TY - JOUR
T1 - Joint Spectrum and Energy Optimization of NOMA-Enabled Small-Cell Networks with QoS Guarantee
AU - Khan, Wali Ullah
AU - Jameel, Furqan
AU - Li, Xingwang
AU - Bilal, Muhammad
AU - Tsiftsis, Theodoros A.
N1 - Funding Information:
Manuscript received October 22, 2020; revised March 6, 2021; accepted June 29, 2021. Date of publication July 9, 2021; date of current version August 13, 2021. The work was supported in part by the Henan Scientific and Technological Research Project under Grant 212102210557, in part by the Key Scientific Research Projects of Higher Education Institutions in Henan Province under Grant 20A510007, in part by the Outstanding Youth Science Foundation of Henan Polytechnic University under Grant J2019-4, in part by the Natural Science Foundation of China under Grant 61901367 and 62001320. The review of this article was coordinated by Prof. Yi-Bing Lin. (Corresponding author: Xingwang Li.) Wali Ullah Khan is with the Interdisciplinary Centre for Security, Reliability, and Trust (SnT)/ SigCom, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg (e-mail: waliullahkhan30@gmail.com).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2021/8
Y1 - 2021/8
N2 - In recent years, wireless communication has experienced a massive shift from a single service (i.e., voice) to an interconnected web of networks. Although many techniques have been developed improving the offered services to mobile users, still the demand for high-quality services cannot be reached. Therefore, this paper proposes a joint non-orthogonal multiple access (NOMA)-enabled optimization framework for small-cell network (SCNet) by utilizing the concepts of multi-objective problem. In particular, the transmit power of base station (BS) in each small-cell simultaneously optimizes to maximize the sum-capacity and total energy efficiency (EE) of SCNet. The multi-objective optimization problem is formulated as non-convex subject to several practical constraints, i.e., individual quality of service requirement, maximum power budget of small-cell BS, and efficient decoding of superimposed signal using successive interference cancellation. Based on the nature of the problem, the optimal solutions are provided using sequential quadratic programming, and Karush-Kuhn-Tucker approaches. The obtained results show significant performance gains over conventional orthogonal multiple access technique in terms of sum-capacity and total EE.
AB - In recent years, wireless communication has experienced a massive shift from a single service (i.e., voice) to an interconnected web of networks. Although many techniques have been developed improving the offered services to mobile users, still the demand for high-quality services cannot be reached. Therefore, this paper proposes a joint non-orthogonal multiple access (NOMA)-enabled optimization framework for small-cell network (SCNet) by utilizing the concepts of multi-objective problem. In particular, the transmit power of base station (BS) in each small-cell simultaneously optimizes to maximize the sum-capacity and total energy efficiency (EE) of SCNet. The multi-objective optimization problem is formulated as non-convex subject to several practical constraints, i.e., individual quality of service requirement, maximum power budget of small-cell BS, and efficient decoding of superimposed signal using successive interference cancellation. Based on the nature of the problem, the optimal solutions are provided using sequential quadratic programming, and Karush-Kuhn-Tucker approaches. The obtained results show significant performance gains over conventional orthogonal multiple access technique in terms of sum-capacity and total EE.
KW - Multi-objective optimization
KW - non-orthogonal multiple access
KW - sequential quadratic programing
UR - http://www.scopus.com/inward/record.url?scp=85113709200&partnerID=8YFLogxK
U2 - 10.1109/TVT.2021.3095955
DO - 10.1109/TVT.2021.3095955
M3 - Article
AN - SCOPUS:85113709200
VL - 70
SP - 8337
EP - 8342
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
SN - 0018-9545
IS - 8
M1 - 9479745
ER -