A Study on Reconfigurable Antenna Array Feed Networks Using Distributed Switched-Line Phase Shifters for mm-Wave Operation
Lead Research Organisation:
Queen Mary University of London
Department Name: Sch of Electronic Eng & Computer Science
Abstract
The primary aim of the research is to design a passive high-gain planar mm-wave antenna which can be electronically scanned in two dimensions by reconfiguring the array feed network. In addition to this, the research aims to implement a design which could be realised using phase-change materials to minimise the insertion loss and size of a switch-line phase shifter, which is suitable for use in an antenna array feed network (this is fundamental to increasing the operating frequency well into the mm-wave bands). Finally, the research also aims to reduce the complexity of configuring the antenna array by developing a machine learning algorithm to assist with the array design incorporating the switched-line phase
shifters.
The research aims to answer the following questions:
1) What benefits can be offered by distributing phase shifters throughout the array feed network rather than at each individual element?
2) Can phase-change materials facilitate sufficiently low-loss RF switches at mm-wave frequencies suitable for a reconfigurable antenna feed network?
3) Can a machine learning algorithm enable a reduction in the complexity of a large dual-scan array configuration by reducing the number of redundant phase states?
To be updated in January 2024 (at Year 3 Progression)
shifters.
The research aims to answer the following questions:
1) What benefits can be offered by distributing phase shifters throughout the array feed network rather than at each individual element?
2) Can phase-change materials facilitate sufficiently low-loss RF switches at mm-wave frequencies suitable for a reconfigurable antenna feed network?
3) Can a machine learning algorithm enable a reduction in the complexity of a large dual-scan array configuration by reducing the number of redundant phase states?
To be updated in January 2024 (at Year 3 Progression)
People |
ORCID iD |
Y Hao (Primary Supervisor) | |
James Henderson (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/V519935/1 | 30/09/2020 | 29/04/2028 | |||
2496930 | Studentship | EP/V519935/1 | 19/01/2021 | 18/01/2025 | James Henderson |