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Power-Level-Design-aware Scalable Framework for Throughput Analysis of GF-NOMA in mMTC
  • Takeshi Hirai ,
  • Rei Oda ,
  • Naoki Wakamiya
Takeshi Hirai
Osaka University

Corresponding Author:[email protected]

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Naoki Wakamiya
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This paper proposes a scalable framework for the throughput analysis of the grant-free power-domain non-orthogonal multiple access (GF-NOMA) and presents the achievable performance in the optimized offered load at each power level (called per-level offered load).
Our analytical model reflects packet errors caused by \textit{power collisions}, characterized by GF-NOMA, based on the power level design guaranteeing the required signal-to-interference-and-noise ratio (SINR).
This idea enables analyzing the throughput of a large-scale GF-NOMA system more accurately than the existing models and thus optimizing the per-level offered load rather than a uniform one in the throughput maximization or energy minimization problem with a throughput condition.
Our analytical results highlighted some key insights into designing future access control methods in GF-NOMA.
First, our analytical model achieved an approximation error percentage of only 0.4% for the exact throughput obtained by the exhaustive search at five power levels; then, the existing one provided that of 25%.
Next, by using our framework, the optimal per-level offered load restrictively improved the throughput above the optimally uniform per-level offered load.
Finally, our framework discovered a 27% more energy-efficient per-level offered load than the existing framework at five power levels while providing higher throughput than the uniform per-level offered load optimized by our framework.