physical-layer behavior, especially in the multi-RIS case. In this paper, we develop an open simulation platform, aimed at modeling the physical-layer electromagnetic coupling and propagation between RIS pairs. We present the platform by initially designing a basic unit cell, and then proceeding to progressively model and simulate multiple and larger RISs. The platform can be used for producing verifiable stochastic models for wireless communication in multi-RIS deployments, such as vehicle-to-everything (V2X) communications in autonomous vehicles and cybersecurity schemes, while its code is freely available to the public.

cs.ET↗

arXiv2020

Workload Characterization of Programmable Metasurfaces

Metasurfaces are envisaged to play a key role in next-generation wireless systems due to their powerful control over electromagnetic waves. The last decade has witnessed huge advances in this regard, shifting from static to programmable metasurfaces. The HyperSurface (HSF) paradigm takes one step further by integrating a network of controllers within the device with the aim of adding intelligence, connectivity, and autonomy. However, little is known about the traffic that this network will have to support as the target electromagnetic function or boundary conditions change. In this paper, we lay down the foundations of a methodology to characterize the workload of programmable metasurfaces and then employ it to analyze the case of beam steering HSFs. We observe that traffic is bursty and highly dependent on the position of the target. These results will enable the early-stage evaluation of intra-HSF networks, as well as the estimation of the system performance and cost.

cs.NI↗

arXiv2020

Toward Fault-Tolerant Deadlock-Free Routing in HyperSurface-Embedded Controller Networks

HyperSurfaces (HSFs) consist of structurally reconfigurable metasurfaces whose electromagnetic properties can be changed via a software interface, using an embedded miniaturized network of controllers. With the HSF controllers, interconnected in an irregular, near-Manhattan geometry, we propose a robust, deterministic Fault-Tolerant (FT), deadlock- and livelock-free routing protocol where faults are contained in a set of disjointed rectangular regions called faulty blocks. The proposed FT protocol can support an unbounded number of faulty nodes as long as nodes outside the faulty blocks are connected. Simulation results show the efficacy of the proposed FT protocol under various faulty node distribution scenarios.

cs.NI↗

arXiv2020

Nanoantennas Design for THz Communication: Material Selection and Performance Enhancement

In the development of terahertz (THz) communication systems, the nanoantenna is the most significant component. Especially, the focus is to design highly directive antennas, because it enhances the performance of the overall system by compensating the large path loss at THz and thus improves the signal-to-noise ratio. This paper presents suitable material for nanoantenna design and the advancement in their performance for THz communications. Copper, Graphene, and carbon nanotube materials are used as promising candidates for nanoantenna design. The performance of nanoantennas is carried out by analyzing the properties and behavior of the material at THz. Results show that the Graphene nanoantenna provides better performance in terms of miniaturization, directivity, and radiation efficiency. Further, the performance enhancement of the nanoantenna at THz is studied by dynamically adjusting the surface conductivity via the chemical potential of Graphene using the electric field effect. The performance of the nanoantenna is enhanced in terms of high miniaturization, high directivity, low reflection, frequency reconfiguration, and stable impedance. The THz nanoantennas using Graphene have the potential to be used for THz communication systems. In view of the smart THz wireless environment; this paper finally presents a THz Hypersurface using Graphene meta-atoms. The user-side Graphene nanoantennas and environment-side Graphene Hypersurface can build a promising smart THz wireless environment.

eess.SP↗

arXiv2020

End-to-end Wireless Path Deployment with Intelligent Surfaces Using Interpretable Neural Networks

Intelligent surfaces exert deterministic control over the wireless propagation phenomenon, enabling novel capabilities in performance, security and wireless power transfer. Such surfaces come in the form of rectangular tiles that cascade to cover large surfaces such as walls, ceilings or building facades. Each tile is addressable and can receive software commands from a controller, manipulating an impinging electromagnetic wave upon it by customizing its reflection direction, focus, polarization and phase. A new problem arises concerning the orchestration of a set of tiles towards serving end-to-end communication objectives. Towards that end, we propose a novel intelligent surface networking algorithm based on interpretable neural networks. Tiles are mapped to neural network nodes and any tile line-of-sight connectivity is expressed as a neural network link. Tile wave manipulation functionalities are captured via geometric reflection with virtually rotatable tile surface norm, thus being able to tunable distribute power impinging upon a tile over the corresponding neural network links, with the corresponding power parts acting as the link weights. A feedforward/backpropagate process optimizes these weights to match ideal propagation outcomes (normalized network power outputs) to wireless user emissions (normalized network power inputs). An interpretation process translates these weights to the corresponding tile wave manipulation functionalities.

eess.SP↗

arXiv2020

A multi-functional reconfigurable metasurface: Electromagnetic design accounting for fabrication aspects

In this paper we present the theoretical considerations and the design evolution of a proof-of-concept reconfigurable metasurface, primarily used as a tunable microwave absorber, but also as a wavefront manipulation and polarization conversion device in reflection. We outline the design evolution and all considerations taken into account, from the selection of patch shape, unit cell size, and substrate, to the topology of the structure that realizes the desired tunability. The presented design conforms to fabrication restrictions and is co-designed to work with an integrated circuit chip for providing tunable complex loads to the metasurface, using a commercially available semiconductor process. The proposed structure can perform multiple tunable functionalities by appropriately biasing the integrated circuit: Perfect absorption for a wide range of incidence angles of both linear polarization states, accommodating a spectral range in the vicinity of 5 GHz, with potential also for wavefront control, exemplified via anomalous reflection and polarization conversion. The end vision is for such a design to be scalable and deployable as a practical HyperSurface, i.e., an intelligent multi-functional metasurface capable of concurrent reconfigurable functionalities: absorption, beam steering, polarization conversion, wavefront shaping, holography, and sensing.

physics.app-ph↗

arXiv2020

Radiation pattern prediction for Metasurfaces: A Neural Network based approach

As the current standardization for the 5G networks nears completion, work towards understanding the potential technologies for the 6G wireless networks is already underway. One of these potential technologies for the 6G networks are Reconfigurable Intelligent Surfaces (RISs). They offer unprecedented degrees of freedom towards engineering the wireless channel, i.e., the ability to modify the characteristics of the channel whenever and however required. Nevertheless, such properties demand that the response of the associated metasurface (MSF) is well understood under all possible operational conditions. While an understanding of the radiation pattern characteristics can be obtained through either analytical models or full wave simulations, they suffer from inaccuracy under certain conditions and extremely high computational complexity, respectively. Hence, in this paper we propose a novel neural networks based approach that enables a fast and accurate characterization of the MSF response. We analyze multiple scenarios and demonstrate the capabilities and utility of the proposed methodology. Concretely, we show that this method is able to learn and predict the parameters governing the reflected wave radiation pattern with an accuracy of a full wave simulation (98.8%-99.8%) and the time and computational complexity of an analytical model. The aforementioned result and methodology will be of specific importance for the design, fault tolerance and maintenance of the thousands of RISs that will be deployed in the 6G network environment.

eess.SP↗

arXiv2020

Graphene Hypersurface for Manipulation of THz Waves

In this work, we investigated graphene hypersurface (HSF) for the manipulation of THz waves. The graphene HSF structure is consists of a periodic array of graphene unit cells deposited on silicon substrate and terminated by a metallic ground plane. The performance of the proposed HSF is numerically analyzed. Electromagnetic parameters of HSF such as permeability, permittivity, and impedance are studied. The proposed graphene HSF has active control over absorption, reflection, and transmission of THz waves. The graphene HSF provides perfect absorption, zero reflection and zero transmission at resonance. Moreover, the graphene HSF structure has the advantage of anomalous reflection and frequency reconfiguration. Incident waves can be reflected in the desired direction, depending on the phase gradient of the HSF and the perfect absorption is maintained at all reconfigurable frequencies upon reconfiguration. The results reveal the effectiveness of the graphene HSF for the manipulation of THz waves.

eess.SP↗