Shannon Wireless’ Post

This study proposes a #minimum-#energy #operational planning problem for multiple #unmanned #aerial #vehicles (#UAVs) conducting a #cooperative #multihop #data-#gathering #mission. A multi-UAV ad hoc network collects data from multiple sources and transmits them to a #ground #base #station. The proposed mixed-integer nonlinear programming formulation simultaneously determines #cooperative #task #allocation, #data #gathering #schedule, #dynamic #aerial #data #flow, and UAV trajectories to minimize operational energy consumption. A hierarchical two-phase solution procedure that decomposes the original problem into a series of less complex problems and solves them efficiently is developed.----Uihwan Choi, Chaehwan Moon, @Jaemyung Ahn More details can be found at this link: https://lnkd.in/g7f9sjjj

This paper proposes a security-aware computation offloading framework tailored for #mobile #edge #computing (#MEC)-enabled #Internet #of #Things (#IoT) networks operating in environments with #aerial #eavesdroppers (#AEs) and #ground #eavesdroppers (#GEs). It is envisaged that multiple #ground #nodes (#GNs) should perform computation tasks partly locally and partly remotely by offloading a portion of these tasks to MEC servers. To facilitate this paradigm, an #unmanned #aerial #vehicle (#UAV) is deployed, serving as both an aerial MEC server and a relay for forwarding part of the tasks to a ground #access #point (#AP) for computing. The computation offloading is further reinforced by incorporating a #reconfigurable #intelligent #surface (#RIS) unit in close proximity to the AP. Within this context, this paper provides an analysis of the #secrecy #outage #probability (#SOP) and formulates an optimization problem aimed at maximizing the minimum #secure #computation #efficiency (#SCE) by jointly optimizing transmit power allocation, time slot scheduling, task allocation, and RIS’s phase shifts. Given the non-convex nature of the problem, an iterative algorithm is introduced to address the fractional objective function and coupled optimization variables by employing Dinkelbach- and #block #coordinate #descent (#BCD)-based methods, respectively. ---- Emmanouel Michailidis, PhD, SMIEEE, Maria-Garyfallio Volakaki, Nikolaos I. Miridakis, Demosthenes Vouyioukas More details can be found at this link: https://lnkd.in/eucbkwxR

This paper proposes a security-aware computation offloading framework tailored for #mobile #edge #computing (#MEC)-enabled #Internet #of #Things (#IoT) networks operating in environments with #aerial #eavesdroppers (#AEs) and #ground #eavesdroppers (#GEs). It is envisaged that multiple #ground #nodes (#GNs) should perform computation tasks partly locally and partly remotely by offloading a portion of these tasks to MEC servers. To facilitate this paradigm, an #unmanned #aerial #vehicle (#UAV) is deployed, serving as both an aerial MEC server and a relay for forwarding part of the tasks to a ground #access #point (#AP) for computing. The computation offloading is further reinforced by incorporating a #reconfigurable #intelligent #surface (#RIS) unit in close proximity to the AP. Within this context, this paper provides an analysis of the #secrecy #outage #probability (#SOP) and formulates an optimization problem aimed at maximizing the minimum #secure #computation #efficiency (#SCE) by jointly optimizing transmit power allocation, time slot scheduling, task allocation, and RIS’s phase shifts. Given the non-convex nature of the problem, an iterative algorithm is introduced to address the fractional objective function and coupled optimization variables by employing Dinkelbach- and #block #coordinate #descent (#BCD)-based methods, respectively. The obtained results confirm the efficacy of the optimized scheme. ---- Emmanouel Michailidis, PhD, SMIEEE, Maria-Garyfallio Volakaki, Nikos Miridakis, Demosthenes Vouyioukas More details can be found at this link: https://lnkd.in/eucbkwxR

I am delighted to announce that our paper entitled "Multi-Agent DRL-Based Energy Harvesting for Freshness of Data in UAV-Assisted Wireless Sensor Networks" has been published in the IEEE Transactions on Network and Service Management (Early Access) (Q1,IF=4.7). First of all, I would like to thank one of our co-authors and my dear friends, Dr. Mohammed Seid, Ph.D and Nahom Abishu Hayla, for their countless contributions to our paper. Congratulations to all authors, Prof. Supeng Leng, Dr. Maged Refat , Prof. Aiman Erbad, and Prof. Mohsen Guizani. We have introduced a novel multi-access edge computing (MEC)-integrated UAV-supported wireless sensor network (WSN) with a laser technology-based energy harvesting (EH) system that makes the UAV act as a flying energy charger to address these issues. This work aims to minimize the age of information (AoI) and improve energy efficiency by jointly optimizing the UAV trajectories, EH, task scheduling, and data offloading. The joint optimization problem is formulated as a Markov decision process (MDP) and then transformed into a stochastic game model to handle the complexity and dynamics of the environment. We employ a multi-agent deep Q-network (MADQN) algorithm to solve the formulated optimization problem. With the MADQN algorithm, UAVs can determine the best data collection and EH decisions to minimize their energy consumption and efficiently collect data from multiple SNs, leading to reduced AoI and improved energy efficiency.

#Reconfigurable #intelligent #surfaces (#RIS) constitute a revolutionary technique of beneficially reconfiguring the smart radio environment. However, despite the fact that wireless propagation is of time-varying nature, most of the existing RIS contributions focus on time-invariant scenarios for the following reasons. Firstly , it becomes impractical to instantaneously feed back the control signal based on the doubly selective #non-#line-#of-#sight (#NLoS) fading scenario. Secondly , channel estimation conceived for the high-mobility and high-dimensional RIS-assisted links has to take into account the #spatial-#domain (#SD), #time-#domain (#TD), and #frequency-#domain (#FD) correlations imposed by the angle-of-arrival/departure (#AoA/#AoD), the Doppler and the #orthogonal #frequency-#division #multiplexing (#OFDM) operations, respectively, where none of the existing solutions can be directly applied. Thirdly , it is far from trivial to maximize the NLoS channel powers on all subcarriers by a common set of RIS reflecting coefficients. Fourthly , in the face of double selectivity, it becomes inevitable to encounter either #inter-#symbol #interference (#ISI) or #inter-#channel #interference (#ICI) during the signal detection in the TD or in the FD, respectively. Against this background, firstly , the authors focus their attention on #line-#of-#sight (#LoS) dominated #unmanned #aerial #vehicle (#UAV) scenarios. Secondly , they conceive new #minimum #mean #squared #error (#MMSE) channel estimation methods for doubly selective fading, which perodically transmit pilot symbols embedded into the TD and FD over the SD in order to beneficially exploit the correlations in the three domains. Thirdly , the RIS coefficients are optimized by a low-complexity algorithm based on the LoS representation of the end-to-end system model. Fourthly , tailor-made interference cancallation techniques are devised for improving the signal detection both in the FD and in the TD. ---- Chao Xu, Jiancheng An, Tong Bai, Luping Xiang, Shinya Sugiura, Prof Rob Maunder, Lie-Liang Yang, Lajos Hanzo More details can be found at this link: https://lnkd.in/d2uEcAkh

🚀 Exciting News Alert! 🚀 Join us at IEEE BlackSeaCom Georgia (Tbilisi, Georgia) for our upcoming tutorial on "TUT-02: TOWARDS #INTEGRATED, #INTELLIGENT AND #UBIQUITOUS #6G #CONNECTIVITY"! With Aryan Kaushik. 📅 Date: Monday, June 24, 2024 🕘 Time: 13:00-16:30 (Local Time) 📍 Location: Georgian Technical University, Georgia Abstract: Following the recently adopted IMT-2030 framework by ITU-R, several major technologies of integrated sensing and communications (ISAC), intelligent metasurfaces (IM), such as reconfigurable intelligent surfaces (RIS), and nonterrestrial networks (NTN) for integrated, intelligent and ubiquitous 6G connectivity have emerged which herald a new era by transcending conventional communication networks and infrastructure to highly energy efficient, with ultrahigh data rates, shared hardware, and spectral resources, smart radio environment, with an exploration of high-frequency bands such as centimeter wave (cmWave), terahertz (THz), and multiple use cases for 6G, such as ISAC for robotics, and NTN for public safety. The amalgamation of these technologies, such as IM-assisted ISAC, NTN with ISAC signalling, IM aided NTN-TN integration, will also provide a paradigm shift to the way we communicate wirelessly today. Early study items on ISAC are being carried out in 3GPP Rel. 19 to support communications-assisted sensing, and sensing assisted communications. While since 3GPP Rel. 17, NTN technology is one of the major technologies considered for global connectivity. In this direction, evolving signal processing methods, edge-cloud computing, AI and next generation multiple access (NGMA)-assisted deployments for low Earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs)/flying platforms, have drastically changed the current realization of the space, sky and terrestrial communication networks. Besides, interference management using NGMA approaches such as rate-splitting multiple access, becomes important for multibeam multicast LEO satellites in NTN. This tutorial presents a comprehensive overview of emerging solutions, vision, trends, fundamentals, challenges, use cases, technology synergies among ISAC, IM and NTN, to provide integrated, intelligent and ubiquitous 6G connectivity. Key Topics: 🌐 Evolution of 6G wireless standards 🤖 Green AI for NTN IoT 💡 Next generation multiple access (NGMA) for NTN 🚁 UAVs/flying platforms in NTN IoT 🌟 Latest NTN IoT use cases and vertical frameworks Don't miss out on this opportunity to gain valuable insights into the future of wireless networking! Register now and secure your spot at the forefront of innovation. #IEEEBlackSeaCom24 #6G #NTN #WirelessNetworking #Innovation

#Reconfigurable #intelligent #surfaces (#RIS) constitute a revolutionary technique of beneficially reconfiguring the smart radio environment. However, despite the fact that wireless propagation is of time-varying nature, most of the existing RIS contributions focus on time-invariant scenarios for the following reasons. Firstly , it becomes impractical to instantaneously feed back the control signal based on the doubly selective #non-#line-#of-#sight (#NLoS) fading scenario. Secondly , channel estimation conceived for the high-mobility and high-dimensional RIS-assisted links has to take into account the #spatial-#domain (#SD), #time-#domain (#TD), and #frequency-#domain (#FD) correlations imposed by the #angle-#of-#arrival/ #departure (#AoA/ #AoD), the Doppler and the #orthogonal #frequency-#division #multiplexing (#OFDM) operations, respectively, where none of the existing solutions can be directly applied. Thirdly , it is far from trivial to maximize the NLoS channel powers on all subcarriers by a common set of RIS reflecting coefficients. Fourthly , in the face of double selectivity, it becomes inevitable to encounter either #inter-#symbol #interference (#ISI) or #inter-#channel #interference (#ICI) during the signal detection in the TD or in the FD, respectively. Against this background, firstly , the authors focus their attention on #line-#of-#sight (#LoS) dominated #unmanned #aerial #vehicle (#UAV) scenarios. Secondly , they conceive new #minimum #mean #squared #error (#MMSE) channel estimation methods for doubly selective fading, which perodically transmit pilot symbols embedded into the TD and FD over the SD in order to beneficially exploit the correlations in the three domains. Thirdly, the RIS coefficients are optimized by a low-complexity algorithm based on the LoS representation of the end-to-end system model. Fourthly , tailor-made interference cancallation techniques are devised for improving the signal detection both in the FD and in the TD. ---- Chao Xu, Jiancheng An, Tong Bai, Luping Xiang, Shinya Sugiura, Prof Rob Maunder, Lie-Liang Yang, Lajos Hanzo More details can be found at this link: https://lnkd.in/d2uEcAkh

#SpaceResearch 117: The integration of smart sensors in space habitats can enhance monitoring and control. We're researching how to use sensors to track environmental conditions and optimize resource use. #SmartSensors #SpaceHabitat #BIM4Space #SmartTech

🚨 EU LAUNCHES GROUNDBREAKING METHANE CRACKDOWN 🚨 The EU has enacted its first-ever regulation to reduce methane emissions, set to be implemented in 2025. This landmark legislation, EU 2024/1787, imposes strict emission standards on fossil fuel operations and imports. Member States must appoint national authorities for compliance, and the European Commission will detail methodologies for reporting methane emissions. This regulation aims to set a global standard in methane reduction, driving significant progress in the fight against climate change. How AIRMO’s sensor technology supports compliance 🌍 Global Coverage: Our CubeSAT satellites and drones provide extensive monitoring capabilities. Both solutions are equipped with our 3 sensors: ◆ Infrared spectrometer: Identifies methane presence by measuring specific wavelengths absorbed by gas molecules, enabling high-precision detection. ◆ LiDAR system: Removes measurement noise via aerosol correction, creating detailed emission sources for precise localization of leaks in various terrains and infrastructures. ◆ RGB camera: Captures high-resolution images for georeferencing and visual verification, complementing data from other sensors. 🔧 Integrated Sensor Synergy: The combination of the infrared spectrometer, LiDAR system, and RGB camera creates a comprehensive monitoring system. The infrared spectrometer detects methane, the LiDAR system improves data accuracy by correcting for aerosols, and the RGB camera provides georeferenced visual context.  This integration results in high precision and reliability in detecting and quantifying methane emissions. 🎯 Scalable and flexible solutions: AIRMO’s plug-and-play technology ensures that our sensors can be deployed across different platforms and environments, offering scalable solutions to meet both current and future regulatory requirements. Curious to learn more about how AIRMO solution can support your business in achieving compliance and sustainability goals? Reach out to us today! ✍ #AIRMO #MethaneRegulation #ClimateAction #EmissionsMonitoring #Sustainability #Innovation #GreenFuture #AIRMOmento #EU

The implementation of a comprehensive, tech-driven surveillance system for solar-powered roadside facilities requires meticulous planning and integration of advanced technologies. High-resolution cameras, thermal imaging, AI-driven analytics, and drones ensure full coverage of the site, while energy storage systems ensure uninterrupted operation. The combination of robust surveillance, energy-efficient solar power, and high-level security measures makes these systems resilient, scalable, and appealing to investors looking to support sustainable transportation infrastructure.