TY - JOUR
T1 - Joint user grouping and power control using whale optimization algorithm for NOMA uplink systems
AU - Rehman, Bilal ur
AU - Babar, Mohammad Inayatullah
AU - Ahmad, Arbab Waheed
AU - Amir, Muhammad
AU - Shahjehan, Waleed
AU - Sadiq, Ali Safaa
AU - Mirjalili, Seyedali
AU - Dehkordi, Amin Abdollahi
N1 - Funding Information:
The authors received no funding for this work.
Publisher Copyright:
© Copyright 2022 Rehman et al.
PY - 2022
Y1 - 2022
N2 - The non-orthogonal multiple access (NOMA) scheme has proven to be a potential candidate to enhance spectral potency and massive connectivity for 5G wireless networks. To achieve effective system performance, user grouping, power control, and decoding order are considered to be fundamental factors. In this regard, a joint combinatorial problem consisting of user grouping and power control is considered, to obtain high spectral-efficiency for NOMA uplink system with lower computational complexity. To solve the joint problem of power control and user grouping, for Uplink NOMA, we have used a newly developed meta-heuristicnature-inspired optimization algorithm i.e., whale optimization algorithm (WOA), for the first time. Furthermore, for comparison, a recently initiated grey wolf optimizer (GWO) and the well-known particle swarm optimization (PSO) algorithms were applied for the same joint issue. To attain optimal and sub-optimal solutions, a NOMA-based model was used to evaluate the potential of the proposed algorithm. Numerical results validate that proposedWOA outperforms GWO, PSO and existing literature reported for NOMA uplink systems in-terms of spectral performance. In addition, WOA attains improved results in terms of joint user grouping and power control with lower system-complexity when compared toGWOand PSO algorithms. The proposed work is a novel enhancement for 5G uplink applications of NOMA systems.
AB - The non-orthogonal multiple access (NOMA) scheme has proven to be a potential candidate to enhance spectral potency and massive connectivity for 5G wireless networks. To achieve effective system performance, user grouping, power control, and decoding order are considered to be fundamental factors. In this regard, a joint combinatorial problem consisting of user grouping and power control is considered, to obtain high spectral-efficiency for NOMA uplink system with lower computational complexity. To solve the joint problem of power control and user grouping, for Uplink NOMA, we have used a newly developed meta-heuristicnature-inspired optimization algorithm i.e., whale optimization algorithm (WOA), for the first time. Furthermore, for comparison, a recently initiated grey wolf optimizer (GWO) and the well-known particle swarm optimization (PSO) algorithms were applied for the same joint issue. To attain optimal and sub-optimal solutions, a NOMA-based model was used to evaluate the potential of the proposed algorithm. Numerical results validate that proposedWOA outperforms GWO, PSO and existing literature reported for NOMA uplink systems in-terms of spectral performance. In addition, WOA attains improved results in terms of joint user grouping and power control with lower system-complexity when compared toGWOand PSO algorithms. The proposed work is a novel enhancement for 5G uplink applications of NOMA systems.
KW - 5g
KW - Grey wolf optimization
KW - Noma
KW - Particle swarm optimization
KW - Uplink
KW - Whale optimization algorithm
KW - Wireless communication
UR - http://www.scopus.com/inward/record.url?scp=85128278523&partnerID=8YFLogxK
U2 - 10.7717/PEERJ-CS.882
DO - 10.7717/PEERJ-CS.882
M3 - Article
AN - SCOPUS:85128278523
VL - 8
JO - PeerJ Computer Science
JF - PeerJ Computer Science
SN - 2376-5992
M1 - e882
ER -