arXiv subjects

Konstantinos Ntontin

Publications and source records attributed to Konstantinos Ntontin.

17 recordsLinked to original sources

arXiv2026

A Tight Channel-Capacity Lower Bound for the Simultaneous Wireless Information and Power Transfer Integrated Receiver

Contrary to the vast majority of works on simultaneous wireless information and power transfer that provide information-theoretic limits for the separate receiver architecture, in this work we focus on the integrated receiver and provide a channel-capacity lower bound. Towards this, we provide a closed-form tight approximation for the probability transition matrix of the channel by leveraging the 4th-order Taylor expansion of the current-voltage characteristic curve of a Schottky diode used for rectification. Numerical results reveal that the consideration of the gamma distribution as an input distribution leads to a tight channel-capacity lower bound, in contrast to other input distributions, such as the Rayleigh and uniform ones. Furthermore, the results reveal that the consideration of the 4th order term in the Taylor expansion leads to a notably higher capacity with respect to the overly simplified 2nd order term-based model.

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arXiv2026

Secure Task Offloading and Resource Allocation Design for Multi-Layer Non-Terrestrial Networks

Remote and resource-constrained Internet-of-Things (IoT) deployments often lack terrestrial connectivity for task offloading, motivating non-terrestrial networks (NTNs) with onboard multiaccess edge computing (MEC) capabilities. Nevertheless, in the presence of malicious actors, authentication needs to be performed to avoid non-authorized nodes from draining the computing resources of the NTN nodes. As a solution, we propose a four-layer MEC-enabled NTN with unmanned aerial vehicles (UAVs) acting as access nodes, a high altitude platform station (HAPS) acting as coordinator and authenticator, and a constellation of low-Earth orbit satellites (LEOSats) acting as remote MEC servers. We consider a tag-based physical-layer authentication (PLA) scheme to authenticate legitimate users, and formulate a joint task offloading decision and resource allocation for the admitted tasks, which is solved via block coordinate descent. Numerical results show that the PLA scheme is efficient and performs better than the benchmark schemes. We also demonstrate that the proposed scheme is robust against malicious attacks even under relaxed false-alarm constraints.

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arXiv2026

Hierarchical Edge-Cloud Task Offloading in NTN for Remote Healthcare

In this work, we study a hierarchical non-terrestrial network as an edge-cloud platform for remote computing of tasks generated by remote ad-hoc healthcare facility deployments, or internet of medical things (IoMT) devices. We consider a high altitude platform station (HAPS) to provide local multiaccess edge server (MEC) services to a set of remote ground medical devices, and a low-earth orbit (LEO) satellite, serving as a bridge to a remote cloud computing server through a ground gateway (GW), providing a large amount of computing resources to the HAPS. In this hierarchical system, the HAPS and the cloud server charges the ground users and the HAPS for the use of the spectrum and the computing of their tasks respectively. Each tier seeks to maximize their own utility in a selfish manner. To encourage the prompt computation of the tasks, a local delay cost is assumed. We formulate the optimal per-task cost at each tier that influences the corresponding offloading policies, and find the corresponding optimal bandwidth allocation.

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arXiv2025

QTCAJOSA: Low-Complexity Joint Offloading and Subchannel Allocation for NTN-Enabled IoMT

In this work, we consider the resource allocation problem for task offloading from Internet of Medical Things (IoMT) devices, to a non-terrestrial network. The architecture considers clusters of IoMT devices that offload their tasks to a dedicated unmanned aerial vehicle (UAV) serving as a multi-access edge computing (MEC) server, which can compute the task or further offload it to an available high-altitude platform station (HAPS) or to a low-earth orbit (LEO) satellite for remote computing. We formulate a problem that has as objective the minimization of the weighted sum delay of the tasks. Given the non-convex nature of the problem, and acknowledging that the complexity of the optimization algorithms impact their performance, we derive a low-complexity joint subchannel allocation and offloading decision algorithm with dynamic computing resource initialization, developed as a greedy heuristic based on convex optimization criteria. Simulations show the gain obtained by including the different non-terrestrial nodes against architectures without them.

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arXiv2025

Statistical CSI-Based Distributed Precoding Design for OFDM-Cooperative Multi-Satellite Systems

This paper investigates the design of distributed precoding for multi-satellite massive MIMO transmissions. We first conduct a detailed analysis of the transceiver model, in which delay and Doppler precompensation is introduced to ensure coherent transmission. In this analysis, we examine the impact of precompensation errors on the transmission model, emphasize the near-independence of inter-satellite interference, and ultimately derive the received signal model. Based on such signal model, we formulate an approximate expected rate maximization problem that considers both statistical channel state information (sCSI) and compensation errors. Unlike conventional approaches that recast such problems as weighted minimum mean square error (WMMSE) minimization, we demonstrate that this transformation fails to maintain equivalence in the considered scenario. To address this, we introduce an equivalent covariance decomposition-based WMMSE (CDWMMSE) formulation derived based on channel covariance matrix decomposition. Taking advantage of the channel characteristics, we develop a low-complexity decomposition method and propose an optimization algorithm. To further reduce computational complexity, we introduce a model-driven scalable deep learning (DL) approach that leverages the equivariance of the mapping from sCSI to the unknown variables in the optimal closed-form solution, enhancing performance through novel dense Transformer network and scaling-invariant loss function design. Simulation results validate the effectiveness and robustness of the proposed method in some practical scenarios. We also demonstrate that the DL approach can adapt to dynamic settings with varying numbers of users and satellites.

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arXiv2024

Beyond Diagonal RIS-Aided Networks: Performance Analysis and Sectorization Tradeoff

Reconfigurable intelligent surfaces (RISs) have emerged as a spectrum- and energy-efficient technology to enhance the coverage of wireless communications within the upcoming 6G networks. Recently, novel extensions of this technology, referred to as multi-sector beyond diagonal RIS (BD-RIS), have been proposed, where the configurable elements are divided into $L$ sectors $(L \geq 2)$ and arranged as a polygon prism, with each sector covering $1/L$ space. This paper presents a performance analysis of a multi-user communication system assisted by a multi-sector BD-RIS operating in time-switching (TS) mode. Specifically, we derive closed-form expressions for the moment-generating function (MGF), probability density function (PDF), and cumulative density function (CDF) of the signal-to-noise ratio (SNR) per user. Furthermore, closed-form expressions for the outage probability, achievable spectral and energy efficiency, symbol error probability, and diversity order for the proposed system model are derived. Moreover, a comparison is performed with the simultaneously transmitting and reflecting (STAR)-RISs, a special case of multi-sector BD-RIS with two sectors. Our analysis shows that for a fixed number of elements, increasing the sectors improves outage performance at the expense of reduced diversity order compared to STAR-RIS. This trade-off is influenced by the Rician factors of the cascaded channel and the number of configurable elements per sector. However, this superiority in slope is observed at outage probability values below $10^{-5}$, which remains below practical operating ranges of communication systems. Additionally, simulations are provided to validate the accuracy of our theoretical analyses showing a notable $182\%$ increase in spectral efficiency and a $238\%$ increase in energy efficiency when transitioning from a 2-sector to a 6-sector configuration.

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arXiv2023

Perpetual Reconfigurable Intelligent Surfaces Through In-Band Energy Harvesting: Architectures, Protocols, and Challenges

Reconfigurable intelligent surfaces (RISs) are considered to be a key enabler of highly energy-efficient 6G and beyond networks. This property arises from the absence of power amplifiers in the structure, in contrast to active nodes, such as small cells and relays. However, still an amount of power is required for their operation. To improve their energy efficiency further, we propose the notion of perpetual RISs, which secure the power needed to supply their functionalities through wireless energy harvesting of the impinging transmitted electromagnetic signals. Towards this, we initially explain the rationale behind such RIS capability and proceed with the presentation of the main RIS controller architecture that can realize this vision under an in-band energy harvesting consideration. Furthermore, we present a typical energy-harvesting architecture followed by two harvesting protocols. Subsequently, we study the performance of the two protocols under a typical communications scenario. Finally, we elaborate on the main research challenges governing the realization of large-scale networks with perpetual RISs.

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arXiv2023

Localization as a key enabler of 6G wireless systems: A comprehensive survey and an outlook

When fully implemented, sixth generation (6G) wireless systems will constitute intelligent wireless networks that enable not only ubiquitous communication but also high-accuracy localization services. They will be the driving force behind this transformation by introducing a new set of characteristics and service capabilities in which location will coexist with communication while sharing available resources. To that purpose, this survey investigates the envisioned applications and use cases of localization in future 6G wireless systems, while analyzing the impact of the major technology enablers. Afterwards, system models for millimeter wave, terahertz and visible light positioning that take into account both line-of-sight (LOS) and non-LOS channels are presented, while localization key performance indicators are revisited alongside mathematical definitions. Moreover, a detailed review of the state of the art conventional and learning-based localization techniques is conducted. Furthermore, the localization problem is formulated, the wireless system design is considered and the optimization of both is investigated. Finally, insights that arise from the presented analysis are summarized and used to highlight the most important future directions for localization in 6G wireless systems.

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arXiv2022

Cooperative Hybrid Networks with Active Relays and RISs for B5G: Applications, Challenges, and Research Directions

Among the recent advances and innovations in wireless technologies, reconfigurable intelligent surfaces (RISs) have received much attention and are envisioned to be one of the enabling technologies for beyond 5G (B5G) networks. On the other hand, active (or classical) cooperative relays have played a key role in providing reliable and power-efficient communications in previous wireless generations. In this article, we focus on hybrid network architectures that amalgamate both active relays and RISs. The operation concept and protocols of each technology are first discussed. Subsequently, we present multiple use cases of cooperative hybrid networks where both active relays and RISs can coexist harmoniously for enhanced rate performance. Furthermore, a case study is provided which demonstrates the achievable rate performance of a communication network assisted by either an active relay, an RIS, or both, and with different relaying protocols. Finally, we provide the reader with the challenges and key research directions in this area.

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arXiv2022

Joint Spatial Division and Multiplexing for FDD in Intelligent Reflecting Surface-assisted Massive MIMO Systems

Intelligent reflecting surface (IRS) is a promising technology to deliver the higher spectral and energy requirements in fifth-generation (5G) and beyond wireless networks while shaping the propagation environment. Such a design can be further enhanced with massive multiple-input-multiple-output (mMIMO) characteristics towards boosting the network performance. However, channel reciprocity, assumed in 5G systems such as mMIMO, appears to be questioned in practice by recent studies on IRS. Hence, contrary to previous works, we consider frequency division duplexing (FDD) to study the performance of an IRS-assisted mMIMO system. However, FDD is not suitable for large number of antennas architectures. For this reason we employ the joint spatial division and multiplexing (JSDM) approach exploiting the structure of the correlation of the channel vectors to reduce the channel state information (CSI) uplink feedback, and thus, allowing the use even of a large number of antennas at the base station. JSDM entails dual-structured precoding and clustering the user equipments (UEs) with the same covariance matrix into groups. Specifically, we derive the sum spectral efficiency (SE) based on statistical CSI in terms of large-scale statistics by using the deterministic equivalent (DE) analysis while accounting for correlated Rayleigh fading. Subsequently, we formulate the optimization problem concerning the sum SE with respect to the reflecting beamforming matrix (RBM) and the total transmit power, which can be performed at every several coherence intervals by taking advantage of the slow-time variation of the large-scale statistics. This notable property contributes further to the decrease of the feedback overhead.

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arXiv2021

Successive Decode-and-Forward Relaying with Reconfigurable Intelligent Surfaces

The key advantage of successive relaying (SR) networks is their ability to mimic the full-duplex (FD) operation with half-duplex (HD) relays. However, the main challenge that comes with such schemes is the associated inter-relay interference (IRI). In this work, we propose a reconfigurable intelligent surface (RIS)-enhanced SR network, where one RIS is deployed near each of the two relay nodes to provide spatial suppression of IRI, and to maximize the gain of desired signals. The resultant max-min optimization problem with joint phase-shift design for both RISs is first tackled via the semidefinite programming (SDP) approach. Then, a lower-complexity solution suitable for real-time implementation is proposed based on particle swarm optimization (PSO). Numerical results demonstrate that even relatively small RISs can provide significant gains in achievable rates of SR networks, and the proposed PSO scheme can achieve a near optimal performance.

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arXiv2021

Simultaneous Control Information and Power Transmission for Reconfigurable Intelligent Surfaces

Reconfigurable intelligent surfaces (RISs) are planar structures with attached electronic circuitry that enable a partially programmable communication environment. RIS operation can be regarded as nearly passive since it acts by simply reflecting the impinging traveling waves towards desired directions, thus requiring energy only for the reconfiguration of its reflective elements (REs). This paper tackles the problem of wirelessly powering RIS circuitry via control signaling. Simultaneous wireless information and power transfer (SWIPT) is considered by taking into account two basic principles: that signal quality of the control signals is sufficient for information detection, and that there is enough harvested energy for the reconfiguration. Some of the most common SWIPT receivers (time sharing, power splitting, dynamic power splitting, and antenna selection) are studied and the corresponding proposed optimization problems implementing the aforementioned principles are formulated and solved in closed form. Numerical results show the effectiveness of the proposed methods in the presence of received power fluctuations.

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arXiv2021

Toward Autonomous Reconfigurable Intelligent Surfaces Through Wireless Energy Harvesting

In this work, we examine the potential of autonomous operation of a reconfigurable intelligent surface (RIS) using wireless energy harvesting from information signals. To this end, we first identify the main RIS power-consuming components and introduce a suitable power-consumption model. Subsequently, we introduce a novel RIS power-splitting architecture that enables simultaneous energy harvesting and beamsteering. Specifically, a subset of the RIS unit cells (UCs) is used for beamsteering while the remaining ones absorb energy. For the subset allocation, we propose policies obtained as solutions to two optimization problems. The first problem aims at maximizing the signal-to-noise ratio (SNR) at the receiver without violating the RIS's energy harvesting demands. Additionally, the objective of the second problem is to maximize the RIS harvested power, while ensuring an acceptable SNR at the receiver. We prove that under particular propagation conditions, some of the proposed policies deliver the optimal solution of the two problems. Furthermore, we report numerical results that reveal the efficiency of the policies with respect to the optimal and very high-complexity brute-force design approach. Finally, through a case study of user tracking, we showcase that the RIS power-consumption demands can be secured by harvesting energy from information signals.

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arXiv2021

Double-RIS Communication with DF Relaying for Coverage Extension: Is One Relay Enough?

In this work, we investigate the decode-and-forward (DF) relay-aided double reconfigurable intelligent surface (RIS)-assisted networks, where the signal is subject to reflections from two RISs before reaching the destination. Different relay-aided network architectures are considered for maximum achievable rate under a total power constraint. Phase optimization for the double-RIS channels is tackled via the alternating optimization and majorization-minimization (MM) schemes. Moreover, closed-form solutions are obtained for each case. Numerical results indicate that the deployment of two relays, one near each RIS, achieves higher rates at low and medium signal-to noise ratios (SNRs) compared to placing a single relay between the two RISs; while at high SNRs, the latter approach achieves higher rates only if the inter-relay interference for the former case is considerably high.

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arXiv2021

Autonomous Reconfigurable Intelligent Surfaces Through Wireless Energy Harvesting

In this paper, we examine the potential for a reconfigurable intelligent surface (RIS) to be powered by energy harvested from information signals. This feature might be key to reap the benefits of RIS technology's lower power consumption compared to active relays. We first identify the main RIS power-consuming components and then propose an energy harvesting and power consumption model. Furthermore, we formulate and solve the problem of the optimal RIS placement together with the amplitude and phase response adjustment of its elements in order to maximize the signal-to-noise ratio (SNR) while harvesting sufficient energy for its operation. Finally, numerical results validate the autonomous operation potential and reveal the range of power consumption values that enables it.

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arXiv2021

Reconfigurable Intelligent Surface Optimal Placement in Millimeter-Wave Networks

This work discusses the optimal reconfigurable intelligent surface placement in highly-directional millimeter wave links. In particular, we present a novel system model that takes into account the relationship between the transmission beam footprint at the RIS plane and the RIS size. Subsequently, based on the model we derive the end-to-end expression of the received signal power and, furthermore, provide approximate closed-form expressions in the case that the RIS size is either much smaller or at least equal to the transmission beam footprint. Moreover, building upon the expressions, we derive the optimal RIS placement that maximizes the end-to-end signal-to-noise ratio. Finally, we substantiate the analytical findings by means of simulations, which reveal important trends regarding the optimal RIS placement according to the system parameters.

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arXiv2017

D2D-Aware Device Caching in MmWave-Cellular Networks

In this paper, we propose a novel policy for device caching that facilitates popular content exchange through high-rate device-to-device (D2D) millimeter-wave (mmWave) communication. The D2D-aware caching (DAC) policy splits the cacheable content into two content groups and distributes it randomly to the user equipment devices (UEs), with the goal to enable D2D connections. By exploiting the high bandwidth availability and the directionality of mmWaves, we ensure high rates for the D2D transmissions, while mitigating the co-channel interference that limits the throughput gains of D2D communication in the sub-6 GHz bands. Furthermore, based on a stochastic-geometry modeling of the network topology, we analytically derive the offloading gain that is achieved by the proposed policy and the distribution of the content retrieval delay considering both half- and full-duplex mode for the D2D communication. The accuracy of the proposed analytical framework is validated through Monte-Carlo simulations. In addition, for a wide range of a content popularity indicator the results show that the proposed policy achieves higher offloading and lower content-retrieval delays than existing state-of-the-art approaches.

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