Accessibility navigation

MIMO channel capacity using convariance matrix and configuration selection for switched parasitic antennas

Pal, P. K. (2018) MIMO channel capacity using convariance matrix and configuration selection for switched parasitic antennas. PhD thesis, University of Reading

Text - Thesis
· Please see our End User Agreement before downloading.

[img] Text - Thesis Deposit Form
· Restricted to Repository staff only


It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.48683/1926.00084395


Multiple-Input Multiple-Output (MIMO) is considered a promising technology to increase the channel capacity and link reliability for future wireless communication systems. The benefits of MIMO can be obtained by placing the antenna terminals far apart to provide uncorrelated signals at the receiver. Reducing the inter-element spacing between the antenna terminals causes signal correlation and mutual coupling that degrade the system performance. However, implementation of MIMO technology is not possible when considering low-cost, battery operated portable devices with limited physical space constraint. The key idea of this thesis is focused on the performance of MIMO with switched parasitic antennas (SPA), in which parasitic elements are switched between terminated impedance loads. MIMO-SPA exploits the pattern diversity by changing the mutual coupling between the antenna array elements. It exploits the electromagnetic field to a greater extent and provides different radiation patterns. The switching operation of parasitic elements changes the current distribution on the antenna array elements and alters the radiation patterns. With the availability of multiple channel realizations, it is possible to select the optimal pattern configuration for a particular propagation environment. The research work in this thesis consists of three parts: The first part of the thesis focuses on the design and analysis of MIMO-SPA, including the channel characteristics and antenna properties. MIMO-SPA consists of active elements connected to RF hardware and surrounded with a number of parasitic elements terminated with controllable loads. The use of parasitic elements exploits the pattern diversity by changing the electromagnetic mutual coupling between the antenna elements. The parasitic element switches between reflector and director states by controlling the terminated loads electronically. The second part of this thesis shows the performance of MIMO-SPA in terms of channel capacity for different loading configurations. Simulation results prove that the proposed MIMO-SPA approach provides comparable results to conventional MIMO systems with reduced size and hardware complexity. The channel capacity further improves using a modified covariance matrix with the incremental antenna selection technique (IAST) and the water-pouring algorithm (WPA) technique. The improved covariance matrix with the optimal power allocation shows significant improvement over uniformly distributing the power among aUthe transmit antennas. The MIMO-SPA system is capable of operating under multiple radiation patterns with multiple channel realizations. This additional degree of freedom (DoF) comes with an overhead of attaining channel state information (CSI) of all the pattern configurations. This channel knowledge should be sent back to the transmitter through a limited feedback link. Lastly, the third part of the thesis proposes a novel selection method using condition number to select optimal pattern configuration. A condition number indicates the multipath richness present in the channel. This channel quality information can be sent back to the transmitter with a low-rate feedback link. The condition number suggests how much S R is required by the system for proper transmission.

Item Type:Thesis (PhD)
Thesis Supervisor:Sherratt, S.
Thesis/Report Department:School of Biological Sciences
Identification Number/DOI:
Divisions:Life Sciences > School of Biological Sciences
ID Code:84395


Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation