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Performance Investigation and Implementation of a Real-Time Adaptive MIMO-DFE System

Ming, Jengis Lo and McLoughlin, Ian (2006) Performance Investigation and Implementation of a Real-Time Adaptive MIMO-DFE System. In: 2006 10th IEEE Singapore International Conference on Communication Systems. IEEE, pp. 1-5. ISBN 1-4244-0410-X. (doi:10.1109/ICCS.2006.301367) (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:48812)

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/ICCS.2006.301367

Abstract

This paper presents the performance investigation and FPGA implementation aspects of a real-time adaptive MIMO DFE system. MIMO communication systems have been a strong research topic for several years because of spectral efficiency advantages, and are starting to see adoption in real-time communication systems. The group research department in Tait Electronics has a reconfigurable platform for MIMO research. In particular, the platform has an adaptive multivariate DFE, utilizing LMS, currently implemented. The LMS algorithm has been simulated and optimized for implementation on the FPGA. The main objective of the paper is to present the investigative work for an alternative RLS algorithm by comparing its performance and implementation to the LMS algorithm. RLS is known to be more complex but offers a potentially faster convergence speed. Stability and complexity issues are also discussed.

Item Type: Book section
DOI/Identification number: 10.1109/ICCS.2006.301367
Additional information: Unmapped bibliographic data: Y1 - 2006/11// [EPrints field already has value set]
Uncontrolled keywords: real time systems; adaptive systems; signal processing algorithms; MIMO; least squares approximation; resonance light scattering; decision feedback equalizers; space technology; field programmable gate arrays; adaptive filters
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Ian McLoughlin
Date Deposited: 04 Sep 2015 14:03 UTC
Last Modified: 02 Jan 2024 10:15 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/48812 (The current URI for this page, for reference purposes)

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