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31 octobre 2018

Quality improvement of the transmitted video in 802.11n wireless communications system

Catégorie : Stagiaire

Master's internship

Duration : 6 months.
Location : Laboratoire de Traitement et de Transport de l’Information.

Required skills:
- Initial training in digital communications and video coding.\\
- Good programming skills in Matlab, C+++ language.

Key words :
- SISO-OFDM, SIMO-OFDM, channel estimation, semi-blind Channel estimation, optimization.

Supervisors :
B. Matei (LIPN); A. Mokraoui (L2TI).

Contact : A. Mokraoui (anissa.mokraoui@univ-paris13.fr)

Brief description of the subject:

In most wireless communications system, channel estimation is a crucial operation since it
is required for equalization and symbol detection. Several solutions have been developed
and can be divided into three main classes: (i) blind (using only unknown data) [1], [2] ;
(ii) pilot-based [3] consuming not only a large part of the throughput but also signi cant
power resources; and (iii) semi-blind methods using both training sequences and unknown
data [4], [5].

This internship focuses on pilot-based and semi-blind channel estimation algorithms
for SISO-OFDM communications system based on Time-Of-Arrival estimation. The objective
is to show the impact of these algorithms on the quality of the transmitted video
in a realistic context. The work is organized as follows. The rst part concerns the implementation
of Decision Feedback Semi-Blind (DFSM) channel estimation and pilot-based
algorithms. The second part adresses the theoretical extension of the DFSM algorithm to
the Single-Input Multiple-Output (SIMO-OFDM) communications systems.


[1] K. Abed-Meraim, W. Qiu, and Y. Hua, Blind system identification," Proceedings of the
IEEE, vol. 85, no. 8, pp. 1310-1322, Aug 1997.
[2] C. Shin, R. W. Heath, and E. J. Powers, Blind channel estimation for MIMO-OFDM
systems," IEEE Trans. on Vehicular Technology, vol. 56, no. 2, pp. 670-685, March 2007.
[3] O. Simeone, Y. Bar-Ness, and U. Spagnolini, \Pilot-based channel estimation for OFDM
systems by tracking the delay-subspace," IEEE Trans. on Wireless Communications, vol. 3,
no. 1, pp. 315-325, Jan 2004.
[4] W. Yang, Y. Cai, and Y. Xun, \Semi-blind channel estimation for OFDM systems," in IEEE
63rd Vehicular Technology Conference, vol. 1, May 2006, pp. 226-230.
[5] A. Ladaycia, A. Belouchrani, K. Abed-Meraim, and A. Mokraoui, \EM-based semi-blind
MIMO-OFDM channel estimation," in 2018 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP), April 2018, pp. 3899-3903.

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