The concatenation of the multiple-input multiple-output (MIMO) linear precoder with an outer forward error correction (FEC) code at the transmitter is investigated in this paper. At the receiver side, the turbo detection is taken into account. It iteratively exchanges the extrinsic information between a soft-demapper and a FEC soft-decoder. We firstly propose a new precoder named FI1designed from an extrinsic information transfer (EXIT) chart analysis. The proposed precoder aims to optimize the iterative receiver convergence by maximizing the ending point I1of the soft-demapper EXIT function. For the sake of low-complexity, FI1is designed for two data streams MIMO transmission with 4-QAM only. Secondly, to cope with the higher data streams transmission, a global b = 2K data streams system is split into K two data streams subsystems. FI1is then applied at each subsystem. Finally, we propose a new algorithm to optimize the inter-subsystems power allocation by maximizing the I1of the global system.

Precoder optimization with full channel state information for finite alphabet signals over multiple-input multiple-output random channels is investigated in this paper. The precoder is represented by a product of power allocation matrix and constellation-forming matrix. There was an optimal algorithm introduced in the literature to globally maximize the channel mutual information by iteratively optimizing these two matrices. However, the computational complexity of the optimal algorithm is painfully high, especially when it is used with the high-order modulation and the high-data stream number. In this paper, we propose a novel sub-optimal low-complexity precoding algorithm and compare it with the optimal one. The new algorithm proceeds in two steps. First, the constellation-forming matrix is fixed in order to maximize the minimum Euclidean distance between the received symbols, which ensures high channel mutual information. Then, given the constellation-forming matrix, an iterative algorithm searches for the power allocation matrix that maximizes the channel mutual information. Since optimizing only one matrix instead of two, the new algorithm not only achieves a lower computational complexity but also avoids the use of initial values, which must be carefully selected for each channel and signal-to-noise ratio for fast convergence. Another advantage of the new algorithm is that the resulting precoder has a fixed form of received constellation thanks to the fixed constellation-forming matrix. This allows us to optimize the symbol mapping on the received constellation. Simulation results show that the proposed low-complexity precoder achieves error-rate performance that is close to performance of the optimal one when the conventional mapping is used. In addition, the new precoder used with optimized mapping at received constellation shows significant error-rate performance improvement.

In this paper, we focus on a multiple-input multiple-output (MIMO) linear precoder based on the minimum Euclidean distance criterion, the max- dmin precoder. We propose an optimization of this precoder for the case of an association with a non-binary low density parity check code (NB- LDPC). After recalling the well-known max-dmin precoder, we set forth an optimization of the mutual information of initial message, i.e. I(0), through the extrinsic information transfer (EXIT) analysis of the system. We present a new adaptive precoder whose forms are determined in function of an adaptive threshold angle, optimized in terms of the mutual information I(0), and depending on the signal-to-noise ratio at the reception (SNR_R). The performance of the new precoder is brought out through a theoretical study along with a series of numerical simulations.

In this paper, we investigate the concatenation of the multiple input multiple output (MIMO) max-dminlinear precoder with an outer forward error correction (FEC) code at the transmitter. At the receiver side, the turbo equalization is taken into account, which iteratively exchanges the extrinsic information between a minimum mean square error interference canceller (MMSE IC) and a FEC decoder. The analysis done by extrinsic information transfer (EXIT) chart shows that a higher mutual information (MI) at the convergence state of the turbo equalization is observed thanks to the linear precoder. In addition, we exploit this property to propose a new precoder named max-dmin-mod. Numerical simulations are in accordance with the theoretical analysis, which exhibits a significant improvement of the error-rate of the turbo equalization as well as a significant gain of max-dmin-mod compared to original max-dminprecoder.

This paper describes a new blind channel estimation algorithm for Space-Time Block Coded (STBC) systems. The proposed method exploits the statistical independence of sources before space-time encoding. The channel matrix is estimated by minimizing a kurtosis-based cost function after Zero-Forcing equalization. In contrast to subspace or Second-Order Statistics (SOS) approaches, the proposed method is more general since it can be employed for the general class of linear STBCs including Spatial Multiplexing, Orthogonal, quasi-Orthogonal and Non-Orthogonal STBCs. Furthermore, unlike other approaches, the method does not require any modification of the transmitter and, consequently, is well-suited for non-cooperative context. Numerical examples corroborate the performance of the proposed algorithm.

The issue addressed in this paper is the determination of the number of communication signals in a sensor array. Most of the available algorithms rely on the spatial uncorrelation of the additive noise. In practice, this condition is rarely satisfied when the receivers are not sufficiently spaced (MIMO communications for example). In this paper, we propose a new method to detect the number of communication signals based on the fact that the signals are independent and non gaussian and that the background noise is gaussian. By using an Independent Component Analysis in conjunction with Kolomogorov-Smirnov (K-S) tests, the method can detect as many communication signals as the number of receiver antennas. Simulations results show that our method performs well in many environments like those with spatially correlated noise.

The blind recognition of communication parameters is a key research issue for commercial and military communication systems. In this paper, we investigate the problem of the blind recognition of linear space-time block codes (STBC). To characterize the space time coding, we propose to compute a time-lag correlation of the received samples. Provided the number of transmitters, the noise variance and the symbol timing are well estimated, we show that the theoretical values of the correlation norm only depend on the STBC and are affected by neither the channel nor the symbol modulation. The automatic recognition of the STBC is realized by selecting the STBC which minimizes the distance between the theoretical values and the experimental ones. Simulations show that our method performs well even for low signal to noise ratio (0 dB).

The blind recognition of communication parameters is a key research issue for commercial and military communication systems. The results of numerous investigations about symbol timing estimation, modulation recognition as well as identification of the number of transmitters have been reported in the literature. But, to our knowledge, none of them have dealt with the recognition of the Space-Time Block Codes (STBC) used in multiple transmitter communications. In order to blindly recognize the STBC of a wireless communication, this paper proposes a method based on the space-time correlations of the received signals. Under perfect timing synchronization and under ideal conditions (full rank channel and a number of receivers greater or equal to the number of transmitters), it shows that the Frobenius norms of these statistics present non-null values whose positions only depend on the STBC at the transmitter side. A classifier for the space-time code recognition of 5 linear STBC (Spatial Multiplexing, Alamouti Coding, and 3 Orthogonal STBC using 3 antennas) is presented. Simulations show that the proposed method performs well even at low signal-to-noise ratios.

Previous papers have shown that multipath wireless channels are capable of enormous capacities, provided that the multipath scattering is sufficiently rich and is properly exploited. A layered space-time architecture, known as BLAST, has been proposed. A basic hypothesis made by the BLAST algorithm is that the symbol period is large compared to the maximum echo delay (hence, the data rate cannot be too high). In this paper, we use an approach that combines BLAST and OFDM. Its interest is to suppress the data rate constraint. First, the symbols are packed into matrices; then matrix manipulations prior to BLAST transmission provide a transmission system which is theoretically equivalent to many independent BLAST channels. Results obtained with the UHF COST 207 channel corresponding to GSM transmission in an urban area are provided and discussed.