Clustered ML Channel Estimation for Ultra-Wideband Signals

The multipath capture of ultrawideband (UWB) communications systems can be dependent on the accuracy of channel estimation. Furthermore, inefficient modeling of the channel often leads to over-parametrization and increased channel estimation error. Relying on a channel model based on clusters, this...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on wireless communications 2007-07, Vol.6 (7), p.2412-2416
Main Authors: Carbonelli, C., Mitra, U.
Format: Article
Language:English
Subjects:
Applied sciences
Bit error rate
Channel estimation
Channels
Clustering algorithms
Communication systems
Delay estimation
Distortion
Exact sciences and technology
Fading
Maximum likelihood estimation
Multipath channels
Noise levels
RAKE receivers
Robustness
Strategy
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
Ultra wideband technology
Ultrawideband
Wireless communication
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The multipath capture of ultrawideband (UWB) communications systems can be dependent on the accuracy of channel estimation. Furthermore, inefficient modeling of the channel often leads to over-parametrization and increased channel estimation error. Relying on a channel model based on clusters, this letter proposes a maximum likelihood estimation strategy which exploits the properties of the UWB channel and offers performance improvement of about 2 dB over less parametric schemes. The robustness of the proposed algorithm in the presence of pulse distortion is investigated and the corresponding BER degradation is observed to be small even when experimental data are employed.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2007.051006