Terminal-Aware Multi-Connectivity Scheduler for Uplink Multi-Layer Non-Terrestrial Networks

Abstract

This paper introduces the concept of multiconnectivity (MC) to the multi-orbit non-terrestrial networks (NTNs), where user terminals can be served by more than one satellite to achieve higher peak throughput. MC is a technique initially introduced by the 3rd Generation Partnership Project (3GPP) for terrestrial communications in 4G and 5G, it has shown much gain in the terrestrial domain and this paper explores areas where this concept can benefit the satellite domain. MC can increase throughput, but this entails increased power consumption at user terminal for uplink transmissions. The energy efficiency of uplink communications can be improved by designing efficient scheduling schemes, and to this end, we developed a terminal aware multi-connectivity scheduling algorithm. This proposed algorithm uses the available radio resources and propagation information to intelligently define a dynamic resource allocation pattern, that optimally routes traffic so as to maximize uplink data rate while minimizing the energy consumption at the UT. The algorithm operates with the terminal differentiating multi-layer NTN resource scheduling architecture, which has a softwarized dispatcher at the network layer that classifies and differentiates the packets based on terminal type. The performance of the proposed algorithm was compared with round robin and joint carrier schedulers in terms of uplink data rate and energy efficiency. We also provide architectural design of implementable schedulers for multi-orbital satellite networks that can operate with different classes of terminals.

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

“…Furthermore, the study in [ 80 ] introduces multi-connectivity to multi-orbit NTNs, allowing user terminals to connect to numerous satellites in order to increase peak throughput. The researchers propose a terminal-aware multi-connectivity scheduling algorithm that optimizes uplink data rates and minimizes energy consumption at the user terminal based on radio availability and propagation data.…”

Energy-Efficient Service-Aware Multi-Connectivity Scheduler for Uplink Multi-Layer Non-Terrestrial Networks

“…1) Design guidelines are outlined for the deployment of a multilayer satellite network comprising low earth orbit (LEO), medium earth orbit (MEO), and geostationary earth orbit (GEO) satellites, which are all served by multi-orbital hybrid gateway stations (HGSs) [10]. These gateway stations operate with softwarized controller and network function virtualization (NFV) elements at the network and data link layers, the softwarized controller performs functions including the segmentation and classification of protocol data units (PDUs) based on the service category of the transmitting user [1]; this allows for a pure softwarized implementation of schedulers.…”

“…2) Developing a scheduler aided by a segmentation algorithm with protocol stack adaptation, which assigns priority and preference for resource allocation to PDUs based on identified service classes. In this work, three classes are considered from 3GPP; namely, ultra-reliable low latency communication (URLLC) 1 , massive machine type communication (mMTC), and enhanced mobile broadband (eMBB). 3) An energy-efficient service aware multi-connectivity (EE-SAMC) scheduling algorithm is developed for optimal resource allocation involving power and spectrum leading to a high capacity transmission with energy efficiency in the uplink.…”

Multi-Connectivity in 5G and Beyond Non-Terrestrial Networks

“…Utilizing efficient scheduling strategies [15] can lead to efficient resource utilization and an increase in spectral efficiency and should be used. Indeed, the usage of MC can lead to a greater number of possible paths through which the data can be routed.…”

“…Multiconnectivity (MC) is a promising method that allows a user equipment (UE) to connect to multiple base stations (BSs) simultaneously. MC in NTNs can be used, for example, in load balancing [3], to provide higher peak throughput [4] to cell edge users, to aid in interference mitigation, and to enhance service continuity [5], energy-efficiency [6], and reliability [7].…”