TY - JOUR
T1 - A review of deep learning in 5G research
T2 - Channel coding, massive MIMO, multiple access, resource allocation, and network security
AU - Ly, Amanda
AU - Yao, Yu Dong
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2021
Y1 - 2021
N2 - The current development of 5G technology is flourishing with widespread deployment across the world at a rapid pace. However, there is still a demand concerning 5G research for service and performance improvement. Research tasks include but are not limited to quality-of-service (QoS), energy efficiency, massive connectivity, reliable communications, and security. Due to the advancement of deep learning, numerous such research has utilized this technique. This article provides a comprehensive review of 5G communications research using deep learning. Specifically, we address the issues of low-density parity-check (LDPC) coding, massive multiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), resource allocation, and security.
AB - The current development of 5G technology is flourishing with widespread deployment across the world at a rapid pace. However, there is still a demand concerning 5G research for service and performance improvement. Research tasks include but are not limited to quality-of-service (QoS), energy efficiency, massive connectivity, reliable communications, and security. Due to the advancement of deep learning, numerous such research has utilized this technique. This article provides a comprehensive review of 5G communications research using deep learning. Specifically, we address the issues of low-density parity-check (LDPC) coding, massive multiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), resource allocation, and security.
KW - Deep learning (DL)
KW - fifth generation (5G)
KW - low-density parity-check coding (LDPC)
KW - machine learning (ML)
KW - massive multiple-input multiple-output (MIMO)
KW - non-orthogonal multiple access (NOMA)
KW - resource allocation
KW - security
UR - http://www.scopus.com/inward/record.url?scp=85113858222&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113858222&partnerID=8YFLogxK
U2 - 10.1109/OJCOMS.2021.3058353
DO - 10.1109/OJCOMS.2021.3058353
M3 - Review article
AN - SCOPUS:85113858222
VL - 2
SP - 396
EP - 408
JO - IEEE Open Journal of the Communications Society
JF - IEEE Open Journal of the Communications Society
M1 - 9353849
ER -