Adaptive Modulation Systems for Predicted Wireless Channels.
Chalmers U. of Technology,
Uppsala University and
7th Wireless World Research Forum Workshop
Eindhoven, the Netherlands, Dec 2002.
The Wireless IP project within the PCC program studies
problems that are crucial in the evolution of UMTS towards high
data rates, as well as in future 4G technologies aimed at
rapidly mobile terminals. The goal is to attain higher
througputs for packet data in particular in downlinks,
without bandwidth expansion and while providing acceptable
quality of service for various classes of traffic.
When adaptive modulation is used to counter short-term
fading in mobile radio channels,
signaling delays create problems with outdated channel
state information. The use of channel power prediction
will improve the performance of the link adaptation.
It is then of interest to take the quality of these
predictions into account explicitly when designing
an adaptive modulation scheme.
We study the optimum design of an adaptive modulation
scheme based on M-QAM modulation assisted by
channel prediction for the flat Rayleigh fading channel.
The data rate and in some variants
transmit power are adaptedto maximize
the spectral efficiency, subject to average power and
bit error rate constraints.
The key issues studied here are how a known prediction error
variance will affect the optimized transmission properties
such as the SNR boundaries that determine when to apply
different modulation rules, and to what extent it affects the
This investigation is performed by analytical optimization
of the link adaptation, using the statistical properties of a
particular but efficient channel power predictor.
Optimum solutions for the rate and transmit power
are derived based on the predicted SNR and the
prediction error variance.
The analytical result are evaluated and presented.
(IEEE TCOM 2004).
Proc. of the IEEE (Dec. 2007)
invited paper on
adaptive transmission in beyond-3G wireless systems.
PhD Thesis on channel prediction
by Torbjörn Ekman, Oct. 2002.
Licenciate Thesis by Sorour Falahati, Feb. 2000.
- VTC02-fall paper
on channel prediction over 0.1-0.8 wavelengths.
A system proposal
in which predictive adaptive modulation is used (RVK02).
An overview of the Wireless IP Project,
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