4.7 Article

NOMA-Enabled Multi-Beam Satellite Systems: Joint Optimization to Overcome Offered-Requested Data Mismatches

期刊

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 70, 期 1, 页码 900-913

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.3047453

关键词

NOMA; Satellite broadcasting; Satellites; Resource management; Optimization; Decoding; Precoding; Max-min fairness; multi-beam satellite systems; non -orthogonal multiple access (NOMA); offered capacity to requested traffic ratio (OCTR); resource optimization

资金

  1. FNR CORE project ROSETTA [11632107]
  2. FNR CORE project FlexSAT [C19/IS/13696663]
  3. project TERESA [TEC2017-90093-C3-1-R]

向作者/读者索取更多资源

The study improves the performance of satellite communication systems using non-orthogonal multiple access (NOMA) technology and evaluates it using the OCTR metric. By jointly optimizing power, decoding orders, and terminal-timeslot assignment, the system's max-min fairness of OCTR is enhanced.
Non-orthogonal multiple access (NOMA) has potentials to improve the performance of multi-beam satellite systems. The performance optimization in satellite-NOMA systems could be different from that in terrestrial-NOMA systems, e.g., considering distinctive channel models, performance metrics, power constraints, and limited flexibility in resource management. In this paper, we adopt a metric, offered capacity to requested traffic ratio (OCTR), to measure the requested-offered data rate mismatch in multi-beam satellite systems. In the considered system, NOMA is applied to mitigate intra-beam interference while precoding is implemented to reduce inter-beam interference. We jointly optimize power, decoding orders, and terminal-timeslot assignment to improve the max-min fairness of OCTR. The problem is inherently difficult due to the presence of combinatorial and non-convex aspects. We first fix the terminal-timeslot assignment, and develop an optimal fast-convergence algorithmic framework based on Perron-Frobenius theory (PF) for the remaining joint power-allocation and decoding-order optimization problem. Under this framework, we propose a heuristic algorithm for the original problem, which iteratively updates the terminal-timeslot assignment and improves the overall OCTR performance. Numerical results show that the proposed algorithm improves the max-min OCTR by 40.2% over orthogonal multiple access (OMA) in average.

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