Deep learning-based signal detection for rate-splitting multiple access under generalized gaussian noise

HIGHLIGHTS

• who: Generalized Gaussian Noise and colleagues from the Department of Electronics and Communication Engineering, PES University, Bengaluru, India have published the article: Deep Learning-Based Signal Detection for Rate-Splitting Multiple Access Under Generalized Gaussian Noise, in the Journal: (JOURNAL)
• what: The authors propose a long short-term memory-based deep learning (DL) architecture for signal detection in uplink and downlink rate-splitting multiple access systems with multi-carrier modulation over Nakagami-m fading and_(GGN). In an orthogonal frequency division multiplexing setting the authors show that the proposed DL detector outperforms the standard SIC . . .
  

   

  

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