Jabeur T.B.,University of Paris Descartes |
Abed-Meraim K.,Telecom ParisTech |
Physical Communication | Year: 2012
In OFDM systems, the Inter-Symbol Interference (ISI) and the Inter-Block Interference (IBI) are mitigated by using Null-Tones (NTs) and the Guard Interval (GI) redundancy of length higher than the channel size. To preserve a high bit rate, channel shortening is required to reduce the GI length. We propose here a new adaptive method for the blind estimation of the Time domain EQualizer (TEQ) for time varying communication channels. Our contribution is three-fold. First, we exploit the knowledge of the first emitted symbol in a differential encoded OFDM system to derive the initial estimate of the TEQ. Then, we update the TEQ coefficients according to the channel variation by optimizing a criterion exploiting both the GI and NT redundancies and using a fast Generalized Eigen Value (GEV) tracking algorithm. Finally, the optimization of the previous criterion is achieved in such a way we control the Target Impulse Response (TIR) quality and we improve the overall system performance. Simulation results are provided to illustrate the performance of our method and assess our theoretical derivations. © 2011 Elsevier B.V.
Kaaniche M.,Telecom ParisTech |
Pesquet J.-C.,University Paris Est Creteil |
Benazza-Benyahia A.,SupCom |
Pesquet-Popescu B.,Telecom ParisTech
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2010
Many existing works related to lossy-to-lossless image compression are based on the lifting concept. However, it has been observed that the separable lifting scheme structure presents some limitations because of the separable processing performed along the image lines and columns. In this paper, we propose to use a 2D non separable lifting scheme decomposition that enables progressive reconstruction and exact decoding of images. More precisely, we focus on the optimization of all the involved decomposition operators. In this respect, we design the prediction filters by minimizing the variance of the detail signals. Concerning the update filters, we propose a new optimization criterion which aims at reducing the inherent aliasing artefacts. Simulations carried out on still and stereo images show the benefits which can be drawn from the proposed optimization of the lifting operators. ©2010 IEEE.
Annales des Telecommunications/Annals of Telecommunications | Year: 2015
In this paper, we investigate throughput and delay enhancement for two multi-user multiple-input multiple-output (MIMO) systems one with space-time block coding (STBC), the other with spatial multiplexing (SM) at the transmitter. Users operate using the slotted ALOHA (SA) protocol to access the wireless channel resulting in a high probability of collision. For both systems, we consider the uplink scenario, and we propose to recover the collided packets with spatial successive interference cancelation (SSIC) and a protocol for retransmission and combining of unsuccessfully received collided packets applying a truncated Hybrid Automatic Repeat reQuest (HARQ) scheme. For the first system, we propose to use channel realizations of collided packets as different signatures to separate them. Moreover, we propose a solution for the problem when the received powers are comparable. For this system, we note that the orthogonality of the STBC matrix allows the use of a simple linear processing step for the initialization of SSIC. For the SM multi-user system, the separation of collided packets is based on V-BLAST processing and SSIC. We also propose how to combine retransmitted packets. For both systems, we evaluate the block error rate, the throughput, and the delay. A comparison is done with the single-user case and with other receivers proposed in the literature. © 2015 Institut Mines-Télécom and Springer-Verlag France
Ben Jebara S.,SupCom |
Besbes H.,Concordia University at Montreal |
Jaidane M.,Campus University
European Signal Processing Conference | Year: 2015
This paper deals with the use of adaptive predictive algorithms in order to improve tracking performances of classical identification scheme. The performances of coupled structure depend on the prediction device. In this paper, we present a new robust algorithm for the predictive scheme. The robustness deals with insensibility of proposed algorithm to the input statistics variations, namely the power and fourth order statistics. We illustrate our contribution by performances evaluation of the proposed structure in double non stationary context: on tracking random walk channel with speech input signal. © 2000 EUSIPCO.
Ayadi R.,SupCom |
Kammoun I.,University of Sfax |
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC | Year: 2013
This paper investigates space-frequency (SF) coding for non-coherent (NC) Multiple Input Multiple Output (MIMO)-Orthogonal Frequency Division Multiplexing (OFDM) fading links, where neither the transmitter nor the receiver knows the channel. Our strategy consists in distributing the convolutional encoded and interleaved bits over the different transmit antennas, OFDM tones and OFDM symbols. The combination of the convolutional coding and bit interleaving with the SF coding can exploit the maximum spatial/frequency diversity over frequency-selective channels. In order to reduce the decoding complexity, we divide the OFDM symbol into several groups and apply differential encoding and decoding between adjacent groups. The proposed NC SF matrix is designed as a combination of a differential Cayley code and a systematic NC SF code, which leads to a simple decoding rule over the multipath channel. We show through asymptotic Pairwise Error Probability (PEP) analysis and simulation results that our encoding strategy can provide full diversity gain and achieves better performance in terms of spectrum efficiency and symbol error rate than all three the systematic NC-SF coding, the Cayley differential SF coding and our proposed SF coding without convolutional encoding and bit interleaving. © 2013 IEEE.