Nature-inspired optimisation algorithms assisted realisation of green communication via CR: <i>a comparison study</i>

作     者：Kaur, Avneet Sharma, Surbhi Mishra, Amit 

作者机构：Thapar Inst Engn & Technol Dept Elect & Commun Engn Patiala Punjab India 

出 版 物：《IET COMMUNICATIONS》 (IET通信)

年 卷 期：2018年第12卷第19期

页      面：2511-2520页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

主　　题：cognitive radio power consumption optimisation quality of service telecommunication power management radiofrequency power amplifiers parameter adaptation multicarrier CR system nature-inspired optimisation algorithms green communication cognitive radio transmission parameters green radios energy efficiency wireless communication systems power amplifier radio-frequency circuits long-range transmissions total system power consumption CR transmitter parameter reconfiguration data transmission scenario ant lion optimiser grasshopper optimisation algorithm Grey wolf optimiser Moth-flame optimisation Whale optimisation algorithm performance metrics QoS constraints CR technology quality of service PA power consumption minimization mathematical formulation class B PA 

摘      要：Cognitive radio (CR) technology enables adaptation of transmission parameters according to the operating environment and different quality of service (QoS) requirements. This feature can be applied to realise green radios as recent research trends are focused on improving the energy efficiency of wireless communication systems. A power amplifier (PA) is found to consume a major portion of energy in radio-frequency circuits for medium- and long-range transmissions. Thus, minimising PA power consumption is one of the major challenges to realise green radios. In this study, mathematical formulation of total system power consumption at CR transmitter with Class B PA is shown and its optimisation is done by parameter reconfiguration for data transmission scenario employing recently proposed nature-inspired optimisation techniques. Performance of ant lion optimiser, grasshopper optimisation algorithm, Grey wolf optimiser, Moth-flame optimisation and Whale optimisation algorithm (WOA) is compared for solving this problem in terms of different performance metrics. Simulation results show the effectiveness of WOA in minimising the system power consumption by parameter adaptation in multicarrier CR system while satisfying different QoS constraints.