Abstract:
Space-air-ground integrated network (SAGIN) is a promising network architecture for next-generation wireless networks, which combines satellite networks, aerial networks,...View moreMetadata
Abstract:
Space-air-ground integrated network (SAGIN) is a promising network architecture for next-generation wireless networks, which combines satellite networks, aerial networks, and terrestrial networks to enable ubiquitous global network services to ground users and improve connectivity for wide deployment wireless applications. Also, free-space optical (FSO) communication with the advantages of low deployment cost, energy efficiency, and extremely high-speed data-delivering capability has attracted more attention recently. However, data transmission efficiency in SAGIN is still limited by the dynamic time-varying network topology and data transmission link connection. In this paper, we construct an FSO/radio frequency (RF) space-air-ground integrated network to enable large-scale and high-speed data transmission as well as degrade the burden of terrestrial networks. In addition, a deep-Q network-based reinforcement learning with an experience replay memory mechanism is proposed to execute dynamic hybrid routing by evaluated rewards. The simulation results show that the proposal achieves significant network performance compared with baseline methods.
Date of Conference: 04-08 December 2023
Date Added to IEEE Xplore: 26 February 2024
ISBN Information: