HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System

MH Rahman, MAS Sejan, MA Aziz, YH You… - IEEE …, 2023 - ieeexplore.ieee.org
Deep learning (DL) techniques can significantly improve successive interference
cancellation (SIC) performance for the non-orthogonal multiple access (NOMA) system. The …
被引用次数：8 相关文章
[PDF] researchgate.net

[PDF][PDF] HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System

MDH RAHMAN, MAS SEJAN, MDA AZIZ, YH YOU… - researchgate.net
Deep learning (DL) techniques can significantly improve successive interference
cancellation (SIC) performance for the non-orthogonal multiple access (NOMA) system. The …

[引用][C] HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System

MH Rahman, MAS Sejan, MA Aziz, YH You… - IEEE …, 2023 - ui.adsabs.harvard.edu
HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and
Signal Detection for NOMA-OFDM System - NASA/ADS Now on home page ads icon ads …
[PDF] researchgate.net

[PDF][PDF] HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System

MDH RAHMAN, MAS SEJAN, MDA AZIZ, YH YOU… - researchgate.net
Deep learning (DL) techniques can significantly improve successive interference
cancellation (SIC) performance for the non-orthogonal multiple access (NOMA) system. The …