Rabah Maoudj

Reduced rank spatial filter for interference cancellation

In radio mobile communication, antenna array structure at the reception is used to perform interference cancellation and equalization. We introduce a reception structure where a spatial filter is split between a set of coefficients applied to received signals and a set of coefficients applied to reference signal (pilots symbols). Instead of trying to find this set of filter coefficients, the approach is based, for rank reduction reasons, on the projection of these coefficients on a discrete Fourier basis. In order to avoid a trivial solution, two constraints on filter coefficients are proposed, related algorithms are developed and simulation results are compared. This paper can be viewed as a follow up of a previous work on a similar topic [1].

4 th order statistics based blind channel estimation for multicarrier transmission

This paper presents a blind channel estimation algorithm for multicarrier systems. The proposed scheme is based on fourth order statistics estimation of received data followed by a Gauss linearization of a non-linear system. The channel estimation is performed over a very short number of symbols in order to stay compliant with the channel coherence time. The proposed approach is well suited to CP-OFDM system transmitting circular M-QAM communication symbols but, being not based on the cyclic prefix properties, it could be applied, with some adjustments, to filterbank multicarrier waveforms transmitting M-OQAM communication symbols. The blind algorithm presented provides finally an increase of the useful throughput and it gives a high flexibility for the waveform usage, avoiding the difficult time and frequency pilot location optimization problem.

DSP implementation of interference cancellation algorithm for a SIMO system

This paper presents an implementation on the fixed-point DSP chip of an interference cancellation algorithm containing a linear system. Difficulty in matching the algorithms performance obtained in full precision (IEEE float-point) implementation to those given by a finite precision tends to increase when the algorithms contains one or several linear system to solve. Gauss and Cholesky methods are implemented. Their performance results are showed and compared. The global implementation margins are discussed.

Blind propagation channel estimation with enhanced auto-deconvolution

This paper deals with blind propagation channel estimation that should be a key feature for future agile waveforms. The proposed approach is based on high order statistics, inverse Fourier Transform and auto-deconvolution. The paper can be seen as a follow up to a previous work devoted to this subject [10]. It introduces an important improvement in the auto-deconvolution step based on a whitening algorithm able to equalize additive noise corrupting high order statistical moments estimation. Simulations results highlight the significance of this new stage, showing its impact, not only on the mean square error, but also on the bit error rate for 4 to 64-QAM modulations.

Constant Modulus Algorithm based on fourth order moments initialization

In this paper we introduce an adapted Constant Modulus Algorithm in order to identify the impulse response of an unknown propagation channel. This algorithm deals with the output of a fourth order moment estimation algorithm of received samples. This paper can be viewed as a follow up of a previous work devoted on blind channel estimation. It will be shown how results obtained in this previous work can be used as an initialization of the proposed adapted CMA, leading to a subsequent performances improvement.

Blind channel estimation and interference management in MIMO-OFDM uplink communication

This paper addresses two majors problems in todays wireless network using MIMO-OFDM. In fact, the performances of such a network depend on the interference management and on the equalization. These two problems are closely linked to channel estimation algorithms. In this paper, we propose a resource sharing scenario combined with a blind channel estimation algorithm based on fourth order statistics of the received signal. The proposed scheme is compared to the existing T/OFDM scenario and simulation results show its outperformance.

Self-adjustment channel rank based on reordered cholesky factorization

This paper presents a self-adjustment of the length of the channel impulse response using a classical Cholesky Factorization. This is of special importance in the context of algorithms containing a matrix inversion and the rank of this matrix is strongly related to the length of the channel impulse, i.e. interferer cancellation algorithm [1]. When the length of the channel impulse response is overestimated, the matrix inversion is carried out with a singular matrix. A self-adjustment is then required to avoid an increase in the noise level.