Multi-Objective Resource Allocation in a NOMA Cognitive Radio Network With a Practical Non-Linear Energy Harvesting Model | Zendy

Yuhao Wang | Zendy; Yuhang Wu | Zendy; Fuhui Zhou | Zendy; Zheng Chu | Zendy; Yongpeng Wu | Zendy; Fei Yuan | Zendy

Open Access

Multi-Objective Resource Allocation in a NOMA Cognitive Radio Network With a Practical Non-Linear Energy Harvesting Model

Author(s) -

Yuhao Wang,

Yuhang Wu,

Fuhui Zhou,

Zheng Chu,

Yongpeng Wu,

Fei Yuan

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2783880

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Cognitive radio and non-orthogonal multiple access are promising for alleviating the severe spectral scarcity problem encountered by the next generation wireless communication systems. In this paper, in order to improve energy efficiency and spectral efficiency, a non-orthogonal multiple access cognitive radio network with simultaneous wireless information and power transfer is studied under a practical non-linear energy harvesting model. A multi-objective resource optimization problem is formulated for maximizing the harvesting power of each energy harvesting receiver. This problem is non-convex and challenging to solve. A weighted Tchebycheff method is applied to solve the formulated problem. It is shown that the performance achieved under the non-linear energy harvesting model is better than that obtained under the linear energy harvesting model.

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