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Journal Article
DNN-based algorithm for joint SIC ordering and power allocation in downlink NOMA-enabled heterogeneous networks
- Authors
- Donghyeon Kim, Jung-Bin Kim, Haejoon Jung, In-Ho Lee
- Issue Date
- 2024-12
- Citation
- ICT EXPRESS, v.10, no.6, pp.1301-1307
- ISSN
- 2405-9595
- Publisher
- ELSEVIER
- Language
- English
- Type
- Journal Article
- Abstract
- In the heterogeneous network (HetNet) employing downlink non-orthogonal multiple access (NOMA), we focus on the non-convex optimization problem to optimize the spectral efficiency (SE) while the users satisfy the quality-of-service (QoS) requirement. In the previous work, the optimal joint successive interference cancellation and power allocation (JSPA) algorithm for maximizing SE is proposed to solve the mixed-integer non-linear programming (MINLP) problem in NOMA-enabled HetNet. However, the optimal solution requires exponential complexity by the number of base stations (BSs). Therefore, we present a deep neural network (DNN)-based algorithm for JSPA to reduce the complexity. In particular, to deal with the MINLP-based JSPA problem, we reformulate it into an equivalently simple problem that optimizes only the power consumption of BSs. Then, we introduce the unsupervised DNN-based method for JSPA to handle the simplified problem. The presented scheme yields improved SE and outage performance compared with traditional DNN-based methods. Additionally, we propose a user selection scheme with low complexity to enhance the SE of the proposed DNN-based power allocation. Through simulations, we illustrate that the suggested DNN-based scheme can attain SE performance similar to that of the optimal scheme.
- KSP Keywords
- Deep neural network(DNN), Low complexity, Mixed-integer non-linear programming(MINLP), Non-convex optimization problems, Nonorthogonal multiple access(NOMA), Optimal Solution, Optimal scheme, Power Consumption, Quality-of-Service(QoS), Spectral efficiency(SE), base station
This work is distributed under the term of Creative Commons License (CCL)
(CC BY NC ND)
(CC BY NC ND)
