Joint User Pairing and Power Allocation for NOMA-Based GEO and LEO Satellite Network

• Published in: IEEE access Vol. 9; pp. 93255 - 93266
• Main Authors: Ge, Ruixing, Bian, Dongming, Cheng, Jian, An, Kang, Hu, Jing, Li, Guangxia
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Interference; Iterative algorithms; Iterative methods; Low earth orbit satellites; Low earth orbits; Multi-layer satellite networks; Multilayers; NOMA; non-orthogonal multiple access; Nonorthogonal multiple access; Optimization; power allocation; Power consumption; Resource management; Satellite broadcasting; Satellite networks; Satellites; Subcarriers; Throughput; user pairing
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3078458

Multi-layer satellite networks (MLSNs) is of great potential for the integrated 5G networks to provide diversified services. However, MLSNs confront frequency interference coordination problem between satellite systems in different orbits. This paper investigates a joint user pairing and power allocation scheme in a non-orthogonal multiple access (NOMA)-based geostationary earth orbit (GEO) and low earth orbit (LEO) satellite network. Specifically, a novel NOMA framework with two uplink receivers, i.e. the GEO and LEO satellites is established where the NOMA groups are formed considering the subcarrier assignment of ground users. To maximize the system capacity, an optimization problem is then introduced subject to the decoding threshold and power consumption. Since the formulated problem is non-convex and mathematically intractable, we decompose it into user pairing and power allocation schemes. In the user pairing scheme, virtual GEO users are generated to transform the multi-user pairing problem into a matching problem and a max-min pairing strategy is adopted to ensure the fairness among NOMA groups. In the power allocation scheme, the non-convex problem is transformed into multiple convex subproblems and solved by iterative algorithm. Simulation results validate the effectiveness and superiority of the proposed schemes when compared with several existing schemes.