1 overview of research areas and contributions tareq y. al-naffouri director office of cooperation...
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1
Overview of Research Areas and Contributions
Tareq Y. Al-Naffouri
Director
Office of Cooperation with KAUST
Assistant Professor
Electrical Engineering
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Major Milestones
• PhD (Stanford), Jan. 2005
• Assistant Prof. (KFUPM), May 2005
• Two month summer visit (Cal Tech), Summer 2006
• Fulbright Scholar (USC), Feb-Aug. 2008
• Director of Cooperation with KAUST Office, Nov. 2008
• Applied to Assoc. Prof., Jan. 10th 2009
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9Research Area Collaborations
Adaptive signal processing Two Brazilian Universities
Statistical signal processing USC
Wireless communications U. of Texas at Dallas
Information Theory Cal Tech
Random Matrix Theory SUPELEC, France
Seismic Signal Processing SchlumbergerGeophysics Dept. (KFUPM)
During
PhD
Research Areas and Collaborations
After
joining
KFUPM
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An Analogy
Spanish
French
German
Training Useful Instruction
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This happens every semester
Spanish
French
German
Portuguese
Russian
Greek
First Semester Second Semester
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How can we reduce the training over
Spanish
French
German
Portuguese
Russian
Greek
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Digital Communication Scenario
• Receiver needs to know the communication medium to recover the transmitted data reliably
• Some of transmission time sacrificed for the sake of training
Training Useful Transmission
0 1 0 0 1 1 …0 1 0 0 1 1 …
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Multiple Transmit Antennas
• With multiple antennas, we can transmit more data
• … But then more training is needed
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Problem Compounded by Mobility
• With mobility, we need to train more often as the medium keeps changing
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How to reduce the training overhead
• Utilize correlation/similarities between different channels, e.g.
1. Spacing between antennas2. Speed of car
• The more similarities used the lower the training needed
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Figure shows error rate comparison between our algorithm and best algorithm known in literature
� State of the art
performance
� Our algorithm
Around 5 dB gain in performance
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Our contributions
• Identified and utilized all possible dimensions (seven) of similarity to reduce training overhead
• Training done in a transparent manner using a dynamic program
“Forward Backward Kalman Filter” • Research resulted in
1. 2 Master Theses2. 2 IEEE papers3. 2 top European Journal papers4. Book Chapter5. Patent (pending)
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Combating Impulsive Noise in DSL
• Impulsive noise is a rare phenomenon
• But when it occurs it destroys the transmitted signal completely
• Caused by bursty disturbances
• Car ignition• Telephone Network switching• A vacuum cleaner
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Typical DSL Signal + Impulsive Noise
• Impulse prob: 3x10^-3
• Impossible to differentiate signal from Imp. Noise
• Can not simply combat noise by clipping
• Result is a punctured signal
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Noise Estimation and Cancellation
Time Domain
Air Domain
Immerse tire in water;
Locate & eliminate
puncture
Water Domain
Freq Domain
Transmission
Band
(signal + noise)Guard
Band
Guard
Band
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� No impulsive noise
Estimate/Remove
Predict presence
of noise
Puncture
Impulse probability
Rate
Around 35% increase in rate
Effective Tech. for Combating Impulsive Noise
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Our Contributions
• Work used an emerging technique for identifying sparse phenomena from few observations
• Work done jointly with a Prof. at USC• Research resulted in
1. M.S. Thesis (in progress)2. 2 IEEE papers (in progress)3. Pending patent
• Working on establishing a research group for estimation of sparse phenomena
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Multi-user Information Theory
Math
Engl.
K subjects
N students
M Professors Phys.
Mgt.
The larger the number of students, the more difficult it is
to cover the material properly
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Broadcasting to Groups of Users
Cartoon
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Assume there are • K TV/Radio channels• N users• M Transmitters
What is the information rate that can received reliably?
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• How can we maintain a constant rate with increasing no. of users?
Increase the number of Antennas
• How much should the number of antennas grow to maintain a constant rate?
and you should not grow at any lower rate
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Our Contributions
• Study is first of its kind; researchers in past focused on independent users
• Study done jointly with researchers at Cal Tech • Research resulted in
1. M.S. Thesis (in progress)2. 2 IEEE papers3. European Journal paper
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Research Time-Line
Year 2006 2007 2008 2009 2010
Proj.Junior Proj.
Uni. Proj 1 Uni Proj 2
SABIC ProjKACST Proj.Seismic Consrt
SABIC Proj.Uni Proj
CLBRCal TechU of TX
Schlumberger USC (Flbright)SUPELEC.Brzl. U. 1
Brzl. U. 2
Grads 2 Grads in 2 Grads out2 Grads in
1 Grad out1 Grad in
2 Grads out
JrnlsIEEE Jrnl. IEEE Jrnl.
1 Eurp JrnlBook Ch.
3 IEEE Jrnl.3 Eurp. Jrnl3 Patents
4 IEEE Jrnl1 Eurp Jrnl
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Thank You
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How to Reduce the Training Period?
Spanish
French
German
Portuguese
Russian
Greek
Use similarities and correlations between the various languages to
reduce the training period