Summary
In this paper, we present a satellite‐integrated 5G testbed that was produced for the EU‐commissioned Satellite and Terrestrial Networks for 5G (SaT5G) project. We first describe the testbed's 3GPP Rel. 15/6‐compliant mobile core and radio access network (RAN) that have been established at the University of Surrey. We then detail how satellite NTN UE and gateway components were integrated into the testbed using virtualization and software‐defined orchestration. The satellite element provides 5G backhaul, which in concert with the terrestrial/mobile segment of the testbed forms a fully integrated end‐to‐end (E2E) 5G network. This hybrid 5G network exercised and validated the four major use cases defined within the SaT5G project: cell backhaul, edge delivery of multimedia content, multicast and caching for media delivery and multilinking using satellite and terrestrial. In this document, we describe the MEC implementations developed to address each of the aforementioned use cases and explore how each MEC system integrates into the 5G network. We also provide measurements from trials of the use cases over a live GEO satellite system and indicate in each case the improvements that result from the use of satellite in the 5G network.
Traditional loss-based Congestion Control Algorithms (CCAs) suffer from performance issues over wireless networks mostly because they fail to distinguish wireless random losses from congestion losses. Different loss discrimination algorithms have been proposed to tackle this issue but they are not efficient for 4G networks since they do not consider the impact of various link layer mechanisms such as adaptive modulation and coding and retransmission techniques on congestion in LTE Radio Access Networks (RANs). We propose MELD (MEC-based Edge Loss Discrimination), a novel server-side loss discrimination mechanism that leverages recent advancements in Multi-access Edge Computing (MEC) services to discriminate packet losses based on real-time RAN statistics. Our approach collects the relevant radio information via MEC's Radio Network Information Service and uses it to correctly distinguish random losses from congestion losses. Our experimental study made with the QUIC transport protocol shows over 80% higher goodput when MELD is used with New Reno and 8% higher goodput when used with Cubic.
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