Abstract
This paper proposes a system EE (energy efficiency) optimization algorithm based on OPS (On-off Power Splitting) strategy for SWIPT (Simultaneous Wireless Information and Power Transfer) two-way relay assisted CR-NOMA (Cognitive Radio Non-Orthogonal Multiple Access) network. The system capacity expression of the secondary users with the OPS strategy is derived. Under the constraints of harvested energy and quality of service (QoS) of the users, the optimization problem with the goal of maximizing energy efficiency is constructed. In this paper, the NP-Hard problem is transformed into three subproblems about relay power, NOMA coefficient, and segmentation coefficient, which are solved by golden section algorithm, monotonicity decision function, and genetic algorithm. The simulation results show that compared with the PS (Power Splitting) and TS (Time Switching) strategies, the OPS strategy can significantly improve the transmission energy efficiency of the system.
Highlights
Research ArticleReceived 7 December 2019; Revised 16 May 2020; Accepted 1 June 2020; Published 29 June 2020
Devices in energy-constrained wireless communication systems, such as wireless sensor networks, wireless positioning networks, and the Internet of ings are mostly battery-powered, and the limitations of battery-powered capacity and inconvenient replacement greatly limit the performance of the system [1]
Hedayati and Kim [12] aimed at the joint power allocation problem in the SWIPTNOMA system based on the TS strategy and proposed an energy efficiency optimization algorithm that satisfies the requirements of transmit power limit, harvested energy, and quality of service
Summary
Received 7 December 2019; Revised 16 May 2020; Accepted 1 June 2020; Published 29 June 2020. Is paper proposes a system EE (energy efficiency) optimization algorithm based on OPS (On-off Power Splitting) strategy for SWIPT (Simultaneous Wireless Information and Power Transfer) two-way relay assisted CR-NOMA (Cognitive Radio NonOrthogonal Multiple Access) network. E system capacity expression of the secondary users with the OPS strategy is derived. Under the constraints of harvested energy and quality of service (QoS) of the users, the optimization problem with the goal of maximizing energy efficiency is constructed. The NP-Hard problem is transformed into three subproblems about relay power, NOMA coefficient, and segmentation coefficient, which are solved by golden section algorithm, monotonicity decision function, and genetic algorithm. E simulation results show that compared with the PS (Power Splitting) and TS (Time Switching) strategies, the OPS strategy can significantly improve the transmission energy efficiency of the system The NP-Hard problem is transformed into three subproblems about relay power, NOMA coefficient, and segmentation coefficient, which are solved by golden section algorithm, monotonicity decision function, and genetic algorithm. e simulation results show that compared with the PS (Power Splitting) and TS (Time Switching) strategies, the OPS strategy can significantly improve the transmission energy efficiency of the system
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