Database-assisted spectrum sharing in satellite communications:A survey

This survey paper discusses the feasibility of sharing the spectrum between satellite telecommunication networks and terrestrial and other satellite networks on the basis of a comprehensive study carried out as part of the European Space Agency's (ESA) Advanced Research in Telecommunications Systems (ARTES) programme. The main area of investigation is the use of spectrum databases to enable a controlled sharing environment. Future satellite systems can largely benefit from the ability to access spectrum bands other than the dedicated licensed spectrum band. Potential spectrum sharing scenarios are classified as: a) secondary use of the satellite spectrum by terrestrial systems, b) satellite system as a secondary user of spectrum, c) extension of a terrestrial network by using the satellite network, and d) two satellite systems sharing the same spectrum. We define practical use cases for each scenario and identify suitable techniques. The proposed scenarios and use cases cover several frequency bands and satellite orbits. Out of all the scenarios reviewed, owing to the announcement of many different mega-constellation satellite networks, we focus on analysing the feasibility of spectrum sharing between geostationary orbit (GSO) and non-geostationary orbit (NGSO) satellite systems. The performance is primarily analysed on the basis of widely accepted recommendations of the Radiocommunications Sector of the International Telecommunications Union (ITU-R). Finally, future research directions are identified

Shared access satellite-terrestrial reconfigurable backhaul network enabled by smart antennas at mm-wave band

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.5G traffic expectations require not only the appropriate access infrastructure, but also the corresponding backhaul infrastructure to ensure a well-balanced network scaling. Optical fibre and terrestrial wireless backhaul will hardly meet 100% coverage and satellite must be considered within the 5G infrastructure to boost ubiquitous and reliable network utilization. This work presents the main outcomes of SANSA project, which proposes a novel solution that overcomes the limitations of the traditional fixed backhaul. It is based on a dynamic integrated satelliteterrestrial backhaul network operating on the mm-wave band. Its key principles are a seamless integration of the satellite segment into terrestrial backhaul networks; a terrestrial wireless network capable of reconfiguring its topology according to traffic demands; and an aggressive frequency reuse within the terrestrial segment and between terrestrial and satellite segments. The two technological enablers of SANSA are smart antenna techniques at mm-wave and a software defined intelligent hybrid network management. This article introduces these 5G enablers, which permit satellite communications to play a key role in different 5G use cases, from the early deployment of 5G services in sparse scenarios to enhanced mobile broadband in denser scenarios.Peer ReviewedPostprint (author's final draft

Dynamic Resource Management in Integrated NOMA Terrestrial-Satellite Networks using Multi-Agent Reinforcement Learning

This study introduces a resource allocation framework for integrated satellite-terrestrial networks to address these challenges. The framework leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to reduce time delays and improve energy efficiency. Our proposed approach utilizes a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG) to optimize user association, cache design, and transmission power control, resulting in enhanced energy efficiency. The approach comprises two phases: User Association and Power Control, where users are treated as agents, and Cache Optimization, where the satellite (Bs) is considered the agent. Through extensive simulations, we demonstrate that our approach surpasses conventional single-agent deep reinforcement learning algorithms in addressing cache design and resource allocation challenges in integrated terrestrial-satellite networks. Specifically, our proposed approach achieves significantly higher energy efficiency and reduced time delays compared to existing methods.Comment: 16, 1

Energy-Efficient Design of Satellite-Terrestrial Computing in 6G Wireless Networks

In this paper, we investigate the issue of satellite-terrestrial computing in the sixth generation (6G) wireless networks, where multiple terrestrial base stations (BSs) and low earth orbit (LEO) satellites collaboratively provide edge computing services to ground user equipments (GUEs) and space user equipments (SUEs) over the world. In particular, we design a complete process of satellite-terrestrial computing in terms of communication and computing according to the characteristics of 6G wireless networks. In order to minimize the weighted total energy consumption while ensuring delay requirements of computing tasks, an energy-efficient satellite-terrestrial computing algorithm is put forward by jointly optimizing offloading selection, beamforming design and resource allocation. Finally, both theoretical analysis and simulation results confirm fast convergence and superior performance of the proposed algorithm for satellite-terrestrial computing in 6G wireless networks