Recent development in reconfigurable dielectric resonator antenna and microwave filter: design and application

被引:5
作者
Rai, Jayant Kumar [1 ]
Ranjan, Pinku [1 ]
Chowdhury, Rakesh [1 ]
机构
[1] ABV Indian Inst Informat Technol & Management, Dept Elect & Elect Engn, Gwalior, India
关键词
cognitive radio (CR); dielectric resonator antenna (DRA); filter; machine learning; PIN diode; reconfigurable antennavaractor diode; TUNABLE BANDPASS FILTER; WIDE-BAND; COGNITIVE RADIO; TUNING RANGE; COMPACT FREQUENCY; PATCH ANTENNA; BANDWIDTH; MIMO; PATTERN; REJECTION;
D O I
10.1002/dac.5859
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Developing wireless communication systems depends on reconfigurable microwave filters (MF) and dielectric resonator antenna (DRA) because the functionality of the various filters and antennas available for a wireless communication system is limited, and reconfigurable DRA and MF are utilized to overcome these limitations. The throughput of a multiantenna system can be achieved with reconfigurable DRA and filter. Various switching strategies and classifications of reconfigurable DRA and MF are presented. The electrical reconfiguration technique is most suitable for developing a reconfigurable DRA and filter among all the switching techniques. In this approach, reconfigurability may be accomplished by utilizing a PIN diode, a varactor diode, and a radio-frequency microelectromechanical switch (RF-MEMS). These switches are more reliable, highly efficient, and easily integrated with the microwave circuit. Reconfigurable DRA with machine learning is demonstrated. The application of reconfigurable DRA and filters in cognitive radio (CR) is also demonstrated. Also, the review article focused on the performance parameters, design, and challenges of reconfigurable antenna and MF. The recent design of reconfigurable dielectric resonator antenna (DRA) and microwave filter (MF) with merit and demerit are discussed. The classification of reconfigurable antenna, various reconfigurable techniques, performance parameters, and challenges in reconfigurable DRA and MF are also discussed. Reconfigurable DRA with machine learning (ML) is discussed, and demonstrated with published work. Application of reconfigurable DRA and MF in cognitive radio (CR) is discussed. image
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页数:24
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