Result: Equalizer's Use Limitation for Complexity Reduction in a Green Radio Receiver

Title:
Equalizer's Use Limitation for Complexity Reduction in a Green Radio Receiver
Contributors:
Andrieux, Myriam, Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Ecole supérieure des communications de Tunis (SUP'COM TUNIS )
Source:
Journal of Computer Networks and Communications, Vol 2013 (2013)
Publisher Information:
Hindawi Limited, 2013.
Publication Year:
2013
Document Type:
Academic journal Article<br />Other literature type
File Description:
text/xhtml
Language:
English
ISSN:
2090-715X
2090-7141
DOI:
10.1155/2013/794202
DOI:
10.60692/p7ekb-tj056
DOI:
10.60692/kdgc6-hf104
Rights:
CC BY
Accession Number:
edsair.doi.dedup.....e7e34be3839b4c6c49d3c39b6c63a9d2
Database:
OpenAIRE

Further Information

This work is about reducing energy consumption in the receiver chain by limiting the use of the equalizer. It is to make the radio receiver aware of its environment and able to take decision to turn on or off the equalizer according to its necessity or not. When the equalizer is off, the computational complexity is reduced and the rate of reduction depends on the percentage of time during which this component is disabled. In order to achieve this scenario of adapting the use of the equalizer, we need to develop a decision-making technique that provides the receiver with the capacities of awareness and adaptability to the state of its environment. For this, we improve a technique based on a statistical modeling of the environment by defining two metrics as channel quality indicators to evaluate the effect of the intersymbol interferences and the channel fading. The statistical modeling technique allows to take into account the impact of the uncertainties of the estimated metrics on the decision making.