Prakash, Shiva, McLoughlin, Ian Vince (2009) Predictive Transmit Antenna Selection with Maximal Ratio Combining. In: Global Telecommunications Conference 2009 GLOBECOM 2009 IEEE. . pp. 1-6. IEEE ISBN 978-1-4244-4148-8. (doi:10.1109/GLOCOM.2009.5425217) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:48897)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1109/GLOCOM.2009.5425217 |
Abstract
Antenna selection has long been a pragmatic method for exploiting spatial diversity in wireless systems with lower complexity than space-time or MIMO coding, and potentially having reduced hardware cost due to the reduction in the number of RF chains required. Whilst receive antenna selection is perhaps more common, transmit antenna selection also has several advantages, particularly for hardware-costly transmit schemes such as those requiring linearisation. However transmit antenna selection (TAS) requires either channel knowledge, or receiver knowledge at the transmitter, typically achieved using data transmission in the reverse direction, and this implies a delay between the channel being sampled and being acted upon. This outdated channel knowledge degrades system performance. In this paper, the degradation is determined, and related to the channel characteristics. A prediction scheme is then applied to mitigate against this degradation for the case of a (2,1;2) TAS system, where one of two transmit antenna is selected to communicate with two receive antennae employing maximal ratio combining.
Item Type: | Conference or workshop item (Paper) |
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DOI/Identification number: | 10.1109/GLOCOM.2009.5425217 |
Uncontrolled keywords: | closed loop systems, diversity reception, fading channels, transmitting antennas, maximal ratio combining, spatial diversity, predictive trasnmit antenna selection |
Subjects: | T Technology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Ian McLoughlin |
Date Deposited: | 07 Sep 2015 12:58 UTC |
Last Modified: | 05 Nov 2024 10:33 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/48897 (The current URI for this page, for reference purposes) |
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