arXiv subjects

Symeon Chatzinotas

Publications and source records attributed to Symeon Chatzinotas.

At least 199 records · Page 11Linked to original sources

arXiv2024

Joint Computation Offloading and Target Tracking in Integrated Sensing and Communication Enabled UAV Networks

In this paper, we investigate a joint computation offloading and target tracking in Integrated Sensing and Communication (ISAC)-enabled unmanned aerial vehicle (UAV) network. Therein, the UAV has a computing task that is partially offloaded to the ground UE for execution. Meanwhile, the UAV uses the offloading bit sequence to estimate the velocity of a ground target based on an autocorrelation function. The performance of the velocity estimation that is represented by Cramer-Rao lower bound (CRB) depends on the length of the offloading bit sequence and the UAV's location. Thus, we jointly optimize the task size for offloading and the UAV's location to minimize the overall computation latency and the CRB of the mean square error for velocity estimation subject to the UAV's budget. The problem is non-convex, and we propose a genetic algorithm to solve it. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm.

cs.IT↗

arXiv2024

Joint Computation and Communication Resource Optimization for Beyond Diagonal UAV-IRS Empowered MEC Networks

Recent advancements in 6G systems signal a leap towards universal connectivity and ultra-reliable, low-latency communications for real-time data devices. Yet, these advancements encounter obstacles such as limited device battery life and computational power, along with urban signal blockages. To counter these, Intelligent Reconfigurable Surfaces (IRS) within Mobile Edge Cloud (MEC) infrastructures offer enhanced computing to overcome device limitations and create alternative communication paths. Despite these improvements, connectivity issues remain for remote areas. Our paper presents the Beyond Diagonal IRS (BD-IRS or IRS 2.0), integrated with UAVs in MEC networks (BD-IRS-UAV), providing on-demand links for remote users to offload tasks, tackling resource and battery limitations. We propose a joint optimization strategy to reduce system's worst-case latency and UAV hovering time by optimizing BD-IRS-UAV deployment and resource allocation. This challenge is approached by dividing it into two sub-problems: BD-IRS-UAV Placement and Computational Resource Optimization, and Communication Resource Optimization, each solved iteratively. This design significantly enhances system performance, showing a $17.75\%$ increase over traditional diagonal IRS and a $25.43\%$ improvement over IRS on buildings, with a $13.44\%$ enhancement in worst-case latency compared to binary offloading schemes.

eess.SP↗

arXiv2024

Energy-Efficient Precoding and Feeder-Link-Beam Matching Design for Bent-Pipe SATCOM Systems

This paper proposes a joint optimization framework for energy-efficient linear precoding and feeder-link-beam matching design in a multi-gateway multi-beam bent-pipe satellite communication system. The proposed scheme jointly optimizes the precoding vectors at the gateway antennas and amplifying-and-matching mechanism at the satellite to maximize the system-weighted energy efficiency under the transmit power budget constraint. The technical designs are formulated into a non-convex sparsity problem consisting of a fractional-form objective function and sparsity-related constraints. To address these challenges, two iterative efficient designs are proposed by utilizing the concepts of Dinkelbach's method and the compressed-sensing approach. The simulation results demonstrate the effectiveness of the proposed scheme compared to another benchmark method.

eess.SP↗

arXiv2024

User-Centric Beam Selection and Precoding Design for Coordinated Multiple-Satellite Systems

This paper introduces a joint optimization framework for user-centric beam selection and linear precoding (LP) design in a coordinated multiple-satellite (CoMSat) system, employing a Digital-Fourier-Transform-based (DFT) beamforming (BF) technique. Regarding serving users at their target SINRs and minimizing the total transmit power, the scheme aims to efficiently determine satellites for users to associate with and activate the best cluster of beams together with optimizing LP for every satellite-to-user transmission. These technical objectives are first framed as a complex mixed-integer programming (MIP) challenge. To tackle this, we reformulate it into a joint cluster association and LP design problem. Then, by theoretically analyzing the duality relationship between downlink and uplink transmissions, we develop an efficient iterative method to identify the optimal solution. Additionally, a simpler duality approach for rapid beam selection and LP design is presented for comparison purposes. Simulation results underscore the effectiveness of our proposed schemes across various settings.

eess.SP↗

arXiv2024

Connecting Space Missions Through NGSO Constellations: Feasibility Study

A satellite internet provider (e.g., Starlink, OneWeb, O3b mPOWER), despite possessing the capability to provide internet services to on-ground users in a global scale, can dramatically change the way space missions are designed and operated in the foreseeable future. Assuming a scenario where space mission satellites can access the internet via a space internet system, the satellite can be connected to the network permanently (24x7) and act as mere terminal independently from its location. The ability to communicate with the satellite on-demand has the potential to improve aspects such as real-time tasking, outage minimization, operation cost, and dependency on the ground. This paper performs a feasibility study on the concept of connecting space missions to the network through commercial mega-constellations. This study includes a review of existing and near-future space internet systems, identification of candidate space missions for the aforementioned concept, a necessary adaptation of existing Commercial off-the-shelf (COTS) terminals to be plugged into space mission satellites, assessment of communication performance, and investigation of the legal aspects of the radio frequency (RF) spectrum usage. The paper evidences that the concept is practically possible to implement in the near future. Among the studied space internet systems (i.e. Starlink, OneWeb, O3b mPOWER), O3b mPOWER stands out as the most suitable system allowing permanent coverage of low earth orbit (LEO) space missions with data rates that can reach up to 21 Mbps per satellite. Although the concept is very promising and can be implemented in the near future, our investigations show that some regulatory aspects regarding the RF usage should be solved for future exploitation of connecting space missions through NGSO constellations.

eess.SY↗

arXiv2024

Two-Timescale Design for Active STAR-RIS Aided Massive MIMO Systems

Simultaneously transmitting and reflecting \textcolor{black}{reconfigurable intelligent surface} (STAR-RIS) is a promising implementation of RIS-assisted systems that enables full-space coverage. However, STAR-RIS as well as conventional RIS suffer from the double-fading effect. Thus, in this paper, we propose the marriage of active RIS and STAR-RIS, denoted as ASTARS for massive multiple-input multiple-output (mMIMO) systems, and we focus on the energy splitting (ES) and mode switching (MS) protocols. Compared to prior literature, we consider the impact of correlated fading, and we rely our analysis on the two timescale protocol, being dependent on statistical channel state information (CSI). On this ground, we propose a channel estimation method for ASTARS with reduced overhead that accounts for its architecture. Next, we derive a \textcolor{black}{closed-form expression} for the achievable sum-rate for both types of users in the transmission and reflection regions in a unified approach with significant practical advantages such as reduced complexity and overhead, which result in a lower number of required iterations for convergence compared to an alternating optimization (AO) approach. Notably, we maximize simultaneously the amplitudes, the phase shifts, and the active amplifying coefficients of the ASTARS by applying the projected gradient ascent method (PGAM). Remarkably, the proposed optimization can be executed at every several coherence intervals that reduces the processing burden considerably. Simulations corroborate the analytical results, provide insight into the effects of fundamental variables on the sum achievable SE, and present the superiority of 16 ASTARS compared to passive STAR-RIS for a practical number of surface elements.

cs.IT↗

arXiv2024

Performance Evaluation of Neuromorphic Hardware for Onboard Satellite Communication Applications

Spiking neural networks (SNNs) implemented on neuromorphic processors (NPs) can enhance the energy efficiency of deployments of artificial intelligence (AI) for specific workloads. As such, NP represents an interesting opportunity for implementing AI tasks on board power-limited satellite communication spacecraft. In this article, we disseminate the findings of a recently completed study which targeted the comparison in terms of performance and power-consumption of different satellite communication use cases implemented on standard AI accelerators and on NPs. In particular, the article describes three prominent use cases, namely payload resource optimization, onboard interference detection and classification, and dynamic receive beamforming; and compare the performance of conventional convolutional neural networks (CNNs) implemented on Xilinx's VCK5000 Versal development card and SNNs on Intel's neuromorphic chip Loihi 2.

eess.SP↗

arXiv2024

Joint Power Allocation and User Scheduling in Integrated Satellite-Terrestrial Cell-Free Massive MIMO IoT Systems

Both space and ground communications have been proven effective solutions under different perspectives in Internet of Things (IoT) networks. This paper investigates multiple-access scenarios, where plenty of IoT users are cooperatively served by a satellite in space and access points (APs) on the ground. Available users in each coherence interval are split into scheduled and unscheduled subsets to optimize limited radio resources. We compute the uplink ergodic throughput of each scheduled user under imperfect channel state information (CSI) and non-orthogonal pilot signals. As maximum-radio combining is deployed locally at the ground gateway and the APs, the uplink ergodic throughput is obtained in a closed-form expression. The analytical results explicitly unveil the effects of channel conditions and pilot contamination on each scheduled user. By maximizing the sum throughput, the system can simultaneously determine scheduled users and perform power allocation based on either a model-based approach with alternating optimization or a learning-based approach with the graph neural network. Numerical results manifest that integrated satellite-terrestrial cell-free massive multiple-input multiple-output systems can significantly improve the sum ergodic throughput over coherence intervals. The integrated systems can schedule the vast majority of users; some might be out of service due to the limited power budget.

cs.IT↗

arXiv2023

Characterizing and Utilizing the Interplay between Quantum Technologies and Non-Terrestrial Networks

Quantum technologies are increasingly recognized as groundbreaking advancements set to redefine the landscape of computing, communications, and sensing by leveraging quantum phenomena, like entanglement and teleportation. Quantum technologies offer an interesting set of advantages such as unconditional security, large communications capacity, unparalleled computational speed, and ultra-precise sensing capabilities. However, their global deployment faces challenges related to communication ranges and geographical boundaries. Non-terrestrial networks (NTNs) have emerged as a potential remedy for these challenges through providing free-space quantum links to circumvent the exponential losses inherent in fiber optics. This paper delves into the dynamic interplay between quantum technologies and NTNs to unveil their synergistic potential. Specifically, we investigate their integration challenges and the potential solutions to foster a symbiotic convergence of quantum and NTN functionalities while identifying avenues for enhanced interoperability. This paper not only offers useful insights into the mutual advantages but also presents future research directions, aiming to inspire additional studies and advance this interdisciplinary collaboration.

eess.SY↗

arXiv2023

Integrated Access and Backhaul via LEO Satellites with Inter-Satellite Links

The third generation partnership project (3GPP) has recently defined two frequency bands for direct access with satellites, which is a concrete step toward realizing the anticipated space-air-ground integrated networks. In addition, given the rapid increase in the numbers of satellites orbiting the Earth and emerging satellites applications, non-terrestrial networks (NTNs) might soon need to operate with integrated access and backhaul (IAB), which has been standardized for terrestrial networks to enable low-cost, flexible and scalable network densification. Therefore, this work investigates the performance of satellite IAB, where the same spectrum resources at a low earth orbit (LEO) satellite are utilized to provide access to a handheld user (UE) and backhaul via inter-satellite links. The UE is assumed to operate with frequency division duplex (FDD) as specified by the 3GPP, while both FDD and time division duplex (TDD) are investigated for backhauling. Our analysis demonstrate that the interference between access and backhaul links can significantly affect the performance under TDD backhauling, especially when the access link comes with a high quality-of-service demands.

cs.IT↗

arXiv2023

User-centric Flexible Resource Management Framework for LEO Satellites with Fully Regenerative Payload

The regenerative capabilities of next-generation satellite systems offer a novel approach to design low earth orbit (LEO) satellite communication systems, enabling full flexibility in bandwidth and spot beam management, power control, and onboard data processing. These advancements allow the implementation of intelligent spatial multiplexing techniques, addressing the ever-increasing demand for future broadband data traffic. Existing satellite resource management solutions, however, do not fully exploit these capabilities. To address this issue, a novel framework called flexible resource management algorithm for LEO satellites (FLARE-LEO) is proposed to jointly design bandwidth, power, and spot beam coverage optimized for the geographic distribution of users. It incorporates multi-spot beam multicasting, spatial multiplexing, caching, and handover (HO). In particular, the spot beam coverage is optimized by using the unsupervised K-means algorithm applied to the realistic geographical user demands, followed by a proposed successive convex approximation (SCA)-based iterative algorithm for optimizing the radio resources. Furthermore, we propose two joint transmission architectures during the HO period, which jointly estimate the downlink channel state information (CSI) using deep learning and optimize the transmit power of the LEOs involved in the HO process to improve the overall system throughput. Simulations demonstrate superior performance in terms of delivery time reduction of the proposed algorithm over the existing solutions.

cs.IT↗

arXiv2023

STAR-RIS Assisted Cell-Free Massive MIMO System Under Spatially-Correlated Channels

This paper investigates the performance of downlink simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, where user equipments (UEs) are located on both sides of the RIS. We account for correlated Rayleigh fading and multiple antennas per access point (AP), while the maximum ratio (MR) beamforming is applied for the design of the active beamforming in terms of instantaneous channel state information (CSI). Firstly, we rely on an aggregated channel estimation approach that reduces the overhead required for channel estimation while providing sufficient information for data processing. We obtain the normalized mean square error (NMSE) of the channel estimate per AP, and design the passive beamforming (PB) of the surface based on the long-time statistical CSI. Next, we derive the received signal in the asymptotic regime of numbers of APs and surface elements. Then, we obtain a closed-form expression of the downlink achievable rate for arbitrary numbers of APs and STAR-RIS elements under statistical CSI. Finally, based on the derived expressions, the numerical results show the feasibility and the advantages of deploying a STAR-RIS into conventional CF mMIMO systems. In particular, we theoretically analyze the properties of STAR-RIS-assisted CF mMIMO systems and reveal explicit insights in terms of the impact of channel correlation, the number of surface elements, and the pilot contamination on the achievable rate.

cs.IT↗

arXiv2023

Max-Min SINR Analysis of STAR-RIS Assisted Massive MIMO Systems with Hardware Impairments

Reconfigurable intelligent surface (RIS) has emerged as a cost-effective solution to improve wireless communication performance through just passive reflection. Recently, the concept of simultaneously transmitting and reflecting RIS (STAR-RIS) has appeared but the study of minimum signal-to-interference-plus-noise ratio (SINR) and the impact of hardware impairments (HWIs) remain open. In addition to previous works on STAR-RIS, we consider a massive multiple-input multiple-output (mMIMO) base station (BS) serving multiple user equipments (UEs) at both sides of the RIS. Specifically, in this work, focusing on the downlink of a single cell, we derive the minimum SINR obtained by the optimal linear precoder (OLP) with HWIs in closed form. The OLP maximises the minimum SINR subject to a given power constraint for any given passive beamforming matrix (PBM). Next, we obtain deterministic equivalents (DEs) for the OLP and the minimum SINR, which are then used to optimise the PBM. Notably, based on the DEs and statistical channel state information (CSI), we optimise simultaneously the amplitude and phase shift by using a projected gradient ascent algorithm (PGAM) for both energy splitting (ES) and mode switching (MS) STAR-RIS operation protocols with reduced feedback, \textcolor{black}{which is quite crucial for STAR-RIS systems that include the double number or variables compared to reflecting only RIS.} Simulations verify the analytical results, shed light on the impact of HWIs, and demonstrate the better performance of STAR-RIS compared to conventional RIS.

cs.IT↗

arXiv2023

Cooperative RIS and STAR-RIS assisted mMIMO Communication: Analysis and Optimization

Reconfigurable intelligent surface (RIS) has emerged as a cost-effective and promising solution to extend the wireless signal coverage and improve the performance via passive signal reflection. Different from existing works which do not account for the cooperation between RISs or do not provide full space coverage, we propose the marriage of cooperative double-RIS with simultaneously transmitting and reflecting RIS (STAR-RIS) technologies denoted as RIS/STAR-RIS under correlated Rayleigh fading conditions to assist the communication in a massive multiple-input multiple-output (mMIMO) setup. The proposed architecture is superior since it enjoys the benefits of the individual designs. We introduce a channel estimation approach of the cascaded channels with reduced overhead. Also, we obtain the deterministic equivalent (DE) of the downlink achievable sum spectral efficiency (SE) in closed form based on large-scale statistics. Notably, relied on statistical channel state information (CSI), we optimise both surfaces by means of the projected gradient ascent method (PGAM), and obtain the gradients in closed form. The proposed optimization achieves to maximise the sum SE of such a complex system, and has low complexity and low overhead since it can be performed at every several coherence intervals. Numerical results show the benefit of the proposed architecture and verify the analytical framework. In particular, we show that the RIS/STAR-RIS architecture outperforms the conventional double-RIS or its single-RIS counterparts.

cs.IT↗

arXiv2023

Satellite Swarms for Narrow Beamwidth Applications

Satellite swarms have recently gained attention in the space industry due to their ability to provide extremely narrow beamwidths at a lower cost than single satellite systems. This paper proposes a concept for a satellite swarm using a distributed subarray configuration based on a 2D normal probability distribution. The swarm comprises multiple small satellites acting as subarrays of a big aperture array limited by a radius of 20000 wavelengths working at a central frequency of 19 GHz. The main advantage of this approach is that the distributed subarrays can provide extremely directive beams and beamforming capabilities that are not possible using a conventional antenna and satellite design. The proposed swarm concept is analyzed, and the simulation results show that the radiation pattern achieves a beamwidth as narrow as 0.0015-degrees with a maximum side lobe level of 18.8 dB and a grating lobe level of 14.8 dB. This concept can be used for high data rates applications or emergency systems.

eess.SP↗

arXiv2023

On Deep Reinforcement Learning for Traffic Steering Intelligent ORAN

This paper aims to develop the intelligent traffic steering (TS) framework, which has recently been considered as one of the key developments of 3GPP for advanced 5G. Since achieving key performance indicators (KPIs) for heterogeneous services may not be possible in the monolithic architecture, a novel deep reinforcement learning (DRL)-based TS algorithm is proposed at the non-real-time (non-RT) RAN intelligent controller (RIC) within the open radio access network (ORAN) architecture. To enable ORAN's intelligence, we distribute traffic load onto appropriate paths, which helps efficiently allocate resources to end users in a downlink multi-service scenario. Our proposed approach employs a three-step hierarchical process that involves heuristics, machine learning, and convex optimization to steer traffic flows. Through system-level simulations, we show the superior performance of the proposed intelligent TS scheme, surpassing established benchmark systems by 45.50%.

cs.NI↗

arXiv2023

Supervised Learning Based Real-Time Adaptive Beamforming On-board Multibeam Satellites

Satellite communications (SatCom) are crucial for global connectivity, especially in the era of emerging technologies like 6G and narrowing the digital divide. Traditional SatCom systems struggle with efficient resource management due to static multibeam configurations, hindering quality of service (QoS) amidst dynamic traffic demands. This paper introduces an innovative solution - real-time adaptive beamforming on multibeam satellites with software-defined payloads in geostationary orbit (GEO). Utilizing a Direct Radiating Array (DRA) with circular polarization in the 17.7 - 20.2 GHz band, the paper outlines DRA design and a supervised learning-based algorithm for on-board beamforming. This adaptive approach not only meets precise beam projection needs but also dynamically adjusts beamwidth, minimizes sidelobe levels (SLL), and optimizes effective isotropic radiated power (EIRP).

eess.SP↗

arXiv2023

Genetic Algorithm-based Beamforming in Subarray Architectures for GEO Satellites

The incorporation of subarrays in Direct Radiating Arrays for satellite missions is fundamental in reducing the number of Radio Frequency chains, which correspondingly diminishes cost, power consumption, space, and mass. Despite the advantages, previous beamforming schemes incur significant losses during beam scanning, particularly when hybrid beamforming is not employed. Consequently, this paper introduces an algorithm capable of compensating for these losses by increasing the power, for this, the algorithm will activate radiating elements required to address a specific Effective Isotropic Radiated Power for a beam pattern over Earth, projected from a GeoStationary satellite. In addition to the aforementioned compensation, other beam parameters have been addressed in the algorithm, such as beamwidth and Side Lobe Levels. To achieve these objectives, we propose employing the array thinning concept through the use of genetic algorithms, which enable beam shaping with the desired characteristics and power. The full array design considers an open-ended waveguide, configured to operate in circular polarization within the Ka-band frequency range of 17.7-20.2 GHz.

eess.SY↗