Caching Through the Skies: The Case of LEO Satellites Connected Edges for 6G and Beyond

2023-03-22 · Basem Abdellatif, Mostafa M. Shibl, Tamer Khattab, John Tadrous, Tarek Elfouly, Nizar Zorba

The deployment of low earth orbit (LEO) satellites with terrestrial networks can potentially increase the efficiency and reduce the cost of relaying content from a data center to a set of edge caches hosted by 6G and beyond enabled macro base stations. In this work, the characteristics of the communication system and the mobility of LEO satellites are thoroughly discussed to describe the channel characteristics of LEO satellites, in terms of their frequency bands, latency, Doppler shifts, fading effects, and satellite access. Three different scenarios are proposed for the relay of data from data centers to edge caches via LEO satellites, which are the "Immediate Forward", "Relay and Forward", and "Store and Forward" scenarios. A comparative problem formulation is utilized to obtain numerical results from simulations to demonstrate the effectiveness and validity as well as the trade-offs of the proposed system model. The simulation results indicate that the integration of LEO satellites in edge caching for 6G and beyond networks decreased the required transmission power for relaying the data from the data center to the edge caches. Future research directions based on the proposed model are discussed.

📄 PDF Abstract BibTeX arXiv:2303.12895

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

BASE 설명 없음

Stochastic Geometry-Based Performance Evaluation for LEO Satellite-Assisted Space Caching

2025-05-27 · Chunyi Ma, Jiajie Xu, Jianhua Yang, Mustafa A. Kishk

To achieve the Internet of Things (IoT) vision,Mobile Edge Computing (MEC) is a promising technology aimed at providing low-latency computing services to user equipment (UE). However, terrestrial MEC network struggles to…

Edge-computing

Deep Reinforcement Learning for Adaptive Caching in Hierarchical Content Delivery Networks

2019-02-27 · Alireza Sadeghi, Gang Wang, Georgios B. Giannakis

Caching is envisioned to play a critical role in next-generation content delivery infrastructure, cellular networks, and Internet architectures. By smartly storing the most popular contents at the storage-enabled network…

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Sparse Incremental Aggregation in Satellite Federated Learning

2025-01-20 · Nasrin Razmi, Sourav Mukherjee, Bho Matthiesen, Armin Dekorsy 외

This paper studies Federated Learning (FL) in low Earth orbit (LEO) satellite constellations, where satellites are connected via intra-orbit inter-satellite links (ISLs) to their neighboring satellites. During the FL tra…

Federated Learning

Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading

2023-12-23 · Dong-Jun Han, Seyyedali Hosseinalipour, David J. Love, Mung Chiang 외

While network coverage maps continue to expand, many devices located in remote areas remain unconnected to terrestrial communication infrastructures, preventing them from getting access to the associated data-driven serv…

Federated Learning Management

LeadCache: Regret-Optimal Caching in Networks

2020-09-17 · Debjit Paria, Abhishek Sinha

We consider an online prediction problem in the context of network caching. Assume that multiple users are connected to several caches via a bipartite network. At any time slot, each user may request an arbitrary file ch…

Combinatorial Optimization