TY - JOUR
T1 - Joint energy efficient subchannel and power optimization for a downlink NOMA heterogeneous network
AU - Fang, F.
AU - Cheng, Julian
AU - Ding, Zhiguo
N1 - Funding Information:
Manuscript received March 21, 2018; revised August 14, 2018; accepted October 11, 2018. Date of publication November 14, 2018; date of current version February 12, 2019. The work of Z. Ding was supported in part by the UK EPSRC under Grant EP/P009719/2 and in part by H2020-MSCA-RISE-2015 under Grant 690750. The review of this paper was coordinated by Prof. W. Song. (Corresponding author: Fang Fang.) F. Fang and Z. Ding are with the School of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, U.K. (e-mail:, [email protected]; [email protected]).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - Non-orthogonal multiple access (NOMA) has been considered as a key technology in the fifth-generation mobile communication networks due to its superior spectrum efficiency. Since the heterogeneous network has been emerged to satisfy users' explosive data rate requirements and large connectivity of mobile Internet, implementing NOMA policy in heterogeneous networks (HetNets) has become an inevitable trend to enhance the 5G system throughput and spectrum efficiency. In this paper, we aim to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation. By considering the co-channel interference and cross-tier interference, the energy efficient resource allocation problem is formulated as a mixed integer nonconvex optimization problem. It is challenging to obtain the optimal solution; therefore, a suboptimal algorithm is proposed to alternatively optimize the macrocell and the small cells resource allocation. Specifically, convex relaxation and dual-decomposition techniques are exploited to optimize the subchannel allocation and power allocation. Moreover, optimal closed-form power allocation expressions are derived for small cell and macrocell user equipments by the Lagrangian approach. Simulations results show that the proposed algorithms can converge within ten iterations and can also attain higher system energy efficiency than the reference schemes.
AB - Non-orthogonal multiple access (NOMA) has been considered as a key technology in the fifth-generation mobile communication networks due to its superior spectrum efficiency. Since the heterogeneous network has been emerged to satisfy users' explosive data rate requirements and large connectivity of mobile Internet, implementing NOMA policy in heterogeneous networks (HetNets) has become an inevitable trend to enhance the 5G system throughput and spectrum efficiency. In this paper, we aim to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation. By considering the co-channel interference and cross-tier interference, the energy efficient resource allocation problem is formulated as a mixed integer nonconvex optimization problem. It is challenging to obtain the optimal solution; therefore, a suboptimal algorithm is proposed to alternatively optimize the macrocell and the small cells resource allocation. Specifically, convex relaxation and dual-decomposition techniques are exploited to optimize the subchannel allocation and power allocation. Moreover, optimal closed-form power allocation expressions are derived for small cell and macrocell user equipments by the Lagrangian approach. Simulations results show that the proposed algorithms can converge within ten iterations and can also attain higher system energy efficiency than the reference schemes.
KW - downlink
KW - Energy efficient
KW - heterogeneous networks
KW - NOMA
KW - optimization
UR - http://www.scopus.com/inward/record.url?scp=85056601794&partnerID=8YFLogxK
U2 - 10.1109/TVT.2018.2881314
DO - 10.1109/TVT.2018.2881314
M3 - Article
AN - SCOPUS:85056601794
SN - 0018-9545
VL - 68
SP - 1351
EP - 1364
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 2
M1 - 8534441
ER -