Shannon Wireless’ Post

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

In this paper, the authors propose a secure #short-#packet #communication (#SPC) system, where a #unmanned #aerial #vehicle (#UAV) serves as a mobile #decode-and-#forward (#DF) relay, periodically receiving and relaying small data packets from a remote IoT device to its receiver in two hops with strict latency requirements, in the presence of an eavesdropper. This system requires careful optimization of important design parameters, such as the coding blocklengths of both hops, transmit powers, and the UAV's trajectory. While the overall optimization problem is nonconvex, the authors tackle it by applying a #block #successive #convex #approximation (#BSCA) approach to divide the original problem into three subproblems and solve them separately. ---- Milad Tatar Mamaghani, PhD, Xiangyun (Sean) Zhou, Nan Yang, A. Lee Swindlehurst More details can be found at this link: https://lnkd.in/ddeZFn5v

We are thrilled to share our latest research presented at the 2024 IEEE Cloud Summit, titled: "Exploiting Correlations for Enhanced Spectrum Efficiency in Smart City 6G with Multi-UAV Networks" 🔍 Abstract: With the rapid growth of user demands and the rise of the Internet of Everything (IoE), efficient spectrum utilization in 6G UAV networks has become a critical challenge—especially in the context of smart cities. Our study introduces a linear programming model designed to leverage source correlations (e.g., co-located video sensors) for optimizing spectrum efficiency. Key Findings: ✅ Significant improvement in spectrum efficiency by exploiting source correlations. ✅ Nearly 100% of delay-intolerant traffic admitted into the network. ✅ Delay-tolerant traffic delays reduced by 50-88%, enhancing overall network performance. ✅ A trade-off mechanism between accuracy and computational complexity to maximize efficiency. This work demonstrates how source correlation exploitation can revolutionize spectrum allocation, pushing the boundaries of 6G technologies in smart cities. 📍 Published In: 2024 IEEE Cloud Summit 📅 Conference Date: June 27-28, 2024 📍 Location: Washington, DC, USA 📖 DOI: 10.1109/Cloud-Summit61220.2024.00027 Stay tuned for more updates as we continue driving innovation in wireless communication and smart city solutions! #6G #UAVNetworks #SmartCity #SpectrumEfficiency #WirelessInnovation #Research  #stc #SpaceUp #SpaceInnovation #SpaceEconomy #SaudiVision2030 https://lnkd.in/dRv-E2SP

This work proposes a novel method of energy and throughput management in a delay-constrained small-world #unmanned #aerial #vehicle (#UAV)-#Internet #of #Things (#IoT) network is proposed. The proposed small-world framework optimizes the number of hops required for the data transmission leading to improved energy efficiency and quality of service. The method introduces optimal long-range links between device pairs resulting in low average path length and high clustering coefficient which are called as small-world characteristics. ----Sreenivasa Reddy Yeduri, @Naga Srinivasarao Chilamkurthy, Om Jee Pandey, @Linga Reddy Cenkeramaddi More details can be found at this link: https://lnkd.in/emQxBtMN

This paper presents a novel framework for #joint #field #data #collection and #wireless #charging in an #unmanned #aerial #vehicle (#UAV)-aided wireless sensor network via #monostatic #backscatter #communication at #millimeter #waves. The framework is divided into three tasks, namely, #energy-#optimized #UAV #transceiver #design, UAV constraints aware #backscatter #nodes (#BSNs) clustering, and optimized resource allocation per cluster. To strike a balance between serving efficiency and self-interference, the optimum BSN cluster size is estimated offline, which in turn governs BSN clustering optimization. With UAV communication energy and clustering information, a #joint #sum #energy #transfer and #sum #data #collection #maximization #problem is formulated by considering the minimum required charging and data collection constraints.----Amit Goel, Nancy Varshney, Swades De More details can be found at this link: https://lnkd.in/gWr8J_GG

This paper tackles the energy concern of #Internet #of #Things (#IoT) devices by utilizing #Unmanned #Aerial #Vehicles (#UAVs) as data collectors and energy transmitters and by promptly charging IoT devices whenever necessary. As for the energy concern of UAVs, the authors deploy a set of #Unmanned #Ground #Vehicles (#UGVs) to energy supply UAVs, allowing them to complete their tasks successfully. Their objective is to employ a #multi-#agent #reinforcement #learning method for optimally controlling the trajectories of both UGVs and UAVs so that it jointly decreases their energy consumption, reduces the #Age #of #Information (#AoI) of IoT devices, and timely charges UAVs and avoids their failures.----Kaddour MESSAOUDI, @Abdullah Baz, Omar Sami Oubbati, Abderrezak Rachedi, Mohamed tahar Bendouma, Mohammed Atiquzzaman More details can be found at this link: https://lnkd.in/g4meWGjv

In this study, the authors propose an innovative #Deep #Reinforcement #Learning (#DRL) agent based on #Proximal #Policy #Optimization (#PPO) to improve the #Energy #Efficiency (#EE) while considering #far-#near #fairness (#FNF) in #non-#orthogonal #multiple #access (#NOMA)-#unmanned #aerial #vehicle (#UAV) networks. This agent is designed to simultaneously control dynamic factors such as UAV 3D trajectory, downlink transmit power, #internet #of #things (#IoT) nodes association, and #power #allocation (#PA). ---- Benmeziane GHOMRI, Mohammed Yassine Bendimerad, Fethi Tarik Bendimerad More details can be found at this link: https://lnkd.in/eJ---izf

This paper considers a multi-#unmanned #aerial #vehicle (#UAV) assisted network in which multiple UAVs and a terrestrial base station (BS) are deployed to provide #mobile #edge #computing (#MEC) services to mobile users. The objective is to minimize an energy and latency-based cost function by jointly optimizing task offloading and MEC server selection decision, transmission power, UAV trajectory, and CPU frequency allocation. An alternating iterative approach based on the block descent method is proposed to solve this problem. In the first layer, task offloading and server selection decision subproblem is solved using a game theoretic approach. The second layer handles offloading and downloading transmission power allocations by utilizing a simplistic #geometric #waterfilling (#GWF) technique, and the UAV trajectory by #successive# convex #approximation (#SCA). Whereas, the third layer solves the computation resource subproblem by performing CPU frequency allocation using a gradient descent method. The proposed method uses a segment-by-segment approach, which divides the entire UAV flight trajectory into shorter timeframe segments to reduce the computation time. ---- Farhan Pervez, Ajmery Sultana, Cungang Yang, Lian Zhao More details can be found at this link: https://lnkd.in/eepwzgmA

Integrating sensing and communication capabilities (ISAC) in mobile networks An exciting part of the evolution of mobile networks is the opportunity to support both sensing and communication capabilities in the future. A network acting as a sensor is unique as it can perform spatial location of unconnected objects and objects connected to other networks with the extensive reach of a mobile network. 3GPP has studied 32 potential use cases where ISAC can add new types of sensors and give access to data never seen before. Enjoy reading this blog post that outlines what this innovation can do in America. #5G #6G #ISAC #JCAS #NetworkAsASensor Yossi Cohen | Erik Ekudden | Marie Hogan | Patrik Persson | Robert Baldemair | Christina Chaccour

Integrated Sensing and Communication (ISAC) represents a transformative approach within 5G and beyond, aiming to merge wireless communication and sensing functionalities into a unified network infrastructure. By repurposing communication signals for sensing, this integration offers enhanced spectrum efficiency, real-time situational awareness, cost and energy reductions, and improved operational performance. We have developed I-SCOUT, an innovative ISAC solution designed to uncover moving targets in NextG networks. I-SCOUT can accurately estimate both the range and velocity of these targets (e.g., drones), and distinguish between multiple targets such as in swarm environments. Joint work of Utku Demir, PhD, Kemal Davaslioglu, Yalin Sagduyu, Tugba Erpek, Gustave Anderson, and Sastry Kompella, Ph.D. was accepted to appear at the IEEE MILCOM’24 conference. A preprint is available at: https://lnkd.in/ekmSNunh Nexcepta, Inc. looks forward to discussing more on the capabilities of I-SCOUT and future directions at MILCOM. #5G #6G #nextg #isac #sensing #communications