Joint optimization of beam-hopping design and NOMA-assisted transmission for flexible satellite systems

Next-generation satellite systems require more flexibility in resource management such that available radio resources can be dynamically allocated to meet time-varying and non-uniform traffic demands. Considering potential benefits of beam hopping (BH) and non-orthogonal multiple access (NOMA), we e...

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Bibliographic Details
Authors: Wang, Anyue, Lei, Lei, Lagunas Targarona, Eva|||0000-0002-9936-7245, Pérez Neira, Ana Isabel|||0000-0003-4281-3934, Chatzinotas, Symeon, Ottersten, Björn
Format: article
Publication Date:2022
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/369753
Online Access:https://hdl.handle.net/2117/369753
https://dx.doi.org/10.1109/TWC.2022.3170435
Access Level:Open access
Keyword:Artificial satellites in telecommunication
Resource allocation
Telecommunication -- Traffic -- Management
Multi-beam satellite systems
Beam hopping
Non-orthogonal multiple access
Resource optimization
Satèl·lits artificials en telecomunicació
Assignació de recursos
Telecomunicació -- Tràfic -- Gestió
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços
Description
Summary:Next-generation satellite systems require more flexibility in resource management such that available radio resources can be dynamically allocated to meet time-varying and non-uniform traffic demands. Considering potential benefits of beam hopping (BH) and non-orthogonal multiple access (NOMA), we exploit the time-domain flexibility in multi-beam satellite systems by optimizing BH design, and enhance the power-domain flexibility via NOMA. In this paper, we investigate the synergy and mutual influence of beam hopping and NOMA. We jointly optimize power allocation, beam scheduling, and terminal-timeslot assignment to minimize the gap between requested traffic demand and offered capacity. In the solution development, we formally prove the NP-hardness of the optimization problem. Next, we develop a bounding scheme to tightly gauge the global optimum and propose a suboptimal algorithm to enable efficient resource assignment. Numerical results demonstrate the benefits of combining NOMA and BH, and validate the superiority of the proposed BH-NOMA schemes over benchmarks.